【作者】 彭春林；

【导师】 孟炜；

【作者基本信息】 复旦大学 ， 流行病与卫生统计学， 2010， 硕士

【摘要】 系统性红斑狼疮(systemic lupus erythematosus, SLE)是一慢性非传染性自身免疫疾病,遗传和环境因素在SLE的发病过程中均起重要作用。本研究采用病例对照研究、单纯病例研究及家系相关性研究设计,应用聚合酶链式反应(Polymerase Chain Reaction, PCR)-限制性片段长度多态性(Restriction Fragment Length Polymorphism, RFLP)等分子生物学技术,对中国长江以南汉族女性人群细胞毒性T淋巴细胞相关抗原4 (cytotoxic T lymphocyte-associated antigen 4, CTLA-4)、程序性细胞凋亡1 (programmed cell death-1, PDCD1)、甲基化CpG结合蛋白2(Methyl-CpG-binding protein 2, MECP2)基因的多态性,以及CTLA-4、PDCD1基因多态与环境因素的交互作用与SLE的相关性进行探索性研究。结果如下：一、系统性红斑狼疮CTLA-4、PDCD1基因多态与环境因素及其交互作用的研究(一)、系统性红斑狼疮CTLA-4、PDCD1基因多态性研究1.病例组与对照组CTLA-4基因启动子区-318位点基因型分布与等位基因频率差异均不存在统计学意义(χ2=2.248,P=0.325；χ2=0.80,P=0.370)。2.病例组与对照组CTLA-4基因启动子区-1722位点基因型分布不同,差异存在统计学意义(χ2=9.300,P=0.010),以CC基因型为参照,携带TC基因型者,其SLE患病风险升高(OR=2.004,95%CI:1.013-3.968),携带TT基因型者,其SLE患病风险也升高(OR=2.953,95%CI:1.451-6.010);病例组T等位基因频率高于对照(χ2=9.110,P=0.003),提示T等位基因可能增加SLE的易感性(OR=1.664,95%CI：1.194-2.318)。3.病例组与对照组PDCD1基因PD1.2位点基因型分布不同,差异存在统计学意义(χ2=20.596,P<0.001),以AA基因型为参照,携带AG基因型的个体,其SLE患病风险升高(OR=2.917,95%CI:1.780-4.780),携带GG基因型的个体,其SLE患病风险也升高(OR=3.111,95%CI:1.284-7.537);病例组G等位基因频率高于对照(χ2=17.000,P<0.001),提示G等位基因可能增加SLE的易感性(OR=2.121,95%CI:1.479-3.042)。4.病例组与对照组PDCD1基因PD1.5位点基因型分布不同,差异存在统计学意义(χ2=7.235,P=0.027),以CC基因型为参照,携带TC基因型者,其SLE患病风险升高(OR=1.681,95%CI:1.039-2.718)；病例组T等位基因频率高于对照(χ2=6.020,P=0.014)，提示T等位基因可能增加SLE的易感性(OR=1.661,95%CI：1.105-2.496)。5.病例组与对照组PDCD1基因PD1.6位点基因型频率分布不同,差异存在统计学意义(χ2=7.658,P=0.022),以AA基因型为参照,携带AG基因型的个体,其SLE患病风险升高(OR=1.756,95%CI:1.085-2.841);病例组G等位基因频率高于对照(χ2=7.070,P=0.008),提示G等位基因可能增加SLE的易感性(OR=1.698,95%CI:1.147-2.514).6.连锁不平衡检验显示,病例和对照人群CTLA-4基因-1722位点与-318位点等位基因之间未见连锁不平衡(D’=0.363,P＞0.05):PDCD1基因PD1.2与PD1.5位点及PD1.2与PD1.6位点等位基因两两之间呈不完全连锁不平衡(D’=0.195,P<0.05：D’=0.035,P<0.05)。7.单倍型在病例与对照组的分布分析结果提示,由PD1.2G/A.PDl.5C/T. PD1.6G/A等位基因组成的A-C-A.G-T-A及G-C-G单倍型均与SLE有关,其他单倍型未发现显著性。在相加遗传模型中,G-T-A与G-C-G单倍型均与SLE相关(β=1.6619,Z=3.4976,P=0.0005,OR=5.2693；β=1.5567,Z=2.8338,P=0.0046,OR=4.7431),提示以不具有某种单倍型为参照,携带G-T-A和G-C-G单倍型的个体,其SLE患病风险均升高；在显性模型中,G-T-A与G-C-G单倍型也均与SLE相关(β=1.5799,Z=3.9499,P=0.0001,OR=4.8545；β=1.5722,Z=3.5024,P=0.0005,OR=4.8172),提示以不具有某种单倍型为参照,携带G-T-A和G-C-G单倍型的个体,其SLE患病风险升高；在隐性遗传模型中,A-C-A单倍型与SLE呈负相关(β=-0.8062,Z=-3.0525,P=0.0023,OR=0.4466),提示以不具有A-C-A单倍型为参照,携带A-C-A单倍型的个体,其SLE患病风险明显降低。且上述三个遗传模型中以相加模型最优(AIC值最小)。(二)、系统性红斑狼疮基因多态与环境危险因素的多因素分析1.多因素非条件Logistic回归分析表明,在遗传因素方面,在相加遗传模型中,CTLA-4基因-1722位点TT基因型(以CC基因型为参照)以及PD1.6位点AG基因型(以AA基因型为参照)均与SLE易感性有关；在显性遗传模型中,仅PD1.6位点AG或GG基因型(以AA基因型为参照)与SLE易感性有关；在隐性遗传模型中,仅CTLA-4基因-1722位点TT基因型(以CC基因型为参照)与SLE易感性有关。而在环境因素方面,冻疮史、居住环境潮湿史、光敏感史、紫外线暴露史、麻疹史及有害物质接触史在上述3种遗传模型中均为SLE的危险因素。且上述3个模型中以相加模型最优(AIC最小)。2.多因素非条件Logistic回归分析表明,在遗传因素方面,在相加遗传模型中,以不具有某种单倍型为参照,PDCD1基因的G-T-A与G-C-G单倍型均与SLE易感性有关；在显性遗传模型中,以不具有某种单倍型为参照,PDCD1基因G-T-A与G-C-G单倍型也均与SLE易感性有关；在隐性遗传模型中,以不具有某种单倍型为参照,PDCD1基因A-C-A单倍型与SLE呈负相关,提示A-C-A可能为SLE的保护单倍型；A-T-G单倍型与SLE的相关性在3个模型中均无显著的统计学意义。而在环境因素方面,冻疮史、居住环境潮湿史、光敏感史、紫外线暴露史、麻疹史及有害物质接触史在上述3种遗传模型下均为SLE的危险因素。且上述3种模型种以相加模型最优(AIC值最小)。(三)、系统性红斑狼疮基因多态与环境危险因素的交互作用研究1.对数线性模型分析结果显示,细胞凋亡生物学通路上可能存在凋亡相关基因与环境危险因素的交互作用,而未发现凋亡基因间及环境危险因素间的交互作用。在由CTLA-4基因-1722位点、PDCD1基因PD1.6位点、紫外线暴露史及年龄构建的模型中,按最优模型进行参数估计,在相加遗传模型中,CTLA-4-1722位点TT基因型与紫外线暴露史存在交互作用,OR值为4.744(95%CI：1.037-21.737)；且TC基因型与紫外线暴露史也存在交互作用,OR值为4.973(95%CI：1.110-22.287)；在PD1.6位点,GG基因型与紫外线暴露史存在交互作用,OR值为3.199(95%CI：1.023-10.004),而AG基因型未发现交互作用。在显性遗传模型中,CTLA-4-1722位点的TT或TC基因型与紫外线暴露史存在交互作用,OR值为4.874(95%CI：1.119-21.242)；而在PD1.6位点基因型未发现交互作用。在隐性遗传模型中,CTLA-4-1722位点基因型未发现交互作用；PD1.6位点GG基因型与紫外线暴露史间存在交互作用,OR值为3.714(95%CI：1.235-11.179)。2.基因多态与环境危险因素间交互作用的Logistic回归分析表明,从基因型角度,仅在相加遗传模型中,发现CTLA-4基因-1722位点TT基因型与紫外线暴露史间存在显著的统计学上的交互作用(β=3.250，P=0.041),其他遗传模型中未发现具有显著性统计学意义的交互作用,其他基因多态与环境危险因素间的交互作用也未见统计学上的显著性：从单倍型角度,不同遗传模型中的基因多态与环境危险因素间的交互作用也未发现统计学上的显著性。二、系统性红斑狼疮MECP2基因的多态性研究(一)、系统性红斑狼疮以人群为基础的相关性研究1.病例组与对照组MECP2基因rs2239464位点基因型分布不同,差异存在统计学意义(χ2=6.902,P=0.009),以AG和GG基因型为参照,携带AA基因型的个体,其患病风险升高(OR=2378,95%CI:1.246-4.537);病例组A等位基因频率高于对照(z2=6.73,P=0.009),提示A等位基因可能增加SLE的易感性(OR=2.170,95%CI:1.196-3.937).2.病例组与对照组MECP2基因rs2075596位点基因型频率分布不同,差异存在统计学意义(χ2=14.432,P<0.001),以AG和GG基因型为参照,携带AA基因型的个体,其患病风险升高(OR=3.259,95%CI:1.772-5.995);病例组A等位基因频率高于对照(χ2=14.16,P<0.001),提示A等位基因可能增加SLE的易感性(OR=2.807,95%CI:1.613-4.884).3.连锁不平衡检验显示,病例和对照人群MECP2基因rs2239464与rs2075596位点等位基因之间呈不完全连锁不平衡(D’=0.19,P<0.05)。4.单倍型在病例与对照组的分布分析结果提示,由MECP2基因rs2239464A/G与rs2075596A/G等位基因组成的A-A及G-G单倍型与SLE有关,其余单倍型未见统计学上的显著性。在相加遗传模型中,A-A为SLE的危险性单倍型(β=1.0038, Z=2.7300, P=0.0063,OR=2.7286),提示以不具有A-A单倍型为参照,携带A-A单倍型的个体,其SLE患病风险升高；在显性遗传模型下,G-G为SLE的保护性单倍型(β=-0.9080, Z=-2.4191, P=0.0156, OR =0.4033),提示以不具有G-G单倍型为参照,携带G-G单倍型的个体,其SLE患病风险降低；在隐性遗传模型下,A-A为SLE的危险性单倍型(β=1.0076,Z=3.5349，P=0.0004,OR=2.739),提示以不具有A-A单倍型为参照,携带A-A单倍型的个体,其SLE患病风险升高。且上述模型中以相加遗传模型最优。(二)系统性红斑狼疮的家系相关性研究1. MECP2基因传递不平衡检验分析表明,在父母双亲至少一方为杂合子的家系中,rs2239464位点A等位基因由杂合子父母向SLE患病子女的传递未见显著增加(χ2=0.2,P>0.05)；单个位点家系关联性检验(family-based association test, FBAT)分析显示,在相加模型及隐性遗传模型中均提示rs2239464位点A等位基因与SLE易感性无关(Z=0.447, P=0.655; Z=0.447, P=0.655);2. MECP2基因传递不平衡检验分析表明,在父母双亲至少一方为杂合子的家系中，rs2075596位点A等位基因由杂合子父母向SLE患病子女的传递显著增加(z2=6,P<0.05)；单个位点FBAT分析显示,在相加模型及隐性遗传模型中均表明rs2075596位点A等位基因增加SLE发病风险(Z=2.646,P=0.008；Z=2.646,P=0.008),提示rs2075596位点A等位基因可能是SLE的保守易感等位基因。更多还原

【Abstract】 Systemic lupus erythematosus(SLE) is a chronic noninfectious autoimmune disease, both genetic factors and environmental factors play important roles in the development of this disease. In order to explore the association of the genetic variations of several genetic factors (including cytotoxic T lymphocyte-associated antigen 4, programmed cell death-1, and Methyl-CpG-binding protein 2) with SLE, as well as interactions between genetic factors (including cytotoxic T lymphocyte-associated antigen 4 and programmed cell death-1) and environmental factors for SLE in Han nationality females in Southern regions of Yangtze River in China, study designs as case-control, case-only and family-based association were adopted, with the aid of some molecular biologic techniques, such as polymerase chain reaction(PCR) and restriction fragement length polymorphism(RFLP). The results are as follows:Part I Study on the main effect and interaction effect of genetic polymorphisms of the CTLA-4 and PDCD1 and environmental factors for SLEThe study on association of genetic polymorphisms of the CTLA-4 and PDCD1 with SLE1. For locus CTLA-4 -318, both genotypic and allelic frequencies were not significantly different between SLE patients and controls (x2=2.248, P=0.325; x2=0.08, P=0.370).2. For locus CTLA-4-1722, the results showed that genotypic frequency in case group was significantly different from that in control group (x2=9.300, P=0.010) Individuals with genotype TC or TT had a higher onset risk of SLE as compared with those having genotype CC, with OR=2.004 for TC (95%CI: 1.013-3.968) and OR=2.953 for TT (95%CI:1.451-6.010). For the allelic frequencies of locus-1722, there was also significant difference between patients and controls (x2=9.110, P=0.003). There was a higher proportion of allele-1722T in SLE patients than that in controls, which may imply that the T allele of -1722 may increase the risk for SLE (OR=1.664,95%CI:1.194-2.318)3. For locus PDCD1-PD1.2, the results showed that genotypic frequency in case group was significantly different from that in control group (x2=20.596, P＜0.001). Individuals with genotype AG or GG had a higher onset risk of SLE as compared with those having genotype AA(OR=2.031 for AG,95%CI:1.445-2.856; OR=3.111 for GG, 95%CI:1.284- 7.537). For the allelic frequency of PD1.2, there was significant difference between patients and in controls (x2=17.000, P＜0.001), and there was a higher proportion of allele G in SLE patients than that in controls, which indicates that the G allele of PD1.2 may increase the risk for SLE(OR=2.121,95%CI: 1.479-3.042)4. For locus PDCD1-PD1.5, the results showed that genotypic frequency in case group was significantly different from that in control group (x2=7.235, P=0.027) Individuals with genotype TC had a higher onset risk of SLE as compared with those having genotype CC(OR=1.681,95%CI:1.039-2.718). For the allelic frequency of PD1.5, there was significant difference between patients and controls (x2=6.020, P=0.014), and there was a higher proportion of allele G in SLE patients than that in controls, which indicates that the T allele of PD1.5 may increase the risk for SLE(OR= 1.661,95%CI:1.105-2.496)5. For locus PDCD1-PD1.6, the results showed that genotypic frequency in case group was significantly different from that in control group (x2=7.658,P=0.022) Individuals with genotype AG had a higher onset risk of SLE as compared with genotype AA(OR=1.756,95%CI:1.085-2.841). For the allelic frequencies of PD16, there was also significant difference between patients and controls (x2=7.070, P=0.008), and there was a higher proportion of allele G in SLE patients than that in controls, which indicates that the G allele of PD1.6 may increase the risk for SLE(OR=1.698,95%CI:1.147-2.514)6. It was found that there was significant linkage disequilibrium between alleles of the locus PD1.2 and PD1.5, as well as between the alleles of the locus PD1.2 and PD1.6 of PDCD1 gene (D’=0.195, R0.05; D’=0.035, R0.05). However, no significant difference was found between alleles of two polymorphic sites of CTLA-4 gene (D’=0.363,P＞0.05)7. It was found that the frequencies of haplotypes in PDCD1 gene were significantly different between SLE patients and controls. The haplotypes of A-C-A, G-T-A and G-C-G that were composed of the alleles of PD1.2, PD1.5 and PD1.6 were found significantly associated with SLE, while other haplotypes were not shown any significant association with SLE. When using individuals with no certain haplotype as reference, the haplotype of G-T-A and G-C-G in PDCD1 gene had a higher onset risk of SLE under the additive model (for G-T-A,β=1.6619, Z=3.4976, P=0.0005, OR=5.2693;for G-C-G,β=1.5567, Z=2.8338, P=0.0046,OR=4.7431); and the same effect was shown under the dominant model for haplotype G-T-A and G-C-G (for G-T-A,β=1.5799, Z=3.9499, P=0.0001, OR=4.8545; for G-C-G,β=1.5722, Z=3.5024, P=0.0005,OR=4.8172); whereas the haplotype of A-C-A in PDCD1 showed a protective effect on SLE under the recessive model(β=-0.8062, Z=-3.0525, P=0.0023, OR=0.4466). Moreover, the additive model was selected as the optimal model according to the value of Akaike’s information criterion(AIC).Multiple logistic regression analysis of genes and environmental factors for SLE1. The multiple logistic regression model was fitted to by the variables of the relevant genotypes of CTLA-4, PDCD1 and environmental factors. It was shown that both genotypes of TT on -1722 site and AG on PD1.6 site were associated with SLE as compared with genotypes of CC and AA, respectively, under the additive model; and genotype of AG on PD1.6 site was associated with SLE as compared with genotype of AA under the dominant model; while genotype of TT on -1722 site was associated with SLE as compared with genotype of CC under the recessive model. However, the history of chilblain, damp of inhabited environment, photosensitivity, ultraviolet exposure, measles and hazardous substances exposure increased the onset risk of SLE under any of the above models. Moreover, the additive model was selected as the optimal model according to the value of AIC.2. The multiple logistic regression model was fitted to by the variables of the relevant haplotypes of PDCD1 and environmental factors. When using individuals with no certain haplotype as reference, it was shown that both the haplotypes of G-T-A and G-C-G in PDCD1 gene had higher onset risk of SLE under the additive model and dominant model, respectively; while the haplotype of A-C-A in PDCD1 showed a protective effect on SLE under the recessive model; and the haplotype of A-T-G was not responsible for the susceptibility of SLE in any of the above models. However, the history of chilblain, damp of inhabited environment, photosensitivity, ultraviolet exposure, measles and hazardous substances exposure increased the onset risk of SLE under any of the above models. Moreover, the additive model was selected as the optimal model according to the value of AIC.Interactions of gene polymorphisms of CTLA-4 and PDCD1 with environment risk factors for SLE1. In case-only study, we performed log-linear model analysis, the results showed that there were interactions between the genetic polymorphisms of CTLA-4 and PDCD1 and environmental factor. However, no interactions were found between genetic polymorphisms of CTLA-4 and PDCD1, and environmental factors. For the model composed of ultraviolet exposure history, locus-1722 of CTLA-4 gene and locus PD1.6 of PDCD1, according to the optimal model, it was found that interaction existed between the genotype of TT on -1722 site and ultraviolet exposure (OR=4.744,95% CI:1.037-21.737), as well as between the genotype of TC on -1722 site and ultraviolet exposure (OR=4.973,95% CI:1.110-22.287) under the additive model; and interaction was also found existed between the genotype of GG on PD1.6 site and ultraviolet exposure (OR=3.199,95% CI:1.023-10.004),while no statistical siginificance was found for interaction between the genotype of GG genotype on PD1.6 site and ultraviolet exposure under the additive model. For CTLA-4 locus, there existed interactions between the genotype of TT or TC on -1722 site and ultraviolet exposure under the dominant model (OR=4.874,95% CI:1.119-21.242); while no evidence was found that there were statistical significance for interaction between the genotypes on PD1.6 site and ultraviolet exposure under the dominant model. Moreover, interaction between the genotype of GG on PD1.6 site and ultraviolet exposure was found existed under the recessive model (OR=3.714,95% CI:1.235-11.179)2. In case-control study, we performed logistic regression analysis. The results showed that except for the interaction existed between the genotype of TT on -1722 site and UV exposure history (β=3.250, P=0.041) under the additive model, no statistical significance was found under other genetic models between the former two factors and between other genetic polymorphisms and risk environmental factors under different genetic models both from the view of genotype and haplotype.PartⅡStudy on the association of genetic polymorphisms of MECP2 with SLEPopulation-based genetic association study for SLE 1. For locus MECP2-rs2239464, the results showed that genotypic frequency in case group was significantly different from that in control group (x2=6.902, P=0.009) Individuals with genotype AA had a higher onset risk of SLE as compared with those having genotype AG and GG(OR=2.378,95%CI:1.246-4.537). For the allelic frequencies of rs2239464, there was significant difference between patients and controls (x2=6.73, P=0.009), There was a higher proportion of allele A in SLE patients than that in controls, which indicates that the A allele of rs2239464 may increase the risk for SLE(OR=2.170,95%CI:1.196-3.937)2. For locus MECP2-rs2075596, the results showed that genotypic frequency in case group was significantly different from that in control group (x2=14.432, P＜0.001). Individuals with genotype AA had a higher onset risk of SLE as compared with those having genotype AG and GG(OR=3.259,95%CI: 1.772-5.995). For the allelic frequencies of rs2075596, there was significant difference between patients and controls (x2=14.16, P＜0.001). There was a higher proportion of allele A in SLE patients than that in controls, which indicates that the A allele of rs2075596 may increase the risk for SLE (OR=2.807,95%CI:1.613-4.884)3. It was found that there was significant linkage disequilibrium between the two sites of MECP2 gene (D’=0.19,P＜0.05)4. The frequencies of haplotypes in MECP2 gene were significantly different between SLE patients and controls. The haplotypes of A-A and G-G that composed of the alleles of rs2239464A/G and rs2075596A/G were found significantly associated with SLE, while other haplotypes did not show any statistical significance. When using individuals with no certain haplotype as reference, the haplotype of A-A in MECP2 gene had a higher onset risk of SLE under the additive model (β=1.0038, Z=2.7300, P=0.0063, OR=2.7286); and the haplotype of G-G in MECP2 gene had a lower onset risk of SLE under the dominant model (β=-0.9080, Z=-2.4191,P=0.0156, OR=0.4033); while the haplotype of A-A in MECP2 gene had a higher onset risk of SLE under the recessive model (β=1.0076, Z=3.5349, P=0.0004, OR=2.739) Moreover, the additive model was selected as the optimal model according to the value of AIC.The family-based association test on SLE1. The transmission disequilibrium test showed that rs2239464 may not increase the transmission of the A allele from heterozygous parents to affected offspring (x2=0.2, P>0.05); and univariate (single-marker) family-based association tests demonstrated that alleles at SNP rs2239464 of the MECP2 gene was not associated with genetic susceptibility to SLE under either of the additive and recessive model, independently (for additive model, Z=0.447, P=0.655; for recessive model, Z=0.447, P=0.655)2. The transmission disequilibrium test showed that rs2075596 have an excess of transmission of the A allele from heterozygous parents to affected offspring (x2=6, P<0.05); and univariate (single-marker) family-based association tests demonstrated that A allele at rs2075596 site of the MECP2 gene was significantly associated with genetic susceptibility to SLE under additive and recessive mode, independently (for additive model, Z=2.646, P=0.008; for recessive model, Z=2.646, P=0.008), which indicates that A allele at rs2075596 site of the MECP2 gene may be a conservative susceptible allele.更多还原