Abstract
Gene-gene and gene-environment interactions may be partially responsible for dyslipidemia, but studies investigating interactions in the reverse cholesterol transport system (RCT) are limited. We explored these interactions in a Xinjiang rural population by genotyping five SNPs using SNPShot technique in APOA1, ABCA1, and LCAT, which are involved in the RCT (690 patients, 743 controls). We conducted unconditional logistical regression analysis to evaluate associations and generalized multifactor dimensionality reduction to evaluate interactions. Results revealed significant differences in rs670 and rs2292318 allele frequencies between cases and controls (P<0.025). rs670 G allele carriers were more likely to develop dyslipidemia than A allele carriers (OR = 1.315, OR 95% CI: 1.067-2.620; P = 0.010). rs2292318 T allele carriers were more likely to develop dyslipidemia than A allele carriers (OR = 1.264, OR 95% CI: 1.037-1.541; P = 0.020). Gene-gene interaction model APOA1rs670-ABCA1rs1800976-ABCA1rs4149313-LCATrs1109166 (P = 0.0107) and gene-environment interaction model ABCA1rs1800976-ABCA1rs4149313-LCATrs1109166-obesity-smoking were optimal dyslipidemia predictors (P = 0.0107) and can interact (4). Differences in A-C-A-C-A and G-G-G-T-G haplotype frequencies were observed (P<0.05). Serum lipid profiles could be partly attributed to RCT gene polymorphisms. Thus, dyslipidemia is influenced by APOA1, ABCA1, LCAT, environmental factors, and their interactions.