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 | [
|
European | — | 33 cohorts
|
iCOGS |
PSS000002 | ER-negative breast cancer | [
|
European | — | 33 cohorts
|
iCOGS |
PSS000003 | ER-positive breast cancer | [
|
European | — | 33 cohorts
|
iCOGS |
PSS000004 | Invasive breast cancer-affected | [ ,
0.0 % Male samples |
European | — | 10 cohorts
|
Prospective Test Set |
PSS000005 | ER-positive breast cancer cases | [ ,
0.0 % Male samples |
European | — | 10 cohorts
|
Prospective Test Set |
PSS000006 | ER-negative breast cancer cases | [ ,
0.0 % Male samples |
European | — | 10 cohorts
|
Prospective Test Set |
PSS000007 | Incident registry-confirmed invasive breast cancers developed | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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. | [ ,
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) | [ ,
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. | [ ,
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 | [
|
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. | [ ,
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). | [
|
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. | [
|
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. | [
|
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. | [ ,
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). | [ ,
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). | [
|
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). | [
|
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). | [ ,
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). | [ ,
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). | [ ,
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). | [ ,
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 | [ ,
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) | [ ,
46.3 % 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. | [ ,
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. | [ ,
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. | [ ,
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 | — | [
|
African unspecified | — | 7 cohorts
|
— |
PSS000031 | Cases are diagnosed with type 1 diabetes. | [
|
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) | [
|
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. | [
|
European | — | 8 cohorts
|
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
|
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
|
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 | [ ,
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. | [ ,
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. | [ ,
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. | [ ,
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 | [ ,
100.0 % Male samples |
European | — | 42 cohorts
|
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 | [ ,
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 | [ ,
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 | [ ,
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. | [ ,
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 | [
|
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. | [ ,
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. | [ ,
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 | [ ,
45.7 % Male samples |
European | — | UKB | Validation set |
PSS000059 | — | [
|
European (Finnish) |
— | FINRISK, Health2000 | — |
PSS000060 | — | [
|
European (British) |
— | NR | Immunochip |
PSS000061 | — | [
|
European (Italian) |
— | NR | — |
PSS000062 | — | [
|
European (Dutch) |
— | NR | — |
PSS000063 | — | [
|
European (British) |
— | NR | — |
PSS000064 | — | [
|
European | — | NIDDK | — |
PSS000065 | The HLA-DQ2.5-positive subset of NIDDK-CIDR | [
|
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} | [
|
European | — | MVP | MVP Cohort = 3.0 |
PSS000067 | — | [ ,
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. | [ ,
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. | [ ,
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. | [ ,
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. | [ ,
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. | [ ,
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. | [ ,
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 | [ ,
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 | [ ,
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. | [ ,
100.0 % Male samples |
European | Self-reported European ancestry | 37 cohorts
|
— |
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. | [ ,
100.0 % Male samples |
European | Self-reported European ancestry | 37 cohorts
|
— |
PSS000076 | — | [ ,
100.0 % Male samples |
European | Self-reported European ancestry | 37 cohorts
|
— |
PSS000077 | — | [ ,
100.0 % Male samples |
European | Self-reported European ancestry | 37 cohorts
|
— |
PSS000078 | — | [ ,
0.0 % Male samples |
East Asian | — | 11 cohorts
|
— |
PSS000079 | — | [ ,
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. | [ ,
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. | [ ,
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. | [ ,
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. | [
|
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. | [ ,
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. | [ ,
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) | [ ,
38.0 % Male samples |
European | — | NIA-LOAD | — |
PSS000086 | — | [
|
East Asian | — | 8 cohorts
|
— |
PSS000087 | — | [
|
European | — | 8 cohorts
|
— |
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. | [ ,
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 | [ ,
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 | [
|
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 | [
|
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 | [
|
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) | [ ,
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. | [ ,
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) | [ ,
100.0 % Male samples |
European | — | ProtecT | — |
PSS000108 | Adjudicated endpoint determined from medical notes by an outcome review committee | [ ,
0.0 % Male samples |
European | — | UKCTOCS | — |
PSS000108 | Adjudicated endpoint determined from medical notes by an outcome review committee | [ ,
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. | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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. | [ ,
47.5 % Male samples |
European | — | CHOP | — |
PSS000180 | Diagnosis of JIA by a paediatric rheumatologist. | [ ,
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. | [ ,
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 | [ ,
46.9 % Male samples |
European | — | MGI | — |
PSS000207 | PheCode 172 | [ ,
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 | [ ,
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 | [ ,
46.9 % Male samples |
European | — | MGI | — |
PSS000210 | PheCode 172.11 | [ ,
45.9 % Male samples |
European | White British Subset | UKB | — |
PSS000211 | PheCode 172 | [ ,
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 | — | [ ,
100.0 % Male samples |
European | — | DOES | — |
PSS000213 | — | [ ,
0.0 % Male samples |
European | — | DOES | — |
PSS000214 | — | [ ,
0.0 % Male samples |
European | — | DOES | — |
PSS000214 | — | [ ,
100.0 % Male samples |
European | — | DOES | — |
PSS000215 | — | [ ,
0.0 % Male samples |
European | — | DOES | — |
PSS000215 | — | [ ,
100.0 % Male samples |
European | — | DOES | — |
PSS000216 | — | [ ,
100.0 % Male samples |
European | — | DOES | — |
PSS000216 | — | [ ,
0.0 % Male samples |
European | — | DOES | — |
PSS000217 | Phenotypic information was self-reported by the individual through an online, interactive health history tool | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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. | [ ,
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 | — | [ ,
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 | — | [ ,
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 | — | [
|
Asian unspecified | — | MESA, VIRGO | Cases are from VIRGO, controls are from MESA |
PSS000228 | — | [
|
African American or Afro-Caribbean | — | MESA, VIRGO | Cases are from VIRGO, controls are from MESA |
PSS000229 | — | [
|
Hispanic or Latin American | — | MESA, VIRGO | Cases are from VIRGO, controls are from MESA |
PSS000230 | — | [
|
European | — | MESA, VIRGO | Cases are from VIRGO, controls are from MESA |
PSS000231 | Advanced primary open-angle glaucoma | [
|
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. | [ ,
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. | [
|
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
46.0 % Male samples |
European | — | BioVU | Vanderbilt University Medical Center (VUMC) biobank (BioVU) |
PSS000238 | Psychosis case subjects were identified with phecode 295 | [ ,
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 | [ ,
41.0 % Male samples |
European | — | MyCode | Geisinger Health System (GHS) |
PSS000240 | Psychosis case subjects were identified with phecode 295 | [ ,
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 | [ ,
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 | [ ,
46.0 % Male samples |
European | — | PHB | Partners HealthCare System (PHS) biobank |
PSS000244 | Psychosis case subjects were identified with phecode 295 | [ ,
46.0 % Male samples |
European | — | PHB | Partners HealthCare System (PHS) biobank |
PSS000245 | — | [ ,
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). | [
|
European | — | UKB | — |
PSS000247 | ICD-10 defined Primary open-angle glaucoma (POAG) | [
|
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). | [
|
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). | [
|
South Asian | — | UKB | — |
PSS000250 | — | [
|
European | — | 15 cohorts
|
Part of PGC29 (PMID: 29700475) |
PSS000251 | Colorectal adenocarcinoma located in the distal colon confirmed by medical records, pathology reports, or death certificate | [ ,
0.0 % Male samples |
European | — | 6 cohorts
|
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 | [ ,
100.0 % Male samples |
European | — | 6 cohorts
|
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 | [ ,
0.0 % Male samples |
European | — | 6 cohorts
|
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 | [ ,
100.0 % Male samples |
European | — | 6 cohorts
|
Training and test split not relevant to PGS |
PSS000255 | Colorectal adenocarcinoma located in the rectum confirmed by medical records, pathology reports, or death certificate | [ ,
0.0 % Male samples |
European | — | 6 cohorts
|
Training and test split not relevant to PGS |
PSS000256 | Colorectal adenocarcinoma located in the rectum confirmed by medical records, pathology reports, or death certificate | [ ,
100.0 % Male samples |
European | — | 6 cohorts
|
Training and test split not relevant to PGS |
PSS000257 | Colorectal adenocarcinoma confirmed by medical records, pathology reports, or death certificate | [ ,
0.0 % Male samples |
European | — | 6 cohorts
|
Training and test split not relevant to PGS |
PSS000258 | Colorectal adenocarcinoma confirmed by medical records, pathology reports, or death certificate | [ ,
100.0 % Male samples |
European | — | 6 cohorts
|
Training and test split not relevant to PGS |
PSS000259 | — | [ ,
57.21 % Male samples |
European (Spanish) |
— | MCC-Spain | — |
PSS000260 | — | [ ,
0.0 % Male samples |
European | — | 14 cohorts
|
— |
PSS000261 | — | [ ,
100.0 % Male samples |
European | — | 14 cohorts
|
— |
PSS000262 | Excluding participants with prevalent cancer at recruitment colorectal cancer was defined as ICD codes: C18 (except C18.1, Appendix), C19 and C20 | [ ,
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 | [ ,
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. | [ ,
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. | [ ,
60.48 % Male samples |
European | — | BLITZ | — |
PSS000271 | — | [ ,
40.85 % Male samples |
East Asian (Han Chinese) |
— | NCRCC | — |
PSS000272 | Primary tumor samples from TCGA | [
|
European | — | TCGA | — |
PSS000272 | — | [
|
European | — | eMERGE | — |
PSS000273 | Primary tumor samples from TCGA | [ ,
0.0 % Male samples |
European | — | TCGA | — |
PSS000273 | — | [ ,
0.0 % Male samples |
European | — | eMERGE | — |
PSS000274 | — | [
|
European | — | eMERGE | — |
PSS000274 | Primary tumor samples from TCGA | [
|
European | — | TCGA | — |
PSS000275 | Primary tumor samples from TCGA | [
|
European | — | TCGA | — |
PSS000275 | — | [
|
European | — | eMERGE | — |
PSS000276 | — | [
|
European | — | eMERGE | — |
PSS000276 | Primary tumor samples from TCGA | [
|
European | — | TCGA | — |
PSS000277 | Primary tumor samples from TCGA | [
|
European | — | TCGA | — |
PSS000277 | — | [
|
European | — | eMERGE | — |
PSS000278 | Primary tumor samples from TCGA | [ ,
0.0 % Male samples |
European | — | TCGA | — |
PSS000278 | — | [ ,
0.0 % Male samples |
European | — | eMERGE | — |
PSS000279 | Primary tumor samples from TCGA | [
|
European | — | TCGA | — |
PSS000279 | — | [
|
European | — | eMERGE | — |
PSS000280 | Primary tumor samples from TCGA | [ ,
100.0 % Male samples |
European | — | TCGA | — |
PSS000280 | — | [ ,
100.0 % Male samples |
European | — | eMERGE | — |
PSS000281 | — | [
|
European | — | eMERGE | — |
PSS000281 | Primary tumor samples from TCGA | [
|
European | — | TCGA | — |
PSS000282 | Primary tumor samples from TCGA | [
|
European | — | TCGA | — |
PSS000282 | — | [
|
European | — | eMERGE | — |
PSS000283 | Composite endpoint of either: myocardial infarction, coronary revascularization, death from coronary causes. | [ ,
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. | [ ,
38.0 % Male samples |
European | — | MDC-CC | — |
PSS000286 | Composite endpoint of either: myocardial infarction, coronary revascularization, death from coronary causes. | [ ,
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). | [
|
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. | [ ,
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 | [ ,
32.0 % 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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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. | [ ,
45.0 % Male samples |
European (Finnish) |
— | FINRISK | FINRISK 2002 |
PSS000328 | ACS was defined as MI, unstable angina or death due to CHD. | [ ,
46.3 % Male samples |
European (Finnish) |
— | Health2000 | — |
PSS000328 | ACS was defined as MI, unstable angina or death due to CHD. | [ ,
45.8 % Male samples |
European (Finnish) |
— | FINRISK97 | FINRISK 1997 |
PSS000328 | ACS was defined as MI, unstable angina or death due to CHD. | [ ,
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. | [ ,
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. | [ ,
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. | [ ,
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. | [ ,
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. | [ ,
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. | [ ,
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. | [ ,
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. | [ ,
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 | [ ,
31.0 % Male samples |
African American or Afro-Caribbean | — | 7 cohorts
|
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 | [ ,
31.0 % Male samples |
African American or Afro-Caribbean | — | 7 cohorts
|
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 | [ ,
44.6 % Male samples |
European | — | 11 cohorts
|
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 | [ ,
44.6 % Male samples |
European | — | 11 cohorts
|
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 | [ ,
36.2 % Male samples |
Hispanic or Latin American | — | 8 cohorts
|
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 | [ ,
36.2 % Male samples |
Hispanic or Latin American | — | 8 cohorts
|
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) | [ ,
46.41 % Male samples |
European | — | deCODE | — |
PSS000342 | Histologically confirmed papillary or follicular thyroid carcinoma (PTC) patients (including traditional PTC and follicular variant PTC) | [ ,
26.08 % Male samples |
European | — | NR | — |
PSS000343 | Cases were ascertained using ICD-10 C73 (PTC, FTC, cancer/carcinoma, and rare nonmedullary) | [ ,
45.97 % Male samples |
European | — | UKB | — |
PSS000344 | — | [
|
African American or Afro-Caribbean | — | COPDGene | — |
PSS000345 | FEV1/FVC<0.7 and FEV1<80% predicted (i.e. corresponding to GOLD 2-4 standards) | [
|
East Asian (Chinese) |
— | CKB | — |
PSS000346 | — | [
|
European | — | 6 cohorts
|
— |
PSS000347 | FEV1/FVC<0.7 and FEV1<80% predicted (i.e. corresponding to GOLD 2-4 standards) | [
|
African unspecified | — | UKB | — |
PSS000348 | FEV1/FVC<0.7 and FEV1<80% predicted (i.e. corresponding to GOLD 2-4 standards) | [
|
European | — | UKB | — |
PSS000349 | FEV1/FVC<0.7 and FEV1<80% predicted (i.e. corresponding to GOLD 2-4 standards) | [
|
Other admixed ancestry | — | UKB | — |
PSS000350 | FEV1/FVC<0.7 and FEV1<80% predicted (i.e. corresponding to GOLD 2-4 standards) | [
|
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 | [ ,
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+) | [ ,
0.0 % Male samples |
European | — | 6 cohorts
|
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); | [ ,
0.0 % Male samples |
European | — | 6 cohorts
|
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) | [ ,
0.0 % Male samples |
European | — | 6 cohorts
|
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+); | [ ,
0.0 % Male samples |
European | — | 6 cohorts
|
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-). | [ ,
0.0 % Male samples |
European | — | 6 cohorts
|
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 | [ ,
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. | [ ,
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). | [ ,
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) | [ ,
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 | [ ,
63.0 % 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. | [ ,
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 | [ ,
57.0 % Male samples |
NR | — | STOLLERY_CC | — |
PSS000382 | Coeliac disease cases were identified using either hospital admission code and/or self‐reported coeliac disease. | [
|
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 | [
|
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 | [
|
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 | [
|
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 | [
|
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 | [
|
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 | [
|
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 | [
|
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 | [
|
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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 | [ ,
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. | [ ,
0.0 % Male samples |
Hispanic or Latin American | — | 7 cohorts
|
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. | [ ,
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. | [ ,
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 | [ ,
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 | [ ,
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). | [
|
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). | [
|
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. | [ ,
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. | [ ,
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. | [ ,
50.11 % Male samples |
European | — | CHOP | — |
PSS000432 | Diagnosis of JIA by a paediatric rheumatologist. | [ ,
58.59 % Male samples |
European | — | CLARITY | Cohort description (PMID): 23153063 |
PSS000433 | Diagnosis of JIA by a paediatric rheumatologist. | [ ,
51.15 % Male samples |
European | — | CLARITY | Cohort description (PMID): 23153063 |
PSS000434 | Diagnosis of JIA by a paediatric rheumatologist. | [ ,
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. | [
|
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. | [
|
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). | [
|
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 | — | [
|
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. | [ ,
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. | [ ,
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. | [ ,
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. | [ ,
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. | [ ,
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. | [
|
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. | [ ,
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. | [ ,
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. | [
|
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. | [ ,
43.7 % Male samples |
European (Finnish) |
— | FinnGen | — |
PSS000449 | — | [ ,
47.0 % Male samples |
European | — | UKB | — |
PSS000449 | — | [ ,
44.4 % Male samples |
European | — | MAS | — |
PSS000449 | — | [ ,
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. | [ ,
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. | [ ,
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). | [ ,
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 | [
|
East Asian (Japanese) |
— | BBJ | — |
PSS000455 | Cause of death under ICD-10.CHF code | [
|
East Asian (Japanese) |
— | BBJ | — |
PSS000456 | Cause of death under ICD-10.I codes | [
|
East Asian (Japanese) |
— | BBJ | — |
PSS000457 | Cause of death under ICD-10.IHD code | [
|
East Asian (Japanese) |
— | BBJ | — |
PSS000458 | Cause of death under ICD-10.J codes | [
|
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. | [ ,
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% | [
|
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% | [
|
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. | [ ,
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 | [ ,
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 | [ ,
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. | [ ,
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. | [ ,
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). | [ ,
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 | [ ,
0.0 % Male samples |
Asian unspecified | — | 8 cohorts
|
— |
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. | [ ,
0.0 % Male samples |
Asian unspecified | — | 8 cohorts
|
— |
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. | [ ,
0.0 % Male samples |
European | — | 63 cohorts
|
— |
PSS000483 | Women (European Ancestry) diagnosed with unilateral breast cancer | [ ,
0.0 % Male samples |
European | — | 63 cohorts
|
— |
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. | [ ,
0.0 % Male samples |
European | — | 42 cohorts
|
— |
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. | [ ,
0.0 % Male samples |
European | — | 42 cohorts
|
— |
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. | [ ,
0.0 % Male samples |
European | — | 42 cohorts
|
— |
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). | [
|
NR | — | NR | — |
PSS000491 | — | [ ,
0.0 % Male samples |
Asian unspecified | — | 10 cohorts
|
— |
PSS000492 | — | [ ,
0.0 % Male samples |
Asian unspecified | — | 10 cohorts
|
— |
PSS000493 | — | [ ,
0.0 % Male samples |
Asian unspecified | — | 10 cohorts
|
— |
PSS000494 | — | [ ,
0.0 % Male samples |
South Asian (Indian) |
— | MYBRCA, SGBCC | — |
PSS000494 | — | [ ,
0.0 % Male samples |
South East Asian (Malay) |
— | MYBRCA, SGBCC | — |
PSS000494 | — | [ ,
0.0 % Male samples |
East Asian (Chinese) |
— | MYBRCA, SGBCC | — |
PSS000495 | — | [ ,
0.0 % Male samples |
East Asian (Chinese) |
— | MYBRCA, SGBCC | — |
PSS000495 | — | [ ,
0.0 % Male samples |
South Asian (Indian) |
— | MYBRCA, SGBCC | — |
PSS000495 | — | [ ,
0.0 % Male samples |
South East Asian (Malay) |
— | MYBRCA, SGBCC | — |
PSS000496 | — | [ ,
0.0 % Male samples |
South Asian (Indian) |
— | MYBRCA, SGBCC | — |
PSS000496 | — | [ ,
0.0 % Male samples |
South East Asian (Malay) |
— | MYBRCA, SGBCC | — |
PSS000496 | — | [ ,
0.0 % Male samples |
East Asian (Chinese) |
— | MYBRCA, SGBCC | — |
PSS000497 | — | [ ,
0.0 % Male samples |
Asian unspecified | — | CanBCS, LAABC, NC-BCFR | — |
PSS000498 | — | [
|
Asian unspecified | — | CanBCS, LAABC, NC-BCFR | — |
PSS000499 | — | [
|
Asian unspecified | — | CanBCS, LAABC, NC-BCFR | — |
PSS000500 | — | [ ,
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. | [ ,
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. | [ ,
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. | [ ,
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. | [ ,
47.5 % Male samples |
European | — | HNR | — |
PSS000505 | — | [
|
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. | [ ,
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. | [
|
European | — | HNR | — |
PSS000508 | — | [
|
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. | [
|
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. | [ ,
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. | [ ,
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. | [ ,
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. | [
|
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) | [ ,
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) | [ ,
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) | [ ,
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) | [ ,
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 | — | [ ,
0.0 % Male samples |
European | — | 59 cohorts
|
— |
PSS000522 | — | [ ,
0.0 % Male samples |
European | — | 59 cohorts
|
— |
PSS000523 | — | [ ,
0.0 % Male samples |
European | — | 59 cohorts
|
— |
PSS000524 | — | [ ,
0.0 % Male samples |
European | — | 59 cohorts
|
— |
PSS000525 | — | [ ,
0.0 % Male samples |
European | — | 59 cohorts
|
— |
PSS000526 | — | [ ,
0.0 % Male samples |
European | — | 59 cohorts
|
— |
PSS000527 | — | [ ,
0.0 % Male samples |
European | — | 59 cohorts
|
— |
PSS000528 | — | [ ,
0.0 % Male samples |
European | — | 59 cohorts
|
— |
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. | [ ,
0.0 % Male samples |
European | — | 61 cohorts
|
— |
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. | [ ,
0.0 % Male samples |
European | — | 61 cohorts
|
— |
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. | [ ,
0.0 % Male samples |
European | — | 61 cohorts
|
— |
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. | [ ,
0.0 % Male samples |
European | — | 61 cohorts
|
— |
PSS000533 | Any Cancer PheCode | [
|
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 | [
|
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 | [
|
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 | [
|
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 | [
|
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 | [
|
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 | [
|
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 | [
|
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 | [
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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 | [
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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 | [
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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 | [
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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 | [
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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 | [
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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 | [
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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 | [
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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 | [
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European | — | MGI | — |
PSS000550 | PheCode:184.11; ICD9CM:183.0, V10.43; ICD10CM:C56, C56.1, C56.2, C56.9 | [
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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 | [
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European | — | MGI | — |
PSS000552 | PheCode:185; ICD9CM:185, 233.4, V10.46; ICD10CM:C61, D07.5 | [
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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 | [
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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 | [
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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 | [
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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 | [
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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 | [
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European | — | MGI | — |
PSS000558 | PheCode:193; ICD9CM:193, V10.87; ICD10CM:C73 | [
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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 | [
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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 | [
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European | — | MGI | — |
PSS000561 | PheCode:204.12; ICD9CM:204.10, 204.11, 204.12; ICD10CM:C91.1, C91.10, C91.11, C91.12 | [
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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 | [
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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 | [
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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 | [
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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 | [
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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 | [
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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 | [
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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 | [
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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 | [
|
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 | [
|
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 | [
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European | — | UKB | — |
PSS000572 | PheCode:184.11; ICD9:183.0; ICD10:C56 | [
|
European | — | UKB | — |
PSS000573 | PheCode:185; ICD9:185, 233.4; ICD10:C61, D07.5 | [
|
European | — | UKB | — |
PSS000574 | PheCode:187.2; ICD9:186, 186.0, 186.9; ICD10:C62.0, C62.1, C62.9 | [
|
European | — | UKB | — |
PSS000575 | PheCode:189.11; ICD9:189.0; ICD10:C64 | [
|
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 | [
|
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 | [
|
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 | [
|
European | — | UKB | — |
PSS000579 | PheCode:193; ICD9:193; ICD10:C73 | [
|
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 | [
|
European | — | UKB | — |
PSS000581 | PheCode:204.12; ICD9:204.1; ICD10:C91.1 | [
|
European | — | UKB | — |
PSS000582 | PheCode:204.4; ICD9:203, 203.0, 203.8; ICD10:C88.1, C88.3, C88.9, C90.0, C90.2 | [
|
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 | [ ,
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 | [
|
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 | — | [ ,
100.0 % Male samples |
African unspecified | — | CAUG | — |
PSS000596 | — | [ ,
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. | [ ,
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. | [ ,
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 | [
|
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. | [
|
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. | [ ,
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. | [ ,
71.7 % Male samples |
European | — | ENGAGE_AF-TIMI_48, FOURIER, PEGASUS-TIMI_54, SAVOR-TIMI_53, |