Trait: skin aging

Experimental Factor Ontology (EFO) Information
Identifier EFO_0005422
Description The gradual irreversible changes in structure of skin that occur as a result of the passage of time.. In humans, skin aging can be precipitated as a result of weather and sun exposure, and expresses through the appearance of wrinkles and localised changes in skin pigmentation
Trait category
Biological process
Mapped terms 2 mapped terms
  • MeSH:D015595
  • SNOMEDCT:26065007

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
GWAS
Dev
Eval
 Scoring File (FTP Link)
PGS001141
(GBE_BIN_FC10001757)
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Facial ageing (looking younger than you are) skin aging 7,676
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001141/ScoringFiles/PGS001141.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
PPM008432 PGS001141
(GBE_BIN_FC10001757)
 PSS003711|
African Ancestry|
6,181 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Facial ageing (Younger than you are) — AUROC: 0.62575 [0.60183, 0.64968] R²: 0.03422
Incremental AUROC (full-covars): -0.0096
PGS R2 (no covariates): 0.0
PGS AUROC (no covariates): 0.49845 [0.4741, 0.5228]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008433 PGS001141
(GBE_BIN_FC10001757)
 PSS003712|
East Asian Ancestry|
1,592 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Facial ageing (Younger than you are) — AUROC: 0.67212 [0.6348, 0.70943] R²: 0.09924
Incremental AUROC (full-covars): -0.00079
PGS R2 (no covariates): 0.00447
PGS AUROC (no covariates): 0.53362 [0.49585, 0.57138]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008434 PGS001141
(GBE_BIN_FC10001757)
 PSS003713|
European Ancestry|
23,150 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Facial ageing (Younger than you are) — AUROC: 0.62901 [0.62066, 0.63735] R²: 0.05714
Incremental AUROC (full-covars): 0.0197
PGS R2 (no covariates): 0.03222
PGS AUROC (no covariates): 0.59793 [0.58944, 0.60642]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008435 PGS001141
(GBE_BIN_FC10001757)
 PSS003714|
South Asian Ancestry|
7,175 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Facial ageing (Younger than you are) — AUROC: 0.62356 [0.60884, 0.63828] R²: 0.05339
Incremental AUROC (full-covars): 0.0021
PGS R2 (no covariates): 0.00778
PGS AUROC (no covariates): 0.54684 [0.53181, 0.56188]		 age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM008436 PGS001141
(GBE_BIN_FC10001757)
 PSS003715|
European Ancestry|
62,155 individuals
 PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
 Reported Trait: Facial ageing (Younger than you are) — AUROC: 0.6077 [0.60261, 0.61279] R²: 0.04153
Incremental AUROC (full-covars): 0.03145
PGS R2 (no covariates): 0.02196
PGS AUROC (no covariates): 0.57753 [0.57241, 0.58265]		 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
PSS003711 — —
[
  • 5,603 cases
  • , 578 controls
]
 — African unspecified — UKB —
PSS003712 — —
[
  • 1,331 cases
  • , 261 controls
]
 — East Asian — UKB —
PSS003713 — —
[
  • 17,565 cases
  • , 5,585 controls
]
 — European non-white British ancestry UKB —
PSS003714 — —
[
  • 5,252 cases
  • , 1,923 controls
]
 — South Asian — UKB —
PSS003715 — —
[
  • 46,228 cases
  • , 15,927 controls
]
 — European white British ancestry UKB Testing cohort (heldout set)