Polygenic Score (PGS) ID: PGS000160

Predicted Trait
Reported Trait Prostate cancer
Mapped Trait(s) prostate carcinoma (EFO_0001663)
Released in PGS: April 29, 2020

Score Details

Score Construction
PGS Name cGRS_Prostate
Variants
Original Genome Build NR
Number of Variants 79
Development Method
Name Pruning + Thresholding
Parameters GWAS significant and r2 < 0.2. PGS levels were computed as product(dosage*weight/expected risk effect), where the expected risk effect for each variant was calculated based on the risk allele frequence (f) and risk allele weight (OR) as f^2*OR^2 + 2f(1-f)OR + (1-f)^2.
PGS Source
PGS Catalog Publication (PGP) ID PGP000075
Citation (link to publication) Shi Z et al. Cancer Med (2019)

Contributing Samples

Source of Variant Associations (GWAS)
Study Identifiers Sample Numbers Sample Ancestry
GWAS Catalog: GCST002606
EuropePMC: 25217961
67,543 individuals European
GWAS Catalog: GCST002606
EuropePMC: 25217961
2,080 individuals Hispanic or Latin American
GWAS Catalog: GCST002606
EuropePMC: 25217961
6,954 individuals East Asian
GWAS Catalog: GCST002606
EuropePMC: 25217961
10,463 individuals Sub-Saharan African, African American or Afro-Caribbean
GWAS Catalog: GCST006085
EuropePMC: 29892016
140,254 individuals European
GWAS Catalog: GCST001148
EuropePMC: 21743467
13,560 individuals European
GWAS Catalog: GCST001942
EuropePMC: 23535732
22,548 individuals European
GWAS Catalog: GCST000489
EuropePMC: 19767754
37,350 individuals European
GWAS Catalog: GCST002944
EuropePMC: 26034056
3,226 individuals East Asian
GWAS Catalog: GCST002944
EuropePMC: 26034056
2,251 individuals African American or Afro-Caribbean
GWAS Catalog: GCST002944
EuropePMC: 26034056
3,629 individuals Hispanic or Latin American
GWAS Catalog: GCST002944
EuropePMC: 26034056
37,272 individuals European
GWAS Catalog: GCST000017
EuropePMC: 17401363
2,329 individuals European

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 ID)
PGS Sample Set ID
(PSS ID)
Performance Source Trait PGS Effect Sizes
(per SD change)
PGS Classification Metrics Other Metrics Covariates Included in the Model PGS Performance: Other Relevant Information
PPM000480 PSS000280 PGP000075
Shi Z et al. (2019)
Reported Trait: Prostate cancer Mean realative risk: 1.3[1.21, 1.38]
Wilcoxon test (case vs. control) p-value: 2.07e-18
PPM000491 PSS000280 PGP000075
Shi Z et al. (2019)
Reported Trait: Prostate cancer Odds Ratio (OR; high vs. average risk groups): 1.73[1.38, 2.17]

Evaluated Samples

PGS Sample Set ID
(PSS ID)
Detailed Phenotype Description Participant Follow-up Time Sample Numbers Age of Study Participants Sample Ancestry Additional Ancestry Description Cohort(s) Additional Sample/Cohort Information
PSS000280
[
  • 0 cases
  • , 6,407 controls
]
,
1.0 % Male samples
European eMERGE
PSS000280 Primary tumor samples from TCGA
[
  • 421 cases
  • , 0 controls
]
,
1.0 % Male samples
Mean = 62.0 years
Sd = 7.0 years
European TCGA