本文選題：全基因組 + 交互作用　； 參考：《北京協(xié)和醫(yī)學(xué)院》2017年博士論文

【摘要】：第一部分:基于全基因組基因-吸煙交互作用識(shí)別漢族人群血壓易感基因背景與目的高血壓是心血管疾病首要危險(xiǎn)因素,位列疾病負(fù)擔(dān)危險(xiǎn)因素的首位。目前大規(guī)模全基因組關(guān)聯(lián)研究(genome-wide association study,GW AS)已經(jīng)鑒定出200余個(gè)血壓位點(diǎn),然而這些位點(diǎn)僅能解釋不足4%的血壓變異。血壓“遺傳度缺失”可能是由于當(dāng)前大部分GWAS沒有考慮基因間和基因-環(huán)境間的交互作用所導(dǎo)致。采用全基因組基因-環(huán)境交互作用分析(genome-wide environmental interaction study,GWEIS)可以在全基因組范圍內(nèi)識(shí)別出與環(huán)境因素共同作用影響血壓的新位點(diǎn)。吸煙作為影響血壓的重要因素,可能與遺傳因素共同作用影響血壓水平。本研究旨在應(yīng)用GWEIS方法在中國(guó)漢族人群中鑒定與吸煙存在交互作用的血壓易感位點(diǎn)。研究對(duì)象與方法本研究分兩階段進(jìn)行。第一階段納入來自中國(guó)心血管健康多中心合作研究(InterAsia)的3,998名研究對(duì)象,采用Affymetrix的Axiom,TM全基因組CHB1陣列芯片進(jìn)行檢測(cè),共獲取657,124個(gè)單核苷酸多態(tài)性(single nucleotide polymorphism,SNP)位點(diǎn)的基因型信息。進(jìn)而使用人類千人基因組數(shù)據(jù)庫(kù)中東亞人群數(shù)據(jù),利用MACH軟件對(duì)未直接檢測(cè)的位點(diǎn)進(jìn)行基因型填補(bǔ)和質(zhì)控,最終大約570萬(wàn)個(gè)SNP位點(diǎn)納入分析。采用1自由度交互作用檢驗(yàn)和2自由度SNP主效應(yīng)與交互效應(yīng)聯(lián)合檢驗(yàn)兩種分析方法,分析單個(gè)SNP位點(diǎn)的交互作用。采用versatile gene-based association study(VEGAS)方法,整合單個(gè)SNP位點(diǎn)交互作用關(guān)聯(lián)P值,分析基于基因水平的交互作用。第二階段,挑選出第一階段關(guān)聯(lián)P值小于1.0×10-4的SNP位點(diǎn)和基因,在466名北京動(dòng)脈粥樣硬化研究(BAS)研究對(duì)象中進(jìn)行重復(fù)驗(yàn)證。第二階段研究對(duì)象采用 Affymetrix GeneChip Human Mapping 500K Array Set 基因芯片進(jìn)行基因分型。統(tǒng)計(jì)分析采用ProbAbel,VEGAS2,Metal,Plink和R等軟件。結(jié)果在第一階段研究中,采用1自由度交互作用檢驗(yàn)共分別發(fā)現(xiàn)49、59、62和38個(gè)獨(dú)立SNP位點(diǎn)與收縮壓、舒張壓、平均動(dòng)脈壓和脈壓的交互作用關(guān)聯(lián)P值小于1×10-4;采用2自由度主效應(yīng)與交互效應(yīng)聯(lián)合檢驗(yàn)共發(fā)現(xiàn)69、65、77和55個(gè)獨(dú)立SNP位點(diǎn)分別與收縮壓、舒張壓、平均動(dòng)脈壓和脈壓的交互作用關(guān)聯(lián)P值小于1×10-4。對(duì)兩階段樣本meta分析,1自由度交互作用檢驗(yàn)發(fā)現(xiàn)3個(gè)SNP位點(diǎn)與吸煙的交互作用達(dá)到全基因組潛在顯著關(guān)聯(lián)水平(P1 ×1(-6),其中,rs2716127(LOC105378753,P1dfinteraction=7.7×10-7)和 rs4751139(EF3,P1dfinteraction=1.58×10-7)的交互作用與舒張壓相關(guān),rs2036086(LO105378150,P1df interaction = 6.16×10-7)的交互作用與平均動(dòng)脈壓相關(guān);2自由度主效應(yīng)與交互效應(yīng)聯(lián)合檢驗(yàn)發(fā)現(xiàn)rs1465405(ADRB2,P2df interaction = 4.3×10-8)與吸煙交互作用對(duì)脈壓的效應(yīng)達(dá)到全基因組顯著關(guān)聯(lián)水平(P5×10-8),rs2400643(ADB2,P2dfinteraction=5.33×10-7)與吸煙交互作用對(duì)收縮壓的效應(yīng)、rs4751139(EBF3,P2df interaction=5.00×10-7)與吸煙交互作用對(duì)舒張壓的效應(yīng)達(dá)到了全基因組潛在顯著關(guān)聯(lián)水平。在吸煙者和非吸煙者中,潛在關(guān)聯(lián)或者顯著關(guān)聯(lián)的SNP位點(diǎn)對(duì)血壓影響的效應(yīng)不同。例如,在InterAsia人群中,SNP rs2716127每增加一個(gè)T等位基因,吸煙者的平均舒張壓升高1.91mmHg,而非吸煙者的平均舒張壓降低0.73mmHg,在BAS人群中結(jié)果相似。本研究同時(shí)發(fā)現(xiàn)7個(gè)既往東亞人群報(bào)道的血壓SNP位點(diǎn)與吸煙有交互作用(P值通過Bonferroni多重校正),位于7個(gè)基因內(nèi),分別是CACNA1D、FGF5、ARL3、CYP17A1、NM2、NT5C2和ATP2B1。7個(gè)SNP位點(diǎn)總體解釋的收縮壓、舒張壓、平均動(dòng)脈壓和脈壓的變異比例分別為1.79%、2.28%、2.24%和0.52%,加入吸煙交互作用之后,解釋的血壓變異比例分別增加到2.11%、2.46%、2.49%和0.85%,解釋的變異比例提升的百分比分別為17.69%、7.82%、11.06%和62.83%。此外,基于基因的關(guān)聯(lián)分析發(fā)現(xiàn)3個(gè)基因與吸煙的交互作用達(dá)到基因水平全基因組顯著關(guān)聯(lián)(P2.5×10-6),分別是 zBTB2、ZNF180和CNNM2。上述結(jié)果中,LOC105378753、EBF3、LOC105378150、ZBTB2和ZNF180基因與血壓表型的關(guān)系是首次報(bào)道。結(jié)論本研究首次在中國(guó)人群中開展了全基因組基因-吸煙交互作用與血壓關(guān)系的GWIES研究,發(fā)現(xiàn)ADRB2rs1465405與血壓顯著相關(guān),EBF3 rs4751139、LOC105378150 rs2716127和LOC1053 78150 rs2036086 三個(gè)位點(diǎn)與血壓潛在相關(guān);此外,基于基因水平的分析鑒定出ZBTB2、ZNF180和CNNM2三個(gè)基因與血壓顯著相關(guān)。本研究結(jié)果提示基于基因-環(huán)境交互作用分析策略不僅可以鑒定出新的血壓相關(guān)遺傳位點(diǎn),而且基因-環(huán)境交互作用可以提升解釋缺失的血壓變異。研究結(jié)果尚需進(jìn)一步在不同人群中進(jìn)行大規(guī)模驗(yàn)證,同時(shí)開展功能學(xué)研究,解釋這些位點(diǎn)的潛在生物學(xué)機(jī)制。第二部分:鈣離子通道相關(guān)基因?qū)h族人群血壓長(zhǎng)期變化的影響背景與目的高血壓是全球首要致病危險(xiǎn)因素。近年來,盡管通過GWAS發(fā)現(xiàn)一系列血壓相關(guān)易感基因,但血壓調(diào)控的遺傳機(jī)制還不明確。以關(guān)鍵血壓易感基因?yàn)榍腥朦c(diǎn)深入研究,可以高效識(shí)別新的血壓易感位點(diǎn),有助于解析血壓的調(diào)節(jié)機(jī)制。電壓門控鈣離子通道(voltage-dependent calcium channels,VDCCs)在血管平滑肌細(xì)胞收縮等血壓調(diào)控過程中具有重要作用,既往橫斷面調(diào)查發(fā)現(xiàn)VDCCs相關(guān)基因與血壓表型相關(guān),但是這些遺傳變異是否影響血壓水平長(zhǎng)期變化及高血壓發(fā)病尚不清楚。本研究旨在通過單個(gè)SNP位點(diǎn)和基于基因的關(guān)聯(lián)分析,探討VDCCs基因與血壓長(zhǎng)期變化和高血壓發(fā)病之間的關(guān)系。研究對(duì)象與方法本研究的研究對(duì)象均來自于鹽敏感性遺傳流行病學(xué)網(wǎng)絡(luò)(Genetic Epidemiology Network of Salt GenSalt Sensitivity,GenSalt)研究,共納入 633 個(gè)家庭的 1,768 名研究對(duì)象�；�調(diào)查時(shí)間為2003-2005年,并分別于2008-2009年和2011-2012年開展兩次隨訪調(diào)查。血壓測(cè)量使用隨機(jī)零點(diǎn)血壓計(jì),每天測(cè)量3次,每次間隔時(shí)間不少于30秒,每次調(diào)查連續(xù)測(cè)量3天,共9次,將9次測(cè)量值的平均收縮壓和舒張壓作為分析血壓。本研究共納入分析9個(gè)VDCCs相關(guān)基因,經(jīng)過質(zhì)量控制后,9個(gè)基因內(nèi)的219個(gè)SNP納入分析。應(yīng)用混合線性模型分析每個(gè)SNP與血壓長(zhǎng)期變化的關(guān)系;應(yīng)用廣義混合線性模型,在剔除基線患有高血壓的173名研究對(duì)象后,分析每個(gè)SNP與高血壓發(fā)病的關(guān)系。采用截點(diǎn)乘積法(truncated product method,TPM),整合單個(gè)SNP分析得到的P值,進(jìn)行基于基因的分析。全部統(tǒng)計(jì)分析結(jié)果采用Bonferroni法進(jìn)行多重檢驗(yàn)校正。結(jié)果1,768名GenSalt研究對(duì)象的男性比例為52.3%,基線階段平均年齡為39歲,平均體質(zhì)指數(shù)(body mass index,BMI)為23.4 kg/m2,平均收縮壓為116.9mmHg,平均舒張壓為73.8mmHg。經(jīng)過平均7.2年的隨訪,平均收縮壓上升至129.1mmHg,平均舒張壓上升至82.2mmHg,同時(shí)出現(xiàn)512例新發(fā)高血壓患者,高血壓累積發(fā)病率為32.1%。在單個(gè)SNP位點(diǎn)分析中,CACNA1A基因內(nèi)的SNP位點(diǎn)rs8182538與舒張壓的長(zhǎng)期變化相關(guān),且經(jīng)Bonferroni多重校正后仍達(dá)統(tǒng)計(jì)學(xué)顯著水平(P = 9.9×10-5)。rs8182538的基因型為C/C、C/T和T/T的研究對(duì)象,年均舒張壓增長(zhǎng)幅度分別為0.85、1.03和1.19mmHg。rs8182538與收縮壓長(zhǎng)期變化也有類似趨勢(shì)(P=0.022)�；诨虻年P(guān)聯(lián)分析發(fā)現(xiàn)CACNA1A與舒張壓的長(zhǎng)期變化顯著相關(guān)(P=2.0×10-5),C4CNA1C基因與收縮壓的長(zhǎng)期變化顯著相關(guān)(P=1.4×0-4)。去除CACNA1A和CACNA1C基因內(nèi)最顯著的SNP位點(diǎn)后,CACNA1A和CACNA1C基因整體變異仍分別與舒張壓和收縮壓長(zhǎng)期變化顯著相關(guān)。結(jié)論我們首次發(fā)現(xiàn)中國(guó)漢族人群中CACNA1A基因的常見SNP位點(diǎn)rs8182538與舒張壓水平長(zhǎng)期變化顯著相關(guān),同時(shí)基于基因水平的關(guān)聯(lián)分析發(fā)現(xiàn)CACNA1A和CACNA1C基因整體分別與舒張壓和收縮壓長(zhǎng)期變化相關(guān)。后續(xù)在大樣本中的重復(fù)驗(yàn)證及功能學(xué)研究將有助于進(jìn)一步闡明CACNA1A和CACNA1C基因的血壓調(diào)節(jié)機(jī)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.

【學(xué)位授予單位】：北京協(xié)和醫(yī)學(xué)院
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2017
【分類號(hào)】：R544.1

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