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 7 synonyms
  • articular gout
  • chronic gout
  • gout
  • gouty arthritis
  • gouty arthropathy
  • tophaceous disease
  • tophaceous gout
Mapped terms 17 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: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
PGS003990
(dbslmm.auto.GCST008972.Gout)
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Gout gout 1,005,456
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003990/ScoringFiles/PGS003990.txt.gz
PGS004006
(lassosum.auto.GCST008972.Gout)
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Gout gout 19,101
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004006/ScoringFiles/PGS004006.txt.gz
PGS004018
(lassosum.CV.GCST008972.Gout)
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Gout gout 100,595
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004018/ScoringFiles/PGS004018.txt.gz
PGS004032
(ldpred2.auto.GCST008972.Gout)
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Gout gout 865,644
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004032/ScoringFiles/PGS004032.txt.gz
PGS004047
(ldpred2.CV.GCST008972.Gout)
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Gout gout 865,644
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004047/ScoringFiles/PGS004047.txt.gz
PGS004060
(megaprs.auto.GCST008972.Gout)
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Gout gout 677,631
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004060/ScoringFiles/PGS004060.txt.gz
PGS004076
(megaprs.CV.GCST008972.Gout)
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Gout gout 677,631
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004076/ScoringFiles/PGS004076.txt.gz
PGS004090
(prscs.auto.GCST008972.Gout)
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Gout gout 976,777
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004090/ScoringFiles/PGS004090.txt.gz
PGS004114
(pt_clump.auto.GCST008972.Gout)
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Gout gout 248
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004114/ScoringFiles/PGS004114.txt.gz
PGS004130
(pt_clump_nested.CV.GCST008972.Gout)
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Gout gout 7,279
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004130/ScoringFiles/PGS004130.txt.gz
PGS004144
(sbayesr.auto.GCST008972.Gout)
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Gout gout 822,407
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004144/ScoringFiles/PGS004144.txt.gz
PGS004160
(UKBB_EnsPGS.GCST008972.Gout)
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Gout gout 976,174
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004160/ScoringFiles/PGS004160.txt.gz
PGS004222
(GRS13_gout)
PGP000522 |
Wu Q et al. J Psychosom Res (2023)
Gout gout 13
-
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004222/ScoringFiles/PGS004222.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] : 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] : 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] : 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] : 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
: 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] : 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] : 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] : 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]
: 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] : 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
PPM020291 PGS002307
(PRS33_gout)
PSS011325|
European Ancestry|
181,559 individuals
PGP000540 |
Zhang T et al. Rheumatology (Oxford) (2023)
|Ext.
Reported Trait: Incident gout with ultraprocessed food consumption Hazard ratio (HR, high UPF consumption and highest PRS quartile vs. low UPF consumption and lowest PRS quartile): 1.9 [1.39, 2.6] age, sex, BMI, education levels, Townsend deprivation index, physical activity, smoking status, drinking status, family history of diseases (hypertension, cardiovascular disease, and diabetes), healthy diet score, ultra-processed food consumption, medical history of hypertension, diabetes, kidney disease, cancer, and cardiovascular disease, first ten genetic principal components and genotype measurement batch
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
PPM019838 PGS003990
(dbslmm.auto.GCST008972.Gout)
PSS011217|
European Ancestry|
199,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.50745
β: 0.41042
AUROC: 0.61 0 beta = log(or)/sd_pgs
PPM019839 PGS003990
(dbslmm.auto.GCST008972.Gout)
PSS011229|
European Ancestry|
257,781 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.59028
β: 0.46391
AUROC: 0.63 0 beta = log(or)/sd_pgs
PPM019841 PGS003990
(dbslmm.auto.GCST008972.Gout)
PSS011240|
South Asian Ancestry|
44,057 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.63718
β: 0.49298
AUROC: 0.64 0 beta = log(or)/sd_pgs
PPM019842 PGS003990
(dbslmm.auto.GCST008972.Gout)
PSS011256|
European Ancestry|
66,865 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.67929
β: 0.51837
AUROC: 0.64 0 beta = log(or)/sd_pgs
PPM019844 PGS003990
(dbslmm.auto.GCST008972.Gout)
PSS011284|
South Asian Ancestry|
9,326 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.46542
β: 0.38214
AUROC: 0.61 0 beta = log(or)/sd_pgs
PPM019846 PGS003990
(dbslmm.auto.GCST008972.Gout)
PSS011270|
European Ancestry|
90,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.88159
β: 0.63211
AUROC: 0.67 0 beta = log(or)/sd_pgs
PPM019901 PGS004006
(lassosum.auto.GCST008972.Gout)
PSS011217|
European Ancestry|
199,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.49846
β: 0.40444
AUROC: 0.61 0 beta = log(or)/sd_pgs
PPM019902 PGS004006
(lassosum.auto.GCST008972.Gout)
PSS011229|
European Ancestry|
257,781 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.5767
β: 0.45534
AUROC: 0.62 0 beta = log(or)/sd_pgs
PPM019904 PGS004006
(lassosum.auto.GCST008972.Gout)
PSS011240|
South Asian Ancestry|
44,057 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.75393
β: 0.56186
AUROC: 0.66 0 beta = log(or)/sd_pgs
PPM019905 PGS004006
(lassosum.auto.GCST008972.Gout)
PSS011256|
European Ancestry|
66,865 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.67964
β: 0.51858
AUROC: 0.64 0 beta = log(or)/sd_pgs
PPM019907 PGS004006
(lassosum.auto.GCST008972.Gout)
PSS011284|
South Asian Ancestry|
9,326 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.48465
β: 0.39518
AUROC: 0.61 0 beta = log(or)/sd_pgs
PPM019909 PGS004006
(lassosum.auto.GCST008972.Gout)
PSS011270|
European Ancestry|
90,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.89517
β: 0.63931
AUROC: 0.67 0 beta = log(or)/sd_pgs
PPM019912 PGS004018
(lassosum.CV.GCST008972.Gout)
PSS011240|
South Asian Ancestry|
44,057 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.79341
β: 0.58412
AUROC: 0.66 0 beta = log(or)/sd_pgs
PPM019910 PGS004018
(lassosum.CV.GCST008972.Gout)
PSS011217|
European Ancestry|
199,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.53836
β: 0.43072
AUROC: 0.62 0 beta = log(or)/sd_pgs
PPM019911 PGS004018
(lassosum.CV.GCST008972.Gout)
PSS011229|
European Ancestry|
257,781 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.63119
β: 0.48931
AUROC: 0.63 0 beta = log(or)/sd_pgs
PPM019913 PGS004018
(lassosum.CV.GCST008972.Gout)
PSS011256|
European Ancestry|
66,865 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.68276
β: 0.52044
AUROC: 0.64 0 beta = log(or)/sd_pgs
PPM019914 PGS004018
(lassosum.CV.GCST008972.Gout)
PSS011284|
South Asian Ancestry|
9,326 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.54257
β: 0.43345
AUROC: 0.62 0 beta = log(or)/sd_pgs
PPM019915 PGS004018
(lassosum.CV.GCST008972.Gout)
PSS011270|
European Ancestry|
90,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.92725
β: 0.6561
AUROC: 0.68 0 beta = log(or)/sd_pgs
PPM019865 PGS004032
(ldpred2.auto.GCST008972.Gout)
PSS011217|
European Ancestry|
199,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.47805
β: 0.39072
AUROC: 0.61 0 beta = log(or)/sd_pgs
PPM019866 PGS004032
(ldpred2.auto.GCST008972.Gout)
PSS011229|
European Ancestry|
257,781 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.53483
β: 0.42842
AUROC: 0.63 0 beta = log(or)/sd_pgs
PPM019868 PGS004032
(ldpred2.auto.GCST008972.Gout)
PSS011240|
South Asian Ancestry|
44,057 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.58389
β: 0.45989
AUROC: 0.64 0 beta = log(or)/sd_pgs
PPM019869 PGS004032
(ldpred2.auto.GCST008972.Gout)
PSS011256|
European Ancestry|
66,865 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.63475
β: 0.49149
AUROC: 0.64 0 beta = log(or)/sd_pgs
PPM019871 PGS004032
(ldpred2.auto.GCST008972.Gout)
PSS011284|
South Asian Ancestry|
9,326 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.38725
β: 0.32733
AUROC: 0.6 0 beta = log(or)/sd_pgs
PPM019873 PGS004032
(ldpred2.auto.GCST008972.Gout)
PSS011270|
European Ancestry|
90,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.91462
β: 0.64952
AUROC: 0.68 0 beta = log(or)/sd_pgs
PPM019811 PGS004047
(ldpred2.CV.GCST008972.Gout)
PSS011217|
European Ancestry|
199,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.57029
β: 0.45126
AUROC: 0.62 0 beta = log(or)/sd_pgs
PPM019812 PGS004047
(ldpred2.CV.GCST008972.Gout)
PSS011229|
European Ancestry|
257,781 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.65592
β: 0.50435
AUROC: 0.64 0 beta = log(or)/sd_pgs
PPM019814 PGS004047
(ldpred2.CV.GCST008972.Gout)
PSS011240|
South Asian Ancestry|
44,057 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.81978
β: 0.59872
AUROC: 0.66 0 beta = log(or)/sd_pgs
PPM019815 PGS004047
(ldpred2.CV.GCST008972.Gout)
PSS011256|
European Ancestry|
66,865 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.73092
β: 0.54865
AUROC: 0.65 0 beta = log(or)/sd_pgs
PPM019817 PGS004047
(ldpred2.CV.GCST008972.Gout)
PSS011284|
South Asian Ancestry|
9,326 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.57863
β: 0.45655
AUROC: 0.63 0 beta = log(or)/sd_pgs
PPM019819 PGS004047
(ldpred2.CV.GCST008972.Gout)
PSS011270|
European Ancestry|
90,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.99932
β: 0.69281
AUROC: 0.69 0 beta = log(or)/sd_pgs
PPM019880 PGS004060
(megaprs.auto.GCST008972.Gout)
PSS011217|
European Ancestry|
199,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.53017
β: 0.42538
AUROC: 0.62 0 beta = log(or)/sd_pgs
PPM019881 PGS004060
(megaprs.auto.GCST008972.Gout)
PSS011229|
European Ancestry|
257,781 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.6092
β: 0.47574
AUROC: 0.63 0 beta = log(or)/sd_pgs
PPM019883 PGS004060
(megaprs.auto.GCST008972.Gout)
PSS011240|
South Asian Ancestry|
44,057 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.8073
β: 0.59183
AUROC: 0.66 0 beta = log(or)/sd_pgs
PPM019884 PGS004060
(megaprs.auto.GCST008972.Gout)
PSS011256|
European Ancestry|
66,865 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.64854
β: 0.49989
AUROC: 0.64 0 beta = log(or)/sd_pgs
PPM019886 PGS004060
(megaprs.auto.GCST008972.Gout)
PSS011284|
South Asian Ancestry|
9,326 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.59359
β: 0.46599
AUROC: 0.63 0 beta = log(or)/sd_pgs
PPM019888 PGS004060
(megaprs.auto.GCST008972.Gout)
PSS011270|
European Ancestry|
90,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.94028
β: 0.66283
AUROC: 0.68 0 beta = log(or)/sd_pgs
PPM019874 PGS004076
(megaprs.CV.GCST008972.Gout)
PSS011217|
European Ancestry|
199,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.55746
β: 0.44305
AUROC: 0.62 0 beta = log(or)/sd_pgs
PPM019875 PGS004076
(megaprs.CV.GCST008972.Gout)
PSS011229|
European Ancestry|
257,781 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.63709
β: 0.49292
AUROC: 0.63 0 beta = log(or)/sd_pgs
PPM019876 PGS004076
(megaprs.CV.GCST008972.Gout)
PSS011240|
South Asian Ancestry|
44,057 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.76885
β: 0.57033
AUROC: 0.66 0 beta = log(or)/sd_pgs
PPM019877 PGS004076
(megaprs.CV.GCST008972.Gout)
PSS011256|
European Ancestry|
66,865 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.67754
β: 0.51733
AUROC: 0.64 0 beta = log(or)/sd_pgs
PPM019878 PGS004076
(megaprs.CV.GCST008972.Gout)
PSS011284|
South Asian Ancestry|
9,326 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.63078
β: 0.48906
AUROC: 0.63 0 beta = log(or)/sd_pgs
PPM019879 PGS004076
(megaprs.CV.GCST008972.Gout)
PSS011270|
European Ancestry|
90,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.97547
β: 0.68081
AUROC: 0.68 0 beta = log(or)/sd_pgs
PPM019892 PGS004090
(prscs.auto.GCST008972.Gout)
PSS011217|
European Ancestry|
199,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.50656
β: 0.40983
AUROC: 0.61 0 beta = log(or)/sd_pgs
PPM019893 PGS004090
(prscs.auto.GCST008972.Gout)
PSS011229|
European Ancestry|
257,781 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.57446
β: 0.45391
AUROC: 0.63 0 beta = log(or)/sd_pgs
PPM019895 PGS004090
(prscs.auto.GCST008972.Gout)
PSS011240|
South Asian Ancestry|
44,057 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.6051
β: 0.47319
AUROC: 0.65 0 beta = log(or)/sd_pgs
PPM019896 PGS004090
(prscs.auto.GCST008972.Gout)
PSS011256|
European Ancestry|
66,865 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.68882
β: 0.52403
AUROC: 0.64 0 beta = log(or)/sd_pgs
PPM019898 PGS004090
(prscs.auto.GCST008972.Gout)
PSS011284|
South Asian Ancestry|
9,326 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.42666
β: 0.35534
AUROC: 0.6 0 beta = log(or)/sd_pgs
PPM019900 PGS004090
(prscs.auto.GCST008972.Gout)
PSS011270|
European Ancestry|
90,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.93464
β: 0.65992
AUROC: 0.68 0 beta = log(or)/sd_pgs
PPM019820 PGS004114
(pt_clump.auto.GCST008972.Gout)
PSS011217|
European Ancestry|
199,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.35293
β: 0.30227
AUROC: 0.59 0 beta = log(or)/sd_pgs
PPM019821 PGS004114
(pt_clump.auto.GCST008972.Gout)
PSS011229|
European Ancestry|
257,781 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.4164
β: 0.34812
AUROC: 0.6 0 beta = log(or)/sd_pgs
PPM019823 PGS004114
(pt_clump.auto.GCST008972.Gout)
PSS011240|
South Asian Ancestry|
44,057 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.6966
β: 0.52862
AUROC: 0.64 0 beta = log(or)/sd_pgs
PPM019824 PGS004114
(pt_clump.auto.GCST008972.Gout)
PSS011256|
European Ancestry|
66,865 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.52441
β: 0.42161
AUROC: 0.62 0 beta = log(or)/sd_pgs
PPM019826 PGS004114
(pt_clump.auto.GCST008972.Gout)
PSS011284|
South Asian Ancestry|
9,326 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.39654
β: 0.334
AUROC: 0.59 0 beta = log(or)/sd_pgs
PPM019828 PGS004114
(pt_clump.auto.GCST008972.Gout)
PSS011270|
European Ancestry|
90,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.60047
β: 0.4703
AUROC: 0.63 0 beta = log(or)/sd_pgs
PPM019829 PGS004130
(pt_clump_nested.CV.GCST008972.Gout)
PSS011217|
European Ancestry|
199,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.41975
β: 0.35048
AUROC: 0.6 0 beta = log(or)/sd_pgs
PPM019830 PGS004130
(pt_clump_nested.CV.GCST008972.Gout)
PSS011229|
European Ancestry|
257,781 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.49959
β: 0.40519
AUROC: 0.61 0 beta = log(or)/sd_pgs
PPM019832 PGS004130
(pt_clump_nested.CV.GCST008972.Gout)
PSS011240|
South Asian Ancestry|
44,057 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.59226
β: 0.46516
AUROC: 0.62 0 beta = log(or)/sd_pgs
PPM019833 PGS004130
(pt_clump_nested.CV.GCST008972.Gout)
PSS011256|
European Ancestry|
66,865 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.54512
β: 0.4351
AUROC: 0.62 0 beta = log(or)/sd_pgs
PPM019835 PGS004130
(pt_clump_nested.CV.GCST008972.Gout)
PSS011284|
South Asian Ancestry|
9,326 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.47895
β: 0.39133
AUROC: 0.6 0 beta = log(or)/sd_pgs
PPM019837 PGS004130
(pt_clump_nested.CV.GCST008972.Gout)
PSS011270|
European Ancestry|
90,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.69355
β: 0.52682
AUROC: 0.65 0 beta = log(or)/sd_pgs
PPM019847 PGS004144
(sbayesr.auto.GCST008972.Gout)
PSS011217|
European Ancestry|
199,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.37049
β: 0.31517
AUROC: 0.59 0 beta = log(or)/sd_pgs
PPM019848 PGS004144
(sbayesr.auto.GCST008972.Gout)
PSS011229|
European Ancestry|
257,781 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.39569
β: 0.33339
AUROC: 0.61 0 beta = log(or)/sd_pgs
PPM019850 PGS004144
(sbayesr.auto.GCST008972.Gout)
PSS011240|
South Asian Ancestry|
44,057 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.35132
β: 0.30108
AUROC: 0.6 0 beta = log(or)/sd_pgs
PPM019851 PGS004144
(sbayesr.auto.GCST008972.Gout)
PSS011256|
European Ancestry|
66,865 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.4915
β: 0.39978
AUROC: 0.62 0 beta = log(or)/sd_pgs
PPM019853 PGS004144
(sbayesr.auto.GCST008972.Gout)
PSS011284|
South Asian Ancestry|
9,326 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.23735
β: 0.21298
AUROC: 0.57 0 beta = log(or)/sd_pgs
PPM019855 PGS004144
(sbayesr.auto.GCST008972.Gout)
PSS011270|
European Ancestry|
90,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.71118
β: 0.53718
AUROC: 0.65 0 beta = log(or)/sd_pgs
PPM019859 PGS004160
(UKBB_EnsPGS.GCST008972.Gout)
PSS011217|
European Ancestry|
199,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.58633
β: 0.46142
AUROC: 0.63 0 beta = log(or)/sd_pgs
PPM019860 PGS004160
(UKBB_EnsPGS.GCST008972.Gout)
PSS011229|
European Ancestry|
257,781 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.67706
β: 0.51704
AUROC: 0.64 0 beta = log(or)/sd_pgs
PPM019861 PGS004160
(UKBB_EnsPGS.GCST008972.Gout)
PSS011240|
South Asian Ancestry|
44,057 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.88658
β: 0.63476
AUROC: 0.67 0 beta = log(or)/sd_pgs
PPM019862 PGS004160
(UKBB_EnsPGS.GCST008972.Gout)
PSS011256|
European Ancestry|
66,865 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.73594
β: 0.55155
AUROC: 0.65 0 beta = log(or)/sd_pgs
PPM019863 PGS004160
(UKBB_EnsPGS.GCST008972.Gout)
PSS011284|
South Asian Ancestry|
9,326 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 1.63885
β: 0.49399
AUROC: 0.64 0 beta = log(or)/sd_pgs
PPM019864 PGS004160
(UKBB_EnsPGS.GCST008972.Gout)
PSS011270|
European Ancestry|
90,274 individuals
PGP000517 |
Monti M R et al. medRxiv (2023)
|Pre
Reported Trait: Gout OR: 2.04859
β: 0.71715
AUROC: 0.69 0 beta = log(or)/sd_pgs
PPM020157 PGS004222
(GRS13_gout)
PSS011298|
Multi-ancestry (including European)|
403,630 individuals
PGP000522 |
Wu Q et al. J Psychosom Res (2023)
Reported Trait: Incident gout p (interaction between PRS and sleep pattern): 0.043 Age, sex, race, Townsend deprivation index (TDI), body mass index (BMI), smoking and drinking status, history of hypertension and diabetes, uric acid, total cholesterol, estimated glomerular filtration rate (eGFR) levels, the use of diuretics medications

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
PSS011284
[
  • 206 cases
  • , 9,120 controls
]
South Asian UKB
PSS011298 382,477 individuals European 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)
PSS011298 21,153 individuals Not reported UKB
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
PSS011217
[
  • 10,646 cases
  • , 188,628 controls
]
European EB
PSS007961 1,810 individuals East Asian China (East Asia) UKB
PSS011229 M13_GOUT, ICD10: M10, ICD9: 2740
[
  • 8,759 cases
  • , 249,022 controls
]
European FinnGen
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
PSS011240
[
  • 282 cases
  • , 43,775 controls
]
South Asian G&H
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
PSS011256
[
  • 1,318 cases
  • , 65,547 controls
]
European HUNT
PSS007742 2,480 individuals African American or Afro-Caribbean Carribean UKB
PSS011325 181,559 individuals European UKB
PSS011270
[
  • 1,676 cases
  • , 88,598 controls
]
European UKB