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新疆农村地区血脂异常患者中参与胆固醇逆转运和环境因素反应的基因之间的相互作用。

Interactions among genes involved in reverse cholesterol transport and in the response to environmental factors in dyslipidemia in subjects from the Xinjiang rural area.

机构信息

Department of Public Health, Shihezi University School of Medicine, Shihezi, China.

Key Laboratory of Xinjiang Endemic and Ethnic Diseases of the Ministry of Education, Shihezi University School of Medicine, Shihezi, China.

出版信息

PLoS One. 2018 May 14;13(5):e0196042. doi: 10.1371/journal.pone.0196042. eCollection 2018.

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.

摘要

基因-基因和基因-环境相互作用可能部分导致血脂异常,但有关逆向胆固醇转运系统(RCT)相互作用的研究有限。我们通过 SNPShot 技术对 APOA1、ABCA1 和 LCAT 中的五个 SNP 进行基因分型,在新疆农村人群中探讨了这些相互作用(690 例患者,743 例对照)。我们进行了无条件逻辑回归分析来评估关联,广义多因素降维分析来评估相互作用。结果显示,病例组和对照组间 rs670 和 rs2292318 等位基因频率存在显著差异(P<0.025)。rs670 G 等位基因携带者比 A 等位基因携带者更易发生血脂异常(OR=1.315,OR95%CI:1.067-2.620;P=0.010)。rs2292318 T 等位基因携带者比 A 等位基因携带者更易发生血脂异常(OR=1.264,OR95%CI:1.037-1.541;P=0.020)。APOA1rs670-ABCA1rs1800976-ABCA1rs4149313-LCATrs1109166 的基因-基因相互作用模型(P=0.0107)和 ABCA1rs1800976-ABCA1rs4149313-LCATrs1109166-肥胖-吸烟的基因-环境相互作用模型是最佳血脂异常预测因子(P=0.0107),并可能相互作用(4)。还观察到 A-C-A-C-A 和 G-G-G-T-G 单倍型频率的差异(P<0.05)。血清脂质谱部分可归因于 RCT 基因多态性。因此,血脂异常受 APOA1、ABCA1、LCAT、环境因素及其相互作用的影响。

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