Profiling of Childhood Adversity-Associated DNA Methylation Changes
GDM_孕妇血清甲状腺激素、25-羟维生素D水平与新生儿低血糖关系
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儿童期心理虐待对特质抑郁的影响:反刍思维和创伤后认知改变的链式中介作用
ቤተ መጻሕፍቲ ባይዱ
体形成易于对不良刺激做出抑郁反应的稳定的行为 倾向，即特质抑郁。以往研究个体抑郁状况通常使 用的是考察个体最近一周或此时此刻的抑郁程度的 量表，如流调中心用抑郁自评量表（CES-D），Zung 氏抑郁自评量表（SDS）或贝克抑郁自评量表（BDI）， 但情绪易受环境变化而变化，这种前提测得的结果 能否反应个体稳定的抑郁倾向还有待商榷[10]。1995 年 Spielberger[11]发表了第一版状态特质抑郁问卷，他 将抑郁分为状态和特质两个水平，分别体现了抑郁 的强度（状态）和频率（特质）。状态抑郁是个体对环 境中不良刺激产生的短暂的情绪状态，特质抑郁是 个体对不良刺激做出抑郁反应的相对稳定的行为倾 向。本研究采用状态特质抑郁问卷（STDEP）考察心 理虐待对特质抑郁的影响。
综上所述，本研究提出如下中介假设模型：心理 虐待通过反刍思维和创伤后认知改变两个中介变量 影响特质抑郁。
1 对象与方法
1.1 对象 采用方便取样，选取哈尔滨师范大学大一到大
四及研究生共 720 人，在自习课上集体施测，获得有 效问卷 603 份，有效率为 83.8%。其中，大一 134 人， 大二 137 人，大三 144 人，大四 76 人，研究生 112 人。 1.2 工具 1.2.1 儿童期心理虐待量表[23] 该量表共 23 道题
将数据录入 SPSS20.0，对人口学变量进行描述 性统计，使用 Pearson 相关分析考察心理虐待、反刍 思维、创伤后认知改变、特质抑郁间的相关性，使用 Mplus7.0，建 立 结 构 方 程 模 型 ，采 用 最 大 似 然 法 （maximum likelihood）检验反刍思维、创伤后认知改 变在心理虐待和特质抑郁间中介作用的显著性。
盐胁迫下盐穗木DNA甲基化程度与去甲基化酶基因(Ros1)表达的相关性研究
盐胁迫下盐穗木DNA甲基化程度与去甲基化酶基因(Ros1)表达的相关性研究杜驰;张冀;张丽丽;张富春【摘要】[Objective] The DNA methylation, which is regulated by methylation and demethylation coordinately, directly affects the expression of stress-related genes.DNA demethylation in plants is mainly mediated by demethylase gene Ros1 (Repressor of silencing 1) to finish the base excision repair.Analysis of the dynamic changes of the DNA methylation of Halostachys caspica and gene expression changes of Ros1 will be helpful to elucidate the molecular mechanism of DNA methylation in response to salt stress.[Method]qRT-PCR was used to measure the degree of genomic DNA methylation in assimilation shoots and roots of H.caspica,the correlation between DNA methylation and HcRos1 gene expression was also analyzed.[Result]The results showed that the degree of genomic DNA methylation in assimilation shoots and roots of H.caspica increased firstly and then decreased under the same concentration of NaCl stress treated with different times, and DNA methylation in assimilating shoots was higher than in roots and reached the highest at 24h.However,the degree of genomic DNA methylation in assimilation shoots and roots of H.caspica also increased firstly and then decreased under the different concentrations of NaCl stress treated with the same time, DNA methylation in assimilating shoots was higher than in roots and reached the highest under concentration of 100 mmol/L NaCl.The gene expressionof HcRos1 did not changed under low concentration of NaCl stress, but increased significantly under concentration of 700 mmol/L at 72h.[Conclusion]Correlation analysis demonstrated that the expression of HcRos1 was negatively correlated with the degree of DNA methylation.Salt stress can increase the expression of HcRos1, reduce the methylation degree of genomic DNA and enhance the salt tolerance of plants.%[目的]甲基化和去甲基化协同调控的DNA甲基化直接影响逆境胁迫相关基因的表达,植物的DNA去甲基化主要由去甲基化酶基因Ros1(Repressor of Silencing 1)介导的碱基切除修复实现.开展盐穗木(Halostachys caspica)DNA甲基化程度与HcRos1表达动态变化的分析,有助于阐明DNA甲基化应答盐胁迫的分子机制.[方法]利用qRT-PCR测定盐胁迫下盐穗木幼苗同化枝和根基因组DNA的甲基化程度,探讨DNA的甲基化程度与去甲基化酶基因HcRos1表达的相关性.[结果]在相同NaCl 浓度胁迫不同时间下盐穗木同化枝和根中DNA甲基化程度呈现先升高后降低的趋势,盐穗木同化枝中的DNA甲基化程度大多高于根中的基因组甲基化程度,且均在24 h达到最高DNA甲基化程度.而在不同浓度NaCl胁迫处理24 h时,盐穗木同化枝和根中DNA甲基化程度也是先升高后降低的趋势,盐穗木同化枝中的基因组甲基化程度高于根中的基因组甲基化程度,且多在100 mmol/L达到最高DNA甲基化程度.HcRos1的基因表达量在低浓度NaCl胁迫下变化不大,但在700 mmol/L NaCl胁迫72 h时则显著升高.[结论]HcRos1表达量与DNA甲基化水平呈明显的负相关, 盐胁迫能够提高HcRos1的表达,降低基因组DNA的甲基化程度,增强植物的耐盐性.【期刊名称】《新疆农业科学》【年(卷),期】2017(054)005【总页数】8页(P878-885)【关键词】盐生植物;基因组;NaCI处理;甲基化和去甲基化;相关性【作者】杜驰;张冀;张丽丽;张富春【作者单位】新疆生物资源基因工程重点实验室/新疆大学生命科学与技术学院,乌鲁木齐830046;新疆生物资源基因工程重点实验室/新疆大学生命科学与技术学院,乌鲁木齐830046;新疆生物资源基因工程重点实验室/新疆大学生命科学与技术学院,乌鲁木齐830046;新疆生物资源基因工程重点实验室/新疆大学生命科学与技术学院,乌鲁木齐830046【正文语种】中文【中图分类】Q756;S188【研究意义】植物生长发育过程中直接会受到干旱、低温、盐碱及辐射等外界环境因素的影响，这些逆境胁迫不利于植物的生长［1，2］。
儿童孤独症患者γ-氨基丁酸(GABA)A类受体基因簇的罕见变异
ＣｈｉｎｅｓｅＭｅｎｔａｌＨｅａｌｔｈＪｏｕｒｎａｌ，Ｖｏｌ３２，Ｎｏ１１，２０１８
儿童孤独症患者 γ氨基丁酸 （ＧＡＢＡ） Ａ类受体基因簇的罕见变异
王琳彦 汪子琪 卢天兰 张天 贾美香 张岱 王力芳
（北京大学第六医院，北京大学精神卫生研究所，卫生部精神卫生学重点实验室 （北京大学），国家精神心理疾病临床医 学研究中心 （北京大学第六医院），北京 １００１９１ 通信作者：王力芳 ｌｉｆａｎｇｗａｎｇ＠ｂｊｍｕｅｄｕｃｎ）
【摘 要】目的：探讨儿童孤独症患者染色体 １５ｑ１２区域 γ氨基丁酸 Ａ类受体基因簇是否存在可能致 病的罕见变异。方法：对 ９６例符合 ＤＳＭＩＶ孤独症诊断标准的中国汉族儿童孤独症患者 γ氨基丁酸 Ａ类 受体基因簇进行靶向测序，采用 Ｓａｎｇｅｒ测序法进行验证。进一步扩大样本筛查罕见变异，通过连续性校正 χ２检验比较罕见变异的分布频率在 ３８４例儿童孤独症病例组和 ３８４例正常对照组的差异。结果：９６例儿童 孤独症 患 者 靶 向 测 序 发 现 ８个 罕 见 变 异， 包 括 ＧＡＢＲＧ３基 因 的 ２个 罕 见 错 义 突 变 ［ｒｓ２０１６０２６５５ （ｐＶａｌ２３３Ｍｅｔ） 和 ｒｓ２０１４２７４６８（ｐＰｒｏ３６５Ｓｅｒ）］ 和 ＧＡＢＲＢ３基因非编码区的 ６个罕见突变。Ｓａｎｇｅｒ测序验 证后进一步扩大样本，ｒｓ２０１６０２６５５杂合型变异在孤独症组出现的频率高于正常对照组 （２１％ ｖｓ０３％， Ｐ＜００５）。功能预测 提 示 ｒｓ２０１６０２６５５罕 见 变 异 为 有 害 突 变，可 能 导 致 ＧＡＢＲＧ３蛋 白 质 的 异 常。结 论： ＧＡＢＲＧ３基因在儿童孤独症存在影响氨基酸改变的罕见变异，是孤独症的易感基因可能参与孤独症的致病。
陶芳标 发育关键期可塑性与生命历程累积效应
2013’预防医学多学科年会暨“环境与人口健康”论坛成年疾病环境病因新知——发育关键期可塑性 与生命历程累积效应Advances in Environmental Determinants for Adulthood Diseases: Critical Period Plasticity & Cumulative Effects over Life Course陶芳标 fbtao@ 成年期疾病 “井喷”与低龄化趋势 ——需要审视慢性病的危险因素和病因学说 环境对胎婴儿发育可塑性影响与终身健康 ——关键期/窗口期与可逆性 生命历程危害因素效应累积 ——为成年期疾病雪上加霜 挑战——（出生）队列、暴露组学与转化研究四种疾病： 心血管疾病 糖尿病 癌症 慢性呼吸道疾病中国：糖尿病 中国：糖尿病上海交通大学医学院附属瑞金医院、上海市内分泌 代谢病研究所与中国疾病预防控制中心组成的研究团 队，基于中国慢性非传染性疾病监测系统，在2010年 选取具代表性的近1万名18岁及以上成人进行调查，并 对参与者进行了血糖等测试。
在依据调查结果进行推算后，研究者认为，中国成 人糖尿病患病率已上升至11.6％，其中男性糖尿病患病 率为12.1％，女性患病率为11％。
城市居民与农村居民 患病率均在上升，分别为14.3％与10.3％。
此外，中国 约70％的糖尿病患者不知道自己已患此病。
以糖化血红蛋白（HbA1c）小于7.0％作为血糖获得 控制的标准，中国接受治疗的成人糖尿病患者中，血 糖控制率不到40％。
中国：糖尿病 中国：糖尿病中国：糖尿病 中国：糖尿病中国：代谢综合征 中国：代谢综合征中国代谢综合征检出率减少四种危险因素： 吸烟 缺乏体育锻炼 不健康的饮食行为 酗酒2013, Dec. 2心血管疾病慢性呼吸道疾病糖尿病癌症50年来（1961-2009）世界食物营养级/食物层次变化 Bonhimmeau S:如果我们所有人都增加自己的营养级/食性层次，那么我们将对生态系统产生更大的影响。
2012-Nature-breast tumours
ARTICLEdoi:10.1038/nature11412 Comprehensive molecular portraits of human breast tumoursThe Cancer Genome Atlas Network*We analysed primary breast cancers by genomic DNA copy number arrays,DNA methylation,exome sequencing, messenger RNA arrays,microRNA sequencing and reverse-phase protein arrays.Our ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms,each of which shows significant molecular heterogeneity.Somatic mutations in only three genes(TP53,PIK3CA and GATA3)occurred at.10%incidence across all breast cancers;however,there were numerous subtype-associated and novel gene mutations including the enrichment of specific mutations in GATA3,PIK3CA and MAP3K1with the luminal A subtype.We identified two novel protein-expression-defined subgroups,possibly produced by stromal/microenvironmental elements,and integrated analyses identified specific signalling pathways dominant in each molecular subtype including a HER2/phosphorylated HER2/EGFR/phosphorylated EGFR signature within the HER2-enriched expression parison of basal-like breast tumours with high-grade serous ovarian tumours showed many molecular commonalities,indicating a related aetiology and similar therapeutic opportunities.The biological finding of the four main breast cancer subtypes caused by different subsets of genetic and epigenetic abnormalities raises the hypothesis that much of the clinically observable plasticity and heterogeneity occurs within,and not across,these major biological subtypes of breast cancer.Breast cancer is one of the most common cancers with greater than 1,300,000cases and450,000deaths each year worldwide.Clinically, this heterogeneous disease is categorized into three basic therapeutic groups.The oestrogen receptor(ER)positive group is the most numerous and diverse,with several genomic tests to assist in predict-ing outcomes for ER1patients receiving endocrine therapy1,2.The HER2(also called ERBB2)amplified group3is a great clinical success because of effective therapeutic targeting of HER2,which has led to intense efforts to characterize other DNA copy number aberrations4,5. Triple-negative breast cancers(TNBCs,lacking expression of ER, progesterone receptor(PR)and HER2),also known as basal-like breast cancers6,are a group with only chemotherapy options,and have an increased incidence in patients with germline BRCA1muta-tions7,8or of African ancestry9.Most molecular studies of breast cancer have focused on just one or two high information content platforms,most frequently mRNA expression profiling or DNA copy number analysis,and more recently massively parallel sequencing10–12.Supervised clustering of mRNA expression data has reproducibly established that breast cancers encompass several distinct disease entities,often referred to as the intrinsic subtypes of breast cancer13,14.The recent development of additional high information content assays focused on abnormalities in DNA methylation,microRNA(miRNA)expression and protein expression,provide further opportunities to characterize more com-pletely the molecular architecture of breast cancer.In this study,a diverse set of breast tumours were assayed using six different technology platforms.Individual platform and integrated pathway analyses iden-tified many subtype-specific mutations and copy number changes that identify therapeutically tractable genomic aberrations and other events driving tumour biology.Samples and clinical dataTumour and germline DNA samples were obtained from825 patients.Different subsets of patients were assayed on each platform:466tumours from463patients had data available on five platforms including Agilent mRNA expression microarrays(n5547),Illumina Infinium DNA methylation chips(n5802),Affymetrix6.0single nucleotide polymorphism(SNP)arrays(n5773),miRNA sequencing (n5697),and whole-exome sequencing(n5507);in addition,348of the466samples also had reverse-phase protein array(RPPA)data (n5403).Owing to the short median overall follow up(17months) and the small number of overall survival events(93out of818),survival analyses will be presented in a later publication.Demographic and clinical characteristics are presented in Supplementary Table1. Significantly mutated genes in breast cancerOverall,510tumours from507patients were subjected to whole-exome sequencing,identifying30,626somatic mutations comprised of28,319point mutations,4dinucleotide mutations,and2,302 insertions/deletions(indels)(ranging from1to53nucleotides).The point mutations included6,486silent,19,045missense,1,437 nonsense,26read-through,506splice-site mutations,and819muta-tions in RNA parison to COSMIC and OMIM databases identified619mutations across177previously reported cancer genes. Of19,045missense mutations,9,484were predicted to have a high probability of being deleterious by Condel15.The MuSiC package16, which determines the significance of the observed mutation rate of each gene based on the background mutation rate,identified35sig-nificantly mutated genes(excluding LOC or Ensembl gene IDs)by at least two tests(convolution and likelihood ratio tests)with false dis-covery rate(FDR),5%(Supplementary Table2).In addition to identifying nearly all genes previously implicated in breast cancer(PIK3CA,PTEN,AKT1,TP53,GATA3,CDH1,RB1, MLL3,MAP3K1and CDKN1B),a number of novel significantly mutated genes were identified including TBX3,RUNX1,CBFB,AFF2, PIK3R1,PTPN22,PTPRD,NF1,SF3B1and CCND3.TBX3,which is mutated in ulnar-mammary syndrome and involved in mammary gland development17,harboured13mutations(8frame-shift indels,*A list of participants and their affiliations appears at the end of the paper.4O C T O B E R2012|V O L490|N A T U R E|61Macmillan Publishers Limited. All rights reserved©20121in-frame deletion,1nonsense,and3missense),suggesting a loss of function.Additionally,2mutations were found in TBX4and1muta-tion in TBX5,which are genes involved in Holt–Oram syndrome18. Two other transcription factors,CTCF and FOXA1,were at or near significance harbouring13and8mutations,respectively.RUNX1and CBFB,both rearranged in acute myeloid leukaemia and interfering with haematopoietic differentiation,harboured19and9mutations, respectively.PIK3R1contained14mutations,most of which clustered in the PIK3CA interaction domain similar to previously identified mutations in glioma19and endometrial cancer20.We also observed a statistically significant exclusion pattern among PIK3R1,PIK3CA, PTEN and AKT1mutations(P50.025).Mutation of splicing factor SF3B1,previously described in myelodysplastic syndromes21and chronic lymphocytic leukaemia22,was significant with15non-silent mutations,of which4were a recurrent K700E substitution.Two protein tyrosine phosphatases(PTPN22and PTPRD)were also signifi-cantly mutated;frequent deletion/mutation of PTPRD is observed in lung adenocarcinoma23.Mutations and mRNA-expression subtype associations We analysed the somatic mutation spectrum within the context of the four mRNA-expression subtypes,excluding the normal-like group owing to small numbers(n58)(Fig.1).Several significantly mutated genes showed mRNA-subtype-specific(Supplementary Figs1–3)and clinical-subtype-specific patterns of mutation(Supplementary Table2). Significantly mutated genes were considerably more diverse and recurrent within luminal A and luminal B tumours than within basal-like and HER2-enriched(HER2E)subtypes;however,the overall mutation rate was lowest in luminal A subtype and highest in the basal-like and HER2E subtypes.The luminal A subtype harboured the most significantly mutated genes,with the most frequent being PIK3CA (45%),followed by MAP3K1,GATA3,TP53,CDH1and MAP2K4. Twelve per cent of luminal A tumours contained likely inactivating mutations in MAP3K1and MAP2K4,which represent two contiguous steps in the p38–JNK1stress kinase pathway24.Luminal B cancers exhibited a diversity of significantly mutated genes,with TP53and PIK3CA(29%each)being the most frequent.The luminal tumour subtypes markedly contrasted with basal-like cancers where TP53 mutations occurred in80%of cases and the majority of the luminal significantly mutated gene repertoire,except PIK3CA(9%),were absent or near absent.The HER2E subtype,which has frequent HER2amplification(80%),had a hybrid pattern with a high frequency of TP53(72%)and PIK3CA(39%)mutations and a much lower fre-quency of other significantly mutated genes including PIK3R1(4%). Intrinsic mRNA subtypes differed not only by mutation frequencies but also by mutation type.Most notably,TP53mutations in basal-like tumours were mostly nonsense and frame shift,whereas missense mutations predominated in luminal A and B tumours(Supplemen-tary Fig.1).Fifty-eight somatic GATA3mutations,some of which were previously described25,were detected including a hotspot2-base-pair deletion within intron4only in the luminal A subtype(13out of13 mutants)(Supplementary Fig.2).In contrast,7out of9frame-shift mutations in exon5(DNA binding domain)occurred in luminal B cancers.PIK3CA mutation frequency and spectrum also varied by mRNA subtype(Supplementary Fig.3);the recurrent PIK3CA E545K mutation was present almost exclusively within luminal A (25out of27)tumours.CDH1mutations were common(30out of 36)within the lobular histological subtype and corresponded with lower CDH1mRNA(Supplementary Fig.4)and protein expression. Finally,we identified4out of8somatic variants in HER2within lobular cancers,three of which were within the tyrosine kinase domain.We performed analyses on a selected set of genes26using the normal tissue DNA data and detected a number of germline predisposing variants.These analyses identified47out of507patients with deleterious germline variants,representing nine different genes (ATM,BRCA1,BRCA2,BRIP1,CHEK2,NBN,PTEN,RAD51C and TP53;Supplementary Table3),supporting the hypothesis that,10% of sporadic breast cancers may have a strong germlinecontribution.PIK3CA TP53MAP3K1MAP2K4GATA3MLL3CDH1PTEN PIK3R1AKT1RUNX1CBFB TBX3NCOR1CTCF FOXA1SF3B1CDKN1B RB1AFF2NF1PTPN22PTPRDCopy number statusClinical dataMutationsper MbFigure1|Significantly mutated genes and correlations with genomic andclinical features.Tumour samples are grouped by mRNA subtype:luminal A(n5225),luminal B(n5126),HER2E(n557)and basal-like(n593).Theleft panel shows non-silent somatic mutation patterns and frequencies forsignificantly mutated genes.The middle panel shows clinical features:darkgrey,positive or T2–4;white,negative or T1;light grey,N/A or equivocal.N,node status;T,tumour size.The right panel shows significantly mutatedgenes with frequent copy number amplifications(red)or deletions(blue).Thefar-right panel shows non-silent mutation rate per tumour(mutations permegabase,adjusted for coverage).The average mutation rate for eachexpression subtype is indicated.Hypermutated:mutation rates.3s.d.abovethe mean(.4.688,indicated by grey line).ARTICLE62|N A T U R E|V O L490|4O C T O B E R2012Macmillan Publishers Limited. All rights reserved©2012These data confirmed the association between the presence of germline BRCA1mutations and basal-like breast cancers7,8.Gene expression analyses(mRNA and miRNA)Several approaches were used to look for structure in the mRNA expression data.We performed an unsupervised hierarchical cluster-ing analysis of525tumours and22tumour-adjacent normal tissues using the top3,662variably expressed genes(Supplementary Fig.5); SigClust analysis identified12classes(5classes with.9samples per class).We performed a semi-supervised hierarchical cluster analysis using a previously published‘intrinsic gene list’14,which identified13 classes(9classes with.9samples per class)(Supplementary Fig.6). We also classified each sample using the50-gene PAM50model14 (Supplementary Fig.5).High concordance was observed between all three analyses;therefore,we used the PAM50-defined subtype predictor as a common classification metric.There were only eight normal-like and eight claudin-low tumours27,thus we did not per-form focussed analyses on these two subtypes.MicroRNA expression levels were assayed via Illumina sequencing, using1,222miRBase28v16mature and star strands as the reference database of miRNA transcripts/genes.Seven subtypes were identified by consensus non-negative matrix factorization(NMF)clustering using an abundance matrix containing the25%most variable miRNAs(306transcripts/genes or MIMATs(miRNA IDs)).These subtypes correlated with mRNA subtypes,ER,PR and HER2clinical status(Supplementary Fig.7).Of note,miRNA groups4and5 showed high overlap with the basal-like mRNA subtype and con-tained many TP53mutations.The remaining miRNA groups(1–3, 6and7)were composed of a mixture of luminal A,luminal B and HER2E with little correlation with the PAM50defined subtypes.With the exception of TP53—which showed a strong positive correlation—and PIK3CA and GATA3—which showed negative associations with groups4and5,respectively—there was little correlation with muta-tion status and miRNA subtype.DNA methylationIllumina Infinium DNA methylation arrays were used to assay802 breast tumours.Data from HumanMethylation27(HM27)and HumanMethylation450(HM450)arrays were combined and filtered to yield a common set of574probes used in an unsupervised clustering analysis,which identified five distinct DNA methylation groups (Supplementary Fig.8).Group3showed a hypermethylated pheno-type and was significantly enriched for luminal B mRNA subtype and under-represented for PIK3CA,MAP3K1and MAP2K4mutations. Group5showed the lowest levels of DNA methylation,overlapped with the basal-like mRNA subtype,and showed a high frequency of TP53mutations.HER2-positive(HER21)clinical status,or the HER2E mRNA subtype,had only a modest association with the methylation subtypes.A supervised analysis of the DNA methylation and mRNA expres-sion data was performed to compare DNA methylation group3 (N549)versus all tumours in groups1,2and4(excluding group5, which consisted predominantly of basal-like tumours).This analysis identified4,283genes differentially methylated(3,735higher in group 3tumours)and1,899genes differentially expressed(1,232downregu-lated);490genes were both methylated and showed lower expression in group3tumours(Supplementary Table4).A DAVID(database for annotation,visualization and integrated discovery)functional annota-tion analysis identified‘extracellular region part’and‘Wnt signalling pathway’to be associated with this490-gene set;the group3hyper-methylated samples showed fewer PIK3CA and MAP3K1mutations, and lower expression of Wnt-pathway genes.DNA copy numberA total of773breast tumours were assayed using Affymetrix6.0 SNP arrays.Segmentation analysis and GISTIC were used to identify focal amplifications/deletions and arm-level gains and losses (Supplementary Table5).These analyses confirmed all previously reported copy number variations and highlighted a number of sig-nificantly mutated genes including focal amplification of regions con-taining PIK3CA,EGFR,FOXA1and HER2,as well as focal deletions of regions containing MLL3,PTEN,RB1and MAP2K4(Supplementary Fig.9);in all cases,multiple genes were included within each altered region.Importantly,many of these copy number changes correlated with mRNA subtype including characteristic loss of5q and gain of 10p in basal-like cancers5,29and gain of1q and/or16q loss in luminal tumours4.NMF clustering of GISTIC segments identified five copy number clusters/groups that correlated with mRNA subtypes,ER,PR and HER2clinical status,and TP53mutation status(Supplementary Fig.10).In addition,this aCGH subtype classification was highly correlated with the aCGH subtypes recently defined by ref.30 (Supplementary Fig.11).Reverse phase protein arraysQuantified expression of171cancer-related proteins and phospho-proteins by RPPA was performed on403breast tumours31. Unsupervised hierarchical clustering analyses identified seven subtypes;one class contained too few cases for further analysis (Supplementary Fig.12).These protein subtypes were highly concordant with the mRNA subtypes,particularly with basal-like and HER2E mRNA subtypes.Closer examination of the HER2-containing RPPA-defined subgroup showed coordinated overexpres-sion of HER2and EGFR with a strong concordance with phosphorylated HER2(pY1248)and EGFR(pY992),probably from heterodimeriza-tion and cross-phosphorylation.Although there is a potential for modest cross reactivity of antibodies against these related total and phospho-proteins,the concordance of phosphorylation of HER2and EGFR was confirmed using multiple independent antibodies.In RPPA-defined luminal tumours,there was high protein expres-sion of ER,PR,AR,BCL2,GATA3and INPP4B,defining mostly luminal A cancers and a second more heterogeneous protein subgroup composed of both luminal A and luminal B cancers.Two potentially novel protein-defined subgroups were identified:reactive I consisted primarily of a subset of luminal A tumours,whereas reactive II consisted of a mixture of mRNA subtypes.These groups are termed ‘reactive’because many of the characteristic proteins are probably produced by the microenvironment and/or cancer-activated fibroblasts including fibronectin,caveolin1and collagen VI.These two RPPA groups did not have a marked difference in the percentage tumour cell content when compared to each other,or the other protein subtypes, as assessed by SNP array analysis or pathological examination.In addition,supervised analyses of reactive I versus II groups using miRNA expression,DNA methylation,mutation,or DNA copy number data identified no significant differences between these groups, whereas similar supervised analyses using protein and mRNA expres-sion identified many differences.Multiplatform subtype discoveryTo reveal higher-order structure in breast tumours based on multiple data types,significant clusters/subtypes from each of five platforms were analysed using a multiplatform data matrix subjected to unsupervised consensus clustering(Fig.2).This‘cluster of clusters’(C-of-C)approach illustrated that basal-like cancers had the most distinct multiplatform signature as all the different platforms for the basal-like groups clustered together.To a great extent,the four major C-of-C subdivisions correlated well with the previously published mRNA subtypes(driven,in part,by the fact that the four intrinsic subtypes were one of the inputs).Therefore,we also performed C-of-C analysis with no mRNA data present(Supplementary Fig.13) or with the12unsupervised mRNA subtypes(Supplementary Fig.14), and in each case4–6groups were identified.Recent work identified ten copy-number-based subgroups in a997breast cancer set30.We evaluatedARTICLE4O C T O B E R2012|V O L490|N A T U R E|63Macmillan Publishers Limited. All rights reserved ©2012this classification in a C-of-C analysis instead of our five-class copy number subtypes,with either the PAM50(Supplementary Fig.15)or 12unsupervised mRNA subtypes (Supplementary Fig.16);each of these C-of-C classifications was highly correlated with PAM50mRNA subtypes and with the other C-of-C analyses (Fig.2).The transcriptional profiling and RPPA platforms demonstrated a high correlation with the consensus structure,indicating that the informa-tion content from copy number aberrations,miRNAs and methylation is captured at the level of gene expression and protein function.Luminal/ER 1summary analysisLuminal/ER 1breast cancers are the most heterogeneous in terms of gene expression (Supplementary Fig.5),mutation spectrum (Fig.1),copy number changes (Supplementary Fig.9)and patient outcomes 1,14.One of the most dominant features is high mRNA and protein expres-sion of the luminal expression signature (Supplementary Fig.5),which contains ESR1,GATA3,FOXA1,XBP1and MYB ;the luminal/ER 1cluster also contained the largest number of significantly mutated genes.Most notably,GATA3and FOXA1were mutated in a mutually exclusive fashion,whereas ESR1and XBP1were typically highly expressed but infrequently mutated.Mutations in RUNX1and its dimerization partner CBFB may also have a role in aberrant ER signalling in luminal tumours,as RUNX1functions as an ER ‘DNA tethering factor’32.PARADIGM 33analysis comparing luminal versus basal-like cancers further emphasized the presence of a hyperactivated FOXA1–ER complex as a critical network hub differentiating these two tumour subtypes (Supplementary Fig.17).A confirmatory finding here was the high mutation frequency of PIK3CA in luminal/ER 1breast cancers 34,35.Through multipletechnology platforms,we examined possible relationships between PIK3CA mutation,PTEN loss,INPP4B loss and multiple gene and protein expression signatures of pathway activity.RPPA data demonstrated that pAKT,pS6and p4EBP1,typical markers of phosphatidylinositol-3-OH kinase (PI(3)K)pathway activation,were not elevated in PIK3CA -mutated luminal A cancers;instead,they were highly expressed in basal-like and HER2E mRNA subtypes (the latter having frequent PIK3CA mutations)and correlated strongly with INPP4B and PTEN loss,and to a degree with PIK3CA amplification.Similarly,protein 36and three mRNA signatures 37–39of PI(3)K pathway activation were enriched in basal-like over luminal A cancers (Fig.3a).This apparent disconnect between the presence of PIK3CA mutations and biomarkers of pathway activation has been previously noted 36.Another striking luminal/ER 1subtype finding was the frequent mutation of MAP3K1and MAP2K4,which represent two contiguous steps within the p38–JNK1pathway 24,40.These mutations are predicted to be inactivating,with MAP2K4also a target of focal DNA loss in luminal tumours (Supplementary Fig.9).To explore the possible interplay between PIK3CA ,MAP3K and MAP2K4signalling,MEMo analysis 41was performed to identify mutually exclusive alterations targeting frequently altered genes likely to belong to the same pathway (Fig.4).Across all breast cancers,MEMo identified a set of modules that highlight the differential activation events within the receptor tyrosine kinase (RTK)–PI(3)K pathway (Fig.4a);mutations of PIK3CA were very common in luminal/ER 1cancers whereas PTEN loss was more common in basal-like tumours.Almost all MAP3K1and MAP2K4mutations were in luminal tumours,yet MAP3K1and MAP2K4appeared almost mutually exclusive relative to one another.The TP53pathway was differentially inactivated in luminal/ER 1breast cancers,with a low TP53mutation frequency in luminal A (12%)and a higher frequency in luminal B (29%)cancers (Fig.1).In addition to TP53itself,a number of other pathway-inactivating events occurred including ATM loss and MDM2amplification (Figs 3b and 4b),both of which occurred more frequently within luminal B cancers.Gene expression analysis demonstrated that individual markers of functional TP53(GADD45A and CDKN1A ),and TP53activity 42,43signatures,were highest in luminal A cancers (Fig.3b).These data indicate that the TP53pathway remains largely intact in luminal A cancers but is often inactivated in the more aggressive luminal B cancers 44.Other PARADIGM-based pathway differences driving luminal B versus luminal A included hyperactivation of transcriptional activity associated with MYC and FOXM1proliferation.The critical retinoblastoma/RB1pathway also showed mRNA-subtype-specific alterations (Fig.3c).RB1itself,by mRNA and protein expression,was detectable in most luminal cancers,with highest levels within luminal A.A common oncogenic event was cyclin D1amplification and high expression,which preferentially occurred within luminal tumours,and more specifically within luminal B.In contrast,the presumed tumour suppressor CDKN2C (also called p18)was at its lowest levels in luminal A cancers,con-sistent with observations in mouse models 45.Finally,RB1activity signatures were also high in luminal cancers 46–48.Luminal A tumours,which have the best prognosis,are the most likely to retain activity of the major tumour suppressors RB1and TP53.These genomic characterizations also provided clues for druggable targets.We compiled a drug target table in which we defined a target as a gene/protein for which there is an approved or investigational drug in human clinical trials targeting the molecule or canonical pathway (Supplementary Table 6).In luminal/ER 1cancers,the high frequency of PIK3CA mutations suggests that inhibitors of this activated kinase or its signalling pathway may be beneficial.Other potential significantly mutated gene drug candidates include AKT1inhibitors (11out of 12AKT1variants were luminal)and PARP inhibitors for BRCA1/BRCA2mutations.Although still unapproved as biomarkers,many potential copy-number-based drugtargetsP <0.001P <0.001P <0.001P <0.001P =0.002P =0.01P <0.001 P <0.001 P <0.001 P <0.001 P =0.02miRNA 2Methy 2CN 2PAM50 LumA RPPA LumA Methy 1miRNA 6RPPA reactive I CN 4RPPA reactive II miRNA 3CN 1Methy 5PAM50 basal RPPA basal miRNA 5PAM50 normal CN 3Methy 4miRNA 4PAM50 HER2RPPA HER2CN 5Methy 3PAM50 LumB RPPA LumA/B miRNA 7miRNA 1acbFigure 2|Coordinated analysis of breast cancer subtypes defined from five different genomic/proteomic platforms.a ,Consensus clustering analysis of the subtypes identifies four major groups (samples,n 5348).The blue and white heat map displays sample consensus.b ,Heat-map display of the subtypes defined independently by miRNAs,DNA methylation,copy number (CN),PAM50mRNA expression,and RPPA expression.The red bar indicates membership of a cluster type.c ,Associations with molecular and clinical features.P values were calculated using a chi-squared test.ARTICLE64|N A T U R E |V O L 490|4O C T O B E R 2012Macmillan Publishers Limited. All rights reserved©2012were identified including amplifications of fibroblast growth factor receptors (FGFRs)and IGFR1,as well as cyclin D1,CDK4and CDK6.A summary of the general findings in luminal tumours and the other subtypes is presented in Table 1.HER2-based classifications and summary analysisDNA amplification of HER2was readily evident in this study (Supplementary Fig.9)together with overexpression of multipleHER2-amplicon-associated genes that in part define the HER2E mRNA subtype (Supplementary Fig.5).However,not all clinically HER21tumours are of the HER2E mRNA subtype,and not all tumours in the HER2E mRNA subtype are clinically HER21.Integrated analysis of the RPPA and mRNA data clearly identified a HER21group (Supplementary Fig.12).When the HER21protein and HER2E mRNA subtypes overlapped,a strong signal of EGFR,pEGFR,HER2and pHER2was observed.However,only ,50%of clinically HER21tumours fall into this HER2E-mRNA-subtype/HER2-protein group,the rest of the clinically HER21tumours were observed predominantly in the luminal mRNA subtypes.These data indicate that there exist at least two types of clinically defined HER21tumours.To identify differences between these groups,a supervised gene expression analysis comparing 36HER2E-mRNA-subtype/HER21versus 31luminal-mRNA-subtype/HER21tumours was performed and identified 302differentially expressed genes (q -value 50%)(Supplementary Fig.18and Supplementary Table 7).These genes largely track with ER status but also indicated that HER2E-mRNA-subtype/HER21tumours showed significantly higher expres-sion of a number of RTKs including FGFR4,EGFR ,HER2itself,as well as genes within the HER2amplicon (including GRB7).Conversely,the luminal-mRNA-subtype/HER21tumours showed higher expression of the luminal cluster of genes including GATA3,BCL2and ESR1.Further support for two types of clinically defined HER21disease was evident in the somatic mutation data supervised by either mRNA subtype or ER status;TP53mutations were significantly enriched in HER2E or ER-negative tumours whereas GATA3muta-tions were only observed in luminal subtypes or ER 1tumours.Analysis of the RPPA data according to mRNA subtype identified 36differentially expressed proteins (q -value ,5%)(Supplementary Fig.18G and Supplementary Table 8).The EGFR/pEGFR/HER2/pHER2signal was again observed and present within the HER2E-mRNA-subtype/HER21tumours,as was high pSRC and pS6;con-versely,many protein markers of luminal cancers again distinguished the luminal-mRNA-subtype/HER21tumours.Given the importance of clinical HER2status,a more focused analysis was performed based on the RPPA-defined protein expression of HER2(Supplementary Fig.19)—the results strongly recapitulated findings from the RPPA and mRNA subtypes including a high correlation between HER2clinical status,HER2protein by RPPA,pHER2,EGFR and pEGFR.These multiple signatures,namely HER2E mRNA subtype,HER2amplicon genes by mRNA expression,and RPPA EGFR/pEGFR/HER2/pHER2signature,ultimately identify at least two groups/subtypes within clinically HER21tumours (Table 1).These signatures represent breast cancer biomarker(s)that could potentially predict response to anti-HER2targeted therapies.Many therapeutic advances have been made for clinically HER21disease.This study has identified additional somatic mutations that represent potential therapeutic targets within this group,including a high frequency of PIK3CA mutations (39%),a lower frequency of PTEN and PIK3R1mutations (Supplementary Table 6),and genomic losses of PTEN and INPP4B .Other possible druggable mutations included variants within HER family members including two somatic mutations in HER2,two within EGFR ,and five within HER3.Pertuzumab,in combination with trastuzumab,targets the HER2–HER3heterodimer 49;however,these data suggest that targeting EGFR with HER2could also be beneficial.Finally,the HER2E mRNA subtype typically showed high aneuploidy,the highest somatic mutation rate (Table 1),and DNA amplification of other potential therapeutic targets including FGFRs,EGFR ,CDK4and cyclin D1.Basal-like summary analysisThe basal-like subtype was discovered more than a decade ago by first-generation cDNA microarrays 13.These tumours are often referred to as triple-negative breast cancers (TNBCs)because most basal-like tumours are typically negative for ER,PR andHER2.IARC GSK KANNAN TROESTERCDKN1A mRNA GADD45A mRNAMDM2 mRNATP53 copy CDKN2A copy CHEK1 copy ATM copy MDM2 copy MDM4 copy PPM1D copy TP53 mutationMissense Nonsense/frame shift Splice siteTP53 LOH Differences by TP53 mutation (P <0.0001)Differences by luminal A subtype vs others (P <0.0001)TP53 pathway (506 tumours with mRNA/mutation data)b Gain Loss Copy change Gene signature activity More Less mRNA expression Low High High Low Protein expression mRNA subtype:Basal-likeLuminal BLuminal ANormal-likePIK3CA mutation PTEN LOH INPP4B LOH Correlated with PI(3)K protein signature (P <0.0005)Differences by PTEN/INPP4B LOH (P <0.05)Differences by basal subtype vs others (P <0.01)pAkt 308pAkt 473pmTOR pGSK3p70S6Kp389pS6 240.244p4EBP1 65INPP4B PTENRPPA (protein)Saal (mRNA)CMap (mRNA)Majumder (mRNA)PI(3)K pathway (390 tumours with mRNA/mutation/protein data)a PTEN copy INPP4B copy PIK3CA copy CHICAS LARAHERSCHKOWITZRB1 mRNA CDKN2A mRNA CDKN2C mRNARB1 copy CCND1 copy CCNE1 copy RB1 mutationRB1 LOH Differences by RB1 mutation (P <0.003)Differences by RB1 LOH (P <0.005)RB1 protein Differences by luminal A subtype vs others (P <0.0001)RB pathway (506 tumours with mRNA/mutation data)c HER2-enriched*‡* † ‡* † ‡* † ‡* † ‡† ‡† ‡† ‡††† ‡† ‡† ‡† ‡* † ‡* † ‡*‡†† ‡† ‡* † ‡† ‡‡* † ‡* † ‡* † ‡* † ‡* ††* †* †* †* †* †*†*†*†‡*†‡Figure 3|Integrated analysis of the PI(3)K,TP53and RB1pathways.Breast cancer subtypes differ by genetic and genomic targeting events,withcorresponding effects on pathway activity.a –c ,For PI(3)K (a ),TP53(b )and RB1(c )pathways,key genes were selected using prior biological knowledge.Multiple mRNA expression signatures for a given pathway were defined (details in Supplementary Methods;PI(3)K:Saal,PTEN loss in human breast tumours;CMap,PI(3)K/mTOR inhibitor treatment in vitro ;Majumder,Akt overexpression in mouse model;TP53:IARC,expert-curated p53targets;GSK,TP53mutant versus wild-type cell lines;KANNAN,TP53overexpression in vitro ;TROESTER,TP53knockdown in vitro ;RB:CHICAS,RB1mouse knockout versus wild type;LARA,RB1knockdown in vitro ;HERSCHKOWITZ,RB1loss of heterozygosity (LOH)in human breast tumours)and applied to the gene expression data,in order to score each tumour for relative signature activity (yellow,more active).The PI(3)K panel includes a protein-based (RPPA)proteomic signature.Tumours were ordered first by mRNA subtype,although specific ordering differs between the panels.P values were calculated by a Pearson’s correlation or a Chi-squared test.ARTICLE 4O C T O B E R 2012|V O L 490|N A T U R E |65Macmillan Publishers Limited. All rights reserved©2012。
解析DNA甲基化临床科研无论什么科室，一定要有project的经典视角｜易基因
解析DNA甲基化临床科研无论什么科室，一定要有project的经典视角｜易基因大家好，这里是专注表观组学十余年，领跑多组学科研服务的易基因。
本期我们来聊聊一直以来备受关注的DNA甲基化。
关键词：DNA甲基化；基金；临床科研（DNA甲基转移酶DNMT靶向特定基因组特征。
/31815535/）（DNA甲基转移酶DNMT靶向特定基因组特征。
https:///31815535/）导言：DNA甲基化（DNA methylation）是一种生物过程，是DNA化学修饰的一种形式，能在不改变DNA序列的前提下改变 DNA 片段的活性、从而改变遗传表现，为表观遗传编码的一部分，是一种外遗传机制，对细胞的正常发育至关重要，因此，与人体的几乎全部病理生理过程都密切相关。
（举例：肿瘤中的DNA甲基化过程。
https:///27256564/）DNA甲基化研究一直以来都是顶级期刊、基金资助、临床研究、药物研发上市的多重热点。
DNA甲基化研究成果17.7%发表在9分+期刊，2.5%发表在24分以上期刊；并且最近几年的论文发表数量增速堪比火箭。
绝对是万众瞩目的热点。
(DNA甲基化研究发表的期刊分布及时间分布）一，DNA甲基化研究论文大数据分析DNA甲基化论文发表的时间和国家分布全球已经在DNA甲基化领域发表了18,838篇Medline收录的文献。
时间分布显示，可以看到针对DNA甲基化的研究论文数量，2018年有1,355篇，2021年为1,728篇。
国家分布可以看到，美国发表的文章数占31.6%；中国发表的研究论文数量为2,794篇，占25.5%，排在第二位；德国、日本和加拿大分列第三到五位。
（SCI论文的时间和国家分布）学术机构排名中南大学、复旦大学、密歇根大学、首都医科大学、麦吉尔大学(加拿大)等所在大学发表的论文最多。
湘雅医院、梅奥诊所、中南大学湘雅二医院、国立癌症中心研究所(日本)、Hospital for Sick Children(加拿大)等是发表论文最多的医院。
蛋白质修饰
• posttranslational modifications: alter their interaction with DNA and nuclear proteins. H3 & H4: long tails; can be modified at several places, including methylation, acetylation, phosphorylation, ubiquitination, sumoylation, citrullination and ADPribosylation. The core of the histones H2A and H3 can also be modified. • Histone Code: hypothesized to be a code consisting of covalent histone tail modifications → epigenetic code
– modification site may be a targeting signal – modification may be a membrane anchor
• Degradation
– identify the protein for degradation
• ……
For more information, see /wiki/Posttranslational_modification
Non-histone Acetylation/Deacetylation
a significant post-translational regulatory mechanism
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ProfilingofChildhoodAdversity-AssociatedDNAMethylationChangesinAlcoholicPatientsandHealthyControls
HuipingZhang1,5*,FanWang1,5,HenryR.Kranzler6,HongyuZhao4,JoelGelernter1,2,3,51DepartmentofPsychiatry,YaleUniversitySchoolofMedicine,NewHaven,Connecticut,UnitedStatesofAmerica,2DepartmentofGenetics,YaleUniversitySchoolofMedicine,NewHaven,Connecticut,UnitedStatesofAmerica,3DepartmentofNeurobiology,YaleUniversitySchoolofMedicine,NewHaven,Connecticut,UnitedStatesofAmerica,4DivisionofBiostatistics,YaleUniversitySchoolofPublicHealth,NewHaven,Connecticut,UnitedStatesofAmerica,5VAConnecticutHealthcareSystem,WestHaven,Connecticut,UnitedStatesofAmerica,6DepartmentofPsychiatry,UniversityofPennsylvaniaPerelmanSchoolofMedicineandVISN4MIRECC,PhiladelphiaVAMC,Philadelphia,Pennsylvania,UnitedStatesofAmerica
AbstractTheincreasedvulnerabilitytoalcoholdependence(AD)seeninindividualswithchildhoodadversity(CA)mayresultinpartfromCA-inducedepigeneticchanges.ToexamineCA-associatedDNAmethylationchangesinADpatients,weexaminedperipheralbloodDNAmethylationlevelsof384CpGsinpromoterregionsof82candidategenesin279AfricanAmericans[AAs;88withCA(70.5%withAD)and191withoutCA(38.2%withAD)]and239EuropeanAmericans[EAs;61withCA(86.9%withAD)and178withoutCA(46.6%withAD)]usingIlluminaGoldenGateMethylationArrayassays.TheeffectofCAonmethylationofindividualCpGsandoverallmethylationinpromoterregionsofgeneswasevaluatedusingalinearregressionanalysis(withconsiderationofsex,age,andancestryproportionofsubjects)andaprincipalcomponents-basedanalysis,respectively.InEAs,hypermethylationof10CpGsinsevengenes(ALDH1A1,CART,CHRNA5,HTR1B,OPRL1,PENK,andRGS19)werecrossvalidatedinADpatientsandhealthycontrolswhowereexposedtoCA.PvaluesoftwoCpGssurvivedBonferronicorrectionwhenallEAsampleswereanalyzedtogethertoincreasestatisticalpower[CHRNA5_cg17108064:Padjust=2.5461025;HTR1B_cg06031989:Padjust=8.9861025].Moreover,overallmethylationlevels
inthepromoterregionsofthreegenes(ALDH1A1,OPRL1andRGS19)wereelevatedinbothEAcaseandcontrolsubjectswhowereexposedtoCA.However,inAAs,CA-associatedDNAmethylationchangesinADpatientswerenotvalidatedinhealthycontrols.OurfindingssuggestthatCAcouldinducepopulation-specificmethylationalterationsinthepromoterregionsofspecificgenes,thusleadingtochangesingenetranscriptionandanincreasedriskforADandotherdisorders.
Citation:ZhangH,WangF,KranzlerHR,ZhaoH,GelernterJ(2013)ProfilingofChildhoodAdversity-AssociatedDNAMethylationChangesinAlcoholicPatientsandHealthyControls.PLoSONE8(6):e65648.doi:10.1371/journal.pone.0065648
Editor:CarmenJ.Marsit,DartmouthMedicalSchool,UnitedStatesofAmericaReceivedJanuary7,2013;AcceptedApril25,2013;PublishedJune14,2013Copyright:ß2013Zhangetal.Thisisanopen-accessarticledistributedunderthetermsoftheCreativeCommonsAttributionLicense,whichpermitsunrestricteduse,distribution,andreproductioninanymedium,providedtheoriginalauthorandsourcearecredited.
Funding:ThisstudywassupportedbytheNationalInstitutesofHealth(NIH)GrantsK99/R00DA022891(toH.Zhang),R01DA12690(toJG),R01AA11330(toJG),R01DA12849(toJG),R01DA018432(toHRK),andgrantsfromtheVeteran’sAffairsConnecticutMentalIllnessResearch,EducationandClinicalCenter(MIRECC)toJGandtheAlcoholicBeverageMedicalResearchFoundation(ABMRF)toH.Zhang.Thefundershadnoroleinstudydesign,datacollectionandanalysis,decisiontopublish,orpreparationofthemanuscript.
CompetingInterests:Theco-authorDr.Kranzlerhasbeenapaidconsultantoradvisoryboardmemberforthefollowingpharmaceuticalcompanies:Alkermes,Lilly,Lundbeck,Pfizer,andRoche.Dr.KranzlerhasalsoreceivedhonorariafromtheAlcoholClinicalTrialsInitiative(ACTIVE),whichissupportedbyAbbott,Lilly,Lundbeck,andPfizer.However,thisdoesnotalterhisadherencetoallthePLOSONEpoliciesonsharingdataandmaterials.ThecorrespondingauthorDr.ZhangiscurrentlytheacademiceditorforPLOSONE.However,thisdoesnotalterhisadherencetoallthePLOSONEpoliciesonsharingdataandmaterials.
*E-mail:huiping.zhang@yale.edu
IntroductionChildhoodadversity(CA)mayleadtoimpairedmentalandphysicalhealththatcanpersistintoadulthood.Adversechildhoodexperienceshavebeenassociatedwithmooddisorders[1],schizophrenia[2,3,4],anxietydisorders[5],suicide[6],person-alitydisorders[7,8],posttraumaticstressdisorder[9,10],andsubstanceusedisorders[11,12,13,14].Excessiveandpersistentadversityinearlychildhoodproducessustainedelevationsofstresshormones(e.g.,cortisol)[15],whichmaydamagethedevelopmentofthebasicneuralcircuitryinthebrain.TheeffectofCAonvulnerabilitytothevarietiesofdisordersmaybemediatedinpartbyepigeneticevents,suchasDNAmethylation,histonemodificationandmicroRNAregulation,whichcansubstantiallyaffectgenetranscriptionwithoutchangingDNAsequence[16,17].Epigeneticmodificationsareessentialfor