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Argentato PP, Guerra JVDS, Luzia LA, Ramos ES, Maschietto M, Rondó PHDC. Excessive Gestational Weight Gain Alters DNA Methylation and Influences Foetal and Neonatal Body Composition. EPIGENOMES 2023; 7:18. [PMID: 37606455 PMCID: PMC10443290 DOI: 10.3390/epigenomes7030018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Revised: 07/29/2023] [Accepted: 07/31/2023] [Indexed: 08/23/2023] Open
Abstract
BACKGROUND Changes in body weight are associated with the regulation of DNA methylation (DNAm). In this study, we investigated the associations between maternal gestational weight gain-related DNAm and foetal and neonatal body composition. METHODS Brazilian pregnant women from the Araraquara Cohort Study were followed up during pregnancy, delivery, and after hospital discharge. Women with normal pre-pregnancy BMI were allocated into two groups: adequate gestational weight gain (AGWG, n = 45) and excessive gestational weight gain (EGWG, n = 30). Foetal and neonatal body composition was evaluated via ultrasound and plethysmography, respectively. DNAm was assessed in maternal blood using Illumina Infinium MethylationEPIC BeadChip arrays. Linear regression models were used to explore the associations between DNAm and foetal and neonatal body composition. RESULTS Maternal weight, GWG, neonatal weight, and fat mass were higher in the EGWG group. Analysis of DNAm identified 46 differentially methylated positions and 11 differentially methylated regions (DMRs) between the EGWG and AGWG groups. Nine human phenotypes were enriched for these 11 DMRs located in 13 genes (EMILIN1, HOXA5, CPT1B, CLDN9, ZFP57, BRCA1, POU5F1, ANKRD33, HLA-B, RANBP17, ZMYND11, DIP2C, TMEM232), highlighting the terms insulin resistance, and hyperglycaemia. Maternal DNAm was associated with foetal total thigh and arm tissues and subcutaneous thigh and arm fat, as well as with neonatal fat mass percentage and fat mass. CONCLUSION The methylation pattern in the EGWG group indicated a risk for developing chronic diseases and involvement of maternal DNAm in foetal lean and fat mass and in neonatal fat mass.
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Affiliation(s)
- Perla Pizzi Argentato
- Nutrition Department, School of Public Health, University of São Paulo, Avenida Dr. Arnaldo 715, São Paulo 01246-904, SP, Brazil; (P.P.A.); (L.A.L.)
| | - João Victor da Silva Guerra
- Brazilian Biosciences National Laboratory (LNBio), Brazilian Centre for Research in Energy and Materials (CNPEM) and Graduate Program in Pharmaceutical Sciences, Faculty of Pharmaceutical Sciences, University of Campinas, Rua Giuseppe Máximo Scolfaro 10.000, Cidade Universitária, Campinas 13083-970, SP, Brazil;
| | - Liania Alves Luzia
- Nutrition Department, School of Public Health, University of São Paulo, Avenida Dr. Arnaldo 715, São Paulo 01246-904, SP, Brazil; (P.P.A.); (L.A.L.)
| | - Ester Silveira Ramos
- Department of Genetics, Ribeirão Preto Medical School, University of São Paulo, Avenida Bandeirantes 3900, Ribeirão Preto 14049-900, SP, Brazil;
| | - Mariana Maschietto
- Boldrini Children’s Hospital, University of Campinas, Rua Márcia Mendes 619, Cidade Universitária, Campinas 13083-884, SP, Brazil;
| | - Patrícia Helen de Carvalho Rondó
- Nutrition Department, School of Public Health, University of São Paulo, Avenida Dr. Arnaldo 715, São Paulo 01246-904, SP, Brazil; (P.P.A.); (L.A.L.)
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Chowdhury SG, Misra S, Karmakar P. Understanding the Impact of Obesity on Ageing in the Radiance of DNA Metabolism. J Nutr Health Aging 2023; 27:314-328. [PMID: 37248755 DOI: 10.1007/s12603-023-1912-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 03/22/2023] [Indexed: 05/31/2023]
Abstract
Ageing is a multi-factorial phenomenon which is considered as a major risk factor for the development of neurodegeneration, osteoporosis, cardiovascular disease, dementia, cancer, and other chronic diseases. Phenotypically, ageing is related with a combination of molecular, cellular, and physiological levels like genomic and epi-genomic alterations, loss of proteostasis, deregulation of cellular and subcellular function and mitochondrial dysfunction. Though, no single molecular mechanism accounts for the functional decline of different organ systems in older humans but accumulation of DNA damage or mutations is a dominant theory which contributes largely to the development of ageing and age-related diseases. However, mechanistic, and hierarchical order of these features of ageing has not been clarified yet. Scientific community now focus on the effect of obesity on accelerated ageing process. Obesity is a complex chronic disease that affects multiple organs and tissues. It can not only lead to various health conditions such as diabetes, cancer, and cardiovascular disease but also can decrease life expectancy which shows similar phenotype of ageing. Higher loads of DNA damage were also observed in the genome of obese people. Thus, inability of DNA damage repair may contribute to both ageing and obesity apart from cancer predisposition. The present review emphasizes on the involvement of molecular phenomenon of DNA metabolism in development of obesity and how it accelerates ageing in mammals.
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Affiliation(s)
- S G Chowdhury
- Parimal Karmakar, Department of Life Science and Biotechnology, Jadavpur University, Kolkata-700032, India.
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Jürgens H, Roht L, Leitsalu L, Nõukas M, Palover M, Nikopensius T, Reigo A, Kals M, Kallak K, Kütner R, Budrikas K, Kuusk S, Valvere V, Laidre P, Toome K, Rekker K, Tooming M, Ülle Murumets, Kahre T, Kruuv-Käo K, Õunap K, Padrik P, Metspalu A, Esko T, Fischer K, Tõnisson N. Precise, Genotype-First Breast Cancer Prevention: Experience With Transferring Monogenic Findings From a Population Biobank to the Clinical Setting. Front Genet 2022; 13:881100. [PMID: 35938029 PMCID: PMC9355130 DOI: 10.3389/fgene.2022.881100] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 06/21/2022] [Indexed: 11/13/2022] Open
Abstract
Although hereditary breast cancer screening and management are well accepted and established in clinical settings, these efforts result in the detection of only a fraction of genetic predisposition at the population level. Here, we describe our experience from a national pilot study (2018-2021) in which 180 female participants of Estonian biobank (of >150,000 participants in total) were re-contacted to discuss personalized clinical prevention measures based on their genetic predisposition defined by 11 breast cancer-related genes. Our results show that genetic risk variants are relatively common in the average-risk Estonian population. Seventy-five percent of breast cancer cases in at-risk subjects occurred before the age of 50 years. Only one-third of subjects would have been eligible for clinical screening according to the current criteria. The participants perceived the receipt of genetic risk information as valuable. Fluent cooperation of project teams supported by state-of-art data management, quality control, and secure transfer can enable the integration of research results to everyday medical practice in a highly efficient, timely, and well-accepted manner. The positive experience in this genotype-first breast cancer study confirms the value of using existing basic genomic data from population biobanks for precise prevention.
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Affiliation(s)
- Hannes Jürgens
- Tartu University Hospital, Clinic of Hematology and Oncology, Tartu, Estonia
- University of Tartu, Clinic of Hematology and Oncology, Tartu, Estonia
| | - Laura Roht
- Department of Clinical Genetics, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
- Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
| | - Liis Leitsalu
- Estonian Biobank, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Margit Nõukas
- Estonian Biobank, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Marili Palover
- Estonian Biobank, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Tiit Nikopensius
- Estonian Biobank, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Anu Reigo
- Estonian Biobank, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Mart Kals
- Estonian Biobank, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Kersti Kallak
- Tartu University Hospital, Clinic of Hematology and Oncology, Tartu, Estonia
- University of Tartu, Clinic of Hematology and Oncology, Tartu, Estonia
| | - Riina Kütner
- North-Estonian Medical Center, Oncology and Haematology Clinic, Tallinn, Estonia
| | - Kai Budrikas
- Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
| | - Saskia Kuusk
- Estonian Biobank, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
| | - Vahur Valvere
- North-Estonian Medical Center, Oncology and Haematology Clinic, Tallinn, Estonia
| | - Piret Laidre
- Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
| | - Kadri Toome
- Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
| | - Kadri Rekker
- Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
| | - Mikk Tooming
- Department of Clinical Genetics, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
- Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
| | - Ülle Murumets
- Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
| | - Tiina Kahre
- Department of Clinical Genetics, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
- Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
| | - Krista Kruuv-Käo
- Estonian Biobank, Institute of Genomics, University of Tartu, Tartu, Estonia
- Tartu University Hospital, Tartu, Estonia
| | - Katrin Õunap
- Department of Clinical Genetics, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
- Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
| | - Peeter Padrik
- Tartu University Hospital, Clinic of Hematology and Oncology, Tartu, Estonia
- University of Tartu, Clinic of Hematology and Oncology, Tartu, Estonia
- Antegenes, Tartu, Estonia
| | - Andres Metspalu
- Estonian Biobank, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Tõnu Esko
- Estonian Biobank, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Krista Fischer
- Estonian Biobank, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
| | - Neeme Tõnisson
- Genetics and Personalized Medicine Clinic, Tartu University Hospital, Tartu, Estonia
- Estonian Biobank, Institute of Genomics, University of Tartu, Tartu, Estonia
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Obesity: The Fat Tissue Disease Version of Cancer. Cells 2022; 11:cells11121872. [PMID: 35741001 PMCID: PMC9221301 DOI: 10.3390/cells11121872] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 06/02/2022] [Accepted: 06/06/2022] [Indexed: 02/06/2023] Open
Abstract
Obesity is a disease with high potential for fatality. It perfectly fits the disease definition, as cancer does. This is because it damages body structure and functions, both mechanically and biologically, and alters physical, mental, and social health. In addition, it shares many common morbid characteristics with the most feared disease, cancer. For example, it is influenced by a sophisticated interaction between a person’s genetics, the environment, and an increasing number of other backgrounds. Furthermore, it displays abnormal cell growth and proliferation events, only limited to white fat, resulting in adipose tissue taking up an increasing amount of space within the body. This occurs through fat “metastases” and via altered signaling that further aggravates the pathology of obesity by inducing ubiquitous dishomeostasis. These metastases can be made graver by angiogenesis, which might boost diseased tissue growth. More common features with cancer include its progressive escalation through different levels of severity and its possibility of re-onset after recovery. Despite all these similarities with cancer, obesity is substantially less agitating for most people. Thus, the ideas proposed herein could have utility to sensitize the public opinion about the hard reality of obesity. This is increasingly needed, as the obesity pandemic has waged a fierce war against our bodies and society in general, while there is still doubt about whether it is a real disease or not. Hence, raising public consciousness to properly face health issues is crucial to improving our health instead of gaining weight unhealthily. It is obviously illogical to fight cancer extremely seriously on the one hand and to consider dying with obesity as self-inflicted on the other. In fact, obesity merits a top position among the most lethal diseases besides cancer.
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Desharnais L, Walsh LA, Quail DF. Exploiting the obesity-associated immune microenvironment for cancer therapeutics. Pharmacol Ther 2021; 229:107923. [PMID: 34171329 DOI: 10.1016/j.pharmthera.2021.107923] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 05/11/2021] [Accepted: 06/10/2021] [Indexed: 12/12/2022]
Abstract
Obesity causes chronic low-grade inflammation and leads to changes in the immune landscape of multiple organ systems. Given the link between chronic inflammatory conditions and cancer, it is not surprising that obesity is associated with increased risk and worse outcomes in many malignancies. Paradoxically, recent epidemiological studies have shown that high BMI is associated with increased efficacy of immune checkpoint inhibitors (ICI), and a causal relationship has been demonstrated in the preclinical setting. It has been proposed that obesity-associated immune dysregulation underlies this observation by inadvertently creating a favourable microenvironment for increased ICI efficacy. The recent success of ICIs in obese cancer patients raises the possibility that additional immune-targeted therapies may hold therapeutic value in this context. Here we review how obesity affects the immunological composition of the tumor microenvironment in ways that can be exploited for cancer immunotherapies. We discuss existing literature supporting a beneficial role for obesity during ICI therapy in cancer patients, potential opportunities for targeting the innate immune system to mitigate chronic inflammatory processes, and how to pinpoint obese patients who are most likely to benefit from immune interventions without relying solely on body mass index. Given that the incidence of obesity is expanding on an international scale, we propose that understanding obesity-associated inflammation is necessary to reduce cancer mortalities and capitalize on novel therapeutic opportunities in the era of cancer immunotherapy.
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Affiliation(s)
- Lysanne Desharnais
- Rosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, QC, Canada; Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Logan A Walsh
- Rosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, QC, Canada; Department of Human Genetics, McGill University, Montreal, QC, Canada.
| | - Daniela F Quail
- Rosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, QC, Canada; Department of Physiology, Faculty of Medicine, McGill University, Montreal, QC, Canada; Department of Medicine, Division of Experimental Medicine, McGill University, Montreal, QC, Canada.
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