Polygenic Score (PGS) ID: PGS000966

Predicted Trait
Reported Trait Iritis
Mapped Trait(s) iritis (EFO_1000997)
Additional Trait Information https://biobankengine.stanford.edu/RIVAS_HG19/snpnet/HC26
Released in PGS Catalog: Oct. 21, 2021
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Terms and Licenses
PGS obtained from the Catalog should be cited appropriately, and used in accordance with any licensing restrictions set by the authors. See EBI Terms of Use (https://www.ebi.ac.uk/about/terms-of-use/) for additional details.

Score Details

Score Construction
PGS Name GBE_HC26
Development Method
Name snpnet
Parameters NR
Variants
Original Genome Build GRCh37
Number of Variants 1
Effect Weight Type NR
PGS Source
PGS Catalog Publication (PGP) ID PGP000244
Citation (link to publication) Tanigawa Y et al. PLoS Genet (2022)
Ancestry Distribution
Score Development/Training
European: 100%
269,704 individuals (100%)
PGS Evaluation
European: 50%
African: 25%
South Asian: 25%
4 Sample Sets

Development Samples

Score Development/Training
Study Identifiers Sample Numbers Sample Ancestry Cohort(s) Phenotype Definitions & Methods Age of Study Participants Participant Follow-up Time Additional Ancestry Description Additional Sample/Cohort Information
[
  • 146 cases
  • , 269,558 controls
]
European UKB white British ancestry

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)
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
PPM007654 PSS004399|
African Ancestry|
6,497 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Iritis AUROC: 0.92131 [0.81365, 1.0] : 0.11296
Incremental AUROC (full-covars): 0.00359
PGS R2 (no covariates): 0.14006
PGS AUROC (no covariates): 0.66325 [0.33513, 0.99137]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007655 PSS004400|
European Ancestry|
24,905 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Iritis AUROC: 0.79843 [0.66002, 0.93684] : 0.10294
Incremental AUROC (full-covars): 0.06447
PGS R2 (no covariates): 0.09763
PGS AUROC (no covariates): 0.75287 [0.61793, 0.88781]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007656 PSS004401|
South Asian Ancestry|
7,831 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Iritis AUROC: 0.961 [0.92628, 0.99572] : 0.2291
Incremental AUROC (full-covars): -0.00048
PGS R2 (no covariates): 0.00222
PGS AUROC (no covariates): 0.49061 [0.48911, 0.49211]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007657 PSS004402|
European Ancestry|
67,425 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Iritis AUROC: 0.77646 [0.69039, 0.86254] : 0.08068
Incremental AUROC (full-covars): 0.22055
PGS R2 (no covariates): 0.10834
PGS AUROC (no covariates): 0.78582 [0.71071, 0.86092]
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
PSS004399
[
  • 3 cases
  • , 6,494 controls
]
African unspecified UKB
PSS004400
[
  • 14 cases
  • , 24,891 controls
]
European non-white British ancestry UKB
PSS004401
[
  • 4 cases
  • , 7,827 controls
]
South Asian UKB
PSS004402
[
  • 40 cases
  • , 67,385 controls
]
European white British ancestry UKB Testing cohort (heldout set)