Polygenic Score (PGS) ID: PGS001040

Predicted Trait
Reported Trait Non melanoma skin cancer
Mapped Trait(s) non-melanoma skin carcinoma (EFO_0009260)
Additional Trait Information https://biobankengine.stanford.edu/RIVAS_HG19/snpnet/cancer1060
Released in PGS Catalog: Oct. 21, 2021
Download Score FTP directory
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_cancer1060
Development Method
Name snpnet
Parameters NR
Variants
Original Genome Build GRCh37
Number of Variants 1,610
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: 16.7%
East Asian: 16.7%
South Asian: 16.7%
6 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
[
  • 16,566 cases
  • , 253,138 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
PPM007958 PSS007651|
African Ancestry|
6,497 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Non-melanoma skin cancer AUROC: 0.80478 [0.72556, 0.884] : 0.07029
Incremental AUROC (full-covars): -0.00066
PGS R2 (no covariates): 0.00133
PGS AUROC (no covariates): 0.54127 [0.39017, 0.69237]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007959 PSS007652|
East Asian Ancestry|
1,704 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Non-melanoma skin cancer AUROC: 0.86455 [0.80574, 0.92335] : 0.12918
Incremental AUROC (full-covars): -0.00442
PGS R2 (no covariates): 0.00152
PGS AUROC (no covariates): 0.4523 [0.1694, 0.73519]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007960 PSS007653|
European Ancestry|
24,905 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Non-melanoma skin cancer AUROC: 0.73342 [0.72065, 0.74619] : 0.10751
Incremental AUROC (full-covars): 0.0378
PGS R2 (no covariates): 0.05185
PGS AUROC (no covariates): 0.66327 [0.64889, 0.67765]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007961 PSS007654|
South Asian Ancestry|
7,831 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Non-melanoma skin cancer AUROC: 0.76366 [0.66832, 0.85901] : 0.06447
Incremental AUROC (full-covars): -0.00934
PGS R2 (no covariates): 0.00078
PGS AUROC (no covariates): 0.47181 [0.35611, 0.58752]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM007962 PSS007655|
European Ancestry|
67,425 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Non-melanoma skin cancer AUROC: 0.70656 [0.69863, 0.7145] : 0.08615
Incremental AUROC (full-covars): 0.04717
PGS R2 (no covariates): 0.03949
PGS AUROC (no covariates): 0.64209 [0.6334, 0.65078]
age, sex, UKB array type, Genotype PCs Full Model & PGS R2 is estimated using Nagelkerke's method
PPM018463 PSS010980|
European Ancestry|
4,797 individuals
PGP000467 |
Farré X et al. Genes (Basel) (2023)
|Ext.
Reported Trait: Ease sunburn β: 0.08836 : 0.01475
PPM018465 PSS010980|
European Ancestry|
4,797 individuals
PGP000467 |
Farré X et al. Genes (Basel) (2023)
|Ext.
Reported Trait: Fitzpatrick scale β: -0.0689 : 0.03786
PPM018459 PSS010980|
European Ancestry|
4,797 individuals
PGP000467 |
Farré X et al. Genes (Basel) (2023)
|Ext.
Reported Trait: Eye colour β: -0.11302 : 0.0106
PPM018460 PSS010980|
European Ancestry|
4,797 individuals
PGP000467 |
Farré X et al. Genes (Basel) (2023)
|Ext.
Reported Trait: Skin colour β: -0.05462 : 0.01757
PPM018461 PSS010980|
European Ancestry|
4,797 individuals
PGP000467 |
Farré X et al. Genes (Basel) (2023)
|Ext.
Reported Trait: Freckles β: 0.09955 : 0.02643
PPM018462 PSS010980|
European Ancestry|
4,797 individuals
PGP000467 |
Farré X et al. Genes (Basel) (2023)
|Ext.
Reported Trait: Ease suntan β: -0.06804 : 0.01892
PPM018464 PSS010980|
European Ancestry|
4,797 individuals
PGP000467 |
Farré X et al. Genes (Basel) (2023)
|Ext.
Reported Trait: Phototype score β: -1.51455 : 0.04441
PPM018466 PSS010980|
European Ancestry|
4,797 individuals
PGP000467 |
Farré X et al. Genes (Basel) (2023)
|Ext.
Reported Trait: Blond hair β: 1.14835 pseudo R²: 0.01006

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
PSS007651
[
  • 11 cases
  • , 6,486 controls
]
African unspecified UKB
PSS007652
[
  • 6 cases
  • , 1,698 controls
]
East Asian UKB
PSS007653
[
  • 1,442 cases
  • , 23,463 controls
]
European non-white British ancestry UKB
PSS007654
[
  • 18 cases
  • , 7,813 controls
]
South Asian UKB
PSS007655
[
  • 4,141 cases
  • , 63,284 controls
]
European white British ancestry UKB Testing cohort (heldout set)
PSS010980 4,797 individuals European NR GCAT