流行病教学课件：分子流行病学

1、分子流行病学Molecular Epidemiology基本概念主要研究内容常用技术方法应用实例提纲分子流行病学（Molecular Epidemiology）分子流行病学是阐明疾病和生物群体中医学相关生物标志的分布及其与疾病/健康的关系和影响因素，并研究防治疾病、促进健康的策略与措施的科学。应用先进的技术测量生物标志的分布情况，结合流行病学现场研究方法，从分子或基因水平阐明疾病的病因及其相关的致病过程。产生背景疾病防治面临新的挑战传染性疾病病原体变异病原体耐药性新发现传染病慢性非传染病暴露与发病（死亡）关系的研究干预效果的研究人群易感性实验医学病因假设分子生物学的发展理论突破DNA双螺旋结构

2、、遗传中心法则、基因突变和基因表达调控等技术创新凝胶电泳技术、分子杂交、基因克隆以及微阵列芯片技术等吸烟肺癌传统流行病学（宏观、群体）分子流行病学（微观、群体） ？分子流行病学与传统流行病学的关系 传统流行病学暴露疾病 ？ 前瞻性研究回顾性研究分子流行病学暴露疾病分子流行病学的特点与传统流行病学不同研究的水平不同所解决的问题不同与分子生物学的区别研究对象不同（人群）研究内容和方向不同（强调与宏观暴露的关系）研究方法不同（流行病学思维和方法） 宏观与微观相结合！血清流行病学和人类基因组流行病学血清流行病学（seroepidemiology）应用血清学方法对血清中各种成分（包括抗原、抗体、生化物质

3、等）的分布情况进行研究，以阐明疾病及健康状态在人群中的分布及其影响因素，并在采取预防措施后应用血清学方法来考核其效果。人类基因组流行病学（human genome epidemiology, HuGE）是应用流行病学与基因组信息相结合的研究方法，开展以人群为基础的研究，评价基因组信息（基因或基因变异及其相应编码的产物）对人群健康和疾病的流行病学意义，是遗传流行病学与分子流行学交叉的前沿学科。基于血清中生物标志和核酸生物标志，二者可列入分子流行病学的范畴。分子流行病学是流行病学的一个分支(分子生物学？群体遗传学？)分子流行病学的研究方法是随着分子生物学的进展不断更新的吸烟肺癌传统流行病学（宏观、

4、群体）（微观、群体） ？-omics的大数据（big data）时代系统流行病学生物标志 (biological markers , biomarkers) 是指从暴露到疾病这个连续过程中可测量的，能反映功能或结构变化的细胞、亚细胞、分子水平的物质。分子生物标志物 (molecular biomarkers)直接反映外来理化因素与细胞靶分子, 特别是生物大分子如核酸和蛋白质的相互作用及其后果, 是生物标志的主要部分。生物标志 研究内容暴露测量 (E, ID, BED)效应测量 (EBE, ASF, CD, PS)易感性测量 (DNA, RNA, Protein, Small Molecular

5、, Phenotype) 暴露标志（exposure marker）（一）外暴露标志主要指环境因素暴露，包括生物性因素和非生物性因素1、生物性病原因子的鉴定2、环境化学污染物（非生物因素）暴露（烟雾浓度）（二）内暴露标志1、传染性疾病： 感染状况抗原抗体检测、病原体基因监测2、慢性非传染性疾病 进入体内的暴露剂量（可替宁浓度）（三）生物有效剂量标志（加合物）效应标志（effect marker）效应标志（effect marker, MEF）：机体暴露后产生功能性或结构性变化，并引起亚临床阶段和疾病发生过程的生物标志，称为效应标志。早期生物效应标志：疾病前期生物标志，细胞毒性反应、染色体畸变、

6、DNA、RNA和蛋白表达改变结构和功能改变 标志：疾病发生标志疾病临床标志：疾病发生后标志，AFP、CEA、PSA、AST易感性标志（susceptibility biomarker）（一）表型 DNA修复能力、端粒长度（效应、易感性都可）（二）表达谱 编码基因、非编码序列、蛋白表达（效应、易感性都可）（三）小分子代谢物 脂类、糖等的代谢产物（暴露、效应、易感性都可）（四）基因组改变 多态性、copy数变异、表观遗传改变在暴露因素作用下，宿主对疾病发生、发展易感程度的生物标志。spontaneous15%Gene-environment interaction78%pure genetic 5

7、%pure environment2%环境基因-+20%80%100%17%83%Schulte, 1994“Genetics loads gun, but Environments trigger”复杂疾病模式人类基因组遗传变异INS/DEL：插入/缺失 TRS：串联重复序列(小卫星和微卫星)CNV：拷贝数变异INVERSION: 颠换SNP：单核苷酸多态性 生物学意义: 不同个体的基因99.9%是一样的，但在序列上有极小(0.1%)的遗传差异，其中主要是单核苷酸多态性(SNP)。这0.1%的差异授予你我他特有的表型；与个体对疾病的易感性、对药物的反应性差别有密切关系。 普遍性: SNP是指

8、在人群中出现的频率1%的先天突变。SNP存在于整个人类基因组中，每100bp以内就存在一个SNP，估计总数在数百万个。 对于人群研究而言的技术可及性和稳定性: Platform and databaseWhy SNPs ?基因组遗传变异与个体疾病易感性差异基因型检测-危险度评价、个体化治疗分子流行病学常用技术及方法核酸技术（DNA & RNA）核酸体外扩增 （PCR）核酸电泳图谱 核酸酶切电泳图谱 （RFLP）扩增片断长度多态性（AFLP）核酸分子杂交 有原位杂交、斑点杂交、转印杂交（包括Southern blot检测DNA和Northern blot检测RNA）等。核酸序列分析蛋白质技术 蛋

9、白质分离鉴定技术主要有：电泳、凝胶电泳、蛋白质转印杂交（Western blot）、色谱分析、蛋白质测序等。酶学技术 包括定性和定量检测，要求一定的条件。多位点酶电泳（multilocus enzyme electrophoresis, MEE）法。免疫学技术： 酶联免疫吸附试验（ELISA）、荧光免疫试验（FIA）、放射免疫试验（RIA）、免疫细胞化学检测（ICC）等；色谱（质谱）技术： 高效液相色谱技术HPLC）、液相蛋白色谱技术（FPLC）等。个体化治疗的途径个体化治疗患者避免-不必要的治疗- 无效治疗- 有害治疗社会-资源有效利用- 减轻经济负担预后相关- 治疗是否合适预测相关- 治疗

10、敏感性- 治疗毒副反应肿瘤特征-组织病理学类型- 遗传学改变- 基因表达- 蛋白表达病人特征-生殖系遗传学改变(SNP)等Automated Liquid HandlerSpectroPREPTMNanoliter DispenserSpectroJETTMMALDI-TOF Mass SpectrometerSpectroREADERTMAutomated AnalysisSpectroTYPERTMMiniaturized BiochipSpectroCHIPTMMassARRAYIntegrated Components基因组研究的平台中低通量检测平台PCR-RFLP、PCR-SSCP,

11、 PCR-based resequencing、TaqMantime-of-flight (MALDI) mass spectrometry、OpenArray基因组芯片SNP Chip（10K、20K、50K、100K、550K、1M、5M） 二代测序（NGS）Roche 454、Illumina Solexa、ABI SOLiD7900 Real-Time PCR TaqMan OpenArrayTaqMan OpenArray Genotyping PlatesHi-Seq iScanSQ 全基因组关联研究(GWAS)通量高、样本量大、多阶段验证、质控统计严格关联结果真实可靠、重复性高！

12、Feero WG et al. New Eng J Med. 2010.I期II期III期SNPs数量筛选外部验证内部验证二代测序（NGS）DNA（全基因组、外显子组）Missing heritabilityUncovered variantsRare variationInDelCopy number variationMutationGermlineSomaticRNA（转录组RNA-Seq，sRNA）Epigenetic（Methyl-Seq，ChIP-Seq）特点：发现新的突变或其他结构变异通量高、数据量大、质控严格研究内容更多更广基因组测序价格显著下降Metagenomic Sequ

13、encingQin J et al. Nature. 2010 Karlsson FH et al. Nature. 2013 Faith JJ et al. Nature. 2013 Integrated GenomicsWhole Genome, Exome, Transcriptome, Small RNA, Methylation Nature 2013Nature 2013Nat Genet 2013分子流行病学在疾病预防和控制中的应用（一）病因的探讨及病因致病机制的研究 1、传染病病因及流行规律的探讨：研究已知或新发传染病的病原体和流行特点 2、疫苗评价、非应答者病原学诊断（基因诊

14、断）、基因分型研究分布特点，传染源追踪和传播途径确定观察病原体在体内持续时间和消长规律案例：1990年7月，美国佛罗里达州一名AIDS妇女，怀疑在当地一牙科诊所手术时感染了HIV，因为该诊所的牙科医生也是一名AIDS患者。随后当地卫生部门对该牙医诊治过的一千余名患者进行HIV检测，共发现7名HIV感染者有在该诊所的就诊史。传染病传播途径分析Science,1992那么这7名HIV感染者是否与该牙医有关呢？针对这一问题可采取的分析方法：1、传统流行病学分析方法：接触者调查，分析感染者可能的危险行为如输血、静脉吸毒、不洁性交史等。2、分子流行病学方法：比较HIV病毒基因序列的差异，分析不同病例感染

15、株遗传关系的远近。Science,1992与牙医感染株的遗传变异性比较与对照感染株的遗传变异性比较病人D当地对照牙医及病人A,B,C,E,G病人F进化树分析2.非传染病的病因及病因致病机制的研究 例：血脂与心血管疾病 吸烟导致肺癌的作用机制 基因表达与疾病的发生与转归、个体化治疗 Mitchell PS et al, PNAS. 2008 Chen X et al, Cell Res. 2008 研究背景： 2008年，中美科学家同步发现血浆中稳定存在miRNAEsquela KA et al, Nat Rev Cancer. 2006Ryan BM et al, Nat Rev Cancer

16、. 2010Maria AC et al, Nat Rev Clin Oncol. 2011Kasinski AL et al, Nat Rev Cancer. 2011 Lujambio A et al, Nature. 2012 血浆miRNA的特点:稳定、非侵入性、可用于早期诊断和疾病监测2万人4年随访早期诊断7名在基线调查抽血时正常但后期发生肺癌的个体比临床平均提前了 14.8 个月队列研究血浆miRNA表达谱作为肺癌早期诊断生物标志物400肺癌病例/220对照10个血浆miRNAs灵敏度：0.93 特异度：0.90例：恶性肿瘤的形成过程及其影响因素前致癌物终致癌物DNA损伤基因突变癌

17、前病变恶性肿瘤活化解毒凋亡增生修复损伤遗传易感性因素（二）疾病易感性的测定 （传染病和非传染病）The Angelina effectMother died from BRCa at age 56, with a BRCA1 mutationShe carries the same BRCA1 mutation87% risk for BRCa and a 50% risk for ovarian cancerAt age 37 (2013), opted for mastectomyRaise public awareness for genomic testing and preventi

18、onIn march 2015, she had her ovaries and fallopian tubes removedHypothesis Driven Approach！（Candidate genes）Functional SNPs:5 flanking5UTRCoding3UTRTagging SNPs:Candidate genesCommon variantsLD valuesMetabolismCell cycleDNA repairApoptosisInflammationImmunity.Target pathwaySmoking Related DNA Damage

19、s and Repair PathwaysLinkage Disequilibrium (LD) based-mappingSequence-based selection approach based on SNP location and potentially functional relevanceGeneral Strategy for Selecting SNPsCategory of SNPsCoding SNPs (cSNPs): non-synonymous SNPs (nsSNPs) vs. synonymous SNPs (sSNPs)Non-coding SNPs (n

20、cSNPs): regulatory SNPs (rSNPs) vs. Other intronic SNPs (iSNPs)rSNPs: located at 3UTR/5UTR, promoter region or exon-intron boundaryNature, 2004Nature, 2004GWAS研究策略Stage IGenome-wide phase利用芯片对所有tagSNPs进行初筛，找出差异位点Stage IIValidation phase I以10-7为水准，在独立大样本人群中进行验证Stage IIIValidation phase II对仍有意义的差异位点，进

21、一步在外部人群验证Seven Years，More than 1600 published GWAS have reported about 2000 robust associations for 300 traitsNHGRI GWA CatalogBy 2013/6Reported GWAS of Lung CancerChromosome-log10 P value15q255p156p21Wang et al, Nat Genet, 2008Three loci indentified in lung cancer GWAS of European ancestryThorgeir

22、et al, Nature, 2008Hung et al, Nature, 2008Amos et al, Nat Genet, 2008McKay et al, Nat Genet, 2008Wang et al, Nat Genet, 2008Heterogeneity among ethnicitiesThe risk alleles of SNPs at 6p21 or 15q25 observed in European (CEU) were rare or not observed in Chinese (CHB), Japanese (JPT) or African (YRI)

23、 data in the HapMap database.LociSNPsBase changeCEUCHBJPTYRI6p21rs3131379 C T0.1020.0000.0000.0426p21rs3117582A C0.0800.0000.0000.04915q25rs8034191T C0.4330.0440.0110.14215q25rs16969968G A0.4250.0330.0110.00015q25rs1051730T C0.4000.0330.0110.110Only 5p15 locus is replicated in ChineseWu C et al. Can

24、cer Res. 2009Jin G et al. Carcinogenesis. 2009LociSNPsAllelesMAF*OR(95%CI) P 5p15rs2736100A C0.450/0.4181.16(1.03-1.30)0.0205p15rs402710C T0.293/0.3110.92(0.81-1.04)0.1616p21rs9295740G A0.188/0.1801.04(0.90-1.21)0.47315q25rs8034191T C0.028/0.0370.72 (0.501.02)0.06515q25rs16969968G A0.028/0.0350.84 (

25、0.591.21)0.34715q25rs1051730T C0.027/0.0330.86 (0.601.24)0.412*Minor allele frequency (case/control); Association results in Chinese population (1,221 cases and 1,344 controls )Similar results were reported in JapaneseMiki D et al. Nat Genet. 2010LociSNPsAllelesMAF*OR(95%CI) P 5p15rs2736100A C0.462/

26、0.3991.29(1.16-1.44)5.2E-066p21rs9295740G A0.163/0.1720.94(0.81-1.09)0.39715q25rs8034191T C0.028/0.0241.18 (0.84-1.65)0.33915q25rs1051730T C0.027/0.0231.20 (0.85-1.69)0.289*Minor allele frequency (case/control); Association results in Japanese population (1,004 cases and 1,900 controls )通过2331例肺癌病例和

27、3077例对照的初筛和后续多阶段验证，发现9个与肺癌相关联的风险区域，可以显著提高肺癌危险度预测效能，其中四个通过与吸烟的交互作用参与肺癌发生Hu Z et al. Nat Genet.2011Dong J et al. Nat Genet.2012鳞癌特异的位点多肿瘤共有危险区域肺癌胃癌食管癌12q23.1 区域遗传变异是肺鳞癌特异的遗传易感区域从遗传的角度区分肺鳞癌和腺癌Jin G, et al, Am J Hum Genet 2012 Dong J, et al, Plos Genet 2012 Significance of GWAS Findings (I)Partially elu

28、cidate susceptibility of Complex disease attributed to low penetrance variants. Risk factors : Lung cancer as a exampleCandidate gene approach: several loci such as CAPS8 D302N for breast cancer. GWAS approach: 200 loci and morePowerful approach!Significance of GWAS Findings (II)Provide new insights

29、 into the biology of complex disease. Science. 2012;337:1190-5About 90% GWAS identified variants are intronic (41.2%) or intergenic (52.5%).Hundreds of GWAS variants are related with long-distance regulation for distant gene targetsPrevious unknown pathogenic pathways: autophagy in Crohns disease, I

30、L-23 pathway (GWA studies: rewriting the story of IBD. Trends Genet. 2009). Clinical usage: GWAS findings have been or probably will be valuable in disease prediction (type 1 diabetes, AUC about 0.9), biomarker identification and disease subclassification (HNF1A-MODY) Significance of GWAS Findings (

31、IIIa)The analyses included 28 subjects with HNF1A-MODY, 294 with autoimmune diabetes, 187 with type 2 diabetes, and 24 with GCK-MODY and 198 nondiabetic control subjects.DIABETES CARE 2010Significance of GWAS Findings (IIIb)Clinical usage: GWAS findings have been or probably will be valuable in dise

32、ase prediction (type 1 diabetes, AUC about 0.9), biomarker identification and disease subclassification (HNF1A-MODY) , treatment selection (ITPA gene deficient)ribavirin induced haemolytic anaemia:利巴韦林引起溶血性贫血ITPA deficiency protects against clinically significant decline inHb concentration induced b

33、y HCV anti-viral treatment.Nature 464, 405408 (2010)Risk of myopathy in chronic simvastatin use :他汀类药物导致的肌病 N. Engl. J. Med. 359, 789799 (2008)Clinical usage: GWAS findings have been or probably will be valuable in disease prediction (type 1 diabetes, AUC about 0.9), biomarker identification and dis

34、ease subclassification (HNF1A-MODY) , treatment selection (ITPA gene deficient), and drug dosing (Statin-Induced Myopathy). Significance of GWAS Findings (IIIc)rs4149056, 影响代谢 FindingsChallengesStrategiesMore loci / rare variantClarify the biological mechanism of GWAS variants in cancer development

35、and determine the causal variants/ genesTranslate these genetic loci from bench to bedside Discovering Missing HeritabilityInternational collaboration: Pooling GWAS data via consortium and sharing pipelines and samplesCopy number variations (CNVs): calling based on GWAS chips, but hard to clean the

36、dataEpistasis and gene-environment interaction: a new wave of GWAS based on carefully designed large representative nested case-control study / stable internal exposure instead of external exposureWhole genome sequencing based GWAS and rare variants: a ideal but cost-dependent approachDetermining Ca

37、usal Variants/GenesGenetic refinement Target sequencing Fine-mapping studyGWASFunction assessment In vitro In vivoExpression analysis eQTLs Proteinomics ENCODE functional annotationMarker SNPsCausalSNPsGWAS109 SNPs (P 10-5)Knock-down/Knock-out果蝇、斑马鱼等模式动物同源基因表型分析相应组织表达谱分析或eQTL分析SNPseQTL-mappingKO mod

38、elGenesSpermatogonium blockspermiogenesisanomalyWTspermiogenesisanomalyPost-GWAS易感基因表型研究流程McCarthy et al, Nat Rev Genet. 2008Identification of susceptibility lociNovel biological insightsImproved measures of individual aetiological processTherapeutictargetsBiomarkersPreventionDiagnosticsPrognosticsT

39、herapeutic optimizationTranslating From Bench to Bedside Calories from Soft Drinks Do They Matter?A Trial of Sugar-free or Sugar-SweetenedBeverages and Body Weight in ChildrenN Engl J Med. 2012 Oct 11;367:1397-406A Randomized Trial of Sugar-Sweetened Beverages and Adolescent Body WeightN Engl J Med.

40、 2012 Oct 11;367:1407-16Nurses Health Study (NHS, 6934 women)Health Professionals Follow-up Study (HPFS, 4423 men)Beverage Intake Genetic-predisposition score from 32 BMI-associated loci Womens Genome Health Study (WGHS, 21740 women)Replication stage:Initial stage:BMIObesityN Engl J Med. 2012 Oct 11

41、; 367(15):1387-96.Sugar-Sweetened Beverages and Genetic Risk of ObestiyDifference in BMI Associated with One Serving of a Sugar-Sweetened Beverage per DayN Engl J Med. 2012 Oct 11;367(15):1387-96.Translating From Bench to Bedside For complex disease, Art and Skill in the whole process！- 没有“解决”方案！(3

42、vs. 17 years)Do you really understand the power and utility of “family history”, maybe the only useful information from patients answerHowever, in a prediction model, family history usually add little AUC useless ? The balance of noise and useful information for complex diseaseClinical utility: targ

43、eted PSA screenSun et al, 2013Genetic score and family historyLimitations of family historyIndirect measurement based on relatives, not purely geneticDifficult to be measured accurately, affected by many factorsDefinitions (first-degree or second-degree)Family sizeCommunication among relativesLess i

44、nformative, either yes or no (vast majority)Some flaws of family historyBrothers have the same family history risk although they only share 50% of the same genes on averageFamily history is uninformative in populations with historically low incidenceGenetic score has a better precisionSun et al, 2013Genetic score could be different for brothers二代测序揭示肿瘤突变谱The landscape of mutational signaturesAlexandrov et al, Nature 20137,042 cancers; 4,938,362 mutations; 20 mutational