| Predicted Trait | |
| Reported Trait | Disorders of porphyrin and bilirubin metabolism (time-to-event) |
| Mapped Trait(s) | |
| Additional Trait Information | https://biobankengine.stanford.edu/RIVAS_HG19/snpnet/HC702 |
| Score Construction | |
| PGS Name | GBE_HC702 |
| Development Method | |
| Name | snpnet |
| Parameters | NR |
| Variants | |
| Original Genome Build | GRCh37 |
| Number of Variants | 5 |
| Effect Weight Type | NR |
| PGS Source | |
| PGS Catalog Publication (PGP) ID | PGP000244 |
| Citation (link to publication) | Tanigawa Y et al. PLoS Genet (2022) |
| Ancestry Distribution | |
| Score Development/Training | European: 100% 269,704 individuals (100%) |
| PGS Evaluation | European: 50% African: 25% South Asian: 25% 4 Sample Sets |
| Study Identifiers | Sample Numbers | Sample Ancestry | Cohort(s) | Phenotype Definitions & Methods | Age of Study Participants | Participant Follow-up Time | Additional Ancestry Description | Additional Sample/Cohort Information |
|---|---|---|---|---|---|---|---|---|
| — | [
|
European | UKB | — | — | — | white British ancestry | — |
|
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 |
|---|---|---|---|---|---|---|---|---|
| PPM007448 | PSS004600| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE disorders of porphyrin and bilirubin metabolism | — | AUROC: 0.87825 [0.76546, 0.99105] | R²: 0.13644 Incremental AUROC (full-covars): -0.00608 PGS R2 (no covariates): 0.01768 PGS AUROC (no covariates): 0.66722 [0.47474, 0.85969] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007449 | PSS004602| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE disorders of porphyrin and bilirubin metabolism | — | AUROC: 0.89799 [0.85782, 0.93815] | R²: 0.23107 Incremental AUROC (full-covars): 0.18304 PGS R2 (no covariates): 0.18886 PGS AUROC (no covariates): 0.85948 [0.81228, 0.90668] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007450 | PSS004603| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE disorders of porphyrin and bilirubin metabolism | — | AUROC: 0.85394 [0.77864, 0.92924] | R²: 0.15917 Incremental AUROC (full-covars): 0.14922 PGS R2 (no covariates): 0.11194 PGS AUROC (no covariates): 0.81401 [0.72659, 0.90144] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
| PPM007451 | PSS004604| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE disorders of porphyrin and bilirubin metabolism | — | AUROC: 0.90591 [0.88325, 0.92858] | R²: 0.23709 Incremental AUROC (full-covars): 0.28213 PGS R2 (no covariates): 0.21843 PGS AUROC (no covariates): 0.88697 [0.86397, 0.90997] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
|
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 |
|---|---|---|---|---|---|---|---|---|
| PSS004604 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS004600 | — | — | [
|
— | African unspecified | — | UKB | — |
| PSS004602 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
| PSS004603 | — | — | [
|
— | South Asian | — | UKB | — |