缺血性脑卒中相关炎症因子及候选基因多态性与环境暴露交互作用的分子流行病学研究
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摘要
研究背景
缺血性脑卒中是一种受遗传、环境共同作用的慢性疾病,基因与环境间的交互作用与缺血性脑卒中易感性密切相关。随着人类基因组密码的逐渐解译,从候选基因及全基因组水平探讨基因多态性与缺血性脑卒中易感性的发病机制成为医学界关注的热点。近年来,越来越多的研究表明炎症可能与缺血性脑卒中、冠心病发病机理密切相关。但是关于炎症因子多态性与缺血性脑卒中易感性的研究,目前,国内报道尚不多。
研究目的1.探究IL-6基因-174G/C、-572G/C多态性与缺血性脑卒中易感性。2.探讨TNF-α-238G/A、-308G/A多态性与缺血性脑卒中易感性。3.探讨IL-1RN、IL-4小卫星VNTR多态性与缺血性脑卒中易感性。4.探讨12P13两候选SNPs与缺血性脑卒中易感性。5.应用CART及MDR模型构建缺血性脑卒中发病风险预测模型。
研究方法
按照TOAST标准,开展以医院为基础的1:1配对病例-对照研究。研究对象来自于深圳三大医院、牡丹江医学院附属医院、新疆哈密市多家三甲医院,病例和对照按年龄≤5岁、性别、民族相同进行匹配,共收集汉族样本648对,维族样本100对。使用一致的个案调查表调查研究对象。用Taqman探针技术及尾巴引物延伸方案来检测基因型。拟合logistic回归模型分析基因多态性与缺血性脑卒中之间的关联性,另外,运用分类回归树构建缺血性脑卒中发病风险预测模型,构建单体型及运用MDR(多因子降维法)分析基因与基因、基因与环境之间的交互作用。
主要研究结果
1.单因素Logistic回归分析结果显示:文化水平、BMI、WHR、吸烟及高血压、负性生活事件、糖尿病、TG等是缺血性脑卒中的危险因素。多变量Logistic回归模型表明:吸烟(OR=2.158;95%CI:1.554~2.997)、腰臀比(OR=2.777;95%CI:2.084~3.699)、糖尿病(OR=1.519;95%CI:1.107~2.086)和高血压(OR=3.143;95%CI:2.445~4.042)是汉族人群缺血性脑卒中发病的独立危险因素;而饮茶史(OR=0.347;95%CI:0.269~0.448)是汉族人群缺血性脑卒中发病的独立保护因素。然而在维族人群中,我们仅发现腰臀比(OR=5.707;95%CI:2.688~12.116)和高血压(OR=13.544;95%CI:5.496~33.380)为其人群缺血性脑卒中发病的独立危险因素。
2. IL-6基因G-572C多态性基因型分布差异具有统计学意义,在未调整混杂因素前后,携带GC基因型的个体患缺血性脑卒中风险为CC的1.49倍,P=0.00。IL-6基因G-572C多态性病例组的G等位基因频率高于对照组,差异有统计学意义(P<0.01),可见随着等位基因G的增加,发生缺血性脑卒中的危险性也增高。在调整上述影响因素后,GC是缺血性脑卒中发病的独立危险因素,OR值为1.446,P=0.004。在维族人群中,以携带CC基因型的个体作为参考基因型,未发现GC基因型在病例组与对照组间存在显著性差异,而GG基因型的携带频率病例组则明显低于对照组比值比为0.36(95% CI:1.19-1.88;P<0.05),G等位基因的携带频率,病例组也明显低于对照组比值比为0.67(95% CI:0.45-0.99;P<0.05)。
3.肿瘤坏死因子启动子-238G/A多态性与两人群缺血性脑卒中发病的关联性不显著。然而,-308 G/A多态性与两人群关联性较强,在两人群中,病例组GA的分布频率均明显低于对照组,同时病例组A等位基因的分布也明显低于对照组。提示,A等位基因对于两人群缺血性脑卒中的发病风险具有保护作用,GA杂合子在调整常见的风险因素后,关联依然显著,其可能是一项中国人群缺血性脑卒中发病的独立的保护因素。
4. IL-4 VNTR和IL-1RN VNTR单个VNTR调整相关混杂因素后,发现其与缺血性脑卒中发病的关联性不显著。然而,两VNTR构建单体型后,则发现2R-2R为汉族人群缺血性脑卒中的风险单体型。
5. 12P13区Rs11833579 A等位基因为在中国汉族人群中风险等位基因,A等位基因型携带者发生缺血性脑卒中的危险性是G等位基因型者的1.27倍,隐性模式下风险性更高,而在维族中却未发现这一结果。Rs11833579多态性在不同民族人群中的频率存在显著差异,提示不同人群中存在明显的遗传异质性。Rs11833579与Rs12425791可能存在交互作用,A-G单体型在中国汉族人群中为缺血性脑卒中的风险单体型, A-G单体型携带者发生缺血性脑卒中的危险性是G-G基因型者的1.52倍。
6.采用分类回归树构建缺血性脑卒中发病风险预测模型,汉族分类树模型生长深度为5层,共纳入7个解释变量,维族分类回归树模型生长深度为3层,共纳入3个解释变量。运用筛检模型评价指标对分类树的灵敏度和特异度进行评价,评价结果表明灵敏度及特异度均较为合理。多因子降维法提示基因-基因,基因-环境间存在交互作用;分类树模型能够较好的拟合缺血性脑卒中发病风险的预测模型。
研究结论
1.传统的心脑血管疾病行为危险因素是汉族及维族人群缺血性脑卒中发生的主要危险因素,高血压、糖尿病、血脂和体重等仍是缺血性脑卒中发病的危险因素。
2.在汉族人群中IL-6-572 G等位基因型可能为缺血性脑卒中的风险基因型,而维族则可能为缺血性脑卒中的保护基因型。
3. TNF-α-308GA杂合子基因型可能是一项中国人群缺血性脑卒中发病的独立的保护因素。
4.未发现单个IL-4或IL-1RN VNTR与IS发病存在显著关联性,但两VNTR的交互作用与IS发病存在一定关联性。
5.12P13区Rs11833579 A等位基因在隐性遗传模式下会增加在汉族人群缺血性脑卒中的风险,A-G单体型在中国汉族人群中为缺血性脑卒中的风险单体型。
6.多因子降维法提示基因-基因,基因-环境间存在一定交互作用;分类回归树模型适合拟合两人群缺血性脑卒中发病风险预测模型。
创新点本研究在国内属于首次基于炎症因子相关信号转导通路及相关基因功能位点在多民族人群中分析基因多态性及环境暴露交互作用与缺血性脑卒中的关联性。同时本研究基于国外GWAS观察结果,分析相关候选基因与中国人群缺血性脑卒中的关联性。本研究还采用全新尾巴引物方案的策略,灵敏检测IL-4与IL-1RN基因的VNTR与缺血性脑卒中的关联性,在国内外尚属首次。
此外本研究在多民族人群中采用分类树结合MDR法分析构建风险预测模型。
Backgrounds
Ischemic stroke (IS) is a chronic disease influenced by environmental and genetic factors. Gene-environmental interaction are closely related with the susceptibility of IS. With the completement of Human Hapmap, it has become the focus in medical fields to study the pathogenesis of IS from the view of candidate Gene and whole-genome. In recent years, more and more studies have suggested that Inflammation play important roles in IS and coronary heart disease (CHD). However, studies on the association of the inflammatory cytokines and the interaction between the gene polymorphisms and environment exposures with IS are rare presently in the Han population.
Objectives
1. To explore the association of the G-174C, G-572C polymorphisms of IL-6 with the susceptibility of IS.
2. To explore the association of the G-238A, G-308A polymorphisms of TNF-αwith the susceptibility of IS.
3. To explore the association of the VNTR polymorphisms of IL-1RN and the VNTR with the susceptibility of IS.
4. To explore two key SNPs on chromosome 12p13 with the susceptibility of IS.
5. Classification tree model and Multifactor dimensionality reduction were applied to explore the possible interaction between gene and environment and build the risk model for IS.
Methods
Case collection was made according to the diagnostic criteria of TOAST, two 1:1 matched hospital- based case-control studies were performed. We enrolled inpatients attending the stroke units of five large general hospitals in Shenzhen, Heinongjiang and Xinjiang from September 2003 to February2009. A total of 748 subjects presenting within 24h of symptom onset were enrolled in two case–control studies. Additionally, 748 age-, gender- and ethnicity-matched normal healthy controls were randomly selected from healthy volunteers from four local community-based populations. A structured questionnaire was used to record general information, clinical history of IS and associated clinical parameters, and epidemiological data. Genotypes were examined by using Taqman Primers and a novel tailed primers protocol. Logistic regression models were used to study the association between the polymorphisms and ischemic stroke. Classification tree model was applied to build up the risk model for IS, multifactor dimensionality reduction and Haplotype analyses were used to assess the possible interaction between gene and environment.
Results
1. Univariate logistic regression showed that traditional risk factors of IS including education, income, BMI, smoking, WHR,hypertension, diabetes, negative events and TG. In two multivariate logistic models, WHR, smoking, Diabetes, and Hypertension were positively associated with IS, with OR=2.158 (95%CI: 1.554~2.997), OR=2.777 (95%CI: 2.084~3.699), OR=1.519 (95%CI: 1.107~2.086), OR=3.143 (95%CI: 2.445~4.042) respectively, while tea-drinking was inversely associated with IS, with an OR of 0.347 (95%CI: 0.269~0.448) in the Hans. However, we only find WHR and Hypertension were independent risk factors of IS with OR=2.158 (95%CI: 1.554~2.997) and OR=2.777 (95%CI: 2.084~3.699) respectively. 2. For IL-6 G-572C polymorphisms, significant difference was found in the distributions of genotypes between two populations. The G allele of the promoter single nucleotide polymorphism (SNP) G-572C was more common in IS subjects than controls (P = 0.004, corrected for multiple testing) in the Han population. GC carriage therefore increased the risk of IS in the Han ethnic group (OR 1.45, 95% CI 1.13–1.86). However, GG carriage decreased the risk of IS in the Uyghur ethnic group (OR= 0.36, 95% CI:1.19-1.88;P<0.05). The G allele was also less common in IS subjects than controls (OR= 0.67, 95% CI:0.45-0.99;P<0.05) in the Uyghur population.
3. No significant difference was found in the association between TNF-α?238G/A and IS in both ethnic populations. However, the result showed that carriage of the TNF-α?308GA was a decreased risk of IS in both Han and Uyghur populations (OR:0.453, 0.213). GA heterozygous may be an independent protective factor for IS in the Chinese Han and Uyghur populations.
4. The distributions of both IL-4 and IL-1RN VNTR polymorphisms were not significantly associated with IS subjects after adjustment for risk factors. We, however, found that subjects with the 2R-2R haplotype had about two fold lower risk of IS than those with the 4R-2R haplotype (OR=0.504, 95%CI: 0.322-0.789, P=0.002).
5. Significant allelic association was identified between rs11833579 and IS in the Han population (OR 1.27, 95% CI 1.08–1.49). The association remained more significant after adjusting for IS covariates in the Han population in a recessive model but not in the Uyghur population. The significant difference in genotypes frequency of Rs11833579 was found between the two ethnic controls (P=0.000), which indicated that there may be genetic variations between Chinese Han and Uyghur populations that may affect the risk of IS. One risk haplotype (A-G; OR 1.52, 95% CI 1.21-1.92) was identified in the Han population. However, the associations between rs12425791 and IS were insignificant in both ethnic populations.
6. Classification regression smodel were applied to build the risk model for IS in two ethnic groups. The model had five stratums including seven explanatory variations in Han population. There were three stratums and three explanatory variations in Uyghur population model. Additionally, the indexes of the screening test were applied to assess the fitness of the model. The results showed that sensitivity and specificity were reasonable in both ethnic populations. There were interactions between gene and environment by multi-factor dimensionality reduction analysis.
Conclusions:
1. The traditional risk factors were the main risk for IS in the Han population and Uyghur population.
2. IL-6 G allele may be an independent risk factor for IS in the Chinese Han population. However, G allele may be protective factor for IS in the Uyghur population.
3. TNF-α?308GA heterozygous may be an independent protective factor for IS in the Chinese Han andUyghur populations.
4. Significant associations were not found between Single VNTR polymorphisms and IS after adjustment for risk factors. 2R-2R haplotype of IL-4 and IL-1RN is significantly associated with lower IS risk in Chinese Han population.
5. The A allele of SNP rs11833579 on chromosome 12p13 may play a role in mediating susceptibility to IS in the Han Chinese population in a recessive model. The A-G haplotype is also significantly associated with higher IS risk in the Han Chinese population.
6. There were interactions between gene and environment by multi-factor dimensionality reduction analysis; Classification tree model can reasonably predict the occurrences of IS.
Innovations:
The study was the first research based on signal transduction pathways associated with Inflammation and related functional polymorphisms in Chinese two populations. Meanwhile, the study was the first to explore the association between two key SNPs on chromosome 12p13 and ischemic stroke in Chinese two populations based on the American genome-wide association study results.
The study was the first to apply a novel tailed primers protocol to identify the association of IL-4 and IL-1RN (receptor antagonist) gene variable number of tandem repeats with ischemic stroke in Chinese Han population.
In addition, the study was the first to apply Classification tree and Multifactor dimensionality reduction model to build up the risk model for IS in Chinese two populations.
缺血性脑卒中是一种受遗传、环境共同作用的慢性疾病,基因与环境间的交互作用与缺血性脑卒中易感性密切相关。随着人类基因组密码的逐渐解译,从候选基因及全基因组水平探讨基因多态性与缺血性脑卒中易感性的发病机制成为医学界关注的热点。近年来,越来越多的研究表明炎症可能与缺血性脑卒中、冠心病发病机理密切相关。但是关于炎症因子多态性与缺血性脑卒中易感性的研究,目前,国内报道尚不多。
研究目的1.探究IL-6基因-174G/C、-572G/C多态性与缺血性脑卒中易感性。2.探讨TNF-α-238G/A、-308G/A多态性与缺血性脑卒中易感性。3.探讨IL-1RN、IL-4小卫星VNTR多态性与缺血性脑卒中易感性。4.探讨12P13两候选SNPs与缺血性脑卒中易感性。5.应用CART及MDR模型构建缺血性脑卒中发病风险预测模型。
研究方法
按照TOAST标准,开展以医院为基础的1:1配对病例-对照研究。研究对象来自于深圳三大医院、牡丹江医学院附属医院、新疆哈密市多家三甲医院,病例和对照按年龄≤5岁、性别、民族相同进行匹配,共收集汉族样本648对,维族样本100对。使用一致的个案调查表调查研究对象。用Taqman探针技术及尾巴引物延伸方案来检测基因型。拟合logistic回归模型分析基因多态性与缺血性脑卒中之间的关联性,另外,运用分类回归树构建缺血性脑卒中发病风险预测模型,构建单体型及运用MDR(多因子降维法)分析基因与基因、基因与环境之间的交互作用。
主要研究结果
1.单因素Logistic回归分析结果显示:文化水平、BMI、WHR、吸烟及高血压、负性生活事件、糖尿病、TG等是缺血性脑卒中的危险因素。多变量Logistic回归模型表明:吸烟(OR=2.158;95%CI:1.554~2.997)、腰臀比(OR=2.777;95%CI:2.084~3.699)、糖尿病(OR=1.519;95%CI:1.107~2.086)和高血压(OR=3.143;95%CI:2.445~4.042)是汉族人群缺血性脑卒中发病的独立危险因素;而饮茶史(OR=0.347;95%CI:0.269~0.448)是汉族人群缺血性脑卒中发病的独立保护因素。然而在维族人群中,我们仅发现腰臀比(OR=5.707;95%CI:2.688~12.116)和高血压(OR=13.544;95%CI:5.496~33.380)为其人群缺血性脑卒中发病的独立危险因素。
2. IL-6基因G-572C多态性基因型分布差异具有统计学意义,在未调整混杂因素前后,携带GC基因型的个体患缺血性脑卒中风险为CC的1.49倍,P=0.00。IL-6基因G-572C多态性病例组的G等位基因频率高于对照组,差异有统计学意义(P<0.01),可见随着等位基因G的增加,发生缺血性脑卒中的危险性也增高。在调整上述影响因素后,GC是缺血性脑卒中发病的独立危险因素,OR值为1.446,P=0.004。在维族人群中,以携带CC基因型的个体作为参考基因型,未发现GC基因型在病例组与对照组间存在显著性差异,而GG基因型的携带频率病例组则明显低于对照组比值比为0.36(95% CI:1.19-1.88;P<0.05),G等位基因的携带频率,病例组也明显低于对照组比值比为0.67(95% CI:0.45-0.99;P<0.05)。
3.肿瘤坏死因子启动子-238G/A多态性与两人群缺血性脑卒中发病的关联性不显著。然而,-308 G/A多态性与两人群关联性较强,在两人群中,病例组GA的分布频率均明显低于对照组,同时病例组A等位基因的分布也明显低于对照组。提示,A等位基因对于两人群缺血性脑卒中的发病风险具有保护作用,GA杂合子在调整常见的风险因素后,关联依然显著,其可能是一项中国人群缺血性脑卒中发病的独立的保护因素。
4. IL-4 VNTR和IL-1RN VNTR单个VNTR调整相关混杂因素后,发现其与缺血性脑卒中发病的关联性不显著。然而,两VNTR构建单体型后,则发现2R-2R为汉族人群缺血性脑卒中的风险单体型。
5. 12P13区Rs11833579 A等位基因为在中国汉族人群中风险等位基因,A等位基因型携带者发生缺血性脑卒中的危险性是G等位基因型者的1.27倍,隐性模式下风险性更高,而在维族中却未发现这一结果。Rs11833579多态性在不同民族人群中的频率存在显著差异,提示不同人群中存在明显的遗传异质性。Rs11833579与Rs12425791可能存在交互作用,A-G单体型在中国汉族人群中为缺血性脑卒中的风险单体型, A-G单体型携带者发生缺血性脑卒中的危险性是G-G基因型者的1.52倍。
6.采用分类回归树构建缺血性脑卒中发病风险预测模型,汉族分类树模型生长深度为5层,共纳入7个解释变量,维族分类回归树模型生长深度为3层,共纳入3个解释变量。运用筛检模型评价指标对分类树的灵敏度和特异度进行评价,评价结果表明灵敏度及特异度均较为合理。多因子降维法提示基因-基因,基因-环境间存在交互作用;分类树模型能够较好的拟合缺血性脑卒中发病风险的预测模型。
研究结论
1.传统的心脑血管疾病行为危险因素是汉族及维族人群缺血性脑卒中发生的主要危险因素,高血压、糖尿病、血脂和体重等仍是缺血性脑卒中发病的危险因素。
2.在汉族人群中IL-6-572 G等位基因型可能为缺血性脑卒中的风险基因型,而维族则可能为缺血性脑卒中的保护基因型。
3. TNF-α-308GA杂合子基因型可能是一项中国人群缺血性脑卒中发病的独立的保护因素。
4.未发现单个IL-4或IL-1RN VNTR与IS发病存在显著关联性,但两VNTR的交互作用与IS发病存在一定关联性。
5.12P13区Rs11833579 A等位基因在隐性遗传模式下会增加在汉族人群缺血性脑卒中的风险,A-G单体型在中国汉族人群中为缺血性脑卒中的风险单体型。
6.多因子降维法提示基因-基因,基因-环境间存在一定交互作用;分类回归树模型适合拟合两人群缺血性脑卒中发病风险预测模型。
创新点本研究在国内属于首次基于炎症因子相关信号转导通路及相关基因功能位点在多民族人群中分析基因多态性及环境暴露交互作用与缺血性脑卒中的关联性。同时本研究基于国外GWAS观察结果,分析相关候选基因与中国人群缺血性脑卒中的关联性。本研究还采用全新尾巴引物方案的策略,灵敏检测IL-4与IL-1RN基因的VNTR与缺血性脑卒中的关联性,在国内外尚属首次。
此外本研究在多民族人群中采用分类树结合MDR法分析构建风险预测模型。
Backgrounds
Ischemic stroke (IS) is a chronic disease influenced by environmental and genetic factors. Gene-environmental interaction are closely related with the susceptibility of IS. With the completement of Human Hapmap, it has become the focus in medical fields to study the pathogenesis of IS from the view of candidate Gene and whole-genome. In recent years, more and more studies have suggested that Inflammation play important roles in IS and coronary heart disease (CHD). However, studies on the association of the inflammatory cytokines and the interaction between the gene polymorphisms and environment exposures with IS are rare presently in the Han population.
Objectives
1. To explore the association of the G-174C, G-572C polymorphisms of IL-6 with the susceptibility of IS.
2. To explore the association of the G-238A, G-308A polymorphisms of TNF-αwith the susceptibility of IS.
3. To explore the association of the VNTR polymorphisms of IL-1RN and the VNTR with the susceptibility of IS.
4. To explore two key SNPs on chromosome 12p13 with the susceptibility of IS.
5. Classification tree model and Multifactor dimensionality reduction were applied to explore the possible interaction between gene and environment and build the risk model for IS.
Methods
Case collection was made according to the diagnostic criteria of TOAST, two 1:1 matched hospital- based case-control studies were performed. We enrolled inpatients attending the stroke units of five large general hospitals in Shenzhen, Heinongjiang and Xinjiang from September 2003 to February2009. A total of 748 subjects presenting within 24h of symptom onset were enrolled in two case–control studies. Additionally, 748 age-, gender- and ethnicity-matched normal healthy controls were randomly selected from healthy volunteers from four local community-based populations. A structured questionnaire was used to record general information, clinical history of IS and associated clinical parameters, and epidemiological data. Genotypes were examined by using Taqman Primers and a novel tailed primers protocol. Logistic regression models were used to study the association between the polymorphisms and ischemic stroke. Classification tree model was applied to build up the risk model for IS, multifactor dimensionality reduction and Haplotype analyses were used to assess the possible interaction between gene and environment.
Results
1. Univariate logistic regression showed that traditional risk factors of IS including education, income, BMI, smoking, WHR,hypertension, diabetes, negative events and TG. In two multivariate logistic models, WHR, smoking, Diabetes, and Hypertension were positively associated with IS, with OR=2.158 (95%CI: 1.554~2.997), OR=2.777 (95%CI: 2.084~3.699), OR=1.519 (95%CI: 1.107~2.086), OR=3.143 (95%CI: 2.445~4.042) respectively, while tea-drinking was inversely associated with IS, with an OR of 0.347 (95%CI: 0.269~0.448) in the Hans. However, we only find WHR and Hypertension were independent risk factors of IS with OR=2.158 (95%CI: 1.554~2.997) and OR=2.777 (95%CI: 2.084~3.699) respectively. 2. For IL-6 G-572C polymorphisms, significant difference was found in the distributions of genotypes between two populations. The G allele of the promoter single nucleotide polymorphism (SNP) G-572C was more common in IS subjects than controls (P = 0.004, corrected for multiple testing) in the Han population. GC carriage therefore increased the risk of IS in the Han ethnic group (OR 1.45, 95% CI 1.13–1.86). However, GG carriage decreased the risk of IS in the Uyghur ethnic group (OR= 0.36, 95% CI:1.19-1.88;P<0.05). The G allele was also less common in IS subjects than controls (OR= 0.67, 95% CI:0.45-0.99;P<0.05) in the Uyghur population.
3. No significant difference was found in the association between TNF-α?238G/A and IS in both ethnic populations. However, the result showed that carriage of the TNF-α?308GA was a decreased risk of IS in both Han and Uyghur populations (OR:0.453, 0.213). GA heterozygous may be an independent protective factor for IS in the Chinese Han and Uyghur populations.
4. The distributions of both IL-4 and IL-1RN VNTR polymorphisms were not significantly associated with IS subjects after adjustment for risk factors. We, however, found that subjects with the 2R-2R haplotype had about two fold lower risk of IS than those with the 4R-2R haplotype (OR=0.504, 95%CI: 0.322-0.789, P=0.002).
5. Significant allelic association was identified between rs11833579 and IS in the Han population (OR 1.27, 95% CI 1.08–1.49). The association remained more significant after adjusting for IS covariates in the Han population in a recessive model but not in the Uyghur population. The significant difference in genotypes frequency of Rs11833579 was found between the two ethnic controls (P=0.000), which indicated that there may be genetic variations between Chinese Han and Uyghur populations that may affect the risk of IS. One risk haplotype (A-G; OR 1.52, 95% CI 1.21-1.92) was identified in the Han population. However, the associations between rs12425791 and IS were insignificant in both ethnic populations.
6. Classification regression smodel were applied to build the risk model for IS in two ethnic groups. The model had five stratums including seven explanatory variations in Han population. There were three stratums and three explanatory variations in Uyghur population model. Additionally, the indexes of the screening test were applied to assess the fitness of the model. The results showed that sensitivity and specificity were reasonable in both ethnic populations. There were interactions between gene and environment by multi-factor dimensionality reduction analysis.
Conclusions:
1. The traditional risk factors were the main risk for IS in the Han population and Uyghur population.
2. IL-6 G allele may be an independent risk factor for IS in the Chinese Han population. However, G allele may be protective factor for IS in the Uyghur population.
3. TNF-α?308GA heterozygous may be an independent protective factor for IS in the Chinese Han andUyghur populations.
4. Significant associations were not found between Single VNTR polymorphisms and IS after adjustment for risk factors. 2R-2R haplotype of IL-4 and IL-1RN is significantly associated with lower IS risk in Chinese Han population.
5. The A allele of SNP rs11833579 on chromosome 12p13 may play a role in mediating susceptibility to IS in the Han Chinese population in a recessive model. The A-G haplotype is also significantly associated with higher IS risk in the Han Chinese population.
6. There were interactions between gene and environment by multi-factor dimensionality reduction analysis; Classification tree model can reasonably predict the occurrences of IS.
Innovations:
The study was the first research based on signal transduction pathways associated with Inflammation and related functional polymorphisms in Chinese two populations. Meanwhile, the study was the first to explore the association between two key SNPs on chromosome 12p13 and ischemic stroke in Chinese two populations based on the American genome-wide association study results.
The study was the first to apply a novel tailed primers protocol to identify the association of IL-4 and IL-1RN (receptor antagonist) gene variable number of tandem repeats with ischemic stroke in Chinese Han population.
In addition, the study was the first to apply Classification tree and Multifactor dimensionality reduction model to build up the risk model for IS in Chinese two populations.
引文
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