Polygenic Score (PGS) ID: PGS001071

Predicted Trait
Reported Trait Facial aging, looking 'about your age'
Mapped Trait(s) skin aging measurement (EFO_0008006)
Additional Trait Information https://biobankengine.stanford.edu/RIVAS_HG19/snpnet/BIN_FC30001757
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_BIN_FC30001757
Development Method
Name snpnet
Parameters NR
Variants
Original Genome Build GRCh37
Number of Variants 6,782
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%
248,639 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
—
[
  • 64,099 cases
  • , 184,540 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
PPM008113 PSS003884|
African Ancestry|
6,181 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Facial ageing (About your age) — AUROC: 0.60393 [0.57749, 0.63037] R²: 0.02228
Incremental AUROC (full-covars): -0.00776
PGS R2 (no covariates): 5e-05
PGS AUROC (no covariates): 0.5003 [0.47293, 0.52766]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008114 PSS003885|
East Asian Ancestry|
1,592 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Facial ageing (About your age) — AUROC: 0.63785 [0.59837, 0.67732] R²: 0.06465
Incremental AUROC (full-covars): 0.00386
PGS R2 (no covariates): 0.00756
PGS AUROC (no covariates): 0.54955 [0.50923, 0.58986]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008115 PSS003886|
European Ancestry|
23,150 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Facial ageing (About your age) — AUROC: 0.60868 [0.60014, 0.61722] R²: 0.03975
Incremental AUROC (full-covars): 0.01725
PGS R2 (no covariates): 0.02392
PGS AUROC (no covariates): 0.58543 [0.57677, 0.5941]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008116 PSS003887|
South Asian Ancestry|
7,175 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Facial ageing (About your age) — AUROC: 0.60693 [0.59118, 0.62268] R²: 0.03623
Incremental AUROC (full-covars): 0.00128
PGS R2 (no covariates): 0.0047
PGS AUROC (no covariates): 0.5379 [0.52202, 0.55377]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008117 PSS003888|
European Ancestry|
62,155 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Facial ageing (About your age) — AUROC: 0.58711 [0.58201, 0.59221] R²: 0.02661
Incremental AUROC (full-covars): 0.0251
PGS R2 (no covariates): 0.01403
PGS AUROC (no covariates): 0.56225 [0.55712, 0.56738]		 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
PSS003884 — —
[
  • 475 cases
  • , 5,706 controls
]
 — African unspecified — UKB —
PSS003885 — —
[
  • 238 cases
  • , 1,354 controls
]
 — East Asian — UKB —
PSS003886 — —
[
  • 5,384 cases
  • , 17,766 controls
]
 — European non-white British ancestry UKB —
PSS003887 — —
[
  • 1,618 cases
  • , 5,557 controls
]
 — South Asian — UKB —
PSS003888 — —
[
  • 16,027 cases
  • , 46,128 controls
]
 — European white British ancestry UKB Testing cohort (heldout set)