| Predicted Trait | |
| Reported Trait | Glioblastoma |
| Mapped Trait(s) | glioblastoma (MONDO_0018177) |
| Score Construction | |
| PGS Name | best_GBM |
| Development Method | |
| Name | Pruning and Thresholding (P+T) |
| Parameters | p < 1×10^-1, r2 < 0.1 |
| Variants | |
| Original Genome Build | GRCh37 |
| Number of Variants | 910 |
| Effect Weight Type | beta |
| PGS Source | |
| PGS Catalog Publication (PGP) ID | PGP000413 |
| Citation (link to publication) | Namba S et al. Cancer Res (2022) |
| Ancestry Distribution | |
| Source of Variant Associations (GWAS) | Not Reported: 100% 15,094 individuals (100%) |
| PGS Evaluation | European: 100% 1 Sample Sets |
| Study Identifiers | Sample Numbers | Sample Ancestry | Cohort(s) |
|---|---|---|---|
GWAS Catalog: GCST006480 Europe PMC: 30152087 |
15,094 individuals | Not reported | NR |
|
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 |
|---|---|---|---|---|---|---|---|---|
| PPM016259 | PSS010078| European Ancestry| 269,806 individuals |
PGP000413 | Namba S et al. Cancer Res (2022) |
Reported Trait: glioblastoma | — | AUROC: 0.758 | R²: 0.0216 | age, sex, top 20 genetic principal components | — |
|
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 |
|---|---|---|---|---|---|---|---|---|
| PSS010078 | C71, histology was either Giant cell glioblastoma or Glioblastoma (NOS) | — | [
|
— | European (British) |
— | UKB | Controls were samples without any cancer diagnosis or self-reported cancer |