Predicted Trait | |
Reported Trait | Multiple sclerosis (time-to-event) |
Mapped Trait(s) | multiple sclerosis (MONDO_0005301) |
Additional Trait Information | https://biobankengine.stanford.edu/RIVAS_HG19/snpnet/HC810 |
Score Construction | |
PGS Name | GBE_HC810 |
Development Method | |
Name | snpnet |
Parameters | NR |
Variants | |
Original Genome Build | GRCh37 |
Number of Variants | 36 |
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 |
---|---|---|---|---|---|---|---|---|
PPM008854 | PSS004637| African Ancestry| 6,497 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE multiple sclerosis | — | AUROC: 0.8033 [0.6935, 0.91311] | PGS R2 (no covariates): 0.01095 R²: 0.10788 Incremental AUROC (full-covars): -0.03509 PGS AUROC (no covariates): 0.39974 [0.23738, 0.56211] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
PPM008855 | PSS004639| European Ancestry| 24,905 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE multiple sclerosis | — | AUROC: 0.65561 [0.60622, 0.705] | R²: 0.02347 Incremental AUROC (full-covars): 0.05454 PGS R2 (no covariates): 0.01258 PGS AUROC (no covariates): 0.61601 [0.56326, 0.66875] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
PPM008856 | PSS004640| South Asian Ancestry| 7,831 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE multiple sclerosis | — | AUROC: 0.97595 [0.94159, 1.0] | R²: 0.33555 Incremental AUROC (full-covars): 0.01648 PGS R2 (no covariates): 0.01091 PGS AUROC (no covariates): 0.55629 [0.19512, 0.91745] |
age, sex, UKB array type, Genotype PCs | Full Model & PGS R2 is estimated using Nagelkerke's method |
PPM008857 | PSS004641| European Ancestry| 67,425 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: TTE multiple sclerosis | — | AUROC: 0.6895 [0.65926, 0.71974] | R²: 0.03906 Incremental AUROC (full-covars): 0.07145 PGS R2 (no covariates): 0.02562 PGS AUROC (no covariates): 0.64688 [0.61364, 0.68013] |
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 |
---|---|---|---|---|---|---|---|---|
PSS004637 | — | — | [
|
— | African unspecified | — | UKB | — |
PSS004639 | — | — | [
|
— | European | non-white British ancestry | UKB | — |
PSS004640 | — | — | [
|
— | South Asian | — | UKB | — |
PSS004641 | — | — | [
|
— | European | white British ancestry | UKB | Testing cohort (heldout set) |