Pathway enrichment analyses.

BackgroundDNA methylation is a dynamic epigenetic mechanism that occurs at cytosine-phosphate-guanine dinucleotide (CpG) sites. Epigenome-wide association studies (EWAS) investigate the strength of association between methylation at individual CpG sites and health outcomes. Although blood methylation may act as a peripheral marker of common disease states, previous EWAS have typically focused only on individual conditions and have had limited power to discover disease-associated loci. This study examined the association of blood DNA methylation with the prevalence of 14 disease states and the incidence of 19 disease states in a single population of over 18,000 Scottish individuals.Methods and findingsDNA methylation was assayed at 752,722 CpG sites in whole-blood samples from 18,413 volunteers in the family-structured, population-based cohort study Generation Scotland (age range 18 to 99 years). EWAS tested for cross-sectional associations between baseline CpG methylation and 14 prevalent disease states, and for longitudinal associations between baseline CpG methylation and 19 incident disease states. Prevalent cases were self-reported on health questionnaires at the baseline. Incident cases were identified using linkage to Scottish primary (Read 2) and secondary (ICD-10) care records, and the censoring date was set to October 2020. The mean time-to-diagnosis ranged from 5.0 years (for chronic pain) to 11.7 years (for Coronavirus Disease 2019 (COVID-19) hospitalisation). The 19 disease states considered in this study were selected if they were present on the World Health Organisation’s 10 leading causes of death and disease burden or included in baseline self-report questionnaires. EWAS models were adjusted for age at methylation typing, sex, estimated white blood cell composition, population structure, and 5 common lifestyle risk factors. A structured literature review was also conducted to identify existing EWAS for all 19 disease states tested. The MEDLINE, Embase, Web of Science, and preprint servers were searched to retrieve relevant articles indexed as of March 27, 2023. Fifty-four of approximately 2,000 indexed articles met our inclusion criteria: assayed blood-based DNA methylation, had >20 individuals in each comparison group, and examined one of the 19 conditions considered. First, we assessed whether the associations identified in our study were reported in previous studies. We identified 69 associations between CpGs and the prevalence of 4 conditions, of which 58 were newly described. The conditions were breast cancer, chronic kidney disease, ischemic heart disease, and type 2 diabetes mellitus. We also uncovered 64 CpGs that associated with the incidence of 2 disease states (COPD and type 2 diabetes), of which 56 were not reported in the surveyed literature. Second, we assessed replication across existing studies, which was defined as the reporting of at least 1 common site in >2 studies that examined the same condition. Only 6/19 disease states had evidence of such replication. The limitations of this study include the nonconsideration of medication data and a potential lack of generalizability to individuals that are not of Scottish and European ancestry.ConclusionsWe discovered over 100 associations between blood methylation sites and common disease states, independently of major confounding risk factors, and a need for greater standardisation among EWAS on human disease.

背景：DNA甲基化是发生于胞嘧啶-磷酸-鸟嘌呤二核苷酸（CpG）位点的动态表观遗传调控机制。全表观基因组关联研究（Epigenome-wide association studies, EWAS）旨在探究单个CpG位点的甲基化水平与健康结局之间的关联强度。尽管血液甲基化可作为常见疾病状态的外周标志物，但既往EWAS通常仅聚焦于单一疾病，且发现疾病关联位点的统计效力有限。本研究在包含18000余名苏格兰个体的单一人群队列中，探究了血液DNA甲基化与14种疾病状态的患病率以及19种疾病状态的发病率之间的关联。
方法与结果：本研究的研究对象为苏格兰世代（Generation Scotland）这项基于家庭结构的人群队列研究中的18413名志愿者，年龄范围为18~99岁。研究人员对所有志愿者的全血样本中752722个CpG位点的甲基化水平进行了检测。EWAS分析分别检验了基线CpG甲基化与14种现患疾病状态的横断面关联，以及基线CpG甲基化与19种新发疾病状态的纵向关联。现患病例通过基线健康问卷的自我报告信息确定；新发病例则通过与苏格兰初级医疗（Read 2编码）及二级医疗（国际疾病分类第10版，ICD-10）诊疗记录的关联进行识别，研究截尾日期设定为2020年10月。从基线至确诊的平均时间跨度从慢性疼痛的5.0年到2019冠状病毒病（COVID-19）住院治疗的11.7年不等。本研究纳入的19种疾病状态，均为世界卫生组织公布的十大死亡与疾病负担原因，或包含在基线自我报告健康问卷中。EWAS模型校正了甲基化检测时的年龄、性别、估计的白细胞组成、人群结构以及5种常见生活方式风险因素。本研究还开展了系统性文献综述，以检索已发表的针对本次检验的19种疾病的EWAS研究。研究人员检索了MEDLINE、Embase、Web of Science数据库及预印本平台，检索时限截至2023年3月27日。约2000篇索引文献中，共有54篇符合纳入标准：检测了血液来源的DNA甲基化水平、每个比较组的研究对象均超过20例、且针对本次纳入的19种疾病之一展开研究。首先，我们评估了本研究中发现的关联是否已在既往研究中被报道：共鉴定出69个CpG位点与4种疾病的患病率存在关联，其中58个为首次报道的新关联，这4种疾病分别为乳腺癌、慢性肾脏病、缺血性心脏病与2型糖尿病。此外还发现64个CpG位点与2种疾病的发病率相关（慢性阻塞性肺疾病，即COPD，与2型糖尿病），其中56个未在本次综述覆盖的文献中被报道。其次，我们评估了现有研究间的结果可重复性，可重复性的定义为：针对同一疾病开展的≥2项研究中，均报道了至少1个共同的CpG位点。仅6种（共19种）疾病存在此类可重复性证据。本研究的局限性包括未纳入用药数据进行校正，且研究结果可能无法推广至非苏格兰及非欧洲血统的人群。
结论：我们在校正主要混杂风险因素的前提下，发现了100余个血液甲基化位点与常见疾病状态之间的关联，并指出针对人类疾病的EWAS研究亟需提升标准化水平。