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Fragoso-Bargas N, Elliott HR, Lee-Ødegård S, Opsahl JO, Sletner L, Jenum AK, Drevon CA, Qvigstad E, Moen GH, Birkeland KI, Prasad RB, Sommer C. Cross-Ancestry DNA Methylation Marks of Insulin Resistance in Pregnancy: An Integrative Epigenome-Wide Association Study. Diabetes 2023; 72:415-426. [PMID: 36534481 PMCID: PMC9935495 DOI: 10.2337/db22-0504] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 12/12/2022] [Indexed: 12/24/2022]
Abstract
Although there are some epigenome-wide association studies (EWAS) of insulin resistance, for most of them authors did not replicate their findings, and most are focused on populations of European ancestry, limiting the generalizability. In the Epigenetics in Pregnancy (EPIPREG; n = 294 Europeans and 162 South Asians) study, we conducted an EWAS of insulin resistance in maternal peripheral blood leukocytes, with replication in the Born in Bradford (n = 879; n = 430 Europeans and 449 South Asians), Methyl Epigenome Network Association (MENA) (n = 320), and Botnia (n = 56) cohorts. In EPIPREG, we identified six CpG sites inversely associated with insulin resistance across ancestry, of which five were replicated in independent cohorts (cg02988288, cg19693031, and cg26974062 in TXNIP; cg06690548 in SLC7A11; and cg04861640 in ZSCAN26). From methylation quantitative trait loci analysis in EPIPREG, we identified gene variants related to all five replicated cross-ancestry CpG sites, which were associated with several cardiometabolic phenotypes. Mediation analyses suggested that the gene variants regulate insulin resistance through DNA methylation. To conclude, our cross-ancestry EWAS identified five CpG sites related to lower insulin resistance.
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Affiliation(s)
- Nicolas Fragoso-Bargas
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Hannah R. Elliott
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Sindre Lee-Ødegård
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Julia O. Opsahl
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Line Sletner
- Department of Pediatric and Adolescents Medicine, Akershus University Hospital, Lørenskog, Norway
| | - Anne Karen Jenum
- General Practice Research Unit (AFE), Department of General Practice, Institute of Health and Society, University of Oslo, Oslo, Norway
| | - Christian A. Drevon
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Oslo, Norway
- Vitas Ltd. Analytical Services, Oslo Science Park, Oslo, Norway
| | - Elisabeth Qvigstad
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Gunn-Helen Moen
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, Queensland, Australia
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Institute of Molecular Biosciences, The University of Queensland, Brisbane, Queensland, Australia
| | - Kåre I. Birkeland
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Rashmi B. Prasad
- Lund University Diabetes Centre, Malmö, Sweden
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Christine Sommer
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
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Bygren LO, Jansåker F, Sundquist K, Johansson SE. Association between attending cultural events and all-cause mortality: a longitudinal study with three measurements (1982-2017). BMJ Open 2023; 13:e065714. [PMID: 36810171 PMCID: PMC9945101 DOI: 10.1136/bmjopen-2022-065714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/24/2023] Open
Abstract
OBJECTIVES To examine the association between cultural attendance and all-cause mortality. DESIGN A longitudinal cohort study over 36 years (1982-2017) with three 8-year interval measurements of exposure (1982/1983, 1990/1991 and 1998/1999) to cultural attendance and a follow-up period to 31 December 2017. SETTING Sweden. PARTICIPANTS The study included 3311 randomly selected individuals from the Swedish population with complete data for all three measurements. PRIMARY OUTCOME MEASUREMENTS All-cause mortality during the study period in relation to level of cultural attendance. Cox regression models with time-varying covariates were used to estimate HRs adjusted for potential confounders. RESULTS The HRs of cultural attendance in the lowest and middle levels compared with the highest level (reference; HR=1) were 1.63 (95% CI 1.34 to 2.00) and 1.25 (95% CI 1.03 to 1.51), respectively. CONCLUSION Attending cultural events has a suggested gradient, the lesser cultural exposure the higher all-cause mortality during the follow-up.
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Affiliation(s)
- Lars Olov Bygren
- Department of Biosciences and Nutrition, Karolinska Institutet, Stockholm, Sweden
- Community Medicine and Rehabilitation, Umeå University, Umeå, Sweden
| | - Filip Jansåker
- Center for Primary Health Care Research, Department of Clinical Sciences, Lund University, Malmö, Sweden
- Department of Clinical Microbiology, Rigshospitalet, Kobenhavn, Denmark
| | - Kristina Sundquist
- Center for Primary Health Care Research, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Sven-Erik Johansson
- Center for Primary Health Care Research, Department of Clinical Sciences, Lund University, Malmö, Sweden
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53
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Jung SY, Bhatti P, Pellegrini M. DNA methylation in peripheral blood leukocytes for the association with glucose metabolism and invasive breast cancer. Clin Epigenetics 2023; 15:23. [PMID: 36782224 PMCID: PMC9926571 DOI: 10.1186/s13148-023-01435-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Accepted: 01/26/2023] [Indexed: 02/15/2023] Open
Abstract
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.
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Affiliation(s)
- Su Yon Jung
- Translational Sciences Section, School of Nursing, University of California, Los Angeles, 700 Tiverton Ave, 3-264 Factor Building, Los Angeles, CA, 90095, USA.
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
| | - Parveen Bhatti
- Cancer Control Research, BC Cancer Research Institute, Vancouver, BC, Canada
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
| | - Matteo Pellegrini
- Department of Molecular, Cell and Developmental Biology, Life Sciences Division, University of California, Los Angeles, Los Angeles, CA, 90095, USA
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54
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Suárez R, Chapela SP, Álvarez-Córdova L, Bautista-Valarezo E, Sarmiento-Andrade Y, Verde L, Frias-Toral E, Sarno G. Epigenetics in Obesity and Diabetes Mellitus: New Insights. Nutrients 2023; 15:nu15040811. [PMID: 36839169 PMCID: PMC9963127 DOI: 10.3390/nu15040811] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 01/20/2023] [Accepted: 01/25/2023] [Indexed: 02/08/2023] Open
Abstract
A long-term complication of obesity is the development of type 2 diabetes (T2D). Patients with T2D have been described as having epigenetic modifications. Epigenetics is the post-transcriptional modification of DNA or associated factors containing genetic information. These environmentally-influenced modifications, maintained during cell division, cause stable changes in gene expression. Epigenetic modifications of T2D are DNA methylation, acetylation, ubiquitylation, SUMOylation, and phosphorylation at the lysine residue at the amino terminus of histones, affecting DNA, histones, and non-coding RNA. DNA methylation has been shown in pancreatic islets, adipose tissue, skeletal muscle, and the liver. Furthermore, epigenetic changes have been observed in chronic complications of T2D, such as diabetic nephropathy, diabetic retinopathy, and diabetic neuropathy. Recently, a new drug has been developed which acts on bromodomains and extraterminal (BET) domain proteins, which operate like epigenetic readers and communicate with chromatin to make DNA accessible for transcription by inhibiting them. This drug (apabetalone) is being studied to prevent major adverse cardiovascular events in people with T2D, low HDL cholesterol, chronic kidney failure, and recent coronary events. This review aims to describe the relationship between obesity, long-term complications such as T2D, and epigenetic modifications and their possible treatments.
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Affiliation(s)
- Rosario Suárez
- School of Medicine, Universidad Técnica Particular de Loja, Calle París, San Cayetano Alto, Loja 110101, Ecuador
| | - Sebastián P. Chapela
- Departamento de Bioquímica Humana, Facultad de Medicina, Universidad de Buenos Aires, Buenos Aires C1121ABE, Argentina
- Hospital Británico de Buenos Aires, Equipo de Soporte Nutricional, Buenos Aires C1280AEB, Argentina
- Correspondence: ; Tel.: +54-91168188308
| | - Ludwig Álvarez-Córdova
- School of Medicine, Universidad Católica Santiago de Guayaquil, Av. Pdte. Carlos Julio Arosemena Tola, Guayaquil 090615, Ecuador
- Carrera de Nutrición y Dietética, Facultad de Ciencias Médicas, Universidad Católica De Santiago de Guayaquil, Av. Pdte. Carlos Julio Arosemena Tola, Guayaquil 090615, Ecuador
| | - Estefanía Bautista-Valarezo
- School of Medicine, Universidad Técnica Particular de Loja, Calle París, San Cayetano Alto, Loja 110101, Ecuador
| | - Yoredy Sarmiento-Andrade
- School of Medicine, Universidad Técnica Particular de Loja, Calle París, San Cayetano Alto, Loja 110101, Ecuador
| | - Ludovica Verde
- Centro Italiano per la Cura e il Benessere del Paziente con Obesità (C.I.B.O), Department of Clinical Medicine and Surgery, Endocrinology Unit, University Medical School of Naples, Via Sergio Pansini 5, 80131 Naples, Italy
| | - Evelyn Frias-Toral
- School of Medicine, Universidad Católica Santiago de Guayaquil, Av. Pdte. Carlos Julio Arosemena Tola, Guayaquil 090615, Ecuador
| | - Gerardo Sarno
- “San Giovanni di Dio e Ruggi D’Aragona” University Hospital, Scuola Medica Salernitana, 84131 Salerno, Italy
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55
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Do WL, Sun D, Meeks K, Dugué PA, Demerath E, Guan W, Li S, Chen W, Milne R, Adeyemo A, Agyemang C, Nassir R, Manson JE, Shadyab AH, Hou L, Horvath S, Assimes TL, Bhatti P, Jordahl KM, Baccarelli AA, Smith AK, Staimez LR, Stein AD, Whitsel EA, Narayan KV, Conneely KN. Epigenome-wide meta-analysis of BMI in nine cohorts: Examining the utility of epigenetically predicted BMI. Am J Hum Genet 2023; 110:273-283. [PMID: 36649705 PMCID: PMC9943731 DOI: 10.1016/j.ajhg.2022.12.014] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 12/20/2022] [Indexed: 01/18/2023] Open
Abstract
This study sought to examine the association between DNA methylation and body mass index (BMI) and the potential of BMI-associated cytosine-phosphate-guanine (CpG) sites to provide information about metabolic health. We pooled summary statistics from six trans-ethnic epigenome-wide association studies (EWASs) of BMI representing nine cohorts (n = 17,034), replicated these findings in the Women's Health Initiative (WHI, n = 4,822), and developed an epigenetic prediction score of BMI. In the pooled EWASs, 1,265 CpG sites were associated with BMI (p < 1E-7) and 1,238 replicated in the WHI (FDR < 0.05). We performed several stratified analyses to examine whether these associations differed between individuals of European and African descent, as defined by self-reported race/ethnicity. We found that five CpG sites had a significant interaction with BMI by race/ethnicity. To examine the utility of the significant CpG sites in predicting BMI, we used elastic net regression to predict log-normalized BMI in the WHI (80% training/20% testing). This model found that 397 sites could explain 32% of the variance in BMI in the WHI test set. Individuals whose methylome-predicted BMI overestimated their BMI (high epigenetic BMI) had significantly higher glucose and triglycerides and lower HDL cholesterol and LDL cholesterol compared to accurately predicted BMI. Individuals whose methylome-predicted BMI underestimated their BMI (low epigenetic BMI) had significantly higher HDL cholesterol and lower glucose and triglycerides. This study confirmed 553 and identified 685 CpG sites associated with BMI. Participants with high epigenetic BMI had poorer metabolic health, suggesting that the overestimation may be driven in part by cardiometabolic derangements characteristic of metabolic syndrome.
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Affiliation(s)
- Whitney L. Do
- Laney Graduate School, Emory University, Atlanta, GA, USA
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China,Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Karlijn Meeks
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA,Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - Pierre-Antoine Dugué
- Precision Medicine, School of Clinical Sciences At Monash Health, Monash University, Clayton, VIC, Australia,Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia
| | - Ellen Demerath
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Weihua Guan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Shengxu Li
- Children’s Minnesota Research Institute, Childrens Minnesota, Minneapolis, MN, USA
| | - Wei Chen
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Roger Milne
- Precision Medicine, School of Clinical Sciences At Monash Health, Monash University, Clayton, VIC, Australia,Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia
| | - Abedowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Charles Agyemang
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - Rami Nassir
- Department of Pathology, School of Medicine, Umm Al-Qura University, Mecca, Saudi Arabia
| | - JoAnn E. Manson
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Aladdin H. Shadyab
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Steve Horvath
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Parveen Bhatti
- Cancer Control Research, BC Cancer, Vancouver, BC, Canada
| | | | - Andrea A. Baccarelli
- Department of Environmental Health Sciences, Columbia University, New York, NY, USA
| | - Alicia K. Smith
- Department of Gynecology and Obstetrics, School of Medicine, Emory University, Atlanta, GA, USA
| | - Lisa R. Staimez
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Aryeh D. Stein
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Eric A. Whitsel
- Departments of Epidemiology and Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - K.M. Venkat Narayan
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Karen N. Conneely
- Department of Human Genetics, School of Medicine, Emory University, Atlanta, GA, USA,Corresponding author
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56
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The Singapore National Precision Medicine Strategy. Nat Genet 2023; 55:178-186. [PMID: 36658435 DOI: 10.1038/s41588-022-01274-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 11/30/2022] [Indexed: 01/21/2023]
Abstract
Precision medicine promises to transform healthcare for groups and individuals through early disease detection, refining diagnoses and tailoring treatments. Analysis of large-scale genomic-phenotypic databases is a critical enabler of precision medicine. Although Asia is home to 60% of the world's population, many Asian ancestries are under-represented in existing databases, leading to missed opportunities for new discoveries, particularly for diseases most relevant for these populations. The Singapore National Precision Medicine initiative is a whole-of-government 10-year initiative aiming to generate precision medicine data of up to one million individuals, integrating genomic, lifestyle, health, social and environmental data. Beyond technologies, routine adoption of precision medicine in clinical practice requires social, ethical, legal and regulatory barriers to be addressed. Identifying driver use cases in which precision medicine results in standardized changes to clinical workflows or improvements in population health, coupled with health economic analysis to demonstrate value-based healthcare, is a vital prerequisite for responsible health system adoption.
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57
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Hao J, Liu Y. Epigenetics of methylation modifications in diabetic cardiomyopathy. Front Endocrinol (Lausanne) 2023; 14:1119765. [PMID: 37008904 PMCID: PMC10050754 DOI: 10.3389/fendo.2023.1119765] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 03/01/2023] [Indexed: 03/17/2023] Open
Abstract
Type 2 diabetes is one of the most common metabolic diseases with complications including diabetic cardiomyopathy and atherosclerotic cardiovascular disease. Recently, a growing body of research has revealed that the complex interplay between epigenetic changes and the environmental factors may significantly contribute to the pathogenesis of cardiovascular complications secondary to diabetes. Methylation modifications, including DNA methylation and histone methylation among others, are important in developing diabetic cardiomyopathy. Here we summarized the literatures of studies focusing on the role of DNA methylation, and histone modifications in microvascular complications of diabetes and discussed the mechanism underlying these disorders, to provide the guidance for future research toward an integrated pathophysiology and novel therapeutic strategies to treat or prevent this frequent pathological condition.
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Affiliation(s)
- Jing Hao
- Department of Emergency, Children’s Hospital of Nanjing Medical University, Nanjing, China
| | - Yao Liu
- Department of Pharmacy, Children’s Hospital of Nanjing Medical University, Nanjing, China
- *Correspondence: Yao Liu,
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58
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Dawed AY, Haider E, Pearson ER. Precision Medicine in Diabetes. Handb Exp Pharmacol 2023; 280:107-129. [PMID: 35704097 DOI: 10.1007/164_2022_590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Tailoring treatment or management to groups of individuals based on specific clinical, molecular, and genomic features is the concept of precision medicine. Diabetes is highly heterogenous with respect to clinical manifestations, disease progression, development of complications, and drug response. The current practice for drug treatment is largely based on evidence from clinical trials that report average effects. However, around half of patients with type 2 diabetes do not achieve glycaemic targets despite having a high level of adherence and there are substantial differences in the incidence of adverse outcomes. Therefore, there is a need to identify predictive markers that can inform differential drug responses at the point of prescribing. Recent advances in molecular genetics and increased availability of real-world and randomised trial data have started to increase our understanding of disease heterogeneity and its impact on potential treatments for specific groups. Leveraging information from simple clinical features (age, sex, BMI, ethnicity, and co-prescribed medications) and genomic markers has a potential to identify sub-groups who are likely to benefit from a given drug with minimal adverse effects. In this chapter, we will discuss the state of current evidence in the discovery of clinical and genetic markers that have the potential to optimise drug treatment in type 2 diabetes.
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Affiliation(s)
- Adem Y Dawed
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Eram Haider
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Ewan R Pearson
- Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, UK.
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59
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Miller RG, Mychaleckyj JC, Onengut-Gumuscu S, Orchard TJ, Costacou T. 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. BMJ Open Diabetes Res Care 2023; 11:e003068. [PMID: 36604111 PMCID: PMC9827189 DOI: 10.1136/bmjdrc-2022-003068] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 12/21/2022] [Indexed: 01/07/2023] Open
Abstract
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.
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Affiliation(s)
- Rachel G Miller
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Josyf C Mychaleckyj
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Trevor J Orchard
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Tina Costacou
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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60
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Hong X, Miao K, Cao W, Lv J, Yu C, Huang T, Sun D, Liao C, Pang Y, Pang Z, Yu M, Wang H, Wu X, Liu Y, Gao W, Li L. Association Between DNA Methylation and Blood Pressure: A 5-Year Longitudinal Twin Study. Hypertension 2023; 80:169-181. [PMID: 36345830 DOI: 10.1161/hypertensionaha.122.19953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
BACKGROUND Previous EWASs (Epigenome-Wide Association Studies) have reported hundreds of blood pressure (BP) associated 5'-cytosine-phosphate-guanine-3' (CpG) sites. However, their results were inconsistent. Longitudinal observations on the temporal relationship between DNA methylation and BP are lacking. METHODS A candidate CpG site association study for BP was conducted on 1072 twins in the Chinese National Twin Registry. PubMed and EMBASE were searched for candidate CpG sites. Cross-lagged models were used to assess the temporal relationship between BP and DNA methylation in 308 twins who completed 2 surveys in 2013 and 2018. Then, the significant cross-lagged associations were validated by adopting the Inference About Causation From Examination of Familial Confounding approach. Finally, to evaluate the cumulative effects of DNA methylation on the progression of hypertension, we established methylation risk scores based on BP-associated CpG sites and performed Markov multistate models. RESULTS 16 and 20 CpG sites were validated to be associated with systolic BP and diastolic BP, respectively. In the cross-lagged analysis, we detected that methylation of 2 CpG sites could predict subsequent systolic BP, and systolic BP predicted methylation at another 3 CpG sites. For diastolic BP, methylation at 3 CpG sites had significant cross-lagged effects for predicting diastolic BP levels, while the prediction from the opposite direction was observed at one site. Among these, 3 associations were validated in the Inference About Causation From Examination of Familial Confounding analysis. Using the Markov multistate model, we observed that methylation risk scores were associated with the development of hypertension. CONCLUSIONS Our findings suggest the significance of DNA methylation in the development of hypertension.
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Affiliation(s)
- Xuanming Hong
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Ke Miao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Weihua Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Chunxiao Liao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Zengchang Pang
- Qingdao Center for Disease Control and Prevention, China (Z.P.)
| | - Min Yu
- Zhejiang Center for Disease Control and Prevention, Hangzhou, China (M.Y.)
| | - Hua Wang
- Jiangsu Center for Disease Control and Prevention, Nanjing, China (H.W.)
| | - Xianping Wu
- Sichuan Center for Disease Control and Prevention, Chengdu, China (X.W.)
| | - Yu Liu
- Heilongjiang Center for Disease Control and Prevention, Harbin, China (Y.L.)
| | - Wenjing Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
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Taylor JY, Huang Y, Zhao W, Wright ML, Wang Z, Hui Q, Potts‐Thompson S, Barcelona V, Prescott L, Yao Y, Crusto C, Kardia SLR, Smith JA, Sun YV. Epigenome-wide association study of BMI in Black populations from InterGEN and GENOA. Obesity (Silver Spring) 2023; 31:243-255. [PMID: 36479596 PMCID: PMC10107734 DOI: 10.1002/oby.23589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 08/09/2022] [Accepted: 08/22/2022] [Indexed: 12/12/2022]
Abstract
OBJECTIVE Obesity is a significant public health concern across the globe. Research investigating epigenetic mechanisms related to obesity and obesity-associated conditions has identified differences that may contribute to cellular dysregulation that accelerates the development of disease. However, few studies include Black women, who experience the highest incidence of obesity and early onset of cardiometabolic disorders. METHODS The association of BMI with epigenome-wide DNA methylation (DNAm) was examined using the 850K Illumina EPIC BeadChip in two Black populations (Intergenerational Impact of Genetic and Psychological Factors on Blood Pressure [InterGEN], n = 239; and The Genetic Epidemiology Network of Arteriopathy [GENOA] study, n = 961) using linear mixed-effects regression models adjusted for batch effects, cell type heterogeneity, population stratification, and confounding factors. RESULTS Cross-sectional analysis of the InterGEN discovery cohort identified 28 DNAm sites significantly associated with BMI, 24 of which had not been previously reported. Of these, 17 were replicated using the GENOA study. In addition, a meta-analysis, including both the InterGEN and GENOA cohorts, identified 658 DNAm sites associated with BMI with false discovery rate < 0.05. In a meta-analysis of Black women, we identified 628 DNAm sites significantly associated with BMI. Using a more stringent significance threshold of Bonferroni-corrected p value 0.05, 65 and 61 DNAm sites associated with BMI were identified from the combined sex and female-only meta-analyses, respectively. CONCLUSIONS This study suggests that BMI is associated with differences in DNAm among women that can be identified with DNA extracted from salivary (discovery) and peripheral blood (replication) samples among Black populations across two cohorts.
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Affiliation(s)
- Jacquelyn Y. Taylor
- Center for Research on People of ColorColumbia University School of NursingNew YorkNew YorkUSA
| | - Yunfeng Huang
- Department of EpidemiologyEmory University Rollins School of Public HealthAtlantaGeorgiaUSA
| | - Wei Zhao
- Department of Epidemiology, School of Public HealthUniversity of MichiganAnn ArborMichiganUSA
| | | | - Zeyuan Wang
- Department of EpidemiologyEmory University Rollins School of Public HealthAtlantaGeorgiaUSA
| | - Qin Hui
- Department of EpidemiologyEmory University Rollins School of Public HealthAtlantaGeorgiaUSA
| | | | - Veronica Barcelona
- Center for Research on People of ColorColumbia University School of NursingNew YorkNew YorkUSA
| | - Laura Prescott
- Center for Research on People of ColorColumbia University School of NursingNew YorkNew YorkUSA
| | - Yutong Yao
- Department of EpidemiologyEmory University Rollins School of Public HealthAtlantaGeorgiaUSA
| | - Cindy Crusto
- Department of PsychiatryYale School of MedicineNew HavenConnecticutUSA
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public HealthUniversity of MichiganAnn ArborMichiganUSA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public HealthUniversity of MichiganAnn ArborMichiganUSA
- Survey Research CenterInstitute for Social Research, University of MichiganAnn ArborMichiganUSA
| | - Yan V. Sun
- Department of EpidemiologyEmory University Rollins School of Public HealthAtlantaGeorgiaUSA
- Atlanta VA Healthcare SystemDecaturGeorgiaUSA
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Chu DT, Bui NL, Vu Thi H, Nguyen Thi YV. Role of DNA methylation in diabetes and obesity. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2023; 197:153-170. [PMID: 37019591 DOI: 10.1016/bs.pmbts.2023.01.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/26/2023]
Abstract
Due to the fact that the upward trend of several metabolic disorders such as diabetes and obesity, in individuals especially monozygotic twins, who are under the same effects from the environment, are not similar, the role of epigenetic elements like DNA methylation needs taking into account. In this chapter, emerging scientific evidence supporting the strong relationship between changes in DNA methylation and those diseases' development was summarized. Changing in the expression level of diabetes/obesity-related genes through being silenced by methylation can be the underlying mechanism of this phenomenon. Genes with abnormal methylation status are potential biomarkers for early prediction and diagnosis. Moreover, methylation-based molecular targets should be investigated as a new treatment for both T2D and obesity.
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Affiliation(s)
- Dinh-Toi Chu
- Center for Biomedicine and Community Health, International School, Vietnam National University, Hanoi, Vietnam; Faculty of Applied Sciences, International School, Vietnam National University, Hanoi, Vietnam.
| | - Nhat-Le Bui
- Center for Biomedicine and Community Health, International School, Vietnam National University, Hanoi, Vietnam; Faculty of Applied Sciences, International School, Vietnam National University, Hanoi, Vietnam
| | - Hue Vu Thi
- Center for Biomedicine and Community Health, International School, Vietnam National University, Hanoi, Vietnam; Faculty of Applied Sciences, International School, Vietnam National University, Hanoi, Vietnam
| | - Yen-Vy Nguyen Thi
- Center for Biomedicine and Community Health, International School, Vietnam National University, Hanoi, Vietnam; Faculty of Applied Sciences, International School, Vietnam National University, Hanoi, Vietnam
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63
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Wang X, Liu J, Wang Q, Chen Q. The transcriptomic and epigenetic alterations in type 2 diabetes mellitus patients of Chinese Tibetan and Han populations. Front Endocrinol (Lausanne) 2023; 14:1122047. [PMID: 36891054 PMCID: PMC9987421 DOI: 10.3389/fendo.2023.1122047] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 02/01/2023] [Indexed: 02/22/2023] Open
Abstract
BACKGROUND Due to the distinctive living environment, lifestyle, and diet, the Tibetan community in China has the lowest prevalence of T2DM and prediabetes among numerous ethnic groups, while Han community shows the highest statistic. In this study, we aim to conclude the clinical manifestations of both Tibetan and Han T2DM patients and their association with transcriptomic and epigenetic alterations. METHODS A cross-sectional study including 120 T2DM patients from Han and Tibetan ethnic groups were conducted between 2019 to 2021 at the Hospital of Chengdu University of Traditional Chinese Medicine. The various clinical features and laboratory tests were recorded and analyzed between the two groups. The genome-wide methylation pattern and RNA expression were determined by Reduced Representation Bisulfite Sequencing (RBBS) and Poly (A) RNA sequencing (RNA-seq) from leucocytes of peripheral blood samples in 6 Han and 6 Tibetan patients. GO analysis and KEGG analysis were conducted in differentially expressed genes and those with differentially methylated regions. RESULTS Compared to Han, Tibetan T2DM individuals intake more coarse grains, meat and yak butter, but less refined grains, vegetables and fruit. They also showed increased BMI, Hb, HbA1c, LDL, ALT, GGT and eGFR, and decreased level of BUN. Among the 12 patients in the exploratory cohort, we identified 5178 hypomethylated and 4787 hypermethylated regions involving 1613 genes in the Tibetan group. RNA-seq showed a total of 947 differentially expressed genes (DEGs) between the two groups, with 523 up-regulated and 424 down-regulated in Tibetan patients. By integrating DNA methylation and RNA expression data, we identified 112 DEGs with differentially methylated regions (overlapping genes) and 14 DEGs with promoter-related DMRs. The functional enrichment analysis demonstrated that the overlapping genes were primarily involved in metabolic pathways, PI3K-Akt signaling pathway, MAPK signaling pathway, pathways in cancer and Rap1 signaling pathway. CONCLUSION Our study demonstrates the clinical characteristics of T2DM differ subtly between various ethnic groups that may be related to epigenetic modifications, thus providing evidence and ideas for additional research on the genetic pattern of T2DM.
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Affiliation(s)
- Xian Wang
- School of Biological and Behavioral Sciences, Queen Mary University of London, London, United Kingdom
- Department of Endocrinology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Jie Liu
- Department of Endocrinology, Kunming Municipal Hospital of Traditional Chinese Medicine, Kumning, China
| | - Qiuhong Wang
- Department of Endocrinology, Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
- *Correspondence: Qiuhong Wang, ; Qiu Chen,
| | - Qiu Chen
- Department of Endocrinology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
- *Correspondence: Qiuhong Wang, ; Qiu Chen,
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Domingo-Relloso A, Gribble MO, Riffo-Campos AL, Haack K, Cole SA, Tellez-Plaza M, Umans JG, Fretts AM, Zhang Y, Fallin MD, Navas-Acien A, Everson TM. Epigenetics of type 2 diabetes and diabetes-related outcomes in the Strong Heart Study. Clin Epigenetics 2022; 14:177. [PMID: 36529747 PMCID: PMC9759920 DOI: 10.1186/s13148-022-01392-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 11/30/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND The prevalence of type 2 diabetes has dramatically increased in the past years. Increasing evidence supports that blood DNA methylation, the best studied epigenetic mark, is related to diabetes risk. Few prospective studies, however, are available. We studied the association of blood DNA methylation with diabetes in the Strong Heart Study. We used limma, Iterative Sure Independence Screening and Cox regression to study the association of blood DNA methylation with fasting glucose, HOMA-IR and incident type 2 diabetes among 1312 American Indians from the Strong Heart Study. DNA methylation was measured using Illumina's MethylationEPIC beadchip. We also assessed the biological relevance of our findings using bioinformatics analyses. RESULTS Among the 358 differentially methylated positions (DMPs) that were cross-sectionally associated either with fasting glucose or HOMA-IR, 49 were prospectively associated with incident type 2 diabetes, although no DMPs remained significant after multiple comparisons correction. Multiple of the top DMPs were annotated to genes with relevant functions for diabetes including SREBF1, associated with obesity, type 2 diabetes and insulin sensitivity; ABCG1, involved in cholesterol and phospholipids transport; and HDAC1, of the HDAC family. (HDAC inhibitors have been proposed as an emerging treatment for diabetes and its complications.) CONCLUSIONS: Our results suggest that differences in peripheral blood DNA methylation are related to cross-sectional markers of glucose metabolism and insulin activity. While some of these DMPs were modestly associated with prospective incident type 2 diabetes, they did not survive multiple testing. Common DMPs with diabetes epigenome-wide association studies from other populations suggest a partially common epigenomic signature of glucose and insulin activity.
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Affiliation(s)
- Arce Domingo-Relloso
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain.
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA.
- Department of Statistics and Operations Research, University of Valencia, Valencia, Spain.
| | - Matthew O Gribble
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Angela L Riffo-Campos
- Millennium Nucleus On Sociomedicine (SocioMed) and Vicerrectoría Académica, Universidad de La Frontera, Temuco, Chile
- Department of Computer Science, ETSE, University of Valencia, Valencia, Spain
| | - Karin Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Shelley A Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Maria Tellez-Plaza
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
| | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, MD, USA
- Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC, USA
| | - Amanda M Fretts
- Department of Epidemiology, Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
| | - Ying Zhang
- Department of Biostatistics and Epidemiology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - M Daniele Fallin
- Emory University Rollins School of Public Health, Atlanta, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Todd M Everson
- Gangarosa Department of Environmental Health, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
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Epigenetics and Gut Microbiota Crosstalk: A potential Factor in Pathogenesis of Cardiovascular Disorders. BIOENGINEERING (BASEL, SWITZERLAND) 2022; 9:bioengineering9120798. [PMID: 36551003 PMCID: PMC9774431 DOI: 10.3390/bioengineering9120798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 12/09/2022] [Accepted: 12/12/2022] [Indexed: 12/15/2022]
Abstract
Cardiovascular diseases (CVD) are the leading cause of mortality, morbidity, and "sudden death" globally. Environmental and lifestyle factors play important roles in CVD susceptibility, but the link between environmental factors and genetics is not fully established. Epigenetic influence during CVDs is becoming more evident as its direct involvement has been reported. The discovery of epigenetic mechanisms, such as DNA methylation and histone modification, suggested that external factors could alter gene expression to modulate human health. These external factors also influence our gut microbiota (GM), which participates in multiple metabolic processes in our body. Evidence suggests a high association of GM with CVDs. Although the exact mechanism remains unclear, the influence of GM over the epigenetic mechanisms could be one potential pathway in CVD etiology. Both epigenetics and GM are dynamic processes and vary with age and environment. Changes in the composition of GM have been found to underlie the pathogenesis of metabolic diseases via modulating epigenetic changes in the form of DNA methylation, histone modifications, and regulation of non-coding RNAs. Several metabolites produced by the GM, including short-chain fatty acids, folates, biotin, and trimethylamine-N-oxide, have the potential to regulate epigenetics, apart from playing a vital role in normal physiological processes. The role of GM and epigenetics in CVDs are promising areas of research, and important insights in the field of early diagnosis and therapeutic approaches might appear soon.
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66
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Fraszczyk E, Thio CHL, Wackers P, Dollé MET, Bloks VW, Hodemaekers H, Picavet HS, Stynenbosch M, Verschuren WMM, Snieder H, Spijkerman AMW, Luijten M. DNA methylation trajectories and accelerated epigenetic aging in incident type 2 diabetes. GeroScience 2022; 44:2671-2684. [PMID: 35947335 PMCID: PMC9768051 DOI: 10.1007/s11357-022-00626-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 07/19/2022] [Indexed: 01/07/2023] Open
Abstract
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.
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Affiliation(s)
- Eliza Fraszczyk
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Chris H L Thio
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Paul Wackers
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Martijn E T Dollé
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Vincent W Bloks
- Department of Pediatrics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Hennie Hodemaekers
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - H Susan Picavet
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Marjolein Stynenbosch
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - W M Monique Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Harold Snieder
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Annemieke M W Spijkerman
- Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Mirjam Luijten
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.
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Hong X, Wu Z, Cao W, Lv J, Yu C, Huang T, Sun D, Liao C, Pang Y, Pang Z, Cong L, Wang H, Wu X, Liu Y, Gao W, Li L. Longitudinal Association of DNA Methylation With Type 2 Diabetes and Glycemic Traits: A 5-Year Cross-Lagged Twin Study. Diabetes 2022; 71:2804-2817. [PMID: 36170668 DOI: 10.2337/db22-0513] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 09/20/2022] [Indexed: 01/11/2023]
Abstract
Investigators of previous cross-sectional epigenome-wide association studies (EWAS) in adults have reported hundreds of 5'-cytosine-phosphate-guanine-3' (CpG) sites associated with type 2 diabetes mellitus (T2DM) and glycemic traits. However, the results from EWAS have been inconsistent, and longitudinal observations of these associations are scarce. Furthermore, few studies have investigated whether DNA methylation (DNAm) could be modified by smoking, drinking, and glycemic traits, which have broad impacts on genome-wide DNAm and result in altering the risk of T2DM. Twin studies provide a valuable tool for epigenetic studies, as twins are naturally matched for genetic information. In this study, we conducted a systematic literature search in PubMed and Embase for EWAS, and 214, 33, and 117 candidate CpG sites were selected for T2DM, HbA1c, and fasting blood glucose (FBG). Based on 1,070 twins from the Chinese National Twin Registry, 67, 17, and 16 CpG sites from previous studies were validated for T2DM, HbA1c, and FBG. Longitudinal review and blood sampling for phenotypic information and DNAm were conducted twice in 2013 and 2018 for 308 twins. A cross-lagged analysis was performed to examine the temporal relationship between DNAm and T2DM or glycemic traits in the longitudinal data. A total of 11 significant paths from T2DM to subsequent DNAm and 15 paths from DNAm to subsequent T2DM were detected, suggesting both directions of associations. For glycemic traits, we detected 17 cross-lagged associations from baseline glycemic traits to subsequent DNAm, and none were from the other cross-lagged direction, indicating that CpG sites may be the consequences, not the causes, of glycemic traits. Finally, a longitudinal mediation analysis was performed to explore the mediation effects of DNAm on the associations of smoking, drinking, and glycemic traits with T2DM. No significant mediations of DNAm in the associations linking smoking and drinking with T2DM were found. In contrast, our study suggested a potential role of DNAm of cg19693031, cg00574958, and cg04816311 in mediating the effect of altered glycemic traits on T2DM.
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Affiliation(s)
- Xuanming Hong
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Zhiyu Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Weihua Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Chunxiao Liao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Zengchang Pang
- Qingdao Center for Disease Control and Prevention, Qingdao, China
| | - Liming Cong
- Zhejiang Center for Disease Control and Prevention, Hangzhou, China
| | - Hua Wang
- Jiangsu Center for Disease Control and Prevention, Nanjing, China
| | - Xianping Wu
- Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Yu Liu
- Heilongjiang Center for Disease Control and Prevention, Harbin, China
| | - Wenjing Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
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Szukiewicz D, Trojanowski S, Kociszewska A, Szewczyk G. Modulation of the Inflammatory Response in Polycystic Ovary Syndrome (PCOS)-Searching for Epigenetic Factors. Int J Mol Sci 2022; 23:ijms232314663. [PMID: 36498989 PMCID: PMC9736994 DOI: 10.3390/ijms232314663] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 11/19/2022] [Accepted: 11/21/2022] [Indexed: 11/25/2022] Open
Abstract
Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women of reproductive age. Despite its incidence, the syndrome is poorly understood and remains underdiagnosed, and female patients are diagnosed with a delay. The heterogenous nature of this complex disorder results from the combined occurrence of genetic, environmental, endocrine, and behavioral factors. Primary clinical manifestations of PCOS are derived from the excess of androgens (anovulation, polycystic ovary morphology, lack of or scanty, irregular menstrual periods, acne and hirsutism), whereas the secondary manifestations include multiple metabolic, cardiovascular, and psychological disorders. Dietary and lifestyle factors play important roles in the development and course of PCOS, which suggests strong epigenetic and environmental influences. Many studies have shown a strong association between PCOS and chronic, low-grade inflammation both in the ovarian tissue and throughout the body. In the vast majority of PCOS patients, elevated values of inflammatory markers or their gene markers have been reported. Development of the vicious cycle of the chronic inflammatory state in PCOS is additionally stimulated by hyperinsulinemia and obesity. Changes in DNA methylation, histone acetylation and noncoding RNA levels are presented in this review in the context of oxidative stress, reactive oxygen species, and inflammatory signaling in PCOS. Epigenetic modulation of androgenic activity in response to inflammatory signaling is also discussed.
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Affiliation(s)
- Dariusz Szukiewicz
- Department of Biophysics, Physiology & Pathophysiology, Faculty of Health Sciences, Medical University of Warsaw, 02-004 Warsaw, Poland
- Correspondence:
| | - Seweryn Trojanowski
- Chair and Department of Obstetrics, Gynecology and Gynecological Oncology, Medical University of Warsaw, 03-242 Warsaw, Poland
| | - Anna Kociszewska
- Chair and Department of Obstetrics, Gynecology and Gynecological Oncology, Medical University of Warsaw, 03-242 Warsaw, Poland
| | - Grzegorz Szewczyk
- Department of Biophysics, Physiology & Pathophysiology, Faculty of Health Sciences, Medical University of Warsaw, 02-004 Warsaw, Poland
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Hawe JS, Saha A, Waldenberger M, Kunze S, Wahl S, Müller-Nurasyid M, Prokisch H, Grallert H, Herder C, Peters A, Strauch K, Theis FJ, Gieger C, Chambers J, Battle A, Heinig M. Network reconstruction for trans acting genetic loci using multi-omics data and prior information. Genome Med 2022; 14:125. [PMID: 36344995 PMCID: PMC9641770 DOI: 10.1186/s13073-022-01124-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 10/11/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Molecular measurements of the genome, the transcriptome, and the epigenome, often termed multi-omics data, provide an in-depth view on biological systems and their integration is crucial for gaining insights in complex regulatory processes. These data can be used to explain disease related genetic variants by linking them to intermediate molecular traits (quantitative trait loci, QTL). Molecular networks regulating cellular processes leave footprints in QTL results as so-called trans-QTL hotspots. Reconstructing these networks is a complex endeavor and use of biological prior information can improve network inference. However, previous efforts were limited in the types of priors used or have only been applied to model systems. In this study, we reconstruct the regulatory networks underlying trans-QTL hotspots using human cohort data and data-driven prior information. METHODS We devised a new strategy to integrate QTL with human population scale multi-omics data. State-of-the art network inference methods including BDgraph and glasso were applied to these data. Comprehensive prior information to guide network inference was manually curated from large-scale biological databases. The inference approach was extensively benchmarked using simulated data and cross-cohort replication analyses. Best performing methods were subsequently applied to real-world human cohort data. RESULTS Our benchmarks showed that prior-based strategies outperform methods without prior information in simulated data and show better replication across datasets. Application of our approach to human cohort data highlighted two novel regulatory networks related to schizophrenia and lean body mass for which we generated novel functional hypotheses. CONCLUSIONS We demonstrate that existing biological knowledge can improve the integrative analysis of networks underlying trans associations and generate novel hypotheses about regulatory mechanisms.
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Affiliation(s)
- Johann S Hawe
- Institute of Computational Biology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,German Heart Centre Munich, Department of Cardiology, Technical University Munich, Munich, Germany.,Department of Informatics, Technical University of Munich, Garching, Germany
| | - Ashis Saha
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany
| | - Sonja Kunze
- Research Unit of Molecular Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany
| | - Simone Wahl
- Research Unit of Molecular Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,IBE, Faculty of Medicine, LMU Munich, 81377, Munich, Germany.,Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany.,Department of Internal Medicine I (Cardiology), Hospital of the Ludwig-Maximilians-University (LMU) Munich, Munich, Germany
| | - Holger Prokisch
- Institute of Human Genetics, School of Medicine, Technische Universität München, Munich, Germany
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,Institute of Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Christian Herder
- German Center for Diabetes Research (DZD), Neuherberg, Germany.,Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany.,Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Annette Peters
- Institute of Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany.,Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Fabian J Theis
- Department of Informatics, Technical University of Munich, Garching, Germany.,Department of Mathematics, Technical University of Munich, Garching, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,Institute of Epidemiology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - John Chambers
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.,Lee Kong Chian School of Medicine, Nanyang Technological University, 308232, Singapore, Singapore
| | - Alexis Battle
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA.,Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Matthias Heinig
- Institute of Computational Biology, German Research Center for Environmental Health, HelmholtzZentrum München, Neuherberg, Germany. .,Department of Informatics, Technical University of Munich, Garching, Germany. .,Munich Heart Association, Partner Site Munich, DZHK (German Centre for Cardiovascular Research), 10785, Berlin, Germany.
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Abstract
Data generated over nearly two decades clearly demonstrate the importance of epigenetic modifications and mechanisms in the pathogenesis of type 2 diabetes. However, the role of pharmacoepigenetics in type 2 diabetes is less well established. The field of pharmacoepigenetics covers epigenetic biomarkers that predict response to therapy, therapy-induced epigenetic alterations as well as epigenetic therapies including inhibitors of epigenetic enzymes. Not all individuals with type 2 diabetes respond to glucose-lowering therapies in the same way, and there is therefore a need for clinically useful biomarkers that discriminate responders from non-responders. Blood-based epigenetic biomarkers may be useful for this purpose. There is also a need for a better understanding of whether existing glucose-lowering therapies exert their function partly through therapy-induced epigenetic alterations. Finally, epigenetic enzymes may be drug targets for type 2 diabetes. Here, I discuss whether pharmacoepigenetics is clinically relevant for type 2 diabetes based on studies addressing this topic.
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Affiliation(s)
- Charlotte Ling
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden.
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71
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Zhang X, Ammous F, Lin L, Ratliff SM, Ware EB, Faul JD, Zhao W, Kardia SLR, Smith JA. The Interplay of Epigenetic, Genetic, and Traditional Risk Factors on Blood Pressure: Findings from the Health and Retirement Study. Genes (Basel) 2022; 13:1959. [PMID: 36360196 PMCID: PMC9689874 DOI: 10.3390/genes13111959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 10/11/2022] [Accepted: 10/19/2022] [Indexed: 01/21/2023] Open
Abstract
The epigenome likely interacts with traditional and genetic risk factors to influence blood pressure. We evaluated whether 13 previously reported DNA methylation sites (CpGs) are associated with systolic (SBP) or diastolic (DBP) blood pressure, both individually and aggregated into methylation risk scores (MRS), in 3070 participants (including 437 African ancestry (AA) and 2021 European ancestry (EA), mean age = 70.5 years) from the Health and Retirement Study. Nine CpGs were at least nominally associated with SBP and/or DBP after adjusting for traditional hypertension risk factors (p < 0.05). MRSSBP was positively associated with SBP in the full sample (β = 1.7 mmHg per 1 standard deviation in MRSSBP; p = 2.7 × 10-5) and in EA (β = 1.6; p = 0.001), and MRSDBP with DBP in the full sample (β = 1.1; p = 1.8 × 10-6), EA (β = 1.1; p = 7.2 × 10-5), and AA (β = 1.4; p = 0.03). The MRS and BP-genetic risk scores were independently associated with blood pressure in EA. The effects of both MRSs were weaker with increased age (pinteraction < 0.01), and the effect of MRSDBP was higher among individuals with at least some college education (pinteraction = 0.02). In AA, increasing MRSSBP was associated with higher SBP in females only (pinteraction = 0.01). Our work shows that MRS is a potential biomarker of blood pressure that may be modified by traditional hypertension risk factors.
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Affiliation(s)
- Xinman Zhang
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Farah Ammous
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Lisha Lin
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Scott M. Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Erin B. Ware
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
| | - Jessica D. Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
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72
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Titanji BK, Lee M, Wang Z, Chen J, Hui Q, Lo Re III V, So-Armah K, Justice AC, Xu K, Freiberg M, Gwinn M, Marconi VC, Sun YV. Epigenome-wide association study of biomarkers of liver function identifies albumin-associated DNA methylation sites among male veterans with HIV. Front Genet 2022; 13:1020871. [PMID: 36303554 PMCID: PMC9592923 DOI: 10.3389/fgene.2022.1020871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 09/22/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Liver disease (LD) is an important cause of morbidity and mortality for people with HIV (PWH). The molecular factors linked with LD in PWH are varied and incompletely characterized. We performed an epigenome-wide association study (EWAS) to identify associations between DNA methylation (DNAm) and biomarkers of liver function-aspartate transaminase, alanine transaminase, albumin, total bilirubin, platelet count, FIB-4 score, and APRI score-in male United States veterans with HIV. Methods: Blood samples and clinical data were obtained from 960 HIV-infected male PWH from the Veterans Aging Cohort Study. DNAm was assessed using the Illumina 450K or the EPIC 850K array in two mutually exclusive subsets. We performed a meta-analysis for each DNAm site measured by either platform. We also examined the associations between four measures of DNAm age acceleration (AA) and liver biomarkers. Results: Nine DNAm sites were positively associated with serum albumin in the meta-analysis of the EPIC and 450K EWAS after correcting for multiple testing. Four DNAm sites (cg16936953, cg18942579, cg01409343, and cg12054453), annotated within the TMEM49 and four of the remaining five sites (cg18181703, cg03546163, cg20995564, and cg23966214) annotated to SOCS3, FKBP5, ZEB2, and SAMD14 genes, respectively. The DNAm site, cg12992827, was not annotated to any known coding sequence. No significant associations were detected for the other six liver biomarkers. Higher PhenoAA was significantly associated with lower level of serum albumin (β = -0.007, p-value = 8.6 × 10-4, CI: -0.011116, -0.002884). Conclusion: We identified epigenetic associations of both individual DNAm sites and DNAm AA with liver function through serum albumin in men with HIV. Further replication analyses in independent cohorts are warranted to confirm the epigenetic mechanisms underlying liver function and LD in PWH.
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Affiliation(s)
- Boghuma K. Titanji
- Division of Infectious Disease, Emory School of Medicine, Atlanta, GA, United States
| | - Mitch Lee
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Zeyuan Wang
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Junyu Chen
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Qin Hui
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Vincent Lo Re III
- Division of Infectious Diseases Department of Medicine and Center for Clinical Epidemiology and Biostatistics Perelman School of Medicine University of Pennsylvania, Philadelphia, PA, United States
| | - Kaku So-Armah
- Boston University Medical School, Boston, MA, United States
| | - Amy C. Justice
- Connecticut Veteran Health System, West Haven, CT, United States,Yale University School of Medicine, New Haven, CT, United States
| | - Ke Xu
- Connecticut Veteran Health System, West Haven, CT, United States,Yale University School of Medicine, New Haven, CT, United States
| | - Matthew Freiberg
- Cardiovascular Medicine Division and Tennessee Valley Healthcare System, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Marta Gwinn
- Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Vincent C. Marconi
- Division of Infectious Disease, Emory School of Medicine, Atlanta, GA, United States,Atlanta Veterans Affairs Health Care System, Decatur, GA, United States,Hubert Department of Global Health, Rollins School of Public Health, Atlanta, GA, United States,Emory Vaccine Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States
| | - Yan V. Sun
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States,Atlanta Veterans Affairs Health Care System, Decatur, GA, United States,*Correspondence: Yan V. Sun,
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73
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Marttila S, Tamminen H, Rajić S, Mishra PP, Lehtimäki T, Raitakari O, Kähönen M, Kananen L, Jylhävä J, Hägg S, Delerue T, Peters A, Waldenberger M, Kleber ME, März W, Luoto R, Raitanen J, Sillanpää E, Laakkonen EK, Heikkinen A, Ollikainen M, Raitoharju E. Methylation status of VTRNA2-1/ nc886 is stable across populations, monozygotic twin pairs and in majority of tissues. Epigenomics 2022; 14:1105-1124. [PMID: 36200237 DOI: 10.2217/epi-2022-0228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aims & methods: The aim of this study was to characterize the methylation level of a polymorphically imprinted gene, VTRNA2-1/nc886, in human populations and somatic tissues.48 datasets, consisting of more than 30 tissues and >30,000 individuals, were used. Results: nc886 methylation status is associated with twin status and ethnic background, but the variation between populations is limited. Monozygotic twin pairs present concordant methylation, whereas ∼30% of dizygotic twin pairs present discordant methylation in the nc886 locus. The methylation levels of nc886 are uniform across somatic tissues, except in cerebellum and skeletal muscle. Conclusion: The nc886 imprint may be established in the oocyte, and, after implantation, the methylation status is stable, excluding a few specific tissues.
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Affiliation(s)
- Saara Marttila
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Gerontology Research Center, Tampere University, Tampere, 33014, Finland
| | - Hely Tamminen
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Sonja Rajić
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Fimlab Laboratories, Arvo Ylpön katu 4, Tampere, 33520, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Fimlab Laboratories, Arvo Ylpön katu 4, Tampere, 33520, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku & Turku University Hospital, Turku, 20014, Finland.,Research Centre of Applied & Preventive Cardiovascular Medicine, University of Turku, Turku, 20014, Finland.,Department of Clinical Physiology & Nuclear Medicine, Turku University Hospital, Turku, 20014, Finland
| | - Mika Kähönen
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Department of Clinical Physiology, Tampere University Hospital, Tampere, 33521, Finland
| | - Laura Kananen
- Faculty of Medicine & Health Technology, & Gerontology Research Center, Tampere University, Arvo Ylpön katu 34, Tampere, 33520,Finland.,Department of Medical Epidemiology & Biostatistics, Karolinska Institutet, Stockholm, 171 77, Sweden.,Faculty of Social Sciences (Health Sciences), & Gerontology Research Center, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Juulia Jylhävä
- Department of Medical Epidemiology & Biostatistics, Karolinska Institutet, Stockholm, 171 77, Sweden.,Faculty of Social Sciences (Health Sciences), & Gerontology Research Center, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Sara Hägg
- Department of Medical Epidemiology & Biostatistics, Karolinska Institutet, Stockholm, 171 77, Sweden
| | - Thomas Delerue
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, D-85764,, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, D-85764, Germany.,German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, D-85764,, Germany.,German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Marcus E Kleber
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, 68167, Germany.,SYNLAB MVZ Humangenetik Mannheim, Mannheim, Germany
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, 68167, Germany.,Competence Cluster for Nutrition & Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig, Jena, 07743, Germany.,SYNLAB Academy, SYNLAB Holding Deutschland GmbH, Augsburg, 86156, Germany.,Clinical Institute of Medical & Chemical Laboratory Diagnostics, Medical University of Graz, Graz, 8010, Austria
| | - Riitta Luoto
- The Social Insurance Institute of Finland (Kela), Helsinki, 00250, Finland.,The UKK Institute for Health Promotion Research, Kaupinpuistonkatu 1, Tampere, 33500, Finland
| | - Jani Raitanen
- The UKK Institute for Health Promotion Research, Kaupinpuistonkatu 1, Tampere, 33500, Finland.,Faculty of Social Sciences (Health Sciences), Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Elina Sillanpää
- Gerontology Research Center & Faculty of Sport & Health Sciences, University of Jyväskylä, Jyväskylä, 40014, Finland.,Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00014, Finland
| | - Eija K Laakkonen
- Gerontology Research Center & Faculty of Sport & Health Sciences, University of Jyväskylä, Jyväskylä, 40014, Finland
| | - Aino Heikkinen
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00014, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00014, Finland
| | - Emma Raitoharju
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
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74
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Fernandes V, Preeti K, Sood A, Nair KP, Khan S, Rao BSS, Khatri DK, Singh SB. Neuroepigenetic Changes in DNA Methylation Affecting Diabetes-Induced Cognitive Impairment. Cell Mol Neurobiol 2022:10.1007/s10571-022-01278-5. [PMID: 36138280 DOI: 10.1007/s10571-022-01278-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 08/22/2022] [Indexed: 11/25/2022]
Abstract
Chronic diabetic conditions have been associated with certain cerebral complications, that include neurobehavioral dysfunctional patterns and morphological alterations of neurons, especially the hippocampus. Neuroanatomical studies done by the authors have shown decreased total dendritic length, intersections, dendritic length per branch order and nodes in the CA1 hippocampal region of the diabetic brain as compared to its normal control group, indicating reduced dendritic arborization of the hippocampal CA1 neurons. Epigenetic alterations in the brain are well known to affect age-associated disorders, however its association with the evolving diabetes-induced damage in the brain is still not fully understood. DNA hypermethylation within the neurons, tend to silent the gene expression of several regulatory proteins. The findings in the study have shown an increase in global DNA methylation in palmitic acid-induced lipotoxic Neuro-2a cells as well as within the diabetic mice brain. Inhibiting DNA methylation, restored the levels of HSF1 and certain HSPs, suggesting plausible effect of DNMTs in maintaining the proteostasis and synaptic fidelity. Neuroinflammation, as exhibited by the astrocyte activation (GFAP), were further significantly decreased in the 5-azadeoxycytidine group (DNMT inhibitor). This was further evidenced by decrease in proinflammatory cytokines TNF⍺, IL-6, and mediators iNOS and Phospho-NFkB. Our results suggest that changes in DNA methylation advocate epigenetic dysregulation and its involvement in disrupting the synaptic exactitude in the hippocampus of diabetic mice model, providing an insight into the pathophysiology of diabetes-induced neuroepigenetic changes.
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Affiliation(s)
- Valencia Fernandes
- Department of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research (NIPER), Hyderabad, Telangana, 500037, India
| | - Kumari Preeti
- Department of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research (NIPER), Hyderabad, Telangana, 500037, India
| | - Anika Sood
- Department of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research (NIPER), Hyderabad, Telangana, 500037, India
| | - Kala P Nair
- Department of Neurophysiology, National Institute of Mental Health and Neuroscience (NIMHANS), Bengaluru, Karnataka, 560029, India
| | - Sabiya Khan
- Department of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research (NIPER), Hyderabad, Telangana, 500037, India
| | - B S Shankaranarayana Rao
- Department of Neurophysiology, National Institute of Mental Health and Neuroscience (NIMHANS), Bengaluru, Karnataka, 560029, India
| | - Dharmendra Kumar Khatri
- Department of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research (NIPER), Hyderabad, Telangana, 500037, India.
| | - Shashi Bala Singh
- Department of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research (NIPER), Hyderabad, Telangana, 500037, India.
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75
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Li Y, Liu X, Tu R, Hou J, Zhuang G. Mendelian Randomization Analysis of the Association of SOCS3 Methylation with Abdominal Obesity. Nutrients 2022; 14:nu14183824. [PMID: 36145200 PMCID: PMC9503364 DOI: 10.3390/nu14183824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 09/06/2022] [Accepted: 09/13/2022] [Indexed: 11/16/2022] Open
Abstract
This study was conducted to evaluate the potential causality association of SOCS3 methylation with abdominal obesity using Mendelian randomization. A case-control study, including 1064 participants, was carried out on Chinese subjects aged 18 to 79. MethylTargetTM was used to detect the methylation level for each CpG site of SOCS3, and SNPscan® was applied to measure the single-nucleotide polymorphism (SNP) genotyping. The logistic regression was used to assess the relationship of SOCS3 methylation level and SNP genotyping with abdominal obesity. Three types of Mendelian randomization methods were implemented to examine the potential causality between SOCS3 methylation and obesity based on the SNP of SOCS3 as instrumental variables. SOCS3 methylation levels were inversely associated with abdominal obesity in five CpG sites (effect estimates ranged from 0.786 (Chr17:76356054) to 0.851 (Chr17:76356084)), and demonstrated positively association in 18 CpG sites (effect estimates ranged from 1.243 (Chr17:76354990) to 1.325 (Chr17:76355061)). The causal relationship between SOCS3 methylation and abdominal obesity was found using the maximum-likelihood method and Mendelian randomization method of penalized inverse variance weighted (MR-IVW), and the β values (95% CI) were 5.342 (0.215, 10.469) and 4.911 (0.259, 9.564), respectively. The causality was found between the SOCS3 methylation level and abdominal obesity in the Chinese population.
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Affiliation(s)
- Yuqian Li
- Departmentof Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Centre, Xi’an 710061, China
- Department of Clinical Pharmacology, School of Pharmaceutical Science, Zhengzhou University, Zhengzhou 450052, China
| | - Xiaotian Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou 450052, China
| | - Runqi Tu
- Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou 450052, China
| | - Jian Hou
- Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou 450052, China
| | - Guihua Zhuang
- Departmentof Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Centre, Xi’an 710061, China
- Correspondence: ; Tel.: +86-29-826-551-03
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76
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Muilwijk M, Loh M, Mahmood S, Palaniswamy S, Siddiqui S, Silva W, Frost GS, Gage HM, Jarvelin MR, Rannan-Eliya RP, Ahmad S, Jha S, Kasturiratne A, Katulanda P, Khawaja KI, Kooner JS, Wickremasinghe AR, van Valkengoed IGM, Chambers JC. The iHealth-T2D study: a cluster randomised trial for the prevention of type 2 diabetes amongst South Asians with central obesity and prediabetes-a statistical analysis plan. Trials 2022; 23:755. [PMID: 36068618 PMCID: PMC9450360 DOI: 10.1186/s13063-022-06667-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 08/18/2022] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND South Asians are at high risk of type 2 diabetes (T2D). Lifestyle modification is effective at preventing T2D amongst South Asians, but the approaches to screening and intervention are limited by high costs, poor scalability and thus low impact on T2D burden. An intensive family-based lifestyle modification programme for the prevention of T2D was developed. The aim of the iHealth-T2D trial is to compare the effectiveness of this programme with usual care. METHODS The iHealth-T2D trial is designed as a cluster randomised controlled trial (RCT) conducted at 120 sites across India, Pakistan, Sri Lanka and the UK. A total of 3682 South Asian men and women with age between 40 and 70 years without T2D but at elevated risk for T2D [defined by central obesity (waist circumference ≥ 95 cm in Sri Lanka or ≥ 100 cm in India, Pakistan and the UK) and/or prediabetes (HbA1c ≥ 6.0%)] were included in the trial. Here, we describe in detail the statistical analysis plan (SAP), which was finalised before outcomes were available to the investigators. The primary outcome will be evaluated after 3 years of follow-up after enrolment to the study and is defined as T2D incidence in the intervention arm compared to usual care. Secondary outcomes are evaluated both after 1 and 3 years of follow-up and include biochemical measurements, anthropometric measurements, behavioural components and treatment compliance. DISCUSSION The iHealth-T2D trial will provide evidence of whether an intensive family-based lifestyle modification programme for South Asians who are at high risk for T2D is effective in the prevention of T2D. The data from the trial will be analysed according to this pre-specified SAP. ETHICS AND DISSEMINATION The trial was approved by the international review board of each participating study site. Study findings will be disseminated through peer-reviewed publications and in conference presentations. TRIAL REGISTRATION EudraCT 2016-001,350-18 . Registered on 14 April 2016. CLINICALTRIALS gov NCT02949739 . Registered on 31 October 2016.
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Affiliation(s)
- Mirthe Muilwijk
- Department of Public Health, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Meibergdreef 9, Amsterdam, The Netherlands.
- Amsterdam Public Health, Health Behaviours & Cardiovascular Diseases, Amsterdam Cardiovascular Sciences, Diabetes & Metabolism, Amsterdam, The Netherlands.
| | - Marie Loh
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, UK
| | - Sara Mahmood
- Department of Endocrinology & Metabolism, Services Institute of Medical Sciences, Services Institute of Medical Sciences, Services Hospital, Ghaus Ul Azam, Jail Road 54700, Lahore, Pakistan
| | - Saranya Palaniswamy
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Samreen Siddiqui
- Max Healthcare, Institute of Endocrinology, Diabetes and Metabolism, Max Super Speciality Hospital, 2, Press Enclave Road, Skaet, New Delhi, 110017, India
| | - Wnurinham Silva
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, UK
| | - Gary S Frost
- Faculty of Medicine, Imperial College London, Hammersmith Campus, DuCane Road, London, W12 ONN, UK
| | - Heather M Gage
- Department of Clinical and Experimental Medicine, Surrey Health Economics Centre, University of Surrey, Leggett Building, Daphne Jackson Road, Guildford, Surrey, GU2 7WG, UK
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, University of Oulu, Oulu, Finland
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, Kingston Lane, Uxbridge, UB8 3PH, Middlesex, UK
| | | | - Sajjad Ahmad
- Punjab Institute of Cardiology, Punjab Institute of Cardiology, Jail Road, Shadman, Lahore, Punjab, Pakistan
| | - Sujeet Jha
- Max Healthcare, Institute of Endocrinology, Diabetes and Metabolism, Max Super Speciality Hospital, 2, Press Enclave Road, Skaet, New Delhi, 110017, India
| | - Anuradhani Kasturiratne
- Faculty of Medicine, University of Kelaniya, Thalagolla Road, PO Box 06, Ragama, 11010, Sri Lanka
| | - Prasad Katulanda
- Department of Clinical Medicine, Faculty of Medicine, University of Colombo, 25 Kynsey Rd, Colombo, 00800, Sri Lanka
| | - Khadija I Khawaja
- Department of Endocrinology & Metabolism, Services Institute of Medical Sciences, Services Institute of Medical Sciences, Services Hospital, Ghaus Ul Azam, Jail Road 54700, Lahore, Pakistan
| | - Jaspal S Kooner
- London Northwest University Healthcare NHS Trust, Uxbridge Road, Southall, UB1 3HW, Middlesex, UK
- National Heart and Lung Institute, Imperial College London, Hammersmith Campus, DuCane Road, London, W12 ONN, UK
| | - Ananda R Wickremasinghe
- Faculty of Medicine, University of Kelaniya, Thalagolla Road, PO Box 06, Ragama, 11010, Sri Lanka
| | - Irene G M van Valkengoed
- Department of Public Health, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health Research Institute, Meibergdreef 9, Amsterdam, The Netherlands
- Amsterdam Public Health, Health Behaviours & Cardiovascular Diseases, Amsterdam Cardiovascular Sciences, Diabetes & Metabolism, Amsterdam, The Netherlands
| | - John C Chambers
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, UK
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Liu Y, Wu Y, Jiang M. The emerging roles of PHOSPHO1 and its regulated phospholipid homeostasis in metabolic disorders. Front Physiol 2022; 13:935195. [PMID: 35957983 PMCID: PMC9360546 DOI: 10.3389/fphys.2022.935195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 07/07/2022] [Indexed: 11/25/2022] Open
Abstract
Emerging evidence suggests that phosphoethanolamine/phosphocholine phosphatase 1 (PHOSPHO1), a specific phosphoethanolamine and phosphocholine phosphatase, is involved in energy metabolism. In this review, we describe the structure and regulation of PHOSPHO1, as well as current knowledge about the role of PHOSPHO1 and its related phospholipid metabolites in regulating energy metabolism. We also examine mechanistic evidence of PHOSPHO1- and phospholipid-mediated regulation of mitochondrial and lipid droplets functions in the context of metabolic homeostasis, which could be potentially targeted for treating metabolic disorders.
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Affiliation(s)
- Yi Liu
- Department of Pharmacology, School of Basic Medical Sciences, Capital Medical University, Beijing, China
| | - Yingting Wu
- Department of Pharmacology, School of Basic Medical Sciences, Capital Medical University, Beijing, China
| | - Mengxi Jiang
- Department of Pharmacology, School of Basic Medical Sciences, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
- *Correspondence: Mengxi Jiang,
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78
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Christiansen C, Tomlinson M, Eliot M, Nilsson E, Costeira R, Xia Y, Villicaña S, Mompeo O, Wells P, Castillo-Fernandez J, Potier L, Vohl MC, Tchernof A, Moustafa JES, Menni C, Steves CJ, Kelsey K, Ling C, Grundberg E, Small KS, Bell JT. Adipose methylome integrative-omic analyses reveal genetic and dietary metabolic health drivers and insulin resistance classifiers. Genome Med 2022; 14:75. [PMID: 35843982 PMCID: PMC9290282 DOI: 10.1186/s13073-022-01077-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 06/21/2022] [Indexed: 12/05/2022] Open
Abstract
BACKGROUND There is considerable evidence for the importance of the DNA methylome in metabolic health, for example, a robust methylation signature has been associated with body mass index (BMI). However, visceral fat (VF) mass accumulation is a greater risk factor for metabolic disease than BMI alone. In this study, we dissect the subcutaneous adipose tissue (SAT) methylome signature relevant to metabolic health by focusing on VF as the major risk factor of metabolic disease. We integrate results with genetic, blood methylation, SAT gene expression, blood metabolomic, dietary intake and metabolic phenotype data to assess and quantify genetic and environmental drivers of the identified signals, as well as their potential functional roles. METHODS Epigenome-wide association analyses were carried out to determine visceral fat mass-associated differentially methylated positions (VF-DMPs) in SAT samples from 538 TwinsUK participants. Validation and replication were performed in 333 individuals from 3 independent cohorts. To assess functional impacts of the VF-DMPs, the association between VF and gene expression was determined at the genes annotated to the VF-DMPs and an association analysis was carried out to determine whether methylation at the VF-DMPs is associated with gene expression. Further epigenetic analyses were carried out to compare methylation levels at the VF-DMPs as the response variables and a range of different metabolic health phenotypes including android:gynoid fat ratio (AGR), lipids, blood metabolomic profiles, insulin resistance, T2D and dietary intake variables. The results from all analyses were integrated to identify signals that exhibit altered SAT function and have strong relevance to metabolic health. RESULTS We identified 1181 CpG positions in 788 genes to be differentially methylated with VF (VF-DMPs) with significant enrichment in the insulin signalling pathway. Follow-up cross-omic analysis of VF-DMPs integrating genetics, gene expression, metabolomics, diet, and metabolic traits highlighted VF-DMPs located in 9 genes with strong relevance to metabolic disease mechanisms, with replication of signals in FASN, SREBF1, TAGLN2, PC and CFAP410. PC methylation showed evidence for mediating effects of diet on VF. FASN DNA methylation exhibited putative causal effects on VF that were also strongly associated with insulin resistance and methylation levels in FASN better classified insulin resistance (AUC=0.91) than BMI or VF alone. CONCLUSIONS Our findings help characterise the adiposity-associated methylation signature of SAT, with insights for metabolic disease risk.
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Affiliation(s)
- Colette Christiansen
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
| | - Max Tomlinson
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- Department of Medical & Molecular Genetics, King's College London, London, UK
| | - Melissa Eliot
- Department of Epidemiology, Brown University School of Public Health, Providence, R.I., USA
| | - Emma Nilsson
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
| | - Ricardo Costeira
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Yujing Xia
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Sergio Villicaña
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Olatz Mompeo
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Philippa Wells
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | | | - Louis Potier
- Diabetology Department, Bichat Hospital, AP-HP, Université de Paris, Paris, France
| | - Marie-Claude Vohl
- Institute of Nutrition and Functional Foods (INAF), Université Laval, Québec, QC, Canada
| | - Andre Tchernof
- Québec Heart and Lung Institute, Université Laval, Québec, QC, Canada
| | | | - Cristina Menni
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Claire J Steves
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Karl Kelsey
- Department of Epidemiology, Brown University School of Public Health, Providence, R.I., USA
| | - Charlotte Ling
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
| | - Elin Grundberg
- Genomic Medicine Center, Children's Mercy Research Institute, Children's Mercy Kansas City, Kansas City, MO, 64108, USA
| | - Kerrin S Small
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
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Chilunga FP, Meeks KAC, Henneman P, Agyemang C, Doumatey AP, Rotimi CN, Adeyemo AA. An epigenome-wide association study of insulin resistance in African Americans. Clin Epigenetics 2022; 14:88. [PMID: 35836279 PMCID: PMC9281172 DOI: 10.1186/s13148-022-01309-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 07/04/2022] [Indexed: 11/18/2022] Open
Abstract
Background African Americans have a high risk for type 2 diabetes (T2D) and insulin resistance. Studies among other population groups have identified DNA methylation loci associated with insulin resistance, but data in African Americans are lacking. Using DNA methylation profiles of blood samples obtained from the Illumina Infinium® HumanMethylation450 BeadChip, we performed an epigenome-wide association study to identify DNA methylation loci associated with insulin resistance among 136 non-diabetic, unrelated African American men (mean age 41.6 years) from the Howard University Family Study. Results We identified three differentially methylated positions (DMPs) for homeostatic model assessment of insulin resistance (HOMA-IR) at 5% FDR. One DMP (cg14013695, HOXA5) is a known locus among Mexican Americans, while the other two DMPs are novel—cg00456326 (OSR1; beta = 0.027) and cg20259981 (ST18; beta = 0.010). Although the cg00456326 DMP is novel, the OSR1 gene has previously been found associated with both insulin resistance and T2D in Europeans. The genes HOXA5 and ST18 have been implicated in biological processes relevant to insulin resistance. Differential methylation at the significant HOXA5 and OSR1 DMPs is associated with differences in gene expression in the iMETHYL database. Analysis of differentially methylated regions (DMRs) did not identify any epigenome-wide DMRs for HOMA-IR. We tested transferability of HOMA-IR associated DMPs from five previous EWAS in Mexican Americans, Indian Asians, Europeans, and European ancestry Americans. Out of the 730 previously reported HOMA-IR DMPs, 47 (6.4%) were associated with HOMA-IR in this cohort of African Americans. Conclusions The findings from our study suggest substantial differences in DNA methylation patterns associated with insulin resistance across populations. Two of the DMPs we identified in African Americans have not been reported in other populations, and we found low transferability of HOMA-IR DMPs reported in other populations in African Americans. More work in African-ancestry populations is needed to confirm our findings as well as functional analyses to understand how such DNA methylation alterations contribute to T2D pathology. Supplementary Information The online version contains supplementary material available at 10.1186/s13148-022-01309-4.
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Affiliation(s)
- Felix P Chilunga
- Department of Public & Occupational Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Karlijn A C Meeks
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Peter Henneman
- Department of Human Genetics, Amsterdam Reproduction & Development Research Institute, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Charles Agyemang
- Department of Public & Occupational Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Ayo P Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Adebowale A Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
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Schrader S, Perfilyev A, Ahlqvist E, Groop L, Vaag A, Martinell M, García-Calzón S, Ling C. Novel Subgroups of Type 2 Diabetes Display Different Epigenetic Patterns That Associate With Future Diabetic Complications. Diabetes Care 2022; 45:1621-1630. [PMID: 35607770 PMCID: PMC9274219 DOI: 10.2337/dc21-2489] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 04/05/2022] [Indexed: 02/03/2023]
Abstract
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.
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Affiliation(s)
- Silja Schrader
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
| | - Alexander Perfilyev
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
| | - Emma Ahlqvist
- Genomics, Diabetes and Endocrinology Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Leif Groop
- Genomics, Diabetes and Endocrinology Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Allan Vaag
- Type 2 Diabetes Biology Research, Steno Diabetes Center, Copenhagen, Denmark
| | - Mats Martinell
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden.,Academic Primary Care Centre, Uppsala, Sweden
| | - Sonia García-Calzón
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden.,Department of Food Science and Physiology, University of Navarra, Pamplona, Spain
| | - Charlotte Ling
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
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Ling C, Bacos K, Rönn T. Epigenetics of type 2 diabetes mellitus and weight change - a tool for precision medicine? Nat Rev Endocrinol 2022; 18:433-448. [PMID: 35513492 DOI: 10.1038/s41574-022-00671-w] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/29/2022] [Indexed: 12/12/2022]
Abstract
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.
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Affiliation(s)
- Charlotte Ling
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden.
| | - Karl Bacos
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
| | - Tina Rönn
- Epigenetics and Diabetes Unit, Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Scania University Hospital, Malmö, Sweden
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82
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Jiang M, Wang X, Gao X, Cardenas A, Baccarelli AA, Guo X, Huang J, Wu S. Association of DNA methylation in circulating CD4 +T cells with short-term PM 2.5 pollution waves: A quasi-experimental study of healthy young adults. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 239:113634. [PMID: 35617899 DOI: 10.1016/j.ecoenv.2022.113634] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Revised: 04/15/2022] [Accepted: 05/09/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Fine particulate matter (PM2.5) is a modifiable environmental risk factor with established adverse effects on human health. However, associations between acute PM2.5 fluctuation and DNA methylation remain unknown. METHODS A quasi-experimental study utilizing naturally occurring PM2.5 pollution waves (PPWs) was conducted on 32 healthy young adults. Repeated follow-up measurements were performed and participants served as their own controls before, during, and after PPWs. Exposure measurements including indoor and ambient PM2.5 levels, and equivalent personal PM2.5 exposure were further estimated based on the time-location information. DNA methylation profiles of circulating CD4+T cells were obtained using Illumina HumanMethylationEPIC BeadChip. Linear mixed-effect models were applied to estimate the associations between two scenarios (during-PPWs vs. pre-PPWs periods and during-PPWs vs. post-PPWs periods) and methylation level of each CpG site. We further validated their associations with the personal PM2.5 exposure, and GO and KEGG analyses and mediation analysis were conducted accordingly. RESULTS Data from 26 participants were included in final analysis after quality control. Short-term high PM2.5 exposure was associated with DNA methylation changes of participants. Nine differently methylated CpG sites were not only significantly associated with PPWs periods but also with personal PM2.5 exposure in 24-h prior to the health examinations (p < 0.01). Gene ontology analysis found that five sites were associated with two pathways relating to membrane protein synthesis. PM2.5-related changes in CpG sites were mediated by sP-selectin, 8-isoPGF2α, EGF, GRO, IL-15, and IFN-α2, with mediated proportions ranging from 9.65% to 23.40%. CONCLUSIONS This is the first quasi-experimental study showing that short-term high PM2.5 exposure could alter the DNA methylation of CD4+T cells, which provided valuable information for further exploring underlying biological mechanisms and epigenetic biomarkers for PM2.5-related acute health effects.
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Affiliation(s)
- Meijie Jiang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Xinmei Wang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Xu Gao
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health and Center for Computational Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Xinbiao Guo
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Jing Huang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China.
| | - Shaowei Wu
- Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China; Key Laboratory of Trace Elements and Endemic Diseases in Ministry of Health, Xi'an, Shaanxi, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, Shaanxi, China.
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83
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Holzapfel C, Waldenberger M, Lorkowski S, Daniel H. Genetics and Epigenetics in Personalized Nutrition: Evidence, Expectations and Experiences. Mol Nutr Food Res 2022; 66:e2200077. [PMID: 35770348 DOI: 10.1002/mnfr.202200077] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 05/17/2022] [Indexed: 11/10/2022]
Abstract
With the presentation of the blueprint of the first human genome in 2001 and the advent of technologies for high-throughput genetic analysis, personalized nutrition (PN) became a new scientific field and the first commercial offerings of genotype-based nutrition advice emerged at the same time. Here, we summarize the state of evidence for the effect of genetic and epigenetic factors in the development of obesity, the metabolic syndrome and resulting illnesses such as non-insulin-dependent diabetes mellitus and cardiovascular diseases. We also critically value the concepts of PN that were built around the new genetic avenue from both the academic and a commercial perspective and their effectiveness in causing sustained changes in diet, lifestyle and for improving health. Despite almost 20 years of research and commercial direct-to-consumer offerings, evidence for the success of gene-based dietary recommendations is still generally lacking. This calls for new concepts of future PN solutions that incorporate more phenotypic measures and provide a panel of instruments (e.g., self- and bio-monitoring tools, feedback systems, algorithms based on artificial intelligence) that increases compliance based on the individual´s physical and social environment and value system. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Christina Holzapfel
- Institute for Nutritional Medicine, Technical University of Munich, School of Medicine, Munich, Germany
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Stefan Lorkowski
- Institute of Nutritional Sciences and Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig, Friedrich Schiller University, Jena, Germany
| | - Hannelore Daniel
- Professor emeritus, Technical University of Munich, Freising, Germany
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Cullell N, Soriano-Tárraga C, Gallego-Fábrega C, Cárcel-Márquez J, Torres-Águila NP, Muiño E, Lledós M, Llucià-Carol L, Esteller M, Castro de Moura M, Montaner J, Fernández-Sanlés A, Elosua R, Delgado P, Martí-Fábregas J, Krupinski J, Roquer J, Jiménez-Conde J, Fernández-Cadenas I. DNA Methylation and Ischemic Stroke Risk: An Epigenome-Wide Association Study. Thromb Haemost 2022; 122:1767-1778. [PMID: 35717949 DOI: 10.1055/s-0042-1749328] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
BACKGROUND Ischemic stroke (IS) risk heritability is partly explained by genetics. Other heritable factors, such as epigenetics, could explain an unknown proportion of the IS risk. The objective of this study is to evaluate DNA methylation association with IS using epigenome-wide association studies (EWAS). METHODS We performed a two-stage EWAS comprising 1,156 subjects. Differentially methylated positions (DMPs) and differentially methylated regions (DMRs) were assessed using the Infinium 450K and EPIC BeadChip in the discovery cohort (252 IS and 43 controls). Significant DMPs were replicated in an independent cohort (618 IS and 243 controls). Stroke subtype associations were also evaluated. Differentially methylated cell-type (DMCT) was analyzed in the replicated CpG sites using EpiDISH. We additionally performed pathway enrichment analysis and causality analysis with Mendelian randomization for the replicated CpG sites. RESULTS A total of 957 CpG sites were epigenome-wide-significant (p ≤ 10-7) in the discovery cohort, being CpG sites in the top signals (logFC = 0.058, p = 2.35 × 10-22; logFC = 0.035, p = 3.22 × 10-22, respectively). ZFHX3 and MAP3K1 were among the most significant DMRs. In addition, 697 CpG sites were replicated considering Bonferroni-corrected p-values (p < 5.22 × 10-5). All the replicated DMPs were associated with risk of cardioembolic, atherothrombotic, and undetermined stroke. The DMCT analysis demonstrated that the significant associations were driven by natural killer cells. The pathway enrichment analysis showed overrepresentation of genes belonging to certain pathways including oxidative stress. ZFHX3 and MAP3K1 methylation was causally associated with specific stroke-subtype risk. CONCLUSION Specific DNA methylation pattern is causally associated with IS risk. These results could be useful for specifically predicting stroke occurrence and could potentially be evaluated as therapeutic targets.
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Affiliation(s)
- Natalia Cullell
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Sant Quintí, Barcelona, Spain.,Department of Neurology, Hospital Universitari MútuaTerrassa/Fundacio Docència i Recerca MútuaTerrassa, Barcelona, Spain.,Facultat de Medicina, Universitat de Barcelona, Barcelona, Spain
| | - Carolina Soriano-Tárraga
- Neurovascular Research Group, Department of Neurology, Hospital del Mar, IMIM, Universitat Autònoma de Barcelona/DCEXS-Universitat Pompeu Fabra, Barcelona, Spain.,Department of Psychiatry, NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, Missouri, United States
| | | | - Jara Cárcel-Márquez
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Sant Quintí, Barcelona, Spain
| | - Nuria P Torres-Águila
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Sant Quintí, Barcelona, Spain.,Evolutionary Developmental Genomics Research Group, The Scottish Oceans Institute, University of St Andrews, St Andrews, United Kingdom
| | - Elena Muiño
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Sant Quintí, Barcelona, Spain
| | - Miquel Lledós
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Sant Quintí, Barcelona, Spain
| | - Laia Llucià-Carol
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Sant Quintí, Barcelona, Spain.,Department of Brain Ischemia and Neurodegeneration, Institut d'Investigacions Biomèdiques de Barcelona, Consejo Superior de Investigaciones Científicas (CSIC), Barcelona, Spain
| | - Manel Esteller
- Josep Carreras Leukaemia Research Institute, Barcelona, Spain.,Physiological Sciences Department, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain.,Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain.,Centro de Investigación Biomédica en Red Cancer, Barcelona, Spain
| | | | - Joan Montaner
- Department of Neurology, Hospital Universitario Virgen Macarena, Institute of Biomedicine of Seville/Hospital Universitario Virgen del Rocío/CSIC/University of Seville, Seville, Spain
| | - Alba Fernández-Sanlés
- Cardiovascular Epidemiology and Genetics Research Group, IMIM, Barcelona, Spain.,Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Roberto Elosua
- Cardiovascular Epidemiology and Genetics Research Group, IMIM, Barcelona, Spain.,CIBER Cardiovascular Diseases, Instituto Carlos III, Barcelona, Spain.,School of Medicine, University of Vic-Central University of Catalonia, Barcelona, Spain
| | - Pilar Delgado
- Neurovascular Research Laboratory, Vall d'Hebron Institute of Research, Barcelona, Spain
| | - Joan Martí-Fábregas
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Jerzy Krupinski
- Department of Neurology, Hospital Universitari MútuaTerrassa/Fundacio Docència i Recerca MútuaTerrassa, Barcelona, Spain.,Centre for Bioscience, School of HealthCare Science, Manchester Metropolitan University, Manchester, England
| | - Jaume Roquer
- Neurovascular Research Group, Department of Neurology, Hospital del Mar, IMIM, Universitat Autònoma de Barcelona/DCEXS-Universitat Pompeu Fabra, Barcelona, Spain
| | - Jordi Jiménez-Conde
- Neurovascular Research Group, Department of Neurology, Hospital del Mar, IMIM, Universitat Autònoma de Barcelona/DCEXS-Universitat Pompeu Fabra, Barcelona, Spain
| | - Israel Fernández-Cadenas
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Sant Quintí, Barcelona, Spain.,Department of Neurology, Hospital Universitari MútuaTerrassa/Fundacio Docència i Recerca MútuaTerrassa, Barcelona, Spain
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85
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Barouti Z, Heidari-Beni M, Shabanian-Boroujeni A, Mohammadzadeh M, Pahlevani V, Poursafa P, Mohebpour F, Kelishadi R. Effects of DNA methylation on cardiometabolic risk factors: a systematic review and meta-analysis. Arch Public Health 2022; 80:150. [PMID: 35655232 PMCID: PMC9161587 DOI: 10.1186/s13690-022-00907-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 05/27/2022] [Indexed: 11/10/2022] Open
Abstract
Background Epigenetic changes, especially DNA methylation have a main role in regulating cardiometabolic disorders and their risk factors. This study provides a review of the current evidence on the association between methylation of some genes (LINE1, ABCG1, SREBF1, PHOSPHO1, ADRB3, and LEP) and cardiometabolic risk factors. Methods A systematic literature search was conducted in electronic databases including Web of Science, PubMed, EMBASE, Google Scholar and Scopus up to end of 2020. All observational human studies (cross-sectional, case–control, and cohort) were included. Studies that assessed the effect of DNA methylation on cardiometabolic risk factors were selected. Results Among 1398 articles, eight studies and twenty-one studies were included in the meta-analysis and the systematic review, respectively. Our study showed ABCG1 and LINE1 methylation were positively associated with blood pressure (Fisher’s zr = 0.07 (0.06, 0.09), 95% CI: 0.05 to 0.08). Methylation in LINE1, ABCG1, SREBF1, PHOSPHO1 and ADRB3 had no significant association with HDL levels (Fisher’s zr = − 0.05 (− 0.13, 0.03), 95% CI:-0.12 to 0.02). Positive association was existed between LINE1, ABCG1 and LEP methylation and LDL levels (Fisher’s zr = 0.13 (0.04, 0.23), 95% CI: 0.03 to 0.23). Moreover, positive association was found between HbA1C and ABCG1 methylation (Fisher’s zr = 0.11 (0.09, 0.13), 95% CI: 0.09 to 0.12). DNA methylation of LINE1, ABCG1 and SREBF1 genes had no significant association with glucose levels (Fisher’s zr = 0.01 (− 0.12, 0.14), 95% CI:-0.12 to 0.14). Conclusion This meta-analysis showed that DNA methylation was associated with some cardiometabolic risk factors including LDL-C, HbA1C, and blood pressure. Registration Registration ID of the protocol on PROSPERO is CRD42020207677.
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86
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Bizjak DA, Ammerpohl O, Schulz SV, Wendt J, Steinacker JM, Flechtner-Mors M. Pro-inflammatory and (Epi-)genetic markers in saliva for disease risk in childhood obesity. Nutr Metab Cardiovasc Dis 2022; 32:1502-1510. [PMID: 35450790 DOI: 10.1016/j.numecd.2022.03.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 03/14/2022] [Accepted: 03/15/2022] [Indexed: 11/22/2022]
Abstract
BACKGROUND AND AIM Childhood obesity is an emerging problem often leading to earlier onset of non-communicable diseases in later life. Biomarkers to identify individual risk scores are insufficient in routine clinical practice, which is related to the need for easily sampled, non-invasive survey methods in children. We aimed to investigate and strengthen possible pro-inflammatory markers and epigenetic risk factors in saliva of obese children compared to lean controls. METHODS AND RESULTS 19 overweight/obese (OC, 10.1 ± 1.9 years, BMI 27.7 ± 3.2 kg/m2) and 19 lean control children (CC, 9.7 ± 2.5 years, BMI 16.4 ± 1.8 kg/m2) participated in this explorative pilot study. Anthropometric measures, saliva and cheek swab samples were taken. Saliva profiles were examined for acute phase proteins (CRP and neopterin) and pro-inflammatory cytokines (IL-17a/IL-1β/IL-6). Cheek swabs were analyzed to investigate DNA methylation differences with subsequent hierarchical cluster and principal component analyses (PCA). Saliva analysis showed significant increased CRP concentrations in OC compared to CC (p < 0.001). There were no significant differences, but high intra-individual values in neopterin, IL-17a, IL-1β and IL-6. An unsupervised PCA of CpG loci with high variance (σ/σmax > 0.2) clearly separated OC and CC according to their methylation pattern. Furthermore, a supervised approach revealed 7125 significantly differentially methylated loci, whose corresponding genes were significantly enriched for genes playing roles in e.g., cellular signalling, cytoskeleton organization and cell motility. CONCLUSIONS CRP and methylation status determinations in saliva are suitable as non-invasive methods for early detection of risks for non-communicable diseases in children/adolescents and might be a useful supplementary approach in the routine clinical practice/monitoring.
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Affiliation(s)
- Daniel A Bizjak
- Ulm University Hospital, Division of Sports and Rehabilitation Medicine, 89075 Ulm, Germany.
| | - Ole Ammerpohl
- Institute for Human Genetics, Ulm University and Ulm University Medical Center, Ulm, Germany
| | - Sebastian Vw Schulz
- Ulm University Hospital, Division of Sports and Rehabilitation Medicine, 89075 Ulm, Germany
| | - Janine Wendt
- Ulm University Hospital, Division of Sports and Rehabilitation Medicine, 89075 Ulm, Germany
| | - Jürgen M Steinacker
- Ulm University Hospital, Division of Sports and Rehabilitation Medicine, 89075 Ulm, Germany
| | - Marion Flechtner-Mors
- Ulm University Hospital, Division of Sports and Rehabilitation Medicine, 89075 Ulm, Germany
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87
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Yousefi PD, Suderman M, Langdon R, Whitehurst O, Davey Smith G, Relton CL. DNA methylation-based predictors of health: applications and statistical considerations. Nat Rev Genet 2022; 23:369-383. [PMID: 35304597 DOI: 10.1038/s41576-022-00465-w] [Citation(s) in RCA: 78] [Impact Index Per Article: 39.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/18/2022] [Indexed: 12/12/2022]
Abstract
DNA methylation data have become a valuable source of information for biomarker development, because, unlike static genetic risk estimates, DNA methylation varies dynamically in relation to diverse exogenous and endogenous factors, including environmental risk factors and complex disease pathology. Reliable methods for genome-wide measurement at scale have led to the proliferation of epigenome-wide association studies and subsequently to the development of DNA methylation-based predictors across a wide range of health-related applications, from the identification of risk factors or exposures, such as age and smoking, to early detection of disease or progression in cancer, cardiovascular and neurological disease. This Review evaluates the progress of existing DNA methylation-based predictors, including the contribution of machine learning techniques, and assesses the uptake of key statistical best practices needed to ensure their reliable performance, such as data-driven feature selection, elimination of data leakage in performance estimates and use of generalizable, adequately powered training samples.
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Affiliation(s)
- Paul D Yousefi
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Matthew Suderman
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Ryan Langdon
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Oliver Whitehurst
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Caroline L Relton
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK.
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88
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Siddiqui MK, Anjana RM, Dawed AY, Martoeau C, Srinivasan S, Saravanan J, Madanagopal SK, Taylor A, Bell S, Veluchamy A, Pradeepa R, Sattar N, Venkatesan R, Palmer CNA, Pearson ER, Mohan V. Young-onset diabetes in Asian Indians is associated with lower measured and genetically determined beta cell function. Diabetologia 2022; 65:973-983. [PMID: 35247066 PMCID: PMC9076730 DOI: 10.1007/s00125-022-05671-z] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 12/06/2021] [Indexed: 01/11/2023]
Abstract
AIMS/HYPOTHESIS South Asians in general, and Asian Indians in particular, have higher risk of type 2 diabetes compared with white Europeans, and a younger age of onset. The reasons for the younger age of onset in relation to obesity, beta cell function and insulin sensitivity are under-explored. METHODS Two cohorts of Asian Indians, the ICMR-INDIAB cohort (Indian Council of Medical Research-India Diabetes Study) and the DMDSC cohort (Dr Mohan's Diabetes Specialties Centre), and one of white Europeans, the ESDC (East Scotland Diabetes Cohort), were used. Using a cross-sectional design, we examined the comparative prevalence of healthy, overweight and obese participants with young-onset diabetes, classified according to their BMI. We explored the role of clinically measured beta cell function in diabetes onset in Asian Indians. Finally, the comparative distribution of a partitioned polygenic score (pPS) for risk of diabetes due to poor beta cell function was examined. Replication of the genetic findings was sought using data from the UK Biobank. RESULTS The prevalence of young-onset diabetes with normal BMI was 9.3% amongst white Europeans and 24-39% amongst Asian Indians. In Asian Indians with young-onset diabetes, after adjustment for family history of type 2 diabetes, sex, insulin sensitivity and HDL-cholesterol, stimulated C-peptide was 492 pmol/ml (IQR 353-616, p<0.0001) lower in lean compared with obese individuals. Asian Indians in our study, and South Asians from the UK Biobank, had a higher number of risk alleles than white Europeans. After weighting the pPS for beta cell function, Asian Indians have lower genetically determined beta cell function than white Europeans (p<0.0001). The pPS was associated with age of diagnosis in Asian Indians but not in white Europeans. The pPS explained 2% of the variation in clinically measured beta cell function, and 1.2%, 0.97%, and 0.36% of variance in age of diabetes amongst Asian Indians with normal BMI, or classified as overweight and obese BMI, respectively. CONCLUSIONS/INTERPRETATION The prevalence of lean BMI in young-onset diabetes is over two times higher in Asian Indians compared with white Europeans. This phenotype of lean, young-onset diabetes appears driven in part by lower beta cell function. We demonstrate that Asian Indians with diabetes also have lower genetically determined beta cell function.
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Affiliation(s)
- Moneeza K. Siddiqui
- grid.8241.f0000 0004 0397 2876National Institute for Health Research Global Health Unit for Diabetes Outcomes Research, Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Ranjit Mohan Anjana
- grid.410867.c0000 0004 1805 2183Dr Mohan’s Diabetes Specialities Centre and Madras Diabetes Research Foundation, Chennai, India
| | - Adem Y. Dawed
- grid.8241.f0000 0004 0397 2876National Institute for Health Research Global Health Unit for Diabetes Outcomes Research, Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Cyrielle Martoeau
- grid.8241.f0000 0004 0397 2876National Institute for Health Research Global Health Unit for Diabetes Outcomes Research, Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Sundararajan Srinivasan
- grid.8241.f0000 0004 0397 2876National Institute for Health Research Global Health Unit for Diabetes Outcomes Research, Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Jebarani Saravanan
- grid.410867.c0000 0004 1805 2183Dr Mohan’s Diabetes Specialities Centre and Madras Diabetes Research Foundation, Chennai, India
| | - Sathish K. Madanagopal
- grid.410867.c0000 0004 1805 2183Dr Mohan’s Diabetes Specialities Centre and Madras Diabetes Research Foundation, Chennai, India
| | - Alasdair Taylor
- grid.8241.f0000 0004 0397 2876National Institute for Health Research Global Health Unit for Diabetes Outcomes Research, Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Samira Bell
- grid.8241.f0000 0004 0397 2876National Institute for Health Research Global Health Unit for Diabetes Outcomes Research, Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Abirami Veluchamy
- grid.8241.f0000 0004 0397 2876National Institute for Health Research Global Health Unit for Diabetes Outcomes Research, Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Rajendra Pradeepa
- grid.410867.c0000 0004 1805 2183Dr Mohan’s Diabetes Specialities Centre and Madras Diabetes Research Foundation, Chennai, India
| | - Naveed Sattar
- grid.8756.c0000 0001 2193 314XInstitute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Radha Venkatesan
- grid.410867.c0000 0004 1805 2183Dr Mohan’s Diabetes Specialities Centre and Madras Diabetes Research Foundation, Chennai, India
| | - Colin N. A. Palmer
- grid.8241.f0000 0004 0397 2876National Institute for Health Research Global Health Unit for Diabetes Outcomes Research, Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Ewan R. Pearson
- grid.8241.f0000 0004 0397 2876National Institute for Health Research Global Health Unit for Diabetes Outcomes Research, Division of Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Viswanathan Mohan
- grid.410867.c0000 0004 1805 2183Dr Mohan’s Diabetes Specialities Centre and Madras Diabetes Research Foundation, Chennai, India
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89
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Manu DM, Mwinyi J, Schiöth HB. Challenges in Analyzing Functional Epigenetic Data in Perspective of Adolescent Psychiatric Health. Int J Mol Sci 2022; 23:5856. [PMID: 35628666 PMCID: PMC9147258 DOI: 10.3390/ijms23105856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 05/11/2022] [Accepted: 05/18/2022] [Indexed: 12/10/2022] Open
Abstract
The formative period of adolescence plays a crucial role in the development of skills and abilities for adulthood. Adolescents who are affected by mental health conditions are at risk of suicide and social and academic impairments. Gene-environment complementary contributions to the molecular mechanisms involved in psychiatric disorders have emphasized the need to analyze epigenetic marks such as DNA methylation (DNAm) and non-coding RNAs. However, the large and diverse bioinformatic and statistical methods, referring to the confounders of the statistical models, application of multiple-testing adjustment methods, questions regarding the correlation of DNAm across tissues, and sex-dependent differences in results, have raised challenges regarding the interpretation of the results. Based on the example of generalized anxiety disorder (GAD) and depressive disorder (MDD), we shed light on the current knowledge and usage of methodological tools in analyzing epigenetics. Statistical robustness is an essential prerequisite for a better understanding and interpretation of epigenetic modifications and helps to find novel targets for personalized therapeutics in psychiatric diseases.
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Affiliation(s)
- Diana M. Manu
- Department of Surgical Sciences, Functional Pharmacology and Neuroscience, Uppsala University, 751 24 Uppsala, Sweden; (J.M.); (H.B.S.)
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90
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Maeda K, Yamada H, Munetsuna E, Fujii R, Yamazaki M, Ando Y, Mizuno G, Ishikawa H, Ohashi K, Tsuboi Y, Hattori Y, Ishihara Y, Hashimoto S, Hamajima N, Suzuki K. Association of drinking behaviors with TXNIP DNA methylation levels in leukocytes among the general Japanese population. THE AMERICAN JOURNAL OF DRUG AND ALCOHOL ABUSE 2022; 48:302-310. [PMID: 35416731 DOI: 10.1080/00952990.2022.2037137] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 01/28/2022] [Accepted: 01/30/2022] [Indexed: 06/14/2023]
Abstract
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.
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Affiliation(s)
- Keisuke Maeda
- Department of Clinical Physiology, Fujita Health University School of Medical Sciences, Toyoake, Japan
| | - Hiroya Yamada
- Department of Hygiene, Fujita Health University School of Medicine, Toyoake, Japan
| | - Eiji Munetsuna
- Department of Biochemistry, Fujita Health University School of Medicine, Toyoake, Japan
| | - Ryosuke Fujii
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake, Japan
| | - Mirai Yamazaki
- Department of Medical Technology, Kagawa Prefectural University of Health Sciences, Takamatsu, Japan
| | - Yoshitaka Ando
- Department of Informative Clinical Medicine, Fujita Health University School of Medical Sciences, Toyoake, Japan
| | - Genki Mizuno
- Department of Informative Clinical Medicine, Fujita Health University School of Medical Sciences, Toyoake, Japan
| | - Hiroaki Ishikawa
- Department of Informative Clinical Medicine, Fujita Health University School of Medical Sciences, Toyoake, Japan
| | - Koji Ohashi
- Department of Informative Clinical Medicine, Fujita Health University School of Medical Sciences, Toyoake, Japan
| | - Yoshiki Tsuboi
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake, Japan
| | - Yuji Hattori
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake, Japan
| | - Yuya Ishihara
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake, Japan
| | - Shuji Hashimoto
- Department of Hygiene, Fujita Health University School of Medicine, Toyoake, Japan
| | - Nobuyuki Hamajima
- Department of Healthcare Administration, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Koji Suzuki
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake, Japan
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91
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Wielscher M, Mandaviya PR, Kuehnel B, Joehanes R, Mustafa R, Robinson O, Zhang Y, Bodinier B, Walton E, Mishra PP, Schlosser P, Wilson R, Tsai PC, Palaniswamy S, Marioni RE, Fiorito G, Cugliari G, Karhunen V, Ghanbari M, Psaty BM, Loh M, Bis JC, Lehne B, Sotoodehnia N, Deary IJ, Chadeau-Hyam M, Brody JA, Cardona A, Selvin E, Smith AK, Miller AH, Torres MA, Marouli E, Gào X, van Meurs JBJ, Graf-Schindler J, Rathmann W, Koenig W, Peters A, Weninger W, Farlik M, Zhang T, Chen W, Xia Y, Teumer A, Nauck M, Grabe HJ, Doerr M, Lehtimäki T, Guan W, Milani L, Tanaka T, Fisher K, Waite LL, Kasela S, Vineis P, Verweij N, van der Harst P, Iacoviello L, Sacerdote C, Panico S, Krogh V, Tumino R, Tzala E, Matullo G, Hurme MA, Raitakari OT, Colicino E, Baccarelli AA, Kähönen M, Herzig KH, Li S, Conneely KN, Kooner JS, Köttgen A, Heijmans BT, Deloukas P, Relton C, Ong KK, Bell JT, Boerwinkle E, Elliott P, Brenner H, Beekman M, Levy D, Waldenberger M, Chambers JC, Dehghan A, Järvelin MR. DNA methylation signature of chronic low-grade inflammation and its role in cardio-respiratory diseases. Nat Commun 2022; 13:2408. [PMID: 35504910 PMCID: PMC9065016 DOI: 10.1038/s41467-022-29792-6] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 03/31/2022] [Indexed: 02/02/2023] Open
Abstract
We performed a multi-ethnic Epigenome Wide Association study on 22,774 individuals to describe the DNA methylation signature of chronic low-grade inflammation as measured by C-Reactive protein (CRP). We find 1,511 independent differentially methylated loci associated with CRP. These CpG sites show correlation structures across chromosomes, and are primarily situated in euchromatin, depleted in CpG islands. These genomic loci are predominantly situated in transcription factor binding sites and genomic enhancer regions. Mendelian randomization analysis suggests altered CpG methylation is a consequence of increased blood CRP levels. Mediation analysis reveals obesity and smoking as important underlying driving factors for changed CpG methylation. Finally, we find that an activated CpG signature significantly increases the risk for cardiometabolic diseases and COPD.
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Affiliation(s)
- Matthias Wielscher
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
- Department of Dermatology, Medical University of Vienna, Vienna, Austria.
| | - Pooja R Mandaviya
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
- Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands
| | - Brigitte Kuehnel
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, Germany
| | - Roby Joehanes
- Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Rima Mustafa
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Oliver Robinson
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Yan Zhang
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
| | - Barbara Bodinier
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Esther Walton
- Department of Psychology, University of Bath, Bath, UK
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Pascal Schlosser
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Rory Wilson
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, Germany
| | - Pei-Chien Tsai
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- Department of Biomedical Sciences, Chang Gung University, Taoyuan City, Taiwan
| | - Saranya Palaniswamy
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Pentti Kaiteran katu 1, Linnanmaa, Oulu, Finland
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK
| | - Giovanni Fiorito
- Laboratory of Biostatistics, Department of Biomedical Sciences, University of Sassari, Sassari, Italy
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | | | - Ville Karhunen
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Genetics, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Bruce M Psaty
- Cardiovacular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Health Services, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Marie Loh
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Lee Kong Chian School of Medicine, Mandalay Road, Singapore, Singapore
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, WA, USA
| | - Benjamin Lehne
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, WA, USA
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Marc Chadeau-Hyam
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, WA, USA
| | - Alexia Cardona
- MRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Elizabeth Selvin
- Dept. of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Alicia K Smith
- Departments of Gynecology and Obstetrics & Psychiatry and Behavioral Science, Emory University School of Medicine, Atlanta, GA, USA
| | - Andrew H Miller
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Mylin A Torres
- Department of Radiation Oncology, Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA, USA
| | - Eirini Marouli
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Xin Gào
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Johanna Graf-Schindler
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, Germany
| | - Wolfgang Rathmann
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Resesarch at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Wolfgang Koenig
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Annette Peters
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Wolfgang Weninger
- Department of Dermatology, Medical University of Vienna, Vienna, Austria
| | - Matthias Farlik
- Department of Dermatology, Medical University of Vienna, Vienna, Austria
| | - Tao Zhang
- Deptarment of Biostatistics, School of Public Health, Shandong University, Jinan, China
| | - Wei Chen
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Yujing Xia
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
| | - Matthias Nauck
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Macus Doerr
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Weihua Guan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Toshiko Tanaka
- Translational Gerontology Branch, Biomedical Research Center, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Krista Fisher
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
| | - Lindsay L Waite
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Silva Kasela
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Paolo Vineis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Niek Verweij
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, Groningen, The Netherlands
| | - Pim van der Harst
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Licia Iacoviello
- Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, IS, Italy
- Department of Medicine and Surgery, Research Center in Epidemiology and Preventive Medicine (EPIMED), University of Insubria, Varese-Como, Italy
| | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, Citta' della Salute e della Scienza Hospital and Centre for Cancer Prevention, Turin, Italy
| | - Salvatore Panico
- Dipartimento di Medicina Clinica e Chirurgia Federico II University, Naples, Italy
| | - Vittorio Krogh
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Rosario Tumino
- Cancer Registry and Histopathology Department, "Civic - MPP Arezzo" Hospital, ASP Ragusa, Ragusa, Italy
| | - Evangelia Tzala
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Giuseppe Matullo
- Department of Medical Sciences, University of Turin, Turin, Italy
- AOU Città della Salute e della Scienza di Torino, Torino, Italy
| | - Mikko A Hurme
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Olli T Raitakari
- Research centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Elena Colicino
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Andrea A Baccarelli
- Laboratory of Environmental Epigenetics, Departments of Environmental Health Sciences and Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Mika Kähönen
- Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
| | - Karl-Heinz Herzig
- Research Unit of Biomedicine, Medical Research Center, Faculty of Medicine, University of Oulu, and Oulu University Hospital, Oulu, Finland
- Department of Gastroenterology and Metabolism, Institute of Pediatrics, Poznan University of Medical Sciences, Poznan, Poland
| | - Shengxu Li
- Children's Minnesota Research Institute, Children's Minnesota, Minneapolis, MN, USA
| | - Karen N Conneely
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Jaspal S Kooner
- National Heart and Lung Institute, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Southall, UK
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Dept. of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Bastiaan T Heijmans
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Panos Deloukas
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Caroline Relton
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ken K Ong
- MRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Eric Boerwinkle
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Houston, TX, USA
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Imperial Biomedical Research Centre, Imperial College London, London, UK
- British Heart Foundation, BHF, Centre for Research Excellence, Imperial College London, London, UK
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
- Network Aging Research, Heidelberg University, Heidelberg, Germany
| | - Marian Beekman
- Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
| | - Daniel Levy
- Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - John C Chambers
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Lee Kong Chian School of Medicine, Mandalay Road, Singapore, Singapore
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Southall, UK
| | - Abbas Dehghan
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- UK Dementia Research Institute at Imperial College London, London, UK
| | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Pentti Kaiteran katu 1, Linnanmaa, Oulu, Finland.
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland.
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK.
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Fraszczyk E, Spijkerman AMW, Zhang Y, Brandmaier S, Day FR, Zhou L, Wackers P, Dollé MET, Bloks VW, Gào X, Gieger C, Kooner J, Kriebel J, Picavet HSJ, Rathmann W, Schöttker B, Loh M, Verschuren WMM, van Vliet-Ostaptchouk JV, Wareham NJ, Chambers JC, Ong KK, Grallert H, Brenner H, Luijten M, Snieder H. Epigenome-wide association study of incident type 2 diabetes: a meta-analysis of five prospective European cohorts. Diabetologia 2022; 65:763-776. [PMID: 35169870 PMCID: PMC8960572 DOI: 10.1007/s00125-022-05652-2] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 11/15/2021] [Indexed: 02/02/2023]
Abstract
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.
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Affiliation(s)
- Eliza Fraszczyk
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Annemieke M W Spijkerman
- Centre for Nutrition, Prevention and Health services, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Yan Zhang
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
| | - Stefan Brandmaier
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Felix R Day
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Li Zhou
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Paul Wackers
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Martijn E T Dollé
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Vincent W Bloks
- Department of Pediatrics, Section of Molecular Metabolism and Nutrition, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Xīn Gào
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Jaspal Kooner
- Department of Cardiology, Ealing Hospital, Ealing, UK
- Imperial College Healthcare NHS Trust, London, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Jennifer Kriebel
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - H Susan J Picavet
- Centre for Nutrition, Prevention and Health services, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Wolfgang Rathmann
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute for Biometrics and Epidemiology, German Diabetes Center, Auf'm Hennekamp, Duesseldorf, Germany
| | - Ben Schöttker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
- Network Aging Research, University of Heidelberg, Heidelberg, Germany
| | - Marie Loh
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - W M Monique Verschuren
- Centre for Nutrition, Prevention and Health services, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Jana V van Vliet-Ostaptchouk
- Genomics Coordination Center, Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - John C Chambers
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Ken K Ong
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Department of Paediatrics, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
- Network Aging Research, University of Heidelberg, Heidelberg, Germany
| | - Mirjam Luijten
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
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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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94
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Epigenetic changes associated with hyperglycaemia exposure in the longitudinal D.E.S.I.R. cohort. DIABETES & METABOLISM 2022; 48:101347. [PMID: 35427775 DOI: 10.1016/j.diabet.2022.101347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 03/21/2022] [Indexed: 11/20/2022]
Abstract
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.
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Loh M, Zhang W, Ng HK, Schmid K, Lamri A, Tong L, Ahmad M, Lee JJ, Ng MCY, Petty LE, Spracklen CN, Takeuchi F, Islam MT, Jasmine F, Kasturiratne A, Kibriya M, Mohlke KL, Paré G, Prasad G, Shahriar M, Chee ML, de Silva HJ, Engert JC, Gerstein HC, Mani KR, Sabanayagam C, Vujkovic M, Wickremasinghe AR, Wong TY, Yajnik CS, Yusuf S, Ahsan H, Bharadwaj D, Anand SS, Below JE, Boehnke M, Bowden DW, Chandak GR, Cheng CY, Kato N, Mahajan A, Sim X, McCarthy MI, Morris AP, Kooner JS, Saleheen D, Chambers JC. Identification of genetic effects underlying type 2 diabetes in South Asian and European populations. Commun Biol 2022; 5:329. [PMID: 35393509 PMCID: PMC8991226 DOI: 10.1038/s42003-022-03248-5] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Accepted: 03/08/2022] [Indexed: 02/08/2023] Open
Abstract
South Asians are at high risk of developing type 2 diabetes (T2D). We carried out a genome-wide association meta-analysis with South Asian T2D cases (n = 16,677) and controls (n = 33,856), followed by combined analyses with Europeans (neff = 231,420). We identify 21 novel genetic loci for significant association with T2D (P = 4.7 × 10-8 to 5.2 × 10-12), to the best of our knowledge at the point of analysis. The loci are enriched for regulatory features, including DNA methylation and gene expression in relevant tissues, and highlight CHMP4B, PDHB, LRIG1 and other genes linked to adiposity and glucose metabolism. A polygenic risk score based on South Asian-derived summary statistics shows ~4-fold higher risk for T2D between the top and bottom quartile. Our results provide further insights into the genetic mechanisms underlying T2D, and highlight the opportunities for discovery from joint analysis of data from across ancestral populations.
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Affiliation(s)
- Marie Loh
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Middlesex, UB1 3HW, UK
| | - Hong Kiat Ng
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
| | - Katharina Schmid
- Institute of Computational Biology, Deutsches Forschungszentrum für Gesundheit und Umwelt, Helmholtz Zentrum München, 85764, Neuherberg, Germany
- Department of Informatics, Technical University of Munich, 85748, Garching bei München, Neuherberg, Germany
| | - Amel Lamri
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
| | - Lin Tong
- The University of Chicago, Biological Sciences Division, Public Health Sciences, 5841 South Maryland Avenue, MC2000, Chicago, IL, 60637, USA
| | - Meraj Ahmad
- Genomic Research on Complex diseases, CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Jung-Jin Lee
- Translational Medicine and Human Genetics, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Medicine, Mayo Hospital, Lahore, Pakistan
| | - Maggie C Y Ng
- Center for Genomics and Personalized Medicine Research, Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, 37215, USA
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Lauren E Petty
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Cassandra N Spracklen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Department of Biostatistics and Epidemiology, University of Massachusetts, Amherst, MA, 01003, USA
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Md Tariqul Islam
- U Chicago Research Bangladesh, House#4, Road#2b, Sector#4, Uttara, Dhaka, 1230, Bangladesh
| | - Farzana Jasmine
- The University of Chicago, Biological Sciences Division, Public Health Sciences, 5841 South Maryland Avenue, MC2000, Chicago, IL, 60637, USA
| | - Anuradhani Kasturiratne
- Department of Public Health, Faculty of Medicine, University of Kelaniya, Kelaniya, Sri Lanka
| | - Muhammad Kibriya
- The University of Chicago, Biological Sciences Division, Public Health Sciences, 5841 South Maryland Avenue, MC2000, Chicago, IL, 60637, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Guillaume Paré
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
| | - Gauri Prasad
- Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, 110020, India
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, 110067, India
| | - Mohammad Shahriar
- The University of Chicago, Biological Sciences Division, Public Health Sciences, 5841 South Maryland Avenue, MC2000, Chicago, IL, 60637, USA
| | - Miao Ling Chee
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - H Janaka de Silva
- Department of Medicine, Faculty of Medicine, University of Kelaniya, Kelaniya, Sri Lanka
| | - James C Engert
- Department of Medicine, McGill University, Montreal, QC, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Hertzel C Gerstein
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - K Radha Mani
- Genomic Research on Complex diseases, CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
| | - Marijana Vujkovic
- Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA
| | - Ananda R Wickremasinghe
- Department of Public Health, Faculty of Medicine, University of Kelaniya, Kelaniya, Sri Lanka
| | - Tien Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | | | - Salim Yusuf
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Habibul Ahsan
- The University of Chicago, Biological Sciences Division, Public Health Sciences, 5841 South Maryland Avenue, MC2000, Chicago, IL, 60637, USA
| | - Dwaipayan Bharadwaj
- Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, 110020, India
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, 110067, India
| | - Sonia S Anand
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Jennifer E Below
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, 48109, USA
| | - Donald W Bowden
- Department of Medicine, Mayo Hospital, Lahore, Pakistan
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, 37215, USA
| | - Giriraj R Chandak
- Genomic Research on Complex diseases, CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
- JSS Academy of Health Education of Research, Mysuru, India
- Science and Engineering Research Board, Department of Science and Technology, Ministry of Science and technology, Government of India, New Delhi, India
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Anubha Mahajan
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Mark I McCarthy
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hosptial, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 7LE, UK
| | - Andrew P Morris
- Department of Biostatistics, University of Liverpool, Liverpool, L69 3GL, UK
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Middlesex, UB1 3HW, UK.
- Imperial College Healthcare NHS Trust, Imperial College London, London, W12 0HS, UK.
- MRC-PHE Centre for Enviroment and Health, Imperial College London, London, W2 1PG, UK.
- National Heart and Lung Institute, Imperial College London, London, W12 0NN, UK.
| | - Danish Saleheen
- Center for Non-Communicable Diseases, Karachi, Pakistan.
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA.
- Department of Cardiology, Columbia University Irving Medical Center, New York, NY, 10032, USA.
| | - John C Chambers
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore.
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK.
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Middlesex, UB1 3HW, UK.
- Imperial College Healthcare NHS Trust, Imperial College London, London, W12 0HS, UK.
- MRC-PHE Centre for Enviroment and Health, Imperial College London, London, W2 1PG, UK.
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96
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Yamazaki M, Yamada H, Munetsuna E, Maeda K, Ando Y, Mizuno G, Fujii R, Tsuboi Y, Ohashi K, Ishikawa H, Hashimoto S, Hamajima N, Suzuki K. DNA methylation level of the gene encoding thioredoxin-interacting protein in peripheral blood cells is associated with metabolic syndrome in the Japanese general population. Endocr J 2022; 69:319-326. [PMID: 34645728 DOI: 10.1507/endocrj.ej21-0339] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
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.
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Affiliation(s)
- Mirai Yamazaki
- Department of Medical Technology, Kagawa Prefectural University of Health Sciences, Takamatsu 761-0123, Japan
| | - Hiroya Yamada
- Department of Hygiene, Fujita Health University School of Medicine, Toyoake 470-1192, Japan
| | - Eiji Munetsuna
- Department of Biochemistry, Fujita Health University School of Medicine, Toyoake 470-1192, Japan
| | - Keisuke Maeda
- Department of Clinical Physiology, Fujita Health University School of Medical Sciences, Toyoake 470-1192, Japan
| | - Yoshitaka Ando
- Department of Biomedical and Analytical Sciences, Fujita Health University School of Medical Sciences, Toyoake 470-1192, Japan
| | - Genki Mizuno
- Department of Joint Research Laboratory of Clinical Medicine, Fujita Health University Hospital, Toyoake 470-1192, Japan
| | - Ryosuke Fujii
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake 470-1192, Japan
| | - Yoshiki Tsuboi
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake 470-1192, Japan
| | - Koji Ohashi
- Department of Biomedical and Analytical Sciences, Fujita Health University School of Medical Sciences, Toyoake 470-1192, Japan
| | - Hiroaki Ishikawa
- Department of Biomedical and Analytical Sciences, Fujita Health University School of Medical Sciences, Toyoake 470-1192, Japan
| | - Shuji Hashimoto
- Department of Hygiene, Fujita Health University School of Medicine, Toyoake 470-1192, Japan
| | - Nobuyuki Hamajima
- Department of Healthcare Administration, Nagoya University Graduate School of Medicine, Nagoya 466-8550, Japan
| | - Koji Suzuki
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake 470-1192, Japan
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97
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Li X, Qi L. Epigenetics in Precision Nutrition. J Pers Med 2022; 12:jpm12040533. [PMID: 35455649 PMCID: PMC9027461 DOI: 10.3390/jpm12040533] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Revised: 03/14/2022] [Accepted: 03/24/2022] [Indexed: 02/01/2023] Open
Abstract
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.
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Affiliation(s)
- Xiang Li
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA;
| | - Lu Qi
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA;
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Correspondence: ; Tel.: +1-504-988-7259
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98
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He Y, Li Y, Zhang J, Chen L, Li J, Zhang M, Zhang Q, Lu Y, Jiang J, Zhang X, Hu J, Ding Y, Zhang M, Peng H. FURIN Promoter Methylation Predicts the Risk of Incident Diabetes: A Prospective Analysis in the Gusu Cohort. Front Endocrinol (Lausanne) 2022; 13:873012. [PMID: 35399937 PMCID: PMC8990793 DOI: 10.3389/fendo.2022.873012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 02/25/2022] [Indexed: 12/02/2022] Open
Abstract
Background Furin has been associated with diabetes but the underlying mechanisms are unclear. As a mediator linking fixed genome and dynamic environment, DNA methylation of its coding gene FURIN may be involved. Here, we aimed to examine the prospective association between DNA methylation in FURIN promoter and incident diabetes during 4 years of follow-up in Chinese adults. Methods DNA methylation levels in FURIN promoter were quantified by target bisulfite sequencing using peripheral blood from 1836 participants in the Gusu cohort who were free of diabetes at baseline. To examine the association between DNA methylation levels in FURIN promoter and incident diabetes, we constructed a logistic regression model adjusting for the conventional factors. Multiple testing was controlled by adjusting for the total number of CpG sites assayed using the false-discovery rate approach. Results Among the 1836 participants free of diabetes at baseline, 109 (5.94%) participants developed diabetes during the average of 4 years of follow-up. Hypermethylation at two of the eight CpG sites assayed in the FURIN promoter was associated with an increased risk of diabetes, after multivariable adjustment and multiple testing correction. Every 5% increment in methylation levels at CpG1 and CpG2 were associated with a 22% (OR=1.22, 95%CI: 1.05-1.43, P=0.009, q=0.038) and 39% (OR=1.39, 95%CI: 1.08-1.77, P=0.009, q=0.038) higher risk of incident diabetes, respectively. The gene-based association analysis revealed that DNA methylation at multiple CpG loci was jointly associated with incident diabetes (P<0.001). Using the average methylation level of the 8 CpG loci in FURIN promoter revealed a similar association (OR=1.28, 95% CI: 1.02-1.62, P=0.037). Conclusions These results suggested that the hypermethylation levels in FURIN promoter were associated with an increased risk for incident diabetes in Chinese adults.
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Affiliation(s)
- Yan He
- Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, China
| | - Yinan Li
- Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, China
| | - Jianan Zhang
- Department of Chronic Disease, Taicang Center for Disease Control and Prevention, Suzhou, China
| | - Linan Chen
- Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, China
| | - Jing Li
- Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, China
| | - Min Zhang
- Department of Central Office, Suzhou National New and Hi-Tech Industrial Development Zone Center for Disease Control and Prevention, Suzhou, China
| | - Qiu Zhang
- Department of Chronic Disease, Gusu Center for Disease Control and Prevention, Suzhou, China
| | - Ying Lu
- Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, China
| | - Jun Jiang
- Department of Tuberculosis Control, Suzhou Center for Disease Control and Prevention, Suzhou, China
| | - Xiaolong Zhang
- Department of Tuberculosis Control, Suzhou Center for Disease Control and Prevention, Suzhou, China
| | - Jianwei Hu
- Department of Central Office, Maternal and Child Health Bureau of Kunshan, Suzhou, China
| | - Yi Ding
- Department of Preventive Medicine, College of Clinical Medicine, Suzhou Vocational Health College, Suzhou, China
| | - Mingzhi Zhang
- Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, China
| | - Hao Peng
- Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, China
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99
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Liu Y, Wang Y, Qin S, Jin X, Jin L, Gu W, Mu Y. Insights Into Genome-Wide Association Study for Diabetes: A Bibliometric and Visual Analysis From 2001 to 2021. Front Endocrinol (Lausanne) 2022; 13:817620. [PMID: 35360064 PMCID: PMC8963272 DOI: 10.3389/fendo.2022.817620] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 02/07/2022] [Indexed: 12/24/2022] Open
Abstract
Hundreds of research and review articles concerning genome-wide association study (GWAS) in diabetes have been published in the last two decades. We aimed to evaluate the hotspots and future trends in GWAS in diabetes research through bibliometric analysis. Accordingly, 567 research and review articles published between 2001 and 2021 were included. A rising trend was noted in the annual number of publications and citations on GWAS in diabetes during this period. Harvard University and Harvard Medical School have played leading roles in genome research. Hotspot analyses indicated that DNA methylation and genetic variation, especially in type 2 diabetes mellitus, are likely to remain the research hotspots. Moreover, the identification of genetic phenotypes associated with adiposity, metabolic memory, pancreatic islet, and inflammation is the leading trend in this research field. Through this review, we provide predictions on the main research trends in the future so as to shed light on new directions and ideas for further investigations on the genetic etiology of diabetes for its prevention and treatment.
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Affiliation(s)
- Yang Liu
- Department of Endocrinology, the First Medical Center of Chinese People’s Liberation Army (PLA) General Hospital, Beijing, China
- Department of Endocrinology, the Eighth Medical Center of People’s Liberation Army (PLA) General Hospital, Beijing, China
| | - Yun Wang
- Department of Endocrinology, the First Medical Center of Chinese People’s Liberation Army (PLA) General Hospital, Beijing, China
| | - Shan Qin
- Department of Endocrinology, the First Medical Center of Chinese People’s Liberation Army (PLA) General Hospital, Beijing, China
| | - Xinye Jin
- Department of Endocrinology, the First Medical Center of Chinese People’s Liberation Army (PLA) General Hospital, Beijing, China
- Department of Nephrology, Hainan Hospital of Chinese People’s Liberation Army (PLA) General Hospital, Academician Chen Xiangmei of Hainan Province Kidney Diseases Research Team Innovation Center, Sanya, China
| | - Lingzi Jin
- Department of International Medical Services, Peking Union Medical College Hospital, Beijing, China
| | - Weijun Gu
- Department of Endocrinology, the First Medical Center of Chinese People’s Liberation Army (PLA) General Hospital, Beijing, China
| | - Yiming Mu
- Department of Endocrinology, the First Medical Center of Chinese People’s Liberation Army (PLA) General Hospital, Beijing, China
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100
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Kalia V, Belsky DW, Baccarelli AA, Miller GW. An exposomic framework to uncover environmental drivers of aging. EXPOSOME 2022; 2:osac002. [PMID: 35295547 PMCID: PMC8917275 DOI: 10.1093/exposome/osac002] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 01/19/2022] [Accepted: 01/24/2022] [Indexed: 01/02/2023]
Abstract
The exposome, the environmental complement of the genome, is an omics level characterization of an individual's exposures. There is growing interest in uncovering the role of the environment in human health using an exposomic framework that provides a systematic and unbiased analysis of the non-genetic drivers of health and disease. Many environmental toxicants are associated with molecular hallmarks of aging. An exposomic framework has potential to advance understanding of these associations and how modifications to the environment can promote healthy aging in the population. However, few studies have used this framework to study biological aging. We provide an overview of approaches and challenges in using an exposomic framework to investigate environmental drivers of aging. While capturing exposures over a life course is a daunting and expensive task, the use of historical data can be a practical way to approach this research.
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Affiliation(s)
- Vrinda Kalia
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Daniel W Belsky
- Department of Epidemiology and Robert N. Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Gary W Miller
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
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