Trait: blood coagulation disease

Experimental Factor Ontology (EFO) Information
Identifier EFO_0009314
Description A condition in which there is a deviation from or interruption of the normal coagulation properties of the blood. [NCIT: C2902]
Trait category
Other disease
Synonyms 21 synonyms
  • Blood Coagulation Disorder
  • Coagulation Defect
  • Coagulation Disorder
  • Coagulation Disorder, Blood
  • Coagulation Disorders, Blood
  • Coagulopathy
  • Disorder, Blood Coagulation
  • Disorders, Blood Coagulation
  • blood coagulation disease
  • blood coagulation disorder
  • clotting disorder
  • coagulation defect
  • coagulation disorder
  • coagulation disorder, blood
  • coagulation disorders, blood
  • coagulopathy
  • disorder, blood coagulation
  • disorders, blood coagulation
  • excessive bleeding
  • postpartum coagulation defect
  • postpartum coagulation defect with delivery
Mapped terms 12 mapped terms
  • DOID:1247
  • ICD10:D68
  • ICD10:D68.9
  • ICD9:286
  • ICD9:286.9
  • ICD9:287.8
  • MESH:D001778
  • MeSH:D001778
  • NCIT:C2902
  • NCIt:C2902
  • SCTID:64779008
  • UMLS:C0005779
Child trait(s) systemic lupus erythematosus

Associated Polygenic Score(s)

Filter PGS by Participant Ancestry
Individuals included in:
G - Source of Variant Associations (GWAS)
D - Score Development/Training
E - PGS Evaluation
List of ancestries includes:
Display options:
Ancestry legend
Multi-ancestry (including European)
Multi-ancestry (excluding European)
African
East Asian
South Asian
Additional Asian Ancestries
European
Greater Middle Eastern
Hispanic or Latin American
Additional Diverse Ancestries
Not Reported
Note: This table shows all PGS for "blood coagulation disease" and any child terms of this trait in the EFO hierarchy by default.
Polygenic Score ID & Name PGS Publication ID (PGP) Reported Trait Mapped Trait(s) (Ontology) Number of Variants Ancestry distribution Scoring File (FTP Link)
PGS000196
(G-PROB_SLE)
PGP000081 |
Knevel R et al. Sci Transl Med (2020)
Systemic lupus eythematosus systemic lupus erythematosus 250
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000196/ScoringFiles/PGS000196.txt.gz
PGS000328
(GRS_SLE)
PGP000099 |
Reid S et al. Ann Rheum Dis (2019)
Systemic lupus erythematosus systemic lupus erythematosus 57
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000328/ScoringFiles/PGS000328.txt.gz
PGS000754
(PRS_SLE)
PGP000160 |
Wang YF et al. Nat Commun (2021)
Systemic lupus erythrmatosus systemic lupus erythematosus 293,684
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000754/ScoringFiles/PGS000754.txt.gz
PGS000771
(GRS95_SLEmain)
PGP000178 |
Chen L et al. Hum Mol Genet (2020)
Systemic lupus erythematosus systemic lupus erythematosus 95
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000771/ScoringFiles/PGS000771.txt.gz
PGS000772
(GRS95_SLEgen)
PGP000178 |
Chen L et al. Hum Mol Genet (2020)
Systemic lupus erythematosus systemic lupus erythematosus 95
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000772/ScoringFiles/PGS000772.txt.gz
PGS000803
(wGRS41_SLE)
PGP000192 |
Kawai VK et al. Lupus (2021)
Systemic lupus erythematosus systemic lupus erythematosus 41
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000803/ScoringFiles/PGS000803.txt.gz
PGS001033
(GBE_HC624)
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Other coagulation defects (time-to-event) blood coagulation disease 1
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001033/ScoringFiles/PGS001033.txt.gz

Performance Metrics

Disclaimer: The performance metrics are displayed as reported by the source studies. It is important to note that metrics are not necessarily comparable with each other. For example, metrics depend on the sample characteristics (described by the PGS Catalog Sample Set [PSS] ID), phenotyping, and statistical modelling. Please refer to the source publication for additional guidance on performance.

PGS Performance
Metric ID (PPM)
Evaluated Score PGS Sample Set ID
(PSS)
Performance Source Trait PGS Effect Sizes
(per SD change)
Classification Metrics Other Metrics Covariates Included in the Model PGS Performance:
Other Relevant Information
PPM000579 PGS000196
(G-PROB_SLE)
PSS000319|
European Ancestry|
243 individuals
PGP000081 |
Knevel R et al. Sci Transl Med (2020)
Reported Trait: Systemic lupus erythematosus diagnosis in patient with arthritis AUROC: 0.61 [0.27, 0.86] (Setting III: Selecting patients presenting with inflammatory arthritis at their first visit)
PPM000573 PGS000196
(G-PROB_SLE)
PSS000318|
European Ancestry|
245 individuals
PGP000081 |
Knevel R et al. Sci Transl Med (2020)
Reported Trait: Systemic lupus erythematosus diagnosis in patient with arthritis AUROC: 0.79 [0.72, 0.85] (Setting II: Assigning patient diagnoses based on medical records)
PPM000567 PGS000196
(G-PROB_SLE)
PSS000324|
Multi-ancestry (including European)|
1,211 individuals
PGP000081 |
Knevel R et al. Sci Transl Med (2020)
Reported Trait: Systemic lupus erythematosus diagnosis in patient with arthritis AUROC: 0.74 [0.7, 0.78] (Setting I: Assigning patient diagnoses based on billing codes)
PPM000882 PGS000328
(GRS_SLE)
PSS000438|
European Ancestry|
15,383 individuals
PGP000099 |
Reid S et al. Ann Rheum Dis (2019)
Reported Trait: Systemic lupus erythematosus AUROC: 0.71 Odds Ratio (OR; highest vs. lowest quartile): 7.48 [6.73, 8.32]
PPM000880 PGS000328
(GRS_SLE)
PSS000436|
European Ancestry|
3,803 individuals
PGP000099 |
Reid S et al. Ann Rheum Dis (2019)
Reported Trait: Systemic lupus erythematosus AUROC: 0.78 Odds Ratio (OR; highest vs. lowest quartile): 12.32 [9.53, 15.71]
PPM000883 PGS000328
(GRS_SLE)
PSS000436|
European Ancestry|
3,803 individuals
PGP000099 |
Reid S et al. Ann Rheum Dis (2019)
Reported Trait: Systemic Lupus damage score (SDI) OR: 1.13 [1.03, 1.24] Odds Ratio (OR; highest vs. lowest quartile): 1.47 [1.06, 2.04]
PPM000881 PGS000328
(GRS_SLE)
PSS000437|
European Ancestry|
1,001 individuals
PGP000099 |
Reid S et al. Ann Rheum Dis (2019)
Reported Trait: Systemic lupus erythematosus (onset before age 20) AUROC: 0.83
PPM000885 PGS000328
(GRS_SLE)
PSS000437|
European Ancestry|
1,001 individuals
PGP000099 |
Reid S et al. Ann Rheum Dis (2019)
Reported Trait: Nephritis in systemic lupus erythematosus patients Hazard Ratio (HR; highest vs. lowest quartile): 2.53 [1.72, 3.71]
PPM000884 PGS000328
(GRS_SLE)
PSS000436|
European Ancestry|
3,803 individuals
PGP000099 |
Reid S et al. Ann Rheum Dis (2019)
Reported Trait: Systemic lupus erythematosus (age-at-onset) Hazard Ratio (HR; highest vs. lowest quartile): 1.47 [1.22, 1.75]
PPM001919 PGS000754
(PRS_SLE)
PSS000963|
East Asian Ancestry|
2,589 individuals
PGP000160 |
Wang YF et al. Nat Commun (2021)
Reported Trait: Systemic lupus erythematosus AUROC: 0.76 [0.74, 0.78]
PPM001920 PGS000754
(PRS_SLE)
PSS000960|
European Ancestry|
1,340 individuals
PGP000160 |
Wang YF et al. Nat Commun (2021)
Reported Trait: Systemic lupus erythematosus AUROC: 0.65
PPM001921 PGS000754
(PRS_SLE)
PSS000961|
European Ancestry|
7,733 individuals
PGP000160 |
Wang YF et al. Nat Commun (2021)
Reported Trait: Systemic lupus erythematosus AUROC: 0.65
PPM001922 PGS000754
(PRS_SLE)
PSS000962|
European Ancestry|
1,112 individuals
PGP000160 |
Wang YF et al. Nat Commun (2021)
Reported Trait: Systemic lupus erythematosus AUROC: 0.62
PPM002076 PGS000754
(PRS_SLE)
PSS001027|
Additional Asian Ancestries|
3,996 individuals
PGP000188 |
Tangtanatakul P et al. Arthritis Res Ther (2020)
|Ext.
Reported Trait: Systemic lupus erythematosus AUROC: 0.76
PPM001996 PGS000771
(GRS95_SLEmain)
PSS000994|
European Ancestry|
524 individuals
PGP000178 |
Chen L et al. Hum Mol Genet (2020)
Reported Trait: Renal disease age of onset AUROC: 0.576 [0.518, 0.634] Renal disease is used as a proxy for systemic lupus erythematosus severity
PPM001998 PGS000771
(GRS95_SLEmain)
PSS000994|
European Ancestry|
524 individuals
PGP000178 |
Chen L et al. Hum Mol Genet (2020)
Reported Trait: Renal disease age of onset Odds Ratio (OR, top 20% vs bottom 20%): 3.155 [1.623, 6.133] Renal disease is used as a proxy for systemic lupus erythematosus severity
PPM001997 PGS000772
(GRS95_SLEgen)
PSS000993|
European Ancestry|
3,101 individuals
PGP000178 |
Chen L et al. Hum Mol Genet (2020)
Reported Trait: Renal disease Odds Ratio (OR, top 20% vs bottom 20%): 1.578 [1.25, 1.991] Renal disease is used as a proxy for systemic lupus erythematosus severity
PPM002100 PGS000803
(wGRS41_SLE)
PSS001038|
European Ancestry|
47,904 individuals
PGP000192 |
Kawai VK et al. Lupus (2021)
Reported Trait: Lupus (localised and systemic) OR: 1.73 [1.62, 1.85]
β: 0.546 (0.034)
PCs(1-5), median age in the electronic health record, sex
PPM002101 PGS000803
(wGRS41_SLE)
PSS001043|
European Ancestry|
18,722 individuals
PGP000192 |
Kawai VK et al. Lupus (2021)
Reported Trait: Lupus (localised and systemic) OR: 1.82 [1.66, 2.0] PCs(1-5), median age in the electronic health record, sex
PPM002102 PGS000803
(wGRS41_SLE)
PSS001035|
European Ancestry|
47,917 individuals
PGP000192 |
Kawai VK et al. Lupus (2021)
Reported Trait: Systemic lupus erythematosus OR: 1.71 [1.6, 1.82]
β: 0.534 (0.034)
PCs(1-5), median age in the electronic health record, sex
PPM002103 PGS000803
(wGRS41_SLE)
PSS001040|
European Ancestry|
18,698 individuals
PGP000192 |
Kawai VK et al. Lupus (2021)
Reported Trait: Systemic lupus erythematosus OR: 1.86 [1.69, 2.04] PCs(1-5), median age in the electronic health record, sex
PPM002104 PGS000803
(wGRS41_SLE)
PSS001037|
European Ancestry|
50,429 individuals
PGP000192 |
Kawai VK et al. Lupus (2021)
Reported Trait: Erythematous conditions OR: 1.28 [1.22, 1.34]
β: 0.246 (0.024)
PCs(1-5), median age in the electronic health record, sex
PPM002105 PGS000803
(wGRS41_SLE)
PSS001042|
European Ancestry|
21,474 individuals
PGP000192 |
Kawai VK et al. Lupus (2021)
Reported Trait: Erythematous conditions OR: 1.08 [1.04, 1.13] PCs(1-5), median age in the electronic health record, sex
PPM002106 PGS000803
(wGRS41_SLE)
PSS001034|
European Ancestry|
47,321 individuals
PGP000192 |
Kawai VK et al. Lupus (2021)
Reported Trait: Cutaneous lupus erythematosus OR: 1.79 [1.54, 2.08]
β: 0.582 (0.078)
PCs(1-5), median age in the electronic health record, sex
PPM002107 PGS000803
(wGRS41_SLE)
PSS001039|
European Ancestry|
18,422 individuals
PGP000192 |
Kawai VK et al. Lupus (2021)
Reported Trait: Cutaneous lupus erythematosus OR: 2.02 [1.71, 2.4] PCs(1-5), median age in the electronic health record, sex
PPM002108 PGS000803
(wGRS41_SLE)
PSS001036|
European Ancestry|
40,528 individuals
PGP000192 |
Kawai VK et al. Lupus (2021)
Reported Trait: Type 1 diabetes OR: 1.11 [1.06, 1.17]
β: 0.108 (0.024)
PCs(1-5), median age in the electronic health record, sex
PPM002109 PGS000803
(wGRS41_SLE)
PSS001041|
European Ancestry|
19,191 individuals
PGP000192 |
Kawai VK et al. Lupus (2021)
Reported Trait: Type 1 diabetes OR: 1.11 [1.05, 1.18] PCs(1-5), median age in the electronic health record, sex
PPM002110 PGS000803
(wGRS41_SLE)
PSS001036|
European Ancestry|
40,528 individuals
PGP000192 |
Kawai VK et al. Lupus (2021)
Reported Trait: Type 1 diabetes with renal manifestations OR: 1.41 [1.26, 1.59]
β: 0.346 (0.06)
PCs(1-5), median age in the electronic health record, sex
PPM002111 PGS000803
(wGRS41_SLE)
PSS001041|
European Ancestry|
19,191 individuals
PGP000192 |
Kawai VK et al. Lupus (2021)
Reported Trait: Type 1 diabetes with renal manifestations OR: 1.38 [1.19, 1.6] PCs(1-5), median age in the electronic health record, sex
PPM002112 PGS000803
(wGRS41_SLE)
PSS001036|
European Ancestry|
40,528 individuals
PGP000192 |
Kawai VK et al. Lupus (2021)
Reported Trait: Type 1 diabetes with opthalmic manifestations OR: 1.32 [1.16, 1.5]
β: 0.275 (0.065)
PCs(1-5), median age in the electronic health record, sex
PPM002113 PGS000803
(wGRS41_SLE)
PSS001041|
European Ancestry|
19,191 individuals
PGP000192 |
Kawai VK et al. Lupus (2021)
Reported Trait: Type 1 diabetes with opthalmic manifestations OR: 1.34 [1.18, 1.52] PCs(1-5), median age in the electronic health record, sex
PPM002114 PGS000803
(wGRS41_SLE)
PSS001036|
European Ancestry|
40,528 individuals
PGP000192 |
Kawai VK et al. Lupus (2021)
Reported Trait: Type 1 diabetes with neurological manifestations OR: 1.16 [1.06, 1.28]
β: 0.151 (0.047)
PCs(1-5), median age in the electronic health record, sex
PPM007928 PGS001033
(GBE_HC624)
PSS004546|
African Ancestry|
6,497 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: TTE other coagulation defects AUROC: 0.68816 [0.60114, 0.77518] : 0.03983
Incremental AUROC (full-covars): -0.00134
PGS R2 (no covariates): 0.00067
PGS AUROC (no covariates): 0.49799 [0.49722, 0.49876]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007929 PGS001033
(GBE_HC624)
PSS004547|
East Asian Ancestry|
1,704 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: TTE other coagulation defects AUROC: 0.8546 [0.65205, 1.0] : 0.119
Incremental AUROC (full-covars): 0.0
PGS R2 (no covariates): 8e-05
PGS AUROC (no covariates): 0.49971 [0.49913, 0.50028]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007930 PGS001033
(GBE_HC624)
PSS004548|
European Ancestry|
24,905 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: TTE other coagulation defects AUROC: 0.64742 [0.59655, 0.69828] : 0.03199
Incremental AUROC (full-covars): 0.06677
PGS R2 (no covariates): 0.0303
PGS AUROC (no covariates): 0.58367 [0.54735, 0.61999]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007931 PGS001033
(GBE_HC624)
PSS004549|
South Asian Ancestry|
7,831 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: TTE other coagulation defects AUROC: 0.66881 [0.55798, 0.77963] : 0.02584
Incremental AUROC (full-covars): 0.02341
PGS R2 (no covariates): 0.00994
PGS AUROC (no covariates): 0.54143 [0.46669, 0.61618]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007932 PGS001033
(GBE_HC624)
PSS004550|
European Ancestry|
67,425 individuals
PGP000244 |
Tanigawa Y et al. medRxiv (2021)
|Pre
Reported Trait: TTE other coagulation defects AUROC: 0.65623 [0.61832, 0.69414] : 0.05179
Incremental AUROC (full-covars): 0.12049
PGS R2 (no covariates): 0.05781
PGS AUROC (no covariates): 0.63402 [0.60616, 0.66189]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method

Evaluated Samples

PGS Sample Set ID
(PSS)
Phenotype Definitions and Methods Participant Follow-up Time Sample Numbers Age of Study Participants Sample Ancestry Additional Ancestry Description Cohort(s) Additional Sample/Cohort Information
PSS001027 Cases were individuals with systemic lupus erythematosus (SLE). All cases were carefully recruited regarding the criteria from the American College of Rheumatology (ACR). Controls included healthy individuals and individuals who had unrelated diseases including: breast cancer, periodontitis, tuberculosis, drug-induced liver injury, epileptic encephalopathy, dengue hemorrhagic fever, thalassemia, and cardiomyopathy.
[
  • 826 cases
  • , 3,170 controls
]
,
40.31 % Male samples
South East Asian
(Thai)
NR Cases were recruited from King Chulalongkorn Memorial Hospital and the Rheumatology clinic at Ramathbodi hospital. Control data was provided by the Department of Medical Science, Min- istry of Public Health, Thailand.
PSS004546
[
  • 35 cases
  • , 6,462 controls
]
African unspecified UKB
PSS004547
[
  • 3 cases
  • , 1,701 controls
]
East Asian UKB
PSS004548
[
  • 123 cases
  • , 24,782 controls
]
European non-white British ancestry UKB
PSS004549
[
  • 18 cases
  • , 7,813 controls
]
South Asian UKB
PSS004550
[
  • 268 cases
  • , 67,157 controls
]
European white British ancestry UKB Testing cohort (heldout set)
PSS000960 Cases were individuals with systemic lupus erythematosus.
[
  • 910 cases
  • , 430 controls
]
European NR
PSS000961 Cases were individuals with systemic lupus erythematosus.
[
  • 2,354 cases
  • , 5,379 controls
]
European NR
PSS000962 Cases were individuals with systemic lupus erythematosus.
[
  • 406 cases
  • , 706 controls
]
European NR
PSS000963 Cases were individuals with systemic lupus erythematosus.
[
  • 1,604 cases
  • , 985 controls
]
East Asian
(Han Chinese)
NR
PSS001034 Cases were individuals with cutaneous lupus erythematosus. Cases were identified by extracting clinical diagnoses from the electronic health record using the 9th and 10th International Statistical Classification of Diseases and Related Health Problems (ICD) Clinical Modification (CM) codes that mapped to the phenotype and transformed these ICD9/ICD10 codes into phecodes, which aggregate one or more related ICD codes into distinct diseases or traits. For each phenotype, cases were defined as individuals with 2 or more instances of the specific phecode in the electronic health record. Phecodes for lupus related disorders (systemic and cutaneous) include: 695.4, 695.41, 696.42.
[
  • 161 cases
  • , 47,160 controls
]
European BioVu
PSS000318 Setting II: Based on ICD codes and review of medical records from Partners HealthCare Biobank; controls = other non-matching arthritis diseases Median = 8.0 years
[
  • 62 cases
  • , 183 controls
]
,
32.0 % Male samples
European PHB
PSS000319 Setting III: Based on ICD codes and final diagnosis in medical records from Partners HealthCare Biobank; controls = other non-matching arthritis diseases Median = 7.0 years
[
  • 7 cases
  • , 236 controls
]
,
32.0 % Male samples
European PHB
PSS001035 Cases were individuals with systemic lupus erythematosus. Cases were identified by extracting clinical diagnoses from the electronic health record using the 9th and 10th International Statistical Classification of Diseases and Related Health Problems (ICD) Clinical Modification (CM) codes that mapped to the phenotype and transformed these ICD9/ICD10 codes into phecodes, which aggregate one or more related ICD codes into distinct diseases or traits. For each phenotype, cases were defined as individuals with 2 or more instances of the specific phecode in the electronic health record. Phecodes for lupus related disorders (systemic and cutaneous) include: 695.4, 695.41, 696.42.
[
  • 880 cases
  • , 47,037 controls
]
European BioVu
PSS001038 Cases were individuals with lupus (localised and systemic). Cases were identified by extracting clinical diagnoses from the electronic health record using the 9th and 10th International Statistical Classification of Diseases and Related Health Problems (ICD) Clinical Modification (CM) codes that mapped to the phenotype and transformed these ICD9/ICD10 codes into phecodes, which aggregate one or more related ICD codes into distinct diseases or traits. For each phenotype, cases were defined as individuals with 2 or more instances of the specific phecode in the electronic health record. Phecodes for lupus related disorders (systemic and cutaneous) include: 695.4, 695.41, 696.42.
[
  • 867 cases
  • , 47,037 controls
]
European BioVu
PSS001037 Cases were individuals with erythematosus conditions. Cases were identified by extracting clinical diagnoses from the electronic health record using the 9th and 10th International Statistical Classification of Diseases and Related Health Problems (ICD) Clinical Modification (CM) codes that mapped to the phenotype and transformed these ICD9/ICD10 codes into phecodes, which aggregate one or more related ICD codes into distinct diseases or traits. For each phenotype, cases were defined as individuals with 2 or more instances of the specific phecode in the electronic health record. Phecodes for lupus related disorders (systemic and cutaneous) include: 695.4, 695.41, 696.42.
[
  • 1,916 cases
  • , 48,513 controls
]
European BioVu
PSS001040 Cases were individuals with systemic lupus erythematosus. Cases were identified by extracting clinical diagnoses from the electronic health record using the 9th and 10th International Statistical Classification of Diseases and Related Health Problems (ICD) Clinical Modification (CM) codes that mapped to the phenotype and transformed these ICD9/ICD10 codes into phecodes, which aggregate one or more related ICD codes into distinct diseases or traits. For each phenotype, cases were defined as individuals with 2 or more instances of the specific phecode in the electronic health record. Phecodes for lupus related disorders (systemic and cutaneous) include: 695.4, 695.41, 696.42.
[
  • 393 cases
  • , 18,305 controls
]
European 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 Median = 16.0 years
[
  • 133 cases
  • , 1,078 controls
]
,
43.0 % Male samples
European, African unspecified, Asian unspecified, NR Primarily European, African and Asian ancestry eMERGE
PSS001042 Cases were individuals with erythematosus conditions. Cases were identified by extracting clinical diagnoses from the electronic health record using the 9th and 10th International Statistical Classification of Diseases and Related Health Problems (ICD) Clinical Modification (CM) codes that mapped to the phenotype and transformed these ICD9/ICD10 codes into phecodes, which aggregate one or more related ICD codes into distinct diseases or traits. For each phenotype, cases were defined as individuals with 2 or more instances of the specific phecode in the electronic health record. Phecodes for lupus related disorders (systemic and cutaneous) include: 695.4, 695.41, 696.42.
[
  • 3,029 cases
  • , 18,445 controls
]
European eMERGE
PSS001043 Cases were individuals with lupus (localised and systemic). Cases were identified by extracting clinical diagnoses from the electronic health record using the 9th and 10th International Statistical Classification of Diseases and Related Health Problems (ICD) Clinical Modification (CM) codes that mapped to the phenotype and transformed these ICD9/ICD10 codes into phecodes, which aggregate one or more related ICD codes into distinct diseases or traits.For each phenotype, cases were defined as individuals with 2 or more instances of the specific phecode in the electronic health record.Phecodes for lupus related disorders (systemic and cutaneous) include: 695.4, 695.41, 696.42.
[
  • 418 cases
  • , 18,304 controls
]
European eMERGE
PSS001039 Cases were individuals with cutaneous lupus erythematosus. Cases were identified by extracting clinical diagnoses from the electronic health record using the 9th and 10th International Statistical Classification of Diseases and Related Health Problems (ICD) Clinical Modification (CM) codes that mapped to the phenotype and transformed these ICD9/ICD10 codes into phecodes, which aggregate one or more related ICD codes into distinct diseases or traits. For each phenotype, cases were defined as individuals with 2 or more instances of the specific phecode in the electronic health record. Phecodes for lupus related disorders (systemic and cutaneous) include: 695.4, 695.41, 696.42.
[
  • 120 cases
  • , 18,302 controls
]
European eMERGE
PSS001036 Cases were individuals with type 1 diabetes. Cases were identified by extracting clinical diagnoses from the electronic health record using the 9th and 10th International Statistical Classification of Diseases and Related Health Problems (ICD) Clinical Modification (CM) codes that mapped to the phenotype and transformed these ICD9/ICD10 codes into phecodes, which aggregate one or more related ICD codes into distinct diseases or traits. For each phenotype, cases were defined as individuals with 2 or more instances of the specific phecode in the electronic health record. Phecodes for type 1 diabetes include: 250.1. Of all the type 1 diabetes cases, 276 had renal manifestations, 240 had ophthalmic manifestations and 475 had neurological manifestations
[
  • 1,881 cases
  • , 38,647 controls
]
European BioVu
PSS001041 Cases were individuals with type 1 diabetes. Cases were identified by extracting clinical diagnoses from the electronic health record using the 9th and 10th International Statistical Classification of Diseases and Related Health Problems (ICD) Clinical Modification (CM) codes that mapped to the phenotype and transformed these ICD9/ICD10 codes into phecodes, which aggregate one or more related ICD codes into distinct diseases or traits. For each phenotype, cases were defined as individuals with 2 or more instances of the specific phecode in the electronic health record. Phecodes for type 1 diabetes include: 250.1. Of the type 1 diabetes cases 165 had renal manifestations, 230 had ophthalmic manifestations and 218 had neurological manifestations.
[
  • 1,156 cases
  • , 18,035 controls
]
European eMERGE
PSS000993 All individuals had systemic lupus erythematosus. Cases are individuals that also have renal disease
[
  • 1,152 cases
  • , 1,949 controls
]
European NR
PSS000994 All individuals had systemic lupus erythematosus. Cases are individuals that also have renal disease
[
  • 146 cases
  • , 378 controls
]
European NR Cases and controls obtained by SLEGEN.
PSS000436 The discovery cohort included 1001 patients from the University clinics in Uppsala, Linköping, Karolinska Institute (Stockholm), Lund, and from the four northern-most counties in Sweden. All subjects fulfilled ≥4 ACR-82 classification criteria for SLE and were of European descent.30 Clinical data were collected from the patients’ medical files, including SDI scores, the ACR-82 classification criteria, clinical antiphospholipid syndrome (APS) diagnosis, glomerular filtration rate, chronic kidney disease (CKD) stages, ESRD, renal biopsy data and CVE, defined as myocardial infarction, ischaemic cerebrovascular disease or venous thromboembolism (VTE). Control individuals were healthy blood donors from Uppsala (Uppsala Bioresource) and Lund or population based controls from Stockholm and the four northernmost counties of Sweden.
[
  • 1,001 cases
  • , 2,802 controls
]
European Karolinska, UHU The discovery cohort included 1001 patients from the University clinics in Uppsala, Linköping, Karolinska Institute (Stockholm), Lund, and from the four northern-most counties in Sweden
PSS000437 The discovery cohort included 1001 patients from the University clinics in Uppsala, Linköping, Karolinska Institute (Stockholm), Lund, and from the four northern-most counties in Sweden. All subjects fulfilled ≥4 ACR-82 classification criteria for SLE and were of European descent.30 Clinical data were collected from the patients’ medical files, including SDI scores, the ACR-82 classification criteria, clinical antiphospholipid syndrome (APS) diagnosis, glomerular filtration rate, chronic kidney disease (CKD) stages, ESRD, renal biopsy data and CVE, defined as myocardial infarction, ischaemic cerebrovascular disease or venous thromboembolism (VTE).
[
  • 1,001 cases
  • , 0 controls
]
European Karolinska, UHU The discovery cohort included 1001 patients from the University clinics in Uppsala, Linköping, Karolinska Institute (Stockholm), Lund, and from the four northern-most counties in Sweden
PSS000438
[
  • 5,524 cases
  • , 9,859 controls
]
European NR The replication cohort is described in Langefeld et al. (PMID:28714469)