Pleiotropic Effects of Common and Rare Exonic Mutations on Cardiometabolic Traits.

BACKGROUND

The common non-synonymous mutation of the glucokinase regulator () gene, namely rs1260326, is widely reported to have pleiotropic effects on cardio-metabolic traits and hematological parameters.

OBJECTIVE

This study aimed to identify whether other variants may have pleiotropic effects independent of the rs1260326 genotypes.

METHODS

In total, 81,097 Taiwan Biobank participants were enrolled for the regional plot association studies and candidate variant analysis of the region around the gene.

RESULTS

The initial candidate variant approach showed the significant association of the rs1260326 genotypes with multiple phenotypes. Regional plot association analysis of the gene region further revealed genome-wide significant associations between variants and serum total and low-density lipoprotein cholesterol; triglyceride, uric acid, creatinine, aspartate aminotransferase, γ-Glutamyl transferase, albumin, and fasting plasma glucose levels; estimated glomerular filtration rate; leukocyte and platelet counts; microalbuminuria, and metabolic syndrome, with rs1260326 being the most common lead polymorphism. Serial conditional analysis identified genome-wide significant associations of two low-frequency exonic mutations, rs143881585 and rs8179206, with high serum triglyceride and albumin levels. In five rare exonic non-synonymous or nonsense mutations available for analysis, rs146175795 showed an independent association with serum triglyceride and albumin levels and rs150673460 showed an independent association with serum triglyceride levels. Weighted genetic risk scores from the combination of rs143881585 and rs146175795 revealed a significant association with metabolic syndrome.

CONCLUSION

In addition to the rs1260326 variant, low-frequency and rare exonic mutations exhibit pleiotropic effects on serum triglyceride and albumin levels and the risk of metabolic syndrome. These results provide evidence that both common and rare variants may play a critical role in predicting the risk of cardiometabolic disorders.