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Shi Q, Song G, Song L, Wang Y, Ma J, Zhang L, Yuan E. Unravelling the function of prdm16 in human tumours: A comparative analysis of haematologic and solid tumours. Biomed Pharmacother 2024; 178:117281. [PMID: 39137651 DOI: 10.1016/j.biopha.2024.117281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Revised: 08/03/2024] [Accepted: 08/07/2024] [Indexed: 08/15/2024] Open
Abstract
Extensive research has shown that PR domain 16 (PRDM16) plays a critical role in adipose tissue metabolism, including processes such as browning and thermogenesis of adipocytes, beigeing of adipocytes, and adipogenic differentiation of myoblasts. These functions have been associated with diseases such as obesity and diabetes. Additionally, PRDM16 has been correlated with various other conditions, including migraines, heterochromatin abnormalities, metabolic syndrome, cardiomyopathy, sarcopenia, nonsyndromic cleft lip, and essential hypertension, among others. However, there is currently no systematic or comprehensive conclusion regarding the mechanism of PRDM16 in human tumours, including haematologic and solid tumours. The aim of this review is to provide an overview of the research progress on PRDM16 in haematologic and solid tumours by incorporating recent literature findings. Furthermore, we explore the prospects of PRDM16 in the precise diagnosis and treatment of human haematologic and solid tumours.
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Affiliation(s)
- Qianqian Shi
- Department of Laboratory Medicine, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Zhengzhou Key Laboratory for In Vitro Diagnosis of Hypertensive Disorders of Pregnancy, Zhengzhou, Henan 450052, China; Tianjian Laboratory of Advanced Biomedical Sciences, Institute of Advanced Biomedical Sciences, Zhengzhou University, Zhengzhou, Henan 450000, China.
| | - Guangyong Song
- Department of Laboratory Medicine, The First Affiliated Hospital, Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Liying Song
- Department of Laboratory Medicine, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Zhengzhou Key Laboratory for In Vitro Diagnosis of Hypertensive Disorders of Pregnancy, Zhengzhou, Henan 450052, China
| | - Yu Wang
- Department of Laboratory Medicine, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Zhengzhou Key Laboratory for In Vitro Diagnosis of Hypertensive Disorders of Pregnancy, Zhengzhou, Henan 450052, China
| | - Jun Ma
- Department of Laboratory Medicine, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Zhengzhou Key Laboratory for In Vitro Diagnosis of Hypertensive Disorders of Pregnancy, Zhengzhou, Henan 450052, China
| | - Linlin Zhang
- Department of Laboratory Medicine, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Zhengzhou Key Laboratory for In Vitro Diagnosis of Hypertensive Disorders of Pregnancy, Zhengzhou, Henan 450052, China; Tianjian Laboratory of Advanced Biomedical Sciences, Institute of Advanced Biomedical Sciences, Zhengzhou University, Zhengzhou, Henan 450000, China.
| | - Enwu Yuan
- Department of Laboratory Medicine, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China; Zhengzhou Key Laboratory for In Vitro Diagnosis of Hypertensive Disorders of Pregnancy, Zhengzhou, Henan 450052, China; Tianjian Laboratory of Advanced Biomedical Sciences, Institute of Advanced Biomedical Sciences, Zhengzhou University, Zhengzhou, Henan 450000, China.
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Long P, Si J, Zhu Z, Jiang Y, Wang Y, Jiang Q, Li W, Xu X, You Y, Qu M, Wang H, Mo T, Liu K, Jiang J, Wang Q, Yu C, Guo Y, Millwood IY, Walters RG, He X, Yuan Y, Wang H, Zhang X, He M, Guo H, Chen Z, Li L, Lv J, Wang C, Wu T. Genome-wide DNA methylation profiling in blood reveals epigenetic signature of incident acute coronary syndrome. Nat Commun 2024; 15:7431. [PMID: 39198424 PMCID: PMC11358540 DOI: 10.1038/s41467-024-51751-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 08/14/2024] [Indexed: 09/01/2024] Open
Abstract
DNA methylation (DNAm) has been implicated in acute coronary syndrome (ACS), but the causality remains unclear in cross-sectional studies. Here, we conduct a prospective epigenome-wide association study of incident ACS in two Chinese cohorts (discovery: 751 nested case-control pairs; replication: 476 nested case-control pairs). We identified and validated 26 differentially methylated positions (DMPs, false discovery rate [FDR] <0.05), including three mapped to known cardiovascular disease genes (PRKCZ, PRDM16, EHBP1L1) and four with causal evidence from Mendelian randomization (PRKCZ, TRIM27, EMC2, EHBP1L1). Two hypomethylated DMPs were negatively correlated with the expression in blood of their mapped genes (PIGG and EHBP1L1), which were further found to overexpress in leukocytes and/or atheroma plaques. Finally, our DMPs could substantially improve the prediction of ACS over traditional risk factors and polygenic scores. These findings demonstrate the importance of DNAm in the pathogenesis of ACS and highlight DNAm as potential predictive biomarkers and treatment targets.
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Affiliation(s)
- Pinpin Long
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jiahui Si
- National Institute of Health Data Science at Peking University, Peking University, Beijing, China
| | - Ziwei Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yi Jiang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yufei Wang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Qin Jiang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Wending Li
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xuedan Xu
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yutong You
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Minghan Qu
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Huihui Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Tingting Mo
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Kang Liu
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jing Jiang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Qiuhong Wang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Yu Guo
- Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Iona Y Millwood
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Robin G Walters
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Ximiao He
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yu Yuan
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Hao Wang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiaomin Zhang
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Meian He
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Huan Guo
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China.
| | - Chaolong Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
| | - Tangchun Wu
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
- Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
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3
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Taschereau A, Thibeault K, Allard C, Juvinao-Quintero D, Perron P, Lutz SM, Bouchard L, Hivert MF. Maternal glycemia in pregnancy is longitudinally associated with blood DNAm variation at the FSD1L gene from birth to 5 years of age. Clin Epigenetics 2023; 15:107. [PMID: 37386647 PMCID: PMC10308691 DOI: 10.1186/s13148-023-01524-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 06/23/2023] [Indexed: 07/01/2023] Open
Abstract
BACKGROUND In utero exposure to maternal hyperglycemia has been associated with an increased risk for the development of chronic diseases in later life. These predispositions may be programmed by fetal DNA methylation (DNAm) changes that persist postnatally. However, although some studies have associated fetal exposure to gestational hyperglycemia with DNAm variations at birth, and metabolic phenotypes in childhood, no study has yet examined how maternal hyperglycemia during pregnancy may be associated with offspring DNAm from birth to five years of age. HYPOTHESIS Maternal hyperglycemia is associated with variation in offspring DNAm from birth to 5 years of age. METHODS We estimated maternal hyperglycemia using the area under the curve for glucose (AUCglu) following an oral glucose tolerance test conducted at 24-30 weeks of pregnancy. We quantified DNAm levels in cord blood (n = 440) and peripheral blood at five years of age (n = 293) using the Infinium MethylationEPIC BeadChip (Illumina). Our total sample included 539 unique dyads (mother-child) with 194 dyads having DNAm at both time-points. We first regressed DNAm M-values against the cell types and child age for each time-point separately to account for the difference by time of measurement for these variables. We then used a random intercept model from the linear mixed model (LMM) framework to assess the longitudinal association between maternal AUCglu and the repeated measures of residuals of DNAm. We adjusted for the following covariates as fixed effects in the random intercept model: maternal age, gravidity, smoking status, child sex, maternal body mass index (BMI) (measured at first trimester of pregnancy), and a binary variable for time-point. RESULTS In utero exposure to higher maternal AUCglu was associated with lower offspring blood DNAm levels at cg00967989 located in FSD1L gene (β = - 0.0267, P = 2.13 × 10-8) in adjusted linear regression mixed models. Our study also reports other CpG sites for which DNAm levels were suggestively associated (P < 1.0 × 10-5) with in utero exposure to gestational hyperglycemia. Two of these (cg12140144 and cg07946633) were found in the promotor region of PRDM16 gene (β: - 0.0251, P = 4.37 × 10-07 and β: - 0.0206, P = 2.24 × 10-06, respectively). CONCLUSION Maternal hyperglycemia is associated with offspring DNAm longitudinally assessed from birth to 5 years of age.
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Affiliation(s)
- Amélie Taschereau
- Department of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences (FMHS), Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Kathrine Thibeault
- Department of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences (FMHS), Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Catherine Allard
- Centre de Recherche du Centre hospitalier universitaire de Sherbrooke (CR-CHUS), Sherbrooke, QC, Canada
| | | | - Patrice Perron
- Centre de Recherche du Centre hospitalier universitaire de Sherbrooke (CR-CHUS), Sherbrooke, QC, Canada
- Department of Medicine, FMHS, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Sharon M Lutz
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Luigi Bouchard
- Department of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences (FMHS), Université de Sherbrooke, Sherbrooke, QC, Canada.
- Department of Medicine, FMHS, Université de Sherbrooke, Sherbrooke, QC, Canada.
- Clinical Department of Laboratory Medicine, Pavillon des Augustines, Centre intégré universitaire de santé et de services sociaux (CIUSSS) du Saguenay-Lac-Saint-Jean - Hôpital de Chicoutimi, 305 rue St-Vallier, Saguenay, QC, G7H 5H6, Canada.
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
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Alfano R, Zugna D, Barros H, Bustamante M, Chatzi L, Ghantous A, Herceg Z, Keski-Rahkonen P, de Kok TM, Nawrot TS, Relton CL, Robinson O, Roumeliotaki T, Scalbert A, Vrijheid M, Vineis P, Richiardi L, Plusquin M. Cord blood epigenome-wide meta-analysis in six European-based child cohorts identifies signatures linked to rapid weight growth. BMC Med 2023; 21:17. [PMID: 36627699 PMCID: PMC9831885 DOI: 10.1186/s12916-022-02685-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 11/29/2022] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Rapid postnatal growth may result from exposure in utero or early life to adverse conditions and has been associated with diseases later in life and, in particular, with childhood obesity. DNA methylation, interfacing early-life exposures and subsequent diseases, is a possible mechanism underlying early-life programming. METHODS Here, a meta-analysis of Illumina HumanMethylation 450K/EPIC-array associations of cord blood DNA methylation at single CpG sites and CpG genomic regions with rapid weight growth at 1 year of age (defined with reference to WHO growth charts) was conducted in six European-based child cohorts (ALSPAC, ENVIRONAGE, Generation XXI, INMA, Piccolipiù, and RHEA, N = 2003). The association of gestational age acceleration (calculated using the Bohlin epigenetic clock) with rapid weight growth was also explored via meta-analysis. Follow-up analyses of identified DNA methylation signals included prediction of rapid weight growth, mediation of the effect of conventional risk factors on rapid weight growth, integration with transcriptomics and metabolomics, association with overweight in childhood (between 4 and 8 years), and comparison with previous findings. RESULTS Forty-seven CpGs were associated with rapid weight growth at suggestive p-value <1e-05 and, among them, three CpGs (cg14459032, cg25953130 annotated to ARID5B, and cg00049440 annotated to KLF9) passed the genome-wide significance level (p-value <1.25e-07). Sixteen differentially methylated regions (DMRs) were identified as associated with rapid weight growth at false discovery rate (FDR)-adjusted/Siddak p-values < 0.01. Gestational age acceleration was associated with decreasing risk of rapid weight growth (p-value = 9.75e-04). Identified DNA methylation signals slightly increased the prediction of rapid weight growth in addition to conventional risk factors. Among the identified signals, three CpGs partially mediated the effect of gestational age on rapid weight growth. Both CpGs (N=3) and DMRs (N=3) were associated with differential expression of transcripts (N=10 and 7, respectively), including long non-coding RNAs. An AURKC DMR was associated with childhood overweight. We observed enrichment of CpGs previously reported associated with birthweight. CONCLUSIONS Our findings provide evidence of the association between cord blood DNA methylation and rapid weight growth and suggest links with prenatal exposures and association with childhood obesity providing opportunities for early prevention.
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Affiliation(s)
- Rossella Alfano
- Medical Research Council Centre for Environment and Health, Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium
| | - Daniela Zugna
- Department of Medical Sciences, University of Turin and CPO-Piemonte, Turin, Italy
| | - Henrique Barros
- Institute of Public Health, University of Porto, Porto, Portugal
| | - Mariona Bustamante
- ISGlobal, Institute of Global Health, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública, Madrid, Spain
| | - Leda Chatzi
- Department of Preventive Medicine, University of Southern California, Los Angeles, USA
| | - Akram Ghantous
- International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69008, Lyon, France
| | - Zdenko Herceg
- International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69008, Lyon, France
| | - Pekka Keski-Rahkonen
- International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69008, Lyon, France
| | - Theo M de Kok
- Department of Toxicogenomics, Maastricht University, Maastricht, The Netherlands
| | - Tim S Nawrot
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium
| | - Caroline L Relton
- Μedical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Oliver Robinson
- Medical Research Council Centre for Environment and Health, Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK
- Mohn Centre for Children's Health and Well-being, The School of Public Health, Imperial College London, London, UK
| | - Theano Roumeliotaki
- Department of Social Medicine, Faculty of Medicine, University of Crete, Heraklion, Greece
| | - Augustin Scalbert
- International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69008, Lyon, France
| | - Martine Vrijheid
- International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69008, Lyon, France
| | - Paolo Vineis
- Medical Research Council Centre for Environment and Health, Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK
| | - Lorenzo Richiardi
- Department of Medical Sciences, University of Turin and CPO-Piemonte, Turin, Italy
| | - Michelle Plusquin
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium.
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Epigenome Modulation Induced by Ketogenic Diets. Nutrients 2022; 14:nu14153245. [PMID: 35956421 PMCID: PMC9370515 DOI: 10.3390/nu14153245] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 08/02/2022] [Accepted: 08/04/2022] [Indexed: 11/17/2022] Open
Abstract
Ketogenic diets (KD) are dietary strategies low in carbohydrates, normal in protein, and high, normal, or reduced in fat with or without (Very Low-Calories Ketogenic Diet, VLCKD) a reduced caloric intake. KDs have been shown to be useful in the treatment of obesity, metabolic diseases and related disorders, neurological diseases, and various pathological conditions such as cancer, nonalcoholic liver disease, and chronic pain. Several studies have investigated the intracellular metabolic pathways that contribute to the beneficial effects of these diets. Although epigenetic changes are among the most important determinants of an organism’s ability to adapt to environmental changes, data on the epigenetic changes associated with these dietary pathways are still limited. This review provides an overview of the major epigenetic changes associated with KDs.
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Ping Z, Guo Z, Lu M, Chen Y, Liu L. Association of CIDEB gene promoter methylation with overweight or obesity in adults. Aging (Albany NY) 2022; 14:3607-3616. [PMID: 35475772 PMCID: PMC9085220 DOI: 10.18632/aging.204032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 03/25/2022] [Indexed: 12/02/2022]
Abstract
Objective: To explore the association of the methylation level of cell death-inducing DFF45-like effector B (CIDEB) gene promoter with overweight or obesity in the abdominal subcutaneous adipose tissue (SAT) and omental adipose tissue (OAT) of adults. Methods: A total of 61 patients undergoing abdominal surgery in the hospital were selected with an average age of 51.87 years. According to the diagnostic criteria of Chinese adult obesity, the subjects were divided into normal-weight group (n = 28) and overweight/obesity group (n = 33). CIDEB promoter methylation level in abdominal SAT and OAT was detected by the MethylTarget technology, then its relationship with overweight or obesity was analyzed. Results: (1) There were no statistical differences between the normal-weight group and overweight/obesity group in Methylation levels of 16 CpG sites in the CIDEB gene promoter sequence. (2) The methylation level of OAT was higher than that of SAT, and there were significant differences in 16 CpG sites. (3) There were 3 statistically significant haplotypes between the normal-weight group and overweight/obesity group (2 in SAT and 1 in OAT). Conclusions: The methylation level of CIDEB gene promoter in abdominal SAT and OAT may be related to overweight or obesity in adults, and the specific regulatory mechanism needs to be further studied.
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Affiliation(s)
- Zhiguang Ping
- College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Zhaoyan Guo
- College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Ming Lu
- Nursing Department of Jiaozuo People's Hospital, Jiaozuo, Henan, China
| | - Yanzi Chen
- Henan Huapu Pharmaceutical Technology Co., Ltd., Zhengzhou, Henan, China
| | - Li Liu
- School of Basic Medical Sciences, Zhengzhou University, Zhengzhou, Henan, China
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7
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Jiang N, Yang M, Han Y, Zhao H, Sun L. PRDM16 Regulating Adipocyte Transformation and Thermogenesis: A Promising Therapeutic Target for Obesity and Diabetes. Front Pharmacol 2022; 13:870250. [PMID: 35462933 PMCID: PMC9024053 DOI: 10.3389/fphar.2022.870250] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Accepted: 03/11/2022] [Indexed: 11/13/2022] Open
Abstract
Given that obesity and diabetes have been major public health concerns and that disease morbidities have been rising continuously, effective treatment for these diseases is urgently needed. Because adipose tissue metabolism is involved in the progression of obesity and diabetes, it might be efficient to target adipocyte metabolic pathways. Positive regulatory domain zinc finger region protein 16 (PRDM16), a transcription factor that is highly expressed in adipocytes, plays a key role in adipose tissue metabolism, such as the browning and thermogenesis of adipocytes, the beigeing of adipocytes, the adipogenic differentiation of myoblasts, and the conversion of visceral adipocytes to subcutaneous adipocytes. Furthermore, clinical and basic studies have shown that the expression of PRDM16 is associated with obesity and diabetes and that PRDM16 signaling participates in the treatment of the two diseases. For example, metformin promotes thermogenesis and alleviates obesity by activating the AMPK/αKG/PRDM16 signaling pathway; rosiglitazone alleviates obesity under the synergistic effect of PRDM16; resveratrol plays an antiobesity role by inducing the expression of PRDM16; liraglupeptide improves insulin resistance by inducing the expression of PRDM16; and mulberry leaves play an anti-inflammatory and antidiabetes role by activating the expression of brown fat cell marker genes (including PRDM16). In this review, we summarize the evidence of PRDM16 involvement in the progression of obesity and diabetes and that PRDM16 may be a promising therapy for obesity and diabetes.
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Alfano R, Robinson O, Handakas E, Nawrot TS, Vineis P, Plusquin M. Perspectives and challenges of epigenetic determinants of childhood obesity: A systematic review. Obes Rev 2022; 23 Suppl 1:e13389. [PMID: 34816569 DOI: 10.1111/obr.13389] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 10/11/2021] [Indexed: 12/20/2022]
Abstract
The tremendous increase in childhood obesity prevalence over the last few decades cannot merely be explained by genetics and evolutionary changes in the genome, implying that gene-environment interactions, such as epigenetic modifications, likely play a major role. This systematic review aims to summarize the evidence of the association between epigenetics and childhood obesity. A literature search was performed via PubMed and Scopus engines using a combination of terms related to epigenetics and pediatric obesity. Articles studying the association between epigenetic mechanisms (including DNA methylation and hydroxymethylation, non-coding RNAs, and chromatin and histones modification) and obesity and/or overweight (or any related anthropometric parameters) in children (0-18 years) were included. The risk of bias was assessed with a modified Newcastle-Ottawa scale for non-randomized studies. One hundred twenty-one studies explored epigenetic changes related to childhood obesity. DNA methylation was the most widely investigated mechanism (N = 101 studies), followed by non-coding RNAs (N = 19 studies) with evidence suggestive of an association with childhood obesity for DNA methylation of specific genes and microRNAs (miRNAs). One study, focusing on histones modification, was identified. Heterogeneity of findings may have hindered more insights into the epigenetic changes related to childhood obesity. Gaps and challenges that future research should face are herein described.
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Affiliation(s)
- Rossella Alfano
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK.,Medical Research Council-Health Protection Agency Centre for Environment and Health, Imperial College London, London, UK.,Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium
| | - Oliver Robinson
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK.,Medical Research Council-Health Protection Agency Centre for Environment and Health, Imperial College London, London, UK
| | - Evangelos Handakas
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK.,Medical Research Council-Health Protection Agency Centre for Environment and Health, Imperial College London, London, UK
| | - Tim S Nawrot
- Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium
| | - Paolo Vineis
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK.,Medical Research Council-Health Protection Agency Centre for Environment and Health, Imperial College London, London, UK.,Unit of Molecular and Genetic Epidemiology, Human Genetic Foundation (HuGeF), Turin, Italy
| | - Michelle Plusquin
- Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium
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Tu R, Liu X, Dong X, Li R, Liao W, Hou J, Mao Z, Huo W, Wang C, Li Y. Janus kinase 2 (JAK2) methylation and obesity: A Mendelian randomization study. Nutr Metab Cardiovasc Dis 2021; 31:3484-3491. [PMID: 34656381 DOI: 10.1016/j.numecd.2021.08.046] [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: 04/07/2021] [Revised: 07/18/2021] [Accepted: 08/25/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND AND AIMS Janus kinase 2 (JAK2) play an important role in the energy metabolism. Whether there is a causal relationship between JAK2 methylation levels and obesity remains unclear. Based on the instrumental variables of 5 SNP sites, this study was aimed to explore the causal relationship between JAK2 methylation levels and obesity by Mendelian randomization analysis. METHODS AND RESULTS A total of 1021 participants (511 cases and 510 controls defined by body mass index (BMI) ≥ 28.0 kg/m2) was conducted from the Henan Rural Cohort study. SNPscan® was performed to test the SNP genotyping and MethylTarget™ was applied to detect the DNA methylation level. The logistic regression model was used to evaluate the associations between SNP or methylation of JAK2 and obesity (according to BMI). Mendelian randomization analysis was used to assess the potential causal association between JAK2 methylation and obesity. According to the logistic regression model, 1 CpG sit in the promotor was related to an increased risk of obesity (P < 0.05). 10 CpG sites in the exon were associated with decreased risk of obesity (P < 0.05). Mendelian randomization analysis showed a causal association between the methylated level of JAK2 and obesity, based on the instrumental variables of 5 SNPs (P < 0.05). CONCLUSIONS This study supported that the methylation degree of JAK2 has a complex relationship with obesity, which might be related to the region of methylation. A causal relationship exists between the methylated level of JAK2 and obesity.
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Affiliation(s)
- Runqi Tu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Xiaotian Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Xiaokang Dong
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Ruiying Li
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Wei Liao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Jian Hou
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Zhenxing Mao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Wenqian Huo
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Yuqian Li
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China; Department of Clinical Pharmacology, School of Pharmaceutical Science, Zhengzhou University, Zhengzhou, Henan, PR China.
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Crujeiras AB, Izquierdo AG, Primo D, Milagro FI, Sajoux I, Jácome A, Fernandez-Quintela A, Portillo MP, Martínez JA, Martinez-Olmos MA, de Luis D, Casanueva FF. Epigenetic landscape in blood leukocytes following ketosis and weight loss induced by a very low calorie ketogenic diet (VLCKD) in patients with obesity. Clin Nutr 2021; 40:3959-3972. [PMID: 34139469 DOI: 10.1016/j.clnu.2021.05.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 05/06/2021] [Accepted: 05/13/2021] [Indexed: 12/16/2022]
Abstract
BACKGROUND The molecular mechanisms underlying the potential health benefits of a ketogenic diet are unknown and could be mediated by epigenetic mechanisms. OBJECTIVE To identify the changes in the obesity-related methylome that are mediated by the induced weight loss or are dependent on ketosis in subjects with obesity underwent a very-low calorie ketogenic diet (VLCKD). METHODS Twenty-one patients with obesity (n = 12 women, 47.9 ± 1.02 yr, 33.0 ± 0.2 kg/m2) after 6 months on a VLCKD and 12 normal weight volunteers (n = 6 women, 50.3 ± 6.2 yrs, 22.7 ± 1.5 kg/m2) were studied. Data from the Infinium MethylationEPIC BeadChip methylomes of blood leukocytes were obtained at time points of ketotic phases (basal, maximum ketosis, and out of ketosis) during VLCKD (n = 10) and at baseline in volunteers (n = 12). Results were further validated by pyrosequencing in representative cohort of patients on a VLCKD (n = 18) and correlated with gene expression. RESULTS After weight reduction by VLCKD, differences were found at 988 CpG sites (786 unique genes). The VLCKD altered methylation levels in patients with obesity had high resemblance with those from normal weight volunteers and was concomitant with a downregulation of DNA methyltransferases (DNMT)1, 3a and 3b. Most of the encoded genes were involved in metabolic processes, protein metabolism, and muscle, organ, and skeletal system development. Novel genes representing the top scoring associated events were identified, including ZNF331, FGFRL1 (VLCKD-induced weight loss) and CBFA2T3, C3orf38, JSRP1, and LRFN4 (VLCKD-induced ketosis). Interestingly, ZNF331 and FGFRL1 were validated in an independent cohort and inversely correlated with gene expression. CONCLUSIONS The beneficial effects of VLCKD therapy on obesity involve a methylome more suggestive of normal weight that could be mainly mediated by the VLCKD-induced ketosis rather than weight loss.
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Affiliation(s)
- Ana B Crujeiras
- Epigenomics in Endocrinology and Nutrition Group, Epigenomics Unit, Instituto de Investigacion Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago de Compostela (CHUS/SERGAS), Spain; CIBER Fisiopatologia de La Obesidad y Nutricion (CIBERobn), Spain.
| | - Andrea G Izquierdo
- Epigenomics in Endocrinology and Nutrition Group, Epigenomics Unit, Instituto de Investigacion Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago de Compostela (CHUS/SERGAS), Spain; CIBER Fisiopatologia de La Obesidad y Nutricion (CIBERobn), Spain
| | - David Primo
- Center of Investigation of Endocrinology and Nutrition, Medicine School and Department of Endocrinology and Investigation, Hospital Clinico Universitario, University of Valladolid, Valladolid, Spain
| | - Fermin I Milagro
- Department of Nutrition, Food Science and Physiology, Centre for Nutrition Research, University of Navarra (UNAV) and IdiSNA, Navarra Institute for Health Research, 31009, Pamplona, Spain; CIBER Fisiopatologia de La Obesidad y Nutricion (CIBERobn), Spain
| | - Ignacio Sajoux
- Medical Department Pronokal Group, PronokalGroup, Barcelona, Spain
| | - Amalia Jácome
- Department of Mathematics, MODES Group, CITIC, Universidade da Coruña, Faculty of Science, A Coruña, Spain
| | - Alfredo Fernandez-Quintela
- Nutrition and Obesity Group, Department of Nutrition and Food Science, University of the Basque Country (UPV/EHU), Lucio Lascaray Research Institute and Health Research Institute BIOARABA, Vitoria, Spain; CIBER Fisiopatologia de La Obesidad y Nutricion (CIBERobn), Spain
| | - María P Portillo
- Nutrition and Obesity Group, Department of Nutrition and Food Science, University of the Basque Country (UPV/EHU), Lucio Lascaray Research Institute and Health Research Institute BIOARABA, Vitoria, Spain; CIBER Fisiopatologia de La Obesidad y Nutricion (CIBERobn), Spain
| | - J Alfredo Martínez
- Department of Nutrition, Food Science and Physiology, Centre for Nutrition Research, University of Navarra (UNAV) and IdiSNA, Navarra Institute for Health Research, 31009, Pamplona, Spain; CIBER Fisiopatologia de La Obesidad y Nutricion (CIBERobn), Spain
| | - Miguel A Martinez-Olmos
- Epigenomics in Endocrinology and Nutrition Group, Epigenomics Unit, Instituto de Investigacion Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago de Compostela (CHUS/SERGAS), Spain; CIBER Fisiopatologia de La Obesidad y Nutricion (CIBERobn), Spain
| | - Daniel de Luis
- Center of Investigation of Endocrinology and Nutrition, Medicine School and Department of Endocrinology and Investigation, Hospital Clinico Universitario, University of Valladolid, Valladolid, Spain
| | - Felipe F Casanueva
- Molecular and Cellular Endocrinology Group. Instituto de Investigacion Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago de Compostela (CHUS) and Santiago de Compostela University (USC), Spain; CIBER Fisiopatologia de La Obesidad y Nutricion (CIBERobn), Spain
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