Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
Diabetologia. 2022 May;65(5):763-776. doi: 10.1007/s00125-022-05652-2. Epub 2022 Feb 15.
AIMS/HYPOTHESIS: Type 2 diabetes is a complex metabolic disease with increasing prevalence worldwide. Improving the prediction of incident type 2 diabetes using epigenetic markers could help tailor prevention efforts to those at the highest risk. The aim of this study was to identify predictive methylation markers for incident type 2 diabetes by combining epigenome-wide association study (EWAS) results from five prospective European cohorts.
We conducted a meta-analysis of EWASs in blood collected 7-10 years prior to type 2 diabetes diagnosis. DNA methylation was measured with Illumina Infinium Methylation arrays. A total of 1250 cases and 1950 controls from five longitudinal cohorts were included: Doetinchem, ESTHER, KORA1, KORA2 and EPIC-Norfolk. Associations between DNA methylation and incident type 2 diabetes were examined using robust linear regression with adjustment for potential confounders. Inverse-variance fixed-effects meta-analysis of cohort-level individual CpG EWAS estimates was performed using METAL. The methylGSA R package was used for gene set enrichment analysis. Confirmation of genome-wide significant CpG sites was performed in a cohort of Indian Asians (LOLIPOP, UK).
The meta-analysis identified 76 CpG sites that were differentially methylated in individuals with incident type 2 diabetes compared with control individuals (p values <1.1 × 10). Sixty-four out of 76 (84.2%) CpG sites were confirmed by directionally consistent effects and p values <0.05 in an independent cohort of Indian Asians. However, on adjustment for baseline BMI only four CpG sites remained genome-wide significant, and addition of the 76 CpG methylation risk score to a prediction model including established predictors of type 2 diabetes (age, sex, BMI and HbA) showed no improvement (AUC 0.757 vs 0.753). Gene set enrichment analysis of the full epigenome-wide results clearly showed enrichment of processes linked to insulin signalling, lipid homeostasis and inflammation.
CONCLUSIONS/INTERPRETATION: By combining results from five European cohorts, and thus significantly increasing study sample size, we identified 76 CpG sites associated with incident type 2 diabetes. Replication of 64 CpGs in an independent cohort of Indian Asians suggests that the association between DNA methylation levels and incident type 2 diabetes is robust and independent of ethnicity. Our data also indicate that BMI partly explains the association between DNA methylation and incident type 2 diabetes. Further studies are required to elucidate the underlying biological mechanisms and to determine potential causal roles of the differentially methylated CpG sites in type 2 diabetes development.
目的/假设：2 型糖尿病是一种复杂的代谢疾病，其发病率在全球范围内呈上升趋势。利用表观遗传标记物来提高 2 型糖尿病发病的预测能力，有助于针对风险最高的人群进行预防。本研究的目的是通过合并五个欧洲前瞻性队列的全基因组关联研究（EWAS）结果，确定预测 2 型糖尿病发病的预测性甲基化标记物。
我们对发病前 7-10 年采集的血液进行了 EWAS 的荟萃分析。使用 Illumina Infinium 甲基化芯片测量 DNA 甲基化。共纳入了来自五个纵向队列的 1250 例病例和 1950 例对照：Doetinchem、ESTHER、KORA1、KORA2 和 EPIC-Norfolk。使用稳健的线性回归，在调整潜在混杂因素后，对 DNA 甲基化与 2 型糖尿病发病之间的相关性进行了检验。使用 METAL 对队列水平的个体 CpG EWAS 估计值进行了逆方差固定效应荟萃分析。使用 methylGSA R 包进行了基因集富集分析。在一个印度亚裔人群的队列（LOLIPOP，英国）中对全基因组显著的 CpG 位点进行了确认。
荟萃分析确定了 76 个在 2 型糖尿病发病患者与对照组个体之间存在差异甲基化的 CpG 位点（p 值<1.1×10）。在一个独立的印度亚裔人群队列中，76 个 CpG 位点中有 64 个（84.2%）的方向一致，且 p 值<0.05。然而，在调整基线 BMI 后，仅有 4 个 CpG 位点保持全基因组显著，将 76 个 CpG 甲基化风险评分添加到包括 2 型糖尿病的既定预测因子（年龄、性别、BMI 和 HbA）的预测模型中，并未显示出改善（AUC 0.757 与 0.753）。对全基因组结果的基因集富集分析清楚地显示了与胰岛素信号、脂质稳态和炎症相关的过程的富集。
结论/解释：通过合并五个欧洲队列的结果，从而显著增加了研究样本量，我们确定了 76 个与 2 型糖尿病发病相关的 CpG 位点。在一个独立的印度亚裔人群队列中对 64 个 CpG 进行了复制，表明 DNA 甲基化水平与 2 型糖尿病发病之间的关联是稳健的，且与种族无关。我们的数据还表明，BMI 部分解释了 DNA 甲基化与 2 型糖尿病发病之间的关联。需要进一步的研究来阐明潜在的生物学机制，并确定 2 型糖尿病发病中差异甲基化 CpG 位点的潜在因果作用。
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