Predicted Trait | |
Reported Trait | type 2 diabetes |
Mapped Trait(s) | type 2 diabetes mellitus (MONDO_0005148) |
Score Construction | |
PGS Name | PRScsx_T2D_LAT_EASweights |
Development Method | |
Name | PRS-CSx |
Parameters | The polygenicity value that maximized the PRS performance in the score development cohort was 1e-02. To calculate a polygenic risk score in any genotyped individual, please follow the next steps. First, use the ancestry-specific weights (PRScsx_T2D_LAT_EURweights, PRScsx_T2D_LAT_EASweights and PRScsx_T2D_LAT_LATweights) to calculate 3 separate scores for each genotyped individual. Second, standardize each score (mean of zero and standard deviation of 1) and combine the three of them to calculate a single score value: metascore=(zscoreEUR* 0.531117)+(zscoreEAS*0.5690198)+(zscoreLAT*0.1465538). Third, standardize the metascore before applying. Evaluation of each ancestry-specific score separately is not the intended use of this PRS-CSx polygenic score. Note that performance reported is based on the combination of the 3 ancestry-specific scores (PRScsx_T2D_LAT_EURweights,PRScsx_T2D_LAT_EASweights,PRScsx_T2D_LAT_LATweights) as explained above. |
Variants | |
Original Genome Build | GRCh37 |
Number of Variants | 1,001,579 |
Effect Weight Type | beta |
PGS Source | |
PGS Catalog Publication (PGP) ID | PGP000445 |
Citation (link to publication) | Huerta-Chagoya A et al. Diabetologia (2023) |
Study Identifiers | Sample Numbers | Sample Ancestry | Cohort(s) |
---|---|---|---|
GWAS Catalog: GCST010118 Europe PMC: 32499647 |
433,540 individuals | East Asian | AGEN |
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 |
---|---|---|---|---|---|---|---|---|
Europe PMC: 10.1101/2022.07.11.499652 |
[
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Hispanic or Latin American (Mexican) |
MXB | — | — | — | — | — |
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 |
---|---|---|---|---|---|---|---|---|
PPM017183 | PSS010157| Hispanic or Latin American Ancestry| 1,484 individuals |
PGP000445 | Huerta-Chagoya A et al. Diabetologia (2023) |
Reported Trait: type 2 diabetes | OR: 1.9 [1.65, 2.19] | AUROC: 0.7475 | R²: 0.207 | sex, age, PCs(1-10), PRScsx_T2D_LAT_EURweights, PRScsx_T2D_LAT_LATweights | NOTE: Performance is based on a linear combination of this PGS with PRScsx_T2D_LAT_EASweights and PRScsx_T2D_LAT_LATweights (metascore=(zscoreEUR* 0.531117)+(zscoreEAS*0.5690198)+(zscoreLAT*0.1465538)). See score development details for how to apply |
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 |
---|---|---|---|---|---|---|---|---|
PSS010157 | — | — | [
|
Mean = 42.3 years | Hispanic or Latin American (Mexican) |
— | METSB | — |