冠心病论文脂质代谢及炎性通路基因与冠心病关联关系研究

1、冠心病论文：脂质代谢及炎性通路基因与冠心病关联关系研究【中文摘要】冠状动脉粥样硬化性心脏病(Coronary Artery Disease or Coronary Atherosclerosis Disease, CAD),简称冠心病,是一种最常见的心脏病,严重危害人类的健康。作为一种复杂疾病,它的发生是由遗传因素和环境因素共同作用引起的。随着越来越多的易感基因被发现,针对动脉粥样硬化的发病机制形成了多种学说,目前被学者广泛接受的两种学说是脂肪浸润学说和炎症学说。本研究选取的7个候选易感基因中,与脂质代谢相关的5个基因是：LRP5 (low density lipoprotein recept

2、or-related protein 5)、LRP6 (low density lipoprotein receptor-related protein 6)、APOC1 (Apolipoprotein C-I)、ABCG1 (ATP-binding cassette, sub-family G (WHITE), member 1)和PCSK9 (proprotein convertase subtilisin/kexin type 9),与炎症相关的2个基因是：TNFSF4 (Tumor necrosis factor superfamily, number 4)和TNFRSF4 (tumo

3、r necrosis factor receptor superfamily, member 4)。应用基于群体的病例对照研究设计,逐步采用多种统计分析方法,探讨中国汉族人群中,脂质代谢通路中的5个候选易感基因(LRP5、LRP6、APOC1. ABCG1、PCSK9)及炎性通路中的2个易感基因(TNFSF4、TNFRSF4)同冠心病的关联性。1.从山东大学齐鲁医院选取了498例病例及509例对照,对研究对象临床资料进行统计描述。2.对LRP5基因上2个SNP (single nucleotide polymorphism)位点(rs41494349、rs3736228)、LRP6基因上9个S

4、NP位点(rs2160525、rs2284396、rs4477532、rs2302685、rs7305037、rs12823243、rs1181333、rs11054731、rs17848270)、APOC1基因上1个SNP位点(rs4420638)、ABCG1基因上4个SNP位点(rs4148082、rs1893590、rs1378577、rs1044317)、PCSK9基因上3个SNP位点(rs572512、rs2483205、rs2495477)、TNFSF4基因上5个SNP位点(rs1234314、rs45454293、rs3850641、rs1234313、rs3861950)以及T

5、NFRSF4基因上1个SNP位点(rs2298212)进行基因分型。3.针对每个SNP位点,利用Armitage趋势检验检测其与冠心病的关联性。4.针对每个基因,将从该基因上选取的SNP位点及混杂因素(年龄、性别、体重指数、收缩压、舒张压、总胆固醇、甘油三酯和葡萄糖8个指标)引入logistic回归模型中,以检测在排除混杂因素影响后,该基因上SNP位点与冠心病的关联性。5.针对选取位点数大于1的每个基因,利用SAS 9.1.3软件的genetics模块进行单倍型分析。6.针对选取位点数大于1的每个基因,采用基于主成分的logistic回归分析来研究每个基因与冠心病的关联性。7.采用偏最小二乘路

6、径模型(partial least square path modeling, PLS-PM)来研究这些基因与冠心病的关联性,在R软件中利用PLS-PM软件包来实现。1.对单个SNP位点的Armitage趋势检验结果显示,APOC1基因的rs4420638 (P=0.0001), PCSK9基因的rs572512 (P=0.0308)以及TNFSF4基因的rs3861950 (P=0.0324)这三个SNP位点与冠心病存在关联性。2.调整混杂因素的logistic回归分析结果显示,LRP5基因的rs41494349 (P=0.0372), LRP6基因的rs4477532 (P=0.0130)

7、、rsl2823243 (P=0.0117)和rs11054731 (P=0.0024), APOC1基因的rs4420638 (P=0.0021)以及PCSK9基因的rs2483205 (0.0402)这六个SNP位点与冠心病存在关联性。3.单体型分析结果显示,LRP6、ABCG1和TNFSF4这三个基因存在在病例组和对照组中的频率差异具有统计学意义的单体型。4.基于主成分的logistic回归分析结果显示,TNFSF4基因的第一主成分(PC1)与冠心病具有统计学关联性(P=0.0236)。5.对LRP5基因与LRP6基因交互作用的PLS-PM处理结果显示,LRP5->LRP6路径系数

8、在病例组和对照组的差异具有显著性(P=0.0099)。对TNFSF4基因与TNFRSF4基因交互作用的PLS-PM处理结果显示,TNFSF4-> TNFRSF4路径系数在病例组和对照组的差异不具有显著性(P=0.4455)。对LRP5、LRP6、APOC1、ABCG1、PCSK9这5个基因与血脂之间的交互作用PLS-PM的处理结果显示,LRP6->BL (P=0.0196)以及PCSK9->BL (P=0.0392)这两个路径系数在病例组和对照组的差异具有显著性。1.在基于主成分的logistic回归分析方法处理下,TNFSF4基因同冠心病存在关联性,而LRP5、LRP6、A

9、BCG1、PCSK9这4个基因同关心病不存在关联性。2.LRP5基因与LRP6基因的交互作用与冠心病存在关联性,而TNFSF4基因与TNFRSF4基因的交互作用与冠心病不存在关联性。与脂质代谢相关的5个基因中(LRP5、LRP6、APOC1、ABCG1、PCSK9), LRP6基因与PCSK9基因在病例组与对照组中对血脂影响具有统计学意义。【英文摘要】BackgroundCoronary atherosclerotic disease (CAD), as the most common type of heart disease, is very dangerous for human hea

10、lth. As a kind of complex disease, CAD results from the interaction of a number of susceptibility genes and environmental factors. With the discovery of more and more susceptibility genes, there form many kinds of hypothesis about the pathogenesis of CAD. At present, fatty infiltration hypothesis an

11、d inflammatory hypothesis are most accepted by researchers.In my research,7 candidate susceptibility genes were selected. LRP5 (low density lipoprotein receptor-related protein 5), LRP6 (low density lipoprotein receptor-related protein 6), APOC1 (Apolipoprotein C-I), ABCG1 (ATP-binding cassette, sub

12、-family G, member 1) and PCSK9 (proprotein convertase subtilisin/kexin type 9), these five genes were related with lipid metabolism. TNFSF4 (Tumor necrosis factor superfamily, number 4) and TNFRSF4 (tumor necrosis factor receptor superfamily, member 4), these two genes were related with inflammation

13、.By applying population-based case-control study design, we used many kinds of statistical methods to explore the association between CAD and 5 candidate susceptibility genes (LRP5, LRP6, APOC1, ABCG1, PCSK9) in lipid metabolism pathway and the association between CAD and 2 candidate susceptibility

14、genes (TNFSF4, TNFRSF4) in inflammatory pathway in Chinese Han population.Methods1. We collected 498 cases and 509 controls from Qilu Hospital of Shandong University and conducted statistical description of the clinical data of them.2.2 SNPs of LRP5 (rs41494349, rs3736228),9 SNPs of LRP6 (rs2160525,

15、 rs2284396, rs4477532, rs2302685, rs7305037, rs12823243, rs1181333, rs11054731, rs17848270),1 SNP of APOC1 (rs4420638),4 SNPs of ABCG1 (rs4148082, rs1893590, rs1378577, rs1044317),3 SNPs of PCSK9 (rs572512, rs2483205, rs2495477),5 SNPs of TNFSF4 (rs1234314, rs45454293, rs3850641, rs1234313, rs386195

16、0) and 1 SNP of TNFRSF4 (rs2298212) were genotyped.3. We used Armitage trend test to detect the association between every single SNP and CAD.4. For every single gene, we put the SNPs selected from the gene and the confounding factors (sex, age, Body Mass Index, Systolic Blood Pressure, Diastolic Blo

17、od Pressure, Total Cholesterol, Triglyceride, Glucose) into logistic regression model. After eliminating the impact of confounding factors, we detected the association between every single SNP and CAD.5. For genes with more than 1 selected SNP, we used Genetics module of SAS 9.1.3 software to do hap

18、lotype analysis.6. For genes with more than 1 selected SNP, we used principal component-based logistic analysis to detect the association between every gene and CAD.7. We applied partial least squares path model to study the association between these 7 genes and CAD. This was done by using PLS-PM so

19、ftware package of R software.Results 1. The results of Armitage trend test suggested that, rs4420638 of APOC1 (P=0.0001), rs572512 of PCSK9 (P=0.0308) and rs3861950 of TNFSF4 (P=0.0324) these 3 SNPs were significantly associated with CAD.2. The results of logistic analysis adjusting confounding fact

20、ors suggested that, rs41494349 of LRP5 (P=0.0372), rs4477532 of LRP6 (P=0.0130), rsl2823243 of LRP6 (P=0.0117), rs 11054731 of LRP6 (P=0.0024), rs4420638 of APOC1 (P=0.0021 and rs2483205 of PCSK9 (P=0.0402) these 6 SNPs were significantly associated with CAD.3. The results of haplotype analysis sugg

21、ested that, there existed haplotypes which were significantly different between case and control in LRP6, ABCG1 and TNFSF4.4. The results of principal component-based logistic analysis suggested that, the first principal component of TNFSF4 has statistical significance (P=0.0236).5. The results of a

22、pplying PLS-PM to detect the interaction between LRP5 and LRP6 suggested that, the path coefficient was significant between case and control (P=0.0099). The results of applying PLS-PM to detect the interaction between TNFSF4 and TNFRSF4 suggested that, the path coefficient was not significant betwee

23、n case and control (P=0.4455). The results of applying PLS-PM to detect the interactions between LRP5, LRP6, APOC1, ABCG1, PCSK9 this 5 genes and blood lipid (BL) suggested that, the path coefficients of LRP6->BL (P=0.0196) and PCSK9->BL (P=0.0392) were significant between case and control.Con

24、clusions1. When applying principal component-based logistic analysis, TNFSF4 is associated with CAD, but LRP5, LRP6, ABCG1 and PCSK9 these 4 genes are not associated with CAD.2. The interaction between LRP5 and LRP6 is associated with CAD. The interaction between TNFSF4 and TNFRSF4 is not associated with CAD. In the 5 genes (LRP5, LRP6, APOC1, ABCG1, PCSK9) which are connected with lipid metabolism, LRP6 and PCSK9 are significantly associated with blood lipid between case and control.【关键词】冠心病 主成分分析 logistic回归分析 偏最