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Linares-Pineda TM, Fragoso-Bargas N, Picón MJ, Molina-Vega M, Jenum AK, Sletner L, Lee-Ødegård S, Opsahl JO, Moen GH, Qvigstad E, Prasad RB, Birkeland KI, Morcillo S, Sommer C. DNA methylation risk score for type 2 diabetes is associated with gestational diabetes. Cardiovasc Diabetol 2024; 23:68. [PMID: 38350951 PMCID: PMC10865541 DOI: 10.1186/s12933-024-02151-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 02/02/2024] [Indexed: 02/15/2024] Open
Abstract
BACKGROUND Gestational diabetes mellitus (GDM) and type 2 diabetes mellitus (T2DM) share many pathophysiological factors including genetics, but whether epigenetic marks are shared is unknown. We aimed to test whether a DNA methylation risk score (MRS) for T2DM was associated with GDM across ancestry and GDM criteria. METHODS In two independent pregnancy cohorts, EPIPREG (n = 480) and EPIDG (n = 32), DNA methylation in peripheral blood leukocytes was measured at a gestational age of 28 ± 2. We constructed an MRS in EPIPREG and EPIDG based on CpG hits from a published epigenome-wide association study (EWAS) of T2DM. RESULTS With mixed models logistic regression of EPIPREG and EPIDG, MRS for T2DM was associated with GDM: odd ratio (OR)[95% CI]: 1.3 [1.1-1.8], P = 0.002 for the unadjusted model, and 1.4 [1.1-1.7], P = 0.00014 for a model adjusted by age, pre-pregnant BMI, family history of diabetes and smoking status. Also, we found 6 CpGs through a meta-analysis (cg14020176, cg22650271, cg14870271, cg27243685, cg06378491, cg25130381) associated with GDM, and some of their methylation quantitative loci (mQTLs) were related to T2DM and GDM. CONCLUSION For the first time, we show that DNA methylation marks for T2DM are also associated with GDM, suggesting shared epigenetic mechanisms between GDM and T2DM.
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Affiliation(s)
- Teresa M Linares-Pineda
- Department of Endocrinology and Nutrition, Instituto de Investigación Biomédica Málaga (IBIMA)- Plataforma Bionand, University Hospital Virgen de la Victoria, Málaga, Spain
- Department of Biochemistry and Molecular Biology 2, University of Granada, Granada, Spain
- Centre for Biomedical Research Network on Obesity Physiopathology and Nutrition (CIBEROBN), Madrid, Spain
| | - Nicolas Fragoso-Bargas
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, 0424, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - María José Picón
- Department of Endocrinology and Nutrition, Instituto de Investigación Biomédica Málaga (IBIMA)- Plataforma Bionand, University Hospital Virgen de la Victoria, Málaga, Spain
| | - Maria Molina-Vega
- Department of Endocrinology and Nutrition, Instituto de Investigación Biomédica Málaga (IBIMA)- Plataforma Bionand, University Hospital Virgen de la Victoria, Málaga, Spain
| | - Anne Karen Jenum
- General Practice Research Unit (AFE), Department of General Practice, Institute of Health and Society, University of Oslo, Oslo, Norway
| | - Line Sletner
- Department of Pediatric and Adolescents Medicine, Akershus University Hospital, Lørenskog, Norway
| | - 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
- Haukeland University Hospital, Bergen, Norway
| | - Gunn-Helen Moen
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, 0424, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Institute of Molecular Bioscience, The University of Queensland, Brisbane, Australia
- K. G Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
- Frazer Institute, The University of Queensland, Woolloongabba, QLD, 4102, Australia
| | - Elisabeth Qvigstad
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, 0424, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Rashmi B Prasad
- Lund University Diabetes Centre, Malmo, Sweden
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Kåre I Birkeland
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, 0424, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Sonsoles Morcillo
- Department of Endocrinology and Nutrition, Instituto de Investigación Biomédica Málaga (IBIMA)- Plataforma Bionand, University Hospital Virgen de la Victoria, Málaga, Spain
- Centre for Biomedical Research Network on Obesity Physiopathology and Nutrition (CIBEROBN), Madrid, Spain
| | - Christine Sommer
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, 0424, Norway.
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Lu AKM, Lin JJ, Tseng HH, Wang XY, Jang FL, Chen PS, Huang CC, Hsieh S, Lin SH. DNA methylation signature aberration as potential biomarkers in treatment-resistant schizophrenia: Constructing a methylation risk score using a machine learning method. J Psychiatr Res 2023; 157:57-65. [PMID: 36442407 DOI: 10.1016/j.jpsychires.2022.11.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 11/08/2022] [Accepted: 11/12/2022] [Indexed: 11/18/2022]
Abstract
Treatment-resistant schizophrenia (TRS) is defined as a non-response to at least two trials of antipsychotic medication with an adequate dose and duration. We aimed to evaluate the discriminant abilities of DNA methylation probes and methylation risk score between treatment-resistant schizophrenia and non-treatment-resistant schizophrenia. This study recruited 96 schizophrenia patients (TRS and non-TRS) and 56 healthy controls (HC). Participants were divided into a discovery set and a validation set. In the discovery set, we conducted genome-wide methylation analysis (human MethylationEPIC 850K BeadChip) on the subject's blood DNA and discriminated significant methylation signatures, then verified these methylation signatures in the validation set. Based on genome-wide scans of TRS versus non-TRS, thirteen differentially methylated probes were identified at FDR <0.05 and >20% differences in DNA methylation β-values. Next, we selected six probes within gene coding regions (LOC404266, LOXL2, CERK, CHMP7, and SLC17A9) to conduct verification in the validation set using quantitative methylation-specific PCR (qMSP). These six methylation probes showed satisfactory discrimination between TRS patients and non-TRS patients, with an AUC ranging from 0.83 to 0.92, accuracy ranging from 77.8% to 87.3%, sensitivity ranging from 80% to 90%, and specificity ranging from 65.6% to 85%. This methylation risk score model showed satisfactory discrimination between TRS patients and non-TRS patients, with an accuracy of 88.3%. These findings support that methylation signatures may be used as an indicator of TRS vulnerability and provide a model for the clinical use of methylation to identify TRS.
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Affiliation(s)
- Andrew Ke-Ming Lu
- Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Jin-Jia Lin
- Department of Psychiatry, Chi Mei Medical Center, Tainan, Taiwan
| | - Huai-Hsuan Tseng
- Department of Psychiatry, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Xin-Yu Wang
- Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Fong-Lin Jang
- Department of Psychiatry, Chi Mei Medical Center, Tainan, Taiwan
| | - Po-See Chen
- Department of Psychiatry, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Institute of Behavioral Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Chih-Chun Huang
- Department of Psychiatry, National Cheng Kung University Hospital, Dou-Liou Branch, Yunlin, Taiwan
| | - Shulan Hsieh
- Department of Psychology, College of Social Sciences, National Cheng Kung University, Tainan, Taiwan
| | - Sheng-Hsiang Lin
- Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Department of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Biostatistics Consulting Center, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
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Ammous F, Zhao W, Lin L, Ratliff SM, Mosley TH, Bielak LF, Zhou X, Peyser PA, Kardia SLR, Smith JA. Epigenetics of single-site and multi-site atherosclerosis in African Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA). Clin Epigenetics 2022; 14:10. [PMID: 35039093 PMCID: PMC8764761 DOI: 10.1186/s13148-022-01229-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 01/05/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND DNA methylation, an epigenetic mechanism modulated by lifestyle and environmental factors, may be an important biomarker of complex diseases including cardiovascular diseases (CVD) and subclinical atherosclerosis. METHODS DNA methylation in peripheral blood samples from 391 African-Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA) was assessed at baseline, and atherosclerosis was assessed 5 and 12 years later. Using linear mixed models, we examined the association between previously identified CpGs for coronary artery calcification (CAC) and carotid plaque, both individually and aggregated into methylation risk scores (MRSCAC and MRScarotid), and four measures of atherosclerosis (CAC, abdominal aorta calcification (AAC), ankle-brachial index (ABI), and multi-site atherosclerosis based on gender-specific quartiles of the single-site measures). We also examined the association between four epigenetic age acceleration measures (IEAA, EEAA, PhenoAge acceleration, and GrimAge acceleration) and the four atherosclerosis measures. Finally, we characterized the temporal stability of the epigenetic measures using repeated DNA methylation measured 5 years after baseline (N = 193). RESULTS After adjusting for CVD risk factors, four CpGs (cg05575921(AHRR), cg09935388 (GFI1), cg21161138 (AHRR), and cg18168448 (LRRC52)) were associated with multi-site atherosclerosis (FDR < 0.1). cg05575921 was also associated with AAC and cg09935388 with ABI. MRSCAC was associated with ABI (Beta = 0.016, P = 0.006), and MRScarotid was associated with both AAC (Beta = 0.605, equivalent to approximately 1.8-fold increase in the Agatston score of AAC, P = 0.004) and multi-site atherosclerosis (Beta = 0.691, P = 0.002). A 5-year increase in GrimAge acceleration (~ 1 SD) was associated with a 1.6-fold (P = 0.012) increase in the Agatston score of AAC and 0.7 units (P = 0.0003) increase in multi-site atherosclerosis, all after adjusting for CVD risk factors. All epigenetic measures were relatively stable over 5 years, with the highest intraclass correlation coefficients observed for MRScarotid and GrimAge acceleration (0.87 and 0.89, respectively). CONCLUSIONS We found evidence of an association between DNA methylation and atherosclerosis at multiple vascular sites in a sample of African-Americans. Further evaluation of these potential biomarkers is warranted to deepen our understanding of the relationship between epigenetics and atherosclerosis.
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Affiliation(s)
- Farah Ammous
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Lisha Lin
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Scott M Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Thomas H Mosley
- Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, MS, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Xiang Zhou
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA.
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Onwuka JU, Li D, Liu Y, Huang H, Xu J, Liu Y, Zhang Y, Zhao Y. A panel of DNA methylation signature from peripheral blood may predict colorectal cancer susceptibility. BMC Cancer 2020; 20:692. [PMID: 32711505 PMCID: PMC7382833 DOI: 10.1186/s12885-020-07194-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Accepted: 07/19/2020] [Indexed: 02/07/2023] Open
Abstract
Background Differential DNA methylation panel derived from peripheral blood could serve as biomarkers of CRC susceptibility. However, most of the previous studies utilized post-diagnostic blood DNA which may be markers of disease rather than susceptibility. In addition, only a few studies have evaluated the predictive potential of differential DNA methylation in CRC in a prospective cohort and on a genome-wide basis. The aim of this study was to identify a potential panel of DNA methylation biomarkers in peripheral blood that is associated with CRC risk and therefore serve as epigenetic biomarkers of disease susceptibility. Methods DNA methylation profile of a nested case-control study with 166 CRC and 424 healthy normal subjects were obtained from the Gene Expression Omnibus (GEO) database. The differentially methylated markers were identified by moderated t-statistics. The DNA methylation panel was constructed by stepwise logistic regression and the least absolute shrinkage and selection operator in the training dataset. A methylation risk score (MRS) model was constructed and the association between MRS and CRC risk assessed. Results We identified 48 differentially methylated CpGs sites, of which 33 were hypomethylated. Of these, sixteen-CpG based MRS that was associated with CRC risk (OR = 2.68, 95% CI: 2.13, 3.38, P < 0.0001) was constructed. This association is confirmed in the testing dataset (OR = 2.02, 95% CI: 1.48, 2.74, P < 0.0001) and persisted in both males and females, younger and older subjects, short and long time-to-diagnosis. The MRS also predicted CRC with AUC 0.82 (95% CI: 0.76, 0.88), indicating high accuracy. Conclusions Our study has identified a novel DNA methylation panel that is associated with CRC and could, if validated be useful for the prediction of CRC risk in the future.
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Affiliation(s)
- Justina Ucheojor Onwuka
- Department of Epidemiology, Public Health College, Harbin Medical University, 157 Baojian Street, Nangang District, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Dapeng Li
- Department of Epidemiology, Public Health College, Harbin Medical University, 157 Baojian Street, Nangang District, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Yupeng Liu
- Department of Epidemiology, Public Health College, Harbin Medical University, 157 Baojian Street, Nangang District, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Hao Huang
- Department of Epidemiology, Public Health College, Harbin Medical University, 157 Baojian Street, Nangang District, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Jing Xu
- Department of Epidemiology, Public Health College, Harbin Medical University, 157 Baojian Street, Nangang District, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Ying Liu
- Department of Epidemiology, Public Health College, Harbin Medical University, 157 Baojian Street, Nangang District, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Yuanyuan Zhang
- Department of Epidemiology, Public Health College, Harbin Medical University, 157 Baojian Street, Nangang District, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Yashuang Zhao
- Department of Epidemiology, Public Health College, Harbin Medical University, 157 Baojian Street, Nangang District, Harbin, 150081, Heilongjiang Province, People's Republic of China.
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