Sample Sets

PGS Sample Set ID
(PSS)
Phenotype Definitions and Methods Sample Numbers Sample Ancestry Additional Ancestry Description Cohort(s) Additional Sample/Cohort Information
PSS000001 All breast cancer
[
  • 33,673 cases
  • , 33,381 controls
]
European 33 cohorts
  • ABCFS
  • ,ABCS
  • ,BBCC
  • ,BIGGS
  • ,BSUCH
  • ,CECILE
  • ,CGPS
  • ,CTS
  • ,DEMOKRITOS
  • ,ESTHER
  • ,GENICA
  • ,HMBCS
  • ,KBCP
  • ,LMBC
  • ,MARIE
  • ,MCBCS
  • ,MCCS
  • ,MEC
  • ,MTLGEBCS
  • ,NBHS
  • ,NorBCS
  • ,OBCS
  • ,ORIGO
  • ,OSU
  • ,PBCS
  • ,RPCI
  • ,SASBAC
  • ,SBCS
  • ,SEARCH
  • ,SKKDKFZS
  • ,SZBCS
  • ,UKBGS
  • ,pKARMA
iCOGS
PSS000002 ER-negative breast cancer
[
  • 5,738 cases
  • , 32,984 controls
]
European 33 cohorts
  • ABCFS
  • ,ABCS
  • ,BBCC
  • ,BIGGS
  • ,BSUCH
  • ,CECILE
  • ,CGPS
  • ,CTS
  • ,DEMOKRITOS
  • ,ESTHER
  • ,GENICA
  • ,HMBCS
  • ,KBCP
  • ,LMBC
  • ,MARIE
  • ,MCBCS
  • ,MCCS
  • ,MEC
  • ,MTLGEBCS
  • ,NBHS
  • ,NorBCS
  • ,OBCS
  • ,ORIGO
  • ,OSU
  • ,PBCS
  • ,RPCI
  • ,SASBAC
  • ,SBCS
  • ,SEARCH
  • ,SKKDKFZS
  • ,SZBCS
  • ,UKBGS
  • ,pKARMA
iCOGS
PSS000003 ER-positive breast cancer
[
  • 21,365 cases
  • , 32,558 controls
]
European 33 cohorts
  • ABCFS
  • ,ABCS
  • ,BBCC
  • ,BIGGS
  • ,BSUCH
  • ,CECILE
  • ,CGPS
  • ,CTS
  • ,DEMOKRITOS
  • ,ESTHER
  • ,GENICA
  • ,HMBCS
  • ,KBCP
  • ,LMBC
  • ,MARIE
  • ,MCBCS
  • ,MCCS
  • ,MEC
  • ,MTLGEBCS
  • ,NBHS
  • ,NorBCS
  • ,OBCS
  • ,ORIGO
  • ,OSU
  • ,PBCS
  • ,RPCI
  • ,SASBAC
  • ,SBCS
  • ,SEARCH
  • ,SKKDKFZS
  • ,SZBCS
  • ,UKBGS
  • ,pKARMA
iCOGS
PSS000004 Invasive breast cancer-affected
[
  • 11,428 cases
  • , 18,323 controls
]
,
0.0 % Male samples
European 10 cohorts
  • AHS
  • ,BGS
  • ,EPIC
  • ,FHRISK
  • ,KARMA
  • ,NHS
  • ,NHS2
  • ,PLCO
  • ,PROCAS
  • ,SISTER
Prospective Test Set
PSS000005 ER-positive breast cancer cases
[
  • 7,992 cases
  • , 3,436 controls
]
,
0.0 % Male samples
European 10 cohorts
  • AHS
  • ,BGS
  • ,EPIC
  • ,FHRISK
  • ,KARMA
  • ,NHS
  • ,NHS2
  • ,PLCO
  • ,PROCAS
  • ,SISTER
Prospective Test Set
PSS000006 ER-negative breast cancer cases
[
  • 1,259 cases
  • , 10,169 controls
]
,
0.0 % Male samples
European 10 cohorts
  • AHS
  • ,BGS
  • ,EPIC
  • ,FHRISK
  • ,KARMA
  • ,NHS
  • ,NHS2
  • ,PLCO
  • ,PROCAS
  • ,SISTER
Prospective Test Set
PSS000007 Incident registry-confirmed invasive breast cancers developed
[
  • 3,215 cases
  • , 186,825 controls
]
,
0.0 % Male samples
European UKB Prospective Test Set (UKB)
PSS000008 Coronary heart disease represented a composite of fatal or non-fatal myocardial infarction, coronary artery bypass grafting, or percutaneous coronary intervention
[
  • 108 cases
  • , 8,641 controls
]
,
67.8 % Male samples
European JUPITER Primary prevention cohorts
PSS000008 Coronary heart disease represented a composite of fatal or non-fatal myocardial infarction, coronary artery bypass grafting, or percutaneous coronary intervention 27,271 individuals,
38.7 % Male samples
European
(Swedish)
MDC Primary prevention cohorts
PSS000008 Coronary heart disease represented a composite of fatal or non-fatal myocardial infarction, coronary artery bypass grafting, or percutaneous coronary intervention
[
  • 149 cases
  • , 6,829 controls
]
,
79.7 % Male samples
European ASCOT Primary prevention cohorts
PSS000009 Coronary heart disease represented a composite of fatal or non-fatal myocardial infarction, coronary artery bypass grafting, or percutaneous coronary intervention
[
  • 229 cases
  • , 1,770 controls
]
,
77.5 % Male samples
European PROVEIT Secondary prevention cohorts
PSS000009 Coronary heart disease represented a composite of fatal or non-fatal myocardial infarction, coronary artery bypass grafting, or percutaneous coronary intervention
[
  • 320 cases
  • , 2,558 controls
]
,
86.1 % Male samples
European CARE_b Secondary prevention cohorts
PSS000010 Incident CHD was defined as coronary revascularization, fatal or nonfatal myocardial infarction, or death due to ischemic heart disease.
[
  • 2,213 cases
  • , 21,382 controls
]
,
38.03 % Male samples
European
(Swedish)
MDC Prospective study
PSS000011 The main outcome of interest was incident CHD event before age 75y. We used the definition of CHD as employed by the Framingham study, namely, one of • MI recognized, with diagnostic ECG (FHS event code #1) • MI recognized, without diagnostic ECG, with enzymes and history (#2) • MI recognized, without diagnostic ECG, with autopsy evidence (new event) (#3) • MI unrecognized, silent (#4) • MI unrecognized, not silent (#5) • Angina pectoris (AP), first episode only (#6) • Coronary insufficiency (CI), definite by both history and ECG (#7) • Questionable MI at exam 1 (#8) • Acute MI by autopsy, previously coded as 1 or 2 (#9) • Death, CHD sudden, with 1 hour (#21) • Death, CHD 1–23 hours, non sudden (#22) • Death, CHD 24-47 hours, non sudden (#23) • Death, CHD, 48 hours or more, non sudden (#24)
[
  • 587 cases
  • , 2,819 controls
]
,
45.0 % Male samples
European FHS FHS Original, FHS Offspring
PSS000012 Coronary heart disease (CHD) was defined as falling into any of the following categories: • I21 or I22 (ICD-10) / 410 (ICD-8/9) as the direct or as a contributing cause of death or I20-I25 (ICD-10) /410-414 (ICD-9) as the underlying cause of death • I21 or I22 (ICD-10) / 410 (ICD-8/9) as the main or secondary diagnosis at hospital discharge. • Coronary bypass surgery or coronary angioplasty at hospital discharge or identified from the Finnish registry of invasive cardiac procedures.
[
  • 757 cases
  • , 11,919 controls
]
,
46.0 % Male samples
European
(Finnish)
FINRISK FR92, FR97, FR02
PSS000013 Atrial fibrillation ascertainment was based on self-report of atrial fibrillation, atrial flutter, or cardioversion in an interview with a trained nurse, an ICD-9 code of 427.3 or ICD-10 code of I48.X in hospitalization records, or a history of a percutaneous ablation or cardioversion based on the OPCS-4 coded procedure (K57.1, K62.1, K62.2, K62.3, or K 62.4), as performed previously
[
  • 4,576 cases
  • , 284,402 controls
]
European UKB UKB Phase 2
PSS000014 Breast cancer ascertainment was based on self-report in an interview with a trained nurse, ICD-9 codes (174 or 174.9) or ICD-10 codes (C50.X) in hospitalization records, or a breast cancer diagnosis reported to the national registry before the date of enrollment.
[
  • 6,586 cases
  • , 151,309 controls
]
,
0.0 % Male samples
European UKB UKB Phase 2
PSS000015 CAD ascertainment was based on a composite of myocardial infarction or coronary revascularization. Myocardial infarction was based on self-report or hospital admission diagnosis, as performed centrally. This included individuals with ICD-9 codes of 410.X, 411.0, 412.X, or 429.79, or ICD-10 codes of I21.X, I22.X, I23.X, I24.1, or I25.2 in hospitalization records. Coronary revascularization was assessed based on an OPCS-4 coded procedure for coronary artery bypass grafting (K40.1–40.4, K41.1–41.4, or K45.1–45.5), or coronary angioplasty with or without stenting (K49.1–49.2, K49.8–49.9, K50.2, K75.1–75.4, or K75.8–75.9).
[
  • 8,676 cases
  • , 280,302 controls
]
European UKB UKB Phase 2
PSS000016 Inflammatory bowel disease ascertainment was based on report in an interview with a trained nurse, or an ICD-9 code of 555.X or ICD-10 code of K51.X in hospitalization records.
[
  • 5,853 cases
  • , 283,125 controls
]
European UKB UKB Phase 2
PSS000017 Type 2 diabetes ascertainment was based on self-report in an interview with a trained nurse or an ICD-10 code of E11.X in hospitalization records.
[
  • 5,853 cases
  • , 283,125 controls
]
European UKB UKB Phase 2
PSS000018 CAD was defined as fatal or nonfatal myocardial infarction (MI) cases, percutaneous transluminal coronary angioplasty (PTCA), or coronary artery bypass grafting (CABG). Prevalent versus incident status was relative to the UKB enrollment assessment. In UKB self-reported data, cases were defined as having had a heart attack diagnosed by a doctor (data field #6150); “non-cancer illnesses that self-reported as heart attack” (data field #20002); or self-reported operation including PTCA, CABG, or triple heart bypass (data field #20004). In HES hospital episodes data and death registry data, MI was defined as hospital admission or cause of death due to ICD-9 410 to 412, or ICD-10 I21 to I24 or I25.2; CABG and PTCA were defined as hospital admission OPCS-4 K40 to K46, K49, K50.1,or K75.
[
  • 22,242 cases
  • , 460,387 controls
]
,
45.6 % Male samples
European, NR ~95% European ancestry samples, <5% non-European ancestry UKB
PSS000019 Prevalent Coronary artery disease (CAD), where CAD is defined as previous diagnosis of myocardial infarction or revascularization procedures (percutaneous coronary intervention or coronary artery bypass grafting).
[
  • 173 cases
  • , 5,589 controls
]
,
41.29 % Male samples
European
(French Canadian)
CARTaGENE
PSS000020 Recurrent CAD event during the follow- up period (median follow-up time =3.9 years [range =1.1–7), where CAD is defined as previous diagnosis of myocardial infarction or revascularization procedures (percutaneous coronary intervention or coronary artery bypass grafting).
[
  • 446 cases
  • , 416 controls
]
European
(French Canadian)
MHI Phase 1
PSS000020 Recurrent CAD event during the follow- up period (median follow-up time =3.9 years [range =1.1–7), where CAD is defined as previous diagnosis of myocardial infarction or revascularization procedures (percutaneous coronary intervention or coronary artery bypass grafting).
[
  • 937 cases
  • , 1,396 controls
]
European
(French Canadian)
MHI Phase 2
PSS000021 Prevalent Coronary artery disease (CAD), where CAD is defined as previous diagnosis of myocardial infarction or revascularization procedures (percutaneous coronary intervention or coronary artery bypass grafting).
[
  • 974 cases
  • , 976 controls
]
,
72.7 % Male samples
European
(French Canadian)
MHI Phase 1
PSS000022 Prevalent Coronary artery disease (CAD), where CAD is defined as previous diagnosis of myocardial infarction or revascularization procedures (percutaneous coronary intervention or coronary artery bypass grafting).
[
  • 2,492 cases
  • , 817 controls
]
,
72.38 % Male samples
European
(French Canadian)
MHI Phase 2
PSS000023 CAD case endpoints were defined as: angina, myocardial infarction, coronary angioplasty, and coronary bypass surgery. Participants are described as Caucasian with diagnosed Familial hypercholesterolemia(FH; Dutch Lipid Criteria score >= 3 [possible, probable, or definite FH]) and carriers of classical French Canadian mutations in the LDLR gene including del .15 kb of the promoter and exon 1, del .5 kb of exons 2 and 3, W66G (exon 3), E207K (exon 4), Y468X (exon 10), and C646Y (exon 14).
[
  • 206 cases
  • , 519 controls
]
,
42.8 % Male samples
European CNMA Nutrition, Metabolism and Atherosclerosis Clinic (CNMA) of Institut de recherches cliniques de Montréal
PSS000024 Cerebrovascular disease (CVD) case endpoints were defined as: transient ischemic attack, stroke, and carotid endarterectomy. Participants are described as Caucasian with diagnosed Familial hypercholesterolemia(FH; Dutch Lipid Criteria score >= 3 [possible, probable, or definite FH]) and carriers of classical French Canadian mutations in the LDLR gene including del .15 kb of the promoter and exon 1, del .5 kb of exons 2 and 3, W66G (exon 3), E207K (exon 4), Y468X (exon 10), and C646Y (exon 14).
[
  • 231 cases
  • , 494 controls
]
,
42.8 % Male samples
European CNMA Nutrition, Metabolism and Atherosclerosis Clinic (CNMA) of Institut de recherches cliniques de Montréal
PSS000025 Incident cases of Type 2 Diabetes in 5.63 years follow-up
[
  • 302 cases
  • , 5,978 controls
]
,
55.0 % Male samples
European
(Estonian)
EB
PSS000026 Cases were defined on the presence or absence of severe insulin deficiency (requiring insulin treatment at 3 years after diagnosis). We cate- gorized people as severely insulin defi- cient if they received continuous insulin treatment at ,3 years from the time of diagnosis and had a low measured C-peptide level (nonfasting measured ,0.6 nmol/L or equivalent fasting blood glucose level or posthome meal urine C-peptide–to–creatinine ratio)
[
  • 46 cases
  • , 177 controls
]
,
46.3 % Male samples
European P2ID A cross-sectional cohort of people in whom diabetes was diagnosed between the ages of 20 and 40 years (n = 223), who had had diabetes for .3 years, and who had self-reported as white European from Devon and Cornwall in South West England. Known monogenic diabetes and secondary diabetes pa- tients were excluded.
PSS000027 Type 1 diabetes status was assigned according to clinician diagnosis.
[
  • 84 cases
  • , 63 controls
]
,
33.78 % Male samples
African American or Afro-Caribbean UFDI Total sample number contains the number of controls, cases, and includes the number of first/second-degree relatives and samples identified as "at risk" (autoantibody positive) used in other analyses.
PSS000028 Type 1 diabetes status was assigned according to clinician diagnosis.
[
  • 65 cases
  • , 43 controls
]
,
44.84 % Male samples
Hispanic or Latin American Samples labeled Caucasian (Hispanic ethnicity) in the original publication. UFDI Total sample number contains the number of controls, cases, and includes the number of first/second-degree relatives and samples identified as "at risk" (autoantibody positive) used in other analyses.
PSS000029 Type 1 diabetes status was assigned according to clinician diagnosis.
[
  • 478 cases
  • , 290 controls
]
,
47.34 % Male samples
European Samples labeled Caucasian (non-Hispanic) in the original publication. UFDI Total sample number contains the number of controls, cases, and includes the number of first/second-degree relatives and samples identified as "at risk" (autoantibody positive) used in other analyses.
PSS000030
[
  • 1,021 cases
  • , 2,928 controls
]
African unspecified 7 cohorts
  • BDC
  • ,CLEAR
  • ,GoKinD
  • ,NYCP
  • ,SEARCH
  • ,T1DGC
  • ,UAB
PSS000031 Cases are diagnosed with type 1 diabetes.
[
  • 61 cases
  • , 54 controls
]
African unspecified UOF
PSS000032 Type 1 Diabetes Case Definition = Clinical diagnosis of diabetes at less than or equal to 20 years of age; On insulin within 1 year from the time of diagnosis; Still on insulin at the time of recruit- ment; Not using oral antihyperglycemic agents; Did not ever self-report as having type 2 diabetes (T2D)
[
  • 387 cases
  • , 373,613 controls
]
European UKB
PSS000033 Most of the studies used standard screening procedures based on history, medical review, screening questions, and cognitive assessments that flagged participants with potential cognitive impairment. These participants underwent complete neurological and neuropsychological evaluation. An initial decision was made regarding the presence or absence of dementia, using the DSM-IV criteria; a diagnosis of possible, probable, or definite AD was made as a second step using NINCDS-ADRDA (National Institute of Neurological Disorders and Stroke Alzheimer’s Disease and Related Disorders Association) criteria.
[
  • 2,782 cases
]
European 8 cohorts
  • 3C
  • ,ACT
  • ,AGES
  • ,CHS
  • ,FHS
  • ,ROSMAP
  • ,RS
  • ,WHICAP
As one SNP (rs9271192) was missing in FHS, WHICAP, and Rotterdam because of poor imputation quality, an 18 SNP-based GRS was computed in these cohorts. As the samples used in this project were partially overlapping with the ones used in the original IGAP study, we ran an additional IGAP meta-analysis after excluding those and did not find significant changes in the estimations of HRs for the SNPs considered
PSS000034 Most of the studies used standard screening procedures based on history, medical review, screening questions, and cognitive assessments that flagged participants with potential cognitive impairment. These participants underwent complete neurological and neuropsychological evaluation. An initial decision was made regarding the presence or absence of dementia, using the DSM-IV criteria; a diagnosis of possible, probable, or definite AD was made as a second step using NINCDS-ADRDA (National Institute of Neurological Disorders and Stroke Alzheimer’s Disease and Related Disorders Association) criteria. 4,353 individuals European 8 cohorts
  • 3C
  • ,ACT
  • ,AGES
  • ,CHS
  • ,FHS
  • ,ROSMAP
  • ,RS
  • ,WHICAP
As one SNP (rs9271192) was missing in FHS, WHICAP, and Rotterdam because of poor imputation quality, an 18 SNP-based GRS was computed in these cohorts. As the samples used in this project were partially overlapping with the ones used in the original IGAP study, we ran an additional IGAP meta-analysis after excluding those and did not find significant changes in the estimations of HRs for the SNPs considered
PSS000035 Most of the studies used standard screening procedures based on history, medical review, screening questions, and cognitive assessments that flagged participants with potential cognitive impairment. These participants underwent complete neurological and neuropsychological evaluation. An initial decision was made regarding the presence or absence of dementia, using the DSM-IV criteria; a diagnosis of possible, probable, or definite AD was made as a second step using NINCDS-ADRDA (National Institute of Neurological Disorders and Stroke Alzheimer’s Disease and Related Disorders Association) criteria. 15,334 individuals European 8 cohorts
  • 3C
  • ,ACT
  • ,AGES
  • ,CHS
  • ,FHS
  • ,ROSMAP
  • ,RS
  • ,WHICAP
As one SNP (rs9271192) was missing in FHS, WHICAP, and Rotterdam because of poor imputation quality, an 18 SNP-based GRS was computed in these cohorts. As the samples used in this project were partially overlapping with the ones used in the original IGAP study, we ran an additional IGAP meta-analysis after excluding those and did not find significant changes in the estimations of HRs for the SNPs considered
PSS000036 Cases are patients with clinically diagnosed AD and compared to cognitively normal older individuals
[
  • 6,984 cases
  • , 10,972 controls
]
,
40.51 % Male samples
European ADGC ADGC Phase 2
PSS000037 288,016 individuals,
45.0 % Male samples
European UKB
PSS000038 Cases were ascertained by linkage to the California Cancer Registry and defined as pathologically-confirmed diagnoses of invasive breast cancers with positive/elevated ER expression on immunohistochemical staining. ER-negative cases and those with unavailable ER status were excluded. Excluded women self-identified as premenopausal, perimenopausal, or postmenopausal as a direct result of surgery or medical treatments, such as chemotherapy. Women on hormonal therapy or selective estrogen receptor modulators at the time of blood draw were also excluded.
[
  • 51 cases
  • , 51 controls
]
,
0.0 % Male samples
East Asian CPMCBHC Nested case-control study from the CPMC Breast Health Cohort.
PSS000039 Cases were ascertained by linkage to the California Cancer Registry and defined as pathologically-confirmed diagnoses of invasive breast cancers with positive/elevated ER expression on immunohistochemical staining. ER-negative cases and those with unavailable ER status were excluded. Excluded women self-identified as premenopausal, perimenopausal, or postmenopausal as a direct result of surgery or medical treatments, such as chemotherapy. Women on hormonal therapy or selective estrogen receptor modulators at the time of blood draw were also excluded.
[
  • 387 cases
  • , 387 controls
]
,
0.0 % Male samples
European CPMCBHC Nested case-control study from the CPMC Breast Health Cohort.
PSS000040 Cases were ascertained by linkage to the California Cancer Registry and defined as pathologically-confirmed diagnoses of invasive breast cancers with positive/elevated ER expression on immunohistochemical staining. ER-negative cases and those with unavailable ER status were excluded. Excluded women self-identified as premenopausal, perimenopausal, or postmenopausal as a direct result of surgery or medical treatments, such as chemotherapy. Women on hormonal therapy or selective estrogen receptor modulators at the time of blood draw were also excluded.
[
  • 495 cases
  • , 486 controls
]
,
0.0 % Male samples
East Asian, European, Hispanic or Latin American CPMCBHC Nested case-control study from the CPMC Breast Health Cohort.
PSS000041 For each cohort core data on disease status, age at diagnosis (age at observation or questionnaire for controls), family history of PrCa, and clinical factors for cases (for example, PSA at diagnosis and Gleason score) was extracted
[
  • 46,939 cases
  • , 27,910 controls
]
,
100.0 % Male samples
European 42 cohorts
  • APCB
  • ,CONOR
  • ,COSM
  • ,CPCS
  • ,CPS
  • ,EPIC
  • ,ERSPC
  • ,FHCRC
  • ,Gene-PARE
  • ,HPFS
  • ,HZ
  • ,IMPACT
  • ,IPO-Porto
  • ,LAAPC
  • ,MCC-Spain
  • ,MCCS
  • ,MDACCS
  • ,MEC
  • ,MOFFITT_PC
  • ,PCMUS
  • ,PCPT
  • ,PHS
  • ,PLCO
  • ,PRAGGA
  • ,PROCAP
  • ,PROFILE
  • ,PROGReSS_PrCa
  • ,Poland
  • ,ProMPT
  • ,ProtecT
  • ,QLD
  • ,RAPPER
  • ,SAAR
  • ,SEARCH
  • ,SFPCS
  • ,SNP_Prostate_Ghent
  • ,SPAG
  • ,STHM
  • ,SWOG-SELECT
  • ,TAMPERE
  • ,TOR
  • ,UKGPCS
These samples (OncoArray) were also used in the GWAS meta-analysis
PSS000042 T2D was defined by a fasting plasma glucose ≥7.0 mmol/L (≥126 mg/dL) or report of taking diabetes medications
[
  • 118 cases
  • , 702 controls
]
,
38.8 % Male samples
African American or Afro-Caribbean CARDIA
PSS000043 T2D was defined by a fasting plasma glucose ≥7.0 mmol/L (≥126 mg/dL) or report of taking diabetes medications
[
  • 97 cases
  • , 1,553 controls
]
,
46.5 % Male samples
European CARDIA
PSS000044 T2D was defined by a fasting plasma glucose ≥7.0 mmol/L (≥126 mg/dL) or report of taking diabetes medications
[
  • 446 cases
  • , 3,025 controls
]
,
46.6 % Male samples
European FOS
PSS000045 BMI difference between ages 21 and 45 1,699 individuals,
100.0 % Male samples
European HPFS
PSS000046 BMI difference between ages 45 and 65 1,634 individuals,
100.0 % Male samples
European HPFS
PSS000047 BMI difference between ages 65 and 80 2,020 individuals,
100.0 % Male samples
European HPFS
PSS000048 BMI difference between ages 18 and 45 5,956 individuals,
0.0 % Male samples
European NHS
PSS000049 BMI difference between age 18 and Menopause 6,705 individuals,
0.0 % Male samples
European NHS
PSS000050 BMI difference between ages 45 and 65 5,640 individuals,
0.0 % Male samples
European NHS
PSS000051 BMI difference between ages 65 and 80 2,942 individuals,
0.0 % Male samples
European NHS
PSS000052 BMI difference between Menopause and age 65 6,436 individuals,
0.0 % Male samples
European NHS
PSS000053 Participants were classified as having AF if an arrhythmia was present on an ECG obtained at a study visit or encounter with external clinicians, Holter monitoring, or noted in hospital records during a median 9.4 years of follow-up.
[
  • 580 cases
  • , 4,026 controls
]
,
45.9 % Male samples
European, NR FHS is principally composed of individuals of European ancestry FHS Samples were obtained from the following FHS cohorts: Original, Offspring, and Third Generation. Participants were eligible for inclusion if they were AF free at an average age of 55.
PSS000054 Prevalent T2D status was defined using self-reported medical history and medication
[
  • 13,480 cases
  • , 311,390 controls
]
European UKB
PSS000055 Current asthma status was assessed at ages 9, 11, 13, 15, 18, 21, 26, 32, and 38 years from standardised interviews of study members (or their mothers if the participant was younger than 13 years) done by pulmonary specialists. Current asthma was defined as a diagnosis of asthma in addition to positive symptoms within the past 12 months, including asthma attack, recurrent wheeze (excluding study members reporting only one or two episodes lasting less than 1 h), or medical treatment for asthma. Age at asthma onset was defined as the earliest age at which wheezing symptoms or diagnosis by a physician were recorded.
[
  • 305 cases
  • , 575 controls
]
,
51.0 % Male samples
European DMHDS
PSS000056 Current asthma status was assessed at ages 9, 11, 13, 15, 18, 21, 26, 32, and 38 years from standardised interviews of study members (or their mothers if the participant was younger than 13 years) done by pulmonary specialists. Current asthma was defined as a diagnosis of asthma in addition to positive symptoms within the past 12 months, including asthma attack, recurrent wheeze (excluding study members reporting only one or two episodes lasting less than 1 h), or medical treatment for asthma. Age at asthma onset was defined as the earliest age at which wheezing symptoms or diagnosis by a physician were recorded. 187 individuals European DMHDS Subset of children from DMHDS with asthma onset in childhood (before age 13 years)
PSS000057 Incident stroke in was defined based on the UK Biobank (UKB) algorithm, based on medical history and linkage to data on hospital admissions and mortality. The authors also subtyped ischaemic stroke, intracerebral haemorrhage, or subarachnoid haemorrhage. UKB Participants with genetic data were excluded from the analysis based on the following criteria: failing genetic quality control (missingness > 5%, sex mismatch, excessive heterozygosity), having a history of stroke or myocardial infarction (MI), self-report of stroke or MI, missing lifestyle information.
[
  • 2,077 cases
  • , 304,396 controls
]
,
44.59 % Male samples
European Unrelated White British subset of UKB participants UKB
PSS000058 Prevalent and incident Ischaemic stroke; defined in http://biobank.ndph.ox.ac.uk/showcase/docs/alg_outcome_stroke.pdf
[
  • 3,075 cases
  • , 392,318 controls
]
,
45.7 % Male samples
European UKB Validation set
PSS000059
[
  • 647 cases
  • , 1,829 controls
]
European
(Finnish)
FINRISK, Health2000
PSS000060
[
  • 5,907 cases
  • , 4,397 controls
]
European
(British)
NR Immunochip
PSS000061
[
  • 497 cases
  • , 543 controls
]
European
(Italian)
NR
PSS000062
[
  • 803 cases
  • , 846 controls
]
European
(Dutch)
NR
PSS000063
[
  • 778 cases
  • , 1,422 controls
]
European
(British)
NR
PSS000064
[
  • 1,259 cases
  • , 437 controls
]
European NIDDK
PSS000065 The HLA-DQ2.5-positive subset of NIDDK-CIDR
[
  • 1,094 cases
  • , 143 controls
]
European NIDDK HLA alleles were imputed using SNP2HLA
PSS000066 VTE was defined in the MVP cohort using the following diagnosis codes for: - Deep Venous Thrombosis ICD-10 codes: {I80.1, I80.2, I82.22, I82.4, I82.5} and ICD-9 codes: {451.11, 451.19, 453.2, 453.4} - Pulmonary Embolism ICD-10 codes: {I26.0, I26.9} and ICD-9 code {415.1}
[
  • 2,100 cases
  • , 53,865 controls
]
European MVP MVP Cohort = 3.0
PSS000067
[
  • 690 cases
  • , 10,285 controls
]
,
0.0 % Male samples
European WHI, WHI-GARNET, WHI-HT, WHI-LLS, WHI-MS
PSS000068 Prostate cancer was classified as localized disease with tumor-node-metastasis stage T2 and below and advanced disease (regional-distant) was classified as localized disease with tumor-node-metastasis stage T3 and above (low aggressive tumor, Gleason score <7; intermediate to highly aggressive tumor, Gleason score ≥7). Elevated serum prostate-specific antigen (PSA) levels were defined as ≥4 ng/ml.
[
  • 3,157 cases
  • , 0 controls
]
,
100.0 % Male samples
European UKGPCS
PSS000068 Prostate cancer was classified as localized disease with tumor-node-metastasis stage T2 and below and advanced disease (regional-distant) was classified as localized disease with tumor-node-metastasis stage T3 and above (low aggressive tumor, Gleason score <7; intermediate to highly aggressive tumor, Gleason score ≥7). Elevated serum prostate-specific antigen (PSA) levels were defined as ≥4 ng/ml.
[
  • 2,148 cases
  • , 6,648 controls
]
,
100.0 % Male samples
European ProtecT
PSS000068 Prostate cancer was classified as localized disease with tumor-node-metastasis stage T2 and below and advanced disease (regional-distant) was classified as localized disease with tumor-node-metastasis stage T3 and above (low aggressive tumor, Gleason score <7; intermediate to highly aggressive tumor, Gleason score ≥7). Elevated serum prostate-specific antigen (PSA) levels were defined as ≥4 ng/ml.
[
  • 4,099 cases
  • , 960 controls
]
,
100.0 % Male samples
European SEARCH
PSS000069 Prostate cancer was classified as localised disease with tumour-node-metastasis (TNM) stage T1-2 N0 M0; and advanced disease (regional-distant) with stage T3 and above or any T N1 M1; as non-aggressive tumour, Gleason score <7, and aggressive tumour, Gleason score ⩾7.
[
  • 1,089 cases
  • , 3,878 controls
]
,
100.0 % Male samples
European
(Finnish)
ERSPC
PSS000070 BRCA1 mutation carriers were followed until breast or ovarian cancer diagnosis, bilateral prophylactic mastectomy, or age at last observation whichever occurred first.
[
  • 7,797 cases
  • , 7,455 controls
]
,
0.0 % Male samples
European Some analyses accounted for samples part of the larger cohort with Ashkenazi Jewish ancestry CIMBA Median censoring age (cases) = 40
PSS000071 BRCA2 mutation carriers were followed until breast or ovarian cancer diagnosis, bilateral prophylactic mastectomy, or age at last observation whichever occurred first.
[
  • 4,330 cases
  • , 3,881 controls
]
,
0.0 % Male samples
European Some analyses accounted for samples part of the larger cohort with Ashkenazi Jewish ancestry CIMBA Median censoring age (cases) = 43
PSS000072 BRCA1 mutation carriers were followed until the age of ovarian cancer diagnosis, age at risk-reducing salpingo-oophorectomy (RRSO) or age at last observation. Breast cancer diagnosis was not considered as a censoring event in the ovarian cancer analysis
[
  • 2,462 cases
  • , 12,790 controls
]
,
0.0 % Male samples
European Some analyses accounted for samples part of the larger cohort with Ashkenazi Jewish ancestry CIMBA Median censoring age (cases) = 50
PSS000073 BRCA2 mutation carriers were followed until the age of ovarian cancer diagnosis, age at risk-reducing salpingo-oophorectomy (RRSO) or age at last observation. Breast cancer diagnosis was not considered as a censoring event in the ovarian cancer analysis
[
  • 631 cases
  • , 7,580 controls
]
,
0.0 % Male samples
European Some analyses accounted for samples part of the larger cohort with Ashkenazi Jewish ancestry CIMBA Median censoring age (cases) = 57
PSS000074 Breast and prostate cancer cases were defined on the basis of age at diagnosis, whichever occurred first. If breast and prostate cancer occurred at the same time, individuals were treated as patients with breast cancer.
[
  • 277 cases
  • , 1,313 controls
]
,
100.0 % Male samples
European Self-reported European ancestry 37 cohorts
  • BCFR
  • ,BFBOCC
  • ,BRICOH
  • ,CBCS
  • ,CIMBA
  • ,CNIO
  • ,CONSIT
  • ,Chicago
  • ,DEMOKRITOS
  • ,DKFZ
  • ,EMBRACE
  • ,FCCC
  • ,G-FaST
  • ,GC-HBOC
  • ,GEMO
  • ,HCSC
  • ,HEBCS
  • ,HEBON
  • ,HUNBOCS
  • ,HVH
  • ,ICO
  • ,ILUH
  • ,IOVHBOCS
  • ,IPOBCS
  • ,MAYO
  • ,MSKCC
  • ,MUV
  • ,NCI
  • ,OCGN
  • ,OSU
  • ,OUH
  • ,PBCS
  • ,SWE-BRCA
  • ,UPENN
  • ,UPITT
  • ,VFCTG
  • ,kConFab
PSS000075 Breast and prostate cancer cases were defined on the basis of age at diagnosis, whichever occurred first. If breast and prostate cancer occurred at the same time, individuals were treated as patients with breast cancer.
[
  • 212 cases
  • , 1,313 controls
]
,
100.0 % Male samples
European Self-reported European ancestry 37 cohorts
  • BCFR
  • ,BFBOCC
  • ,BRICOH
  • ,CBCS
  • ,CIMBA
  • ,CNIO
  • ,CONSIT
  • ,Chicago
  • ,DEMOKRITOS
  • ,DKFZ
  • ,EMBRACE
  • ,FCCC
  • ,G-FaST
  • ,GC-HBOC
  • ,GEMO
  • ,HCSC
  • ,HEBCS
  • ,HEBON
  • ,HUNBOCS
  • ,HVH
  • ,ICO
  • ,ILUH
  • ,IOVHBOCS
  • ,IPOBCS
  • ,MAYO
  • ,MSKCC
  • ,MUV
  • ,NCI
  • ,OCGN
  • ,OSU
  • ,OUH
  • ,PBCS
  • ,SWE-BRCA
  • ,UPENN
  • ,UPITT
  • ,VFCTG
  • ,kConFab
PSS000076
[
  • 2,012 cases
  • , 1,313 controls
]
,
100.0 % Male samples
European Self-reported European ancestry 37 cohorts
  • BCFR
  • ,BFBOCC
  • ,BRICOH
  • ,CBCS
  • ,CIMBA
  • ,CNIO
  • ,CONSIT
  • ,Chicago
  • ,DEMOKRITOS
  • ,DKFZ
  • ,EMBRACE
  • ,FCCC
  • ,G-FaST
  • ,GC-HBOC
  • ,GEMO
  • ,HCSC
  • ,HEBCS
  • ,HEBON
  • ,HUNBOCS
  • ,HVH
  • ,ICO
  • ,ILUH
  • ,IOVHBOCS
  • ,IPOBCS
  • ,MAYO
  • ,MSKCC
  • ,MUV
  • ,NCI
  • ,OCGN
  • ,OSU
  • ,OUH
  • ,PBCS
  • ,SWE-BRCA
  • ,UPENN
  • ,UPITT
  • ,VFCTG
  • ,kConFab
PSS000077
[
  • 53 cases
  • , 1,313 controls
]
,
100.0 % Male samples
European Self-reported European ancestry 37 cohorts
  • BCFR
  • ,BFBOCC
  • ,BRICOH
  • ,CBCS
  • ,CIMBA
  • ,CNIO
  • ,CONSIT
  • ,Chicago
  • ,DEMOKRITOS
  • ,DKFZ
  • ,EMBRACE
  • ,FCCC
  • ,G-FaST
  • ,GC-HBOC
  • ,GEMO
  • ,HCSC
  • ,HEBCS
  • ,HEBON
  • ,HUNBOCS
  • ,HVH
  • ,ICO
  • ,ILUH
  • ,IOVHBOCS
  • ,IPOBCS
  • ,MAYO
  • ,MSKCC
  • ,MUV
  • ,NCI
  • ,OCGN
  • ,OSU
  • ,OUH
  • ,PBCS
  • ,SWE-BRCA
  • ,UPENN
  • ,UPITT
  • ,VFCTG
  • ,kConFab
PSS000078
[
  • 11,905 cases
  • , 11,662 controls
]
,
0.0 % Male samples
East Asian 11 cohorts
  • ACP
  • ,BCAC
  • ,HERPACC
  • ,LAABC
  • ,MYBRCA
  • ,SBCGS
  • ,SEBCS
  • ,SGBCC
  • ,SGWAS
  • ,TBCS
  • ,TWBCS
PSS000079
[
  • 2,867 cases
  • , 2,285 controls
]
,
0.0 % Male samples
East Asian
(Chinese)
SGWAS SGWAS (Stage 1). Smaller set of the larger test set from this study.
PSS000080 Questionnaires were mailed to women biennially to collect information on breast cancer risk factors, including age at menarche, age at first birth, parity, family history of breast cancer, height, weight, physical activity, menopausal status, age at menopause, and HT use. Incident breast cancer cases up to 1 June 2010 were also identified through biennial questionnaires. Diagnoses were confirmed with the participants (or next of kin), and permission was obtained to collect relevant medical or pathology reports. Analysis was restricted to invasive breast cancer.
[
  • 4,006 cases
  • , 7,874 controls
]
,
0.0 % Male samples
European, NR NHS, NHS2 Performance metrics are reported for the "All women" results of Table 2
PSS000081 Questionnaires were mailed to women biennially to collect information on breast cancer risk factors, including age at menarche, age at first birth, parity, family history of breast cancer, height, weight, physical activity, menopausal status, age at menopause, and HT use. Incident breast cancer cases up to 1 June 2010 were also identified through biennial questionnaires. Diagnoses were confirmed with the participants (or next of kin), and permission was obtained to collect relevant medical or pathology reports. Analysis was restricted to invasive breast cancer.
[
  • 2,676 cases
  • , 5,484 controls
]
,
0.0 % Male samples
European, NR NHS, NHS2 Performance metrics are reported for the "All women" results of Table 3
PSS000082 A family-based cohort including 323 breast cancer cases and 262 unaffected relatives from 101 families. Unaffected relatives derived from 49 out of 101 families.
[
  • 323 cases
  • , 262 controls
]
,
0.0 % Male samples
European NR
PSS000083 Cases were clinically diagnosed with T1D before 17 years of age and treated with insulin from diagnosis. Patients with known MODY or NDM were excluded.
[
  • 1,963 cases
  • , 0 controls
]
European WTCCC Cases with Type 1 Diabetes
PSS000083 MODY patients with a confirmed monogenic etiology on genetic testing (415 patients with HNF1A MODY, 346 with GCK MODY, 42 with HNF4A MODY, and 2 with HNF1B MODY). The median age of diagnosis was 20 years (interquartile range 15, 30), and 532 patients were female.
[
  • 805 cases
  • , 0 controls
]
,
33.91 % Male samples
European NR Maturity-onset diabetes of young (MODY) cases ascertained from the Genetic Βeta Cell Research Bank, Exeter, U.K.
PSS000084 EFIGA recruited patients from families multiply affected by LOAD, but of Caribbean Hispanic ancestry from the Dominican Republic and New York. Families were recruited after confirming diagnoses in the probands. Family members with dementia were also interviewed and neurologically evaluated. Clinical diagnoses were made in a consensus diagnostic conference by a panel of neurologists, neuropsychologists, and psychiatrists. Detailed description is available elsewhere.14 For these family-based studies, we included data from families for which their members (1) were 60 years or older at the time of enrollment; (2) had a diagnosis of probable or possible LOAD according to National Institute of Neurological and Communicative Disorders and Stroke–Alzheimer’s Disease and Related Disorders Association (NINDS-ADRDA) criteria; (3) had available pedigree information and covariates.
[
  • 2,155 cases
  • , 1,169 controls
]
,
34.0 % Male samples
Hispanic or Latin American Samples are described as "Carribbean Hispanic" EFIGA
PSS000085 Selection criteria included (1) a proband who received a dianosis of definite or probable late onset Alzheimer's Disease (LOAD) with age at onset of at least 60 years; (2) a full sibling with definite, probable, or possible LOAD with age at onset after 60 years; (3) a related family member (first-,second-,or third-degree relative) of theaffected sibling pair and 60 years or older if unaffected, or 50 years or older if dianosed with LOAD or mild cognitive impairment (MCI)
[
  • 2,128 cases
  • , 2,664 controls
]
,
38.0 % Male samples
European NIA-LOAD
PSS000086
[
  • 8,580 cases
  • , 13,050 controls
]
East Asian 8 cohorts
  • COLON
  • ,CORSA
  • ,DACHS
  • ,EPIC
  • ,HPFS
  • ,MGI
  • ,NHS
  • ,UKB
PSS000087
[
  • 12,952 cases
  • , 48,383 controls
]
European 8 cohorts
  • COLON
  • ,CORSA
  • ,DACHS
  • ,EPIC
  • ,HPFS3
  • ,MGI
  • ,NHS3
  • ,UKB
PSS000088 Parkinson Disease symptom progression was assessed during 1 to 3 follow-up examinations by a movement disorder team (June 1, 2007, to August 31, 2013; mean [SD] time from disease onset, 7.3 [2.8] years) using the following methods: - Cognitive decline was determined with the Mini-Mental State Examination (MMSE; range, 0-30, with lower scores indicating worse cognitive function). Cognitive decline was defined as a 4-point decrease from baseline MMSE score and time to event as the time from the baseline to follow-up examinations in which a 4-point decrease was first measured - Motor decline was defined as a 20-point increase in Unified Parkinson’s Disease Rating Scale part III (UPDRS-III) score, and time to event as the time from the baseline to follow-up examinations in which a 20-point increase was first measured. - Motor decline was also measured by assessing conversion to stage 3 or higher of the Hoehn & Yahr (H&Y) scale. Time to conversion to H&Y stage 3 was defined as the time from the baseline to first follow-up examinations in which the patient scored at least stage 3.
[
  • 285 cases
  • , 0 controls
]
,
56.14 % Male samples
European PEG Patients with idiopathic PD diagnosed less than 3 years previously were recruited from June 1, 2001, through November 31, 2007. Patients were confirmed as having clinically probable or possible Parkinson Disease by a team of movement disorder specialists
PSS000089 Total carotid plaque burden (mm2) 4,392 individuals NR BioImage
PSS000090 Total coronary arterial clacification (CAC) was coded as a a dichotomous outcome variable (CAC>0 versus CAC=0), and quantified by the Agatston method 1,154 individuals NR CARDIA
PSS000091 Nonfatal myocardial infarction or death from CHD 2,440 individuals,
100.0 % Male samples
NR NR Participants were all men hypercholesterolemia but without a history of myocardial infarction, allocated to the placebo group
PSS000092 Incident Major coronary events (MCE) are defined as: fatal or nonfatal coronary artery disease (CAD) events, nonfatal myocardial infarction, or unstable angina
[
  • 675 cases
  • , 4,685 controls
]
,
64.8 % Male samples
European Self reported white ACCORD Type 2 Diabetes patients
PSS000093 Incident Major coronary events (MCE) are defined as: fatal or nonfatal coronary artery disease (CAD) events, nonfatal myocardial infarction, or unstable angina
[
  • 163 cases
  • , 1,768 controls
]
European Self reported white ORIGIN Participants are from the Outcome Reduction With Initial Glargine Intervention (ORIGIN) trial and were enrolled based on having some combination of impaired fasting glucose, impaired glucose tolerance or type 2 diabetes, and high cardiovascular risk
PSS000094 Incident CHD was defined as myocardial infarction (MI), resuscitated cardiac arrest, definite or probable angina if followed by a revascularization and CHD death
[
  • 86 cases
  • , 1,234 controls
]
European Analysis restricted to "White participants" MESA
PSS000095 Incident CHD was defined as myocardial infarction (MI), resuscitated cardiac arrest, definite or probable angina if followed by a revascularization and CHD death
[
  • 144 cases
  • , 1,062 controls
]
European Analysis restricted to "White participants" MESA
PSS000096 Lipid levels are represented in mg/dL, individuals on any lipid-lowering medication (n = 1,018) were omitted from all analyses. 1,355 individuals,
46.2 % Male samples
African American or Afro-Caribbean MESA MESA Classic Cohort
PSS000097 Lipid levels are represented in mg/dL, individuals on any lipid-lowering medication (n = 1,018) were omitted from all analyses. 666 individuals,
50.15 % Male samples
East Asian MESA MESA Classic Cohort
PSS000098 Lipid levels are represented in mg/dL, individuals on any lipid-lowering medication (n = 1,018) were omitted from all analyses. 2,063 individuals,
46.78 % Male samples
European MESA MESA Classic Cohort
PSS000099 Lipid levels are represented in mg/dL, individuals on any lipid-lowering medication (n = 1,018) were omitted from all analyses. 1,256 individuals,
48.89 % Male samples
Hispanic or Latin American MESA MESA Classic Cohort
PSS000100 Serum levels of high-density lipoprotein (HDL), low-density lipoprotein (LDL) cholesterol and triglycerides (TG) 6,407 individuals,
44.0 % Male samples
Sub-Saharan African APCDR APCDR-Uganda study
PSS000101 Serum levels of high-density lipoprotein (HDL), low-density lipoprotein (LDL) cholesterol and triglycerides (TG) 21,295 individuals,
38.0 % Male samples
East Asian
(Chinese)
CKB - 20810 samples had HDL measurements - 17662 samples had LDL measurements - 20222 samples had triglyceride measurements
PSS000102 Serum levels of high-density lipoprotein (HDL), low-density lipoprotein (LDL) cholesterol and triglycerides (TG) 1,641 individuals,
58.0 % Male samples
European
(Greek)
Population isolate from the Pomak villages in the North of Greece HELIC - 1186 samples had HDL measurements - 1186 samples had LDL measurements - 1176 samples had triglyceride measurements
PSS000103 Serum levels of high-density lipoprotein (HDL), low-density lipoprotein (LDL) cholesterol and triglycerides (TG) 1,945 individuals,
66.0 % Male samples
European
(Greek)
Population isolate from the Mylopotamos villages in Crete HELIC - 1078 samples had HDL measurements - 1075 samples had LDL measurements - 1066 samples had triglyceride measurements
PSS000104 Serum levels of high-density lipoprotein (HDL), low-density lipoprotein (LDL) cholesterol and triglycerides (TG) 9,962 individuals,
56.0 % Male samples
European UKHLS - 9706 samples had HDL measurements - 9767 samples had LDL measurements - 9635 samples had triglyceride measurements
PSS000105 Men screened with PSA testing (3.0 ng/L or higher), who received a diagnosis of aggressive prostate cancer (defined as any of Gleason score ≥7, stage T3-T4, PSA concentration ≥10 ng/mL, nodal metastasis, or distant metastasis)
[
  • 628 cases
]
,
100.0 % Male samples
European ProtecT
PSS000105 Men screened with PSA testing, who did not receive a diagnosis of prostate cancer. 4,828 individuals,
100.0 % Male samples
European ProtecT
PSS000106 Men screened with PSA testing (3.0 ng/L or higher), who received a diagnosis of prostate cancer.
[
  • 1,583 cases
]
,
100.0 % Male samples
European ProtecT
PSS000106 Men screened with PSA testing, who did not receive a diagnosis of prostate cancer. 4,828 individuals,
100.0 % Male samples
European ProtecT
PSS000107 Men screened with PSA testing, who did not receive a diagnosis of prostate cancer. 4,828 individuals,
100.0 % Male samples
European ProtecT
PSS000107 Men screened with PSA testing (3.0 ng/L or higher), who received a diagnosis of very aggressive prostate cancer (defined as any of Gleason score ≥8, stage T3-4, positive nodes, or distant metastases)
[
  • 220 cases
]
,
100.0 % Male samples
European ProtecT
PSS000108 Adjudicated endpoint determined from medical notes by an outcome review committee
[
  • 750 cases
  • , 1,428 controls
]
,
0.0 % Male samples
European UKCTOCS
PSS000108 Adjudicated endpoint determined from medical notes by an outcome review committee
[
  • 489 cases
  • , 1,428 controls
]
,
0.0 % Male samples
European UKCTOCS
PSS000109 Participants were followed-up for cancer events mainly through linkage with official death certificates, chronic disease registries, and the Chinese national health insurance system.
[
  • 1,316 cases
  • , 94,092 controls
]
,
42.93 % Male samples
East Asian
(Chinese)
CKB
PSS000110 Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 29010
[
  • 2,248 cases
  • , 410,354 controls
]
,
46.0 % Male samples
European GERA, UKB
PSS000111 Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 26000
[
  • 17,901 cases
  • , 219,648 controls
]
,
0.0 % Male samples
European GERA, UKB
PSS000112 Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 27010
[
  • 6,568 cases
  • , 219,648 controls
]
,
0.0 % Male samples
European GERA, UKB
PSS000113 Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 21041 - 21049, 21051, 21052, and 21060
[
  • 5,895 cases
  • , 410,354 controls
]
,
46.0 % Male samples
European GERA, UKB
PSS000114 Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 27020
[
  • 2,051 cases
  • , 219,648 controls
]
,
0.0 % Male samples
European GERA, UKB
PSS000115 Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 29020
[
  • 1,341 cases
  • , 410,354 controls
]
,
46.0 % Male samples
European GERA, UKB
PSS000116 Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 35011 - 35013
[
  • 853 cases
  • , 410,354 controls
]
,
46.0 % Male samples
European GERA, UKB
PSS000117 Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 22030
[
  • 2,488 cases
  • , 410,354 controls
]
,
46.0 % Male samples
European GERA, UKB
PSS000118 Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 25010
[
  • 6,782 cases
  • , 410,354 controls
]
,
46.0 % Male samples
European GERA, UKB
PSS000119 Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 33041, and 33042
[
  • 2,411 cases
  • , 410,354 controls
]
,
46.0 % Male samples
European GERA, UKB
PSS000120 Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 20010, 20020, 20030, 20040, 20050, 20060, 20070, 20080, 20090, and 20100
[
  • 1,223 cases
  • , 410,354 controls
]
,
46.0 % Male samples
European GERA, UKB
PSS000121 Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 27040
[
  • 1,261 cases
  • , 219,648 controls
]
,
0.0 % Male samples
European GERA, UKB
PSS000122 Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 21100
[
  • 665 cases
  • , 410,354 controls
]
,
46.0 % Male samples
European GERA, UKB
PSS000123 Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 28010
[
  • 10,810 cases
  • , 190,706 controls
]
,
100.0 % Male samples
European GERA, UKB
PSS000125 Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 28020
[
  • 713 cases
  • , 169,967 controls
]
,
100.0 % Male samples
European UKB
PSS000126 Cancer diagnoses were obtained from reigstry data in GERA, and ICD-9/10 codes mapped to ICD-O-3 codes in UK Biobank. Cancers for this phenotype were classified using the following SEER site recode(s): 32010
[
  • 764 cases
  • , 410,354 controls
]
,
46.0 % Male samples
European GERA, UKB
PSS000127 39,986 individuals,
50.0 % Male samples
European INTERVAL
PSS000128 40,133 individuals,
50.0 % Male samples
European INTERVAL
PSS000129 40,276 individuals,
49.0 % Male samples
European INTERVAL
PSS000130 40,326 individuals,
49.0 % Male samples
European INTERVAL
PSS000131 40,340 individuals,
49.0 % Male samples
European INTERVAL
PSS000132 40,329 individuals,
49.0 % Male samples
European INTERVAL
PSS000133 40,244 individuals,
49.0 % Male samples
European INTERVAL
PSS000134 40,225 individuals,
49.0 % Male samples
European INTERVAL
PSS000135 40,227 individuals,
49.0 % Male samples
European INTERVAL
PSS000136 39,191 individuals,
50.0 % Male samples
European INTERVAL
PSS000137 39,178 individuals,
50.0 % Male samples
European INTERVAL
PSS000138 40,108 individuals,
50.0 % Male samples
European INTERVAL
PSS000139 40,265 individuals,
50.0 % Male samples
European INTERVAL
PSS000140 40,080 individuals,
50.0 % Male samples
European INTERVAL
PSS000141 39,177 individuals,
50.0 % Male samples
European INTERVAL
PSS000142 39,189 individuals,
50.0 % Male samples
European INTERVAL
PSS000143 37,224 individuals,
50.0 % Male samples
European INTERVAL
PSS000144 39,138 individuals,
50.0 % Male samples
European INTERVAL
PSS000145 39,190 individuals,
50.0 % Male samples
European INTERVAL
PSS000146 37,306 individuals,
49.0 % Male samples
European INTERVAL
PSS000147 37,262 individuals,
50.0 % Male samples
European INTERVAL
PSS000148 38,939 individuals,
49.0 % Male samples
European INTERVAL
PSS000149 40,262 individuals,
49.0 % Male samples
European INTERVAL
PSS000150 40,253 individuals,
49.0 % Male samples
European INTERVAL
PSS000151 40,286 individuals,
49.0 % Male samples
European INTERVAL
PSS000152 40,466 individuals,
49.0 % Male samples
European INTERVAL
PSS000153 80,944 individuals,
46.0 % Male samples
European UKB
PSS000154 80,906 individuals,
46.0 % Male samples
European UKB
PSS000155 81,294 individuals,
46.0 % Male samples
European UKB
PSS000156 81,283 individuals,
45.0 % Male samples
European UKB
PSS000157 81,622 individuals,
46.0 % Male samples
European UKB
PSS000158 81,548 individuals,
46.0 % Male samples
European UKB
PSS000159 80,067 individuals,
46.0 % Male samples
European UKB
PSS000160 80,088 individuals,
46.0 % Male samples
European UKB
PSS000161 79,282 individuals,
46.0 % Male samples
European UKB
PSS000162 81,455 individuals,
45.0 % Male samples
European UKB
PSS000163 81,464 individuals,
46.0 % Male samples
European UKB
PSS000164 81,303 individuals,
46.0 % Male samples
European UKB
PSS000165 81,570 individuals,
46.0 % Male samples
European UKB
PSS000166 81,431 individuals,
46.0 % Male samples
European UKB
PSS000167 80,799 individuals,
46.0 % Male samples
European UKB
PSS000168 80,627 individuals,
46.0 % Male samples
European UKB
PSS000169 78,320 individuals,
46.0 % Male samples
European UKB
PSS000170 81,358 individuals,
45.0 % Male samples
European UKB
PSS000171 81,423 individuals,
46.0 % Male samples
European UKB
PSS000172 78,161 individuals,
46.0 % Male samples
European UKB
PSS000173 78,290 individuals,
46.0 % Male samples
European UKB
PSS000174 78,246 individuals,
46.0 % Male samples
European UKB
PSS000175 81,614 individuals,
45.0 % Male samples
European UKB
PSS000176 79,344 individuals,
46.0 % Male samples
European UKB
PSS000177 79,362 individuals,
46.0 % Male samples
European UKB
PSS000178 81,606 individuals,
46.0 % Male samples
European UKB
PSS000179 JIA diagnosis was made according to International League of Associations for Rheumatology standards (PMID:14760812) from EHR. Control subjects were unrelated and disease-free children.
[
  • 559 cases
  • , 2,954 controls
]
,
47.5 % Male samples
European CHOP
PSS000180 Diagnosis of JIA by a paediatric rheumatologist.
[
  • 362 cases
  • , 578 controls
]
,
48.9 % Male samples
European CLARITY Cohort description (PMID): 23153063
PSS000181 LDL-C serum biochemistry was desribed previously (http://biobank.ndph.ox.ac.uk/showcase/showcase/docs/serum_biochemistry.pdf). 4,680 individuals,
45.8 % Male samples
African unspecified UKB Genotyping Array Cohort
PSS000182 Cardiovascular disease events were defined as coronary and carotid revascularization, myocardial infarction, ischemic stroke, and all-cause mortality. The CVD events occurring before and after enrollment were included. Events occurring prior to enrollment were identified by either self-reported medical history and/or previous hospital admission documented in an electronic health record.
[
  • 5,397 cases
  • , 42,448 controls
]
,
43.36 % Male samples
European, East Asian, African unspecified UKB Genotyping Array & Exome Sequencing Cohort
PSS000183 LDL-C serum biochemistry was desribed previously (http://biobank.ndph.ox.ac.uk/showcase/showcase/docs/serum_biochemistry.pdf). 10,640 individuals,
45.8 % Male samples
East Asian UKB Genotyping Array Cohort
PSS000184 LDL-C serum biochemistry was desribed previously (http://biobank.ndph.ox.ac.uk/showcase/showcase/docs/serum_biochemistry.pdf). 439,871 individuals,
45.8 % Male samples
European UKB Genotyping Array Cohort
PSS000185 LDL-C serum biochemistry was desribed previously (http://biobank.ndph.ox.ac.uk/showcase/showcase/docs/serum_biochemistry.pdf). 4,680 individuals,
45.8 % Male samples
African unspecified UKB Genotyping Array Cohort
PSS000185 LDL-C serum biochemistry was desribed previously (http://biobank.ndph.ox.ac.uk/showcase/showcase/docs/serum_biochemistry.pdf). 10,640 individuals,
45.8 % Male samples
East Asian UKB Genotyping Array Cohort
PSS000185 LDL-C serum biochemistry was desribed previously (http://biobank.ndph.ox.ac.uk/showcase/showcase/docs/serum_biochemistry.pdf). 439,871 individuals,
45.8 % Male samples
European UKB Genotyping Array Cohort
PSS000206 Melanomas of skin : ICD9- 172.0,172.1,172.2,172.3,172.4,172.5,172.6,172.7,172.8,172.9
[
  • 1,279 cases
  • , 19,189 controls
]
,
46.9 % Male samples
European MGI
PSS000207 PheCode 172
[
  • 3,002 cases
  • , 17,466 controls
]
,
46.9 % Male samples
European MGI
PSS000208 Squamous cell carcinoma: ICD9-173.02,173.12,173.22,173.32,173.42,173.52,173.62,173.72,173.82,173.92
[
  • 563 cases
  • , 19,905 controls
]
,
46.9 % Male samples
European MGI
PSS000209 Basal cell carcinoma: ICD9-173.01,173.11,173.21,173.31,173.41,173.51,173.61,173.71,173.81,173.91
[
  • 884 cases
  • , 19,584 controls
]
,
46.9 % Male samples
European MGI
PSS000210 PheCode 172.11
[
  • 2,718 cases
  • , 27,180 controls
]
,
45.9 % Male samples
European White British Subset UKB
PSS000211 PheCode 172
[
  • 13,624 cases
  • , 136,233 controls
]
,
45.9 % Male samples
European White British Subset UKB
PSS000212 902 individuals,
0.0 % Male samples
European DOES
PSS000212 557 individuals,
100.0 % Male samples
European DOES
PSS000213
[
  • 135 cases
  • , 422 controls
]
,
100.0 % Male samples
European DOES
PSS000213
[
  • 95 cases
  • , 807 controls
]
,
0.0 % Male samples
European DOES
PSS000214
[
  • 395 cases
  • , 507 controls
]
,
0.0 % Male samples
European DOES
PSS000214
[
  • 135 cases
  • , 422 controls
]
,
100.0 % Male samples
European DOES
PSS000215
[
  • 166 cases
  • , 736 controls
]
,
0.0 % Male samples
European DOES
PSS000215
[
  • 53 cases
  • , 504 controls
]
,
100.0 % Male samples
European DOES
PSS000216
[
  • 9 cases
  • , 548 controls
]
,
100.0 % Male samples
European DOES
PSS000216
[
  • 103 cases
  • , 799 controls
]
,
0.0 % Male samples
European DOES
PSS000217 Phenotypic information was self-reported by the individual through an online, interactive health history tool
[
  • 239 cases
  • , 10,064 controls
]
,
17.1 % Male samples
European CG Samples are individuals whose healthcare provider had ordered a Color Genomics multi-gene panel test
PSS000218 Phenotypic information was self-reported by the individual through an online, interactive health history tool
[
  • 828 cases
  • , 8,701 controls
]
,
0.0 % Male samples
European CG Samples are individuals whose healthcare provider had ordered a Color Genomics multi-gene panel test
PSS000219 Phenotypic information was self-reported by the individual through an online, interactive health history tool
[
  • 126 cases
  • , 10,884 controls
]
,
17.1 % Male samples
European CG Samples are individuals whose healthcare provider had ordered a Color Genomics multi-gene panel test
PSS000220 Age of onset of aggressive prostate cancer, defined by Gleason score ≥7, PSA ≥10 ng/mL, T3-T4 stage, nodal metastases, or distant metastases
[
  • 26,419 cases
  • , 30,575 controls
]
,
100.0 % Male samples
European, East Asian, African American or Afro-Caribbean, Oceanian, Hispanic or Latin American, South Asian, African unspecified, NR Combined analysis of multiple ancestries, including: European, East Asian, African American, Hawaiian, Hispanic American, South Asian, Black African, Black Caribbean, and Other (not specified) OncoArray_Prostate List of Cohorts available from dbGaP: https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001391.v1.p1
PSS000221 Age of onset of aggressive prostate cancer, defined by Gleason score ≥7, PSA ≥10 ng/mL, T3-T4 stage, nodal metastases, or distant metastases
[
  • 1,424 cases
  • , 3,013 controls
]
,
100.0 % Male samples
African unspecified Subset of OncoArray_APC_onset samples. Determined from genetic PCs via FastPop OncoArray_Prostate List of Cohorts available from dbGaP: https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001391.v1.p1
PSS000222 Age of onset of aggressive prostate cancer, defined by Gleason score ≥7, PSA ≥10 ng/mL, T3-T4 stage, nodal metastases, or distant metastases
[
  • 716 cases
  • , 1,185 controls
]
,
100.0 % Male samples
Asian unspecified Subset of OncoArray_APC_onset samples. Determined from genetic PCs via FastPop OncoArray_Prostate List of Cohorts available from dbGaP: https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001391.v1.p1
PSS000223 Age of onset of aggressive prostate cancer, defined by Gleason score ≥7, PSA ≥10 ng/mL, T3-T4 stage, nodal metastases, or distant metastases
[
  • 24,279 cases
  • , 26,377 controls
]
,
100.0 % Male samples
European Subset of OncoArray_APC_onset samples. Determined from genetic PCs via FastPop OncoArray_Prostate List of Cohorts available from dbGaP: https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001391.v1.p1
PSS000224 Age at death due to prostate cancer.
[
  • 3,983 cases
  • , 30,575 controls
]
,
100.0 % Male samples
European, East Asian, African American or Afro-Caribbean, Oceanian, Hispanic or Latin American, South Asian, African unspecified, NR Combined analysis of multiple ancestries, including: European, East Asian, African American, Hawaiian, Hispanic American, South Asian, Black African, Black Caribbean, and Other (not specified) OncoArray_Prostate List of Cohorts available from dbGaP: https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001391.v1.p1
PSS000225
[
  • 334 cases
  • , 135 controls
]
,
55.22 % Male samples
European PPMI Both the PPMI and WUSTL datasets are available by request from the PPMI website (www.ppmi-info.org)
PSS000226
[
  • 493 cases
  • , 293 controls
]
,
58.27 % Male samples
European WUSTL Both the PPMI and WUSTL datasets are available by request from the PPMI website (www.ppmi-info.org)
PSS000227
[
  • 40 cases
  • , 504 controls
]
Asian unspecified MESA, VIRGO Cases are from VIRGO, controls are from MESA
PSS000228
[
  • 336 cases
  • , 962 controls
]
African American or Afro-Caribbean MESA, VIRGO Cases are from VIRGO, controls are from MESA
PSS000229
[
  • 168 cases
  • , 751 controls
]
Hispanic or Latin American MESA, VIRGO Cases are from VIRGO, controls are from MESA
PSS000230
[
  • 1,537 cases
  • , 1,544 controls
]
European MESA, VIRGO Cases are from VIRGO, controls are from MESA
PSS000231 Advanced primary open-angle glaucoma
[
  • 1,734 cases
  • , 2,938 controls
]
European ANZRAG Samples come from Phase 1 and Phase 2 of ANZRAG.
PSS000232 Individuals with T2D were defined as those with fasting time >8 h and fasting glucose levels ≥126 mg/dL, fasting ≤8 h and fasting glucose ≥200 mg/dL, post–oral glucose tolerance test glucose ≥200 mg/dL, HbA1c ≥6.5% (48 mmol/mol), or on current treatment with antihyperglycemia medications.
[
  • 2,499 cases
  • , 5,247 controls
]
,
39.65 % Male samples
Hispanic or Latin American
(Central American, Cuban, Dominican, Mexican, Puerto Rican, South American)
Ancestry groups were defined based on a combination of self-identified Hispanic/Latino background and genetic similarity HCHS, SOL
PSS000233 Gout identified by self-report at the inclusion visit, individuals with an ICD-10 for gout (M10) in hospital admissions who did not self-report gout were excluded from the analysis.
[
  • 4,908 cases
  • , 329,972 controls
]
European White British subset, unrelated UKB
PSS000234 Incident type 2 diabtes defined as fasting glucose >= 7 mmol/L, 2 hour glucose >= 11.1 mmol/L, antidiabetic medication use, or a physician diagnosis of type 2 diabetes
[
  • 262 cases
  • , 1,644 controls
]
,
37.93 % Male samples
African unspecified ARIC, MESA Partial overlap with discovery GWAS
PSS000235 Incident type 2 diabtes defined as fasting glucose >= 7 mmol/L, 2 hour glucose >= 11.1 mmol/L, antidiabetic medication use, or a physician diagnosis of type 2 diabetes
[
  • 2,391 cases
  • , 2,682 controls
]
,
47.45 % Male samples
East Asian MESA, SCHS Partial overlap with discovery GWAS
PSS000236 Incident type 2 diabtes defined as fasting glucose >= 7 mmol/L, 2 hour glucose >= 11.1 mmol/L, antidiabetic medication use, or a physician diagnosis of type 2 diabetes
[
  • 13,145 cases
  • , 24,212 controls
]
,
43.47 % Male samples
European ARIC, FHS, InterAct, MESA Partial overlap with discovery GWAS
PSS000237 Schizophrenia case subjects had two or more ICD codes included in phecode 295.1
[
  • 110 cases
  • , 33,584 controls
]
,
46.0 % Male samples
European BioVU Vanderbilt University Medical Center (VUMC) biobank (BioVU)
PSS000238 Psychosis case subjects were identified with phecode 295
[
  • 451 cases
  • , 33,243 controls
]
,
46.0 % Male samples
European BioVU Vanderbilt University Medical Center (VUMC) biobank (BioVU)
PSS000239 Schizophrenia case subjects had two or more ICD codes included in phecode 295.1
[
  • 211 cases
  • , 44,225 controls
]
,
41.0 % Male samples
European MyCode Geisinger Health System (GHS)
PSS000240 Psychosis case subjects were identified with phecode 295
[
  • 499 cases
  • , 43,937 controls
]
,
41.0 % Male samples
European MyCode Geisinger Health System (GHS)
PSS000241 Schizophrenia case subjects had two or more ICD codes included in phecode 295.1
[
  • 53 cases
  • , 9,516 controls
]
,
48.0 % Male samples
European BioMe BioMe Biobank at the Mount Sinai School of Medicine (MSSM)
PSS000243 Schizophrenia case subjects had two or more ICD codes included in phecode 295.1
[
  • 148 cases
  • , 18,313 controls
]
,
46.0 % Male samples
European PHB Partners HealthCare System (PHS) biobank
PSS000244 Psychosis case subjects were identified with phecode 295
[
  • 385 cases
  • , 18,076 controls
]
,
46.0 % Male samples
European PHB Partners HealthCare System (PHS) biobank
PSS000245
[
  • 74 cases
  • , 1,721 controls
]
,
43.0 % Male samples
European BMES
PSS000246 MYOC p.Gln368Ter (rs74315329) carriers using imputation. Glaucoma cases were defined as those who (i) had an ICD-10 diagnosis of ‘primary open angle glaucoma’, ‘other glaucoma’ or ‘glaucoma, unspecified’; (ii) responded ‘glaucoma’ to the question ‘Has a doctor told you that you have any of the following problems with your eyes?’; or (iii) responded ‘glaucoma’ to the question ‘In the touch screen you selected that you have been told by a doctor that you have other serious illnesses or disabilities, could you now tell me what they are? (non-cancer illness).
[
  • 72 cases
  • , 893 controls
]
European UKB
PSS000247 ICD-10 defined Primary open-angle glaucoma (POAG)
[
  • 112 cases
  • , 3,000 controls
]
European UKB
PSS000248 Glaucoma cases were defined as those who (i) had an ICD-10 diagnosis of ‘primary open angle glaucoma’, ‘other glaucoma’ or ‘glaucoma, unspecified’; (ii) responded ‘glaucoma’ to the question ‘Has a doctor told you that you have any of the following problems with your eyes?’; or (iii) responded ‘glaucoma’ to the question ‘In the touch screen you selected that you have been told by a doctor that you have other serious illnesses or disabilities, could you now tell me what they are? (non-cancer illness).
[
  • 112 cases
  • , 3,000 controls
]
European UKB
PSS000249 Glaucoma cases were defined as those who (i) had an ICD-10 diagnosis of ‘primary open angle glaucoma’, ‘other glaucoma’ or ‘glaucoma, unspecified’; (ii) responded ‘glaucoma’ to the question ‘Has a doctor told you that you have any of the following problems with your eyes?’; or (iii) responded ‘glaucoma’ to the question ‘In the touch screen you selected that you have been told by a doctor that you have other serious illnesses or disabilities, could you now tell me what they are? (non-cancer illness).
[
  • 192 cases
  • , 6,841 controls
]
South Asian UKB
PSS000250
[
  • 14,696 cases
  • , 22,013 controls
]
European 15 cohorts
  • BOMA
  • ,CoLaus
  • ,Edinburgh
  • ,GenPOD
  • ,GenRED
  • ,MARS
  • ,MPIP
  • ,NESDA
  • ,QIMR
  • ,RADIANT
  • ,RS
  • ,SHIP
  • ,STAR*D
  • ,TwinGene
  • ,i2b2
Part of PGC29 (PMID: 29700475)
PSS000251 Colorectal adenocarcinoma located in the distal colon confirmed by medical records, pathology reports, or death certificate
[
  • 1,026 cases
  • , 3,860 controls
]
,
0.0 % Male samples
European 6 cohorts
  • DACHS
  • ,DALS
  • ,HPFS
  • ,NHS
  • ,VITAL
  • ,WHI
Training and test split not relevant to PGS
PSS000252 Colorectal adenocarcinoma located in the distal colon confirmed by medical records, pathology reports, or death certificate
[
  • 827 cases
  • , 2,442 controls
]
,
100.0 % Male samples
European 6 cohorts
  • DACHS
  • ,DALS
  • ,HPFS
  • ,NHS
  • ,VITAL
  • ,WHI
Training and test split not relevant to PGS
PSS000253 Colorectal adenocarcinoma located in the proximal colon confirmed by medical records, pathology reports, or death certificate
[
  • 1,670 cases
  • , 3,860 controls
]
,
0.0 % Male samples
European 6 cohorts
  • DACHS
  • ,DALS
  • ,HPFS
  • ,NHS
  • ,VITAL
  • ,WHI
Training and test split not relevant to PGS
PSS000254 Colorectal adenocarcinoma located in the proximal colon confirmed by medical records, pathology reports, or death certificate
[
  • 850 cases
  • , 2,442 controls
]
,
100.0 % Male samples
European 6 cohorts
  • DACHS
  • ,DALS
  • ,HPFS
  • ,NHS
  • ,VITAL
  • ,WHI
Training and test split not relevant to PGS
PSS000255 Colorectal adenocarcinoma located in the rectum confirmed by medical records, pathology reports, or death certificate
[
  • 713 cases
  • , 3,860 controls
]
,
0.0 % Male samples
European 6 cohorts
  • DACHS
  • ,DALS
  • ,HPFS
  • ,NHS
  • ,VITAL
  • ,WHI
Training and test split not relevant to PGS
PSS000256 Colorectal adenocarcinoma located in the rectum confirmed by medical records, pathology reports, or death certificate
[
  • 725 cases
  • , 2,442 controls
]
,
100.0 % Male samples
European 6 cohorts
  • DACHS
  • ,DALS
  • ,HPFS
  • ,NHS
  • ,VITAL
  • ,WHI
Training and test split not relevant to PGS
PSS000257 Colorectal adenocarcinoma confirmed by medical records, pathology reports, or death certificate
[
  • 380 cases
  • , 353 controls
]
,
0.0 % Male samples
European 6 cohorts
  • DACHS
  • ,DALS
  • ,HPFS
  • ,NHS
  • ,VITAL
  • ,WHI
Training and test split not relevant to PGS
PSS000258 Colorectal adenocarcinoma confirmed by medical records, pathology reports, or death certificate
[
  • 486 cases
  • , 516 controls
]
,
100.0 % Male samples
European 6 cohorts
  • DACHS
  • ,DALS
  • ,HPFS
  • ,NHS
  • ,VITAL
  • ,WHI
Training and test split not relevant to PGS
PSS000259
[
  • 1,336 cases
  • , 2,744 controls
]
,
57.21 % Male samples
European
(Spanish)
MCC-Spain
PSS000260
[
  • 2,568 cases
  • , 2,932 controls
]
,
0.0 % Male samples
European 14 cohorts
  • CPSII
  • ,DACHS
  • ,DALS
  • ,HPFS
  • ,Hawaiian_Colo2&3
  • ,KCCS
  • ,MCCS
  • ,MEC
  • ,MECC
  • ,NFCCR
  • ,NHS
  • ,PLCO
  • ,VITAL
  • ,WHI
PSS000261
[
  • 2,307 cases
  • , 2,359 controls
]
,
100.0 % Male samples
European 14 cohorts
  • CPSII
  • ,DACHS
  • ,DALS
  • ,HPFS
  • ,Hawaiian_Colo2&3
  • ,KCCS
  • ,MCCS
  • ,MEC
  • ,MECC
  • ,NFCCR
  • ,NHS
  • ,PLCO
  • ,VITAL
  • ,WHI
PSS000262 Excluding participants with prevalent cancer at recruitment colorectal cancer was defined as ICD codes: C18 (except C18.1, Appendix), C19 and C20
[
  • 1,623 cases
  • , 359,920 controls
]
,
45.0 % Male samples
European UKB Follow-up time = 1,751,445 person years
PSS000263 Excluding participants with prevalent cancer at recruitment colorectal cancer was defined as ICD codes: C18 (except C18.1, Appendix), C19 and C20
[
  • 1,294 cases
  • , 285,583 controls
]
,
46.0 % Male samples
European UKB Follow-up time = 1,388,191 person years
PSS000268 Unselected participants of the German screening colonoscopy program are recruited by gastroenterology practices in southern Germany in this multicenter study.Colonoscopy and histology reports are collected and information from these reports is extracted independently in a standardized way by two trained investigators, who are blinded with respect to questionnaire and genotype data and who resolve discrepancies by consensus after further review and discussion. Based on colonoscopy reports, participants are categorized with respect to the most advanced lesion: CRC, advanced adenoma (AA), non-advanced adenoma (NAA), hyperplastic polyp, or undefined polyp. Advanced adenomas are defined as adenomas ≥1 cm or adenomas with cellular or structural atypia.
[
  • 294 cases
  • , 749 controls
]
,
61.74 % Male samples
European BLITZ
PSS000269 Unselected participants of the German screening colonoscopy program are recruited by gastroenterology practices in southern Germany in this multicenter study.Colonoscopy and histology reports are collected and information from these reports is extracted independently in a standardized way by two trained investigators, who are blinded with respect to questionnaire and genotype data and who resolve discrepancies by consensus after further review and discussion. Based on colonoscopy reports, participants are categorized with respect to the most advanced lesion: CRC, advanced adenoma (AA), non-advanced adenoma (NAA), hyperplastic polyp, or undefined polyp. Advanced adenomas are defined as adenomas ≥1 cm or adenomas with cellular or structural atypia.
[
  • 249 cases
  • , 500 controls
]
,
60.48 % Male samples
European BLITZ
PSS000271
[
  • 1,316 cases
  • , 2,207 controls
]
,
40.85 % Male samples
East Asian
(Han Chinese)
NCRCC
PSS000272 Primary tumor samples from TCGA
[
  • 343 cases
  • , 0 controls
]
European TCGA
PSS000272
[
  • 0 cases
  • , 13,427 controls
]
European eMERGE
PSS000273 Primary tumor samples from TCGA
[
  • 827 cases
  • , 0 controls
]
,
0.0 % Male samples
European TCGA
PSS000273
[
  • 0 cases
  • , 7,020 controls
]
,
0.0 % Male samples
European eMERGE
PSS000274
[
  • 0 cases
  • , 13,427 controls
]
European eMERGE
PSS000274 Primary tumor samples from TCGA
[
  • 387 cases
  • , 0 controls
]
European TCGA
PSS000275 Primary tumor samples from TCGA
[
  • 992 cases
  • , 0 controls
]
European TCGA
PSS000275
[
  • 0 cases
  • , 13,427 controls
]
European eMERGE
PSS000276
[
  • 0 cases
  • , 13,427 controls
]
European eMERGE
PSS000276 Primary tumor samples from TCGA
[
  • 908 cases
  • , 0 controls
]
European TCGA
PSS000277 Primary tumor samples from TCGA
[
  • 450 cases
  • , 0 controls
]
European TCGA
PSS000277
[
  • 0 cases
  • , 13,427 controls
]
European eMERGE
PSS000278 Primary tumor samples from TCGA
[
  • 531 cases
  • , 0 controls
]
,
0.0 % Male samples
European TCGA
PSS000278
[
  • 0 cases
  • , 7,020 controls
]
,
0.0 % Male samples
European eMERGE
PSS000279 Primary tumor samples from TCGA
[
  • 163 cases
  • , 0 controls
]
European TCGA
PSS000279
[
  • 0 cases
  • , 13,427 controls
]
European eMERGE
PSS000280 Primary tumor samples from TCGA
[
  • 421 cases
  • , 0 controls
]
,
100.0 % Male samples
European TCGA
PSS000280
[
  • 0 cases
  • , 6,407 controls
]
,
100.0 % Male samples
European eMERGE
PSS000281
[
  • 0 cases
  • , 13,427 controls
]
European eMERGE
PSS000281 Primary tumor samples from TCGA
[
  • 453 cases
  • , 0 controls
]
European TCGA
PSS000282 Primary tumor samples from TCGA
[
  • 387 cases
  • , 0 controls
]
European TCGA
PSS000282
[
  • 0 cases
  • , 13,427 controls
]
European eMERGE
PSS000283 Composite endpoint of either: myocardial infarction, coronary revascularization, death from coronary causes.
[
  • 1,230 cases
  • , 6,584 controls
]
,
45.0 % Male samples
European ARIC
PSS000284 Cross-sectional analysis of baseline scores for coronary artery calcification (Agatston score) 4,260 individuals,
44.0 % Male samples
European BioImage
PSS000285 Composite endpoint of either: myocardial infarction, coronary revascularization, death from coronary causes.
[
  • 2,902 cases
  • , 19,487 controls
]
,
38.0 % Male samples
European MDC-CC
PSS000286 Composite endpoint of either: myocardial infarction, coronary revascularization, death from coronary causes.
[
  • 971 cases
  • , 20,251 controls
]
,
0.0 % Male samples
European WGHS
PSS000287 (i) Secondary cardiovascular events (sCVE; incl myocardial infarction, stroke, ruptured abdominal aortic aneurysm, fatal cardiac failure, percuteneous of bypass surgery, leg amputation due to cardiovascular causes, cardiovascular death), (ii) atherosclerotic carotid plaque characteristics 1,319 individuals,
69.3 % Male samples
European
(Dutch)
AEGS1
PSS000290 2,314 individuals European
(French Canadian)
CARTaGENE
PSS000291 39,260 individuals European INTERVAL
PSS000292 Composite end point of cardiovascular events was defined as myocardial infarction, ischemic stroke, and death from coronary heart disease. Death from coronary heart disease was defined on the basis of codes 412 and 414 (ICD-9) or I22–I23 and I25 (ICD-10) in the Swedish Cause of Death Register. Myocardial infarction was defined on the basis of codes 410 and I21 in the International Classification of Diseases, 9th Revision and 10th Revision (ICD-9 and ICD-10), respectively. Ischemic stroke was defined on the basis of codes 434 or 436 (ICD-9) and I63 or I64 (ICD-10).
[
  • 238 cases
  • , 3,994 controls
]
European MDC
PSS000294 Participants completed an online follow-up questionnaire assessing common mental health disorders, including MDD symptoms. Phenotypes were derived from this questionnaire. Individuals with probable MDD met lifetime criteria based on their responses to questions derived from the Composite International Diagnostic Interview. We excluded cases if they self-reported diagnoses of schizophrenia, other psychoses, or bipolar disorder. Controls were excluded if they self-reported any mental illness, taking any drug with an antidepressant indication, or had been hospitalised with a mood disorder or met previously-defined criteria for a mood disorder.
[
  • 29,475 cases
  • , 63,482 controls
]
,
45.0 % Male samples
European UKB
PSS000310 Setting II: Based on ICD codes and review of medical records from Partners HealthCare Biobank; controls = other non-matching arthritis diseases
[
  • 32 cases
  • , 213 controls
]
,
32.0 % Male samples
European PHB
PSS000311 Setting III: Based on ICD codes and final diagnosis in medical records from Partners HealthCare Biobank; controls = other non-matching arthritis diseases
[
  • 22 cases
  • , 221 controls
]
,
32.0 % Male samples
European PHB
PSS000312 Setting II: Based on ICD codes and review of medical records from Partners HealthCare Biobank; controls = other non-matching arthritis diseases
[
  • 30 cases
  • , 215 controls
]
,
32.0 % Male samples
European PHB
PSS000313 Setting III: Based on ICD codes and final diagnosis in medical records from Partners HealthCare Biobank; controls = other non-matching arthritis diseases
[
  • 22 cases
  • , 221 controls
]
,
32.0 % Male samples
European PHB
PSS000314 Setting II: Based on ICD codes and review of medical records from Partners HealthCare Biobank; controls = other non-matching arthritis diseases
[
  • 90 cases
  • , 155 controls
]
,
32.0 % Male samples
European PHB
PSS000315 Setting III: Based on ICD codes and final diagnosis in medical records from Partners HealthCare Biobank; controls = other non-matching arthritis diseases
[
  • 115 cases
  • , 128 controls
]
,
32.0 % Male samples
European PHB
PSS000316 Setting II: Based on ICD codes and review of medical records from Partners HealthCare Biobank; controls = other non-matching arthritis diseases
[
  • 31 cases
  • , 214 controls
]
,
32.0 % Male samples
European PHB
PSS000317 Setting III: Based on ICD codes and final diagnosis in medical records from Partners HealthCare Biobank; controls = other non-matching arthritis diseases
[
  • 8 cases
  • , 235 controls
]
,
32.0 % Male samples
European PHB
PSS000318 Setting II: Based on ICD codes and review of medical records from Partners HealthCare Biobank; controls = other non-matching arthritis diseases
[
  • 62 cases
  • , 183 controls
]
,
32.0 % Male samples
European PHB
PSS000319 Setting III: Based on ICD codes and final diagnosis in medical records from Partners HealthCare Biobank; controls = other non-matching arthritis diseases
[
  • 7 cases
  • , 236 controls
]
,
32.0 % Male samples
European PHB
PSS000320 Setting I: Based on ICD codes and expert opinion (ACR2010 criteria), in eMERGE network EMR database from Stanaway 2018; controls = other non-matching arthritis diseases
[
  • 387 cases
  • , 824 controls
]
,
43.0 % Male samples
European, African unspecified, Asian unspecified, NR Primarily European, African and Asian ancestry eMERGE
PSS000321 Setting I: Based on ICD codes and expert opinion (ACR2010 criteria), in eMERGE network EMR database from Stanaway 2018; controls = other non-matching arthritis diseases
[
  • 52 cases
  • , 1,159 controls
]
,
43.0 % Male samples
European, African unspecified, Asian unspecified, NR Primarily European, African and Asian ancestry eMERGE
PSS000322 Setting I: Based on ICD codes and expert opinion (ACR2010 criteria), in eMERGE network EMR database from Stanaway 2018; controls = other non-matching arthritis diseases
[
  • 574 cases
  • , 637 controls
]
,
43.0 % Male samples
European, African unspecified, Asian unspecified, NR Primarily European, African and Asian ancestry eMERGE
PSS000323 Setting I: Based on ICD codes and expert opinion (ACR2010 criteria), in eMERGE network EMR database from Stanaway 2018; controls = other non-matching arthritis diseases
[
  • 65 cases
  • , 1,146 controls
]
,
43.0 % Male samples
European, African unspecified, Asian unspecified, NR Primarily European, African and Asian ancestry eMERGE
PSS000324 Setting I: Based on ICD codes and expert opinion (ACR2010 criteria), in eMERGE network EMR database from Stanaway 2018; controls = other non-matching arthritis diseases
[
  • 133 cases
  • , 1,078 controls
]
,
43.0 % Male samples
European, African unspecified, Asian unspecified, NR Primarily European, African and Asian ancestry eMERGE
PSS000328 ACS was defined as MI, unstable angina or death due to CHD.
[
  • 148 cases
  • , 7,182 controls
]
,
45.0 % Male samples
European
(Finnish)
FINRISK FINRISK 2002
PSS000328 ACS was defined as MI, unstable angina or death due to CHD.
[
  • 119 cases
  • , 5,004 controls
]
,
46.3 % Male samples
European
(Finnish)
Health2000
PSS000328 ACS was defined as MI, unstable angina or death due to CHD.
[
  • 229 cases
  • , 6,338 controls
]
,
45.8 % Male samples
European
(Finnish)
FINRISK97 FINRISK 1997
PSS000328 ACS was defined as MI, unstable angina or death due to CHD.
[
  • 235 cases
  • , 4,869 controls
]
,
44.8 % Male samples
European
(Finnish)
FINRISK FINRISK 1992
PSS000329 CHD was defined as myocardial infarction, unstable angina pectoris, coronary revascularization (coronary artery bypass graft or percutaneous transluminal coronary angioplasty), or death due to CHD.
[
  • 209 cases
  • , 7,121 controls
]
,
45.0 % Male samples
European
(Finnish)
FINRISK FINRISK 2002
PSS000329 CHD was defined as myocardial infarction, unstable angina pectoris, coronary revascularization (coronary artery bypass graft or percutaneous transluminal coronary angioplasty), or death due to CHD.
[
  • 343 cases
  • , 4,761 controls
]
,
44.8 % Male samples
European
(Finnish)
FINRISK FINRISK 1992
PSS000329 CHD was defined as myocardial infarction, unstable angina pectoris, coronary revascularization (coronary artery bypass graft or percutaneous transluminal coronary angioplasty), or death due to CHD.
[
  • 344 cases
  • , 6,223 controls
]
,
45.8 % Male samples
European
(Finnish)
FINRISK97 FINRISK 1997
PSS000329 CHD was defined as myocardial infarction, unstable angina pectoris, coronary revascularization (coronary artery bypass graft or percutaneous transluminal coronary angioplasty), or death due to CHD.
[
  • 197 cases
  • , 4,926 controls
]
,
46.3 % Male samples
European
(Finnish)
Health2000
PSS000330 CHD was defined as myocardial infarction, unstable angina pectoris, coronary revascularization (coronary artery bypass graft or percutaneous transluminal coronary angioplasty), or death due to CHD. CVD included CHD and ischemic stroke events.
[
  • 261 cases
  • , 4,862 controls
]
,
46.3 % Male samples
European
(Finnish)
Health2000
PSS000330 CHD was defined as myocardial infarction, unstable angina pectoris, coronary revascularization (coronary artery bypass graft or percutaneous transluminal coronary angioplasty), or death due to CHD. CVD included CHD and ischemic stroke events.
[
  • 501 cases
  • , 4,603 controls
]
,
44.8 % Male samples
European
(Finnish)
FINRISK FINRISK 1992
PSS000330 CHD was defined as myocardial infarction, unstable angina pectoris, coronary revascularization (coronary artery bypass graft or percutaneous transluminal coronary angioplasty), or death due to CHD. CVD included CHD and ischemic stroke events.
[
  • 499 cases
  • , 6,068 controls
]
,
45.8 % Male samples
European
(Finnish)
FINRISK97 FINRISK 1997
PSS000330 CHD was defined as myocardial infarction, unstable angina pectoris, coronary revascularization (coronary artery bypass graft or percutaneous transluminal coronary angioplasty), or death due to CHD. CVD included CHD and ischemic stroke events.
[
  • 291 cases
  • , 7,039 controls
]
,
45.0 % Male samples
European
(Finnish)
FINRISK FINRISK 2002
PSS000331 CHD was defined as occurrence of either myocardial infarction (MI) or coronary revascularization events (such as percutaneous coronary intervention or coronary artery bypass grafting) using ICD codes. Individuals with MI were defined as those whose EHR included at least two related diagnostic codes on separate occasions within a 5-day window, and individuals with coronary revascularization were defined as those who had at least one relevant procedural code in the EHR. ICD codelists and phenotyping algorithm in PMID:27678441 and PMID:25717410
[
  • 838 cases
  • , 6,759 controls
]
,
31.0 % Male samples
African American or Afro-Caribbean 7 cohorts
  • BioMe
  • ,BioVU
  • ,Columbia
  • ,KP
  • ,Nugene
  • ,PHB
  • ,eMERGE
right censored at age 75 years or at the age of last observation (whichever was first)
PSS000332 CHD was defined as occurrence of either myocardial infarction (MI) or coronary revascularization events (such as percutaneous coronary intervention or coronary artery bypass grafting) using ICD codes. Individuals with MI were defined as those whose EHR included at least two related diagnostic codes on separate occasions within a 5-day window, and individuals with coronary revascularization were defined as those who had at least one relevant procedural code in the EHR. We identified the first CHD event and classified it as ‘‘incident’’ if the event occurred at least 6 months after the participant’s first record in the EHR and if there were no previous ICD-9-CM or ICD-10-CM codes associated with CHD. ICD codelists and phenotyping algorithm in PMID:27678441 and PMID:25717410
[
  • 311 cases
  • , 6,759 controls
]
,
31.0 % Male samples
African American or Afro-Caribbean 7 cohorts
  • BioMe
  • ,BioVU
  • ,Columbia
  • ,KP
  • ,Nugene
  • ,PHB
  • ,eMERGE
right censored at age 75 years or at the age of last observation (whichever was first)
PSS000333 CHD was defined as occurrence of either myocardial infarction (MI) or coronary revascularization events (such as percutaneous coronary intervention or coronary artery bypass grafting) using ICD codes. Individuals with MI were defined as those whose EHR included at least two related diagnostic codes on separate occasions within a 5-day window, and individuals with coronary revascularization were defined as those who had at least one relevant procedural code in the EHR. ICD codelists and phenotyping algorithm in PMID:27678441 and PMID:25717410
[
  • 8,108 cases
  • , 37,537 controls
]
,
44.6 % Male samples
European 11 cohorts
  • BioMe
  • ,BioVU
  • ,CCHMC
  • ,Columbia
  • ,KP
  • ,MAYO
  • ,Marshfield
  • ,MyCode
  • ,Nugene
  • ,PHB
  • ,eMERGE
right censored at age 75 years or at the age of last observation (whichever was first)
PSS000334 CHD was defined as occurrence of either myocardial infarction (MI) or coronary revascularization events (such as percutaneous coronary intervention or coronary artery bypass grafting) using ICD codes. Individuals with MI were defined as those whose EHR included at least two related diagnostic codes on separate occasions within a 5-day window, and individuals with coronary revascularization were defined as those who had at least one relevant procedural code in the EHR. We identified the first CHD event and classified it as ‘‘incident’’ if the event occurred at least 6 months after the participant’s first record in the EHR and if there were no previous ICD-9-CM or ICD-10-CM codes associated with CHD. ICD codelists and phenotyping algorithm in PMID:27678441 and PMID:25717410
[
  • 2,221 cases
  • , 37,537 controls
]
,
44.6 % Male samples
European 11 cohorts
  • BioMe
  • ,BioVU
  • ,CCHMC
  • ,Columbia
  • ,KP
  • ,MAYO
  • ,Marshfield
  • ,MyCode
  • ,Nugene
  • ,PHB
  • ,eMERGE
right censored at age 75 years or at the age of last observation (whichever was first)
PSS000335 CHD was defined as occurrence of either myocardial infarction (MI) or coronary revascularization events (such as percutaneous coronary intervention or coronary artery bypass grafting) using ICD codes. Individuals with MI were defined as those whose EHR included at least two related diagnostic codes on separate occasions within a 5-day window, and individuals with coronary revascularization were defined as those who had at least one relevant procedural code in the EHR. ICD codelists and phenotyping algorithm in PMID:27678441 and PMID:25717410
[
  • 419 cases
  • , 2,074 controls
]
,
36.2 % Male samples
Hispanic or Latin American 8 cohorts
  • BioMe
  • ,BioVU
  • ,Columbia
  • ,KP
  • ,MAYO
  • ,Nugene
  • ,PHB
  • ,eMERGE
right censored at age 75 years or at the age of last observation (whichever was first)
PSS000336 CHD was defined as occurrence of either myocardial infarction (MI) or coronary revascularization events (such as percutaneous coronary intervention or coronary artery bypass grafting) using ICD codes. Individuals with MI were defined as those whose EHR included at least two related diagnostic codes on separate occasions within a 5-day window, and individuals with coronary revascularization were defined as those who had at least one relevant procedural code in the EHR. We identified the first CHD event and classified it as ‘‘incident’’ if the event occurred at least 6 months after the participant’s first record in the EHR and if there were no previous ICD-9-CM or ICD-10-CM codes associated with CHD. ICD codelists and phenotyping algorithm in PMID:27678441 and PMID:25717410
[
  • 120 cases
  • , 2,074 controls
]
,
36.2 % Male samples
Hispanic or Latin American 8 cohorts
  • BioMe
  • ,BioVU
  • ,Columbia
  • ,KP
  • ,MAYO
  • ,Nugene
  • ,PHB
  • ,eMERGE
right censored at age 75 years or at the age of last observation (whichever was first)
PSS000339 7,599 individuals,
47.16 % Male samples
European COGA
PSS000340 1,251 individuals,
45.6 % Male samples
European
(Finnish)
FinnTwin12 Twin Study
PSS000341 Cases were ascertained using ICD-10 C73 (PTC, FTC, cancer/carcinoma, and rare nonmedullary)
[
  • 723 cases
  • , 129,556 controls
]
,
46.41 % Male samples
European deCODE
PSS000342 Histologically confirmed papillary or follicular thyroid carcinoma (PTC) patients (including traditional PTC and follicular variant PTC)
[
  • 1,544 cases
  • , 1,593 controls
]
,
26.08 % Male samples
European NR
PSS000343 Cases were ascertained using ICD-10 C73 (PTC, FTC, cancer/carcinoma, and rare nonmedullary)
[
  • 534 cases
  • , 407,945 controls
]
,
45.97 % Male samples
European UKB
PSS000344
[
  • 910 cases
  • , 1,556 controls
]
African American or Afro-Caribbean COPDGene
PSS000345 FEV1/FVC<0.7 and FEV1<80% predicted (i.e. corresponding to GOLD 2-4 standards)
[
  • 69,567 cases
  • , 6,013 controls
]
East Asian
(Chinese)
CKB
PSS000346
[
  • 6,979 cases
  • , 3,915 controls
]
European 6 cohorts
  • COPDGene
  • ,ECLIPSE
  • ,GenKOLS
  • ,NAS
  • ,NETT
  • ,SPIROMICS
PSS000347 FEV1/FVC<0.7 and FEV1<80% predicted (i.e. corresponding to GOLD 2-4 standards)
[
  • 172 cases
  • , 4,053 controls
]
African unspecified UKB
PSS000348 FEV1/FVC<0.7 and FEV1<80% predicted (i.e. corresponding to GOLD 2-4 standards)
[
  • 288,467 cases
  • , 15,103 controls
]
European UKB
PSS000349 FEV1/FVC<0.7 and FEV1<80% predicted (i.e. corresponding to GOLD 2-4 standards)
[
  • 5,752 cases
  • , 281 controls
]
Other admixed ancestry UKB
PSS000350 FEV1/FVC<0.7 and FEV1<80% predicted (i.e. corresponding to GOLD 2-4 standards)
[
  • 6,046 cases
  • , 312 controls
]
South Asian UKB
PSS000351 72,796 individuals East Asian
(Chinese)
CKB
PSS000352 4,225 individuals African unspecified UKB
PSS000353 1,208 individuals Other admixed ancestry
(Admixed African (unspecified) and European)
UKB
PSS000354 1,607 individuals East Asian UKB
PSS000355 303,570 individuals European UKB
PSS000356 6,033 individuals Other admixed ancestry UKB
PSS000357 6,358 individuals South Asian UKB
PSS000358 UPDRS motor severity was estimated as a mean value acrosseach patient’s recordings, relative to the rest of the data
[
  • 336 cases
  • , 0 controls
]
,
66.0 % Male samples
European NR Testing dataset genotyped as part of a larger study of a total of 1380 patients with idiopathic PD and 1295 control subjects by 5 collaborating groups in Norway and Sweden. (https://www.sciencedirect.com/science/article/abs/pii/S0197458012005301?showall%3Dtrue%26via%3Dihub)
PSS000359 Defined intrinsic-like breast cancer subtypes based on tumor status of ER, PR, HER2 and grade: (4) HER2-enriched-like (ER- and PR-, HER2+)
[
  • 718 cases
  • , 20,815 controls
]
,
0.0 % Male samples
European 6 cohorts
  • BCAC
  • ,MMHS
  • ,PLCO
  • ,SISTER
  • ,UKBGS
  • ,pKARMA
Heldout subset (20%) of the BCAC consortium data
PSS000360 Defined intrinsic-like breast cancer subtypes based on tumor status of ER, PR, HER2 and grade: (1) luminal A-like (ER+ and/or PR+, HER2-, grade 1 & 2); 
[
  • 7,325 cases
  • , 20,815 controls
]
,
0.0 % Male samples
European 6 cohorts
  • BCAC
  • ,MMHS
  • ,PLCO
  • ,SISTER
  • ,UKBGS
  • ,pKARMA
Heldout subset (20%) of the BCAC consortium data
PSS000361 Defined intrinsic-like breast cancer subtypes based on tumor status of ER, PR, HER2 and grade: (2) luminal B/HER2-negative-like (ER+ and/or PR+, HER2-, grade 3)
[
  • 1,779 cases
  • , 20,815 controls
]
,
0.0 % Male samples
European 6 cohorts
  • BCAC
  • ,MMHS
  • ,PLCO
  • ,SISTER
  • ,UKBGS
  • ,pKARMA
Heldout subset (20%) of the BCAC consortium data
PSS000362 Defined intrinsic-like breast cancer subtypes based on tumor status of ER, PR, HER2 and grade: (3) luminal B-like (ER+ and/or PR+, HER2+); 
[
  • 1,682 cases
  • , 20,815 controls
]
,
0.0 % Male samples
European 6 cohorts
  • BCAC
  • ,MMHS
  • ,PLCO
  • ,SISTER
  • ,UKBGS
  • ,pKARMA
Heldout subset (20%) of the BCAC consortium data
PSS000363 Defined intrinsic-like breast cancer subtypes based on tumor status of ER, PR, HER2 and grade: (5) triple-negative ( ER-, PR-, HER2-). 
[
  • 2,006 cases
  • , 20,815 controls
]
,
0.0 % Male samples
European 6 cohorts
  • BCAC
  • ,MMHS
  • ,PLCO
  • ,SISTER
  • ,UKBGS
  • ,pKARMA
Heldout subset (20%) of the BCAC consortium data
PSS000364 4,678 individuals European
(Swedish)
MDC
PSS000365 Case-control study of first-onset acute myocardial infarction
[
  • 247 cases
]
,
90.7 % Male samples
South Asian BRAVE
PSS000365 Case-control study of first-onset acute myocardial infarction 244 individuals,
90.2 % Male samples
South Asian BRAVE
PSS000366 Cases composed of men and women diagnosed with coronary artery disease. Controls were selected from consenting men and women without any form of heart disease.
[
  • 1,800 cases
]
,
90.2 % Male samples
South Asian MedGenome
PSS000366 Cases composed of men and women diagnosed with coronary artery disease. Controls were selected from consenting men and women without any form of heart disease. 1,163 individuals,
76.4 % Male samples
South Asian MedGenome
PSS000367 Ascertainment of coronary artery disease was based on self-report or hospital admission diagnosis. This included individuals with ICD-9 codes of 410.X, 411.0, 412.X, or 429.79, or ICD-10 codes of I21.X, I22.X, I23.X, I24.1, or I25.2 in hospitalization records. Coronary revascularization was assessed based on an OPCS-4 coded procedure for coronary artery bypass grafting (K40.1–40.4, K41.1–41.4, or K45.1–45.5), or coronary angioplasty with or without stenting (K49.1–49.2, K49.8–49.9, K50.2, K75.1–75.4, or K75.8–75.9).
[
  • 398 cases
]
,
86.7 % Male samples
South Asian UKB
PSS000367 Ascertainment of coronary artery disease was based on self-report or hospital admission diagnosis. This included individuals with ICD-9 codes of 410.X, 411.0, 412.X, or 429.79, or ICD-10 codes of I21.X, I22.X, I23.X, I24.1, or I25.2 in hospitalization records. Coronary revascularization was assessed based on an OPCS-4 coded procedure for coronary artery bypass grafting (K40.1–40.4, K41.1–41.4, or K45.1–45.5), or coronary angioplasty with or without stenting (K49.1–49.2, K49.8–49.9, K50.2, K75.1–75.4, or K75.8–75.9). 6,846 individuals,
52.1 % Male samples
South Asian UKB
PSS000368 TEDDY children were followed prospectively from 3–4 months of age, with visits every 3 months until 4 years of age. Each evaluation tested the three islet antibodies (GADA, IA2A and IAA), changes in family history, as well as other measurements specified by the TEDDY protocol. After 4 years of age, children with any islet autoantibodies remained on quarterly visits, while antibody-negative children were evaluated every 6 months. Children were followed prospectively until 15 years of age or until T1D onset, as defined using the American Diabetes Association’s criteria for diagnosis (doi: 10.1196/annals.1447.062)
[
  • 305 cases
  • , 7,493 controls
]
,
50.86 % Male samples
NR TEDDY From 2004–2010, 424,788 newborns were screened at six US and European centers for high-risk HLA genotypes. TEDDY then enrolled 8,676 eligible infants with the intent to follow them until 15 years of age. The three major eligible HLA DR–DQ haplotypes are DR3–DQA1*0501–DQB1*0201, DR4–DQA1*0301–DQB1*0302 and DR8–DQA1*0401–DQB1*0402.
PSS000369 Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 334 individuals,
69.2 % Male samples
European TRAILS, TRAILSCC TRAILS Clinical Cohort
PSS000370 Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 329 individuals,
69.2 % Male samples
European TRAILS, TRAILSCC TRAILS Clinical Cohort
PSS000371 Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 288 individuals,
69.2 % Male samples
European TRAILS, TRAILSCC TRAILS Clinical Cohort
PSS000372 Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 265 individuals,
69.2 % Male samples
European TRAILS, TRAILSCC TRAILS Clinical Cohort
PSS000373 Individuals who have been referred to a child psychiatric outpatient clinic in the Northern Netherlands before the age of 11. We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 245 individuals,
69.2 % Male samples
European TRAILS, TRAILSCC TRAILS Clinical Cohort
PSS000374 We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 1,318 individuals,
47.6 % Male samples
European TRAILS
PSS000375 We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 1,313 individuals,
47.6 % Male samples
European TRAILS
PSS000376 We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 1,354 individuals,
47.56 % Male samples
European TRAILS
PSS000377 We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 1,174 individuals,
47.6 % Male samples
European TRAILS
PSS000378 We measured weight and height using regularly calibrated equipment (scales and stadiometer models 770 and 214, respectively; Seca, Hamburg, Germany). Body mass index (BMI; in kg/m2) was also calculated. We measured waist circumference at the midpoint between the lower costal margin and the iliac crest. The hip circumference was measured over both trochanter majores (tangible bone on the outside of the hip joint). Waist to hip ratio was also calculated. We performed all measurements in duplicate, and, if the difference between these measurements exceeded a predefined value, a third measurement was performed. All available measurements were used to calculate means. Heart rate, systolic (SBP) and diastolic (DBP) blood pressure were measured in duplicate with a Dinamap Critikon 1846SX (Critikon Inc, Tampa, FL), from which we calculated means. At the third visit, fasting blood sample of participants were drawn for the measurement of glucose (Roche Diagnostics, Basel, Switzerland), insulin (Diagnostic Systems Laboratories Inc, Webster, TX), HbA1c (high performance liquid chromatography, Variant, Bio-Rad), triglycerides, total cholesterol, HDL cholesterol (Roche Diagnostics) and LDL cholesterol (calculated according to Friedewald’s equation5), as well as alanine transaminase (Photometric determination according to the reference method of the International Federation of Clinical Chemistry (IFCC)6) and lipoprotein(a) (Nephelometric method, BN2, DadeBehring). Serum creatinine was measured by photometric determination with the Jaffé method without deproteinisation (Ecoline® MEGA, DiaSys Diagnostic Systems GmbH. Merck). eGFR for adolescents who were younger than 18 years old was calculated using the Schwartz formula.7 High‐sensitivity C‐reactive protein (hsCRP) was determined using an immunonephelometric method, BN2 (CardioPhase hsCRP, Siemens) with a lower detection limit of 0.175 mg/L. Total IgE measurements were performed using the Phadia Immunocap 100 system with fluoroenzyme immunoassay (FEIA). 1,095 individuals,
47.6 % Male samples
European TRAILS
PSS000381 Diagnosis of coeliac disease was made by a modification of European serological diagnostic guidelines for patients referred to a tertiary paediatric clinic in Alberta, Canada, for consideration of coeliac disease diagnosis
[
  • 63 cases
  • , 0 controls
]
,
63.0 % Male samples
NR STOLLERY_CC
PSS000381 Control subjects (n = 40) were paediatric general gastroenterology patients whom were negative for coeliac disease by both intestinal biopsy and negative tissue transglutaminase serology.
[
  • 0 cases
  • , 40 controls
]
,
48.0 % Male samples
NR STOLLERY_CC
PSS000381 Diagnosis of coeliac disease was made by endoscopy for patients referred to a tertiary paediatric clinic in Alberta, Canada, for consideration of coeliac disease diagnosis
[
  • 51 cases
  • , 0 controls
]
,
57.0 % Male samples
NR STOLLERY_CC
PSS000382 Coeliac disease cases were identified using either hospital admission code and/or self‐reported coeliac disease.
[
  • 1,237 cases
  • , 378,530 controls
]
European UKB
PSS000383 Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings
[
  • 1,350 cases
  • , 146,635 controls
]
European, African unspecified, NR 98.3% White European, 1.7% Black/Other UKB PCE Prospective Cohort (lipid-lowering treatment performed)
PSS000384 Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings
[
  • 10,899 cases
  • , 137,086 controls
]
European, African unspecified, NR 98.3% White European, 1.7% Black/Other UKB PCE Prospective Cohort (lipid-lowering treatment performed)
PSS000385 Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings
[
  • 1,339 cases
  • , 145,771 controls
]
European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry UKB QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed)
PSS000386 Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings
[
  • 2,826 cases
  • , 144,284 controls
]
European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry UKB QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed)
PSS000387 Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings
[
  • 4,922 cases
  • , 199,753 controls
]
European, African unspecified, NR 98.3% White European, 1.7% Black/Other UKB PCE Prospective Cohort (lipid-lowering treatment performed)
PSS000388 Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings
[
  • 2,854 cases
  • , 201,821 controls
]
European, African unspecified, NR 98.3% White European, 1.7% Black/Other UKB PCE Prospective Cohort (lipid-lowering treatment performed)
PSS000389 Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings
[
  • 4,900 cases
  • , 198,720 controls
]
European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry UKB QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed)
PSS000390 Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings
[
  • 10,824 cases
  • , 192,796 controls
]
European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry UKB QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed)
PSS000391 Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings
[
  • 4,493 cases
  • , 142,870 controls
]
,
100.0 % Male samples
European, African unspecified, NR 98.3% White European, 1.7% Black/Other UKB PCE Prospective Cohort (lipid-lowering treatment performed)
PSS000392 Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings
[
  • 8,595 cases
  • , 138,768 controls
]
,
100.0 % Male samples
European, African unspecified, NR 98.3% White European, 1.7% Black/Other UKB PCE Prospective Cohort (lipid-lowering treatment performed)
PSS000393 Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings
[
  • 4,471 cases
  • , 142,102 controls
]
,
100.0 % Male samples
European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry UKB QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed)
PSS000394 Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings
[
  • 8,536 cases
  • , 138,037 controls
]
,
100.0 % Male samples
European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry UKB QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed)
PSS000395 Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings
[
  • 1,779 cases
  • , 203,518 controls
]
,
0.0 % Male samples
European, African unspecified, NR 98.3% White European, 1.7% Black/Other UKB PCE Prospective Cohort (lipid-lowering treatment performed)
PSS000396 Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings
[
  • 5,158 cases
  • , 200,139 controls
]
,
0.0 % Male samples
European, African unspecified, NR 98.3% White European, 1.7% Black/Other UKB PCE Prospective Cohort (lipid-lowering treatment performed)
PSS000397 Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings
[
  • 1,768 cases
  • , 202,389 controls
]
,
0.0 % Male samples
European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry UKB QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed)
PSS000398 Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings
[
  • 5,114 cases
  • , 199,043 controls
]
,
0.0 % Male samples
European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry UKB QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed)
PSS000399 Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings
[
  • 6,272 cases
  • , 346,388 controls
]
,
41.8 % Male samples
European, African unspecified, NR 98.3% White European, 1.7% Black/Other UKB PCE Prospective Cohort (lipid-lowering treatment performed)
PSS000400 Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings
[
  • 13,753 cases
  • , 338,907 controls
]
,
41.8 % Male samples
European, African unspecified, NR 98.3% White European, 1.7% Black/Other UKB PCE Prospective Cohort (lipid-lowering treatment performed)
PSS000401 Coronary artery disease was defined as myocardial infarction and its related sequelae (coronary angioplasty, and coronary artery bypass grafts). ICD-10 codes: I21, I22, I23, I24.1, I25.2 ICD-9 codes: 410, 411, 412, 429.79 OPCS-4 codes: K40.1-4, K41.1-4, K45.1-5, K49.1-2, K49.8-9, K50.2, K75.1-4, K54.8-9 UKBiobank field 20002 code: 1075 UKBiobank field 20004 codes: 1070, 1095 UKBiobank field 6150 code: 1 See eTable 1 for risk factor codings
[
  • 6,239 cases
  • , 344,491 controls
]
,
41.0 % Male samples
European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry UKB QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed)
PSS000402 Cardiovascular disease was defined as coronary artery disease, and additionally includes angina, nonhemorrhagic stroke, and transient ischemic attack. ICD-10 codes: G45, I20, I21, I22, I23, I24.1, I25, I63. I64 ICD-9 codes: 410, 411, 412, 413, 414, 434, 436 OPCS-4 codes: K40, K41, K42, K43, K44, K45, K46, K47.1, K49, K50, K75 UKBiobank field 20002 codes: 1074, 1075, 1082, 1548 UKBiobank field 20004 codes: 1070, 1071, 1095, 1105, 1109, 1514 UKBiobank field 6150 codes: 1, 2, 3 See eTable 1 for risk factor codings
[
  • 13,650 cases
  • , 337,080 controls
]
,
41.0 % Male samples
European, South Asian, African American or Afro-Caribbean, African unspecified, East Asian, Asian unspecified 2,332 Africans, 145 Bangladeshi, 3,165 Carribeans, 1,136 Chinese, 3,790 Indians, 1,258 Other Asians, 1,182 Pakistani, 332,326 White Europeans and Unkown ancestry UKB QRISK3 Prospective Cohort/Testing Set (lipid-lowering treatment performed)
PSS000406 Women with invasive breast cancer were considered cases and those without breast cancer were considered controls.
[
  • 4,658 cases
  • , 7,622 controls
]
,
0.0 % Male samples
Hispanic or Latin American 7 cohorts
  • CAMA
  • ,COLUMBUS
  • ,MEC
  • ,NC-BCFR
  • ,PEGEN-BC
  • ,RPEGH
  • ,SFBCS
See supplement for cohort-specific participant recruitment/ascertainment
PSS000407 Women with invasive breast cancer were considered cases and those without breast cancer were considered controls.
[
  • 2,962 cases
  • , 2,001 controls
]
,
0.0 % Male samples
Hispanic or Latin American CAMA, COLUMBUS, PEGEN-BC See supplement for cohort-specific participant recruitment/ascertainment
PSS000408 Women with invasive breast cancer were considered cases and those without breast cancer were considered controls.
[
  • 1,696 cases
  • , 5,621 controls
]
,
0.0 % Male samples
Hispanic or Latin American MEC, NC-BCFR, RPEGH, SFBCS See supplement for cohort-specific participant recruitment/ascertainment
PSS000409 The death registry data were available through November 30, 2016, for the centers in Scotland and January 31, 2018, for the centers in England and Wales. We determined whether an individual died of a particular disease by considering the ICD-10 code listed as the primary cause of death
[
  • 1,720 cases
  • , 58,588 controls
]
,
0.0 % Male samples
European UKB
PSS000410 The death registry data were available through November 30, 2016, for the centers in Scotland and January 31, 2018, for the centers in England and Wales. We determined whether an individual died of a particular disease by considering the ICD-10 code listed as the primary cause of death
[
  • 2,784 cases
  • , 49,290 controls
]
,
100.0 % Male samples
European UKB
PSS000411 59 MC4R mutations that had previously been reported to play a role in obesity were included in our analyses (Table S2) All phenotypic data used for analyses were collected at the baseline visit. We provide a brief description here; more details can be found in S1 Text and elsewhere [18–21]. BMI, calculated as weight (kg) divided by height squared (m2), was used to categorize individuals with underweight (BMI < 18.5 kg/m2), normal weight (18.5 kg/m2 ≤ BMI < 25 kg/m2), overweight (25 kg/m2 ≤ BMI < 30 kg/m2), or obesity (BMI ≥ 30 kg/m2).
[
  • 76 cases
  • , 28 controls
]
European UKB
PSS000412 59 MC4R mutations that had previously been reported to play a role in obesity were included in our analyses (Table S2) All phenotypic data used for analyses were collected at the baseline visit. We provide a brief description here; more details can be found in S1 Text and elsewhere [18–21]. BMI, calculated as weight (kg) divided by height squared (m2), was used to categorize individuals with underweight (BMI < 18.5 kg/m2), normal weight (18.5 kg/m2 ≤ BMI < 25 kg/m2), overweight (25 kg/m2 ≤ BMI < 30 kg/m2), or obesity (BMI ≥ 30 kg/m2).
[
  • 109,216 cases
  • , 147,554 controls
]
European UKB
PSS000413 All phenotypic data used for analyses were collected at the baseline visit. We provide a brief description here; more details can be found in S1 Text and elsewhere [18–21]. BMI, calculated as weight (kg) divided by height squared (m2), was used to categorize individuals with underweight (BMI < 18.5 kg/m2), normal weight (18.5 kg/m2 ≤ BMI < 25 kg/m2), overweight (25 kg/m2 ≤ BMI < 30 kg/m2), or obesity (BMI ≥ 30 kg/m2). 206,612 individuals,
100.0 % Male samples
European UKB
PSS000413 All phenotypic data used for analyses were collected at the baseline visit. We provide a brief description here; more details can be found in S1 Text and elsewhere [18–21]. BMI, calculated as weight (kg) divided by height squared (m2), was used to categorize individuals with underweight (BMI < 18.5 kg/m2), normal weight (18.5 kg/m2 ≤ BMI < 25 kg/m2), overweight (25 kg/m2 ≤ BMI < 30 kg/m2), or obesity (BMI ≥ 30 kg/m2). 244,896 individuals,
0.0 % Male samples
European UKB
PSS000421 Blood testosterone levels (UKB field 30850). Individuals taking the following testosterone-related drugs (methyltestosterone, finasteride, dutasteride, testosterone, mesterolone, and cyproterone) were excluded. 28,640 individuals,
0.0 % Male samples
European UKB
PSS000422 Blood testosterone levels (UKB field 30850). Individuals taking the following testosterone-related drugs (methyltestosterone, finasteride, dutasteride, testosterone, mesterolone, and cyproterone) were excluded. 28,601 individuals,
100.0 % Male samples
European UKB
PSS000429 JIA diagnosis was made according to International League of Associations for Rheumatology standards (PMID:14760812) from EHR. Control subjects were unrelated and disease-free children.
[
  • 66 cases
  • , 2,954 controls
]
,
51.46 % Male samples
European CHOP
PSS000430 JIA diagnosis was made according to International League of Associations for Rheumatology standards (PMID:14760812) from EHR. Control subjects were unrelated and disease-free children.
[
  • 203 cases
  • , 2,954 controls
]
,
49.19 % Male samples
European CHOP
PSS000431 JIA diagnosis was made according to International League of Associations for Rheumatology standards (PMID:14760812) from EHR. Control subjects were unrelated and disease-free children.
[
  • 135 cases
  • , 2,954 controls
]
,
50.11 % Male samples
European CHOP
PSS000432 Diagnosis of JIA by a paediatric rheumatologist.
[
  • 16 cases
  • , 578 controls
]
,
58.59 % Male samples
European CLARITY Cohort description (PMID): 23153063
PSS000433 Diagnosis of JIA by a paediatric rheumatologist.
[
  • 159 cases
  • , 578 controls
]
,
51.15 % Male samples
European CLARITY Cohort description (PMID): 23153063
PSS000434 Diagnosis of JIA by a paediatric rheumatologist.
[
  • 75 cases
  • , 578 controls
]
,
54.82 % Male samples
European CLARITY Cohort description (PMID): 23153063
PSS000435 Cases were selected from the iPSYCH sample as those diagnosed with ASD in 2013 or earlier by a psychiatrist according to ICD10, including diagnoses of childhood autism (ICD10 code F84.0), atypical autism (F84.1), Asperger’s syndrome (F84.5), other pervasive developmental disorders (F84.8), and pervasive developmental disorder, unspecified (F84.9). As controls we selected from the random iPSYCH control cohort children that did not have an ASD diagnosis by 2013.
[
  • 2,615 cases
  • , 4,532 controls
]
European iPSYCH Average case/control numbers of each fold used in cross-validation (1/5th of total iPSYCH).
PSS000436 The discovery cohort included 1001 patients from the University clinics in Uppsala, Linköping, Karolinska Institute (Stockholm), Lund, and from the four northern-most counties in Sweden. All subjects fulfilled ≥4 ACR-82 classification criteria for SLE and were of European descent.30 Clinical data were collected from the patients’ medical files, including SDI scores, the ACR-82 classification criteria, clinical antiphospholipid syndrome (APS) diagnosis, glomerular filtration rate, chronic kidney disease (CKD) stages, ESRD, renal biopsy data and CVE, defined as myocardial infarction, ischaemic cerebrovascular disease or venous thromboembolism (VTE). Control individuals were healthy blood donors from Uppsala (Uppsala Bioresource) and Lund or population based controls from Stockholm and the four northernmost counties of Sweden.
[
  • 1,001 cases
  • , 2,802 controls
]
European Karolinska, UHU The discovery cohort included 1001 patients from the University clinics in Uppsala, Linköping, Karolinska Institute (Stockholm), Lund, and from the four northern-most counties in Sweden
PSS000437 The discovery cohort included 1001 patients from the University clinics in Uppsala, Linköping, Karolinska Institute (Stockholm), Lund, and from the four northern-most counties in Sweden. All subjects fulfilled ≥4 ACR-82 classification criteria for SLE and were of European descent.30 Clinical data were collected from the patients’ medical files, including SDI scores, the ACR-82 classification criteria, clinical antiphospholipid syndrome (APS) diagnosis, glomerular filtration rate, chronic kidney disease (CKD) stages, ESRD, renal biopsy data and CVE, defined as myocardial infarction, ischaemic cerebrovascular disease or venous thromboembolism (VTE).
[
  • 1,001 cases
  • , 0 controls
]
European Karolinska, UHU The discovery cohort included 1001 patients from the University clinics in Uppsala, Linköping, Karolinska Institute (Stockholm), Lund, and from the four northern-most counties in Sweden
PSS000438
[
  • 5,524 cases
  • , 9,859 controls
]
European NR The replication cohort is described in Langefeld et al. (PMID:28714469)
PSS000439 National registries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2018, whichever came first. Disease endpoints are defined in Table S9.
[
  • 229 cases
  • , 10,332 controls
]
,
47.3 % Male samples
European
(Finnish)
FINRISK FINRISK surveys from 1992, 1997, 2002 and 2007
PSS000440 Coronary heart disease was defined as Myocardial infarction|Myocardial infarction, strict|Complications following myocardial infarction|Prior myocardial infactrion|Angina pectoris|Other coronary atherosclerosis|Coronary artery bypass graft**|Coronary angioplasty**. ICD9/10 codes are listed in Table S9. National registries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2018, whichever came first.
[
  • 1,209 cases
  • , 18,956 controls
]
,
47.3 % Male samples
European
(Finnish)
FINRISK FINRISK surveys from 1992, 1997, 2002 and 2007
PSS000441 National registries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2018, whichever came first. Disease endpoints are defined in Table S9.
[
  • 1,346 cases
  • , 19,684 controls
]
,
47.3 % Male samples
European
(Finnish)
FINRISK FINRISK surveys from 1992, 1997, 2002 and 2007
PSS000442 National registries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2018, whichever came first. Disease endpoints are defined in Table S9.
[
  • 12,809 cases
  • , 122,491 controls
]
,
43.7 % Male samples
European
(Finnish)
FinnGen
PSS000443 National registries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2018, whichever came first. Disease endpoints are defined in Table S9.
[
  • 4,960 cases
  • , 71,213 controls
]
,
0.0 % Male samples
European
(Finnish)
FinnGen
PSS000444 National registries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2018, whichever came first. Disease endpoints are defined in Table S9.
[
  • 742 cases
  • , 37,099 controls
]
European
(Finnish)
FinnGen
PSS000445 Coronary heart disease was defined as Myocardial infarction|Myocardial infarction, strict|Complications following myocardial infarction|Prior myocardial infactrion|Angina pectoris|Other coronary atherosclerosis|Coronary artery bypass graft**|Coronary angioplasty**. ICD9/10 codes are listed in Table S9. National registries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2018, whichever came first.
[
  • 20,179 cases
  • , 115,121 controls
]
,
43.7 % Male samples
European
(Finnish)
FinnGen
PSS000446 National registries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2018, whichever came first. Disease endpoints are defined in Table S9.
[
  • 3,617 cases
  • , 55,509 controls
]
,
100.0 % Male samples
European
(Finnish)
FinnGen
PSS000447 National registries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2018, whichever came first. Disease endpoints are defined in Table S9.
[
  • 1,172 cases
  • , 47,679 controls
]
European
(Finnish)
FinnGen
PSS000448 National registries were used to assess disease incidence. Follow-up ended at first-ever diagnosis of the disease of interest, death or at the end of follow-up on December 31, 2018, whichever came first. Disease endpoints are defined in Table S9.
[
  • 17,519 cases
  • , 117,781 controls
]
,
43.7 % Male samples
European
(Finnish)
FinnGen
PSS000449
[
  • 383 cases
  • , 1,915 controls
]
,
47.0 % Male samples
European UKB
PSS000449
[
  • 77 cases
  • , 588 controls
]
,
44.4 % Male samples
European MAS
PSS000449
[
  • 216 cases
  • , 631 controls
]
,
54.7 % Male samples
European ABIL
PSS000450 Breast cancer cases were identified through the Finnish Cancer Registry with diagnosis C50 (International Classification of Diseases for Oncology, 3rd Edition; ICD-O-3), from the drug reimbursement registry by selecting individuals with a reimbursement code for breast cancer, and from the death registry with ICD-10 C50.
[
  • 8,401 cases
  • , 114,577 controls
]
,
0.0 % Male samples
European
(Finnish)
FinnGen
PSS000451 Chronotype was assessed using a singl self-evaluatation question from a shortend version of Horne and Ostber'gs MEQ (sMEQ) on chronotype. The sMEQ included 6 items (items 4,7,9,15,17 and 19) from the original MEQ. The answers were scored according to the scoring of the original MEQ. For the single self-evaluation question item 19 was used. The question was used as a binary varable in which those who replied either "rather more an evening than a morning type" or "definitely an evening type" were regarded as evening types, and those who replied "definitely a morning type" or "rather more a morning type than an evening type" were regarrded as morning types.
[
  • 4,674 cases
  • , 3,759 controls
]
,
47.78 % Male samples
European
(Finnish)
FINRISK Included participants from the National FINRISK 2007 and 2012 studies
PSS000452 Chronotype was assessed using a shortend version of Horne and Ostberg's MEQ(sMEQ) . The sMEQ included 6 items (items 4,7,9,15,17 and 19) from the original MEQ. The answers were scored according to the scoring of the original MEQ. The sum score was used as a binary variable (evening type: socres from 5-15, morning type: socres from 16 to 27; binary sMEQ score).
[
  • 2,364 cases
  • , 5,072 controls
]
,
46.4 % Male samples
European
(Finnish)
FINRISK Included participants from the National FINRISK 2007 and 2012 studies
PSS000453 Chronotype was assessed using a shortend version of Horne and Ostberg's MEQ(sMEQ) The sMEQ included 6 items (items 4,7,9,15,17 and 19) from the original MEQ. The answers were scored according to the scoring of the original MEQ. The sum score was used as a continuous variable (continuous sMEQ score). 7,436 individuals European
(Finnish)
FINRISK Included participants from the National FINRISK 2007 and 2012 studies
PSS000454 Cause of death under ICD-10 code
[
  • 9,816 cases
  • , 39,414 controls
]
East Asian
(Japanese)
BBJ
PSS000455 Cause of death under ICD-10.CHF code
[
  • 362 cases
  • , 48,868 controls
]
East Asian
(Japanese)
BBJ
PSS000456 Cause of death under ICD-10.I codes
[
  • 2,122 cases
  • , 47,108 controls
]
East Asian
(Japanese)
BBJ
PSS000457 Cause of death under ICD-10.IHD code
[
  • 464 cases
  • , 48,766 controls
]
East Asian
(Japanese)
BBJ
PSS000458 Cause of death under ICD-10.J codes
[
  • 1,193 cases
  • , 48,037 controls
]
East Asian
(Japanese)
BBJ
PSS000459 CAD was defined as a composite of stable angina, unstable angina and myocardial infarction. The disease definitions are dependent on the physician's diagnosis based on general medical practices following relevant guidelines and according to the clinical symptoms and diagnotic tests.
[
  • 1,827 cases
  • , 9,172 controls
]
,
84.0 % Male samples
East Asian
(Japanese)
BBJ
PSS000460 Atrial fibrillation was defined as a clinical history of AF or atrial flutter (AFL) and/or AF(L) on baseline electrocardiogram. Patients were regarded as having sinus rhythm if they had no history of AF and sinus rhythm on baseline ECG. HFpEF defined as LVEF >/= 50%
[
  • 307 cases
  • , 223 controls
]
European BIOSTAT-CHF BIOSTAT-CHF study included patients from 11 European countries. Patients from Scotland were included in the vaidation cohort between October 2010 and April 2014
PSS000461 Atrial fibrillation was defined as a clinical history of AF or atrial flutter (AFL) and/or AF(L) on baseline electrocardiogram. Patients were regarded as having sinus rhythm if they had no history of AF and sinus rhythm on baseline ECG.HFrEF defined as LVEF <40%
[
  • 1,125 cases
  • , 1,137 controls
]
European BIOSTAT-CHF BIOSTAT-CHF study included patients from 11 European countries. Patients from Scotland were included in the vaidation cohort between October 2010 and April 2014
PSS000462 Atrial fibrillation was defined as a clinical history of AF or atrial flutter (AFL) and/or AF(L) on baseline electrocardiogram. Patients were regarded as having sinus rhythm if they had no history of AF and sinus rhythm on baseline ECG.
[
  • 1,976 cases
  • , 1,783 controls
]
,
70.0 % Male samples
European BIOSTAT-CHF BIOSTAT-CHF study included patients from 11 European countries. Patients from Scotland were included in the vaidation cohort between October 2010 and April 2014
PSS000463 Unaffected family members from families with increased melaona risk. Recruited families were ranked as low-, medium- or high-risk using a risk index (T) that factored in the number of confirmed cases of melanoma versus number of unaffected family members, ages and year of birth
[
  • 1,292 cases
  • , 1,774 controls
]
,
46.28 % Male samples
European Australia BATS, QFMP
PSS000464 Unaffected family members from families with increased melaona risk. Recruited families were ranked as low-, medium- or high-risk using a risk index (T) that factored in the number of confirmed cases of melanoma versus number of unaffected family members, ages and year of birth
[
  • 111 cases
  • , 1,774 controls
]
,
46.37 % Male samples
European Australia BATS, QFMP
PSS000465 Individuals ≥18 years with clinically diagnosed heterozygous familial hypercholesterolemia (FH) from the BCFH cohort. Individuals who were positive for the common French Canadian variant in the LDLR gene including del.15 kb of the promoter and exon 1, del.5 kb of exons 2 and 3, p.W66G (exon 3), p.E207K (exon 4), p.Y468X (exon 10), or p.C646Y (exon 14) in this study. Fasting clinical lipid profiles were obtained following a 4-week washout of any cholesterol-lowering medications from the CNMA cohort. Individuals who were positive for a LDLR, APOB, or PCSK9 variant that was deemed to cause FH in the UKB cohort.Any atherosclerotic cardiovascular disease (ASCVD) event, which was defined as myocardial infarction, coronary artery disease or carotid revascularization, transient ischemic attack or stroke. For the UK Biobank, retrospecitvie ASCVD was self reported and prospective ASCVD were defined using hospital episode statistics and 10th revision of the International Statistical Classification of Diseases and Related Health Problems diagnosis codes and OPCS Classification of Interventions and Procedures version 4 procedure codes 1,120 individuals,
40.4 % Male samples
European, NR European (94%), Not reported (6%) BCFH, CNMA, UKB
PSS000466 Any atherosclerotic cardiovascular disease (ASCVD) event, which was defined as myocardial infarction, coronary artery disease or carotid revascularization, transient ischemic attack or stroke. For the UK Biobank, retrospecitvie ASCVD was self reported and prospective ASCVD were defined using hospital episode statistics and 10th revision of the International Statistical Classification of Diseases and Related Health Problems diagnosis codes and OPCS Classification of Interventions and Procedures version 4 procedure codes 389,127 individuals European UKB
PSS000467 Individuals were free of CAD at time of enrollment. CAD was defined as (1)fatal or nonfatal myocardial infarction: defined based on either International Classification of Diseases, Ninth Revision (ICD-9) code 410 or Tenth Revision (ICD-10) code I21, (2)coronary artery bypass graft surgery: defined as procedure codes 3065, 3066, 3068, 3080, 3092, 3105, 3127 or 3158 (the Op6 system) or procedure code FN (the KKA97 system), (3)percutaneous coronary intervention, (4)death due to CAD: defined as ICD-9 codes 412 and 414 or ICD-10 codes I22, I23 and I25.
[
  • 4,122 cases
  • , 24,434 controls
]
,
38.7 % Male samples
European, NR European=28286, NR=270 MDC
PSS000468 Individuals were free of CAD at time of enrollment. CAD was defined as (1)fatal or nonfatal myocardial infarction: defined based on either International Classification of Diseases, Ninth Revision (ICD-9) code 410 or Tenth Revision (ICD-10) code I21, (2)coronary artery bypass graft surgery: defined as procedure codes 3065, 3066, 3068, 3080, 3092, 3105, 3127 or 3158 (the Op6 system) or procedure code FN (the KKA97 system), (3)percutaneous coronary intervention, (4)death due to CAD: defined as ICD-9 codes 412 and 414 or ICD-10 codes I22, I23 and I25. All individuals included had measured cholesterol concentrations.
[
  • 815 cases
  • , 4,870 controls
]
,
41.16 % Male samples
European, NR European=5640, NR=45 MDC-CC Cardiovascular Cohort
PSS000469 Individuals were free of CAD at time of enrollment. CAD was defined based on hospitalisation with or death due to ICD-10 codes for acute or subsequent myocaridal infarction (I21, I22, I23, I24.1, and I25.2); or hospitalisation with ICD-9 codes for myocaridal. infarction (410, 411, and 412); or hospitalisation with OPCS-4 (Office of Population Censuses and Surveys) codes. for coronary artery bypass grafting (K40, K41, and K45) or coronary angioplasty with or without stenting (K49, K50.2, and K75).
[
  • 7,708 cases
  • , 317,295 controls
]
,
44.2 % Male samples
European, African unspecified, South Asian, East Asian, NR European=304270, African unspecified=5760, South Asian=6832, East Asian (Chinese)=1117, NR=7024 UKB
PSS000480 Women (European Ancestry) diagnosed with unilateral breast cancer
[
  • 12,133 cases
  • , 13,398 controls
]
,
0.0 % Male samples
Asian unspecified 8 cohorts
  • CBCS
  • ,HERPACC
  • ,HKBCS
  • ,MYBRCA
  • ,NC-BCFR
  • ,SEBCS
  • ,SGBCC
  • ,TWBCS
PSS000481 Women (Asian Ancestry) diagnosed with unilateral breast cancer or CBC. CBC was defined as breast cancer (in situ or invasive) in the contralateral breast irrespective of the time since the first breast cancer.
[
  • 340 cases
  • , 12,133 controls
]
,
0.0 % Male samples
Asian unspecified 8 cohorts
  • CBCS
  • ,HERPACC
  • ,HKBCS
  • ,MYBRCA
  • ,NC-BCFR
  • ,SEBCS
  • ,SGBCC
  • ,TWBCS
PSS000482 Women (European Ancestry) diagnosed with unilateral breast cancer or CBC. CBC was defined as breast cancer (in situ or invasive) in the contralateral breast irrespective of the time since the first breast cancer.
[
  • 3,607 cases
  • , 81,000 controls
]
,
0.0 % Male samples
European 63 cohorts
  • ABCFS
  • ,ABCS
  • ,ABCS-F
  • ,ABCTB
  • ,BBCC
  • ,BBCS
  • ,BCEES
  • ,BCFR-NY
  • ,BCFR-PA
  • ,BCFR-UTAH
  • ,BIGGS
  • ,BREOGAN
  • ,BSUCH
  • ,CBCS
  • ,CCGP
  • ,CGPS
  • ,CNIO-BCS
  • ,DIETCOMPLYF
  • ,FHRISK
  • ,GC-HBOC
  • ,GENICA
  • ,GESBC
  • ,GLACIER
  • ,HABCS
  • ,HCSC
  • ,HEBCS
  • ,HMBCS
  • ,HUBCS
  • ,ICICLE
  • ,KARBAC
  • ,KARMA
  • ,KBCP
  • ,KCONFAB/AOCS
  • ,LMBC
  • ,MABCS
  • ,MARIE
  • ,MBCSG
  • ,MCBCS
  • ,MCCS
  • ,MEC
  • ,MISS
  • ,MMHS
  • ,NBCS
  • ,NC-BCFR
  • ,NCBRCS
  • ,OBCS
  • ,OFBCR
  • ,ORIGO
  • ,PBCS
  • ,POSH
  • ,PREFACE
  • ,PROCAS
  • ,RBCS
  • ,SASBAC
  • ,SBCS
  • ,SEARCH
  • ,SKKDKFZS
  • ,SUCCESSB
  • ,SUCCESSC
  • ,SZBCS
  • ,TNBCC
  • ,UCIBCS
  • ,pKARMA
PSS000483 Women (European Ancestry) diagnosed with unilateral breast cancer
[
  • 81,000 cases
  • , 62,830 controls
]
,
0.0 % Male samples
European 63 cohorts
  • ABCFS
  • ,ABCS
  • ,ABCS-F
  • ,ABCTB
  • ,BBCC
  • ,BBCS
  • ,BCEES
  • ,BCFR-NY
  • ,BCFR-PA
  • ,BCFR-UTAH
  • ,BIGGS
  • ,BREOGAN
  • ,BSUCH
  • ,CBCS
  • ,CCGP
  • ,CGPS
  • ,CNIO-BCS
  • ,DIETCOMPLYF
  • ,FHRISK
  • ,GC-HBOC
  • ,GENICA
  • ,GESBC
  • ,GLACIER
  • ,HABCS
  • ,HCSC
  • ,HEBCS
  • ,HMBCS
  • ,HUBCS
  • ,ICICLE
  • ,KARBAC
  • ,KARMA
  • ,KBCP
  • ,KCONFAB/AOCS
  • ,LMBC
  • ,MABCS
  • ,MARIE
  • ,MBCSG
  • ,MCBCS
  • ,MCCS
  • ,MEC
  • ,MISS
  • ,MMHS
  • ,NC-BCFR
  • ,NCBCS
  • ,NorBCS
  • ,OBCS
  • ,OFBCR
  • ,ORIGO
  • ,PBCS
  • ,POSH
  • ,PREFACE
  • ,PROCAS
  • ,RBCS
  • ,SASBAC
  • ,SBCS
  • ,SEARCH
  • ,SKKDKFZS
  • ,SUCCESSB
  • ,SUCCESSC
  • ,SZBCS
  • ,TNBCC
  • ,UCIBCS
  • ,pKARMA
PSS000484 Women (European Ancestry) diagnosed with unilateral breast cancer or metachronous contralateral breast cancer (CBC). Metachronous contralateral breast cancer was defined as breast cancer in the contralateral breast (in situ or invasive) diagnosed at least 3 months after the first breast cancer.
[
  • 1,027 cases
  • , 55,041 controls
]
,
0.0 % Male samples
European 42 cohorts
  • ABCFS
  • ,ABCS
  • ,ABCS-F
  • ,ABCTB
  • ,AOCS
  • ,BBCC
  • ,BCFR-PA
  • ,BIGGS
  • ,BREOGAN
  • ,BSUCH
  • ,CCGP
  • ,CGPS
  • ,GC-HBOC
  • ,GENICA
  • ,HCSC
  • ,HEBCS
  • ,KARBAC
  • ,KARMA
  • ,LMBC
  • ,MABCS
  • ,MARIE
  • ,MBCSG
  • ,MCBCS
  • ,MEC
  • ,MISS
  • ,NBCS
  • ,NC-BCFR
  • ,OBCS
  • ,OFBCR
  • ,ORIGO
  • ,PBCS
  • ,POSH
  • ,PROCAS
  • ,RBCS
  • ,SASBAC
  • ,SBCS
  • ,SEARCH
  • ,SKKDKFZS
  • ,SZBCS
  • ,UCIBCS
  • ,kConFab
  • ,pKARMA
PSS000485 Women (European Ancestry) diagnosed with unilateral breast cancer or metachronous contralateral breast cancer (CBC). Metachronous contralateral breast cancer was defined as breast cancer in the contralateral breast (in situ or invasive) diagnosed at least 3 months after the first breast cancer.
[
  • 275 cases
  • , 55,793 controls
]
,
0.0 % Male samples
European 42 cohorts
  • ABCFS
  • ,ABCS
  • ,ABCS-F
  • ,ABCTB
  • ,AOCS
  • ,BBCC
  • ,BCFR-PA
  • ,BIGGS
  • ,BREOGAN
  • ,BSUCH
  • ,CCGP
  • ,CGPS
  • ,GC-HBOC
  • ,GENICA
  • ,HCSC
  • ,HEBCS
  • ,KARBAC
  • ,KARMA
  • ,LMBC
  • ,MABCS
  • ,MARIE
  • ,MBCSG
  • ,MCBCS
  • ,MEC
  • ,MISS
  • ,NBCS
  • ,NC-BCFR
  • ,OBCS
  • ,OFBCR
  • ,ORIGO
  • ,PBCS
  • ,POSH
  • ,PROCAS
  • ,RBCS
  • ,SASBAC
  • ,SBCS
  • ,SEARCH
  • ,SKKDKFZS
  • ,SZBCS
  • ,UCIBCS
  • ,kConFab
  • ,pKARMA
PSS000486 Women (European Ancestry) diagnosed with unilateral breast cancer or metachronous contralateral breast cancer (CBC). Metachronous contralateral breast cancer was defined as breast cancer in the contralateral breast (in situ or invasive) diagnosed at least 3 months after the first breast cancer.
[
  • 923 cases
  • , 55,145 controls
]
,
0.0 % Male samples
European 42 cohorts
  • ABCFS
  • ,ABCS
  • ,ABCS-F
  • ,ABCTB
  • ,AOCS
  • ,BBCC
  • ,BCFR-PA
  • ,BIGGS
  • ,BREOGAN
  • ,BSUCH
  • ,CCGP
  • ,CGPS
  • ,GC-HBOC
  • ,GENICA
  • ,HCSC
  • ,HEBCS
  • ,KARBAC
  • ,KARMA
  • ,LMBC
  • ,MABCS
  • ,MARIE
  • ,MBCSG
  • ,MCBCS
  • ,MEC
  • ,MISS
  • ,NBCS
  • ,NC-BCFR
  • ,OBCS
  • ,OFBCR
  • ,ORIGO
  • ,PBCS
  • ,POSH
  • ,PROCAS
  • ,RBCS
  • ,SASBAC
  • ,SBCS
  • ,SEARCH
  • ,SKKDKFZS
  • ,SZBCS
  • ,UCIBCS
  • ,kConFab
  • ,pKARMA
PSS000489 The diagnosttic criteria for each disease was based on gold-standard clinical guidelines. 339 individuals European
(Spanish)
PRECISESADS
PSS000490 Cases included physician-confirmed psoriatic arthritis (PsA). Controls inclded individuals with psoriasis with no history of joint symptoms (psoriasis only - PsO).
[
  • 140 cases
  • , 403 controls
]
NR NR
PSS000491
[
  • 15,755 cases
  • , 16,483 controls
]
,
0.0 % Male samples
Asian unspecified 10 cohorts
  • ACP
  • ,HERPACC
  • ,HKBCS
  • ,KOHBRA
  • ,MYBRCA
  • ,NagBCS
  • ,SBCGS
  • ,SEBCS
  • ,SGBCC
  • ,TWBCS
PSS000492
[
  • 10,477 cases
  • , 16,483 controls
]
,
0.0 % Male samples
Asian unspecified 10 cohorts
  • ACP
  • ,HERPACC
  • ,HKBCS
  • ,KOHBRA
  • ,MYBRCA
  • ,NagBCS
  • ,SBCGS
  • ,SEBCS
  • ,SGBCC
  • ,TWBCS
PSS000493
[
  • 4,764 cases
  • , 16,483 controls
]
,
0.0 % Male samples
Asian unspecified 10 cohorts
  • ACP
  • ,HERPACC
  • ,HKBCS
  • ,KOHBRA
  • ,MYBRCA
  • ,NagBCS
  • ,SBCGS
  • ,SEBCS
  • ,SGBCC
  • ,TWBCS
PSS000494
[
  • 580 cases
  • , 1,018 controls
]
,
0.0 % Male samples
South Asian
(Indian)
MYBRCA, SGBCC
PSS000494
[
  • 1,084 cases
  • , 1,332 controls
]
,
0.0 % Male samples
South East Asian
(Malay)
MYBRCA, SGBCC
PSS000494
[
  • 5,236 cases
  • , 5,156 controls
]
,
0.0 % Male samples
East Asian
(Chinese)
MYBRCA, SGBCC
PSS000495
[
  • 1,365 cases
  • , 5,156 controls
]
,
0.0 % Male samples
East Asian
(Chinese)
MYBRCA, SGBCC
PSS000495
[
  • 184 cases
  • , 1,018 controls
]
,
0.0 % Male samples
South Asian
(Indian)
MYBRCA, SGBCC
PSS000495
[
  • 336 cases
  • , 1,332 controls
]
,
0.0 % Male samples
South East Asian
(Malay)
MYBRCA, SGBCC
PSS000496
[
  • 374 cases
  • , 1,018 controls
]
,
0.0 % Male samples
South Asian
(Indian)
MYBRCA, SGBCC
PSS000496
[
  • 715 cases
  • , 1,332 controls
]
,
0.0 % Male samples
South East Asian
(Malay)
MYBRCA, SGBCC
PSS000496
[
  • 3,627 cases
  • , 5,156 controls
]
,
0.0 % Male samples
East Asian
(Chinese)
MYBRCA, SGBCC
PSS000497
[
  • 1,507 cases
  • , 1,212 controls
]
,
0.0 % Male samples
Asian unspecified CanBCS, LAABC, NC-BCFR
PSS000498
[
  • 280 cases
  • , 1,212 controls
]
Asian unspecified CanBCS, LAABC, NC-BCFR
PSS000499
[
  • 1,022 cases
  • , 1,212 controls
]
Asian unspecified CanBCS, LAABC, NC-BCFR
PSS000500
[
  • 413 cases
  • , 9,842 controls
]
,
0.0 % Male samples
East Asian
(Chinese)
SCHS
PSS000501 Cases: Male, self-reported European ancestry, greater or equal to 18 years of age at prostate cancer diagnosis. JHH cases were patients undergoing radical prostatectomy for the treatment of clinically localized PrCa in 2002 to 2015 and were included if disease was organ‐confined and Gleason score ≤6 or ≥8, as determined upon pathological evaluation of the prostatectomy specimen. Only the high‐ and low‐grade PrCa JHH cases were included because they were previously curated to assess the association of RPVs in cancer susceptibility genes with PrCa. JHH controls were included if they self repored with European American ancestry, had a normal digital rectal examination, PSA level less than 4.0 ng/mL and were older than 55 years. AG cases and controls were men referred for multigene panel testing in 2017 to 2019. Among AG cases, 104 patients had Gleason ≥8, and 59 patients had Gleason ≤6, and 230 patients had no pathology information. AG controls were unaffected with prostate cancer at the time of testing. NSGI controls had a minimum of 1 year clincal history available in the EHR and were exlucded if any ICD9/10 diagnosis of cancer was present at any time in the EHR. Men who tested positive for RPVs in any prostate cancer susceptibility gene were exlcuded from further analysis.
[
  • 1,972 cases
  • , 1,919 controls
]
,
100.0 % Male samples
European AG, JHH, NSGHI
PSS000502 Cases: Male, self-reported European ancestry, greater or equal to 18 years of age at prostate cancer diagnosis. JHH cases were patients undergoing radical prostatectomy for the treatment of clinically localized PrCa in 2002 to 2015 and were included if disease was organ‐confined and Gleason score ≤6 or ≥8, as determined upon pathological evaluation of the prostatectomy specimen. Only the high‐ and low‐grade PrCa JHH cases were included because they were previously curated to assess the association of RPVs in cancer susceptibility genes with PrCa. JHH controls were included if they self repored with European American ancestry, had a normal digital rectal examination, PSA level less than 4.0 ng/mL and were older than 55 years. AG cases and controls were men referred for multigene panel testing in 2017 to 2019. Among AG cases, 104 patients had Gleason ≥8, and 59 patients had Gleason ≤6, and 230 patients had no pathology information. AG controls were unaffected with prostate cancer at the time of testing.
[
  • 744 cases
  • , 295 controls
]
,
100.0 % Male samples
European AG, JHH
PSS000503 Cases: Male, self-reported European ancestry, greater or equal to 18 years of age at prostate cancer diagnosis. JHH cases were patients undergoing radical prostatectomy for the treatment of clinically localized PrCa in 2002 to 2015 and were included if disease was organ‐confined and Gleason score ≤6 or ≥8, as determined upon pathological evaluation of the prostatectomy specimen. Only the high‐ and low‐grade PrCa JHH cases were included because they were previously curated to assess the association of RPVs in cancer susceptibility genes with PrCa. JHH controls were included if they self repored with European American ancestry, had a normal digital rectal examination, PSA level less than 4.0 ng/mL and were older than 55 years. AG cases and controls were men referred for multigene panel testing in 2017 to 2019. Among AG cases, 104 patients had Gleason ≥8, and 59 patients had Gleason ≤6, and 230 patients had no pathology information. AG controls were unaffected with prostate cancer at the time of testing.
[
  • 1,133 cases
  • , 1,172 controls
]
,
100.0 % Male samples
European AG, JHH
PSS000504 Participants with no prior Coronary Heart Disease (CHD) at the time of enrollment were included within the present study. Incidental CHD was the primary end-points of the study. CHD was defined as fatal and non-fatal myocardial infarction, stroke and coronary death.
[
  • 343 cases
  • , 3,698 controls
]
,
47.5 % Male samples
European HNR
PSS000505
[
  • 2,734 cases
  • , 1,307 controls
]
European HNR
PSS000506 Male participants with no prior Coronary Heart Disease (CHD) at the time of enrollment were included within the present study. Incidental CHD was the primary end-points of the study. CHD was defined as fatal and non-fatal myocardial infarction, stroke and coronary death.
[
  • 219 cases
  • , 1,700 controls
]
,
100.0 % Male samples
European HNR
PSS000507 Participants with no prior Coronary Heart Disease (CHD) at the time of enrollment were included within the present study. Incidental CHD was the primary end-points of the study. CHD was defined as fatal and non-fatal myocardial infarction, stroke and coronary death. Cardiovascular risk factor data required included smoking status, current use of medication, body mass index, levels of serum triglycerides, low densitity lipoprotein-cholesterol and high densitity lipoprotein-cholesterol and diabetes defined as either of 4 criteria (1) participants reported a history of clinically diagnosed diabetes, (2) participants took glucose-lowering medications, (3) participants had fasting glucose levels of greater than 125mg/dL or (4) participants had non-fasting glucose levels of 200mg/dL or greater.
[
  • 321 cases
  • , 3,427 controls
]
European HNR
PSS000508
[
  • 2,536 cases
  • , 1,212 controls
]
European HNR
PSS000509 Participants with no prior Coronary Heart Disease (CHD) at the time of enrollment with coronary artery calcification>0 were included. Incidental CHD was the primary end-points of the study. CHD was defined as fatal and non-fatal myocardial infarction, stroke and coronary death. Cardiovascular risk factor data required included smoking status, current use of medication, body mass index, levels of serum triglycerides, low densitity lipoprotein-cholesterol and high densitity lipoprotein-cholesterol and diabetes defined as either of 4 criteria (1) participants reported a history of clinically diagnosed diabetes, (2) participants took glucose-lowering medications, (3) participants had fasting glucose levels of greater than 125mg/dL or (4) participants had non-fasting glucose levels of 200mg/dL or greater.
[
  • 278 cases
  • , 2,282 controls
]
European HNR
PSS000510 Male participants with no prior Coronary Heart Disease (CHD) at the time of enrollment were included within the present study. Incidental CHD was the primary end-points of the study. CHD was defined as fatal and non-fatal myocardial infarction, stroke and coronary death. Cardiovascular risk factor data required included smoking status, current use of medication, body mass index, levels of serum triglycerides, low densitity lipoprotein-cholesterol and high densitity lipoprotein-cholesterol and diabetes defined as either of 4 criteria (1) participants reported a history of clinically diagnosed diabetes, (2) participants took glucose-lowering medications, (3) participants had fasting glucose levels of greater than 125mg/dL or (4) participants had non-fasting glucose levels of 200mg/dL or greater.
[
  • 202 cases
  • , 1,563 controls
]
,
100.0 % Male samples
European HNR
PSS000511 Male participants with no prior Coronary Heart Disease (CHD) at the time of enrollment with coronary artery calcification>0 were included. Incidental CHD was the primary end-points of the study. CHD was defined as fatal and non-fatal myocardial infarction, stroke and coronary death. Cardiovascular risk factor data required included smoking status, current use of medication, body mass index, levels of serum triglycerides, low densitity lipoprotein-cholesterol and high densitity lipoprotein-cholesterol and diabetes defined as either of 4 criteria (1) participants reported a history of clinically diagnosed diabetes, (2) participants took glucose-lowering medications, (3) participants had fasting glucose levels of greater than 125mg/dL or (4) participants had non-fasting glucose levels of 200mg/dL or greater.
[
  • 186 cases
  • , 1,240 controls
]
,
100.0 % Male samples
European HNR
PSS000512 A harmonized definition of POAG used the following criteria: (1) open anterior segment angles; (2) reproducible glaucomatous visual field loss on reliable tests; or (3) an eye with cup-disc ratio of at least 0.7 with 1 visual field showing glaucomatous loss; and (4) no identifiable secondary cause for optic nerve disease. 
[
  • 3,108 cases
  • , 3,430 controls
]
,
43.38 % Male samples
European GLAUGEN, NEIGHBOR
PSS000513 A harmonized definition of POAG used the following criteria: (1) open anterior segment angles; (2) reproducible glaucomatous visual field loss on reliable tests; or (3) an eye with cup-disc ratio of at least 0.7 with 1 visual field showing glaucomatous loss; and (4) no identifiable secondary cause for optic nerve disease. 
[
  • 2,947 cases
  • , 0 controls
]
European GLAUGEN, NEIGHBOR
PSS000514 ICD-9 diagnosis code for acute myocardial infarction, other acute/subacute forms of ischemic heart disease, old myocardial infarction, other forms of chronic ischemic heart disease, certain unspecified sequelae of myocardial infarction, coronary bypass, or coronary revascularization (36.1, 36.2, 410, 411, 412, 414, 429.7); ICD-10 diagnosis code for acute myocardial infarction, subsequent myocardial infarction, complications following myocardial infarction, other acute ischemic heart disease, or chronic ischemic heart disease (I21, I22, I23, I24, I25); CPT procedure code for coronary artery bypass, percutaneous transluminal angioplasty/revascularization/thrombectomy, or coronary thrombolysis (3351x, 3353x, 9292x, 9293x, 9294x, 9297x)
[
  • 2,824 cases
  • , 21,547 controls
]
,
42.7 % Male samples
European, Hispanic or Latin American, African unspecified African unspecified=6979, European=10344, Hispanic or Latin American=7048 BioMe
PSS000515 ICD-9 diagnosis code for acute myocardial infarction, other acute/subacute forms of ischemic heart disease, old myocardial infarction, other forms of chronic ischemic heart disease, certain unspecified sequelae of myocardial infarction, coronary bypass, or coronary revascularization (36.1, 36.2, 410, 411, 412, 414, 429.7); ICD-10 diagnosis code for acute myocardial infarction, subsequent myocardial infarction, complications following myocardial infarction, other acute ischemic heart disease, or chronic ischemic heart disease (I21, I22, I23, I24, I25); CPT procedure code for coronary artery bypass, percutaneous transluminal angioplasty/revascularization/thrombectomy, or coronary thrombolysis (3351x, 3353x, 9292x, 9293x, 9294x, 9297x) 6,979 individuals African unspecified BioMe
PSS000516 ICD-9 diagnosis code for acute myocardial infarction, other acute/subacute forms of ischemic heart disease, old myocardial infarction, other forms of chronic ischemic heart disease, certain unspecified sequelae of myocardial infarction, coronary bypass, or coronary revascularization (36.1, 36.2, 410, 411, 412, 414, 429.7); ICD-10 diagnosis code for acute myocardial infarction, subsequent myocardial infarction, complications following myocardial infarction, other acute ischemic heart disease, or chronic ischemic heart disease (I21, I22, I23, I24, I25); CPT procedure code for coronary artery bypass, percutaneous transluminal angioplasty/revascularization/thrombectomy, or coronary thrombolysis (3351x, 3353x, 9292x, 9293x, 9294x, 9297x) 10,344 individuals European BioMe
PSS000517 ICD-9 diagnosis code for acute myocardial infarction, other acute/subacute forms of ischemic heart disease, old myocardial infarction, other forms of chronic ischemic heart disease, certain unspecified sequelae of myocardial infarction, coronary bypass, or coronary revascularization (36.1, 36.2, 410, 411, 412, 414, 429.7); ICD-10 diagnosis code for acute myocardial infarction, subsequent myocardial infarction, complications following myocardial infarction, other acute ischemic heart disease, or chronic ischemic heart disease (I21, I22, I23, I24, I25); CPT procedure code for coronary artery bypass, percutaneous transluminal angioplasty/revascularization/thrombectomy, or coronary thrombolysis (3351x, 3353x, 9292x, 9293x, 9294x, 9297x) 7,048 individuals Hispanic or Latin American BioMe
PSS000518 ICD-9 diagnosis code for acute myocardial infarction, other acute/subacute forms of ischemic heart disease, old myocardial infarction, other forms of chronic ischemic heart disease, certain unspecified sequelae of myocardial infarction, coronary bypass, or coronary revascularization (36.1, 36.2, 410, 411, 412, 414, 429.7); ICD-10 diagnosis code for acute myocardial infarction, subsequent myocardial infarction, complications following myocardial infarction, other acute ischemic heart disease, or chronic ischemic heart disease (I21, I22, I23, I24, I25); CPT procedure code for coronary artery bypass, percutaneous transluminal angioplasty/revascularization/thrombectomy, or coronary thrombolysis (3351x, 3353x, 9292x, 9293x, 9294x, 9297x)
[
  • 3,538 cases
  • , 10,129 controls
]
,
45.0 % Male samples
European, African unspecified, Hispanic or Latin American, East Asian, South Asian African unspecified=867, East Asian=167, European=11725, Hispanic or Latin American=799, South Asian=109 PHB
PSS000519 ICD-9 diagnosis code for acute myocardial infarction, other acute/subacute forms of ischemic heart disease, old myocardial infarction, other forms of chronic ischemic heart disease, certain unspecified sequelae of myocardial infarction, coronary bypass, or coronary revascularization (36.1, 36.2, 410, 411, 412, 414, 429.7); ICD-10 diagnosis code for acute myocardial infarction, subsequent myocardial infarction, complications following myocardial infarction, other acute ischemic heart disease, or chronic ischemic heart disease (I21, I22, I23, I24, I25); CPT procedure code for coronary artery bypass, percutaneous transluminal angioplasty/revascularization/thrombectomy, or coronary thrombolysis (3351x, 3353x, 9292x, 9293x, 9294x, 9297x)
[
  • 4,658 cases
  • , 4,412 controls
]
,
59.0 % Male samples
European, African unspecified African unspecified=1927, European=7143 PMB
PSS000520 ICD-9 diagnosis code for acute myocardial infarction, other acute/subacute forms of ischemic heart disease, old myocardial infarction, other forms of chronic ischemic heart disease, certain unspecified sequelae of myocardial infarction, coronary bypass, or coronary revascularization (36.1, 36.2, 410, 411, 412, 414, 429.7); ICD-10 diagnosis code for acute myocardial infarction, subsequent myocardial infarction, complications following myocardial infarction, other acute ischemic heart disease, or chronic ischemic heart disease (I21, I22, I23, I24, I25); CPT procedure code for coronary artery bypass, percutaneous transluminal angioplasty/revascularization/thrombectomy, or coronary thrombolysis (3351x, 3353x, 9292x, 9293x, 9294x, 9297x)
[
  • 11,020 cases
  • , 36,088 controls
]
,
46.52 % Male samples
European, African unspecified, Hispanic or Latin American, East Asian, South Asian African unspecified=9773, East Asian=167, European=29212, Hispanic or Latin America=7847, South Asian=109 BioMe, PHB, PMB
PSS000521
[
  • 9,473 cases
  • , 9,462 controls
]
,
0.0 % Male samples
European 59 cohorts
  • BCFR-AU
  • ,BCFR-NY
  • ,BCFR-PA
  • ,BCFR-UTAH
  • ,BFBOCC
  • ,BMBSA
  • ,BRICOH
  • ,CNIO
  • ,COH
  • ,CONSIT_TEAM
  • ,CopBCS
  • ,DEMOKRITOS
  • ,DFCI
  • ,DKFZ
  • ,EMBRACE
  • ,FCCC
  • ,G-FaST
  • ,GC-HBOC
  • ,GEMO
  • ,Georgetown
  • ,HCSC
  • ,HEBCS
  • ,HEBON
  • ,HUNBOCS
  • ,HUVH
  • ,ICO
  • ,IHCC
  • ,INHERIT
  • ,IOVHBOCS
  • ,IPOBCS
  • ,KUMC
  • ,LUHR
  • ,MACBRCA
  • ,MAYO
  • ,MCGILL
  • ,MDACCS
  • ,MODSQUAD
  • ,MSKCC
  • ,MUV
  • ,NC-BCFR
  • ,NCI
  • ,NICCC
  • ,NNPIO
  • ,NRG_ONCOLOGY
  • ,NSUHS
  • ,OCGN
  • ,OFBCR
  • ,OUH
  • ,PiBCS
  • ,SWE-BRCA
  • ,UC
  • ,UCLA
  • ,UCSF
  • ,UKGRFOCR
  • ,UPENN
  • ,UPITT
  • ,VFCTG
  • ,WCRI
  • ,kConFab
PSS000522
[
  • 3,263 cases
  • , 10,138 controls
]
,
0.0 % Male samples
European 59 cohorts
  • BCFR-AU
  • ,BCFR-NY
  • ,BCFR-PA
  • ,BCFR-UTAH
  • ,BFBOCC
  • ,BMBSA
  • ,BRICOH
  • ,CNIO
  • ,COH
  • ,CONSIT_TEAM
  • ,CopBCS
  • ,DEMOKRITOS
  • ,DFCI
  • ,DKFZ
  • ,EMBRACE
  • ,FCCC
  • ,G-FaST
  • ,GC-HBOC
  • ,GEMO
  • ,Georgetown
  • ,HCSC
  • ,HEBCS
  • ,HEBON
  • ,HUNBOCS
  • ,HUVH
  • ,ICO
  • ,IHCC
  • ,INHERIT
  • ,IOVHBOCS
  • ,IPOBCS
  • ,KUMC
  • ,LUHR
  • ,MACBRCA
  • ,MAYO
  • ,MCGILL
  • ,MDACCS
  • ,MODSQUAD
  • ,MSKCC
  • ,MUV
  • ,NC-BCFR
  • ,NCI
  • ,NICCC
  • ,NNPIO
  • ,NRG_ONCOLOGY
  • ,NSUHS
  • ,OCGN
  • ,OFBCR
  • ,OUH
  • ,PiBCS
  • ,SWE-BRCA
  • ,UC
  • ,UCLA
  • ,UCSF
  • ,UKGRFOCR
  • ,UPENN
  • ,UPITT
  • ,VFCTG
  • ,WCRI
  • ,kConFab
PSS000523
[
  • 1,025 cases
  • , 12,376 controls
]
,
0.0 % Male samples
European 59 cohorts
  • BCFR-AU
  • ,BCFR-NY
  • ,BCFR-PA
  • ,BCFR-UTAH
  • ,BFBOCC
  • ,BMBSA
  • ,BRICOH
  • ,CNIO
  • ,COH
  • ,CONSIT_TEAM
  • ,CopBCS
  • ,DEMOKRITOS
  • ,DFCI
  • ,DKFZ
  • ,EMBRACE
  • ,FCCC
  • ,G-FaST
  • ,GC-HBOC
  • ,GEMO
  • ,Georgetown
  • ,HCSC
  • ,HEBCS
  • ,HEBON
  • ,HUNBOCS
  • ,HUVH
  • ,ICO
  • ,IHCC
  • ,INHERIT
  • ,IOVHBOCS
  • ,IPOBCS
  • ,KUMC
  • ,LUHR
  • ,MACBRCA
  • ,MAYO
  • ,MCGILL
  • ,MDACCS
  • ,MODSQUAD
  • ,MSKCC
  • ,MUV
  • ,NC-BCFR
  • ,NCI
  • ,NICCC
  • ,NNPIO
  • ,NRG_ONCOLOGY
  • ,NSUHS
  • ,OCGN
  • ,OFBCR
  • ,OUH
  • ,PiBCS
  • ,SWE-BRCA
  • ,UC
  • ,UCLA
  • ,UCSF
  • ,UKGRFOCR
  • ,UPENN
  • ,UPITT
  • ,VFCTG
  • ,WCRI
  • ,kConFab
PSS000524
[
  • 2,068 cases
  • , 16,867 controls
]
,
0.0 % Male samples
European 59 cohorts
  • BCFR-AU
  • ,BCFR-NY
  • ,BCFR-PA
  • ,BCFR-UTAH
  • ,BFBOCC
  • ,BMBSA
  • ,BRICOH
  • ,CNIO
  • ,COH
  • ,CONSIT_TEAM
  • ,CopBCS
  • ,DEMOKRITOS
  • ,DFCI
  • ,DKFZ
  • ,EMBRACE
  • ,FCCC
  • ,G-FaST
  • ,GC-HBOC
  • ,GEMO
  • ,Georgetown
  • ,HCSC
  • ,HEBCS
  • ,HEBON
  • ,HUNBOCS
  • ,HUVH
  • ,ICO
  • ,IHCC
  • ,INHERIT
  • ,IOVHBOCS
  • ,IPOBCS
  • ,KUMC
  • ,LUHR
  • ,MACBRCA
  • ,MAYO
  • ,MCGILL
  • ,MDACCS
  • ,MODSQUAD
  • ,MSKCC
  • ,MUV
  • ,NC-BCFR
  • ,NCI
  • ,NICCC
  • ,NNPIO
  • ,NRG_ONCOLOGY
  • ,NSUHS
  • ,OCGN
  • ,OFBCR
  • ,OUH
  • ,PiBCS
  • ,SWE-BRCA
  • ,UC
  • ,UCLA
  • ,UCSF
  • ,UKGRFOCR
  • ,UPENN
  • ,UPITT
  • ,VFCTG
  • ,WCRI
  • ,kConFab
PSS000525
[
  • 6,332 cases
  • , 6,007 controls
]
,
0.0 % Male samples
European 59 cohorts
  • BCFR-AU
  • ,BCFR-NY
  • ,BCFR-PA
  • ,BCFR-UTAH
  • ,BFBOCC
  • ,BMBSA
  • ,BRICOH
  • ,CNIO
  • ,COH
  • ,CONSIT_TEAM
  • ,CopBCS
  • ,DEMOKRITOS
  • ,DFCI
  • ,DKFZ
  • ,EMBRACE
  • ,FCCC
  • ,G-FaST
  • ,GC-HBOC
  • ,GEMO
  • ,Georgetown
  • ,HCSC
  • ,HEBCS
  • ,HEBON
  • ,HUNBOCS
  • ,HUVH
  • ,ICO
  • ,IHCC
  • ,INHERIT
  • ,IOVHBOCS
  • ,IPOBCS
  • ,KUMC
  • ,LUHR
  • ,MACBRCA
  • ,MAYO
  • ,MCGILL
  • ,MDACCS
  • ,MODSQUAD
  • ,MSKCC
  • ,MUV
  • ,NC-BCFR
  • ,NCI
  • ,NICCC
  • ,NNPIO
  • ,NRG_ONCOLOGY
  • ,NSUHS
  • ,OCGN
  • ,OFBCR
  • ,OUH
  • ,PiBCS
  • ,SWE-BRCA
  • ,UC
  • ,UCLA
  • ,UCSF
  • ,UKGRFOCR
  • ,UPENN
  • ,UPITT
  • ,VFCTG
  • ,WCRI
  • ,kConFab
PSS000526
[
  • 703 cases
  • , 8,049 controls
]
,
0.0 % Male samples
European 59 cohorts
  • BCFR-AU
  • ,BCFR-NY
  • ,BCFR-PA
  • ,BCFR-UTAH
  • ,BFBOCC
  • ,BMBSA
  • ,BRICOH
  • ,CNIO
  • ,COH
  • ,CONSIT_TEAM
  • ,CopBCS
  • ,DEMOKRITOS
  • ,DFCI
  • ,DKFZ
  • ,EMBRACE
  • ,FCCC
  • ,G-FaST
  • ,GC-HBOC
  • ,GEMO
  • ,Georgetown
  • ,HCSC
  • ,HEBCS
  • ,HEBON
  • ,HUNBOCS
  • ,HUVH
  • ,ICO
  • ,IHCC
  • ,INHERIT
  • ,IOVHBOCS
  • ,IPOBCS
  • ,KUMC
  • ,LUHR
  • ,MACBRCA
  • ,MAYO
  • ,MCGILL
  • ,MDACCS
  • ,MODSQUAD
  • ,MSKCC
  • ,MUV
  • ,NC-BCFR
  • ,NCI
  • ,NICCC
  • ,NNPIO
  • ,NRG_ONCOLOGY
  • ,NSUHS
  • ,OCGN
  • ,OFBCR
  • ,OUH
  • ,PiBCS
  • ,SWE-BRCA
  • ,UC
  • ,UCLA
  • ,UCSF
  • ,UKGRFOCR
  • ,UPENN
  • ,UPITT
  • ,VFCTG
  • ,WCRI
  • ,kConFab
PSS000527
[
  • 2,312 cases
  • , 6,440 controls
]
,
0.0 % Male samples
European 59 cohorts
  • BCFR-AU
  • ,BCFR-NY
  • ,BCFR-PA
  • ,BCFR-UTAH
  • ,BFBOCC
  • ,BMBSA
  • ,BRICOH
  • ,CNIO
  • ,COH
  • ,CONSIT_TEAM
  • ,CopBCS
  • ,DEMOKRITOS
  • ,DFCI
  • ,DKFZ
  • ,EMBRACE
  • ,FCCC
  • ,G-FaST
  • ,GC-HBOC
  • ,GEMO
  • ,Georgetown
  • ,HCSC
  • ,HEBCS
  • ,HEBON
  • ,HUNBOCS
  • ,HUVH
  • ,ICO
  • ,IHCC
  • ,INHERIT
  • ,IOVHBOCS
  • ,IPOBCS
  • ,KUMC
  • ,LUHR
  • ,MACBRCA
  • ,MAYO
  • ,MCGILL
  • ,MDACCS
  • ,MODSQUAD
  • ,MSKCC
  • ,MUV
  • ,NC-BCFR
  • ,NCI
  • ,NICCC
  • ,NNPIO
  • ,NRG_ONCOLOGY
  • ,NSUHS
  • ,OCGN
  • ,OFBCR
  • ,OUH
  • ,PiBCS
  • ,SWE-BRCA
  • ,UC
  • ,UCLA
  • ,UCSF
  • ,UKGRFOCR
  • ,UPENN
  • ,UPITT
  • ,VFCTG
  • ,WCRI
  • ,kConFab
PSS000528
[
  • 718 cases
  • , 11,621 controls
]
,
0.0 % Male samples
European 59 cohorts
  • BCFR-AU
  • ,BCFR-NY
  • ,BCFR-PA
  • ,BCFR-UTAH
  • ,BFBOCC
  • ,BMBSA
  • ,BRICOH
  • ,CNIO
  • ,COH
  • ,CONSIT_TEAM
  • ,CopBCS
  • ,DEMOKRITOS
  • ,DFCI
  • ,DKFZ
  • ,EMBRACE
  • ,FCCC
  • ,G-FaST
  • ,GC-HBOC
  • ,GEMO
  • ,Georgetown
  • ,HCSC
  • ,HEBCS
  • ,HEBON
  • ,HUNBOCS
  • ,HUVH
  • ,ICO
  • ,IHCC
  • ,INHERIT
  • ,IOVHBOCS
  • ,IPOBCS
  • ,KUMC
  • ,LUHR
  • ,MACBRCA
  • ,MAYO
  • ,MCGILL
  • ,MDACCS
  • ,MODSQUAD
  • ,MSKCC
  • ,MUV
  • ,NC-BCFR
  • ,NCI
  • ,NICCC
  • ,NNPIO
  • ,NRG_ONCOLOGY
  • ,NSUHS
  • ,OCGN
  • ,OFBCR
  • ,OUH
  • ,PiBCS
  • ,SWE-BRCA
  • ,UC
  • ,UCLA
  • ,UCSF
  • ,UKGRFOCR
  • ,UPENN
  • ,UPITT
  • ,VFCTG
  • ,WCRI
  • ,kConFab
PSS000529 Eligibility was restricted to female BRCA1 and BRCA2 carriers who at completion of the baseline questionnaire were free of any cancer diagnosis (excluding non-melanoma skin cancer) and had not undergone risk-reducing bilateral mastectomy. Participants diagosed with a first breast cancer were considered affected.
[
  • 297 cases
  • , 1,791 controls
]
,
0.0 % Male samples
European 61 cohorts
  • BCFR
  • ,BCFR-AU
  • ,BCFR-NY
  • ,BCFR-PA
  • ,BCFR-UTAH
  • ,BFBOCC
  • ,BMBSA
  • ,BRICOH
  • ,CNIO
  • ,COH
  • ,CONSIT_TEAM
  • ,CopBCS
  • ,DEMOKRITOS
  • ,DFCI
  • ,DKFZ
  • ,EMBRACE
  • ,FCCC
  • ,G-FaST
  • ,GC-HBOC
  • ,GEMO
  • ,Georgetown
  • ,HCSC
  • ,HEBCS
  • ,HEBON
  • ,HUNBOCS
  • ,HUVH
  • ,IBCCS
  • ,ICO
  • ,IHCC
  • ,INHERIT
  • ,IOVHBOCS
  • ,IPOBCS
  • ,KUMC
  • ,LUHR
  • ,MACBRCA
  • ,MAYO
  • ,MCGILL
  • ,MDACCS
  • ,MODSQUAD
  • ,MSKCC
  • ,MUV
  • ,NC-BCFR
  • ,NCI
  • ,NICCC
  • ,NNPIO
  • ,NRG_ONCOLOGY
  • ,NSUHS
  • ,OCGN
  • ,OFBCR
  • ,OUH
  • ,PiBCS
  • ,SWE-BRCA
  • ,UC
  • ,UCLA
  • ,UCSF
  • ,UKGRFOCR
  • ,UPENN
  • ,UPITT
  • ,VFCTG
  • ,WCRI
  • ,kConFab
PSS000530 To assess associationss between the PRS and ovarian cancer risk, eligibility was restricted to women who had not been diagnosed with ovarian cancer and had not had RRSO at the time of baselinne questionnaire completion. Carriers diagnosed with invasive ovarian, fallopian tube, or peritoneal cancer during the follow-up were considered affected.
[
  • 108 cases
  • , 3,044 controls
]
,
0.0 % Male samples
European 61 cohorts
  • BCFR
  • ,BCFR-AU
  • ,BCFR-NY
  • ,BCFR-PA
  • ,BCFR-UTAH
  • ,BFBOCC
  • ,BMBSA
  • ,BRICOH
  • ,CNIO
  • ,COH
  • ,CONSIT_TEAM
  • ,CopBCS
  • ,DEMOKRITOS
  • ,DFCI
  • ,DKFZ
  • ,EMBRACE
  • ,FCCC
  • ,G-FaST
  • ,GC-HBOC
  • ,GEMO
  • ,Georgetown
  • ,HCSC
  • ,HEBCS
  • ,HEBON
  • ,HUNBOCS
  • ,HUVH
  • ,IBCCS
  • ,ICO
  • ,IHCC
  • ,INHERIT
  • ,IOVHBOCS
  • ,IPOBCS
  • ,KUMC
  • ,LUHR
  • ,MACBRCA
  • ,MAYO
  • ,MCGILL
  • ,MDACCS
  • ,MODSQUAD
  • ,MSKCC
  • ,MUV
  • ,NC-BCFR
  • ,NCI
  • ,NICCC
  • ,NNPIO
  • ,NRG_ONCOLOGY
  • ,NSUHS
  • ,OCGN
  • ,OFBCR
  • ,OUH
  • ,PiBCS
  • ,SWE-BRCA
  • ,UC
  • ,UCLA
  • ,UCSF
  • ,UKGRFOCR
  • ,UPENN
  • ,UPITT
  • ,VFCTG
  • ,WCRI
  • ,kConFab
PSS000531 Eligibility was restricted to female BRCA1 and BRCA2 carriers who at completion of the baseline questionnaire were free of any cancer diagnosis (excluding non-melanoma skin cancer) and had not undergone risk-reducing bilateral mastectomy. Participants diagosed with a first breast cancer were considered affected.
[
  • 215 cases
  • , 1,542 controls
]
,
0.0 % Male samples
European 61 cohorts
  • BCFR
  • ,BCFR-AU
  • ,BCFR-NY
  • ,BCFR-PA
  • ,BCFR-UTAH
  • ,BFBOCC
  • ,BMBSA
  • ,BRICOH
  • ,CNIO
  • ,COH
  • ,CONSIT_TEAM
  • ,CopBCS
  • ,DEMOKRITOS
  • ,DFCI
  • ,DKFZ
  • ,EMBRACE
  • ,FCCC
  • ,G-FaST
  • ,GC-HBOC
  • ,GEMO
  • ,Georgetown
  • ,HCSC
  • ,HEBCS
  • ,HEBON
  • ,HUNBOCS
  • ,HUVH
  • ,IBCCS
  • ,ICO
  • ,IHCC
  • ,INHERIT
  • ,IOVHBOCS
  • ,IPOBCS
  • ,KUMC
  • ,LUHR
  • ,MACBRCA
  • ,MAYO
  • ,MCGILL
  • ,MDACCS
  • ,MODSQUAD
  • ,MSKCC
  • ,MUV
  • ,NC-BCFR
  • ,NCI
  • ,NICCC
  • ,NNPIO
  • ,NRG_ONCOLOGY
  • ,NSUHS
  • ,OCGN
  • ,OFBCR
  • ,OUH
  • ,PiBCS
  • ,SWE-BRCA
  • ,UC
  • ,UCLA
  • ,UCSF
  • ,UKGRFOCR
  • ,UPENN
  • ,UPITT
  • ,VFCTG
  • ,WCRI
  • ,kConFab
PSS000532 To assess associationss between the PRS and ovarian cancer risk, eligibility was restricted to women who had not been diagnosed with ovarian cancer and had not had RRSO at the time of baseline questionnaire completion. Carriers diagnosed with invasive ovarian, fallopian tbe, or peritoneal cancer during the follow-up were considered affected.
[
  • 56 cases
  • , 2,439 controls
]
,
0.0 % Male samples
European 61 cohorts
  • BCFR
  • ,BCFR-AU
  • ,BCFR-NY
  • ,BCFR-PA
  • ,BCFR-UTAH
  • ,BFBOCC
  • ,BMBSA
  • ,BRICOH
  • ,CNIO
  • ,COH
  • ,CONSIT_TEAM
  • ,CopBCS
  • ,DEMOKRITOS
  • ,DFCI
  • ,DKFZ
  • ,EMBRACE
  • ,FCCC
  • ,G-FaST
  • ,GC-HBOC
  • ,GEMO
  • ,Georgetown
  • ,HCSC
  • ,HEBCS
  • ,HEBON
  • ,HUNBOCS
  • ,HUVH
  • ,IBCCS
  • ,ICO
  • ,IHCC
  • ,INHERIT
  • ,IOVHBOCS
  • ,IPOBCS
  • ,KUMC
  • ,LUHR
  • ,MACBRCA
  • ,MAYO
  • ,MCGILL
  • ,MDACCS
  • ,MODSQUAD
  • ,MSKCC
  • ,MUV
  • ,NC-BCFR
  • ,NCI
  • ,NICCC
  • ,NNPIO
  • ,NRG_ONCOLOGY
  • ,NSUHS
  • ,OCGN
  • ,OFBCR
  • ,OUH
  • ,PiBCS
  • ,SWE-BRCA
  • ,UC
  • ,UCLA
  • ,UCSF
  • ,UKGRFOCR
  • ,UPENN
  • ,UPITT
  • ,VFCTG
  • ,WCRI
  • ,kConFab
PSS000533 Any Cancer PheCode
[
  • 10,394 cases
  • , 4,892 controls
]
European MGI
PSS000534 PheCode:145.2; ICD9CM:141.0, 141.1, 141.2, 141.3, 141.4, 141.5, 141.6, 141.8, 141.9, V10.01; ICD10CM:C01, C02, C02.0, C02.1, C02.2, C02.3, C02.4, C02.8, C02.9
[
  • 259 cases
  • , 2,582 controls
]
European MGI
PSS000535 PheCode:145; ICD9CM:140.0, 140.1, 140.3, 140.4, 140.5, 140.6, 140.8, 140.9, 141.0, 141.1, 141.2, 141.3, 141.4, 141.5, 141.6, 141.8, 141.9, 142.0, 142.1, 142.2, 142.8, 142.9, 143.0, 143.1, 143.8, 143.9, 144.0, 144.1, 144.8, 144.9, 145.0, 145.1, 145.2, 145.3, 145.4, 145.5, 145.6, 145.8, 145.9, 230.0, V10.01; ICD10CM:C00, C00.0, C00.1, C00.2, C00.3, C00.4, C00.5, C00.6, C00.8, C00.9, C01, C02, C02.0, C02.1, C02.2, C02.3, C02.4, C02.8, C02.9, C03, C03.0, C03.1, C03.9, C04, C04.0, C04.1, C04.8, C04.9, C05, C05.0, C05.1, C05.2, C05.8, C05.9, C06, C06.0, C06.1, C06.2, C06.8, C06.80, C06.89, C06.9, C07, C08, C08.0, C08.1, C08.9, D00.0, D00.00, D00.01, D00.02, D00.03, D00.04, D00.05, D00.06, D00.07, D00.08
[
  • 578 cases
  • , 5,750 controls
]
European MGI
PSS000536 PheCode:149.4; ICD9CM:161.0, 161.1, 161.2, 161.3, 161.8, 161.9, 231.0, V10.21; ICD10CM:C32, C32.0, C32.1, C32.2, C32.3, C32.8, C32.9, D02.0
[
  • 158 cases
  • , 1,580 controls
]
European MGI
PSS000537 PheCode:150; ICD9CM:150.0, 150.1, 150.2, 150.3, 150.4, 150.5, 150.8, 150.9, 230.1, V10.03; ICD10CM:C15, C15.3, C15.4, C15.5, C15.8, C15.9, D00.1
[
  • 188 cases
  • , 1,876 controls
]
European MGI
PSS000538 PheCode:153.2; ICD9CM:153.0, 153.1, 153.2, 153.3, 153.4, 153.5, 153.6, 153.7, 153.8, 153.9, 159.0, 209.10, 209.11, 209.12, 209.13, 209.14, 209.15, 209.16, 230.3, V10.05; ICD10CM:C18, C18.0, C18.1, C18.2, C18.3, C18.4, C18.5, C18.6, C18.7, C18.8, C18.9, C26.0, C7A.020, C7A.021, C7A.022, C7A.023, C7A.024, C7A.025, C7A.029, D01.0
[
  • 462 cases
  • , 4,569 controls
]
European MGI
PSS000539 PheCode:153.3; ICD9CM:154.0, 154.1, 154.2, 154.3, 209.17, 230.4, 230.5, 230.6, 796.70, 796.71, 796.72, 796.73, 796.74, 796.76, V10.06; ICD10CM:C19, C20, C21.0, C21.1, C7A.026, D01.1, D01.2, D01.3, R85.610, R85.611, R85.612, R85.613, R85.614, R85.619
[
  • 325 cases
  • , 3,232 controls
]
European MGI
PSS000540 PheCode:153; ICD9CM:153.0, 153.1, 153.2, 153.3, 153.4, 153.5, 153.6, 153.7, 153.8, 153.9, 154.0, 154.1, 154.2, 154.3, 154.8, 159.0, 209.10, 209.11, 209.12, 209.13, 209.14, 209.15, 209.16, 209.17, 230.3, 230.4, 230.5, 230.6, 796.70, 796.71, 796.72, 796.73, 796.74, 796.76, V10.05, V10.06; ICD10CM:C18, C18.0, C18.1, C18.2, C18.3, C18.4, C18.5, C18.6, C18.7, C18.8, C18.9, C19, C20, C21.0, C21.1, C21.2, C21.8, C26.0, C7A.020, C7A.021, C7A.022, C7A.023, C7A.024, C7A.025, C7A.026, C7A.029, D01.0, D01.1, D01.2, D01.3, R85.610, R85.611, R85.612, R85.613, R85.614, R85.619
[
  • 607 cases
  • , 6,026 controls
]
European MGI
PSS000541 PheCode:165.1; ICD9CM:162.0, 162.2, 162.3, 162.4, 162.5, 162.8, 162.9, 209.21, 231.2, V10.11; ICD10CM:C33, C34, C34.0, C34.00, C34.01, C34.02, C34.1, C34.10, C34.11, C34.12, C34.2, C34.3, C34.30, C34.31, C34.32, C34.8, C34.80, C34.81, C34.82, C34.9, C34.90, C34.91, C34.92, C7A.090, D02.2, D02.20, D02.21, D02.22
[
  • 428 cases
  • , 4,270 controls
]
European MGI
PSS000542 PheCode:165; ICD9CM:162.0, 162.2, 162.3, 162.4, 162.5, 162.8, 162.9, 163.0, 163.1, 163.8, 163.9, 165.0, 165.8, 165.9, 209.21, 231.1, 231.2, 231.8, 231.9, V10.11, V10.12, V10.20, V10.29; ICD10CM:C33, C34, C34.0, C34.00, C34.01, C34.02, C34.1, C34.10, C34.11, C34.12, C34.2, C34.3, C34.30, C34.31, C34.32, C34.8, C34.80, C34.81, C34.82, C34.9, C34.90, C34.91, C34.92, C38.4, C39, C39.0, C39.9, C45.0, C7A.090, D02.1, D02.2, D02.20, D02.21, D02.22, D02.3, D02.4
[
  • 475 cases
  • , 4,743 controls
]
European MGI
PSS000543 PheCode:172.1; ICD9CM:172.0, 172.1, 172.2, 172.3, 172.4, 172.5, 172.6, 172.7, 172.8, 172.9, V10.82; ICD10CM:C43, C43.0, C43.1, C43.10, C43.11, C43.12, C43.2, C43.20, C43.21, C43.22, C43.3, C43.30, C43.31, C43.39, C43.4, C43.5, C43.51, C43.52, C43.59, C43.6, C43.60, C43.61, C43.62, C43.7, C43.70, C43.71, C43.72, C43.8, C43.9, D03, D03.0, D03.1, D03.10, D03.11, D03.12, D03.2, D03.20, D03.21, D03.22, D03.3, D03.30, D03.39, D03.4, D03.5, D03.51, D03.52, D03.59, D03.6, D03.60, D03.61, D03.62, D03.7, D03.70, D03.71, D03.72, D03.8, D03.9
[
  • 1,325 cases
  • , 10,649 controls
]
European MGI
PSS000544 PheCode:172.21; ICD9CM:173.01, 173.11, 173.21, 173.31, 173.41, 173.51, 173.61, 173.71, 173.81, 173.91; ICD10CM:C44.01, C44.111, C44.112, C44.119, C44.211, C44.212, C44.219, C44.310, C44.311, C44.319, C44.41, C44.510, C44.511, C44.519, C44.611, C44.612, C44.619, C44.711, C44.712, C44.719, C44.81, C44.91
[
  • 1,481 cases
  • , 9,841 controls
]
European MGI
PSS000545 PheCode:172.22; ICD9CM:173.02, 173.12, 173.22, 173.32, 173.42, 173.52, 173.62, 173.72, 173.82, 173.92; ICD10CM:C44.02, C44.121, C44.122, C44.129, C44.221, C44.222, C44.229, C44.320, C44.321, C44.329, C44.42, C44.520, C44.521, C44.529, C44.621, C44.622, C44.629, C44.721, C44.722, C44.729, C44.82, C44.92
[
  • 982 cases
  • , 7,491 controls
]
European MGI
PSS000546 PheCode:172.2; ICD9CM:173.00, 173.01, 173.02, 173.09, 173.10, 173.11, 173.12, 173.19, 173.20, 173.21, 173.22, 173.29, 173.30, 173.31, 173.32, 173.39, 173.40, 173.41, 173.42, 173.49, 173.50, 173.51, 173.52, 173.59, 173.60, 173.61, 173.62, 173.69, 173.70, 173.71, 173.72, 173.79, 173.80, 173.81, 173.82, 173.89, 173.90, 173.91, 173.92, 173.99, 209.31, 209.32, 209.33, 209.34, 209.35, 209.36, V10.83; ICD10CM:C44.0, C44.00, C44.01, C44.02, C44.09, C44.1, C44.10, C44.101, C44.102, C44.109, C44.11, C44.111, C44.112, C44.119, C44.12, C44.121, C44.122, C44.129, C44.19, C44.191, C44.192, C44.199, C44.2, C44.20, C44.201, C44.202, C44.209, C44.21, C44.211, C44.212, C44.219, C44.22, C44.221, C44.222, C44.229, C44.29, C44.291, C44.292, C44.299, C44.30, C44.300, C44.301, C44.309, C44.31, C44.310, C44.311, C44.319, C44.320, C44.321, C44.329, C44.39, C44.390, C44.391, C44.399, C44.4, C44.40, C44.41, C44.42, C44.49, C44.500, C44.501, C44.509, C44.51, C44.510, C44.511, C44.519, C44.52, C44.520, C44.521, C44.529, C44.59, C44.590, C44.591, C44.599, C44.6, C44.60, C44.601, C44.602, C44.609, C44.61, C44.611, C44.612, C44.619, C44.62, C44.621, C44.622, C44.629, C44.69, C44.691, C44.692, C44.699, C44.7, C44.70, C44.701, C44.702, C44.709, C44.71, C44.711, C44.712, C44.719, C44.72, C44.721, C44.722, C44.729, C44.79, C44.791, C44.792, C44.799, C44.8, C44.80, C44.81, C44.82, C44.89, C44.9, C44.90, C44.91, C44.92, C44.99, C4A, C4A.0, C4A.1, C4A.10, C4A.11, C4A.12, C4A.2, C4A.20, C4A.21, C4A.22, C4A.3, C4A.30, C4A.31, C4A.39, C4A.4, C4A.5, C4A.51, C4A.52, C4A.59, C4A.6, C4A.60, C4A.61, C4A.62, C4A.7, C4A.70, C4A.71, C4A.72, C4A.8, C4A.9
[
  • 2,954 cases
  • , 12,944 controls
]
European MGI
PSS000547 PheCode:172.3; ICD9CM:232.0, 232.1, 232.2, 232.3, 232.4, 232.5, 232.6, 232.7, 232.8, 232.9; ICD10CM:D04, D04.0, D04.1, D04.10, D04.11, D04.12, D04.2, D04.20, D04.21, D04.22, D04.3, D04.30, D04.39, D04.4, D04.5, D04.6, D04.60, D04.61, D04.62, D04.7, D04.70, D04.71, D04.72, D04.8, D04.9
[
  • 585 cases
  • , 4,915 controls
]
European MGI
PSS000548 PheCode:172; ICD9CM:172.0, 172.1, 172.2, 172.3, 172.4, 172.5, 172.6, 172.7, 172.8, 172.9, 173.00, 173.01, 173.02, 173.09, 173.10, 173.11, 173.12, 173.19, 173.20, 173.21, 173.22, 173.29, 173.30, 173.31, 173.32, 173.39, 173.40, 173.41, 173.42, 173.49, 173.50, 173.51, 173.52, 173.59, 173.60, 173.61, 173.62, 173.69, 173.70, 173.71, 173.72, 173.79, 173.80, 173.81, 173.82, 173.89, 173.90, 173.91, 173.92, 173.99, 209.31, 209.32, 209.33, 209.34, 209.35, 209.36, 232.0, 232.1, 232.2, 232.3, 232.4, 232.5, 232.6, 232.7, 232.8, 232.9, V10.82, V10.83; ICD10CM:C43, C43.0, C43.1, C43.10, C43.11, C43.12, C43.2, C43.20, C43.21, C43.22, C43.3, C43.30, C43.31, C43.39, C43.4, C43.5, C43.51, C43.52, C43.59, C43.6, C43.60, C43.61, C43.62, C43.7, C43.70, C43.71, C43.72, C43.8, C43.9, C44.0, C44.00, C44.01, C44.02, C44.09, C44.1, C44.10, C44.101, C44.102, C44.109, C44.11, C44.111, C44.112, C44.119, C44.12, C44.121, C44.122, C44.129, C44.19, C44.191, C44.192, C44.199, C44.2, C44.20, C44.201, C44.202, C44.209, C44.21, C44.211, C44.212, C44.219, C44.22, C44.221, C44.222, C44.229, C44.29, C44.291, C44.292, C44.299, C44.30, C44.300, C44.301, C44.309, C44.31, C44.310, C44.311, C44.319, C44.320, C44.321, C44.329, C44.39, C44.390, C44.391, C44.399, C44.4, C44.40, C44.41, C44.42, C44.49, C44.500, C44.501, C44.509, C44.51, C44.510, C44.511, C44.519, C44.52, C44.520, C44.521, C44.529, C44.59, C44.590, C44.591, C44.599, C44.6, C44.60, C44.601, C44.602, C44.609, C44.61, C44.611, C44.612, C44.619, C44.62, C44.621, C44.622, C44.629, C44.69, C44.691, C44.692, C44.699, C44.7, C44.70, C44.701, C44.702, C44.709, C44.71, C44.711, C44.712, C44.719, C44.72, C44.721, C44.722, C44.729, C44.79, C44.791, C44.792, C44.799, C44.8, C44.80, C44.81, C44.82, C44.89, C44.9, C44.90, C44.91, C44.92, C44.99, C4A, C4A.0, C4A.1, C4A.10, C4A.11, C4A.12, C4A.2, C4A.20, C4A.21, C4A.22, C4A.3, C4A.30, C4A.31, C4A.39, C4A.4, C4A.5, C4A.51, C4A.52, C4A.59, C4A.6, C4A.60, C4A.61, C4A.62, C4A.7, C4A.70, C4A.71, C4A.72, C4A.8, C4A.9, D03, D03.0, D03.1, D03.10, D03.11, D03.12, D03.2, D03.20, D03.21, D03.22, D03.3, D03.30, D03.39, D03.4, D03.5, D03.51, D03.52, D03.59, D03.6, D03.60, D03.61, D03.62, D03.7, D03.70, D03.71, D03.72, D03.8, D03.9, D04, D04.0, D04.1, D04.10, D04.11, D04.12, D04.2, D04.20, D04.21, D04.22, D04.3, D04.30, D04.39, D04.4, D04.5, D04.6, D04.60, D04.61, D04.62, D04.7, D04.70, D04.71, D04.72, D04.8, D04.9
[
  • 3,557 cases
  • , 14,050 controls
]
European MGI
PSS000549 PheCode:174.1; ICD9CM:174.0, 174.1, 174.2, 174.3, 174.4, 174.5, 174.6, 174.8, 174.9, 233.0, V10.3; ICD10CM:C50, C50.0, C50.01, C50.011, C50.012, C50.019, C50.02, C50.021, C50.022, C50.029, C50.1, C50.11, C50.111, C50.112, C50.119, C50.12, C50.121, C50.122, C50.129, C50.2, C50.21, C50.211, C50.212, C50.219, C50.22, C50.221, C50.222, C50.229, C50.3, C50.31, C50.311, C50.312, C50.319, C50.32, C50.321, C50.322, C50.329, C50.4, C50.41, C50.411, C50.412, C50.419, C50.42, C50.421, C50.422, C50.429, C50.5, C50.51, C50.511, C50.512, C50.519, C50.52, C50.521, C50.522, C50.529, C50.6, C50.61, C50.611, C50.612, C50.619, C50.62, C50.621, C50.622, C50.629, C50.8, C50.81, C50.811, C50.812, C50.819, C50.82, C50.821, C50.822, C50.829, C50.9, C50.91, C50.911, C50.912, C50.919, C50.92, C50.921, C50.922, C50.929, D05, D05.0, D05.00, D05.01, D05.02, D05.1, D05.10, D05.11, D05.12, D05.8, D05.80, D05.81, D05.82, D05.9, D05.90, D05.91, D05.92
[
  • 1,341 cases
  • , 6,444 controls
]
European MGI
PSS000550 PheCode:184.11; ICD9CM:183.0, V10.43; ICD10CM:C56, C56.1, C56.2, C56.9
[
  • 174 cases
  • , 1,730 controls
]
European MGI
PSS000551 PheCode:184; ICD9CM:181, 183.0, 183.2, 183.3, 183.4, 183.5, 183.8, 183.9, 184.0, 184.1, 184.2, 184.3, 184.4, 184.8, 184.9, 233.30, 233.31, 233.32, 233.39, 236.0, 236.1, 236.2, 236.3, V10.40, V10.43, V10.44; ICD10CM:C51, C51.0, C51.1, C51.2, C51.8, C51.9, C52, C56, C56.1, C56.2, C56.9, C57, C57.0, C57.00, C57.01, C57.02, C57.1, C57.10, C57.11, C57.12, C57.2, C57.20, C57.21, C57.22, C57.3, C57.4, C57.7, C57.8, C57.9, C58, D07.1, D07.2, D07.3, D07.30, D07.39, D39, D39.0, D39.1, D39.10, D39.11, D39.12, D39.2, D39.8, D39.9, N90.3
[
  • 453 cases
  • , 4,452 controls
]
European MGI
PSS000552 PheCode:185; ICD9CM:185, 233.4, V10.46; ICD10CM:C61, D07.5
[
  • 1,190 cases
  • , 4,417 controls
]
European MGI
PSS000553 PheCode:187.2; ICD9CM:186.0, 186.9, V10.47; ICD10CM:C62, C62.0, C62.00, C62.01, C62.02, C62.1, C62.10, C62.11, C62.12, C62.9, C62.90, C62.91, C62.92
[
  • 73 cases
  • , 682 controls
]
European MGI
PSS000554 PheCode:187; ICD9CM:186.0, 186.9, 187.1, 187.2, 187.3, 187.4, 187.5, 187.6, 187.7, 187.8, 187.9, 233.5, 233.6, 236.4, 236.5, 236.6, V10.45, V10.47, V10.48, V10.49; ICD10CM:C60, C60.0, C60.1, C60.2, C60.8, C60.9, C62, C62.0, C62.00, C62.01, C62.02, C62.1, C62.10, C62.11, C62.12, C62.9, C62.90, C62.91, C62.92, C63, C63.0, C63.00, C63.01, C63.02, C63.1, C63.10, C63.11, C63.12, C63.2, C63.7, C63.8, C63.9, D07.4, D07.6, D07.60, D07.61, D07.69, D40, D40.0, D40.1, D40.10, D40.11, D40.12, D40.8, D40.9
[
  • 137 cases
  • , 1,353 controls
]
European MGI
PSS000555 PheCode:189.2; ICD9CM:188.0, 188.1, 188.2, 188.3, 188.4, 188.5, 188.6, 188.7, 188.8, 188.9, 233.7, 236.7, 239.4, V10.51; ICD10CM:C67, C67.0, C67.1, C67.2, C67.3, C67.4, C67.5, C67.6, C67.7, C67.8, C67.9, D09.0, D41.4, D49.4
[
  • 789 cases
  • , 6,833 controls
]
European MGI
PSS000556 PheCode:190; ICD9CM:190.0, 190.1, 190.2, 190.3, 190.4, 190.5, 190.6, 190.7, 190.8, 190.9, 234.0, V10.84; ICD10CM:C69, C69.0, C69.00, C69.01, C69.02, C69.1, C69.10, C69.11, C69.12, C69.2, C69.20, C69.21, C69.22, C69.3, C69.30, C69.31, C69.32, C69.4, C69.40, C69.41, C69.42, C69.5, C69.50, C69.51, C69.52, C69.6, C69.60, C69.61, C69.62, C69.8, C69.80, C69.81, C69.82, C69.9, C69.90, C69.91, C69.92, D09.2, D09.20, D09.21, D09.22
[
  • 62 cases
  • , 610 controls
]
European MGI
PSS000557 PheCode:191.11; ICD9CM:191.0, 191.1, 191.2, 191.3, 191.4, 191.5, 191.6, 191.7, 191.8, 191.9, V10.85; ICD10CM:C71, C71.0, C71.1, C71.2, C71.3, C71.4, C71.5, C71.6, C71.7, C71.8, C71.9
[
  • 233 cases
  • , 2,330 controls
]
European MGI
PSS000558 PheCode:193; ICD9CM:193, V10.87; ICD10CM:C73
[
  • 389 cases
  • , 3,881 controls
]
European MGI
PSS000559 PheCode:201; ICD9CM:201.00, 201.01, 201.02, 201.03, 201.04, 201.05, 201.06, 201.07, 201.08, 201.10, 201.11, 201.12, 201.13, 201.14, 201.15, 201.16, 201.17, 201.18, 201.20, 201.21, 201.22, 201.23, 201.24, 201.25, 201.26, 201.27, 201.28, 201.40, 201.41, 201.42, 201.43, 201.44, 201.45, 201.46, 201.47, 201.48, 201.50, 201.51, 201.52, 201.53, 201.54, 201.55, 201.56, 201.57, 201.58, 201.60, 201.61, 201.62, 201.63, 201.64, 201.65, 201.66, 201.67, 201.68, 201.70, 201.71, 201.72, 201.73, 201.74, 201.75, 201.76, 201.77, 201.78, 201.90, 201.91, 201.92, 201.93, 201.94, 201.95, 201.96, 201.97, 201.98, V10.72; ICD10CM:C81, C81.0, C81.00, C81.01, C81.02, C81.03, C81.04, C81.05, C81.06, C81.07, C81.08, C81.09, C81.1, C81.10, C81.11, C81.12, C81.13, C81.14, C81.15, C81.16, C81.17, C81.18, C81.19, C81.2, C81.20, C81.21, C81.22, C81.23, C81.24, C81.25, C81.26, C81.27, C81.28, C81.29, C81.3, C81.30, C81.31, C81.32, C81.33, C81.34, C81.35, C81.36, C81.37, C81.38, C81.39, C81.4, C81.40, C81.41, C81.42, C81.43, C81.44, C81.45, C81.46, C81.47, C81.48, C81.49, C81.7, C81.70, C81.71, C81.72, C81.73, C81.74, C81.75, C81.76, C81.77, C81.78, C81.79, C81.9, C81.90, C81.91, C81.92, C81.93, C81.94, C81.95, C81.96, C81.97, C81.98, C81.99
[
  • 71 cases
  • , 704 controls
]
European MGI
PSS000560 PheCode:202.21; ICD9CM:202.00, 202.01, 202.02, 202.03, 202.04, 202.05, 202.06, 202.07, 202.08; ICD10CM:C82, C82.0, C82.00, C82.01, C82.02, C82.03, C82.04, C82.05, C82.06, C82.07, C82.08, C82.09, C82.1, C82.10, C82.11, C82.12, C82.13, C82.14, C82.15, C82.16, C82.17, C82.18, C82.19, C82.2, C82.20, C82.21, C82.22, C82.23, C82.24, C82.25, C82.26, C82.27, C82.28, C82.29, C82.3, C82.30, C82.31, C82.32, C82.33, C82.34, C82.35, C82.36, C82.37, C82.38, C82.39, C82.4, C82.40, C82.41, C82.42, C82.43, C82.44, C82.45, C82.46, C82.47, C82.48, C82.49, C82.5, C82.50, C82.51, C82.52, C82.53, C82.54, C82.55, C82.56, C82.57, C82.58, C82.59, C82.6, C82.60, C82.61, C82.62, C82.63, C82.64, C82.65, C82.66, C82.67, C82.68, C82.69, C82.8, C82.80, C82.81, C82.82, C82.83, C82.84, C82.85, C82.86, C82.87, C82.88, C82.89, C82.9, C82.90, C82.91, C82.92, C82.93, C82.94, C82.95, C82.96, C82.97, C82.98, C82.99
[
  • 296 cases
  • , 2,960 controls
]
European MGI
PSS000561 PheCode:204.12; ICD9CM:204.10, 204.11, 204.12; ICD10CM:C91.1, C91.10, C91.11, C91.12
[
  • 69 cases
  • , 687 controls
]
European MGI
PSS000562 PheCode:204.1; ICD9CM:204.00, 204.01, 204.02, 204.10, 204.11, 204.12, 204.20, 204.21, 204.22, 204.80, 204.81, 204.82, 204.90, 204.91, 204.92, V10.61; ICD10CM:C91, C91.0, C91.00, C91.01, C91.02, C91.1, C91.10, C91.11, C91.12, C91.3, C91.30, C91.31, C91.32, C91.4, C91.40, C91.41, C91.42, C91.5, C91.50, C91.51, C91.52, C91.6, C91.60, C91.61, C91.62, C91.9, C91.90, C91.91, C91.92, C91.A, C91.A0, C91.A1, C91.A2, C91.Z, C91.Z0, C91.Z1, C91.Z2
[
  • 87 cases
  • , 870 controls
]
European MGI
PSS000563 PheCode:204.4; ICD9CM:203.00, 203.01, 203.02, 203.80, 203.81, 203.82; ICD10CM:C88.2, C88.3, C88.9, C90.0, C90.00, C90.01, C90.02, C90.2, C90.20, C90.21, C90.22, C90.30, C90.31, C90.32
[
  • 83 cases
  • , 825 controls
]
European MGI
PSS000564 PheCode:153; ICD9:154.8; ICD10:C18.0, C18.1, C18.2, C18.3, C18.4, C18.5, C18.6, C18.7, C18.8, C18.9, C19, C20, C21.0, C21.1, C21.8, C26.0, D01.0, D01.1, D01.2, D01.3
[
  • 2,271 cases
  • , 22,725 controls
]
European UKB
PSS000565 PheCode:157; ICD9:157, 157.0, 157.1, 157.2, 157.3, 157.4, 157.8, 157.9; ICD10:C25.0, C25.1, C25.2, C25.3, C25.4, C25.7, C25.8, C25.9
[
  • 327 cases
  • , 3,264 controls
]
European UKB
PSS000566 PheCode:165.1; ICD9:162, 162.0, 162.2, 162.3, 162.4, 162.5, 162.8, 162.9, 231.2; ICD10:C33, C34.0, C34.1, C34.2, C34.3, C34.8, C34.9, D02.2
[
  • 1,109 cases
  • , 11,092 controls
]
European UKB
PSS000567 PheCode:172.1; ICD9:-; ICD10:C43.0, C43.1, C43.2, C43.3, C43.4, C43.5, C43.6, C43.7, C43.8, C43.9, D03.0, D03.1, D03.2, D03.3, D03.4, D03.5, D03.6, D03.7, D03.8, D03.9
[
  • 1,317 cases
  • , 13,165 controls
]
European UKB
PSS000568 PheCode:172.21; ICD9:173, 173.0, 173.1, 173.2, 173.3, 173.4, 173.5, 173.6, 173.7, 173.8, 173.9; ICD10:C44.0, C44.1, C44.2, C44.3, C44.4, C44.5, C44.6, C44.7, C44.8, C44.9
[
  • 5,450 cases
  • , 54,568 controls
]
European UKB
PSS000569 PheCode:172.22; ICD9:173, 173.0, 173.1, 173.2, 173.3, 173.4, 173.5, 173.6, 173.7, 173.8, 173.9; ICD10:C44.0, C44.1, C44.2, C44.3, C44.4, C44.5, C44.6, C44.7, C44.8, C44.9
[
  • 5,450 cases
  • , 54,568 controls
]
European UKB
PSS000570 PheCode:174.1; ICD9:233.0; ICD10:C50.0, C50.1, C50.2, C50.3, C50.4, C50.5, C50.6, C50.8, C50.9, D05.1, D05.7, D05.9, Z85.3
[
  • 6,242 cases
  • , 62,289 controls
]
European UKB
PSS000571 PheCode:182; ICD9:179, 182, 182.0, 182.1, 182.8, 233.2; ICD10:C54.0, C54.1, C54.2, C54.3, C54.8, C54.9, C55, D07.0
[
  • 634 cases
  • , 6,353 controls
]
European UKB
PSS000572 PheCode:184.11; ICD9:183.0; ICD10:C56
[
  • 473 cases
  • , 4,723 controls
]
European UKB
PSS000573 PheCode:185; ICD9:185, 233.4; ICD10:C61, D07.5
[
  • 3,012 cases
  • , 29,652 controls
]
European UKB
PSS000574 PheCode:187.2; ICD9:186, 186.0, 186.9; ICD10:C62.0, C62.1, C62.9
[
  • 135 cases
  • , 1,349 controls
]
European UKB
PSS000575 PheCode:189.11; ICD9:189.0; ICD10:C64
[
  • 529 cases
  • , 5,289 controls
]
European UKB
PSS000576 PheCode:189.2; ICD9:233.7, 236.7, 239.4; ICD10:C67.0, C67.1, C67.2, C67.3, C67.4, C67.5, C67.6, C67.7, C67.8, C67.9, D09.0, D41.4
[
  • 1,229 cases
  • , 12,301 controls
]
European UKB
PSS000577 PheCode:191.11; ICD9:191, 191.0, 191.1, 191.2, 191.3, 191.4, 191.5, 191.6, 191.7, 191.8, 191.9; ICD10:C71.0, C71.1, C71.2, C71.3, C71.4, C71.5, C71.6, C71.7, C71.8, C71.9
[
  • 275 cases
  • , 2,745 controls
]
European UKB
PSS000578 PheCode:191.1; ICD9:192, 192.0, 192.1, 192.2, 192.3, 192.8, 192.9; ICD10:C70.0, C70.1, C70.9, C71.0, C71.1, C71.2, C71.3, C71.4, C71.5, C71.6, C71.7, C71.8, C71.9, C72.0, C72.1, C72.2, C72.3, C72.4, C72.5, C72.8, C72.9
[
  • 283 cases
  • , 2,827 controls
]
European UKB
PSS000579 PheCode:193; ICD9:193; ICD10:C73
[
  • 161 cases
  • , 1,617 controls
]
European UKB
PSS000580 PheCode:202.2; ICD9:200, 200.2, 200.8, 202.1, 202.2, 202.8, 202.9; ICD10:B21.1, C82.0, C82.1, C82.2, C82.7, C82.9, C83.0, C83.1, C83.2, C83.3, C83.4, C83.5, C83.6, C83.7, C83.8, C83.9, C84.0, C84.1, C84.2, C84.3, C84.4, C84.5, C85.0, C85.1, C85.7, C85.9, C96.7, C96.9, L41.2
[
  • 901 cases
  • , 9,051 controls
]
European UKB
PSS000581 PheCode:204.12; ICD9:204.1; ICD10:C91.1
[
  • 249 cases
  • , 2,509 controls
]
European UKB
PSS000582 PheCode:204.4; ICD9:203, 203.0, 203.8; ICD10:C88.1, C88.3, C88.9, C90.0, C90.2
[
  • 248 cases
  • , 2,490 controls
]
European UKB
PSS000583 Case inclusion ICD codes: ICD9=571.5, ICD9=571.8, ICD9=571.9, ICD10=K75.81, ICD10=K76.0, ICD10=K76.9
[
  • 1,106 cases
  • , 8,571 controls
]
,
42.6 % Male samples
European eMERGE
PSS000584 Controls are cases with Nonalcoholic fatty liver disease activity score <5 and cases are those with a score >5. Case inclusion ICD codes: ICD9=571.5, ICD9=571.8, ICD9=571.9, ICD10=K75.81, ICD10=K76.0, ICD10=K76.9
[
  • 79 cases
  • , 156 controls
]
European eMERGE
PSS000585 3,426 individuals,
0.0 % Male samples
European, NR SOF
PSS000585 4,741 individuals,
47.5 % Male samples
European UKB
PSS000585 6,704 individuals,
49.3 % Male samples
European, NR CLSA
PSS000585 4,657 individuals,
100.0 % Male samples
European MrOS-USA
PSS000585 1,880 individuals,
100.0 % Male samples
European
(Swedish)
MrOS-SWE
PSS000586 80,027 individuals,
47.5 % Male samples
European UKB
PSS000587 Measured using fasting blood samples 426 individuals,
46.0 % Male samples
East Asian
(Chinese)
NR Adults
PSS000588 Derived from the Friedewald’s formula 426 individuals,
46.0 % Male samples
East Asian
(Chinese)
NR Adults
PSS000589 Measured using fasting blood samples 1,941 individuals,
57.7 % Male samples
East Asian
(Chinese)
HKDB
PSS000590 Derived from the Friedewald’s formula 1,941 individuals,
57.7 % Male samples
East Asian
(Chinese)
HKDB
PSS000591 Measured using fasting blood samples 865 individuals,
57.6 % Male samples
East Asian
(Chinese)
HKDB
PSS000592 Derived from the Friedewald’s formula 865 individuals,
57.6 % Male samples
East Asian
(Chinese)
HKDB
PSS000593 Measured using fasting blood samples 4,917 individuals,
44.9 % Male samples
East Asian
(Chinese)
HKDR
PSS000594 Derived from the Friedewald’s formula 4,917 individuals,
44.9 % Male samples
East Asian
(Chinese)
HKDR
PSS000595
[
  • 1,586 cases
  • , 1,047 controls
]
,
100.0 % Male samples
African unspecified CAUG
PSS000596
[
  • 6,852 cases
  • , 193,117 controls
]
,
100.0 % Male samples
European UKB
PSS000597 In this study, cases were incident patients with primary pancreatic adenocarcinoma ascertained between 1984 and 2010 through self- report, report of next-of-kin, or death certificates and confirmed by medical record review and tumor registry data. Cases Diagnosed within 10 years of blood collection.
[
  • 304 cases
  • , 652 controls
]
,
28.1 % Male samples
European HPFS, NHS, PHS, WHI Overlap with GWAS samples (percentage unknown). Cross validation approach used (20% as testing sample)
PSS000598 In this study, cases were incident patients with primary pancreatic adenocarcinoma ascertained between 1984 and 2010 through self- report, report of next-of-kin, or death certificates and confirmed by medical record review and tumor registry data.
[
  • 500 cases
  • , 1,091 controls
]
,
33.4 % Male samples
European HPFS, NHS, PHS, WHI Overlap with GWAS samples (percentage unknown). Cross validation approach used (20% as testing sample)
PSS000599 Cases: ICD 10 code N17. Controls: no ICD10 code N17, frequency-matched by age-group and sex
[
  • 1,013 cases
  • , 2,434 controls
]
European UKB Possible overlap between GWAS cohorts and this dataset.
PSS000600 CKDi25 cases defined as >25% eGFRcrea decline during follow-up together with a movement from eGFRcrea≥60 mL/min/1.73m^2 at baseline to eGFR<60 mL/min/1.73m^2 at follow up compared to CKDi25 controls defined as eGFRcrea≥60 mL/min/1.73m^2. High risk groups had 8-14 adverse alleles. Low risk groups had 0-5 adverse alleles.
[
  • 448 cases
  • , 10,992 controls
]
European DIACORE, KORA, UKB 87.61% overlap between the CKDi25 GWAS cohort and this dataset.
PSS000601 All patients with atrial fibrillation and CHADS2 score of 2 or higher who were treated with anticoagulation. The endpoint of interest was ischemic stroke. In each trial, ischemic stroke was formally adjudicated by an independent clinical endpoint committee blinded to treatment assignment.
[
  • 395 cases
  • , 10,792 controls
]
,
60.78 % Male samples
European ENGAGE_AF-TIMI_48
PSS000602 The endpoint of interest was ischemic stroke. In each trial, ischemic stroke was formally adjudicated by an independent clinical endpoint committee blinded to treatment assignment.
[
  • 960 cases
  • , 50,328 controls
]
,
71.7 % Male samples
European ENGAGE_AF-TIMI_48, FOURIER, PEGASUS-TIMI_54, SAVOR-TIMI_53,