| Predicted Trait | |
| Reported Trait | Breast carcinoma |
| Mapped Trait(s) | breast carcinoma (EFO_0000305) |
| Score Construction | |
| PGS Name | SBayesR |
| Development Method | |
| Name | SBayesR |
| Parameters | SBayesR adjusts GWAS SNP effect estimates using a Bayesian approach. This method assumes that standardised SNP effects are drawn from a mixture of four distributions, allowing for greater flexibility by varying the proportion of SNPs within each distribution. With the default settings and sparse LD matrix, the scaling factor (𝛾) for the variance of each mixture component is set to 0, 0.01, 0.1, and 1, respectively. SBayesR estimates the fraction of causal SNPs directly from the GWAS summary statistics, eliminating the need for a tuning sample. |
| Variants | |
| Original Genome Build | GRCh37 |
| Number of Variants | 789,305 |
| 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 |
| Study Identifiers | Sample Numbers | Sample Ancestry | Cohort(s) |
|---|---|---|---|
GWAS Catalog: GCST010098 Europe PMC: 32424353 |
247,173 individuals | European | BCAC |
|
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 |
|---|---|---|---|---|---|---|---|---|
| PPM023140 | PSS012140| European Ancestry| 212,360 individuals |
PGP000771 | Tanha HM et al. Eur J Hum Genet (2026) |
Reported Trait: Breast Carcinoma | — | AUROC: 0.663 [0.654, 0.673] | — | - | — |
| PPM023145 | PSS012138| European Ancestry| 8,291 individuals |
PGP000771 | Tanha HM et al. Eur J Hum Genet (2026) |
Reported Trait: Breast Carcinoma | — | AUROC: 0.65 [0.611, 0.69] | — | - | — |
| PPM023155 | PSS012139| African Ancestry| 4,427 individuals |
PGP000771 | Tanha HM et al. Eur J Hum Genet (2026) |
Reported Trait: Breast Carcinoma | — | AUROC: 0.607 [0.501, 0.713] | — | - | — |
| PPM023160 | PSS012141| South Asian Ancestry| 4,435 individuals |
PGP000771 | Tanha HM et al. Eur J Hum Genet (2026) |
Reported Trait: Breast Carcinoma | — | AUROC: 0.657 [0.575, 0.74] | — | - | — |
| PPM023165 | PSS012140| European Ancestry| 212,360 individuals |
PGP000771 | Tanha HM et al. Eur J Hum Genet (2026) |
Reported Trait: Breast Carcinoma | — | AUROC: 0.667 [0.657, 0.676] | — | Age-specific absolute risk adjusted by PGS relative risk | — |
| PPM023170 | PSS012138| European Ancestry| 8,291 individuals |
PGP000771 | Tanha HM et al. Eur J Hum Genet (2026) |
Reported Trait: Breast Carcinoma | — | AUROC: 0.646 [0.607, 0.685] | — | Age-specific absolute risk adjusted by PGS relative risk | — |
| PPM023175 | PSS012137| European Ancestry| 2,654 individuals |
PGP000771 | Tanha HM et al. Eur J Hum Genet (2026) |
Reported Trait: Breast Carcinoma | — | AUROC: 0.66 [0.621, 0.699] | — | Age-specific absolute risk adjusted by PGS relative risk | — |
| PPM023180 | PSS012139| African Ancestry| 4,427 individuals |
PGP000771 | Tanha HM et al. Eur J Hum Genet (2026) |
Reported Trait: Breast Carcinoma | — | AUROC: 0.611 [0.514, 0.707] | — | Age-specific absolute risk adjusted by PGS relative risk | — |
| PPM023185 | PSS012141| South Asian Ancestry| 4,435 individuals |
PGP000771 | Tanha HM et al. Eur J Hum Genet (2026) |
Reported Trait: Breast Carcinoma | — | AUROC: 0.639 [0.556, 0.723] | — | Age-specific absolute risk adjusted by PGS relative risk | — |
| PPM023150 | PSS012137| European Ancestry| 2,654 individuals |
PGP000771 | Tanha HM et al. Eur J Hum Genet (2026) |
Reported Trait: Breast Carcinoma | — | AUROC: 0.666 [0.627, 0.706] | — | - | — |
|
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. | — | [ ,
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. | — | [ ,
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. | — | [ ,
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. | — | [ ,
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. | — | [ ,
0.0 % Male samples |
South Asian | SAS individuals were identified by PC1-PC4 from 1000G and k-means clustering. | UKB | — |