BACKGROUND DNA 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 FINDINGS DNA 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. CONCLUSIONS We 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.

中文翻译：

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对 19 种常见疾病状态进行基于血液的表观基因组分析：一项针对 18,413 名苏格兰人的纵向、基于人群的关联队列研究。

背景DNA甲基化是发生在胞嘧啶-磷酸-鸟嘌呤二核苷酸(CpG)位点的动态表观遗传机制。全表观基因组关联研究 (EWAS) 研究各个 CpG 位点的甲基化与健康结果之间的关联强度。尽管血液甲基化可能作为常见疾病状态的外周标志物，但以前的 EWAS 通常只关注个体情况，并且发现疾病相关位点的能力有限。这项研究检查了血液 DNA 甲基化与 14 种疾病的患病率以及 18,000 多名苏格兰人的单一人群中 19 种疾病的发病率之间的关系。方法和结果 对来自家庭结构的 18,413 名志愿者的全血样本中的 752,722 个 CpG 位点进行了 DNA 甲基化检测。基于人群的队列研究“苏格兰一代”（年龄范围 18 至 99 岁）。EWAS 测试了基线 CpG 甲基化与 14 种流行疾病状态之间的横断面关联，以及基线 CpG 甲基化与 19 种突发疾病状态之间的纵向关联。流行病例在基线时通过健康调查问卷自我报告。通过与苏格兰初级（阅读 2）和二级（ICD-10）护理记录的链接来识别事件病例，并将审查日期设置为 2020 年 10 月。平均诊断时间范围为 5.0 年（慢性疼痛）到11.7 年（2019 年冠状病毒病 (COVID-19) 住院治疗）。本研究考虑的 19 种疾病状态如果出现在世界卫生组织的 10 种主​​要死亡原因和疾病负担中或包含在基线自我报告问卷中，则被选中。EWAS 模型根据甲基化分型时的年龄、性别、估计的白细胞组成、人口结构和 5 种常见的生活方式危险因素进行了调整。还进行了结构化文献综述，以确定所有测试的 19 种疾病状态的现有 EWAS。搜索了 MEDLINE、Embase、Web of Science 和预印本服务器，以检索截至 2023 年 3 月 27 日索引的相关文章。约 2,000 篇索引文章中的 54 篇符合我们的纳入标准：检测基于血液的 DNA 甲基化，每个比较组中有超过 20 名个体，并检查了所考虑的 19 种情况之一。第一的，我们评估了我们研究中确定的关联是否在之前的研究中报告过。我们确定了 CpG 与 4 种病症患病率之间的 69 种关联，其中 58 种是新描述的。这些疾病包括乳腺癌、慢性肾病、缺血性心脏病和2型糖尿病。我们还发现了 64 个与 2 种疾病状态（慢性阻塞性肺病和 2 型糖尿病）发病相关的 CpG，其中 56 个在调查文献中未报告。其次，我们评估了现有研究的重复性，这被定义为在> 2项研究相同条件的研究中报告至少1个共同位点。只有 6/19 的疾病状态有这种复制的证据。这项研究的局限性包括未考虑药物数据以及对非苏格兰和欧洲血统的个体可能缺乏普遍性。结论 我们发现血液甲基化位点与常见疾病状态之间存在 100 多个关联，独立于主要的混杂风险因素，并且需要在人类疾病的 EWAS 中实现更大程度的标准化。