Epigenome-wide association study identifies TXNIP gene associated with type 2 diabetes mellitus and sustained hyperglycemia

CpG methylation changes associated with hyperglycemia in type 1 diabetes occur at angiogenic glomerular and retinal gene loci

Chronic hyperglycemia is a major risk factor for glomerular or retinal microangiopathy and cardiovascular complications of type 1 diabetes (T1D). At the interface of genetics and environment, dynamic epigenetic changes associated with hyperglycemia may unravel some of the mechanisms contributing to these T1D complications. In this study, blood samples were collected from 112 young patients at T1D diagnosis and 3 years later in average. Whole genome-wide bisulfite sequencing was used to measure blood DNA methylation changes of about 28 million CpGs at single base resolution over this time. Chronic hyperglycemia was estimated every 3-4 months by HbA1c measurement. Linear regressions with adjustment to age, sex, treatment duration, blood proportions and batch effects were employed to characterize the relationships between the dynamic changes of DNA methylation and average HbA1c levels. We identified that longitudinal DNA methylation changes at 815 CpGs (with suggestive p-value threshold of 1e-4) were associated with average HbA1c. Most of them (> 98%) were located outside of the promoter regions and were enriched in CpG island shores and multiple immune cell type specific accessible chromatin regions. Among the 36 more strongly associated loci (p-value < 5e-6), 16 were harbouring genes or non-coding sequences involved in angiogenesis regulation, glomerular and retinal vascularization or development, or coronary disease. Our findings support the identification of new genomic sites where CpG methylation associated with hyperglycemia may contribute to long-term complications of T1D, shedding light on potential mechanisms for further exploration.

The Multi-State Epigenetic Pacemaker enables the identification of combinations of factors that influence DNA methylation

Epigenetic clocks, DNA methylation-based predictive models of chronological age, are often utilized to study aging associated biology. Despite their widespread use, these methods do not account for other factors that also contribute to the variability of DNA methylation data. For example, many CpG sites show strong sex-specific or cell-type-specific patterns that likely impact the predictions of epigenetic age. To overcome these limitations, we developed a multidimensional extension of the Epigenetic Pacemaker, the Multi-state Epigenetic Pacemaker (MSEPM). We show that the MSEPM is capable of accurately modeling multiple methylation-associated factors simultaneously, while also providing site-specific models that describe the per site relationship between methylation and these factors. We utilized the MSEPM with a large aggregate cohort of blood methylation data to construct models of the effects of age-, sex-, and cell-type heterogeneity on DNA methylation. We found that these models capture a large faction of the variability at thousands of DNA methylation sites. Moreover, this approach allows us to identify sites that are primarily affected by aging and no other factors. An analysis of these sites reveals that those that lose methylation over time are enriched for CTCF transcription factor chip peaks, while those that gain methylation over time are associated with bivalent promoters of genes that are not expressed in blood. These observations suggest mechanisms that underlie age-associated methylation changes and suggest that age-associated increases in methylation may not have strong functional consequences on cell states. In conclusion, the MSEPM is capable of accurately modeling multiple methylation-associated factors, and the models produced can illuminate site-specific combinations of factors that affect methylation dynamics.

Epigenome-wide association study of incident type 2 diabetes in Black and White participants from the Atherosclerosis Risk in Communities Study

AIMS/HYPOTHESIS

DNA methylation studies of incident type 2 diabetes in US populations are limited and to our knowledge none include individuals of African descent. We aimed to fill this gap by identifying methylation sites (CpG sites) and regions likely influencing the development of type 2 diabetes using data from Black and White individuals from the USA.

METHODS

We prospectively followed 2091 Black and 1029 White individuals without type 2 diabetes from the Atherosclerosis Risk in Communities study over a median follow-up period of 17 years, and performed an epigenome-wide association analysis of blood-based methylation levels with incident type 2 diabetes using Cox regression. We assessed whether significant CpG sites were associated with incident type 2 diabetes independently of BMI or fasting glucose at baseline. We estimated variation in incident type 2 diabetes accounted for by the major non-genetic risk factors and the significant CpG sites. We also examined groups of methylation sites that were differentially methylated. We performed replication of previously discovered CpG sites associated with prevalent and/or incident type 2 diabetes. All analyses were adjusted for batch effects, cell-type proportions and relevant confounders.

RESULTS

At an epigenome-wide threshold (10-7), we detected seven novel diabetes-associated CpG sites, of which the sites at MICOS10 (cg05380846: HR 0.89, p=8.4 × 10-12), ZNF2 (cg01585592: HR 0.88, p=1.6 × 10-9), JPH3 (cg16696007: HR 0.87, p=7.8 × 10-9) and GPX6 (cg02793507: HR 0.85, p=2.7 × 10-8; cg00647063: HR 1.20, p=2.5 × 10-8) were identified in Black adults; chr17q25 (cg16865890: HR 0.8, p=6.9 × 10-8) in White adults; and chr11p15 (cg13738793: HR 1.11, p=7.7 × 10-8) in the meta-analysed group. The JPH3 and GPX6 sites remained epigenome-wide significant on adjustment for BMI, while only the JPH3 site retained significance after adjusting for fasting glucose. We replicated known type 2 diabetes-associated CpG sites, including cg19693031 at TXNIP, cg00574958 at CPT1A, cg16567056 at PLCB2, cg11024682 at SREBF1, cg08857797 at VPS25 and cg06500161 at ABCG1, three of which were replicated in Black adults at the epigenome-wide threshold and all of which had directionally consistent effects. We observed a modest increase in type 2 diabetes variance explained by the significantly associated CpG sites over and above traditional type 2 diabetes risk factors and fasting glucose (26.2% vs 30.5% in Black adults; 36.9% vs 39.4% in White adults). At the Šidák-corrected significance threshold of 5%, our differentially methylated region (DMR) analyses revealed several clusters of significant CpG sites, including a DMR consisting of a previously discovered CpG site at ADCY7 (pBlack=1.8 × 10-4, pWhite=3.6 × 10-3, pAll=1.6 × 10-9) and a DMR consisting of the promoter region of TP63 (pBlack=7.4 × 10-4, pWhite=3.9 × 10-3, pAll=1.4 × 10-5), which were differentially methylated across all racial and ethnic groups.

CONCLUSIONS/INTERPRETATION

This study illustrates improved discovery of CpG sites and regions by leveraging both individual CpG site analysis and DMR analyses in an unexplored population. Our findings include genes linked to diabetes in experimental studies (e.g. GPX6, JPH3 and TP63). The JPH3 and GPX6 sites were likely associated with incident type 2 diabetes independently of BMI. All the CpG sites except that at JPH3 were likely consequences of elevated glucose. Replication in African-descent individuals of CpG sites previously discovered mostly in individuals of European descent indicates that some of these methylation-type 2 diabetes associations are robust across racial and ethnic groups. This study is a first step towards understanding the influence of methylation on the incidence of type 2 diabetes and its disparity in two major racial and ethnic groups in the USA. It paves the way for future studies to investigate causal relationships between type 2 diabetes and the CpG sites and potentially elucidate molecular targets for intervention.

Txnip promotes autophagic apoptosis in diabetic cardiomyopathy by upregulating FoxO1 and its acetylation

Autophagy dysfunction and apoptosis exacerbate the risk of heart failure in patients with diabetic cardiomyopathy (DCM). However, the interactions between autophagy and apoptosis in DCM and their underlying mechanisms remain poorly understood. This study induced type 1 DCM in C57BL/6 mice via streptozotocin injection and exposed H9C2 cells to high glucose to investigate these mechanisms. The study revealed a significant elevation in autophagic vesicles and compromised autophagic flux, accompanied by pronounced myocardial cell apoptosis in the myocardium of diabetic mice. Long-term exposure to high glucose in H9C2 cells led to enhanced autophagosome formation and impaired autophagic flux, while inhibition of autophagy with 3-MA reduced cell apoptosis. Additionally, we observed an increase in Txnip expression in the myocardium of diabetic mice and in high glucose-treated H9C2 cells, which regulates autophagic apoptosis in high glucose-treated H9C2 cells. Furthermore, Txnip regulates autophagic apoptosis through the modulation of forkhead box-1 (FoxO1) expression and acetylation. Prolonged high glucose exposure resulted in increased levels of phosphorylated sirtuin 1 (SIRT1) and reduced SIRT1/FoxO1 interaction, changes that were ameliorated by Txnip knockdown. Txnip overexpression elevated FoxO1 levels, which could be suppressed by NAC and GSH. These findings revealed that Txnip mediates autophagic apoptosis in DCM by upregulating FoxO1 via ROS and enhancing FoxO1 acetylation through the suppression of SIRT1 activity. The discovery of this new mechanism provides new perspectives and potential therapeutic targets for understanding and treating DCM.

A comprehensive lifestyle index and its associations with DNA methylation and type 2 diabetes among Ghanaian adults: the rodam study

BACKGROUND

A series of modifiable lifestyle factors, such as diet quality, physical activity, alcohol intake, and smoking, may drive the rising burden of type 2 diabetes (T2DM) among sub-Saharan Africans globally. It is unclear whether epigenetic changes play a mediatory role in the associations between these lifestyle factors and T2DM. We assessed the associations between a comprehensive lifestyle index, DNA methylation and T2DM among Ghanaian adults.

METHODS

We used whole-blood Illumina 450 k DNA methylation data from 713 Ghanaians from the Research on Obesity and Diabetes among African Migrants (RODAM) study. We constructed a comprehensive lifestyle index based on established cut-offs for diet quality, physical activity, alcohol intake, and smoking status. In the T2DM-free discovery cohort (n = 457), linear models were fitted to identify differentially methylated positions (DMPs) and differentially methylated regions (DMRs) associated with the lifestyle index after adjustment for age, sex, body mass index (BMI), and technical covariates. Associations between the identified DMPs and the primary outcome (T2DM), as well as secondary outcomes (fasting blood glucose (FBG) and HbA1c), were determined via logistic and linear regression models, respectively.

RESULTS

In the present study population (mean age: 52 ± 10 years; male: 42.6%), the comprehensive lifestyle index showed a significant association with one DMP annotated to an intergenic region on chromosome 7 (false discovery rate (FDR) = 0.024). Others were annotated to ADCY7, SMARCE1, AHRR, LOXL2, and PTBP1 genes. One DMR was identified and annotated to the GFPT2 gene (familywise error rate (FWER) from bumphunter bootstrap = 0.036). None of the DMPs showed significant associations with T2DM; directions of effect were positive for the DMP in the AHRR and inverse for all the other DMPs. Higher methylation of the ADCY7 DMP was associated with higher FBG (p = 0.024); LOXL2 DMP was associated with lower FBG (p = 0.023) and HbA1c (p = 0.049); and PTBP1 DMP was associated with lower HbA1c (p = 0.002).

CONCLUSIONS

In this explorative epigenome-wide association study among Ghanaians, we identified one DMP and DMR associated with a comprehensive lifestyle index not previously associated with individual lifestyle factors. Based on our findings, we infer that lifestyle factors in combination, affect DNA methylation, thereby influencing the risk of T2DM among Ghanaian adults living in different contexts.

NMR metabolomics-guided DNA methylation mortality predictors

BACKGROUND

1H-NMR metabolomics and DNA methylation in blood are widely known biomarkers predicting age-related physiological decline and mortality yet exert mutually independent mortality and frailty signals.

METHODS

Leveraging multi-omics data in four Dutch population studies (N = 5238, ∼40% of which male) we investigated whether the mortality signal captured by 1H-NMR metabolomics could guide the construction of DNA methylation-based mortality predictors.

FINDINGS

We trained DNA methylation-based surrogates for 64 metabolomic analytes and found that analytes marking inflammation, fluid balance, or HDL/VLDL metabolism could be accurately reconstructed using DNA-methylation assays. Interestingly, a previously reported multi-analyte score indicating mortality risk (MetaboHealth) could also be accurately reconstructed. Sixteen of our derived surrogates, including the MetaboHealth surrogate, showed significant associations with mortality, independent of relevant covariates.

INTERPRETATION

The addition of our metabolic analyte-derived surrogates to the well-established epigenetic clock GrimAge demonstrates that our surrogates potentially represent valuable mortality signal.

FUNDING

BBMRI-NL, X-omics, VOILA, Medical Delta, NWO, ERC.

DNA methylation-estimated phenotypes, telomere length and risk of ischemic stroke: epigenetic age acceleration of screening and a Mendelian randomization study

BACKGROUND

Aging is a complex biological process that may be accelerated in certain pathological conditions. DNA methylation age (DNAmAge) has emerged as a biomarker for biological age, which can differ from chronological age. This research peels back the layers of the relationship between fast-forward aging and ischemic stroke, poking and prodding the potential two-way causal influences between stroke and biological aging indicators.

METHODS

We analyzed a cohort of ischemic stroke patients, comparing DNAmAge with chronological age to measure age acceleration. We assessed variations in age acceleration among stroke subtypes and between sexes. Using Mendelian randomization, we examined the causal links between stroke, aging biomarkers like telomere length, and age acceleration's effect on stroke risk.

RESULTS

Our investigation reveals a pronounced association between ischemic stroke and age acceleration, most notably in patients with cardioembolic strokes, who exhibited a striking median difference of 9 years between DNAmAge and chronological age. Furthermore, age acceleration differed significantly across stroke subtypes and was higher in women than in men. In terms of causality, MR analysis indicated a modest negative effect of stroke on telomere length, but no causal effect of age phenotypes on stroke or its subtypes. However, some indication of a potential causal effect of ischemic stroke on PhenoAge acceleration was observed.

CONCLUSION

The study provides insight into the relationship between DNAmAge and ischemic stroke, particularly cardioembolic stroke, and suggests possible gender differences. These insights carry profound clinical significance and set stage for future investigations into the entwined pathways of stroke and accelerated aging.

Visit to visit transition in TXNIP gene methylation and the risk of type 2 diabetes mellitus: a nested case-control study

Our study aimed to investigate the association between the transition of the TXNIP gene methylation level and the risk of incident type 2 diabetes mellitus (T2DM). This study included 263 incident cases of T2DM and 263 matched non-T2DM participants. According to the methylation levels of five loci (CpG1-5; chr1:145441102-145442001) on the TXNIP gene, the participants were classified into four transition groups: maintained low, low to high, high to low, and maintained high methylation levels. Compared with individuals whose methylation level of CpG2-5 at the TXNIP gene was maintained low, individuals with maintained high methylation levels showed a 61-87% reduction in T2DM risk (66% for CpG2 [OR: 0.34, 95% CI: 0.14, 0.80]; 77% for CpG3 [OR: 0.23, 95% CI: 0.07, 0.78]; 87% for CpG4 [OR: 0.13, 95% CI: 0.03, 0.56]; and 61% for CpG5 [OR: 0.39, 95% CI: 0.16, 0.92]). Maintained high methylation levels of four loci of the TXNIP gene are associated with a reduction of T2DM incident risk in the current study. Our study suggests that preserving hypermethylation levels of the TXNIP gene may hold promise as a potential preventive measure against the onset of T2DM.

Association between DNA methylation levels of thioredoxin-interacting protein (TXNIP) and changes in glycemic traits: a longitudinal population-based study

Thioredoxin-interacting protein (TXNIP) plays an important role in glucose metabolism, and its expression is regulated by DNA methylation (DNAm). Although the association between TXNIP DNAm and type 2 diabetes mellitus has been demonstrated in studies with a cross-sectional design, prospective studies are needed. We therefore examined the association between TXNIP DNAm levels and longitudinal changes in glycemic traits by conducting a longitudinal study involving 169 subjects who underwent two health checkups in 2015 and 2019. We used a pyrosequencing assay to determine TXNIP DNAm levels in leukocytes (cg19693031). Logistic regression analyses were performed to assess the associations between dichotomized TXNIP DNAm levels and marked increases in glycemic traits. At four years, the TXNIP DNA hypomethylation group had a higher percentage of changes in fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) compared to those in the hypermethylation group. The adjusted odds ratios for FPG and HbA1c levels were significantly higher in the TXNIP DNA hypomethylation group than in the hypermethylation group. We found that TXNIP DNA hypomethylation at baseline was associated with a marked increase in glycemic traits. Leukocyte TXNIP DNAm status could potentially be used as an early biomarker for impaired glucose homeostasis.

DNA methylation and stroke prognosis: an epigenome-wide association study

BACKGROUND AND AIMS

Stroke is the leading cause of adult-onset disability. Although clinical factors influence stroke outcome, there is a significant variability among individuals that may be attributed to genetics and epigenetics, including DNA methylation (DNAm). We aimed to study the association between DNAm and stroke prognosis.

METHODS AND RESULTS

To that aim, we conducted a two-phase study (discovery-replication and meta-analysis) in Caucasian patients with ischemic stroke from two independent centers (BasicMar [discovery, N = 316] and St. Pau [replication, N = 92]). Functional outcome was assessed using the modified Rankin Scale (mRS) at three months after stroke, being poor outcome defined as mRS > 2. DNAm was determined using the 450K and EPIC BeadChips in whole-blood samples collected within the first 24 h. We searched for differentially methylated positions (DMPs) in 370,344 CpGs, and candidates below p-value < 10-5 were subsequently tested in the replication cohort. We then meta-analyzed DMP results from both cohorts and used them to identify differentially methylated regions (DMRs). After doing the epigenome-wide association study, we found 29 DMPs at p-value < 10-5 and one of them was replicated: cg24391982, annotated to thrombospondin-2 (THBS2) gene (p-valuediscovery = 1.54·10-6; p-valuereplication = 9.17·10-4; p-valuemeta-analysis = 6.39·10-9). Besides, four DMRs were identified in patients with poor outcome annotated to zinc finger protein 57 homolog (ZFP57), Arachidonate 12-Lipoxygenase 12S Type (ALOX12), ABI Family Member 3 (ABI3) and Allantoicase (ALLC) genes (p-value < 1·10-9 in all cases).

DISCUSSION

Patients with poor outcome showed a DMP at THBS2 and four DMRs annotated to ZFP57, ALOX12, ABI3 and ALLC genes. This suggests an association between stroke outcome and DNAm, which may help identify new stroke recovery mechanisms.

Serum carotenoid levels are positively associated with DNA methylation of thioredoxin-interacting protein

Background: Carotenoids have been reported to exert protective effects against age-related diseases via changes in DNA methylation. Although lower thioredoxin-interacting protein (TXNIP) DNA methylation is associated with age-related diseases, only a few studies have investigated the factors influencing TXNIP DNA methylation. Carotenoids may be a factor linking TXNIP to specific pathophysiological functions. The aim of this study was to examine whether serum carotenoid levels are associated with TXNIP DNA methylation levels. Methods: We conducted a cross-sectional study using 376 health examination participants (169 men). DNA methylation levels were determined using a pyrosequencing assay. Serum carotenoid levels were determined by high-performance liquid chromatography. Multivariable regression analyses were performed to examine the associations between TXNIP DNA methylation levels and serum carotenoid levels with adjustment for age, BMI, HbA1c, CRP, smoking habits, alcohol consumption, exercise habits, and percentage of neutrophils. Results: Multiple linear regression analyses showed that TXNIP DNA methylation levels were positively associated with serum levels of zeaxanthin/lutein (β [95%CI]: 1.935 [0.184, 3.685]), β-cryptoxanthin (1.447 [0.324, 2.570]), α-carotene (1.061 [0.044, 2.077]), β-carotene (1.272 [0.319, 2.226]), total carotenes (1.255 [0.040, 2.469]), total xanthophylls (2.133 [0.315, 3.951]), provitamin A (1.460 [0.402, 2.519]), and total carotenoids (1.972 [0.261, 3.683]) in men (all p<0.05). Of these, provitamin A showed the stronger association (standardized β=0.216). No significant association of TXNIP DNA methylation and serum carotenoid was observed in women. Conclusions: The findings of this study suggest that carotenoid intake may protect against age-related diseases by altering TXNIP DNA methylation status in men.

DNA methylation and type 2 diabetes: a systematic review

OBJECTIVE

DNA methylation influences gene expression and function in the pathophysiology of type 2 diabetes mellitus (T2DM). Mapping of T2DM-associated DNA methylation could aid early detection and/or therapeutic treatment options for diabetics.

DESIGN

A systematic literature search for associations between T2DM and DNA methylation was performed. Prospero registration ID: CRD42020140436.

METHODS

PubMed and ScienceDirect databases were searched (till October 19, 2023). Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and New Castle Ottawa scale were used for reporting the selection and quality of the studies, respectively.

RESULT

Thirty-two articles were selected. Four of 130 differentially methylated genes in blood, adipose, liver or pancreatic islets (TXNIP, ABCG1, PPARGC1A, PTPRN2) were reported in > 1 study. TXNIP was hypomethylated in diabetic blood across ethnicities. Gene enrichment analysis of the differentially methylated genes highlighted relevant disease pathways (T2DM, type 1 diabetes and adipocytokine signaling). Three prospective studies reported association of methylation in IGFBP2, MSI2, FTO, TXNIP, SREBF1, PHOSPHO1, SOCS3 and ABCG1 in blood at baseline with incident T2DM/hyperglycemia. Sex-specific differential methylation was reported only for HOOK2 in visceral adipose tissue (female diabetics: hypermethylated, male diabetics: hypomethylated). Gene expression was inversely associated with methylation status in 8 studies, in genes including ABCG1 (blood), S100A4 (adipose tissue), PER2 (pancreatic islets), PDGFA (liver) and PPARGC1A (skeletal muscle).

CONCLUSION

This review summarizes available evidence for using DNA methylation patterns to unravel T2DM pathophysiology. Further validation studies in diverse populations will set the stage for utilizing this knowledge for identifying early diagnostic markers and novel druggable pathways.

DNA methylation signatures of youth-onset type 2 diabetes and exposure to maternal diabetes

OBJECTIVE

Youth-onset type 2 diabetes (T2D) is physiologically distinct from adult-onset, but it is not clear how the two diseases differ at a molecular level. In utero exposure to maternal type 2 diabetes (T2D) is known to be a specific risk factor for youth-onset T2D. DNA methylation (DNAm) changes associated with T2D but which differ between youth- and adult-onset might delineate the impacts of T2D development at different ages and could also determine the contribution of exposure to in utero diabetes.

METHODS

We performed an epigenome-wide analysis of DNAm on whole blood from 218 youth with T2D and 77 normoglycemic controls from the iCARE (improving renal Complications in Adolescents with type 2 diabetes through REsearch) cohort. Associations were tested using multiple linear regression models while adjusting for maternal diabetes, sex, age, BMI, smoking status, second-hand smoking exposure, cell-type proportions and genetic ancestry.

RESULTS

We identified 3830 differentially methylated sites associated with youth T2D onset, of which 3794 were moderately (adjusted p-value < 0.05 and effect size estimate > 0.01) associated and 36 were strongly (adjusted p-value < 0.05 and effect size estimate > 0.05) associated. A total of 3725 of these sites were not previously reported in the EWAS Atlas as associated with T2D, adult obesity or youth obesity. Moreover, three CpGs associated with youth-onset T2D in the PFKFB3 gene were also associated with maternal T2D exposure (FDR < 0.05 and effect size > 0.01). This is the first study to link PFKFB3 and T2D in youth.

CONCLUSION

Our findings support that T2D in youth has different impacts on DNAm than adult-onset, and suggests that changes in DNAm could provide an important link between in utero exposure to maternal diabetes and the onset of T2D.

Epigenomic insights into common human disease pathology

The epigenome-the chemical modifications and chromatin-related packaging of the genome-enables the same genetic template to be activated or repressed in different cellular settings. This multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan. The causal role of the epigenome in human pathology, beyond imprinting disorders and specific tumour suppressor genes, was further brought into the spotlight by large-scale sequencing projects identifying that mutations in epigenomic machinery genes could be critical drivers in both cancer and developmental disorders. Abrogation of this cellular mechanism is providing new molecular insights into pathogenesis. However, deciphering the full breadth and implications of these epigenomic changes remains challenging. Knowledge is accruing regarding disease mechanisms and clinical biomarkers, through pathogenically relevant and surrogate tissue analyses, respectively. Advances include consortia generated cell-type specific reference epigenomes, high-throughput DNA methylome association studies, as well as insights into ageing-related diseases from biological 'clocks' constructed by machine learning algorithms. Also, 3rd-generation sequencing is beginning to disentangle the complexity of genetic and DNA modification haplotypes. Cell-free DNA methylation as a cancer biomarker has clear clinical utility and further potential to assess organ damage across many disorders. Finally, molecular understanding of disease aetiology brings with it the opportunity for exact therapeutic alteration of the epigenome through CRISPR-activation or inhibition.

Epigenome editing for targeted DNA (de)methylation: a new perspective in modulating gene expression

Traditionally, it has been believed that inheritance is driven as phenotypic variations resulting from changes in DNA sequence. However, this paradigm has been challenged and redefined in the contemporary era of epigenetics. The changes in DNA methylation, histone modification, non-coding RNA biogenesis, and chromatin remodeling play crucial roles in genomic functions and regulation of gene expression. More importantly, some of these changes are inherited to the next generations as a part of epigenetic memory and play significant roles in gene expression. The sum total of all changes in DNA bases, histone proteins, and ncRNA biogenesis constitutes the epigenome. Continuous progress in deciphering epigenetic regulations and the existence of heritable epigenetic/epiallelic variations associated with trait of interest enables to deploy epigenome editing tools to modulate gene expression. DNA methylation marks can be utilized in epigenome editing for the manipulation of gene expression. Initially, genome/epigenome editing technologies relied on zinc-finger protein or transcriptional activator-like effector protein. However, the discovery of clustered regulatory interspaced short palindromic repeats CRISPR)/deadCRISPR-associated protein 9 (dCas9) enabled epigenome editing to be more specific/efficient for targeted DNA (de)methylation. One of the major concerns has been the off-target effects, wherein epigenome editing may unintentionally modify gene/regulatory element which may cause unintended change/harmful effects. Moreover, epigenome editing of germline cell raises several ethical/safety issues. This review focuses on the recent developments in epigenome editing tools/techniques, technological limitations, and future perspectives of this emerging technology in therapeutics for human diseases as well as plant improvement to achieve sustainable developmental goals.

Identifying epigenetic aging moderators using the epigenetic pacemaker

Epigenetic clocks are DNA methylation-based chronological age prediction models that are commonly employed to study age-related biology. The difference between the predicted and observed age is often interpreted as a form of biological age acceleration, and many studies have measured the impact of environmental and disease-associated factors on epigenetic age. Most epigenetic clocks are fit using approaches that minimize the error between the predicted and observed chronological age, and as a result, they may not accurately model the impact of factors that moderate the relationship between the actual and epigenetic age. Here, we compare epigenetic clocks that are constructed using penalized regression methods to an evolutionary framework of epigenetic aging with the epigenetic pacemaker (EPM), which directly models DNA methylation as a function of a time-dependent epigenetic state. In simulations, we show that the value of the epigenetic state is impacted by factors such as age, sex, and cell-type composition. Next, in a dataset aggregated from previous studies, we show that the epigenetic state is also moderated by sex and the cell type. Finally, we demonstrate that the epigenetic state is also moderated by toxins in a study on polybrominated biphenyl exposure. Thus, we find that the pacemaker provides a robust framework for the study of factors that impact epigenetic age acceleration and that the effect of these factors may be obscured in traditional clocks based on linear regression models.

Epigenome-wide association study of incident type 2 diabetes in Black and White participants from the Atherosclerosis Risk in Communities Study

DNA methylation studies of incident type 2 diabetes in US populations are limited, and to our knowledge none included individuals of African descent living in the US. We performed an epigenome-wide association analysis of blood-based methylation levels at CpG sites with incident type 2 diabetes using Cox regression in 2,091 Black and 1,029 White individuals from the Atherosclerosis Risk in Communities study. At an epigenome-wide significance threshold of 10-7, we detected 7 novel diabetes-associated CpG sites in C1orf151 (cg05380846: HR= 0.89, p = 8.4 × 10-12), ZNF2 (cg01585592: HR= 0.88, p = 1.6 × 10-9), JPH3 (cg16696007: HR= 0.87, p = 7.8 × 10-9), GPX6 (cg02793507: HR= 0.85, p = 2.7 × 10-8 and cg00647063: HR= 1.20, p = 2.5 × 10-8), chr17q25 (cg16865890: HR= 0.8, p = 6.9 × 10-8), and chr11p15 (cg13738793: HR= 1.11, p = 7.7 × 10-8). The CpG sites at C1orf151, ZNF2, JPH3 and GPX6, were identified in Black adults, chr17q25 was identified in White adults, and chr11p15 was identified upon meta-analyzing the two groups. The CpG sites at JPH3 and GPX6 were likely associated with incident type 2 diabetes independent of BMI. All the CpG sites, except at JPH3, were likely consequences of elevated glucose at baseline. We additionally replicated known type 2 diabetes-associated CpG sites including cg19693031 at TXNIP, cg00574958 at CPT1A, cg16567056 at PLBC2, cg11024682 at SREBF1, cg08857797 at VPS25, and cg06500161 at ABCG1, 3 of which were replicated in Black adults at the epigenome-wide threshold. We observed modest increase in type 2 diabetes variance explained upon addition of the significantly associated CpG sites to a Cox model that included traditional type 2 diabetes risk factors and fasting glucose (increase from 26.2% to 30.5% in Black adults; increase from 36.9% to 39.4% in White adults). We examined if groups of proximal CpG sites were associated with incident type 2 diabetes using a gene-region specific and a gene-region agnostic differentially methylated region (DMR) analysis. Our DMR analyses revealed several clusters of significant CpG sites, including a DMR consisting of a previously discovered CpG site at ADCY7 and promoter regions of TP63 which were differentially methylated across all race groups. This study illustrates improved discovery of CpG sites/regions by leveraging both individual CpG site and DMR analyses in an unexplored population. Our findings include genes linked to diabetes in experimental studies (e.g., GPX6, JPH3, and TP63), and future gene-specific methylation studies could elucidate the link between genes, environment, and methylation in the pathogenesis of type 2 diabetes.

Epigenome-wide methylation study identified two novel CpGs associated with T2DM risk and a network of co-methylated CpGs capable of patient's classifications

Prevention of Type 2 diabetes mellitus (T2DM) pandemic needs markers that can precisely predict the disease risk in an individual. Alterations in DNA methylations due to exposure towards environmental risk factors are widely sought markers for T2DM risk prediction. To identify such individual DNA methylation signatures and their effect on disease risk, we performed an epigenome-wide association study (EWAS) in 844 Indian individuals of Indo-European origin. We identified and validated methylation alterations at two novel CpG sites in MIR1287 (cg01178710) and EDN2-SCMH1 (cg04673737) genes associated with T2DM risk at the epigenome-wide-significance-level (P < 1.2 × 10-7). Further, we also replicated the association of two known CpG sites in TXNIP, and CPT1A in the Indian population. With 535 EWAS significant CpGs (P < 1.2 × 10-7) identified in the discovery phase samples, we created a co-methylation network using weighted correlation network analysis and identified four modules among the CpGs. We observed that methylation of one of the module associates with T2DM risk factors (e.g. BMI, insulin and C-peptide) and can be used as markers to segregate T2DM patients with good glycemic control (e.g. low HbA1c) and dyslipidemia (low HDL and high TG) from the other patients. Additionally, an intronic SNP (rs6503650) in the JUP gene, a member of the same module, associated with methylation at all the 14 hub CpG sites of that module as methQTL. Our network-assisted EWAS is the first to systematically explore DNA methylation variations conferring risks to T2DM in Indians and use the identified risk CpG sites for patient segregation with different clinical outcomes. These findings can be useful for better stratification of patients to improve the clinical management and treatment effects.

Identification of key DNA methylation changes on fasting plasma glucose: a genome-wide DNA methylation analysis in Chinese monozygotic twins

BACKGROUND

Elevated fasting plasma glucose (FPG) levels can increase morbidity and mortality even when it is below the diagnostic threshold of type 2 diabetes mellitus (T2DM). We conducted a genome-wide DNA methylation analysis to detect DNA methylation (DNAm) variants potentially related to FPG in Chinese monozygotic twins.

METHODS

Genome-wide DNA methylation profiling in whole blood of twins was performed using Reduced Representation Bisulfite Sequencing (RRBS), yielding 551,447 raw CpGs. Association between DNAm of single CpG and FPG was tested using a generalized estimation equation. Differentially methylated regions (DMRs) were identified using comb-P approach. ICE FALCON method was utilized to perform the causal inference. Candidate CpGs were quantified and validated using Sequenom MassARRAY platform in a community population. Weighted gene co-expression network analysis (WGCNA) was conducted using gene expression data from twins.

RESULTS

The mean age of 52 twin pairs was 52 years (SD: 7). The relationship between DNAm of 142 CpGs and FPG reached the genome-wide significance level. Thirty-two DMRs within 24 genes were identified, including TLCD1, MRPS31P5, CASZ1, and CXADRP3. The causal relationship of top CpGs mapped to TLCD1, MZF1, PTPRN2, SLC6A18, ASTN2, IQCA1, GRIN1, and PDE2A genes with FPG were further identified using ICE FALCON method. Pathways potentially related to FPG were also identified, such as phospholipid-hydroperoxide glutathione peroxidase activity and mitogen-activated protein kinase p38 binding. Three CpGs mapped to SLC6A18 gene were validated in a community population, with a hypermethylated direction in diabetic patients. The expression levels of 18 genes (including SLC6A18 and TLCD1) were positively correlated with FPG levels.

CONCLUSIONS

We detect many DNAm variants that may be associated with FPG in whole blood, particularly the loci within SLC6A18 gene. Our findings provide important reference for the epigenetic regulation of elevated FPG levels and diabetes.

Investigating causality in the association between DNA methylation and type 2 diabetes using bidirectional two-sample Mendelian randomisation

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.

Genetic and epigenetic background of diabetic kidney disease

Diabetic kidney disease (DKD) is a severe diabetic complication that affects up to half of the individuals with diabetes. Elevated blood glucose levels are a key underlying cause of DKD, but DKD is a complex multifactorial disease, which takes years to develop. Family studies have shown that inherited factors also contribute to the risk of the disease. During the last decade, genome-wide association studies (GWASs) have emerged as a powerful tool to identify genetic risk factors for DKD. In recent years, the GWASs have acquired larger number of participants, leading to increased statistical power to detect more genetic risk factors. In addition, whole-exome and whole-genome sequencing studies are emerging, aiming to identify rare genetic risk factors for DKD, as well as epigenome-wide association studies, investigating DNA methylation in relation to DKD. This article aims to review the identified genetic and epigenetic risk factors for DKD.

DNA methylation patterns at birth predict health outcomes in young adults born very low birthweight

Background

Individuals born very low birthweight (VLBW) are at increased risk of impaired cardiovascular and respiratory function in adulthood. To identify markers to predict future risk for VLBW individuals, we analyzed DNA methylation at birth and at 28 years in the New Zealand (NZ) VLBW cohort (all infants born < 1500 g in NZ in 1986) compared with age-matched, normal birthweight controls. Associations between neonatal methylation and cardiac structure and function (echocardiography), vascular function and respiratory outcomes at age 28 years were documented.

Results

Genomic DNA from archived newborn heel-prick blood (n = 109 VLBW, 51 controls) and from peripheral blood at ~ 28 years (n = 215 VLBW, 96 controls) was analyzed on Illumina Infinium MethylationEPIC 850 K arrays. Following quality assurance and normalization, methylation levels were compared between VLBW cases and controls at both ages by linear regression, with genome-wide significance set to p < 0.05 adjusted for false discovery rate (FDR, Benjamini-Hochberg). In neonates, methylation at over 16,400 CpG methylation sites differed between VLBW cases and controls and the canonical pathway most enriched for these CpGs was Cardiac Hypertrophy Signaling (p = 3.44E⁻¹¹). The top 20 CpGs that differed most between VLBW cases and controls featured clusters in ARID3A, SPATA33, and PLCH1 and these 3 genes, along with MCF2L, TRBJ2-1 and SRC, led the list of 15,000 differentially methylated regions (DMRs) reaching FDR-adj significance. Fifteen of the 20 top CpGs in the neonate EWAS showed associations between methylation at birth and adult cardiovascular traits (particularly LnRHI). In 28-year-old adults, twelve CpGs differed between VLBW cases and controls at FDR-adjusted significance, including hypermethylation in EBF4 (four CpGs), CFI and UNC119B and hypomethylation at three CpGs in HIF3A and one in KCNQ1. DNA methylation GrimAge scores at 28 years were significantly greater in VLBW cases versus controls and weakly associated with cardiovascular traits. Four CpGs were identified where methylation differed between VLBW cases and controls in both neonates and adults, three reversing directions with age (two CpGs in EBF4, one in SNAI1 were hypomethylated in neonates, hypermethylated in adults). Of these, cg16426670 in EBF4 at birth showed associations with several cardiovascular traits in adults.

Conclusions

These findings suggest that methylation patterns in VLBW neonates may be informative about future adult cardiovascular and respiratory outcomes and have value in guiding early preventative care to improve adult health.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-023-01463-3.

TXNIP Exacerbates the Senescence and Aging-Related Dysfunction of β Cells by Inducing Cell Cycle Arrest Through p38-p16/p21-CDK-Rb Pathway

Aims: Thioredoxin-interacting protein (TXNIP) is a crucial molecular promoter of oxidative stress and has been identified to be associated with cellular senescence. It is an important mediator of β cell insulin secretion and has effects on β cell mass. However, its role in β cell senescence is unclear. The present study was designed to investigate the effects and mechanisms of TXNIP on the senescence and aging- and diet-related dysfunction of β cells. Methods: Human pancreatic paraffin tissues and serum samples from different ages were collected to detect TXNIP expression. TXNIP^-/- and C57BL/6J mice were fed either a normal chow diet (NCD) or a high-fat diet (HFD) until 5, 11, 14, or 20 months. The recapitulation experiment was conducted with TXNIP protein injection. MIN6 cells were transfected with LV-TXNIP and LV-siTXNIP. The biochemical indexes, ageing-related markers, cell cycle proteins, and pathways were examined both in vivo and in vitro. Results: TXNIP expression showed an age-related increase in β cells and serum samples from humans. TXNIP significantly impaired glucose metabolism and insulin secretion in an age-dependent manner. TXNIP aggravated age-related and obesity-induced structural failure, oxidative stress, decreased proliferation, increased apoptosis in β cells, and induced the cell cycle arrest. TXNIP interacted with p38 mitogen-activated protein kinase (p38MAPK) and modulated the p16/p21-CDK-Rb axis to accelerate β cell senescence. Innovation and Conclusions: The present study demonstrated that TXNIP may exacerbate pancreatic β cell senescence and age-related dysfunction by inducing cell cycle arrest through the p38-p16/p21-CDK-Rb pathway, in natural and pathological states. Antioxid. Redox Signal. 38, 480-495.

DNA methylation in peripheral blood leukocytes for the association with glucose metabolism and invasive breast cancer

BACKGROUND

Insulin resistance (IR) is a well-established factor for breast cancer (BC) risk in postmenopausal women, but the interrelated molecular pathways on the methylome are not explicitly described. We conducted a population-level epigenome-wide association (EWA) study for DNA methylation (DNAm) probes that are associated with IR and prospectively correlated with BC development, both overall and in BC subtypes among postmenopausal women.

METHODS

We used data from Women's Health Initiative (WHI) ancillary studies for our EWA analyses and evaluated the associations of site-specific DNAm across the genome with IR phenotypes by multiple regressions adjusting for age and leukocyte heterogeneities. For our analysis of the top 20 IR-CpGs with BC risk, we used the WHI and the Cancer Genomic Atlas (TCGA), using multiple Cox proportional hazards and logit regressions, respectively, accounting for age, diabetes, obesity, leukocyte heterogeneities, and tumor purity (for TCGA). We further conducted a Gene Set Enrichment Analysis.

RESULTS

We detected several EWA-CpGs in TXNIP, CPT1A, PHGDH, and ABCG1. In particular, cg19693031 in TXNIP was replicated in all IR phenotypes, measured by fasting levels of glucose, insulin, and homeostatic model assessment-IR. Of those replicated IR-genes, 3 genes (CPT1A, PHGDH, and ABCG1) were further correlated with BC risk; and 1 individual CpG (cg01676795 in POR) was commonly detected across the 2 cohorts.

CONCLUSIONS

Our study contributes to better understanding of the interconnected molecular pathways on the methylome between IR and BC carcinogenesis and suggests potential use of DNAm markers in the peripheral blood cells as preventive targets to detect an at-risk group for IR and BC in postmenopausal women.

Machine Learning Approximations to Predict Epigenetic Age Acceleration in Stroke Patients

Age acceleration (Age-A) is a useful tool that is able to predict a broad range of health outcomes. It is necessary to determine DNA methylation levels to estimate it, and it is known that Age-A is influenced by environmental, lifestyle, and vascular risk factors (VRF). The aim of this study is to estimate the contribution of these easily measurable factors to Age-A in patients with cerebrovascular disease (CVD), using different machine learning (ML) approximations, and try to find a more accessible model able to predict Age-A. We studied a CVD cohort of 952 patients with information about VRF, lifestyle habits, and target organ damage. We estimated Age-A using Hannum's epigenetic clock, and trained six different models to predict Age-A: a conventional linear regression model, four ML models (elastic net regression (EN), K-Nearest neighbors, random forest, and support vector machine models), and one deep learning approximation (multilayer perceptron (MLP) model). The best-performing models were EN and MLP; although, the predictive capability was modest (R² 0.358 and 0.378, respectively). In conclusion, our results support the influence of these factors on Age-A; although, they were not enough to explain most of its variability.

Epigenome-wide association studies of meat traits in Chinese Yorkshire pigs highlights several DNA methylation loci and genes

In this study, we aimed to identified CpG sites at which DNA methylation levels are associated with meat quality traits in 140 Yorkshire pigs, including pH at 45 min (pH_45min), pH at 24 h (pH_24h), drip loss (DL), meat redness value (a*), yellowness (b*) and lightness (L*). Genome-wide methylation levels were measured in muscular tissue using reduced representation bisulfite sequencing (RRBS). Associations between DNA methylation levels and meat quality traits were examined using linear mixed-effect models that were adjusted for gender, year, month and body weight. A Bonferroni-corrected p-value lower than 7.79 × 10 - 8 was considered statistically significant threshold. Eight CpG sites were associated with DL, including CpG sites annotated to RBM4 gene (cpg301054, cpg301055, cpg301058, cpg301059, cpg301066, cpg301072 and cpg301073) and NCAM1 gene (cpg1802985). Two CpG sites were associated with b*, including RNFT1 and MED13 (cpg2272837) and TRIM37 gene (cpg2270611). Five CpG sites were associated with L*, including GSDMA and LRRC3C gene (cpg2252750) and ENSSSCG00000043539 and IRX1 gene (cpg2820178, cpg2820179, cpg2820181 and cpg2820182). No significant associations were observed with pH_45min, pH_24h or a*. We reported associations of meat quality traits with DNA methylation and identified some candidate genes associated with these traits, such as NCAM1, MED13 and TRIM37 gene. These results provide new insight into the epigenetic molecular mechanisms of meat quality traits in pigs.

TXNIP DNA methylation is associated with glycemic control over 28 years in type 1 diabetes: findings from the Pittsburgh Epidemiology of Diabetes Complications (EDC) study

INTRODUCTION

DNA methylation (DNAme) has been cross-sectionally associated with type 2 diabetes and hemoglobin A1c (HbA1c) in the general population. However, longitudinal data and data in type 1 diabetes are currently very limited. Thus, we performed an epigenome-wide association study (EWAS) in an observational type 1 diabetes cohort to identify loci with DNAme associated with concurrent and future HbA1cs, as well as other clinical risk factors, over 28 years.

RESEARCH DESIGN AND METHODS

Whole blood DNAme in 683 597 CpGs was analyzed in the Pittsburgh Epidemiology of Diabetes Complications study of childhood onset (<17 years) type 1 diabetes (n=411). An EWAS of DNAme beta values and concurrent HbA1c was performed using linear models adjusted for diabetes duration, sex, pack years of smoking, estimated cell type composition variables, and technical/batch covariates. A longitudinal EWAS of subsequent repeated HbA1c measures was performed using mixed models. We further identified methylation quantitative trait loci (meQTLs) for significant CpGs and conducted a Mendelian randomization.

RESULTS

DNAme at cg19693031 (Chr 1, Thioredoxin-Interacting Protein (TXNIP)) and cg21534330 (Chr 17, Casein Kinase 1 Isoform Delta) was significantly inversely associated with concurrent HbA1c. In longitudinal analyses, hypomethylation of cg19693031 was associated with consistently higher HbA1c over 28 years, and with higher triglycerides, pulse rate, and albumin:creatinine ratio (ACR) independently of HbA1c. We further identified 34 meQTLs in SLC2A1/SLC2A1-AS1 significantly associated with cg19693031 DNAme.

CONCLUSIONS

Our results extend prior findings that TXNIP hypomethylation relates to worse glycemic control in type 1 diabetes by demonstrating the association persists over the long term. Additionally, the associations with triglycerides, pulse rate, and ACR suggest TXNIP DNAme could play a role in vascular damage independent of HbA1c. These findings strengthen potential for interventions targeting TXNIP to improve glycemic control in type 1 diabetes through its role in SLC2A1/glucose transporter 1-mediated glucose regulation.

Epigenetic Clock Explains White Matter Hyperintensity Burden Irrespective of Chronological Age

In this manuscript we studied the relationship between WMH and biological age (B-age) in patients with acute stroke. We included in this study 247 patients with acute stroke recruited at Hospital del Mar having both epigenetic (DNA methylation) and magnetic resonance imaging data. WMH were measured using a semi-automated method. B-age was calculated using two widely used methods: the Hannum and Horvath formulas. We used multiple linear regression models to interrogate the role of B-age on WMH volume after adjusting for chronological age (C-age) and other covariables. Average C-age of the sample was 68.4 (±11.8) and we observed a relatively high median WMH volume (median = 8.8 cm³, Q1-Q3 = 4.05-18.8). After adjusting for potential confounders, we observed a significant effect of B-age_Hannum on WMH volume (β_Hannum = 0.023, p-value = 0.029) independently of C-age, which remained significant (β_C-age = 0.021, p-value = 0.036). Finally, we performed a mediation analysis, which allowed us to discover that 42.7% of the effect of C-age on WMH is mediated by B-age_Hannum. On the other hand, B-age_Hoarvath showed no significant associations with WMH after being adjusted for C-age. In conclusion, we show for the first time that biological age, measured through DNA methylation, contributes substantially to explain WMH volumetric burden irrespective of chronological age.

DNA methylation trajectories and accelerated epigenetic aging in incident type 2 diabetes

DNA methylation (DNAm) patterns across the genome changes during aging and development of complex diseases including type 2 diabetes (T2D). Our study aimed to estimate DNAm trajectories of CpG sites associated with T2D, epigenetic age (DNAmAge), and age acceleration based on four epigenetic clocks (GrimAge, Hannum, Horvath, phenoAge) in the period 10 years prior to and up to T2D onset. In this nested case-control study within Doetinchem Cohort Study, we included 132 incident T2D cases and 132 age- and sex-matched controls. DNAm was measured in blood using the Illumina Infinium Methylation EPIC array. From 107 CpG sites associated with T2D, 10 CpG sites (9%) showed different slopes of DNAm trajectories over time (p < 0.05) and an additional 8 CpG sites (8%) showed significant differences in DNAm levels (at least 1%, p-value per time point < 0.05) at all three time points with nearly parallel trajectories between incident T2D cases and controls. In controls, age acceleration levels were negative (slower epigenetic aging), while in incident T2D cases, levels were positive, suggesting accelerated aging in the case group. We showed that DNAm levels at specific CpG sites, up to 10 years before T2D onset, are different between incident T2D cases and healthy controls and distinct patterns of clinical traits over time may have an impact on those DNAm profiles. Up to 10 years before T2D diagnosis, cases manifested accelerated epigenetic aging. Markers of biological aging including age acceleration estimates based on Horvath need further investigation to assess their utility for predicting age-related diseases including T2D.

Altered methylation pattern in EXOC4 is associated with stroke outcome: an epigenome-wide association study

BACKGROUND AND PURPOSE

The neurological course after stroke is highly variable and is determined by demographic, clinical and genetic factors. However, other heritable factors such as epigenetic DNA methylation could play a role in neurological changes after stroke.

METHODS

We performed a three-stage epigenome-wide association study to evaluate DNA methylation associated with the difference between the National Institutes of Health Stroke Scale (NIHSS) at baseline and at discharge (ΔNIHSS) in ischaemic stroke patients. DNA methylation data in the Discovery (n = 643) and Replication (n = 62) Cohorts were interrogated with the 450 K and EPIC BeadChip. Nominal CpG sites from the Discovery (p value < 10-06) were also evaluated in a meta-analysis of the Discovery and Replication cohorts, using a random-fixed effect model. Metabolic pathway enrichment was calculated with methylGSA. We integrated the methylation data with 1305 plasma protein expression levels measured by SOMAscan in 46 subjects and measured RNA expression with RT-PCR in a subgroup of 13 subjects. Specific cell-type methylation was assessed using EpiDISH.

RESULTS

The meta-analysis revealed an epigenome-wide significant association in EXOC4 (p value = 8.4 × 10-08) and in MERTK (p value = 1.56 × 10-07). Only the methylation in EXOC4 was also associated in the Discovery and in the Replication Cohorts (p value = 1.14 × 10-06 and p value = 1.3 × 10-02, respectively). EXOC4 methylation negatively correlated with the long-term outcome (coefficient = - 4.91) and showed a tendency towards a decrease in EXOC4 expression (rho = - 0.469, p value = 0.091). Pathway enrichment from the meta-analysis revealed significant associations related to the endocytosis and deubiquitination processes. Seventy-nine plasma proteins were differentially expressed in association with EXOC4 methylation. Pathway analysis of these proteins showed an enrichment in natural killer (NK) cell activation. The cell-type methylation analysis in blood also revealed a differential methylation in NK cells.

CONCLUSIONS

DNA methylation of EXOC4 is associated with a worse neurological course after stroke. The results indicate a potential modulation of pathways involving endocytosis and NK cells regulation.

Novel Subgroups of Type 2 Diabetes Display Different Epigenetic Patterns That Associate With Future Diabetic Complications

OBJECTIVE

Type 2 diabetes (T2D) was recently reclassified into severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), and mild age-related diabetes (MARD), which have different risk of complications. We explored whether DNA methylation differs between these subgroups and whether subgroup-unique methylation risk scores (MRSs) predict diabetic complications.

RESEARCH DESIGN AND METHODS

Genome-wide DNA methylation was analyzed in blood from subjects with newly diagnosed T2D in discovery and replication cohorts. Subgroup-unique MRSs were built, including top subgroup-unique DNA methylation sites. Regression models examined whether MRSs associated with subgroups and future complications.

RESULTS

We found epigenetic differences between the T2D subgroups. Subgroup-unique MRSs were significantly different in those patients allocated to each respective subgroup compared with the combined group of all other subgroups. These associations were validated in an independent replication cohort, showing that subgroup-unique MRSs associate with individual subgroups (odds ratios 1.6-6.1 per 1-SD increase, P < 0.01). Subgroup-unique MRSs were also associated with future complications. Higher MOD-MRS was associated with lower risk of cardiovascular (hazard ratio [HR] 0.65, P = 0.001) and renal (HR 0.50, P < 0.001) disease, whereas higher SIRD-MRS and MARD-MRS were associated with an increased risk of these complications (HR 1.4-1.9 per 1-SD increase, P < 0.01). Of 95 methylation sites included in subgroup-unique MRSs, 39 were annotated to genes previously linked to diabetes-related traits, including TXNIP and ELOVL2. Methylation in the blood of 18 subgroup-unique sites mirrors epigenetic patterns in tissues relevant for T2D, muscle and adipose tissue.

CONCLUSIONS

We identified differential epigenetic patterns between T2D subgroups that associated with future diabetic complications. These data support a reclassification of diabetes and the need for precision medicine in T2D subgroups.

Epigenetics of type 2 diabetes mellitus and weight change - a tool for precision medicine?

Pioneering studies performed over the past few decades demonstrate links between epigenetics and type 2 diabetes mellitus (T2DM), the metabolic disorder with the most rapidly increasing prevalence in the world. Importantly, these studies identified epigenetic modifications, including altered DNA methylation, in pancreatic islets, adipose tissue, skeletal muscle and the liver from individuals with T2DM. As non-genetic factors that affect the risk of T2DM, such as obesity, unhealthy diet, physical inactivity, ageing and the intrauterine environment, have been associated with epigenetic modifications in healthy individuals, epigenetics probably also contributes to T2DM development. In addition, genetic factors associated with T2DM and obesity affect the epigenome in human tissues. Notably, causal mediation analyses found DNA methylation to be a potential mediator of genetic associations with metabolic traits and disease. In the past few years, translational studies have identified blood-based epigenetic markers that might be further developed and used for precision medicine to help patients with T2DM receive optimal therapy and to identify patients at risk of complications. This Review focuses on epigenetic mechanisms in the development of T2DM and the regulation of body weight in humans, with a special focus on precision medicine.

Endothelial thioredoxin interacting protein (TXNIP) modulates endothelium-dependent vasorelaxation in hyperglycemia

Endothelial dysfunction, hallmarked by an imbalance between vasoconstriction and vasorelaxation, is associated with diabetes. Thioredoxin Interacting protein (TXNIP), controlled by an exquisitely glucose sensitive gene, is increasingly recognized for its role in diabetes. However, the role of TXNIP in modulating diabetes-related endothelial dysfunction remains unclear. To elucidate the role of TXNIP, we generated two novel mouse strains; endothelial-specific TXNIP knockout (EKO) and a Tet-O inducible, endothelial-specific TXNIP overexpression (EKI). Hyperglycemia was induced by streptozotocin (STZ) treatment in floxed control (fl/fl) and EKO mice. Doxycycline (DOX) was given to EKI mice to induce endothelial TXNIP overexpression. The ablation of endothelial TXNIP improved glucose tolerance in EKO mice. Acetylcholine-induced, endothelium-dependent vasorelaxation was impaired in STZ-treated fl/fl mice while this STZ impaired vasorelaxation was attenuated in EKO mice. Hyperglycemia induction of NLRP3 and reductions in Akt and eNOS phosphorylation were also mitigated in EKO mice. Overexpression of endothelial TXNIP did not impair glucose tolerance in DOX-treated EKI mice, however induction of endothelial TXNIP led to impaired vasorelaxation in EKI mice. This was associated with increased NLRP3 and reduced Akt and eNOS activation. In conclusion, deletion of endothelial TXNIP is protective against and overexpression of endothelial TXNIP induces endothelial dysfunction; thus, endothelial TXNIP plays a critical role in modulating endothelial dysfunction.

Association of drinking behaviors with TXNIP DNA methylation levels in leukocytes among the general Japanese population

Background: Thioredoxin-interacting protein (TXNIP) controls the cellular redox balance by binding to and inhibiting the expression and function of thioredoxin. DNA methylation of the TXNIP gene is involved in the regulation of TXNIP mRNA expression. Changes in TXNIP DNA methylation levels are associated with the development of various diseases such as type 2 diabetes mellitus (T2DM). However, few studies have focused on the influence of lifestyle factors such as alcohol intake on TXNIP DNA methylation.Objectives: This research examines the association of drinking behaviors with TXNIP DNA methylation levels in the general Japanese population.Methods: We conducted a cross-sectional study of 404 subjects (176 males and 228 females) who were divided into non-, moderate and heavy drinkers based on self-reported drinking behaviors. TXNIP DNA methylation levels in leukocytes were determined using a pyrosequencing assay.Results: The mean TXNIP DNA methylation level in heavy drinkers (74.2%) was significantly lower than that in non- and moderate drinkers (non: 77.7%, p < .001; moderate: 76.6%, p = .011). Multivariable linear regression analysis showed that log-transformed values of daily (b = -1.34; p < .001) and cumulative (b = -1.06; p = .001) alcohol consumption were associated with decreased TXNIP DNA methylation levels.Conclusion: TXNIP DNA methylation levels in heavy drinkers was lower than in non- and- moderate drinkers. Decreased TXNIP DNA methylation level increases the expression of TXNIP and elevates the risk of developing of diseases such as T2DM. Therefore, decreasing alcohol use in heavy drinkers may lessen the likelihood of some alcohol-related illnesses moderated through TXNIP DNA methylation.

Epigenome-wide association study of incident type 2 diabetes: a meta-analysis of five prospective European cohorts

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.

METHODS

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).

RESULTS

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 × 10-7). 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 HbA1c) 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.

Additive and Interactive Genetically Contextual Effects of HbA1c on cg19693031 Methylation in Type 2 Diabetes

Type 2 diabetes mellitus (T2D) has a complex genetic and environmental architecture that underlies its development and clinical presentation. Despite the identification of well over a hundred genetic variants and CpG sites that associate with T2D, a robust biosignature that could be used to prevent or forestall clinical disease has not been developed. Based on the premise that underlying genetic variation influences DNA methylation (DNAm) independently of or in combination with environmental exposures, we assessed the ability of local and distal gene x methylation (GxMeth) interactive effects to improve cg19693031 models for predicting T2D status in an African American cohort. Using genome-wide genetic data from 506 subjects, we identified a total of 1476 GxMeth terms associated with HbA1c values. The GxMeth SNPs map to biological pathways associated with the development and complications of T2D, with genetically contextual differences in methylation observed only in diabetic subjects for two GxMeth SNPs (rs2390998 AG vs. GG, p = 4.63 × 10−11, Δβ = 13%, effect size = 0.16 [95% CI = 0.05, 0.32]; rs1074390 AA vs. GG, p = 3.93 × 10−4, Δβ = 9%, effect size = 0.38 [95% CI = 0.12, 0.56]. Using a repeated stratified k-fold cross-validation approach, a series of balanced random forest classifiers with random under-sampling were built to evaluate the addition of GxMeth terms to cg19693031 models to discriminate between normoglycemic controls versus T2D subjects. The results were compared to those obtained from models incorporating only the covariates (age, sex and BMI) and the addition of cg19693031. We found a post-pruned classifier incorporating 10 GxMeth SNPs and cg19693031 adjusted for covariates predicted the T2D status, with the AUC, sensitivity, specificity and precision of the positive target class being 0.76, 0.81, 0.70 and 0.63, respectively. Comparatively, the AUC, sensitivity, specificity and precision using the covariates and cg19693031 were only 0.71, 0.74, 0.67 and 0.59, respectively. Collectively, we demonstrate correcting for genetic confounding of cg19693031 improves its ability to detect type 2 diabetes. We conclude that an integrated genetic–epigenetic approach could inform personalized medicine programming for more effective prevention and treatment of T2D.

Epigenetic changes associated with hyperglycaemia exposure in the longitudinal D.E.S.I.R. cohort

AIM

- Understanding DNA methylation dynamics associated with progressive hyperglycaemia exposure could provide early diagnostic biomarkers and an avenue for delaying type 2 diabetes mellitus (T2DM). We aimed to identify DNA methylation changes during a 6-year period associated with early hyperglycaemia exposure using the longitudinal D.E.S.I.R.

COHORT

METHODS

- We selected individuals with progressive hyperglycaemia exposure based on T2DM diagnostic criteria: 27 with long-term exposure, 34 with short-term exposure and 34 normoglycaemic controls. DNA from blood at inclusion and at the 6-year visit was subjected to methylation analysis using 850K methylation-EPIC arrays. A linear mixed model was used to perform an epigenome-wide association study (EWAS) and identify methylated changes associated with hyperglycaemia exposure during a 6-year time-period.

RESULTS

- We did not identify differentially methylated sites that reached false discovery rate (FDR)-significance in our cohort. Based on EWAS, we focused our analysis on methylation sites that had a constant effect during the 6 years across the hyperglycaemia groups compared to controls and found the most statistically significant site was the reported cg19693031 probe (TXNIP). We also performed an EWAS with HbA1c, using the inclusion and the 6-year methylation data and did not identify any FDR-significant CpGs.

CONCLUSIONS

- Our study reveals that DNA methylation changes are not robustly associated with hyperglycaemia exposure or HbA1c during a short-term period, however, our top loci indicate potential interest and should be replicated in larger cohorts.

DNA methylation level of the gene encoding thioredoxin-interacting protein in peripheral blood cells is associated with metabolic syndrome in the Japanese general population

Metabolic syndrome (MetS) is cluster of metabolic diseases, including abdominal obesity, hyperglycemia, high blood pressure, and dyslipidemia, that directly escalate the risk of type 2 diabetes, heart disease, and stroke. Thioredoxin-interacting protein (TXNIP) is a binding protein for thioredoxin, a molecule that is a key inhibitor of cellular oxidation, and thus regulates the cellular redox state. Epigenetic alteration of the TXNIP-encoding locus has been associated with components of MetS. In the present study, we sought to determine whether the level of TXNIP methylation in blood is associated with MetS in the general Japanese population. DNA was extracted from the peripheral blood cells of 37 subjects with and 392 subjects without MetS. The level of TXNIP methylation at cg19693031 was assessed by the bisulfite-pyrosequencing method. We observed that TXNIP methylation levels were lower in MetS subjects (median 74.9%, range 71.7-78.4%) than in non-MetS subjects (median 77.7%, range 74.4-80.5%; p = 0.0024). Calculation of the confounding factor-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for hypomethylation revealed that subjects with MetS exhibited significantly higher ORs for hypomethylation than did those without MetS (OR, 2.92; 95% CI, 1.33-6.62; p = 0.009). Our findings indicated that lower levels of TXNIP methylation are associated with MetS in the general Japanese population. Altered levels of DNA methylation in TXNIP at cg19693031 might play an important role in the pathogenesis of MetS.

Epigenetics in Precision Nutrition

Precision nutrition is an emerging area of nutrition research, with primary focus on the individual variability in response to dietary and lifestyle factors, which are mainly determined by an individual’s intrinsic variations, such as those in genome, epigenome, and gut microbiome. The current research on precision nutrition is heavily focused on genome and gut microbiome, while epigenome (DNA methylation, non-coding RNAs, and histone modification) is largely neglected. The epigenome acts as the interface between the human genome and environmental stressors, including diets and lifestyle. Increasing evidence has suggested that epigenetic modifications, particularly DNA methylation, may determine the individual variability in metabolic health and response to dietary and lifestyle factors and, therefore, hold great promise in discovering novel markers for precision nutrition and potential targets for precision interventions. This review summarized recent studies on DNA methylation with obesity, diabetes, and cardiovascular disease, with more emphasis put in the relations of DNA methylation with nutrition and diet/lifestyle interventions. We also briefly reviewed other epigenetic events, such as non-coding RNAs, in relation to human health and nutrition, and discussed the potential role of epigenetics in the precision nutrition research.

Deconvolution of the epigenetic age discloses distinct inter-personal variability in epigenetic aging patterns

BACKGROUND

The epigenetic age can now be extrapolated from one of several epigenetic clocks, which are based on age-related changes in DNA methylation levels at specific multiple CpG sites. Accelerated aging, calculated from the discrepancy between the chronological age and the epigenetic age, has shown to predict morbidity and mortality rate. We assumed that deconvolution of epigenetic age to its components could shed light on the diversity of epigenetic, and by inference, on inter-individual variability in the causes of biological aging.

RESULTS

Using the Horvath original epigenetic clock, we identified several CpG sites linked to distinct genes that quantitatively explain much of the inter-personal variability in epigenetic aging, with CpG sites related to secretagogin and malin being the most variable. We show that equal epigenetic age in different subjects can result from variable contribution size of the same CpG sites to the total epigenetic age. In a healthy cohort, the most variable CpG sites are responsible for accelerated and decelerated epigenetic aging, relative to chronological age.

CONCLUSIONS

Of the 353 CpG sites that form the basis for the Horvath epigenetic age, we have found the CpG sites that are responsible for accelerated and decelerated epigenetic aging in healthy subjects. However, the relative contribution of each site to aging varies between individuals, leading to variable personal aging patterns. Our findings pave the way to form personalized aging cards allowing the identification of specific genes related to CpG sites, as aging markers, and perhaps treatment of these targets in order to hinder undesirable age drifting.

Interaction between a diabetes-related methylation site (TXNIP cg19693031) and variant (GLUT1 rs841853) on fasting blood glucose levels among non-diabetics

Background

Type 2 diabetes mellitus (T2DM) is caused by a combination of environmental, genetic, and epigenetic factors including, fasting blood glucose (FBG), genetic variant rs841853, and cg19693031 methylation. We evaluated the interaction between rs841853 and cg19693031 on the FBG levels of non-diabetic Taiwanese adults.

Methods

We used Taiwan Biobank (TWB) data collected between 2008 and 2016. The TWB data source contains information on basic demographics, personal lifestyles, medical history, methylation, and genotype. The study participants included 1300 people with DNA methylation data. The association of cg19693031 methylation (stratified into quartiles) with rs841853 and FBG was determined using multiple linear regression analysis. The beta-coefficients (β) and p-values were estimated.

Results

The mean ± standard deviation (SD) of FBG in rs841853-CC individuals (92.07 ± 7.78) did not differ significantly from that in the CA + AA individuals (91.62 ± 7.14). However, the cg19693031 methylation levels were significantly different in the two groups (0.7716 ± 0.05 in CC individuals and 0.7631 ± 0.05 in CA + AA individuals (p = 0.002). The cg19693031 methylation levels according to quartiles were β < 0.738592 (< Q1), 0.738592 ≤ 0.769992 (Q1–Q2), 0.769992 ≤ 0.800918 (Q2–Q3), and β ≥ 0.800918 (≥ Q3). FBG increased with decreasing cg19693031 methylation levels in a dose–response manner (p_trend = 0.005). The β-coefficient was − 0.0236 (p = 0.965) for Q2–Q3, 1.0317 (p = 0.058) for Q1–Q2, and 1.3336 (p = 0.019 for < Q1 compared to the reference quartile (≥ Q3). The genetic variant rs841853 was not significantly associated with FBG. However, its interaction with cg19693031 methylation was significant (p-value = 0.036). Based on stratification by rs841853 genotypes, only the CC group retained the inverse and dose–response association between FBG and cg19693031 methylation. The β (p-value) was 0.8082 (0.255) for Q2–Q3, 1.6930 (0.022) for Q1–Q2, and 2.2190 (0.004) for < Q1 compared to the reference quartile (≥ Q3). The p_trend was 0.002.

Conclusion

Summarily, methylation at cg19693031 was inversely associated with fasting blood glucose in a dose-dependent manner. The inverse association was more prominent in rs841853-CC individuals, suggesting that rs841853 could modulate the association between cg19693031 methylation and FBG. Our results suggest that genetic variants may be involved in epigenetic mechanisms associated with FBG, a hallmark of diabetes. Therefore, integrating genetic and epigenetic data may provide more insight into the early-onset of diabetes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03269-y.

Blood DNA methylation at TXNIP and glycemic changes in response to weight-loss diet interventions: the POUNDS lost trial

Background:

Methods:

Results:

Conclusions:

Data Analysis of DNA Methylation Epigenome-Wide Association Studies (EWAS): A Guide to the Principles of Best Practice

Array-based EWAS have become an increasingly popular technique to identify population epigenetic effects, particularly in humans. With the arrival of nonhuman species arrays, such as the mouse, this is likely to become an even more widely used technology. This chapter provides the less experienced researcher a guide to the analysis of data from the most widely used platform, the Illumina Infinium Methylation assay. This includes an overview of quality filtering, data normalization, analysis options, and techniques to improve the interpretation of results.

Circulating Nucleic Acid-Based Biomarkers of Type 2 Diabetes

Type 2 diabetes (T2D) is a deficiency in how the body regulates glucose. Uncontrolled T2D will result in chronic high blood sugar levels, eventually resulting in T2D complications. These complications, such as kidney, eye, and nerve damage, are even harder to treat. Identifying individuals at high risk of developing T2D and its complications is essential for early prevention and treatment. Numerous studies have been done to identify biomarkers for T2D diagnosis and prognosis. This review focuses on recent T2D biomarker studies based on circulating nucleic acids using different omics technologies: genomics, transcriptomics, and epigenomics. Omics studies have profiled biomarker candidates from blood, urine, and other non-invasive samples. Despite methodological differences, several candidate biomarkers were reported for the risk and diagnosis of T2D, the prognosis of T2D complications, and pharmacodynamics of T2D treatments. Future studies should be done to validate the findings in larger samples and blood-based biomarkers in non-invasive samples to support the realization of precision medicine for T2D.

Antidiabetic effects of quercetin and liraglutide combination through modulation of TXNIP/IRS-1/PI3K pathway

The study was designed to assess the possible augmented antidiabetic effects of combining quercetin and liraglutide in a type 1 diabetes model, with emphasis on the contribution of hepatic thioredoxin interacting protein (TXNIP)/insulin receptor substrate 1 (IRS-1)/phosphatidyl inositol-3 kinase (PI3K) pathway. The wound-healing effects were also examined. Diabetes was induced by a single i.p STZ injection (55 mg/kg). Diabetic rats were treated with either quercetin (100 mg/kg/day, orally) or liraglutide (0.3 mg/kg/twice daily, S.C.) or their combination. Drugs were also applied topically on the wound. Blood glucose levels, serum albumin, total protein, total cholesterol and triglycerides were measured. Histopathological examination of the liver, pancreas and skin tissues was performed using haematoxylin and eosin staining. The hepatic malondialdehyde level was measured spectrophotometrically. Hepatic TXNIP and PI3K levels were measured by enzyme-linked immunsorbent assay (ELISA). Tissue expression of IRS-1 and phospho-IRS-1 (Ser 616) was assessed by immunohistochemistry. Quercetin, liraglutide and their combination effectively decreased blood glucose levels, improved lipid profile, upregulated albumin and total protein serum levels and reduced hepatic oxidative stress with the combination being most effective. Moreover, the combination group showed enhanced wound-healing effects and almost normalized hepatic and pancreatic histopathology. Quercetin and/or liraglutide significantly decreased TXNIP levels and serine phosphorylation of IRS-1 and increased PI3K levels compared to the diabetic untreated group. Interestingly, only the combination therapy normalized hepatic IRS-1 expression. The combination of quercetin and liraglutide showed enhanced antidiabetic effects, possibly through lowering hepatic TXNIP levels, with the resultant up-regulation of the IRS-1/PI3K pathway.

Blood DNA methylation markers associated with type 2 diabetes, fasting glucose, and HbA1c levels: An epigenome-wide association study in 316 adult twin pairs

DNA methylation plays an important role in the development and etiology of type 2 diabetes; however, few epigenomic studies have been conducted on twins. Herein, a two-stage study was performed to explore the associations between DNA methylation and type 2 diabetes, fasting plasma glucose, and HbA1c. DNA methylation in 316 twin pairs from the Chinese National Twin Registry (CNTR) was measured using Illumina Infinium BeadChips. In the discovery sample, the results revealed that 63 CpG sites and 6 CpG sites were significantly associated with fasting plasma glucose and HbA1c, respectively. In the replication sample, cg19690313 in TXNIP was associated with both fasting plasma glucose (P = 1.23 × 10^-17, FDR < 0.001) and HbA1c (P = 2.29 × 10^-18, FDR < 0.001). Furthermore, cg04816311, cg08309687, and cg09249494 may provide new insight in the metabolic mechanism of HbA1c. Our study provides solid evidence that cg19690313 on TXNIP correlates with HbA1c and fasting plasma glucose levels.

Extrinsic and intrinsic factors influencing metabolic memory in type 2 diabetes

Direct and indirect influence of pathological conditions in Type 2 Diabetes (T2D) on vasculature manifests in micro and/or macro vascular complications that act as a major source of morbidity and mortality. Although preventive therapies exist to control hyperglycemia, diabetic subjects are always at risk to accrue vascular complications. One of the hypotheses explained is 'glycemic' or 'metabolic' memory, a process of permanent epigenetic change in different cell types whereby diabetes associated vascular complications continue despite glycemic control by antidiabetic drugs. Epigenetic mechanisms including DNA methylation possess a strong influence on the association between environment and gene expression, thus indicating its importance in the pathogenesis of a complex disease such as T2D. The vascular system is more prone to environmental influences and present high flexibility in response to physiological and pathological challenges. DNA methylation based epigenetic changes during metabolic memory are influenced by sustained hyperglycemia, inflammatory mediators, gut microbiome composition, lifestyle modifications and gene-nutrient interactions. Hence, understanding underlying mechanisms in manifesting vascular complications regulated by DNA methylation is of high clinical importance. The review provides an insight into various extrinsic and intrinsic factors influencing the regulation of DNA methyltransferases contributing to the pathogenesis of vascular complications during T2D.

Associations between an integrated component of maternal glycemic regulation in pregnancy and cord blood DNA methylation

Background: Previous studies suggest that fetal programming to hyperglycemia in pregnancy is due to modulation of DNA methylation (DNAm), but they have been limited in their maternal glycemic characterization. Methods: In the Gen3G study, we used a principal component analysis to integrate multiple glucose and insulin values measured during the second trimester oral glucose tolerance test. We investigated associations between principal components and cord blood DNAm levels in an epigenome-wide analysis among 430 mother-child pairs. Results: The first principal component was robustly associated with lower DNAm at cg26974062 (TXNIP; p = 9.9 × 10^-9) in cord blood. TXNIP is a well-known DNAm marker for type 2 diabetes in adults. Conclusion: We hypothesize that abnormal glucose metabolism in pregnancy may program dysregulation of TXNIP across the life course.

DNA Methylation of TXNIP Independently Associated with Inflammation and Diabetes Mellitus in Twins

Thioredoxin-interacting protein (TXNIP) plays a key role in diabetes development and prognosis through its role in pancreatic β-cell dysfunction and death as well as in upregulating the inflammatory response in hyperglycemia. DNA methylation (DNAm) of TXNIP (TXNIP-cg19693031) is associated with the prevalence and incidence of type 2 diabetes (T2D); however, its role in inflammation and its relationship with T2D remain unclear. We aimed to investigate the epigenetic associations of TXNIP-cg19693031 with a panel of inflammatory biomarkers and to examine whether these inflammatory biomarkers modify the association between TXNIP-cg19693031 methylation and diabetes in 218 middle-aged male twins from the Emory Twin Study. We confirmed the association of TXNIP-cg19693031 DNAm with T2D, as well as with HbA1c, insulin and fasting glucose. We found that hypomethylation at TXNIP-cg19693031 is strongly associated with both type 2 diabetes and higher levels of inflammatory biomarkers (VCAM-1, ICAM-1, MMP-2, sRAGE and P-selectin); however, the relationship between TXNIP-cg19693031 and T2D is independent of the levels of these inflammatory biomarkers. Our results suggest that DNA methylation of TXNIP is linked with multiple biological processes, through which the TXNIP may have broad influence on chronic disease risk.

The β Cell in Diabetes: Integrating Biomarkers With Functional Measures

The pathogenesis of hyperglycemia observed in most forms of diabetes is intimately tied to the islet β cell. Impairments in propeptide processing and secretory function, along with the loss of these vital cells, is demonstrable not only in those in whom the diagnosis is established but typically also in individuals who are at increased risk of developing the disease. Biomarkers are used to inform on the state of a biological process, pathological condition, or response to an intervention and are increasingly being used for predicting, diagnosing, and prognosticating disease. They are also proving to be of use in the different forms of diabetes in both research and clinical settings. This review focuses on the β cell, addressing the potential utility of genetic markers, circulating molecules, immune cell phenotyping, and imaging approaches as biomarkers of cellular function and loss of this critical cell. Further, we consider how these biomarkers complement the more long-established, dynamic, and often complex measurements of β-cell secretory function that themselves could be considered biomarkers.