Polygenic Score (PGS) ID: PGS001318

Predicted Trait
Reported Trait Disorders of lipoprotein metabolism and other lipidaemias (time-to-event)
Mapped Trait(s) metabolic disease (EFO_0000589)
Additional Trait Information https://biobankengine.stanford.edu/RIVAS_HG19/snpnet/HC700
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_HC700
Development Method
Name snpnet
Parameters NR
Variants
Original Genome Build GRCh37
Number of Variants 7,845
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
—
[
  • 55,447 cases
  • , 214,257 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
PPM009083 PSS004595|
African Ancestry|
6,497 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE disorders of lipoprotein metabolism and other lipidaemias — AUROC: 0.72671 [0.71075, 0.74267] R²: 0.1504
Incremental AUROC (full-covars): 0.008
PGS R2 (no covariates): 0.01331
PGS AUROC (no covariates): 0.5658 [0.54786, 0.58375]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM009084 PSS004596|
East Asian Ancestry|
1,704 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE disorders of lipoprotein metabolism and other lipidaemias — AUROC: 0.72108 [0.68694, 0.75523] R²: 0.12667
Incremental AUROC (full-covars): 0.00638
PGS R2 (no covariates): 0.01352
PGS AUROC (no covariates): 0.56443 [0.52596, 0.6029]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM009085 PSS004597|
European Ancestry|
24,905 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE disorders of lipoprotein metabolism and other lipidaemias — AUROC: 0.74382 [0.73637, 0.75127] R²: 0.17729
Incremental AUROC (full-covars): 0.02969
PGS R2 (no covariates): 0.04099
PGS AUROC (no covariates): 0.61613 [0.60728, 0.62497]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM009086 PSS004598|
South Asian Ancestry|
7,831 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE disorders of lipoprotein metabolism and other lipidaemias — AUROC: 0.7175 [0.70581, 0.7292] R²: 0.17483
Incremental AUROC (full-covars): 0.01739
PGS R2 (no covariates): 0.02931
PGS AUROC (no covariates): 0.5892 [0.57589, 0.60251]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM009087 PSS004599|
European Ancestry|
67,425 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: TTE disorders of lipoprotein metabolism and other lipidaemias — AUROC: 0.73453 [0.73009, 0.73896] R²: 0.17195
Incremental AUROC (full-covars): 0.03242
PGS R2 (no covariates): 0.04352
PGS AUROC (no covariates): 0.61734 [0.61215, 0.62253]		 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
PSS004595 — —
[
  • 1,165 cases
  • , 5,332 controls
]
 — African unspecified — UKB —
PSS004596 — —
[
  • 243 cases
  • , 1,461 controls
]
 — East Asian — UKB —
PSS004597 — —
[
  • 4,635 cases
  • , 20,270 controls
]
 — European non-white British ancestry UKB —
PSS004598 — —
[
  • 2,630 cases
  • , 5,201 controls
]
 — South Asian — UKB —
PSS004599 — —
[
  • 13,783 cases
  • , 53,642 controls
]
 — European white British ancestry UKB Testing cohort (heldout set)