LPA、GLU、LTF和PLTP基因单核苷酸多态性与冠心病相关性研究

发布时间：2018-05-06 20:35

本文选题：冠心病 + 单核苷酸多态性　；参考：《北京协和医学院》2015年博士论文

【摘要】：背景：冠心病是危害人类健康影响寿命的重要公共卫生问题之一。已有大量分子流行病学和遗传学研究显示,冠心病是一种复杂的多基因疾病,多种遗传因素和环境因素与冠心病有关,尤其是与脂质代谢相关的多个基因在冠心病发生发展中起重要作用。其中,从2008年至2013年,全基因组关联性研究(genome-wide association studies, GWAS)报道了近200个与脂代谢相关位点,得到了丰富的研究成果。本研究根据GWAS在脂代谢和冠心病中的研究结果,同时结合本实验室的前期研究工作,共筛选了脂蛋白a (Lipoprotein(a), LPA)基因、凝集素(clusterin, CLU)基因、磷脂转运蛋白(phospholipid transfer protein, PLTP)基因和乳铁蛋白(lactoferrin, LTF)基因这四个候选基因进行其基因单核苷酸多态性研究。目的：探讨LPA、CLU、PLTP、LTF基因单核苷酸多态性与冠心病的相关性及相关代谢指标的关系。方法：1、研究对象(1)非冠心病组：选择367名冠状动脉造影所示所有冠状动脉主要分支直径狭窄均不大于25%的人群入选至非冠心病组。(2)冠心病组：选择496名冠状动脉造影所示至少一支心外膜下冠状动脉主要分支直径狭窄大于75%的人群入选至冠心病组。2、候选基因和SNPs位点的选择：本文根据本实验室前期工作的研究成果,同时结合GWAS在冠心病中的研究结果,确定LPA、CLU、PLTP和LTF这四个候选基因进行单核苷酸多态性研究。SNPs位点选择上,首先选取基因功能区可能对蛋白质水平产生影响的所有SNPs位点,再综合该位点在中国北方汉族人群中最小等位基因频率(Minor Allele Frequency, MAF)和文献检索对该位点其他人群验证结果报道等进行筛选,最终筛选出了10个有意义的SNPs位点。3、SNPs位点的检测方法：使用基质辅助激光解吸附电离飞行时间质谱分析质谱技术(matrix-assisted laser desorption/ionization-time of flight, MALDI-TOF)进行分型检测。4、统计分析方法：应用SPSS 20.0软件对计数资料进行卡方检验,对正态分布的计量资料进行单因素方差分析,对非正态分布的计量资料进行秩和检验,当P值小于0.05认为具有显著的统计学差异。结果：1、Hardy-Winberg平衡检验：9个SNPs位点符合H-W平衡。2、冠心病组与非冠心病组间关联分析结果：(1)组间等位基因频率的关联分析结果：位于LPA基因上的rs3798220位点(C/T)在等位基因频率方面具有显著统计学差异(P=0.049),余位点未见显著性差异。(2)组间基因型频率的关联分析结果：9个SNPs位点均未见显著差异(P0.05)。(3)组间基因模型中基因型频率的关联分析结果：显性模型中LPA基因的rs3798220位点(CC+CT型vs TT型)具有显著的统计学差异(p=0.043),余位点未见显著差异。隐性模型中CLU基因上的rs3216167位点(DEL型vs A. DEL+AA型)在两组受试者间具有显著的统计学差异P=0.047,余位点未见显著性差异(P0.05)。(4)单倍体分析：rs3798220和rs1801693位点、rs3216167、rs7982、rs1532278位点之间以及rs378114和rs394643位点之间为连锁不平衡区域,各连锁不平衡区域均与冠心病不相关。3、不同基因型间计量指标的比较：(1)LPA基因：rs3798220位点中血清LPA具有显著的统计学差异(P=0.001);rs1801693位点中未见有显著性差异的血清代谢指标；rs7765803位点中血清LPA具有显著的统计学差异[P=0]；(2)CLU基因：rs3216167位点中血清LPA和HbAlc具有显著的统计学差异(P值分别为0.032,0.029)；rs7982位点中血清TC、LDL具有显著的统计学差异(P值分别为0.069,0.051);rsl532278位点中血清TC水平、LDL、APOB具有显著的统计学差异(P值分别为0.048,0.039和0.052)；(3)LTF基因：rs1126477位点血清TG具有显著的统计学差异(P=0.011)；(4) PLTP基因：rs378114位点中未见有显著差异的血清代谢指标；rs394643位点中血清APOB具有显著的统计学差异(P=0.011)4、SNP位点等位基因变化引起冠心病风险变化程度rs3798220位点中,CT+CC型发生冠心病的风险比TT增加了1.5倍。该位点能够解释0.7%的冠心病病因(Nagelkerke R2=0.07)。5、血LPA和冠心病关系的关联指标根据rs3798220基因型分组,比较基因型-疾病,基因型-血清LPA水平,推导出血清LPA水平和冠心病关系的关联指标OELPA-CAD=1.503K 14.64,即血清LPA变化K个单位时发生冠心病的效应值。结论：1、LPA基因：rs3798220位点可能通过影响血清LPA水平影响冠心病发生；rs7765803位点可能影响血LPA水平；2、CLU基因：rs3216167位点可能影响血清LPA水平,并与冠心病发生相关；rs7982位点可能影响血TC、LDL水平；rs1532278位点可能影响血TC、LDL、APOB水平；3、LTF基因：rs1126477位点可能影响血TG水平4、PLTP基因：rs394643位点可能影响血APOB水平5、血清LPA变化K个单位史冠心病风险ORLPA-CAD=1.503K/14.64
[Abstract]:Background: coronary heart disease is one of the important public health problems which harm the life of human health. A large number of molecular epidemiology and genetic studies have shown that coronary heart disease is a complex polygenic disease. Many genetic and environmental factors are associated with coronary heart disease, especially the multiple genes associated with lipid metabolism in coronary heart disease. Development plays an important role. From 2008 to 2013, the genome-wide association studies (GWAS) reported nearly 200 lipid metabolism related sites and obtained abundant research results. This study, based on the results of GWAS in lipid metabolism and coronary heart disease, combined with previous research work in the laboratory. A total of four candidate genes, such as lipoprotein a (Lipoprotein (a), LPA) gene, clusterin (CLU) gene, phospholipid transporter (phospholipid transfer protein, PLTP) gene and lactoferrin (lactoferrin, LTF) gene, were screened to study the single nucleotide polymorphisms of the genes. Association of acid polymorphism with coronary heart disease and related metabolic indicators. Methods: 1, subjects (1) non coronary heart disease group: selected 367 coronary arteriography of all the main branches of coronary artery stenosis not more than 25% of the population were selected to non coronary heart disease group. (2) coronary heart disease group: select 496 coronary arteriography at least to show at least The selection of.2, candidate genes and SNPs loci in a group of coronary artery disease with a diameter of more than 75% of the main branch of the epicardium coronary artery was selected. According to the results of earlier work in this laboratory, and combined with the results of GWAS in coronary heart disease, the four candidate genes of LPA, CLU, PLTP and LTF were identified for single nucleotide polymorphisms. In the selection of.SNPs loci, first select all SNPs loci which may affect the protein level of the gene function region, and then select the minimum allele frequency (Minor Allele Frequency, MAF) in the Han population in northern China and the literature retrieval to screen the results of the other populations of the loci. 10 meaningful SNPs loci,.3, SNPs loci were selected for detection of SNPs loci: using matrix assisted laser desorption ionization time of flight mass spectrometry analysis mass spectrometry (matrix-assisted laser desorption/ionization-time of flight, MALDI-TOF) for typing detection.4, statistical analysis method: using SPSS 20 software to carry out counting data Chi square test, a single factor variance analysis was carried out on the measurement data of the normal distribution. The rank sum test of the non normal distribution data was carried out. When the P value was less than 0.05, there were significant statistical differences. Results: 1, Hardy-Winberg balance test: 9 SNPs loci were conformed to H-W balance.2, the correlation analysis between coronary heart disease group and non coronary heart disease group was found. (1) correlation analysis of allele frequencies between groups: the rs3798220 loci (C/T) located on the LPA gene had significant statistical differences (P=0.049), and there was no significant difference in the residual loci. (2) the correlation analysis of genotype frequencies between groups had no significant difference between 9 SNPs loci (P0.05). (3) gene modes among groups. The correlation analysis results of genotype frequency in the model: the rs3798220 locus (CC+CT type vs TT type) of the LPA gene in the dominant model had significant statistical differences (p=0.043), and there was no significant difference in the residual loci. The rs3216167 loci on the CLU gene (DEL vs A. DEL+AA type) in the recessive model had significant statistical differences between the two groups. There was no significant difference in the residual loci (P0.05). (4) haploid analysis: rs3798220 and rs1801693 loci, rs3216167, rs7982, rs1532278 sites and rs378114 and rs394643 loci were interlinked unbalance regions, and the interlinked unbalance regions were not associated with coronary heart disease, and the comparison between different genotypes was compared: (1) LPA gene: RS3 There were significant statistical differences in serum LPA in the 798220 loci (P=0.001); there was no significant difference in serum metabolism index in the rs1801693 locus, and there was a significant statistical difference between the serum LPA and [P=0] in the rs7765803 locus. (2) the serum LPA and HbAlc of the rs3216167 site were statistically significant (P value was 0.032,0.02). 9): the serum TC and LDL in the rs7982 site had significant statistical differences (P values were 0.069,0.051), and the serum TC level, LDL, and APOB in the rsl532278 locus had significant statistical differences (P values were 0.048,0.039 and 0.052), and (3) the LTF genes were statistically significant; (4) There was no significant difference in serum metabolic index in the 114 loci. The serum APOB in the rs394643 site had significant statistical difference (P=0.011) 4. The change of SNP allele caused the risk of coronary heart disease in rs3798220 site, and the risk of coronary heart disease of type CT+CC was 1.5 times higher than that of TT. This site could explain 0.7% of coronary heart disease. The correlation index of the relationship between (Nagelkerke R2=0.07).5, blood LPA and coronary heart disease is based on the grouping of rs3798220 genotypes, comparing genotype - disease, genotype - serum LPA level, and deducing the correlation index of the relationship between LPA level and coronary heart disease, OELPA-CAD=1.503K 14.64, that is, the effect of coronary heart disease in serum LPA change K units. Conclusion: 1, LPA Gene: rs3798220 locus may affect coronary heart disease by affecting serum LPA level; rs7765803 locus may affect blood LPA level; 2, CLU gene: rs3216167 locus may affect serum LPA level and may be associated with coronary heart disease; rs7982 site may affect TC, LDL level, and rs1532278 locus may affect blood TC, levels, levels 3, LTF gene: rs1126477 locus may affect blood TG level 4, PLTP gene: rs394643 site may affect blood APOB level 5, serum LPA changes K unit history of coronary heart disease risk ORLPA-CAD=1.503K/14.64

【学位授予单位】：北京协和医学院
【学位级别】：博士
【学位授予年份】：2015
【分类号】：R541.4

【共引文献】