基因—吸烟交互作用和钙离子通道相关基因对于汉族人群血压的影响

发布时间：2018-04-25 12:09

本文选题：全基因组 + 交互作用　；参考：《北京协和医学院》2017年博士论文

【摘要】：第一部分:基于全基因组基因-吸烟交互作用识别汉族人群血压易感基因背景与目的高血压是心血管疾病首要危险因素,位列疾病负担危险因素的首位。目前大规模全基因组关联研究(genome-wide association study,GW AS)已经鉴定出200余个血压位点,然而这些位点仅能解释不足4%的血压变异。血压“遗传度缺失”可能是由于当前大部分GWAS没有考虑基因间和基因-环境间的交互作用所导致。采用全基因组基因-环境交互作用分析(genome-wide environmental interaction study,GWEIS)可以在全基因组范围内识别出与环境因素共同作用影响血压的新位点。吸烟作为影响血压的重要因素,可能与遗传因素共同作用影响血压水平。本研究旨在应用GWEIS方法在中国汉族人群中鉴定与吸烟存在交互作用的血压易感位点。研究对象与方法本研究分两阶段进行。第一阶段纳入来自中国心血管健康多中心合作研究(InterAsia)的3,998名研究对象,采用Affymetrix的Axiom,TM全基因组CHB1阵列芯片进行检测,共获取657,124个单核苷酸多态性(single nucleotide polymorphism,SNP)位点的基因型信息。进而使用人类千人基因组数据库中东亚人群数据,利用MACH软件对未直接检测的位点进行基因型填补和质控,最终大约570万个SNP位点纳入分析。采用1自由度交互作用检验和2自由度SNP主效应与交互效应联合检验两种分析方法,分析单个SNP位点的交互作用。采用versatile gene-based association study(VEGAS)方法,整合单个SNP位点交互作用关联P值,分析基于基因水平的交互作用。第二阶段,挑选出第一阶段关联P值小于1.0×10-4的SNP位点和基因,在466名北京动脉粥样硬化研究(BAS)研究对象中进行重复验证。第二阶段研究对象采用 Affymetrix GeneChip Human Mapping 500K Array Set 基因芯片进行基因分型。统计分析采用ProbAbel,VEGAS2,Metal,Plink和R等软件。结果在第一阶段研究中,采用1自由度交互作用检验共分别发现49、59、62和38个独立SNP位点与收缩压、舒张压、平均动脉压和脉压的交互作用关联P值小于1×10-4;采用2自由度主效应与交互效应联合检验共发现69、65、77和55个独立SNP位点分别与收缩压、舒张压、平均动脉压和脉压的交互作用关联P值小于1×10-4。对两阶段样本meta分析,1自由度交互作用检验发现3个SNP位点与吸烟的交互作用达到全基因组潜在显著关联水平(P1 ×1(-6),其中,rs2716127(LOC105378753,P1dfinteraction=7.7×10-7)和 rs4751139(EF3,P1dfinteraction=1.58×10-7)的交互作用与舒张压相关,rs2036086(LO105378150,P1df interaction = 6.16×10-7)的交互作用与平均动脉压相关;2自由度主效应与交互效应联合检验发现rs1465405(ADRB2,P2df interaction = 4.3×10-8)与吸烟交互作用对脉压的效应达到全基因组显著关联水平(P5×10-8),rs2400643(ADB2,P2dfinteraction=5.33×10-7)与吸烟交互作用对收缩压的效应、rs4751139(EBF3,P2df interaction=5.00×10-7)与吸烟交互作用对舒张压的效应达到了全基因组潜在显著关联水平。在吸烟者和非吸烟者中,潜在关联或者显著关联的SNP位点对血压影响的效应不同。例如,在InterAsia人群中,SNP rs2716127每增加一个T等位基因,吸烟者的平均舒张压升高1.91mmHg,而非吸烟者的平均舒张压降低0.73mmHg,在BAS人群中结果相似。本研究同时发现7个既往东亚人群报道的血压SNP位点与吸烟有交互作用(P值通过Bonferroni多重校正),位于7个基因内,分别是CACNA1D、FGF5、ARL3、CYP17A1、NM2、NT5C2和ATP2B1。7个SNP位点总体解释的收缩压、舒张压、平均动脉压和脉压的变异比例分别为1.79%、2.28%、2.24%和0.52%,加入吸烟交互作用之后,解释的血压变异比例分别增加到2.11%、2.46%、2.49%和0.85%,解释的变异比例提升的百分比分别为17.69%、7.82%、11.06%和62.83%。此外,基于基因的关联分析发现3个基因与吸烟的交互作用达到基因水平全基因组显著关联(P2.5×10-6),分别是 zBTB2、ZNF180和CNNM2。上述结果中,LOC105378753、EBF3、LOC105378150、ZBTB2和ZNF180基因与血压表型的关系是首次报道。结论本研究首次在中国人群中开展了全基因组基因-吸烟交互作用与血压关系的GWIES研究,发现ADRB2rs1465405与血压显著相关,EBF3 rs4751139、LOC105378150 rs2716127和LOC1053 78150 rs2036086 三个位点与血压潜在相关;此外,基于基因水平的分析鉴定出ZBTB2、ZNF180和CNNM2三个基因与血压显著相关。本研究结果提示基于基因-环境交互作用分析策略不仅可以鉴定出新的血压相关遗传位点,而且基因-环境交互作用可以提升解释缺失的血压变异。研究结果尚需进一步在不同人群中进行大规模验证,同时开展功能学研究,解释这些位点的潜在生物学机制。第二部分:钙离子通道相关基因对汉族人群血压长期变化的影响背景与目的高血压是全球首要致病危险因素。近年来,尽管通过GWAS发现一系列血压相关易感基因,但血压调控的遗传机制还不明确。以关键血压易感基因为切入点深入研究,可以高效识别新的血压易感位点,有助于解析血压的调节机制。电压门控钙离子通道(voltage-dependent calcium channels,VDCCs)在血管平滑肌细胞收缩等血压调控过程中具有重要作用,既往横断面调查发现VDCCs相关基因与血压表型相关,但是这些遗传变异是否影响血压水平长期变化及高血压发病尚不清楚。本研究旨在通过单个SNP位点和基于基因的关联分析,探讨VDCCs基因与血压长期变化和高血压发病之间的关系。研究对象与方法本研究的研究对象均来自于盐敏感性遗传流行病学网络(Genetic Epidemiology Network of Salt GenSalt Sensitivity,GenSalt)研究,共纳入 633 个家庭的 1,768 名研究对象。基线调查时间为2003-2005年,并分别于2008-2009年和2011-2012年开展两次随访调查。血压测量使用随机零点血压计,每天测量3次,每次间隔时间不少于30秒,每次调查连续测量3天,共9次,将9次测量值的平均收缩压和舒张压作为分析血压。本研究共纳入分析9个VDCCs相关基因,经过质量控制后,9个基因内的219个SNP纳入分析。应用混合线性模型分析每个SNP与血压长期变化的关系;应用广义混合线性模型,在剔除基线患有高血压的173名研究对象后,分析每个SNP与高血压发病的关系。采用截点乘积法(truncated product method,TPM),整合单个SNP分析得到的P值,进行基于基因的分析。全部统计分析结果采用Bonferroni法进行多重检验校正。结果1,768名GenSalt研究对象的男性比例为52.3%,基线阶段平均年龄为39岁,平均体质指数(body mass index,BMI)为23.4 kg/m2,平均收缩压为116.9mmHg,平均舒张压为73.8mmHg。经过平均7.2年的随访,平均收缩压上升至129.1mmHg,平均舒张压上升至82.2mmHg,同时出现512例新发高血压患者,高血压累积发病率为32.1%。在单个SNP位点分析中,CACNA1A基因内的SNP位点rs8182538与舒张压的长期变化相关,且经Bonferroni多重校正后仍达统计学显著水平(P = 9.9×10-5)。rs8182538的基因型为C/C、C/T和T/T的研究对象,年均舒张压增长幅度分别为0.85、1.03和1.19mmHg。rs8182538与收缩压长期变化也有类似趋势(P=0.022)。基于基因的关联分析发现CACNA1A与舒张压的长期变化显著相关(P=2.0×10-5),C4CNA1C基因与收缩压的长期变化显著相关(P=1.4×0-4)。去除CACNA1A和CACNA1C基因内最显著的SNP位点后,CACNA1A和CACNA1C基因整体变异仍分别与舒张压和收缩压长期变化显著相关。结论我们首次发现中国汉族人群中CACNA1A基因的常见SNP位点rs8182538与舒张压水平长期变化显著相关,同时基于基因水平的关联分析发现CACNA1A和CACNA1C基因整体分别与舒张压和收缩压长期变化相关。后续在大样本中的重复验证及功能学研究将有助于进一步阐明CACNA1A和CACNA1C基因的血压调节机制。
[Abstract]:The first part: Based on the whole genome gene - smoking interaction to identify the background and objective of blood pressure susceptibility gene in Han population, hypertension is the first risk factor of cardiovascular disease. It is the first of the risk factors of disease burden. At present, more than 200 blood pressure has been identified by genome-wide association study, GW AS. Loci, however, can only explain less than 4% of the blood pressure variation. The "lack of heredity" of blood pressure may be due to the fact that most of the current GWAS does not take into account the interaction between genes and the gene environment. Genome-wide environmental interaction study (GWEIS) can be used in the whole genome gene environment interaction analysis (GWEIS). A new locus of blood pressure affecting blood pressure is identified in the genome scope. Smoking is an important factor affecting blood pressure and may affect blood pressure with genetic factors. The aim of this study is to use GWEIS method to identify the blood pressure susceptibility loci in the Han population of China. Methods this study was carried out in two stages. The first stage was included in 3998 subjects from the Chinese cardiovascular health multi center cooperative study (InterAsia). The Affymetrix Axiom and TM whole genome CHB1 array chips were used to detect 657124 single nucleotide polymorphisms (single nucleotide polymorphism, SNP) loci. Information. Then using the data of East Asian population in the human genome database, MACH software was used to fill and control the non directly detected loci, and the final 5 million 700 thousand SNP loci were analyzed. Two analysis methods were analyzed by the combined test of the interaction of 1 degrees of freedom and the joint test of the 2 degree of freedom SNP main effect and the interaction effect. The interaction of single SNP loci. Using the versatile gene-based association study (VEGAS) method to integrate the interaction of single SNP sites with the interaction of P and analyze the interaction based on the gene level. In the second stage, the first stage was selected to identify the SNP loci and genes associated with P less than 1 * 10-4, in 466 Beijing atherosclerosis studies (BAS). The research object is repeated validation. The second stage research object uses Affymetrix GeneChip Human Mapping 500K Array Set gene chip for genotyping. Statistical analysis uses ProbAbel, VEGAS2, Metal, Plink, R and other software. Results in the first stage of the study, the use of 1 degrees of freedom interaction test found a total of 38 and 38 The interaction of independent SNP loci with systolic pressure, diastolic pressure, mean arterial pressure and pulse pressure was associated with a P value less than 1 x 10-4. A co test of 69,65,77 and 55 independent SNP loci with the interaction effect of 2 degrees of freedom and interaction effects associated with the interaction of the systolic pressure, diastolic pressure, mean arterial pressure and pulse pressure was less than 1 * 10-4. to two order, respectively. Meta analysis and 1 degree of freedom interaction test found that the interaction between 3 SNP sites and smoking reached a potential significant correlation (P1 * 1 (-6)), in which the interaction of rs2716127 (LOC105378753, P1dfinteraction=7.7 x 10-7) and rs4751139 (EF3, P1dfinteraction= 1.58 x 10-7) was associated with diastolic pressure, rs2036086 (LO1053781) 50, the interaction of P1df interaction = 6.16 x 10-7) was associated with the mean arterial pressure; the joint test of the 2 degree of freedom principal effect and interaction effect found that the effects of rs1465405 (ADRB2, P2df interaction = 4.3 * 10-8) on the pulse pressure were significantly related to the whole genome (P5 x 10-8), rs2400643 (ADB2, P2dfinteraction=5.33 x 10-7). The effect of interaction with smoking on systolic blood pressure, the effect of rs4751139 (EBF3, P2df interaction=5.00 x 10-7) and smoking interaction on diastolic pressure has reached a potentially significant level in the whole genome. Among smokers and non smokers, potential or significantly associated SNP sites have different effects on blood pressure. For example, in InterAsia In the population, SNP rs2716127 increased one T allele, and the average diastolic pressure of smokers increased by 1.91mmHg, while the average diastolic blood pressure of non smokers was 0.73mmHg, and the results were similar in the BAS population. The study also found that the blood pressure SNP loci in 7 previous East Asian populations were interacted with smoking (P value through Bonferroni multicorrection). In 7 genes, the systolic pressure, diastolic pressure, mean arterial pressure and pulse pressure were 1.79%, 2.28%, 2.24%, and 0.52%, respectively, in CACNA1D, FGF5, ARL3, CYP17A1, NM2, NT5C2, and ATP2B1.7 SNP sites, respectively. The proportion of blood pressure variations explained by smoking interaction increased to 2.11%, 2.46%, 2.49%, and 0.85%, respectively. The percentages of the mutation ratio were 17.69%, 7.82%, 11.06% and 62.83%., respectively. Gene based correlation analysis found that the interaction between 3 genes and smoking reached a significant gene level genome (P2.5 x 10-6), which were LOC105378753, EBF3, LOC105378150, ZBTB2, and ZNF180 genes in zBTB2, ZNF180 and CNNM2., respectively. The relationship with the blood pressure phenotype is the first report. Conclusion this study was the first to carry out the GWIES study on the relationship between the whole genome gene smoking interaction and blood pressure in the Chinese population. It was found that ADRB2rs1465405 was significantly related to blood pressure. EBF3 rs4751139, LOC105378150 rs2716127 and LOC1053 78150 rs2036086 were associated with the potential of blood pressure. In addition, three genes of ZBTB2, ZNF180 and CNNM2 were identified with significant correlation with blood pressure based on gene level analysis. The results suggest that the gene environmental interaction analysis strategy not only can identify new blood pressure related genetic sites, but also the gene environmental interaction can enhance the interpretation of the missing blood pressure variation. The results are still needed. Further large-scale validation in different populations and functional studies to explain the potential biological mechanisms of these sites. Second part: the influence of calcium channel related genes on the long-term changes of blood pressure in the Han population and objective hypertension is the leading risk factor in the world. In recent years, although GWAS has been found through the discovery of one system Blood pressure related susceptibility genes are listed, but the genetic mechanism of blood pressure regulation is not clear. The key blood pressure susceptibility base is studied deeply because of the penetration point. It can effectively identify the new blood pressure susceptibility loci and help to analyze the regulation mechanism of blood pressure. The voltage gated calcium channel (voltage-dependent calcium channels, VDCCs) can be used in vascular smooth muscle cells. VDCCs related genes are associated with blood pressure phenotype, but whether these genetic variations affect long-term changes in blood pressure and the incidence of hypertension is not clear. The purpose of this study was to explore the VDCCs gene and the length of blood pressure based on a single SNP locus and based on the association analysis of the base. The subjects and methods of this study were based on the study of Genetic Epidemiology Network of Salt GenSalt Sensitivity (GenSalt), which included 1768 subjects in 633 families. The baseline survey time was 2003-2005 years. Do not carry out two follow-up surveys in 2008-2009 and 2011-2012 years. The blood pressure measurement uses a random zero point sphygmomanometer, measured 3 times a day, with a interval of no less than 30 seconds. The average systolic and diastolic pressure of the 9 measured values of the mean systolic and diastolic pressure is analyzed for 3 days at each time, and the average systolic pressure and diastolic pressure of the 9 measured values are analyzed. This study included the analysis of 9 VDCCs related genes. After quality control, 219 SNP in 9 genes were analyzed. A mixed linear model was used to analyze the relationship between each SNP and the long-term changes in blood pressure; the relationship between each SNP and hypertension was analyzed with a generalized mixed linear model, and the relationship between each SNP and hypertension was analyzed. The cross section product (truncated product met) was used. Hod, TPM), integrating the P values obtained by the single SNP analysis. All the statistical analysis results were corrected by the Bonferroni method. The results showed that the male proportion of the 1768 GenSalt subjects was 52.3%, the average age of the baseline was 39 years, the average body mass index (body mass index, BMI) was 23.4 kg/m2, and the mean systolic pressure was For 116.9mmHg, the mean diastolic pressure was 73.8mmHg. after an average of 7.2 years of follow-up, the mean systolic pressure rose to 129.1mmHg, the average diastolic pressure increased to 82.2mmHg, and 512 cases of new hypertensive patients were presented. The cumulative incidence of hypertension was 32.1%. in a single SNP locus analysis, and the long-term variation of the rs8182538 and diastolic pressure of the SNP loci within the CACNA1A gene was in the CACNA1A gene. The genotypes of the statistical significant level (P = 9.9 * 10-5).Rs8182538 after Bonferroni multiplex correction were the subjects of C/C, C/T and T/T, and the average annual diastolic pressure growth was also similar to that of 0.85,1.03 and 1.19mmHg.rs8182538 and systolic pressure (P=0.022). Based on gene correlation analysis, CACNA1A was found. The long term change of diastolic pressure was significantly correlated (P=2.0 x 10-5), and the C4CNA1C gene was significantly related to the long term changes in systolic pressure (P=1.4 x 0-4). After removing the most significant SNP locus in the CACNA1A and CACNA1C genes, the whole variation of CACNA1A and CACNA1C genes was still significantly related to the diastolic pressure and the long systolic pressure. The common SNP locus rs8182538 of the CACNA1A gene in the ethnic group is significantly related to the diastolic pressure level, and the correlation analysis based on the gene level shows that the CACNA1A and CACNA1C genes are related to the diastolic pressure and systolic pressure in the long term. The mechanism of blood pressure regulation of CACNA1A and CACNA1C genes.

【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】：2017
【分类号】：R544.1

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