| Predicted Trait | |
| Reported Trait | Total cholesterol |
| Mapped Trait(s) | total cholesterol measurement (EFO_0004574) |
| Score Construction | |
| PGS Name | GRS_286_TC |
| Development Method | |
| Name | PRSice |
| Parameters | For GRS construction, SNPs from MVP serum lipid summary statistics were clumped based on their linkage disequilibrium. We clumped SNPs at different r2 thresholds, and a 500kb clumping window with r2 of 0.5 proved to be the best fitting and best performing model for all lipid traits. We also tested the best P-value threshold for selecting which clumped SNPs we would include in the final GRS for the range of 1 to 5E-08. The P-value threshold, which accounted for the highest proportion of the variance of the trait R2, was selected as the best GRS. |
| Variants | |
| Original Genome Build | GRCh38 |
| Number of Variants | 286 |
| Effect Weight Type | beta |
| PGS Source | |
| PGS Catalog Publication (PGP) ID | PGP000313 |
| Citation (link to publication) | Kamiza AB et al. Nat Med (2022) |
| Ancestry Distribution | |
| Source of Variant Associations (GWAS) | |
| Score Development/Training | African: 100% 6,407 individuals (100%) |
| PGS Evaluation | African: 100% 1 Sample Sets |
| Study Identifiers | Sample Numbers | Sample Ancestry | Cohort(s) |
|---|---|---|---|
Europe PMC: 30275531 |
312,571 individuals, 92.0 % Male samples |
African American or Afro-Caribbean, European, Hispanic or Latin American | MVP |
| 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: 31675503 |
6,407 individuals, 26.2 % Male samples |
Sub-Saharan African (Ugandans) |
UGR | Non-fasting serum lipid levels were measured using the Cobas Integra 400 Plus Chemistry analyser, an automated analyser that employs four different technologies: absorption photometry, fluorescence polarization immunoassay, immune-turbidimetry, and potentiometry for accurate analysis. LDL-C were measured using the homogeneous enzymatic colorimetric assays | Mean = 34.1 years Ci = [15.8, 52.4] years |
— | — | — |
|
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 |
|---|---|---|---|---|---|---|---|---|
| PPM012985 | PSS009639| African Ancestry| 2,569 individuals |
PGP000313 | Kamiza AB et al. Nat Med (2022) |
Reported Trait: Total cholesterol levels | — | AUROC: 0.651 [0.631, 0.671] | R²: 0.0693 | age, sex, type 2 diabetes, PC1, PC2, PC3, PC4, PC5 | Nagelkerke’s R2 (estimate of variance explained by the PGS after covariate adjustment) |
|
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 |
|---|---|---|---|---|---|---|---|---|
| PSS009639 | Non-fasting serum lipid levels were measured using the Cobas Integra 400 Plus Chemistry analyser, an automated analyser that employs four different technologies: absorption photometry, fluorescence polarization immunoassay, immune-turbidimetry, and potentiometry for accurate analysis. LDL-C were measured using the homogeneous enzymatic colorimetric assays | — | 2,569 individuals, 42.9 % Male samples |
Mean = 33.1 years Ci = [18.0, 48.2] years |
Sub-Saharan African (South Africans) |
— | SAZ | — |