Trait: gout

Experimental Factor Ontology (EFO) Information
Identifier EFO_0004274
Description A condition characterized by painful swelling of the joints, which is caused by deposition of urate crystals. [NCIT: C34650]
Trait category
Metabolic disorder
Synonyms 4 synonyms
  • articular gout
  • gout
  • gouty arthritis
  • gouty arthropathy
Mapped terms 18 mapped terms
  • DOID:13189
  • ICD10:M10
  • ICD10CM:M10
  • ICD9:274
  • ICD9:274.0
  • ICD9:274.00
  • ICD9:274.9
  • MESH:D006073
  • MONDO:0005393
  • MeSH:D006073
  • MedDRA:10018627
  • MedDRA:10018633
  • NCIT:C34650
  • NCIt:C34650
  • SCTID:190828008
  • SNOMEDCT:90560007
  • UMLS:C0003868
  • UMLS:C0018099

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
Polygenic Score ID & Name PGS Publication ID (PGP) Reported Trait Mapped Trait(s) (Ontology) Number of Variants Ancestry distribution Scoring File (FTP Link)
PGS000199
(G-PROB_Gout)
 PGP000081 |
Knevel R et al. Sci Transl Med (2020)
 Gout gout 250
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000199/ScoringFiles/PGS000199.txt.gz
PGS000711
(HC328)
 PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
 Gout gout 183,332
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000711/ScoringFiles/PGS000711.txt.gz - Check Terms/Licenses
PGS001248
(GBE_HC328)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Gout gout 880
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001248/ScoringFiles/PGS001248.txt.gz
PGS001249
(GBE_HC1215)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Gout (time-to-event) gout 1,796
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001249/ScoringFiles/PGS001249.txt.gz
PGS001789
(1kgeur_gbmi_leaveUKBBout_Gout_pst_eff_a1_b0.5_phiauto)
 PGP000262 |
Wang Y et al. Cell Genom (2023)
 Gout gout 910,151
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001789/ScoringFiles/PGS001789.txt.gz
PGS001822
(portability-PLR_274.1)
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Gout gout 216
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001822/ScoringFiles/PGS001822.txt.gz
PGS002030
(portability-ldpred2_274.1)
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Gout gout 163,210
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002030/ScoringFiles/PGS002030.txt.gz
PGS002307
(PRS33_gout)
 PGP000329 |
Zhang Y et al. BMC Med (2022)
 Gout gout 33
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002307/ScoringFiles/PGS002307.txt.gz
PGS002762
(Urate_prscs)
 PGP000364 |
Mars N et al. Am J Hum Genet (2022)
 Gout gout 1,092,214
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002762/ScoringFiles/PGS002762.txt.gz
PGS003329
(PRS19_gout)
 PGP000394 |
Sumpter NA et al. Arthritis Rheumatol (2022)
 Gout gout 19
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003329/ScoringFiles/PGS003329.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
PPM000582 PGS000199
(G-PROB_Gout)
 PSS000311|
European Ancestry|
243 individuals
 PGP000081 |
Knevel R et al. Sci Transl Med (2020)
 Reported Trait: Gout diagnosis in patient with arthritis — AUROC: 0.85 [0.8, 0.91] — — (Setting III: Selecting patients presenting with inflammatory arthritis at their first visit)
PPM000576 PGS000199
(G-PROB_Gout)
 PSS000310|
European Ancestry|
245 individuals
 PGP000081 |
Knevel R et al. Sci Transl Med (2020)
 Reported Trait: Gout diagnosis in patient with arthritis — AUROC: 0.82 [0.73, 0.94] — — (Setting II: Assigning patient diagnoses based on medical records)
PPM000570 PGS000199
(G-PROB_Gout)
 PSS000320|
Multi-ancestry (including European)|
1,211 individuals
 PGP000081 |
Knevel R et al. Sci Transl Med (2020)
 Reported Trait: Gout diagnosis in patient with arthritis — AUROC: 0.78 [0.75, 0.8] — — (Setting I: Assigning patient diagnoses based on billing codes)
PPM001603 PGS000711
(HC328)
 PSS000815|
European Ancestry|
87,413 individuals
 PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
 Reported Trait: Gout — AUROC: 0.7107 — Age, sex, PCs(1-10) —
PPM001616 PGS000711
(HC328)
 PSS000816|
European Ancestry|
135,300 individuals
 PGP000128 |
Sinnott-Armstrong N et al. Nat Genet (2021)
 Reported Trait: Gout HR: 1.58 [1.51, 1.65] C-index: 0.673 — Age as time scale, sex, batch, PCs(1-10) —
PPM008749 PGS001248
(GBE_HC328)
 PSS004452|
African Ancestry|
6,497 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Gout — AUROC: 0.8285 [0.79138, 0.86562] R²: 0.15624
Incremental AUROC (full-covars): 0.01741
PGS R2 (no covariates): 0.02051
PGS AUROC (no covariates): 0.62118 [0.56505, 0.67731]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008750 PGS001248
(GBE_HC328)
 PSS004453|
East Asian Ancestry|
1,704 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Gout — AUROC: 0.84973 [0.79458, 0.90489] R²: 0.22864
Incremental AUROC (full-covars): 0.02603
PGS R2 (no covariates): 0.04315
PGS AUROC (no covariates): 0.65938 [0.56975, 0.74901]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008751 PGS001248
(GBE_HC328)
 PSS004454|
European Ancestry|
24,905 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Gout — AUROC: 0.83619 [0.82126, 0.85113] R²: 0.17414
Incremental AUROC (full-covars): 0.02904
PGS R2 (no covariates): 0.03561
PGS AUROC (no covariates): 0.66092 [0.63744, 0.6844]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008752 PGS001248
(GBE_HC328)
 PSS004455|
South Asian Ancestry|
7,831 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Gout — AUROC: 0.77913 [0.74649, 0.81177] R²: 0.11671
Incremental AUROC (full-covars): 0.03258
PGS R2 (no covariates): 0.0283
PGS AUROC (no covariates): 0.63533 [0.59256, 0.6781]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008753 PGS001248
(GBE_HC328)
 PSS004456|
European Ancestry|
67,425 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Gout — AUROC: 0.81572 [0.80628, 0.82516] Incremental AUROC (full-covars): 0.04061
PGS R2 (no covariates): 0.04014
R²: 0.15436
PGS AUROC (no covariates): 0.66908 [0.65556, 0.6826]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008754 PGS001249
(GBE_HC1215)
 PSS004203|
African Ancestry|
6,497 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE gout — AUROC: 0.77537 [0.73576, 0.81498] R²: 0.12063
Incremental AUROC (full-covars): 0.01433
PGS R2 (no covariates): 0.01201
PGS AUROC (no covariates): 0.58952 [0.54447, 0.63458]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008755 PGS001249
(GBE_HC1215)
 PSS004204|
East Asian Ancestry|
1,704 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE gout — AUROC: 0.8503 [0.79897, 0.90164] R²: 0.23863
Incremental AUROC (full-covars): 0.01971
PGS R2 (no covariates): 0.02733
PGS AUROC (no covariates): 0.62617 [0.54055, 0.7118]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008756 PGS001249
(GBE_HC1215)
 PSS004205|
European Ancestry|
24,905 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE gout — AUROC: 0.81772 [0.80388, 0.83156] R²: 0.17135
Incremental AUROC (full-covars): 0.02929
PGS R2 (no covariates): 0.03724
PGS AUROC (no covariates): 0.65807 [0.63913, 0.67702]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008757 PGS001249
(GBE_HC1215)
 PSS004206|
South Asian Ancestry|
7,831 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE gout — AUROC: 0.76492 [0.73884, 0.79099] PGS AUROC (no covariates): 0.61344 [0.57941, 0.64746]
R²: 0.11928
Incremental AUROC (full-covars): 0.02377
PGS R2 (no covariates): 0.02209		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008758 PGS001249
(GBE_HC1215)
 PSS004207|
European Ancestry|
67,425 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE gout — AUROC: 0.79258 [0.7842, 0.80095] R²: 0.14867
Incremental AUROC (full-covars): 0.03784
PGS R2 (no covariates): 0.03919
PGS AUROC (no covariates): 0.65389 [0.64293, 0.66484]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM009309 PGS001789
(1kgeur_gbmi_leaveUKBBout_Gout_pst_eff_a1_b0.5_phiauto)
 PSS007699|
African Ancestry|
6,206 individuals
 PGP000262 |
Wang Y et al. Cell Genom (2023)
 Reported Trait: Gout — AUROC: 0.805 Nagelkerke's R2 (covariates regressed out): 0.01073 sex,age,age2,age*sex,age^2*sex, 20PCs —
PPM009293 PGS001789
(1kgeur_gbmi_leaveUKBBout_Gout_pst_eff_a1_b0.5_phiauto)
 PSS007712|
European Ancestry|
359,345 individuals
 PGP000262 |
Wang Y et al. Cell Genom (2023)
 Reported Trait: Gout — AUROC: 0.807 Nagelkerke's R2 (covariates regressed out): 0.03121 sex,age,age2,age*sex,age^2*sex, 20PCs —
PPM009304 PGS001789
(1kgeur_gbmi_leaveUKBBout_Gout_pst_eff_a1_b0.5_phiauto)
 PSS007703|
Additional Asian Ancestries|
8,184 individuals
 PGP000262 |
Wang Y et al. Cell Genom (2023)
 Reported Trait: Gout — AUROC: 0.78 Nagelkerke's R2 (covariates regressed out): 0.00748 sex,age,age2,age*sex,age^2*sex, 20PCs —
PPM009476 PGS001822
(portability-PLR_274.1)
 PSS009292|
European Ancestry|
19,983 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Gout — — Partial Correlation (partial-r): 0.0364 [0.0226, 0.0503] sex, age, birth date, deprivation index, 16 PCs —
PPM009477 PGS001822
(portability-PLR_274.1)
 PSS009066|
European Ancestry|
4,135 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Gout — — Partial Correlation (partial-r): 0.043 [0.0125, 0.0735] sex, age, birth date, deprivation index, 16 PCs —
PPM009478 PGS001822
(portability-PLR_274.1)
 PSS008620|
European Ancestry|
6,655 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Gout — — Partial Correlation (partial-r): 0.0538 [0.0297, 0.0777] sex, age, birth date, deprivation index, 16 PCs —
PPM009479 PGS001822
(portability-PLR_274.1)
 PSS008396|
Greater Middle Eastern Ancestry|
1,200 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Gout — — Partial Correlation (partial-r): 0.0122 [-0.0449, 0.0692] sex, age, birth date, deprivation index, 16 PCs —
PPM009480 PGS001822
(portability-PLR_274.1)
 PSS008174|
South Asian Ancestry|
6,325 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Gout — — Partial Correlation (partial-r): 0.0166 [-0.008, 0.0413] sex, age, birth date, deprivation index, 16 PCs —
PPM009481 PGS001822
(portability-PLR_274.1)
 PSS007961|
East Asian Ancestry|
1,810 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Gout — — Partial Correlation (partial-r): 0.0287 [-0.0176, 0.075] sex, age, birth date, deprivation index, 16 PCs —
PPM009482 PGS001822
(portability-PLR_274.1)
 PSS007742|
African Ancestry|
2,480 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Gout — — Partial Correlation (partial-r): 0.0314 [-0.0082, 0.0708] sex, age, birth date, deprivation index, 16 PCs —
PPM009483 PGS001822
(portability-PLR_274.1)
 PSS008845|
African Ancestry|
3,918 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Gout — — Partial Correlation (partial-r): 0.0294 [-0.002, 0.0607] sex, age, birth date, deprivation index, 16 PCs —
PPM011116 PGS002030
(portability-ldpred2_274.1)
 PSS008620|
European Ancestry|
6,655 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Gout — — Partial Correlation (partial-r): 0.0476 [0.0236, 0.0716] sex, age, birth date, deprivation index, 16 PCs —
PPM011114 PGS002030
(portability-ldpred2_274.1)
 PSS009292|
European Ancestry|
19,983 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Gout — — Partial Correlation (partial-r): 0.0415 [0.0277, 0.0554] sex, age, birth date, deprivation index, 16 PCs —
PPM011115 PGS002030
(portability-ldpred2_274.1)
 PSS009066|
European Ancestry|
4,135 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Gout — — Partial Correlation (partial-r): 0.047 [0.0165, 0.0775] sex, age, birth date, deprivation index, 16 PCs —
PPM011117 PGS002030
(portability-ldpred2_274.1)
 PSS008396|
Greater Middle Eastern Ancestry|
1,200 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Gout — — Partial Correlation (partial-r): -0.0053 [-0.0623, 0.0518] sex, age, birth date, deprivation index, 16 PCs —
PPM011118 PGS002030
(portability-ldpred2_274.1)
 PSS008174|
South Asian Ancestry|
6,325 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Gout — — Partial Correlation (partial-r): 0.0231 [-0.0015, 0.0478] sex, age, birth date, deprivation index, 16 PCs —
PPM011119 PGS002030
(portability-ldpred2_274.1)
 PSS007961|
East Asian Ancestry|
1,810 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Gout — — Partial Correlation (partial-r): 0.0262 [-0.0201, 0.0725] sex, age, birth date, deprivation index, 16 PCs —
PPM011120 PGS002030
(portability-ldpred2_274.1)
 PSS007742|
African Ancestry|
2,480 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Gout — — Partial Correlation (partial-r): 0.0336 [-0.006, 0.073] sex, age, birth date, deprivation index, 16 PCs —
PPM011121 PGS002030
(portability-ldpred2_274.1)
 PSS008845|
African Ancestry|
3,918 individuals
 PGP000263 |
Privé F et al. Am J Hum Genet (2022)
 Reported Trait: Gout — — Partial Correlation (partial-r): 0.0254 [-0.006, 0.0568] sex, age, birth date, deprivation index, 16 PCs —
PPM013045 PGS002307
(PRS33_gout)
 PSS009665|
European Ancestry|
416,481 individuals
 PGP000329 |
Zhang Y et al. BMC Med (2022)
 Reported Trait: Incident gout — — Hazard Ratio (HR, highest vs. lowest tertile): 1.77 [1.66, 1.89] Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI) —
PPM013046 PGS002307
(PRS33_gout)
 PSS009665|
European Ancestry|
416,481 individuals
 PGP000329 |
Zhang Y et al. BMC Med (2022)
 Reported Trait: Incident gout without cardiometabolic diseases — — Hazard Ratio (HR, highest vs. lowest tertile): 4.94 [3.91, 6.23] Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI), Unfavorable lifestyle —
PPM013047 PGS002307
(PRS33_gout)
 PSS009665|
European Ancestry|
416,481 individuals
 PGP000329 |
Zhang Y et al. BMC Med (2022)
 Reported Trait: Incident gout with cardiometabolic diseases — — Hazard Ratio (HR, highest vs. lowest tertile): 3.0 [2.62, 3.43] Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI), Unfavorable lifestyle —
PPM013048 PGS002307
(PRS33_gout)
 PSS009665|
European Ancestry|
416,481 individuals
 PGP000329 |
Zhang Y et al. BMC Med (2022)
 Reported Trait: Incident gout — — Hazard Ratio (HR, middle vs. lowest tertile): 1.53 [1.35, 1.74] Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI), favorable lifestyle —
PPM013049 PGS002307
(PRS33_gout)
 PSS009665|
European Ancestry|
416,481 individuals
 PGP000329 |
Zhang Y et al. BMC Med (2022)
 Reported Trait: Incident gout — — Hazard Ratio (HR, middle vs. lowest tertile): 2.39 [2.12, 2.7] Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI), unfavorable lifestyle —
PPM013050 PGS002307
(PRS33_gout)
 PSS009665|
European Ancestry|
416,481 individuals
 PGP000329 |
Zhang Y et al. BMC Med (2022)
 Reported Trait: Incident gout — — Hazard Ratio (HR, highest vs. lowest tertile): 1.98 [1.75, 2.24] Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI), favorable lifestyle —
PPM013044 PGS002307
(PRS33_gout)
 PSS009665|
European Ancestry|
416,481 individuals
 PGP000329 |
Zhang Y et al. BMC Med (2022)
 Reported Trait: Incident gout — — Hazard Ratio (HR, middle vs. lowest tertile): 1.44 [1.35, 1.54] Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI) —
PPM013051 PGS002307
(PRS33_gout)
 PSS009665|
European Ancestry|
416,481 individuals
 PGP000329 |
Zhang Y et al. BMC Med (2022)
 Reported Trait: Incident gout — — Hazard Ratio (HR, highest vs. lowest tertile): 3.13 [2.79, 3.52] Sex, age, socioeconomic status, education level, C-reactive protein, serum creatinine, cholesterol, triglyceride, cardiovascular disease, diabetes, hypertension, genetic risk, each lifestyle factor, and body mass index (BMI), unfavorable lifestyle —
PPM014962 PGS002762
(Urate_prscs)
 PSS009939|
European Ancestry|
39,444 individuals
 PGP000364 |
Mars N et al. Am J Hum Genet (2022)
 Reported Trait: Gout OR: 1.69 [1.6, 1.78] — — age, sex, 10 PCs, technical covariates —
PPM016117 PGS003329
(PRS19_gout)
 PSS010039|
European Ancestry|
5,522 individuals
 PGP000394 |
Sumpter NA et al. Arthritis Rheumatol (2022)
 Reported Trait: Age at onset of gout (in men) β: -3.61 [-4.32, -2.9] — — 10 Global PCs —
PPM016120 PGS003329
(PRS19_gout)
 PSS010039|
European Ancestry|
5,522 individuals
 PGP000394 |
Sumpter NA et al. Arthritis Rheumatol (2022)
 Reported Trait: Tophaceous Disease (in men) β: 1.15 [1.0, 1.31] — — 10 Global PCs —
PPM016123 PGS003329
(PRS19_gout)
 PSS010039|
European Ancestry|
5,522 individuals
 PGP000394 |
Sumpter NA et al. Arthritis Rheumatol (2022)
 Reported Trait: Age at onset of gout (in women) β: 0.07 [-2.32, 2.45] — — 10 Global PCs —
PPM016126 PGS003329
(PRS19_gout)
 PSS010039|
European Ancestry|
5,522 individuals
 PGP000394 |
Sumpter NA et al. Arthritis Rheumatol (2022)
 Reported Trait: Tophaceous Disease (in women) β: 0.68 [0.42, 1.1] — — 10 Global PCs —
PPM016119 PGS003329
(PRS19_gout)
 PSS010040|
Additional Diverse Ancestries|
869 individuals
 PGP000394 |
Sumpter NA et al. Arthritis Rheumatol (2022)
 Reported Trait: Age at onset of gout (in men) β: -3.51 [-5.46, -1.57] — — 10 Global PCs + 10 Oceanian PCs —
PPM016121 PGS003329
(PRS19_gout)
 PSS010038|
Additional Diverse Ancestries|
1,386 individuals
 PGP000394 |
Sumpter NA et al. Arthritis Rheumatol (2022)
 Reported Trait: Tophaceous Disease (in men) β: 2.6 [1.66, 4.06] — — 10 Global PCs + 10 Oceanian PCs —
PPM016122 PGS003329
(PRS19_gout)
 PSS010040|
Additional Diverse Ancestries|
869 individuals
 PGP000394 |
Sumpter NA et al. Arthritis Rheumatol (2022)
 Reported Trait: Tophaceous Disease (in men) β: 1.53 [1.07, 2.19] — — 10 Global PCs + 10 Oceanian PCs —
PPM016124 PGS003329
(PRS19_gout)
 PSS010038|
Additional Diverse Ancestries|
1,386 individuals
 PGP000394 |
Sumpter NA et al. Arthritis Rheumatol (2022)
 Reported Trait: Age at onset of gout (in women) β: 0.2 [-7.21, 7.62] — — 10 Global PCs + 10 Oceanian PCs —
PPM016125 PGS003329
(PRS19_gout)
 PSS010040|
Additional Diverse Ancestries|
869 individuals
 PGP000394 |
Sumpter NA et al. Arthritis Rheumatol (2022)
 Reported Trait: Age at onset of gout (in women) β: -3.33 [-9.28, 2.62] — — 10 Global PCs + 10 Oceanian PCs —
PPM016127 PGS003329
(PRS19_gout)
 PSS010038|
Additional Diverse Ancestries|
1,386 individuals
 PGP000394 |
Sumpter NA et al. Arthritis Rheumatol (2022)
 Reported Trait: Tophaceous Disease (in women) β: 1.45 [0.39, 5.36] — — 10 Global PCs + 10 Oceanian PCs —
PPM016118 PGS003329
(PRS19_gout)
 PSS010038|
Additional Diverse Ancestries|
1,386 individuals
 PGP000394 |
Sumpter NA et al. Arthritis Rheumatol (2022)
 Reported Trait: Age at onset of gout (in men) β: -6.35 [-8.91, -3.8] — — 10 Global PCs + 10 Oceanian PCs —

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
PSS000815 — — 87,413 individuals — European — UKB —
PSS000816 ICD-10 M10 —
[
  • 1,936 cases
  • , 133,364 controls
]
 — European
(Finnish)		 — FinnGen —
PSS009292 — — 19,983 individuals — European UK (+ Ireland) UKB —
PSS008396 — — 1,200 individuals — Greater Middle Eastern (Middle Eastern, North African or Persian) Iran (Middle East) UKB —
PSS009066 — — 4,135 individuals — European Poland (NE Europe) UKB —
PSS000310 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
[
  • 32 cases
  • , 213 controls
]
,
32.0 % Male samples
 — European — PHB —
PSS000311 Setting III: Based on ICD codes and final diagnosis in medical records from Partners HealthCare Biobank; controls = other non-matching arthritis diseases Median = 7.0 years
[
  • 22 cases
  • , 221 controls
]
,
32.0 % Male samples
 — European — PHB —
PSS004452 — —
[
  • 93 cases
  • , 6,404 controls
]
 — African unspecified — UKB —
PSS004453 — —
[
  • 38 cases
  • , 1,666 controls
]
 — East Asian — UKB —
PSS004454 — —
[
  • 486 cases
  • , 24,419 controls
]
 — European non-white British ancestry UKB —
PSS004455 — —
[
  • 175 cases
  • , 7,656 controls
]
 — South Asian — UKB —
PSS004456 — —
[
  • 1,484 cases
  • , 65,941 controls
]
 — European white British ancestry UKB Testing cohort (heldout set)
PSS008174 — — 6,325 individuals — South Asian India (South Asia) UKB —
PSS004203 — —
[
  • 145 cases
  • , 6,352 controls
]
 — African unspecified — UKB —
PSS004204 — —
[
  • 46 cases
  • , 1,658 controls
]
 — East Asian — UKB —
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 Median = 16.0 years
[
  • 387 cases
  • , 824 controls
]
,
43.0 % Male samples
 — European, African unspecified, Asian unspecified, NR Primarily European, African and Asian ancestry eMERGE —
PSS004205 — —
[
  • 749 cases
  • , 24,156 controls
]
 — European non-white British ancestry UKB —
PSS004206 — —
[
  • 286 cases
  • , 7,545 controls
]
 — South Asian — UKB —
PSS004207 — —
[
  • 2,391 cases
  • , 65,034 controls
]
 — European white British ancestry UKB Testing cohort (heldout set)
PSS007699 — —
[
  • 54 cases
  • , 6,151 controls
]
 — African unspecified Africa or admixed-ancestry diaspora UKB —
PSS007703 — —
[
  • 97 cases
  • , 8,086 controls
]
 — Asian unspecified Central and South Asian UKB —
PSS008845 — — 3,918 individuals — African unspecified Nigeria (West Africa) UKB —
PSS007712 — —
[
  • 3,783 cases
  • , 355,561 controls
]
 — European — UKB —
PSS007961 — — 1,810 individuals — East Asian China (East Asia) UKB —
PSS010038 — —
[
  • 682 cases
  • , 704 controls
]
 — Oceanian Aotearoa NZ Maori and Cook Island Maori ancestry NR East Polynesian
PSS010039 — —
[
  • 4,016 cases
  • , 1,506 controls
]
 — European — CLEAR Australia and Aotearoa New Zealand cohort, GlobalGout, LASSO, CRYSTAL, LIGHT
PSS010040 — —
[
  • 490 cases
  • , 379 controls
]
 — Oceanian Samoan, Tongan, Niuean, Tokelauan and Pukapukan NR West Polynesian
PSS009939 — — 39,444 individuals — European
(Finnish)		 — FinnGen —
PSS008620 — — 6,655 individuals — European Italy (South Europe) UKB —
PSS009665 Gout was ascertained based on information from self- report (Data-Field 20002, code: 1466), medical records (ICD-10 codes: M10.0, M10.2, M10.3, M10.4, M10.9), and death records (ICD-10 codes: M10.0, M10.2, M10.3, M10.4, M10.9) Median = 12.1 years
[
  • 6,206 cases
  • , 410,275 controls
]
,
45.9 % Male samples
 Mean = 56.6 years
Sd = 8.0 years		 European — UKB —
PSS007742 — — 2,480 individuals — African American or Afro-Caribbean Carribean UKB —