Polygenic Score (PGS) ID: PGS005349

Predicted Trait
Reported Trait Breast carcinoma
Mapped Trait(s) breast carcinoma (EFO_0000305)
Released in PGS Catalog: Feb. 26, 2026
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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 SBayesRC
Development Method
Name SBayesRC
Parameters SBayesRC extends SBayesR by incorporating functional annotations, enabling the joint analysis of all common SNPs across the genome. It utilises a multicomponent annotation-dependent mixture prior to more accurately model the distribution of SNP effects, allowing it to estimate both annotation parameters and SNP effects. SBayesRC does not require a tuning cohort.
Variants
Original Genome Build GRCh37
Number of Variants 5,387,266
Effect Weight Type beta
PGS Source
PGS Catalog Publication (PGP) ID PGP000771
Citation (link to publication) Tanha HM et al. Eur J Hum Genet (2026)
Ancestry Distribution
Source of Variant
Associations (GWAS)
European: 100%
247,173 individuals (100%)
PGS Evaluation
European: 60%
African: 20%
South Asian: 20%
5 Sample Sets

Development Samples

Source of Variant Associations (GWAS)
Study Identifiers Sample Numbers Sample Ancestry Cohort(s)
GWAS Catalog: GCST010098
Europe PMC: 32424353
 247,173 individuals European BCAC

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
PPM023141 PSS012140|
European Ancestry|
212,360 individuals
 PGP000771 |
Tanha HM et al. Eur J Hum Genet (2026)
 Reported Trait: Breast Carcinoma — AUROC: 0.639 [0.63, 0.649] — - —
PPM023146 PSS012138|
European Ancestry|
8,291 individuals
 PGP000771 |
Tanha HM et al. Eur J Hum Genet (2026)
 Reported Trait: Breast Carcinoma — AUROC: 0.647 [0.607, 0.686] — - —
PPM023151 PSS012137|
European Ancestry|
2,654 individuals
 PGP000771 |
Tanha HM et al. Eur J Hum Genet (2026)
 Reported Trait: Breast Carcinoma — AUROC: 0.727 [0.692, 0.762] — - —
PPM023156 PSS012139|
African Ancestry|
4,427 individuals
 PGP000771 |
Tanha HM et al. Eur J Hum Genet (2026)
 Reported Trait: Breast Carcinoma — AUROC: 0.605 [0.483, 0.727] — - —
PPM023161 PSS012141|
South Asian Ancestry|
4,435 individuals
 PGP000771 |
Tanha HM et al. Eur J Hum Genet (2026)
 Reported Trait: Breast Carcinoma — AUROC: 0.693 [0.614, 0.773] — - —
PPM023166 PSS012140|
European Ancestry|
212,360 individuals
 PGP000771 |
Tanha HM et al. Eur J Hum Genet (2026)
 Reported Trait: Breast Carcinoma — AUROC: 0.644 [0.634, 0.654] — Age-specific absolute risk adjusted by PGS relative risk —
PPM023171 PSS012138|
European Ancestry|
8,291 individuals
 PGP000771 |
Tanha HM et al. Eur J Hum Genet (2026)
 Reported Trait: Breast Carcinoma — AUROC: 0.645 [0.605, 0.685] — Age-specific absolute risk adjusted by PGS relative risk —
PPM023176 PSS012137|
European Ancestry|
2,654 individuals
 PGP000771 |
Tanha HM et al. Eur J Hum Genet (2026)
 Reported Trait: Breast Carcinoma — AUROC: 0.713 [0.678, 0.748] — Age-specific absolute risk adjusted by PGS relative risk —
PPM023181 PSS012139|
African Ancestry|
4,427 individuals
 PGP000771 |
Tanha HM et al. Eur J Hum Genet (2026)
 Reported Trait: Breast Carcinoma — AUROC: 0.585 [0.485, 0.685] — Age-specific absolute risk adjusted by PGS relative risk —
PPM023186 PSS012141|
South Asian Ancestry|
4,435 individuals
 PGP000771 |
Tanha HM et al. Eur J Hum Genet (2026)
 Reported Trait: Breast Carcinoma — AUROC: 0.647 [0.564, 0.731] — Age-specific absolute risk adjusted by PGS relative risk —

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
PSS012137 Linked cancer registry records were used to identify females diagnosed with invasive breast cancer (ICD-10 code: C50; ICD-9 code: 174) within five years of prediction baseline. —
[
  • 194 cases
  • , 2,460 controls
]
,
0.0 % Male samples
 European PC1-PC4 values ±3s.d. from the 1000G European cluster MCCS MCCS had a case/sub-cohort design, leading to a higher proportion of cases
PSS012138 Linked cancer registry records were used to identify females diagnosed with invasive breast cancer (ICD-10 code: C50; ICD-9 code: 174) within five years of prediction baseline. —
[
  • 176 cases
  • , 8,115 controls
]
,
0.0 % Male samples
 European PC1-PC4 values ±3s.d. from the 1000G European cluster QSKIN —
PSS012139 Linked cancer registry records were used to identify females diagnosed with invasive breast cancer (ICD-10 code: C50; ICD-9 code: 174) within five years of prediction baseline. —
[
  • 27 cases
  • , 4,400 controls
]
,
0.0 % Male samples
 African American or Afro-Caribbean AFR individuals were identified by PC1-PC4 from 1000G and k-means clustering. UKB —
PSS012140 Linked cancer registry records were used to identify females diagnosed with invasive breast cancer (ICD-10 code: C50; ICD-9 code: 174) within five years of prediction baseline. —
[
  • 3,083 cases
  • , 209,277 controls
]
,
0.0 % Male samples
 European EUR individuals were identified by PC1-PC4 from 1000G and k-means clustering. UKB —
PSS012141 Linked cancer registry records were used to identify females diagnosed with invasive breast cancer (ICD-10 code: C50; ICD-9 code: 174) within five years of prediction baseline. —
[
  • 43 cases
  • , 4,392 controls
]
,
0.0 % Male samples
 South Asian SAS individuals were identified by PC1-PC4 from 1000G and k-means clustering. UKB —