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Juvinao-Quintero DL, Sharp GC, Sanderson ECM, Relton CL, Elliott HR. Investigating causality in the association between DNA methylation and type 2 diabetes using bidirectional two-sample Mendelian randomisation. Diabetologia 2023; 66:1247-1259. [PMID: 37202507 PMCID: PMC10244277 DOI: 10.1007/s00125-023-05914-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 01/25/2023] [Indexed: 05/20/2023]
Abstract
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.
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Affiliation(s)
- Diana L Juvinao-Quintero
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
| | - Gemma C Sharp
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Eleanor C M Sanderson
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Hannah R Elliott
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
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Dawes K, Philibert W, Darbro B, Simons RL, Philibert R. Additive and Interactive Genetically Contextual Effects of HbA1c on cg19693031 Methylation in Type 2 Diabetes. Genes (Basel) 2022; 13:genes13040683. [PMID: 35456489 PMCID: PMC9025650 DOI: 10.3390/genes13040683] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 04/05/2022] [Accepted: 04/11/2022] [Indexed: 02/06/2023] Open
Abstract
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.
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Affiliation(s)
- Kelsey Dawes
- Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USA; (W.P.); (R.P.)
- Correspondence: ; Tel.: +1-319-361-2081
| | - Willem Philibert
- Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USA; (W.P.); (R.P.)
| | - Benjamin Darbro
- Department of Pediatrics, University of Iowa, Iowa City, IA 52242, USA;
| | - Ronald L. Simons
- Department of Sociology, University of Georgia, Athens, GA 30602, USA;
| | - Robert Philibert
- Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USA; (W.P.); (R.P.)
- Behavioral Diagnostics LLC, Coralville, IA 52246, USA
- Cardio Diagnostics Inc., Coralville, IA 52246, USA
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Chu Y, Widjaja J, Hong J, Dolo PR, Zhu X, Yao L. Effect of Sleeve Gastrectomy on Plasma Thioredoxin-Interacting Protein (TXNIP). Obes Surg 2021; 31:4829-4835. [PMID: 34370159 DOI: 10.1007/s11695-021-05649-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 07/28/2021] [Accepted: 07/30/2021] [Indexed: 02/03/2023]
Abstract
PURPOSE The mechanism in which bariatric surgery induces diabetes remission is still poorly understood. This study proposes Thioredoxin-interacting protein (TXNIP) as a possible factor for the anti-diabetic mechanism after sleeve gastrectomy (SG). MATERIALS AND METHODS Plasma TXNIP level in obesity patients with diabetes (T2D, N = 20), obesity patients without diabetes (NDO, N = 20), and patients without obesity and diabetes (lean, N = 10) were assessed before surgery and at 1 and 12 months after SG. RESULTS Preoperative TXNIP level was significantly higher in T2D (196.4 ± 76.0 pg/ml) and NDO (149.7 ± 94.1 pg/ml) patients when compared with lean patients (98.7 ± 22.7 pg/ml) (p-value < 0.05). At 1 month and 12 months postoperatively, the TXNIP levels were reduced significantly from the preoperative levels in the T2D and NDO patients (p-value < 0.05). Before surgery, a correlation between TXNIP and fasting blood glucose (FBG) (r2 = 0.1585, p-value = 0.0109), HbA1C (r2 = 0.2120, p-value = 0.0028), and insulin (r2 = 0.1217, p-value = 0.0274) was observed. At 12 months after surgery, the reduction of TXNIP was also correlated with the degree of FBG (r2 = 0.1038, p-value = 0.0426), HbA1C (r2 = 0.2459, p-value = 0.0011), and insulin (r2 = 0.1365, p-value = 0.0190) reduction. CONCLUSION Plasma TXNIP level is elevated in obesity patients with/without diabetes. SG resulted in a significant reduction of plasma TXNIP level which is correlated with the degree of FBG, HbA1C, and insulin reduction. Regulation of TXNIP could be part of the mechanism of diabetes remission after bariatric surgery.
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Affiliation(s)
- Yuxiao Chu
- Department of Gastrointestinal Surgery, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, 221002, People's Republic of China
| | - Jason Widjaja
- Department of Gastrointestinal Surgery, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, 221002, People's Republic of China
| | - Jian Hong
- Department of Gastrointestinal Surgery, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, 221002, People's Republic of China
| | - Ponnie Robertlee Dolo
- Department of Gastrointestinal Surgery, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, 221002, People's Republic of China
| | - Xiaocheng Zhu
- Department of Gastrointestinal Surgery, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, 221002, People's Republic of China
| | - Libin Yao
- Department of Gastrointestinal Surgery, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, 221002, People's Republic of China.
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Domingues A, Jolibois J, Marquet de Rougé P, Nivet-Antoine V. The Emerging Role of TXNIP in Ischemic and Cardiovascular Diseases; A Novel Marker and Therapeutic Target. Int J Mol Sci 2021; 22:ijms22041693. [PMID: 33567593 PMCID: PMC7914816 DOI: 10.3390/ijms22041693] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 02/03/2021] [Accepted: 02/04/2021] [Indexed: 12/17/2022] Open
Abstract
Thioredoxin interacting protein (TXNIP) is a metabolism- oxidative- and inflammation-related marker induced in cardiovascular diseases and is believed to represent a possible link between metabolism and cellular redox status. TXNIP is a potential biomarker in cardiovascular and ischemic diseases but also a novel identified target for preventive and curative medicine. The goal of this review is to focus on the novelties concerning TXNIP. After an overview in TXNIP involvement in oxidative stress, inflammation and metabolism, the remainder of this review presents the clues used to define TXNIP as a new marker at the genetic, blood, or ischemic site level in the context of cardiovascular and ischemic diseases.
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Affiliation(s)
- Alison Domingues
- INSERM 1140, Innovative Therapies in Haemostasis, Faculty of Pharmacy, Université de Paris, 75006 Paris, France; (A.D.); (J.J.); (P.M.d.R.)
| | - Julia Jolibois
- INSERM 1140, Innovative Therapies in Haemostasis, Faculty of Pharmacy, Université de Paris, 75006 Paris, France; (A.D.); (J.J.); (P.M.d.R.)
| | - Perrine Marquet de Rougé
- INSERM 1140, Innovative Therapies in Haemostasis, Faculty of Pharmacy, Université de Paris, 75006 Paris, France; (A.D.); (J.J.); (P.M.d.R.)
| | - Valérie Nivet-Antoine
- INSERM 1140, Innovative Therapies in Haemostasis, Faculty of Pharmacy, Université de Paris, 75006 Paris, France; (A.D.); (J.J.); (P.M.d.R.)
- Clinical Biochemistry Department, Assistance Publique des Hôpitaux de Paris, Necker Hospital, 75015 Paris, France
- Correspondence:
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Andrade S, Morais T, Sandovici I, Seabra AL, Constância M, Monteiro MP. Adipose Tissue Epigenetic Profile in Obesity-Related Dysglycemia - A Systematic Review. Front Endocrinol (Lausanne) 2021; 12:681649. [PMID: 34290669 PMCID: PMC8288106 DOI: 10.3389/fendo.2021.681649] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 05/26/2021] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Obesity is a major risk factor for dysglycemic disorders, including type 2 diabetes (T2D). However, there is wide phenotypic variation in metabolic profiles. Tissue-specific epigenetic modifications could be partially accountable for the observed phenotypic variability. SCOPE The aim of this systematic review was to summarize the available data on epigenetic signatures in human adipose tissue (AT) that characterize overweight or obesity-related insulin resistance (IR) and dysglycemia states and to identify potential underlying mechanisms through the use of unbiased bioinformatics approaches. METHODS Original data published in the last decade concerning the comparison of epigenetic marks in human AT of individuals with metabolically unhealthy overweight/obesity (MUHO) versus normal weight individuals or individuals with metabolically healthy overweight/obesity (MHO) was assessed. Furthermore, association of these epigenetic marks with IR/dysglycemic traits, including T2D, was compiled. RESULTS We catalogued more than two thousand differentially methylated regions (DMRs; above the cut-off of 5%) in the AT of individuals with MUHO compared to individuals with MHO. These DNA methylation changes were less likely to occur around the promoter regions and were enriched at loci implicated in intracellular signaling (signal transduction mediated by small GTPases, ERK1/2 signaling and intracellular trafficking). We also identified a network of seven transcription factors that may play an important role in targeting DNA methylation changes to specific genes in the AT of subjects with MUHO, contributing to the pathogeny of obesity-related IR/T2D. Furthermore, we found differentially methylated CpG sites at 8 genes that were present in AT and whole blood, suggesting that DMRs in whole blood could be potentially used as accessible biomarkers of MUHO. CONCLUSIONS The overall evidence linking epigenetic alterations in key tissues such AT to metabolic complications in human obesity is still very limited, highlighting the need for further studies, particularly those focusing on epigenetic marks other than DNA methylation. Our initial analysis suggests that DNA methylation patterns can potentially discriminate between MUHO from MHO and provide new clues into why some people with obesity are less susceptible to dysglycemia. Identifying AT-specific epigenetic targets could also lead to novel approaches to modify the progression of individuals with obesity towards metabolic disease. SYSTEMATIC REVIEW REGISTRATION PROSPERO, identifier CRD42021227237.
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Affiliation(s)
- Sara Andrade
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Porto, Portugal
| | - Tiago Morais
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Porto, Portugal
| | - Ionel Sandovici
- University of Cambridge Metabolic Research Laboratories and MRC Metabolic Diseases Unit, Institute of Metabolic Science, Addenbrookes Hospital, Cambridge, United Kingdom
- Department of Obstetrics and Gynaecology and National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge, United Kingdom
- Centre for Trophoblast Research, Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, United Kingdom
| | - Alexandre L. Seabra
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Porto, Portugal
| | - Miguel Constância
- University of Cambridge Metabolic Research Laboratories and MRC Metabolic Diseases Unit, Institute of Metabolic Science, Addenbrookes Hospital, Cambridge, United Kingdom
- Department of Obstetrics and Gynaecology and National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge, United Kingdom
- Centre for Trophoblast Research, Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, United Kingdom
- National Institute of Health Research, Cambridge Biomedical Research Centre, Cambridge, United Kingdom
| | - Mariana P. Monteiro
- Endocrine and Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, Porto, Portugal
- Department of Anatomy, Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Porto, Portugal
- *Correspondence: Mariana P. Monteiro,
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Systematic integrated analysis of genetic and epigenetic variation in diabetic kidney disease. Proc Natl Acad Sci U S A 2020; 117:29013-29024. [PMID: 33144501 DOI: 10.1073/pnas.2005905117] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Poor metabolic control and host genetic predisposition are critical for diabetic kidney disease (DKD) development. The epigenome integrates information from sequence variations and metabolic alterations. Here, we performed a genome-wide methylome association analysis in 500 subjects with DKD from the Chronic Renal Insufficiency Cohort for DKD phenotypes, including glycemic control, albuminuria, kidney function, and kidney function decline. We show distinct methylation patterns associated with each phenotype. We define methylation variations that are associated with underlying nucleotide variations (methylation quantitative trait loci) and show that underlying genetic variations are important drivers of methylation changes. We implemented Bayesian multitrait colocalization analysis (moloc) and summary data-based Mendelian randomization to systematically annotate genomic regions that show association with kidney function, methylation, and gene expression. We prioritized 40 loci, where methylation and gene-expression changes likely mediate the genotype effect on kidney disease development. Functional annotation suggested the role of inflammation, specifically, apoptotic cell clearance and complement activation in kidney disease development. Our study defines methylation changes associated with DKD phenotypes, the key role of underlying genetic variations driving methylation variations, and prioritizes methylome and gene-expression changes that likely mediate the genotype effect on kidney disease pathogenesis.
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