Table 9.
Genome-Wide Association Study Results for Baseline High-Density Lipoprotein Cholesterol Using an Unrelated Subset of Subjects from the Metabolic Syndrome in Men Cohort
| LR | LMM | BOLT-INF | BOLT-LMM | cvBLUP | |
|---|---|---|---|---|---|
| lambdaGC | 1.04 | 1.04 | 1.04 | 1.04 | 1.04 |
| p-values below 1e-06 | 15 | 15 | 14 | 14 | 16 |
| Mean ratio of effect size estimates, 1e-06 | 1.02 | 1 | 0.992 | 0.992 | 0.999 |
| Standard error in ratio of effect sizes, 1e-06 | 0.00294 | 0 | 0.00134 | 0.00134 | 0.000866 |
| p-values below 5e-08 | 13 | 11 | 11 | 13 | 12 |
| Mean ratio of effect size estimates, 5e-08 | 1.01 | 1 | 0.997 | 0.997 | 1 |
| Standard error in ratio of effect sizes, 5e-08 | 0.00288 | 0 | 0.000681 | 0.000681 | 0.000897 |
LMM with GLS analysis of SNP effects implemented in GCTA, cvBLUP: cross-validated prediction-adjusted LR, BOLT-INF; BOLT assuming infinitesimal genetic model, BOLT-LMM, BOLT using sparse genetic architecture. cvBLUP-adjusted analyses, LMM, and BOLT were used in a leave-one-chromosome-out scheme with variance components, cvBLUPs, covariance models (LMM, GCTA), and genetic predictions and residuals (BOLT) generated using SNPs on chromosomes other than that of the test-SNPs.