Lipids in Health and Disease (May 2019)
Pleiotropic association of LIPC variants with lipid and urinary 8-hydroxy deoxyguanosine levels in a Taiwanese population
Abstract
Abstract Background Hepatic lipase (HL, encoded by LIPC) is a glycoprotein primarily synthesized and secreted by hepatocytes. Previous studies had demonstrated that HL is crucial for reverse cholesterol transport and affects the metabolism, composition, and level of several lipoproteins. In current study, we investigated the association of LIPC (Lipase C, Hepatic Type) variants with circulating and urinary biomarker levels by using subgroup and mediation analyses. Methods A total of 572 participants from Taiwan were genotyped for three LIPC single nucleotide polymorphisms (SNPs) by using TaqMan assay. Fasting levels of glucose, lipid profile, inflammation markers, urine creatinine and 8-hydroxy deoxyguanosine (8-OHdG) were measured. The chi-square test, 2-sample t test and Analysis of variance (ANOVA) were used to examine differences among variables and genotype frequencies. Results SNPs rs2043085 and rs1532085 were significantly associated with urinary 8-OHdG levels, whereas all three SNPs were more significantly associated with Triglycerides (TG) or HDL-cholesterol (HDL-C) levels after additional adjustment for HDL-C or TG levels, respectively. Subgroup analyses revealed that the association of the LIPC SNPs with the levels of serum TG, HDL-C, and urinary 8-OHdG were predominantly observed in the men but not in the women. Differential associations of the LIPC SNPs with various lipid levels were observed in participants with different adiposity statuses. Mediation analyses indicated that TG levels acted as a suppressor masking the association of the LIPC genotypes with HDL-C levels, particularly in the men (Sobel test, all P < 0.01). Conclusion Our data revealed that interaction and suppression effects mediated the pleiotropic association of the LIPC variants. The effects of the LIPC SNPs depended on sex, adiposity status, and TG levels. Thus, our findings can provide a method for identifying high-risk populations of cardiovascular diseases for clinical diagnosis.
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