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煤矿工人轮班制与RAAS基因多态性交互作用对EH的影响
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摘要
目的
     原发性高血压(EH)是遗传因素和环境因素共同作用而引起的复杂性疾病,基因-基因、环境-环境以及基因-环境因素间交互作用在原发性高血压的发病中起重要的作用,因此应将遗传因素与环境因素结合起来探讨原发性高血压的病因。肾素-血管紧张素-醛固酮系统(RAAS)能够调节血容量和血压水平,在原发性高血压的发病及心血管病理发生发展中起重要作用,编码该系统的基因就成为原发性高血压重要的侯选基因。轮换班制度作为一种职业性社会心理因素,干扰生物节律,直接或间接引起一系列生理、心理等方面的应激反应。轮换班制度作为一种潜在的危险因素容易诱发心血管疾病等慢性疾病。本研究是以煤矿井下作业工人为研究对象的病例-对照研究,从环境因素和遗传因素两方面分析轮换班和基因多态性与原发性高血压的关系,探讨轮换班制度与基因多态性交互作用对原发性高血压的影响,从而为煤矿工人原发性高血压的防治提供理论依据。
     内容与方法
     1研究对象的选择
     随机选择参加2010年职业健康检查的某地区汉族男性煤矿井下作业工人1048例为研究对象。严格按照纳入排除标准选择病例和对照。研究对象经知情同意后入选。
     2现场流行病学调查
     自行设计职业流行病学调查表,经预调查反复修改后使用;统一培训调查员,采用面对面访谈式问卷调查;调查内容包括人口学资料、职业史、家族史、个人史(吸烟、饮酒等)、以及饮食习惯等;对被调查对象进行测量身高、体重、血压等体格检查。
     3实验室检测
     抽取清晨空腹静脉血5ml,用于生化指标检测及基因组DNA提取。全自动生化分析仪检测血糖(GLU)、尿酸(UA)、甘油三酯(TG)、总胆固醇(TC)、高密度脂蛋白(HDLC)、低密度脂蛋白(LDLC)、高敏C反应蛋白(hs-CRP)等生化指标。低渗法分离白细胞,酚氯仿法提取基因组DNA;聚合酶链反应(PCR)检测血管紧张素转换酶(ACE)插入/缺失(I/D)序列多态性;限制性片段长度多态性(PCR-RFLP)检测血管紧张素原(AGT)基因M235T位点、血管紧张素II1型受体(AT1R)基因A1166C位点和醛固酮合成酶(CYP11B2)基因-344T/C位点的多态性。
     4统计分析
     Epidata3.0数据库管理软件建立数据库,SPSS16.0、SAS8.0、MDR2.0统计分析软件进行数据分析。计量资料以均数±标准差(x|-±s)表示,组间比较采用t检验或方差分析;计数资料组间比较采用χ~2检验或确切概率法(fisher’s test)。
     采用χ~2检验分析基因型分布是否符合Hardy-Weinberg遗传平衡定律,比较病例组和对照组之间基因型和等位基因的分布;单因素条件logistic回归分析轮换班、基因多态性与原发性高血压的关系;采用叉生分析、多因素logistic回归、多因子降维法分析基因-基因和环境-基因交互作用对原发性高血压的影响。
     检验水准α=0.05,P<0.05,差异有统计学意义。
     结果
     1环境因素与原发性高血压的关系
     单因素分析表明,超重或肥胖者发生原发性高血压的危险是正常体重者的2.14(95%CI:1.67~2.74)倍,有高血压家族史者发生原发性高血压的危险增高1.49(95%CI:1.14~1.94)倍,从事轮换工作发生原发性高血压的危险是正常固定班的1.45(95%CI:1.12~1.86)倍,经常参加体育锻炼者发生原发性高血压的危险是不经常参加体育锻炼的0.64(95%CI:0.49~0.84)倍,打鼾者发生原发性高血压的危险是不打鼾者的1.28(95%CI:1.09~1.51)倍,差异有统计学意义(P<0.05);饮食方面食盐摄入量较多可使原发性高血压的发病风险增加1.20(95%CI:1.04~1.39)倍,较多食用粗粮、蔬菜、水果则可降低原发性高血压的发病风险。病例组和对照组血液生化指标GLU、UA、TG、TC、HDLC、LDLC水平比较,差异有统计学意义(P<0.05),其水平异常增高可不同程度地增加或降低原发性高血压的发病危险。
     多因素logistic回归分析在排除研究因素间的干扰、控制混杂因素的影响后,表明BMI≥24kg/m2、高血压家族史、轮换班、血糖、TC/HDLC≥4.5、LDLC≥2.7mmol可分别使原发性高血压的发病危险增加2.09(95%CI:1.59~2.74)、1.47(95%CI:1.09~1.97)、1.44(95%CI:1.09~1.90)、1.45(95%CI:1.04~2.01)、2.39(95%CI:1.69~3.38)和2.18(95%CI:1.62~2.95)倍,差异有统计学意义(P<0.05),是原发性高血压的危险因素;增加水果摄入量、体育锻炼使原发性高血压的发病危险降低,其OR(95%CI)分别为0.65(0.49~0.88)和0.74(0.61~0.91),差异有显著性意义(P<0.05),是原发性高血压的保护性因素。
     2基因多态性与原发性高血压的关系
     AGT基因M235T位点MM、MT、TT基因型频率在病例组和对照组分别为13.93%、46.37%、39.70%和16.60%、52.48%、30.92%,基因型在两组中的分布有显著性差异(χ~2=8.92,P=0.01);病例组携带T等位基因的频率(62.88%)高于对照组(57.16%),差异有统计学意义(χ~2=7.16,P=0.01),但多因素分析尚不能认为AGT基因M235T多态性与原发性高血压发病风险有关(P>0.05)。
     ACE基因插入/缺失序列II、ID、DD基因型在病例组和对照组中频率分别为45.99%、39.31%、14.70%和49.81%、40.46%、9.73%,基因型在两组中的分布比较,差异无统计学意义(χ~2=6.16,P=0.05);病例组携带D等位基因的频率(34.35%)高于对照组(29.96%),差异有统计学意义(χ~2=4.63,P=0.03)。多因素分析表明携带DD基因型者发生原发性高血压的风险增加1.73(95%CI:1.12~2.68)倍,差异有统计学意义(P<0.05),ACE基因DD基因型可能是原发性高血压的易感基因型。
     AT1R基因A1166C位点AA基因型频率病例组(91.79%)高于对照组(87.60%),组间分布有显著性差异(χ~2=5.00,P=0.03);等位基因A和C的分布在两组间无显著性差异(P>0.05)。多因素分析表明携带C等位基因的基因型发生原发性高血压的风险是AA基因型的0.55(95%CI:0.35~0.87)倍,差异有统计学意义(P<0.05),提示A等位基因可能是原发性高血压的易感基因。
     CYP11B2基因-334T/C位点TT、TC、CC基因型频率在病例组和对照组分别为50.76%、41.22%、8.02%和49.24%、42.56%、8.20%;病例组携带T等位基因和C等位基因的频率分别是71.37%、28.63%,对照组分别为70.52%、29.48%,两组中基因型及等位基因分布均无显著性差异(P>0.05),且多因素分析表明不能认为CYP11B2基因与原发性高血压的发病有关。
     3基因-基因交互作用分析
     叉生分析方法分析基因间相加模型的交互作用,结果显示AGT基因与ACE基因间交互项OR_(int)=0.10<1,对交互作用进行显著性检验,差异有统计学意义(χ~2=19.26, P=0.01);AGT基因与CYP11B2基因交互项OR_(int)=8.54,对交互作用进行显著性检验,差异有显著性(χ~2=16.47, P=0.04);AGT基因与AT1R基因间、ACE基因与AT1R基因间交互项OR_(int)值分别为1.10和1.10,对交互作用进行显著性检验,差异均有统计学意义(P<0.05);未发现ACE基因与CYP11B2基因间和AT1R基因与CYP11B2基因间存在基于相加模型的交互作用(P>0.05)。
     将各基因变量及其交互项共同引入Logistic回归模型,同时控制轮换班、体重指数、高血压家族史等因素的影响,分析基因间交互作用,尚不能认为各基因在原发性高血压的发生发展过程中存在基于相乘模型的交互作用(P>0.05)。应用MDR方法分析基因间交互作用时所有模型的显著性检验均无统计学意义(P>0.05),不能认为基因间存在交互作用。
     4基因-轮换班交互作用分析
     利用叉生分析轮换班与基因间基于相加模型的交互作用,结果表明轮换班与AGT、ACE、AT1R基因交互项OR_(int)<1,且差异均有显著性(P<0.05),提示存在负交互作用;未发现轮换班与CYP11B2基因存在基于相加模型的交互作用(P>0.05)。将轮换班、基因变量以及两者的交互项共同引入logistic回归模型,分析轮换班与基因基于相乘模型的交互作用与原发性高血压的关系,轮换班与AGT、ACE、AT1R、CYP11B2基因交互项ORnt值分别为1.05(95%CI:0.70~1.56)、0.84(95%CI:0.56~1.25)、0.58(95%CI:0.23~1.47)、0.81(95%CI:0.52~1.27),交互作用显著性检验均无统计学意义(P>0.05),尚不能认为轮换班与各基因间存在相乘模型的交互作用。
     5基因-高血压家族史交互作用分析
     利用叉生分析高血压家族史与基因间基于相加模型的交互作用,高血压家族史与AGT、AT1R基因交互项ORnt值分别为1.40和1.12,差异有显著性(P<0.05);高血压家族史与ACE基因交互项ORnt值=0.71,差异有统计学意义(P<0.05);高血压家族史与CYP11B2基因间交互作用显著性检验,差异无统计学意义(P>0.05)。Logistic回归分析高血压家族史与基因间基于相乘模型的交互作用与原发性高血压的关系,高血压家族史与AGT、ACE、AT1R、CYP11B2基因交互项ORnt值分别为1.12(95%CI:0.73~1.72)、1.49(95%CI:0.96~2.30)、1.35(95%CI:0.50~3.66)、1.03(95%CI:0.64~1.64),交互作用显著性检验均无统计学意义(P>0.05),尚不能认为高血压家族史与各基因交互作用与原发性高血压有关。
     6基因-体重指数交互作用分析
     叉生分析体重指数与基因间基于相加模型的交互作用,体重指数与AGT、ACE、AT1R基因交互项ORnt值分别为0.61、0.14、0.58,差异有显著性(P<0.05);体重指数与CYP11B2基因间交互作用显著性检验,差异有统计学意义(P<0.05)。logistic回归分析体重指数与基因间基于相乘模型的交互作用与原发性高血压的关系,体重指数与AGT、AT1R、CYP11B2基因交互项ORnt值分别为1.11(95%CI:0.75~1.64)、0.66(95%CI:0.27~1.62)、1.29(95%CI:0.84~1.99),交互作用显著性检验均无统计学意义(P>0.05);体重指数与ACE基因间交互项OR_(int)=0.61(95%CI:0.41~0.90),交互作用显著性检验有统计学意义。
     7MDR法分析基因-环境交互作用
     MDR方法对基因-环境交互作用分析结果表明,4因子和7因子模型为基因-环境因素MDR交互作用模型,轮换班与体重指数、水果摄入量、TC/HDLC、AGT、ACE、CYP11B2存在交互作用,并能增加原发性高血压的发病危险。
     结论
     1轮换班可能是原发性高血压的危险因素。
     2ACE基因I/D序列多态性和AT1R基因A1166C基因多态性与原发性高血压有关,ACE基因DD基因型和AT1R基因A1166C基因多态性AA基因型可能是原发性高血压的易感基因型。
     3轮换班与ACE基因I/D多态性、AT1R基因A1166C位点多态性间存在基于相加模型的交互作用;轮换班与体重指数、水果摄入量、TC/HDLC、AGT、ACE、CYP11B2存在交互作用,并能增加原发性高血压的发病危险;未发现基因间存在交互作用。
Objectives
     Essential hypertension (EH) is a complex disease caused by genetic andenvironmental factors. We should explore mechanism of EH combined genetic factorswith environmental factors, for which the interaction between genetic factors andenvironmental factors plays an important role in the pathogenesis of EH. Therenin-angiotensin-aldosterone system (RAAS), which can regulate blood volume andblood pressure levels, is important for the pathogenesis and pathology ofcardiovascular disease, therefore the gene from RAAS maybe important candidategenes of hypertension. Shift work as a potential risk factor is likely to causecardiovascular disease and other chronic diseases. A case-control study based on coalworkers was designed to analyze the relationship among gene polymorphisms, shiftwork and EH, the interaction of gene-environmental was analyzed too.
     Methods
     1Choice of object
     A case-control study was adopted.1048coal workers, who acceptedoccupational health examination were chosen to participate in this study.
     2Field epidemiological investigation
     Design occupational epidemiology questionnaire, face-to-face interview wasconducted. The survey contents including demographic data, occupational history,family history, personal history (smoking, drinking, etc), as well as eating habits, etc.;measuring height, weight, blood pressure and other physical examination.
     3Laboratory test
     5ml venous blood were extracted in early morning, some used for the detectionof biochemical indicators including blood glucose (GLU), uric acid (UA),triglycerides (TG), total cholesterol (TC), high-density lipoprotein (HDLC), lowdensity lipoprotein (LDLC), C-reactive protein (CRP) and so on. Separate whiteblood cells with hyptonic method, and genomic DNA were extracted with phenol-chloroform methods. Polymerase chain reaction (PCR) was used to detectpolymorphism of insertion/deletion (I/D) polymorphism of angiotensin-convertingenzyme (ACE). The polymorphisms of AGT-M235T, AT1R-A1166C andCYP11B2-344T/C gene were detected by polymerase chain reaction-restrictionfragment length polymorphism (PCR-RFLP).
     4Statistical Analysis
     Database was established with Epi-data3.0, SPSS16.0, SAS8.0and MDR2.0statistical analysis software were used for data analysis. The measurement data wereexpressed as x±s, t test or ANOVAS were used to compare the difference betweengroups.
     The χ~2test were used to analyze whether distribution of genotype in accordancewith Hardy-Weinberg genetic equilibrium or not; and compared the distribution ofgenotype and allele between case and control groups; Univariate analysis analyzed therelationship of environmental factors and gene polymorphism with essentialhypertension risk. Using stratifies analysis and multivariate analysis methodsanalyzed the relationship between interaction of genes-genes, environment-genewith EH.
     Test level of α=0.05, P <0.05expressed the difference was statisticallysignificant.
     Results
     1Environmental factors with EH
     Univariate analysis demonstrated that overweight or obese increased the risk ofEH2.14(95%CI:1.67~2.74) times; family history of hypertension increased therisk of EH1.49(95%CI:1.14~1.94) times; shift work increase the risk of EH1.45(95%CI:1.12~1.86) times; participate in regular physical exercise increased the riskof suffering from EH0.64(95%CI:0.49~0.84) times compared with not participatein physical exercise; snorers with the risk of EH was1.28(95%CI:1.09~1.51) timescompared with not snorers, and the difference was statistically significant (P <0.05).Much more salt intake is likely to increase the risk of EH of1.20(95%CI:1.04~1.39) times, but eat more coarse grains, vegetables, fruits may reduce the risk of EH.There was significant difference of GLU, UA, TG, TC, HDLC and LDLC levelbetween case group and control group.
     With multivariate analysis, BMI≥24kg/m~2, family history of hypertension, shift work, blood glucose, TC/HDLC≥4.5, LDLC≥2.7mmol may increase the risk ofEH of2.09(95%CI:1.59~2.74).1.47(95%CI:1.09~1.966),1.44(95%CI:1.09~1.90),1.45(95%CI:1.04~2.01),2.39(95%CI:1.69~3.38) and2.18(95%CI:1.62~2.95) times separately, and the difference was statistically significant (P <0.05),they were risk factors of EH. Increase intake of fruit, more physical exercise mayreduced the risk of EH, and the OR (95%CI) were0.65(0.49~0.88) and0.74(0.61~0.91), the difference was significant (P <0.05), they were protective factors of EH.
     2The relationship between gene polymorphism and essential hypertension
     There were significant differences in M235T genotypes and allele frequencies ofAGT gene between cases and control group (χ~2=8.92, P=0.01); the T allele frequencyin case group (62.88%) was higher than control group (57.16%), the difference wassignificant (χ~2=7.16, P=0.01). However, there is not yet that M235T polymorphism ofAGT gene is related with EH (P>0.05) in multivariate analysis.
     The II, ID and DD genotype frequency of ACE gene in cases and control groupswere45.99%,39.31%,14.70%and49.81%,40.46%,9.73%separately, and there wasno significant difference of distribution of genotype between case and control groups(χ~2=6.16, P=0.05). The allele frequency of D in case group (34.35%)was higher thancontrol group (29.96%), the difference was significant (χ~2=4.63, P=0.03). Multivariateanalysis revealed that carrying DD genotype increased the risk of EH of1.73(95%CI:1.12~2.68) times, the difference was statistically significant (P <0.05), DD genotypeof ACE gene might be the susceptible genotypes for EH.
     There was significant difference in distribution of AA genotype of AT1R genebetween case and control groups(χ~2=5.00, P=0.03). The distribution of alleles A andC was no significant difference between the two groups (P>0.05). Multivariateanalysis showed that the genotype that carrying C allele increase the risk of EH0.55(95%CI:0.35~0.87) times than AA genotype, the difference was statisticallysignificant (P <0.05), which suggesting that A allele may be susceptible gene for EH.
     TT, TC and CC genotype frequencies of CYP11B2gene-334T/C loci in case andcontrol groups were50.76%,41.22%,8.02%and49.24%,42.56%,8.20%respectively; carrying T allele and C allele frequencies in case group were71.37%,28.63%, in control group were70.52%,29.48%, there was no significant difference ofgenotype and allele distribution in the two groups (P>0.05), and multivariate analysisconcluded that it can not be considered CYP11B2gene was related with thepathogenesis of EH.
     3Analysis of interaction among genes
     Stratify analysis method was used to analyze interaction based on the additivemodel among the genes, the results showed that there were negative interactionbetween the AGT gene and ACE gene (χ~2=19.26, P=0.01); There was significantdifference of interactions between AGT gene and CYP11B2gene (χ~2=16.47, P=0.04),between AGT gene and AT1R gene, between ACE gene and AT1R gene. Still, nosignificant interactions based on the additive model between ACE gene and CYP11B2gene, AT1R gene and CYP11B2gene were founded.
     After adjusted shift work, BMI, family history of hypertension and other factors,gene variables and their interaction terms were introduced to logistic regression modelfor the multiplicative model of interaction analysis, the results show that there was notinteraction among genes during the development of EH(P>0.05).
     4Interaction analysis between gene and shift work
     Stratify analysis method was used to analyze interaction based on the additivemodel between shift work and gene, the results showed that there was negativeinteraction between shift work and AGT、ACE、AT1R genes, and the differences weresignificant (P<0.05). Shift work, genetic variables, and the interaction term wereintroduced to logistic regression model, to analyze the relationship of shift work andgene interaction based on the multiplicative model with EH, the interaction OR_(int)values of shift work and AGT、ACE、AT1R、CYP11B2genes were1.05(95%CI:0.70~1.56),0.84(95%CI:0.56~1.25),0.58(95%CI:0.23~1.47),0.81(95%CI:0.52~1.27) separately, there were not statistically significant (P>0.05), still it can notbelieve that there were interactions based on multiplicative model between shift workand each gene.
     5Interaction analysis between gene and family history of hypertension
     Stratify analysis method was used to analyze interaction based on the additivemodel between family history of hypertension and genes, it found that OR_(int) values ofinteraction terms between family history of hypertension and AGT, AT1R, ACE genewas1.40,1.12,0.71respectively, the difference were significantly (P<0.05); therewas no interactions between family history of hypertension and CYP11B2gene.Logistic regression analysis was used to analyze the interaction between familyhistory and gene based on multiplicative model, it can not believe that there weresignificant difference between family history of hypertension and AGT、ACE、AT1R、 CYP11B2genes.
     6Interaction analysis between gene and BMI
     Stratify analysis method was used to analyze interaction based on the additivemodel between BMI and genes, it concluded that there were significant difference ininteractions between BMI and AGT, ACE, AT1R, CYP11B2genes(P<0.05). Logisticregression analysis was used to analyze the relationship of interaction between BMIand genes based on multiplicative model, OR_(int)values of interaction terms betweenBMI and AGT、AT1R、CYP11B2were1.11(95%CI:0.75~1.64)、0.66(95%CI:0.27~1.62)、1.29(95%CI:0.84~1.99) respectively, there were no significantdifference in interactions(P>0.05). However, there was interactions between BMIand ACE gene.
     7Gene-environment interaction analysis with MDR method
     MDR method was used to analyze gene-environment interaction, the resultsshowed that the4-factor and7-factor model were MDR interaction models of gene-environmental factors. There were interactions between shift work and BMI, fruitintake, TC/HDLC, AGT, ACE, CYP11B2gene, which can increase the risk of theincidence of EH.
     Conlusions
     1Shift work may be risk factor of EH.
     2The polymorphism of sequence I/D of ACE gene and A1166C of AT1R gene mightrelated with EH. DD genotype of ACE gene and AA genotype of AT1R gene may besusceptible genotype of EH.
     3There were interactions based on additive model between shift work and ACE geneI/D polymorphism, AT1R gene A1166C polymorphism. Still there were interactionsbetween shift work and BMI, fruit intake, TC/HDLC AGT, ACE, of CYP11B2, andwhich could increase the risk of the incidence of EH.
引文
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