Polygenic Score (PGS) ID: PGS001023

Predicted Trait
Reported Trait Disorders of mineral metabolism (time-to-event)
Mapped Trait(s) mineral metabolism disease (EFO_0009556)
Additional Trait Information https://biobankengine.stanford.edu/RIVAS_HG19/snpnet/HC703
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_HC703
Development Method
Name snpnet
Parameters NR
Variants
Original Genome Build GRCh37
Number of Variants 2
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: 40%
African: 20%
East Asian: 20%
South Asian: 20%
5 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
—
[
  • 2,315 cases
  • , 267,389 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
PPM007878 PSS004605|
African Ancestry|
6,497 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE disorders of mineral metabolism — AUROC: 0.70572 [0.64003, 0.77141] R²: 0.04772
Incremental AUROC (full-covars): -0.00243
PGS R2 (no covariates): 0.00257
PGS AUROC (no covariates): 0.49279 [0.49133, 0.49424]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007879 PSS004606|
East Asian Ancestry|
1,704 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE disorders of mineral metabolism — AUROC: 0.72332 [0.56417, 0.88247] Incremental AUROC (full-covars): 0.0
R²: 0.06686
PGS R2 (no covariates): 0.00038
PGS AUROC (no covariates): 0.49882 [0.49767, 0.49998]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007880 PSS004607|
European Ancestry|
24,905 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE disorders of mineral metabolism — AUROC: 0.70459 [0.66766, 0.74152] R²: 0.07164
Incremental AUROC (full-covars): 0.05404
PGS R2 (no covariates): 0.07064
PGS AUROC (no covariates): 0.63902 [0.6046, 0.67344]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007881 PSS004608|
South Asian Ancestry|
7,831 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE disorders of mineral metabolism — AUROC: 0.60481 [0.54255, 0.66706] R²: 0.01967
Incremental AUROC (full-covars): -0.00045
PGS R2 (no covariates): 0.00194
PGS AUROC (no covariates): 0.50905 [0.4878, 0.5303]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007882 PSS004609|
European Ancestry|
67,425 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE disorders of mineral metabolism — AUROC: 0.65351 [0.63175, 0.67527] R²: 0.03407
Incremental AUROC (full-covars): 0.05096
PGS R2 (no covariates): 0.02793
PGS AUROC (no covariates): 0.57843 [0.55918, 0.59767]		 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
PSS004605 — —
[
  • 49 cases
  • , 6,448 controls
]
 — African unspecified — UKB —
PSS004606 — —
[
  • 8 cases
  • , 1,696 controls
]
 — East Asian — UKB —
PSS004607 — —
[
  • 225 cases
  • , 24,680 controls
]
 — European non-white British ancestry UKB —
PSS004608 — —
[
  • 65 cases
  • , 7,766 controls
]
 — South Asian — UKB —
PSS004609 — —
[
  • 613 cases
  • , 66,812 controls
]
 — European white British ancestry UKB Testing cohort (heldout set)