【作者】 彭玲梅；

【导师】 姜晓丹； 谭盛；

【作者基本信息】 南方医科大学 ， 临床医学（专业学位）， 2013， 博士

【摘要】 研究背景缺血性脑卒中(Ischemic stroke, IS)是指突然发生的脑局部血液循环障碍导致脑组织缺血缺氧引起的局灶性神经功能缺损综合征。IS是世界范围内三大死亡疾病之一,也是成年人首位致残原因。由于目前IS的病因及发病机制尚未完全阐明,且临床上理想的治疗手段有限,使得其不仅发病率很高,致死率、致残率及复发率也较高,给个人和社会造成了巨大的负担。IS是一种由遗传和环境因素共同作用的复杂性疾病,遗传易感性与IS的发生发展密切相关。随着人类基因组计划的完成和分子遗传学的发展,能够反映个体间基因差异、决定疾病易感性和药物反应差异性的单核苷酸多态性(single neucleotide polymorphism, SNP)受到广泛重视,寻找致病易感候选基因成为当前研究的热点。近年来,越来越多研究认为,炎症在IS的病理生理过程中起重要作用。炎症因子作为候选易感基因之一,其基因多态性与IS发病风险的关系也倍受关注。转化生长因子-p1(transforming growth factor-β1, TGF-β1)是具有潜在抗炎特性的多功能细胞因子,目前发现其可通过多种途径参与脑缺血后损伤与修复的病理生理过程。TGF-β1在机体中的表达水平受其基因多态性的调控。TGF-β1基因位于人类染色体19q13.1-13.3,目前在该基因上至少已经发现了10个常见的基因多态性位点。其中,T869C(rs1982073; Leu10/Pro10; T29C; codon10)位点位于第一外显子信号肽序列,有研究称其可通过增加TGF-β1mRNA表达而提高TGF-β1在血浆中的水平,进而在疾病的发生发展中发挥其生物学功能。迄今为止,国内外已有多个流行病学研究调查了TGF-β1基因T869C多态性与IS发病风险的相关性。然而,这些研究的结果不完全一致,有的研究结果甚至还相互矛盾。考虑到单个研究由于样本量小且统计学和临床异质性差异大,缺乏有效的统计学效能,因此,我们运用Meta分析的方法,系统而全面地收集所有已发表的国内外相关文献,用定量合成的方法进行统计学处理,以期得到更加肯定和客观、可靠的结论。目的应用Meta分析的方法综合评估TGF-β1基因T869C多态性与缺血性脑卒中发病风险的关系。方法计算机检索PubMed、Cochrane图书馆、Science Direct、BIOSIS Previews、 CBM、CNKI、万方、维普等中英文数据库,辅以手工检索进行文献追溯,全面收集2013年3月以前发表的有关TGF-β1基因T869C多态性与缺血性脑卒中发病风险的国内外流行病学文献,严格制定纳入/排除标准,由两名研究者独立进行资料提取,采用Newcastle-Ottawa Scale (NOS)标准进行质量评估后、再以RevMan5.1和Stata12.0软件对符合质量要求的文献进行Meta分析。用比值比(odds ratio, OR)和95%可信区间(confidence interval, CI)作为评价标准,分别计算不同遗传模型下T869C基因多态性与缺血性脑卒中发病风险的关联程度,包括：等位基因模型(Cvs.T),共显性遗传模型(纯合子模型CC vs. TT;杂合子模型CT vs.TT)、显性遗传模型(CC+CT vs.TT)和隐性遗传模型(CC vs. CT+TT)。使用Q检验和12统计量进行异质性检验,根据异质性情况选择适当的效应模型进行数据合并。若各研究结果间无异质性,采用Mantel-Haenszel固定效应模型；否则采用DerSimoninan-Laird随机效应模型进行合并分析。根据人种、对照组来源以及研究类型进行亚组分析来探索异质性来源。用敏感性分析来评估结果的稳定性。通过绘制漏斗图定性观察联合Egger线性回归法定量检验来综合评估发表性偏倚。结果共纳入6个研究,其中4个为病例对照研究,2个为队列研究,包括1701例患者和10334例对照。异质性检验结果提示在所有遗传模型下各个研究间均存在显著异质性,因此采用DerSimoninan-Laird随机效应模型进行数据合并。6个研究合并分析的结果显示：TGF-β1基因T869C多态性与缺血性脑卒中风险的相关性无统计学意义[其中：等位基因模型C vs.T：OR=1.08,95%CI(0.88,1.32)；共显性遗传模型(纯合子模型CC vs.TT：OR=1.17,95%CI(0.79,1.72)；杂合子模型CT vs.TT：OR=0.91,95%CI(0.68,1.22))；显性遗传模型CC+CT vs.TT：OR=0.99,95%CI(0.73,1.35)；隐性遗传模型CC vs.CT+TT：OR=1.23,95%CI(0.95,1.59)]。基于人种及对照组来源的亚组分析结果同样显示,两者相关性无统计学意义；而基于研究类型的亚组分析结果显示,研究类型为队列研究的亚组中TGF-β1基因T869C多态性是缺血性脑卒中的危险因素[其中：等位基因模型Cvs.T：OR=1.18,95%CI(1.05,1.32)；共显性遗传模型(纯合子模型CC vs.TT：OR=1.40,95%CI(1.10,1.77)；杂合子模型CT vs.TT：OR=1.23,95%CI(1.02,1.49))；显性遗传模型CC+CT vs.TT：OR=1.27,95%CI(1.03,1.57)]；研究类型为病例对照研究的亚组分析结果则显示,携带CT基因型的人群发生缺血性脑卒中的风险减低[CT vs.CC：OR=0.72,95%CI(0.57,0.92)]。对各遗传模型进行敏感性分析所得合并效应量及异质性情况无明显改变,漏斗图和Egger检验结果均提示无发表性偏倚,表明Meta分析结果稳定可靠。结论1、根据Meta分析的结果,我们认为TGF-β1基因T869C多态性与缺血性脑卒中发病风险具有相关性的证据不足。2、由于纳入研究的样本量仍偏少,加之存在各研究间存在显著异质性,且未考虑到“基因-基因”以及“基因-环境”等协同作用的局限性,本Meta分析得出的结论尚待开展更多设计良好的大样本,以进一步进行相关的前瞻性分析。更多还原

【Abstract】 BackgroundIschemice stroke(IS) is manifested by the abrupt onset of focal neurologic deficits, which were caused by a suddent reduction or completely blockage of blood supply to local brain tissues. IS is a leading cause of death and adult long-term disability worldwide, and remains as an enormous burden for personality and society due to lack of illustrated etiology and effective treatments.IS is a multifactorial disease involving complex interactions between genetic and environmental factors, in which the genetic susceptibility has been considered playing an important role in the development of IS. With the accomplishment of the human genome project and the development of molecular genetics, the study on the single neucleotide polymorphism(SNP), which can reflect the variance among individuals and decide the susceptibility of diseases and response to drugs, is highly regarded as one of the most important post-genomic projects. Identification of the candidate gene susceptibility to IS has also become one of the most popular scientific focuses. Recently, emerging evidences have demonstrated that inflammation play an important role in the pathogenesis of IS. As one of the candidate susceptible gene of IS, the functional polymorphisms of inflammatory factors arouse close attentions.TGF-β1is a pleiotropic cytokine with potent anti-inflammation property, and has been considered as an essential risk factor in the inflammatory process of IS. The TGF-β1gene is located on chromosome19(q13.1-13.3) with several common known SNPs in this gene. Among them, T869C (rs1982073; Leu10/Pro10; T29C; codon10) polymorphism, located in the signal peptide sequence, has been indicated that it can increase the expression of TGF-β1mRNA, resulting in the elevated serum TGF-β1level.To date, several studies have been performed to investigate the association between T869C polymorphism of TGF-β1gene and risk of IS. However, the results remain controversial. Considering a single study may lack the power to provide reliable conclusion due to small amount of subjects, masses of statistical and clinical heterogeneities, we performed this meta-analysis combining eligible published literatures based on quantitative synthesis to derive a more convincing estimation for the association between T869C polymorphism and risk of IS.ObjectiveTo explore the association between TGF-β1T869C polymorphism and risk of ischemic stroke by performing a meta-analysis based on published articles.MethodsSystematic electronic searches of PubMed, Cochrane Library, Science Direct, BIOSIS Previews, Chinese Biomedical Database, Chinese National Knowledge Infrastructure, and WANGFANG Database until March2013were performed to idetify the published epidemiological studies on TGF-β1T869C polymorphism and risk of ischemic stroke. Strict inclusion and exclusion criteria were determined before data analyses. Data were reviewed and extracted by2independent investigators. Quality of the included studies was evaluated independently using Newcastle-Ottawa Scale (NOS). The strength of association between TGF-β1T869C polymorphism and IS risk was assessed by crude ORs with corresponding95%CIs under the following five genetic models:the allele comparison(C vs. T), the homozygote comparison (CC vs. TT), the heterozygote comparison (CT vs. TT), the dominant model (CC+CT vs. TT), and the recessive model (CC vs. CT+TT). The degree of heterogeneity between studies was detected by the Q-test and I2-statistics. The pooled estimate was combined by a random-effect model(DerSimonian-Laird method) or a fixed-effect model (Mantel-Haenszel method) according to whether the heterogeneity existed or not. Subgroup analysis based on ethnicity, source of controls, and study design were further conducted respectively to explore the potential sources of heterogeneity. Sensitivity analysis was performed to elucidate the stability of the outcomes. Publication bias was evaluated by funnel plot and Egger’s test. All analyses were conducted using RevMan5.1and Stata12.0software.ResultsA total of6studies involving1701cases and10334controls were included in this meta-analysis. The overall estimates did not show any significant association between TGF-β1T869C polymorphism and risk of IS under all genetic models (allele comparison C vs. T:OR=1.08,95%CI=0.88-1.32; homozygote comparison CC vs. TT: OR=1.17,95%CI=0.79-1.72; heterozygote comparison CT vs. TT:OR=0.91,95%CI=0.68-1.22; dominant model CC+CT vs. TT:OR=0.99,95%CI=0.73-1.35; recessive model CC vs. CT+TT:OR=1.23,95%CI=0.95-1.59). Similar lacking associations were observed in subgroup analysis based on ethnicity and source of controls. When stratified by study design, a significant increased association of IS risk was found in cohort studies under genetic models except recessive model (C vs. T:OR=1.18,95%CI=1.05-1.32; CC vs. TT:OR=1.40,95%CI=1.10-1.77; CT vs. TT: OR=1.23,95%CI=1.02-1.49; CC+CT vs. TT:OR=1.27,95%CI=1.03-1.57; CC vs. CT+TT, OR=1.21,95%CI=0.99-1.47), whereas a significant decreased risk was detected under heterozygote comparison(CT vs. CC:OR=0.72,95%CI=0.57-0.92) in the case-control studies. Sensitivity analysis did not significantly alter in overall and subgroup results under all genetic models; In addition, results from funnel plot and Egger’s test indicated no evidence of publication bias.Conclusion1. Upon the results of this meta-analysis, it implied that the current epidemiological studies of TGF-β1T869C polymorphism were too inconsistent to draw a conclusion on the association with IS susceptibility.2. Given the small sample size and the remarkable heterogeneity in it, more well-designed prospective large-scale studies with different ethnicities considering both genetic and environmental factors will be performed further in future.更多还原