| Predicted Trait | |
| Reported Trait | Stroke |
| Mapped Trait(s) | stroke disorder (MONDO_0005098) |
| Score Construction | |
| PGS Name | PRS_stroke |
| Development Method | |
| Name | AnnoPred |
| Parameters | tier=3; p=0.01; h2 non-inf model |
| Variants | |
| Original Genome Build | hg19 |
| Number of Variants | 1,997,066 |
| Effect Weight Type | NR |
| PGS Source | |
| PGS Catalog Publication (PGP) ID | PGP000794 |
| Citation (link to publication) | Ye Y et al. Front Bioinform (2024) |
| Ancestry Distribution | |
| Source of Variant Associations (GWAS) | European: 100% 446,696 individuals (100%) |
| PGS Evaluation | European: 100% 1 Sample Sets |
| Study Identifiers | Sample Numbers | Sample Ancestry | Cohort(s) |
|---|---|---|---|
GWAS Catalog: GCST006906 Europe PMC: 29531354 |
446,696 individuals | European | 14 cohorts
|
|
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 |
|---|---|---|---|---|---|---|---|---|
| PPM030660 | PSS012229| European Ancestry| 21,092 individuals |
PGP000794 | Ye Y et al. Front Bioinform (2024) |
Reported Trait: Stroke | — | AUROC: 0.542 [0.499, 0.585] | AUROC of meta-PRS (PRS_CAD + PRS_IS + PRS_HF) for stroke: 0.523 [0.48, 0.566] | PRS_CAD (PGS Catalog ID: PGS005236) + PRS_IS (this paper) + PRS_HF (this paper) combined to derive meta-PRS | The meta-PRS was constructed by combining PRS_CAD, PRS_IS, and PRS_HF at the PRS level using weights described in the study. Implementation details are available at: https://github.com/JqiHu/meta-PRS-CVD |
|
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 |
|---|---|---|---|---|---|---|---|---|
| PSS012229 | — | — | [
|
— | European (British) |
— | UKB | — |