Predicted Trait | |
Reported Trait | Multiple sclerosis |
Mapped Trait(s) | multiple sclerosis (MONDO_0005301) |
Additional Trait Information | https://biobankengine.stanford.edu/RIVAS_HG19/snpnet/HC151 |
Score Construction | |
PGS Name | GBE_HC151 |
Development Method | |
Name | snpnet |
Parameters | NR |
Variants | |
Original Genome Build | GRCh37 |
Number of Variants | 41 |
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 |
---|---|---|---|---|---|---|---|---|
PPM008850 | PSS004273| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Multiple sclerosis | — | AUROC: 0.78603 [0.68344, 0.88862] | R²: 0.07124 Incremental AUROC (full-covars): -0.04449 PGS R2 (no covariates): 0.02639 PGS AUROC (no covariates): 0.35945 [0.2174, 0.5015] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
PPM008851 | PSS004274| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Multiple sclerosis | — | AUROC: 0.65766 [0.60651, 0.7088] | R²: 0.02306 Incremental AUROC (full-covars): 0.0559 PGS R2 (no covariates): 0.01225 PGS AUROC (no covariates): 0.61627 [0.56233, 0.67022] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
PPM008852 | PSS004275| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Multiple sclerosis | — | AUROC: 0.9739 [0.9358, 1.0] | R²: 0.3229 Incremental AUROC (full-covars): 0.01955 PGS R2 (no covariates): 0.02901 PGS AUROC (no covariates): 0.64875 [0.24603, 1.0] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
PPM008853 | PSS004276| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Multiple sclerosis | — | AUROC: 0.69658 [0.66502, 0.72814] | R²: 0.04105 Incremental AUROC (full-covars): 0.08355 PGS R2 (no covariates): 0.02904 PGS AUROC (no covariates): 0.65856 [0.62428, 0.69284] |
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 |
---|---|---|---|---|---|---|---|---|
PSS004276 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |
PSS004273 | — | — | [
|
— | African unspecified | — | UKB | — |
PSS004274 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
PSS004275 | — | — | [
|
— | South Asian | — | UKB | — |