Background Type 2 diabetes (T2D) is a heterogeneous disease with well-known genetic and environmental risk factors contributing to its prevalence. Epigenetic mechanisms related to changes in DNA methylation (DNAm), may also contribute to T2D risk, but larger studies are required to discover novel markers, and to confirm existing ones. Results We performed a large meta-analysis of individual epigenome-wide association studies (EWAS) of prevalent T2D conducted in four European studies using peripheral blood DNAm. Analysis of differentially methylated regions (DMR) was also undertaken, based on the meta-analysis results. We found three novel CpGs associated with prevalent T2D in Europeans at cg00144180 (HDAC4), cg16765088 (near SYNM) and cg24704287 (near MIR23A) and confirmed three CpGs previously identified (mapping to TXNIP, ABCG1 and CPT1A). We also identified 77 T2D associated DMRs, most of them hypomethylated in T2D cases versus controls. In adjusted regressions among diabetic-free participants in ALSPAC, we found that all six CpGs identified in the meta-EWAS were associated with white cell-types. We estimated that these six CpGs captured 11% of the variation in T2D, which was similar to the variation explained by the model including only the common risk factors of BMI, sex, age and smoking (R2 = 10.6%). Conclusions This study identifies novel loci associated with T2D in Europeans. We also demonstrate associations of the same loci with other traits. Future studies should investigate if our findings are generalizable in non-European populations, and potential roles of these epigenetic markers in T2D etiology or in determining long term consequences of T2D.

To investigate the role of epigenetics in statins' diabetogenic effect comparing DNA methylation (DNAm) between statin users and nonusers in an epigenome-wide association study in blood. RESEARCH DESIGN AND METHODSFive cohort studies' participants (n 5 8,270) were classified as statin users when they were on statin therapy at the time of DNAm assessment with Illumina 450K or EPIC array or noncurrent users otherwise. Associations of DNAm with various outcomes like incident type 2 diabetes, plasma glucose, insulin, and insulin resistance (HOMA of insulin resistance [HOMA-IR]) as well as with gene expression were investigated. RESULTS Discovery(n 5 6,820) and replication (n 5 1,450) phases associated five DNAm sites with statin use: cg17901584 (1.12 3 10 225 [DHCR24]), cg10177197 (3.94 3 10 208 [DHCR24]), cg06500161 (2.67 3 10 223 [ABCG1]), cg27243685 (6.01 3 10 209 [ABCG1]), and cg05119988 (7.26 3 10 212 [SC4MOL]). Two sites were associated with at least one glycemic trait or type 2 diabetes. Higher cg06500161 methylation was associated with higher fasting glucose, insulin, HOMA-IR, and type 2 diabetes (odds ratio 1.34 [95% CI 1.22, 1.47]). Mediation analyses suggested that ABCG1 methylation partially mediates the effect of statins on high insulin and HOMA-IR. Gene expression analyses showed that statin exposure and ABCG1 methylation were associated with ABCG1 downregulation, suggesting epigenetic regulation of ABCG1 expression. Further, outcomes insulin and HOMA-IR were significantly associated with ABCG1 expression. CONCLUSIONSThis study sheds light on potential mechanisms linking statins with type 2 diabetes risk, providing evidence on DNAm partially mediating statins' effects on insulin traits. Further efforts shall disentangle the molecular mechanisms through which statins may induce DNAm changes, potentially leading to ABCG1 epigenetic regulation.Statins effectively reduce the risk of cardiovascular disease (1). However, clinical trials and observational studies show that statins lead to insulin resistance and type 2 diabetes (2,3). The underlying mechanisms remain unclear.Statins are associated with epigenetic changes, including histone acetylation, miRNA regulation (4), and DNA methylation (DNAm), particularly at genes related to lipid and insulin metabolism (5). DNAm is linked to type 2 diabetes pathophysiology (6); thus, it may be a potential mechanism contributing to the increased risk of type 2

OBJECTIVE Maternal glycemic dysregulation during pregnancy increases the risk of adverse health outcomes in her offspring, a risk thought to be linearly related to maternal hyperglycemia. It is hypothesized that changes in offspring DNA methylation (DNAm) underline these associations. RESEARCH DESIGN AND METHODS To address this hypothesis, we conducted fixed-effects meta-analyses of epigenome-wide association study (EWAS) results from eight birth cohorts investigating relationships between cord blood DNAm and fetal exposure to maternal glucose (Nmaximum = 3,503), insulin (Nmaximum = 2,062), and area under the curve of glucose (AUCgluc) following oral glucose tolerance tests (Nmaximum = 1,505). We performed lookup analyses for identified cytosine-guanine dinucleotides (CpGs) in independent observational cohorts to examine associations between DNAm and cardiometabolic traits as well as tissue-specific gene expression. RESULTS Greater maternal AUCgluc was associated with lower cord blood DNAm at neighboring CpGs cg26974062 (β [SE] = 0.013 [2.1 × 10−3], P value corrected for false discovery rate [PFDR] = 5.1 × 10−3) and cg02988288 (β [SE]−0.013 [2.3 × 10−3], PFDR = 0.031) in TXNIP. These associations were attenuated in women with GDM. Lower blood DNAm at these two CpGs near TXNIP was associated with multiple metabolic traits later in life, including type 2 diabetes. TXNIP DNAm in liver biopsies was associated with hepatic expression of TXNIP. We observed little evidence of associations between either maternal glucose or insulin and cord blood DNAm. CONCLUSIONS Maternal hyperglycemia, as reflected by AUCgluc, was associated with lower cord blood DNAm at TXNIP. Associations between DNAm at these CpGs and metabolic traits in subsequent lookup analyses suggest that these may be candidate loci to investigate in future causal and mediation analyses.

Background: Gestational hyperglycemia is associated with adverse perinatal outcomes and long-term offspring metabolic programming, likely through dysregulation of DNA methylation (DNAm). Materials & methods: We tested associations between maternal HbA1c and cord blood DNAm among 412 mother–child pairs in the genetics of glucose regulation in gestation and growth (Gen3G) and implemented Mendelian randomization to infer causality. We sought replication in an independent sample from Healthy Start. Results: Higher second trimester HbA1c levels were associated with lower DNAm at cg21645848 (p = 3.9 × 10-11) near URGCP. Mendelian randomization and replication analyses showed same direction of effect between HbA1c and DNAm at cg21645848, but did not reach statistical significance. Conclusion: We found that higher maternal glycemia reflected by HbA1c is associated with cord blood DNAm at URGCP, a gene related with inflammatory pathways.

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Purpose of Review This review summarises recent advances in the field of epigenetics in order to understand the aetiology of type 2 diabetes (T2D). Recent Findings DNA methylation at a number of loci has been shown to be robustly associated with T2D, including TXNIP, ABCG1, CPT1A, and SREBF1. However, due to the cross-sectional nature of many epidemiological studies and predominant analysis in samples derived from blood rather than disease relevant tissues, inferring causality is difficult. We therefore outline the use of Mendelian randomisation (MR) as one method able to assess causality in epigenetic studies of T2D. Summary Epidemiological studies have been fruitful in identifying epigenetic markers of T2D. Triangulation of evidence including utilisation of MR is essential to delineate causal from non-causal biomarkers of disease. Understanding the causality of epigenetic markers in T2D more fully will aid prioritisation of CpG sites as early biomarkers to detect disease or in drug development to target epigenetic mechanisms in order to treat patients.

Aims/hypothesis Several studies have identified associations between type 2 diabetes and DNA methylation (DNAm). However, the causal role of these associations remains unclear. This study aimed to provide evidence for a causal relationship between DNAm and type 2 diabetes. Methods We used bidirectional two-sample Mendelian randomisation (2SMR) to evaluate causality at 58 CpG sites previously detected in a meta-analysis of epigenome-wide association studies (meta-EWAS) of prevalent type 2 diabetes in European populations. We retrieved genetic proxies for type 2 diabetes and DNAm from the largest genome-wide association study (GWAS) available. We also used data from the Avon Longitudinal Study of Parents and Children (ALSPAC, UK) when associations of interest were not available in the larger datasets. We identified 62 independent SNPs as proxies for type 2 diabetes, and 39 methylation quantitative trait loci as proxies for 30 of the 58 type 2 diabetes-related CpGs. We applied the Bonferroni correction for multiple testing and inferred causality based on p<0.001 for the type 2 diabetes to DNAm direction and p<0.002 for the opposing DNAm to type 2 diabetes direction in the 2SMR analysis. Results We found strong evidence of a causal effect of DNAm at cg25536676 (DHCR24) on type 2 diabetes. An increase in transformed residuals of DNAm at this site was associated with a 43% (OR 1.43, 95% CI 1.15, 1.78, p=0.001) higher risk of type 2 diabetes. We inferred a likely causal direction for the remaining CpG sites assessed. In silico analyses showed that the CpGs analysed were enriched for expression quantitative trait methylation sites (eQTMs) and for specific traits, dependent on the direction of causality predicted by the 2SMR analysis. Conclusions/interpretation We identified one CpG mapping to a gene related to the metabolism of lipids (DHCR24) as a novel causal biomarker for risk of type 2 diabetes. CpGs within the same gene region have previously been associated with type 2 diabetes-related traits in observational studies (BMI, waist circumference, HDL-cholesterol, insulin) and in Mendelian randomisation analyses (LDL-cholesterol). Thus, we hypothesise that our candidate CpG in DHCR24 may be a causal mediator of the association between known modifiable risk factors and type 2 diabetes. Formal causal mediation analysis should be implemented to further validate this assumption. Graphical Abstract