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Ma Z, Chai Z, Yang H, Zhang X, Zhao H, Luo X, Zhong J, Wu Z. Comprehensive analysis of the expression patterns and function of the FTO-LINE1 axis in yak tissues and muscle satellite cells. Front Vet Sci 2024; 11:1448587. [PMID: 39301283 PMCID: PMC11410761 DOI: 10.3389/fvets.2024.1448587] [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: 06/13/2024] [Accepted: 08/27/2024] [Indexed: 09/22/2024] Open
Abstract
Background The long interspersed nuclear element 1 (LINE1) retrotransposon has been identified as a specific substrate for fat mass and obesity-related gene (FTO), which facilitates the removal of N6-methyladenosine modifications from its targeted RNAs. Methods This study examined the dynamic interaction between FTO and LINE1 in yak tissues and muscle satellite cells, utilizing RT-qPCR, RNA immunoprecipitation (RIP), immunofluorescence staining, and techniques involving overexpression and interference of FTO and LINE1 to elucidate the relationship between FTO and LINE1 in yak tissues and muscle satellite cells. Results Cloning and analysis of the FTO coding sequence in Jiulong yak revealed a conserved protein structure across various Bos breeds, with notable homology observed with domestic yak, domestic cattle, and Java bison. Comprehensive examination of FTO and LINE1 gene expression patterns in Jiulong yaks revealed consistent trends across tissues in both sexes. FTO mRNA levels were markedly elevated in the heart and kidney, while LINE1 RNA was predominantly expressed in the heart. Immunoprecipitation confirmed the direct interaction between the FTO protein and LINE1 RNA in yak tissues and muscle satellite cells. The FTO-LINE1 axis was confirmed by a significant decrease in LINE1 RNA enrichment following its expression interference in yak muscle satellite cells. Overexpression of FTO substantially reduced the expression of recombinant myogenic factor 5 (MYF5). However, FTO interference had no discernible effect on MYF5 and myoblast determination protein 1 (MYOD1) mRNA levels. Immunofluorescence analysis revealed no alterations in Ki-67 protein expression following FTO interference or overexpression. However, phalloidin staining demonstrated enhancement in the myotube fusion rate of yak muscle satellite cells upon LINE1 interference. Conclusion This comprehensive mapping of the FTO and LINE1 mRNA expression patterns establishes a direct interaction between the FTO protein and LINE1 RNA in yak. The findings suggest that FTO overexpression promotes muscle satellite cells differentiation, whereas LINE1 negatively regulates myotube fusion. The study provides fundamental insights into the role of the FTO-LINE1 axis in determining the fate of muscle satellite cells in yak, laying a solid theoretical foundation for future investigations.
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Affiliation(s)
- Zongliang Ma
- Qinghai-Tibetan Plateau Grass-Feeding Livestock Engineering Technology Research Center of Sichuan Province, Southwest Minzu University, Chengdu, China
- Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization Key Laboratory of Sichuan Province, Southwest Minzu University, Chengdu, China
- Sichuan Academy of Grassland Sciences, Chengdu, China
| | - Zhixin Chai
- Qinghai-Tibetan Plateau Grass-Feeding Livestock Engineering Technology Research Center of Sichuan Province, Southwest Minzu University, Chengdu, China
- Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization Key Laboratory of Sichuan Province, Southwest Minzu University, Chengdu, China
| | - Huan Yang
- Qinghai-Tibetan Plateau Grass-Feeding Livestock Engineering Technology Research Center of Sichuan Province, Southwest Minzu University, Chengdu, China
- Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization Key Laboratory of Sichuan Province, Southwest Minzu University, Chengdu, China
| | | | - Hongwen Zhao
- Sichuan Academy of Grassland Sciences, Chengdu, China
| | - Xiaolin Luo
- Sichuan Academy of Grassland Sciences, Chengdu, China
| | - Jincheng Zhong
- Qinghai-Tibetan Plateau Grass-Feeding Livestock Engineering Technology Research Center of Sichuan Province, Southwest Minzu University, Chengdu, China
- Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization Key Laboratory of Sichuan Province, Southwest Minzu University, Chengdu, China
- Institute of Qinghai-Tibetan Plateau, Southwest Minzu University, Chengdu, China
| | - Zhijuan Wu
- Qinghai-Tibetan Plateau Grass-Feeding Livestock Engineering Technology Research Center of Sichuan Province, Southwest Minzu University, Chengdu, China
- Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization Key Laboratory of Sichuan Province, Southwest Minzu University, Chengdu, China
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Mehta NH, Huey SL, Kuriyan R, Peña-Rosas JP, Finkelstein JL, Kashyap S, Mehta S. Potential Mechanisms of Precision Nutrition-Based Interventions for Managing Obesity. Adv Nutr 2024; 15:100186. [PMID: 38316343 PMCID: PMC10914563 DOI: 10.1016/j.advnut.2024.100186] [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] [Received: 09/20/2023] [Revised: 01/17/2024] [Accepted: 02/01/2024] [Indexed: 02/07/2024] Open
Abstract
Precision nutrition (PN) considers multiple individual-level and environmental characteristics or variables to better inform dietary strategies and interventions for optimizing health, including managing obesity and metabolic disorders. Here, we review the evidence on potential mechanisms-including ones to identify individuals most likely to respond-that can be leveraged in the development of PN interventions addressing obesity. We conducted a review of the literature and included laboratory, animal, and human studies evaluating biochemical and genetic data, completed and ongoing clinical trials, and public programs in this review. Our analysis describes the potential mechanisms related to 6 domains including genetic predisposition, circadian rhythms, physical activity and sedentary behavior, metabolomics, the gut microbiome, and behavioral and socioeconomic characteristics, i.e., the factors that can be leveraged to design PN-based interventions to prevent and treat obesity-related outcomes such as weight loss or metabolic health as laid out by the NIH 2030 Strategic Plan for Nutrition Research. For example, single nucleotide polymorphisms can modify responses to certain dietary interventions, and epigenetic modulation of obesity risk via physical activity patterns and macronutrient intake have also been demonstrated. Additionally, we identified limitations including questions of equitable implementation across a limited number of clinical trials. These include the limited ability of current PN interventions to address systemic influences such as supply chains and food distribution, healthcare systems, racial or cultural inequities, and economic disparities, particularly when designing and implementing PN interventions in low- and middle-income communities. PN has the potential to help manage obesity by addressing intra- and inter-individual variation as well as context, as opposed to "one-size fits all" approaches though there is limited clinical trial evidence to date.
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Affiliation(s)
- Neel H Mehta
- Division of Nutritional Sciences, Cornell University, Ithaca, NY, United States
| | - Samantha L Huey
- Division of Nutritional Sciences, Cornell University, Ithaca, NY, United States; Center for Precision Nutrition and Health, Cornell University, Ithaca, NY, United States
| | - Rebecca Kuriyan
- Division of Nutrition, St. John's Research Institute, Bengaluru, Karnataka, India
| | - Juan Pablo Peña-Rosas
- Global Initiatives, The Department of Nutrition and Food Safety, World Health Organization, Geneva, Switzerland
| | - Julia L Finkelstein
- Division of Nutritional Sciences, Cornell University, Ithaca, NY, United States; Center for Precision Nutrition and Health, Cornell University, Ithaca, NY, United States; Division of Nutrition, St. John's Research Institute, Bengaluru, Karnataka, India
| | - Sangeeta Kashyap
- Division of Endocrinology, Diabetes and Metabolism, Weill Cornell Medicine New York Presbyterian, New York, NY, United States
| | - Saurabh Mehta
- Division of Nutritional Sciences, Cornell University, Ithaca, NY, United States; Center for Precision Nutrition and Health, Cornell University, Ithaca, NY, United States; Division of Medical Informatics, St. John's Research Institute, Bengaluru, Karnataka, India.
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Ahmetov II, John G, Semenova EA, Hall ECR. Genomic predictors of physical activity and athletic performance. ADVANCES IN GENETICS 2024; 111:311-408. [PMID: 38908902 DOI: 10.1016/bs.adgen.2024.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/24/2024]
Abstract
Physical activity and athletic performance are complex phenotypes influenced by environmental and genetic factors. Recent advances in lifestyle and behavioral genomics led to the discovery of dozens of DNA polymorphisms (variants) associated with physical activity and allowed to use them as genetic instruments in Mendelian randomization studies for identifying the causal links between physical activity and health outcomes. On the other hand, exercise and sports genomics studies are focused on the search for genetic variants associated with athlete status, sports injuries and individual responses to training and supplement use. In this review, the findings of studies investigating genetic markers and their associations with physical activity and athlete status are reported. As of the end of September 2023, a total of 149 variants have been associated with various physical activity traits (of which 42 variants are genome-wide significant) and 253 variants have been linked to athlete status (115 endurance-related, 96 power-related, and 42 strength-related).
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Affiliation(s)
- Ildus I Ahmetov
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, United Kingdom; Sports Genetics Laboratory, St Petersburg Research Institute of Physical Culture, St. Petersburg, Russia; Laboratory of Genetics of Aging and Longevity, Kazan State Medical University, Kazan, Russia; Department of Physical Education, Plekhanov Russian University of Economics, Moscow, Russia.
| | - George John
- Transform Specialist Medical Centre, Dubai, United Arab Emirates
| | - Ekaterina A Semenova
- Department of Molecular Biology and Genetics, Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia; Research Institute of Physical Culture and Sport, Volga Region State University of Physical Culture, Sport and Tourism, Kazan, Russia
| | - Elliott C R Hall
- Faculty of Health Sciences and Sport, University of Stirling, Stirling, United Kingdom
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Huang C, Chen W, Wang X. Studies on the fat mass and obesity-associated (FTO) gene and its impact on obesity-associated diseases. Genes Dis 2023; 10:2351-2365. [PMID: 37554175 PMCID: PMC10404889 DOI: 10.1016/j.gendis.2022.04.014] [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: 12/19/2021] [Revised: 03/29/2022] [Accepted: 04/01/2022] [Indexed: 10/18/2022] Open
Abstract
Obesity has become a major health crisis in the past ∼50 years. The fat mass and obesity-associated (FTO) gene, identified by genome-wide association studies (GWAS), was first reported to be positively associated with obesity in humans. Mice with more copies of the FTO gene were observed to be obese, while loss of the gene in mice was found to protect from obesity. Later, FTO was found to encode an m6A RNA demethylase and has a profound effect on many biological and metabolic processes. In this review, we first summarize recent studies that demonstrate the critical roles and regulatory mechanisms of FTO in obesity and metabolic disease. Second, we discuss the ongoing debates concerning the association between FTO polymorphisms and obesity. Third, since several small molecule drugs and micronutrients have been found to regulate metabolic homeostasis through controlling the expression or activity of FTO, we highlight the broad potential of targeting FTO for obesity treatment. Improving our understanding of FTO and the underlying mechanisms may provide new approaches for treating obesity and metabolic diseases.
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Affiliation(s)
- Chaoqun Huang
- College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
- Key Laboratory of Molecular Animal Nutrition, Zhejiang University, Ministry of Education, Hangzhou, Zhejiang 310058, China
- Key Laboratory of Animal Nutrition and Feed Science (Eastern of China), Ministry of Agriculture and Rural Affairs, Hangzhou, Zhejiang 310058, China
- Key Laboratory of Animal Feed and Nutrition of Zhejiang Province, Hangzhou, Zhejiang 310058, China
| | - Wei Chen
- College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
- Key Laboratory of Molecular Animal Nutrition, Zhejiang University, Ministry of Education, Hangzhou, Zhejiang 310058, China
- Key Laboratory of Animal Nutrition and Feed Science (Eastern of China), Ministry of Agriculture and Rural Affairs, Hangzhou, Zhejiang 310058, China
- Key Laboratory of Animal Feed and Nutrition of Zhejiang Province, Hangzhou, Zhejiang 310058, China
| | - Xinxia Wang
- College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
- Key Laboratory of Molecular Animal Nutrition, Zhejiang University, Ministry of Education, Hangzhou, Zhejiang 310058, China
- Key Laboratory of Animal Nutrition and Feed Science (Eastern of China), Ministry of Agriculture and Rural Affairs, Hangzhou, Zhejiang 310058, China
- Key Laboratory of Animal Feed and Nutrition of Zhejiang Province, Hangzhou, Zhejiang 310058, China
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Carter AR, Harrison S, Gill D, Davey Smith G, Taylor AE, Howe LD, Davies NM. Educational attainment as a modifier for the effect of polygenic scores for cardiovascular risk factors: cross-sectional and prospective analysis of UK Biobank. Int J Epidemiol 2022; 51:885-897. [PMID: 35134953 PMCID: PMC9189971 DOI: 10.1093/ije/dyac002] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 01/06/2022] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Understanding the interplay between educational attainment and genetic predictors of cardiovascular risk may improve our understanding of the aetiology of educational inequalities in cardiovascular disease. METHODS In up to 320 120 UK Biobank participants of White British ancestry (mean age = 57 years, female 54%), we created polygenic scores for nine cardiovascular risk factors or diseases: alcohol consumption, body mass index, low-density lipoprotein cholesterol, lifetime smoking behaviour, systolic blood pressure, atrial fibrillation, coronary heart disease, type 2 diabetes and stroke. We estimated whether educational attainment modified genetic susceptibility to these risk factors and diseases. RESULTS On the additive scale, higher educational attainment reduced genetic susceptibility to higher body mass index, smoking, atrial fibrillation and type 2 diabetes, but increased genetic susceptibility to higher LDL-C and higher systolic blood pressure. On the multiplicative scale, there was evidence that higher educational attainment increased genetic susceptibility to atrial fibrillation and coronary heart disease, but little evidence of effect modification was found for all other traits considered. CONCLUSIONS Educational attainment modifies the genetic susceptibility to some cardiovascular risk factors and diseases. The direction of this effect was mixed across traits considered and differences in associations between the effect of the polygenic score across strata of educational attainment was uniformly small. Therefore, any effect modification by education of genetic susceptibility to cardiovascular risk factors or diseases is unlikely to substantially explain the development of inequalities in cardiovascular risk.
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Affiliation(s)
- Alice R Carter
- MRC Integrative Epidemiology Unit, University of Bristol Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Sean Harrison
- MRC Integrative Epidemiology Unit, University of Bristol Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Dipender Gill
- Clinical Pharmacology and Therapeutics Section, Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George’s, University of London, London, UK
- Clinical Pharmacology Group, Pharmacy and Medicines Directorate, St George’s University Hospitals NHS Foundation Trust, London, UK
- Novo Nordisk Research Centre Oxford, Old Road Campus, Oxford, UK
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University of Bristol, Bristol, UK
| | - Amy E Taylor
- MRC Integrative Epidemiology Unit, University of Bristol Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University of Bristol, Bristol, UK
| | - Laura D Howe
- MRC Integrative Epidemiology Unit, University of Bristol Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Neil M Davies
- MRC Integrative Epidemiology Unit, University of Bristol Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
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Arablou T, Khodaverdi S, Kolahdouz-Mohammadi R, Farhangnia P, Delbandi AA. Body mass index and endometriosis: Is there a relationship? JOURNAL OF ENDOMETRIOSIS AND PELVIC PAIN DISORDERS 2022. [DOI: 10.1177/22840265221092872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Objective: Previous studies on the relationship between the presence of endometriosis (EM) and body mass index (BMI) have shown inconsistent results. This study aimed to compare the BMI between women with EM and non-endometriotic controls. Methods: In the present cross-sectional study, BMI of 65 endometriotic women with 43 non-endometriotic controls undergoing laparoscopy were compared. The comparison of BMI between the two groups and in disease stages was analyzed using t-test. Results: BMI was significantly lower in women with EM compared to control women ( p = 0.01). There were no statistically significant differences in BMI between disease stages. Conclusion: The present study results showed that women with EM have lower BMI compared to non-endometriotic controls. More studies are suggested to clarify the mechanisms of this association.
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Affiliation(s)
- Tahereh Arablou
- Department of Nutrition, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
| | - Sepideh Khodaverdi
- Endometriosis Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Roya Kolahdouz-Mohammadi
- Department of Nutrition, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
| | - Pooya Farhangnia
- Immunology Research Center, Institute of Immunology and Infectious Disease, Iran University of Medical Sciences, Tehran, Iran
| | - Ali-Akbar Delbandi
- Immunology Research Center, Institute of Immunology and Infectious Disease, Iran University of Medical Sciences, Tehran, Iran
- Department of Immunology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
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7
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Naess M, Sund ER, Vie GÅ, Bjørngaard JH, Åsvold BO, Holmen TL, Kvaløy K. Intergenerational polygenic obesity risk throughout adolescence in a cross-sectional study design: The HUNT study, Norway. Obesity (Silver Spring) 2021; 29:1916-1924. [PMID: 34651441 DOI: 10.1002/oby.23284] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 07/08/2021] [Accepted: 08/06/2021] [Indexed: 12/15/2022]
Abstract
OBJECTIVE This study examined the relationship between parental obesity polygenic risk and children's BMI throughout adolescence. Additionally, from a smaller subsample, the objective was to assess whether parental polygenic risk score (PRS) may act as a proxy for offspring PRS in studies lacking offspring genetic data. METHODS A total of 8,561 parent-offspring (age 13-19 years) trios from the Trøndelag Health Study (the HUNT Study) were included, of which, 1,286 adolescents had available genetic data. Weighted parental PRSs from 900 single-nucleotide polymorphisms robustly associated with adult BMI were constructed and applied in linear mixed-effects models. RESULTS A positive association between parental PRS and offspring sex- and age-adjusted BMI (iso-BMI) throughout adolescence was identified. The estimated marginal effects per standard deviation increase in parental PRS were 0.26 (95% CI: 0.18-0.33), 0.36 (95% CI: 0.29-0.43), and 0.62 kg/m2 (95% CI: 0.51-0.72) for maternal, paternal, and combined parental PRS, respectively. In subsample analyses, the magnitude of association of the parental PRS versus offspring PRS with iso-BMI in adolescents was similar. CONCLUSIONS Parental PRS was consistently associated with offspring iso-BMI throughout adolescence. Results from subsample analyses support the use of parental PRS of obesity as a proxy for adolescent PRS in the absence of offspring genetic data.
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Affiliation(s)
- Marit Naess
- HUNT Research Centre, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Nord-Trøndelag Hospital Trust, Levanger Hospital, Levanger, Norway
| | - Erik R Sund
- HUNT Research Centre, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Nord-Trøndelag Hospital Trust, Levanger Hospital, Levanger, Norway
- Faculty of Nursing and Health Sciences, Nord University, Levanger, Norway
| | - Gunnhild Å Vie
- Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Johan H Bjørngaard
- Faculty of Nursing and Health Sciences, Nord University, Levanger, Norway
- Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Bjørn Olav Åsvold
- HUNT Research Centre, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Endocrinology, St. Olav's University Hospital, Trondheim University Hospital, Trondheim, Norway
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Turid Lingaas Holmen
- HUNT Research Centre, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Kirsti Kvaløy
- HUNT Research Centre, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Nord-Trøndelag Hospital Trust, Levanger Hospital, Levanger, Norway
- Centre for Sami Health Research, Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway
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Gasmi A, Mujawdiya PK, Noor S, Piscopo S, Menzel A. Lifestyle Genetics-Based Reports in the Treatment of Obesity. ARCHIVES OF RAZI INSTITUTE 2021; 76:707-719. [PMID: 35096307 PMCID: PMC8790989 DOI: 10.22092/ari.2021.356057.1768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Accepted: 10/12/2021] [Indexed: 10/07/2022]
Abstract
Obesity becomes a chronic disease due to the increasing number of mortality and morbidity cases around the world. In most regions, chronic illnesses, such as obesity, are important sources of morbidity and mortality. Due to a lack of effective strategies for prevention and management, the adverse effects of obesity and related diseases on health continue to be a serious problem. Relevant information was searched from Google Scholar, Scopus, and PubMed using such different terms as "Obesity", "Obesity Management", "Obesity AND Physical activity", "Obesity AND Genetics", "Obesity AND Diet", and "Obesity AND Nutrigenomics". Obesity is characterized by a complex interaction of hereditary and lifestyle factors, which includes food. Diet is an environmental element that plays an important and considerable role in the management of health and reduces the risk of obesity and its comorbidities. Changes in lifestyle patterns not only help burn extra calories but also prevent the development of obesity via its modulating effect on genetic factors. Different people respond differently to an obesogenic environment. The notion of nutrigenetics emerged as a result of various genetic variations that may explain this heterogeneity. Nutritional genomics, also known as nutrigenetics, is the study that investigates and analyses gene variations linked to varied responses to certain foods; moreover, it links this variation to diseases, such as obesity. As a result, tailored nutrition advice based on a person's genetic profile may improve the outcomes of a specific dietary strategy and offer a novel dietary strategy to improve life quality and preventing obesity. This study concluded that physical activity and dietary interventions play an effective role in the management of obesity. Moreover, understanding of the function of the most prominent obesity-related genes, as well as the interaction between nutrition and gene expression, will help researchers design personalized treatment strategies for humans.
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Affiliation(s)
- A Gasmi
- Société Francophone de Nutrithérapie et de Nutrigénétique Appliquée, Villeurbanne, France
| | - P K Mujawdiya
- Inochi Care Private Limited, New Delhi-110017, India
| | - S Noor
- Institute of Molecular Biology and Biotechnology, Bahauddin Zakariya University Multan, Pakistan
| | - S Piscopo
- Société Francophone de Nutrithérapie et de Nutrigénétique Appliquée, Villeurbanne, France
- Research and Development Department, Nutri-Logics SA, Weiswampach, Luxembourg
| | - A Menzel
- Laboratoires Réunis, Junglinster, Luxembourg
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Hiraike Y, Yang CT, Liu WJ, Yamada T, Lee CL. FTO Obesity Variant-Exercise Interaction on Changes in Body Weight and BMI: The Taiwan Biobank Study. J Clin Endocrinol Metab 2021; 106:e3673-e3681. [PMID: 33929497 DOI: 10.1210/clinem/dgab295] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Indexed: 02/05/2023]
Abstract
CONTEXT Gene-exercise interaction on cross-sectional body mass index (BMI) has been extensively studied and is well established. However, gene-exercise interaction on changes in body weight/BMI remains controversial. OBJECTIVE To examine the interaction between the FTO obesity variant and regular exercise on changes in body weight/BMI. PARTICIPANTS Taiwan Biobank participants aged 30-70 years (N = 20 906) were examined at both baseline and follow-up visit (mean follow-up duration: 3.7 years). MAIN OUTCOME MEASURES The interaction between the FTO obesity variant rs1421085 and regular exercise habit (no exercise, ≤20 metabolic equivalent of tasks (METs)/week exercise, >20 METs/week exercise) on changes in body weight/BMI. RESULTS Individuals with the risk allele of rs1421085 gained more weight and increased BMI than those without the risk allele if they did not exercise. In contrast, individuals with the risk allele gained less weight and BMI if they exercised regularly, indicating an interaction between rs1421085 and regular exercise habit (P = .030 for Δbody weight and P = .034 for ΔBMI). The effect of exercise on maintaining body weight was larger in those with the risk allele of rs1421085. When we focused on individuals without regular exercise at baseline, individuals with the risk allele again tended to lose more weight than those with a nonrisk allele if they had acquired an exercise habit by the follow-up visit. CONCLUSION The beneficial effect of exercise is greater in individuals genetically prone to obesity due to the interaction between the FTO obesity variant rs1421085 and regular exercise on changes in body weight and BMI.
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Affiliation(s)
- Yuta Hiraike
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
- Department of Cell Biology, Harvard Medical School , Boston, MA 02115, USA
| | - Chao-Tung Yang
- Department of Computer Science, Tunghai University, Taichung, Taiwan
- Research Center for Smart Sustainable Circular Economy, Tunghai University, Taiwan
- Research Center for Nanotechnology, Tunghai University, Taiwan
| | - Wei-Ju Liu
- Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Tomohide Yamada
- Institute of Population Health, King's College London, London, UK
| | - Chia-Lin Lee
- Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- Department of Medicine, School of Medicine, National Yang-Ming Chiao Tung University, Taipei, Taiwan
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10
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Chauhdary Z, Rehman K, Akash MSH. The composite alliance of FTO locus with obesity-related genetic variants. Clin Exp Pharmacol Physiol 2021; 48:954-965. [PMID: 33735452 DOI: 10.1111/1440-1681.13498] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 03/05/2021] [Accepted: 03/15/2021] [Indexed: 12/14/2022]
Abstract
Obesity has become a genuine global pandemic due to lifestyle and environmental modifications, and is associated with chronic lethal comorbidities. Various environmental factors such as lack of physical activity due to modernization and higher intake of energy-rich diets are primary obesogenic factors in pathogenesis of obesity. Genome-wide association study has identified the crucial role of FTO (fat mass and obesity) in human obesity. A bunch of SNPs in the first intron of FTO has been identified and subsequently correlated to body mass index and body composition. Findings of in silico, in vitro, and in vivo studies have manifested the robust role of FTO in regulation of energy expenditure and food consumption. Numerous studies have highlighted the mechanistic pathways behind the concomitant functions of FTO in adipogenesis and body size. Current investigation has also revealed the link of FTO neighbouring genes i.e., RPGRIP1L, IRX3 and IRX5 and epigenetic factors with obesity phenotypes. The motive behind this review is to cite the consequences of FTO on obesity vulnerability.
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Affiliation(s)
- Zunera Chauhdary
- Department of Pharmaceutical Chemistry, Government College University, Faisalabad, Pakistan
| | - Kanwal Rehman
- Department of Pharmacy, University of Agriculture, Faisalabad, Pakistan
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Rana S, Sultana A, Bhatti AA. Effect of interaction between obesity-promoting genetic variants and behavioral factors on the risk of obese phenotypes. Mol Genet Genomics 2021; 296:919-938. [PMID: 33966103 DOI: 10.1007/s00438-021-01793-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 04/22/2021] [Indexed: 01/28/2023]
Abstract
The studies investigating gene-gene and gene-environment (or gene-behavior) interactions provide valuable insight into the pathomechanisms underlying obese phenotypes. The Pakistani population due to its unique characteristics offers numerous advantages for conducting such studies. In this view, the current study was undertaken to examine the effects of gene-gene and gene-environment/behavior interactions on the risk of obesity in a sample of Pakistani population. A total of 578 adult participants including 290 overweight/obese cases and 288 normal-weight controls were involved. The five key obesity-associated genetic variants namely MC4R rs17782313, BDNF rs6265, FTO rs1421085, TMEM18 rs7561317, and NEGR1 rs2815752 were genotyped using the TaqMan allelic discrimination assays. The data related to behavioral factors, such as eating pattern, diet consciousness, the tendency toward fat-dense food (TFDF), sleep duration, sleep-wake cycle (SWC), shift work (SW), and physical activity levels were collected via a questionnaire. Gene-gene and gene-behavior interactions were analyzed by multifactor dimensionality reduction and linear regression, respectively. In our study, only TMEM18 rs7561317 was found to be significantly associated with anthropometric traits with no significant effect of gene-gene interactions were observed on obesity-related phenotypes. However, the genetic variants were found to interact with the behavioral factors to significantly influence various obesity-related anthropometric traits including BMI, waist circumference, hip circumference, waist-to-hip ratio, waist-to-height ratio, and percentage of body fat. In conclusion, the interaction between genetic architecture and behavior/environment determines the outcome of obesity-related anthropometric phenotypes. Thus, gene-environment/behavior interaction studies should be promoted to explore the risk of complex and multifactorial disorders, such as obesity.
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Affiliation(s)
- Sobia Rana
- Molecular Biology and Human Genetics Laboratory, Dr. Panjwani Center for Molecular Medicine and Drug Research (PCMD), International Center for Chemical and Biological Sciences (ICCBS), University of Karachi, Karachi, 75270, Pakistan.
| | - Ayesha Sultana
- Molecular Biology and Human Genetics Laboratory, Dr. Panjwani Center for Molecular Medicine and Drug Research (PCMD), International Center for Chemical and Biological Sciences (ICCBS), University of Karachi, Karachi, 75270, Pakistan
| | - Adil Anwar Bhatti
- Molecular Biology and Human Genetics Laboratory, Dr. Panjwani Center for Molecular Medicine and Drug Research (PCMD), International Center for Chemical and Biological Sciences (ICCBS), University of Karachi, Karachi, 75270, Pakistan
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12
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Apalasamy YD, Awang H, Mansor N, AbRashid N, Kamarulzaman ND, Lih Yoong T. Factors Associated With Obesity and Abdominal Obesity Among Malaysian Older Adults. Asia Pac J Public Health 2021; 33:547-554. [PMID: 34013778 DOI: 10.1177/10105395211014634] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Obesity is a rising concern globally. This study investigated the prevalence and factors associated with obesity and abdominal obesity (AO) among 5613 Malaysians aged 40 years and older via computer-assisted personal interviewing and anthropometric measurements. Obesity and AO prevalence were 37.8% and 63.1%, respectively. Significant associations were observed between: obesity with higher risk in patients aged between 40 and 49 years, Indians, females, income ≥RM 2000, and health status, and AO with higher risk in patients aged between 50 and 59 years, Indians, females, never married, income ≥RM 2000, and vigorous physical activity. Hence, age, sex, income, and ethnicity are associated with both obesity and AO. Promoting healthy body mass index and waist circumference is essential for healthy ageing.
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13
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Gordon-Larsen P, French JE, Moustaid-Moussa N, Voruganti VS, Mayer-Davis EJ, Bizon CA, Cheng Z, Stewart DA, Easterbrook JW, Shaikh SR. Synergizing Mouse and Human Studies to Understand the Heterogeneity of Obesity. Adv Nutr 2021; 12:2023-2034. [PMID: 33885739 PMCID: PMC8483969 DOI: 10.1093/advances/nmab040] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 02/17/2021] [Accepted: 03/13/2021] [Indexed: 12/12/2022] Open
Abstract
Obesity is routinely considered as a single disease state, which drives a "one-size-fits-all" approach to treatment. We recently convened the first annual University of North Carolina Interdisciplinary Nutrition Sciences Symposium to discuss the heterogeneity of obesity and the need for translational science to advance understanding of this heterogeneity. The symposium aimed to advance scientific rigor in translational studies from animal to human models with the goal of identifying underlying mechanisms and treatments. In this review, we discuss fundamental gaps in knowledge of the heterogeneity of obesity ranging from cellular to population perspectives. We also advocate approaches to overcoming limitations in the field. Examples include the use of contemporary mouse genetic reference population models such as the Collaborative Cross and Diversity Outbred mice that effectively model human genetic diversity and the use of translational models that integrate -omics and computational approaches from pre-clinical to clinical models of obesity. Finally, we suggest best scientific practices to ensure strong rigor that will allow investigators to delineate the sources of heterogeneity in the population with obesity. Collectively, we propose that it is critical to think of obesity as a heterogeneous disease with complex mechanisms and etiologies, requiring unique prevention and treatment strategies tailored to the individual.
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Affiliation(s)
| | - John E French
- Department of Nutrition, Gillings School of Global Public Health and School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA,Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - Naima Moustaid-Moussa
- Obesity Research Institute and Department of Nutritional Sciences, Texas Tech University, Lubbock, TX, USA
| | - Venkata S Voruganti
- Department of Nutrition, Gillings School of Global Public Health and School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA,Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - Elizabeth J Mayer-Davis
- Department of Nutrition, Gillings School of Global Public Health and School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Christopher A Bizon
- Renaissance Computing Institute, University of North Carolina at Chapel Hill, NC, USA
| | - Zhiyong Cheng
- Food Science and Human Nutrition Department, University of Florida, Gainesville, FL, USA
| | - Delisha A Stewart
- Department of Nutrition, Gillings School of Global Public Health and School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA,Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - John W Easterbrook
- Department of Nutrition, Gillings School of Global Public Health and School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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14
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Schnurr TM, Stallknecht BM, Sørensen TIA, Kilpeläinen TO, Hansen T. Evidence for shared genetics between physical activity, sedentary behaviour and adiposity-related traits. Obes Rev 2021; 22:e13182. [PMID: 33354910 DOI: 10.1111/obr.13182] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 11/23/2020] [Accepted: 11/25/2020] [Indexed: 12/20/2022]
Abstract
Observational, cross-sectional and longitudinal studies showed that physical activity and sedentary behaviour are associated with adiposity-related traits, apparently in a bidirectional manner. Physical activity is also suggested to suppress the genetic risk of adiposity. Since phenotypic associations with genetic variants are not subject to reverse causation or confounding, they may be used as tools to shed light on cause and effect in this complex interdependency. We review the evidence for shared genetics of physical activity and adiposity-related traits and for gene-by-physical activity interactions on adiposity-related traits in human studies. We outline limitations, challenges and opportunities in studying and understanding of these relationships. In summary, physical activity and sedentary behaviour are genetically correlated with body mass index and fat percentage but may not be correlated with lean body mass. Mendelian randomisation analyses show that physical activity and sedentary behaviour have bidirectional relationships with adiposity. Several studies suggest that physical activity suppresses genetic risk of adiposity. No studies have yet tested whether adiposity enhances genetic predisposition to sedentariness. The complexity of the comprehensive causal model makes the assessment of the single or combined components challenging. Substantial progress in this field may need long-term intervention studies.
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Affiliation(s)
- Theresia M Schnurr
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Bente M Stallknecht
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Thorkild I A Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.,Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tuomas O Kilpeläinen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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15
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Wolf RM, Nagpal M, Magge SN. Diabetes and cardiometabolic risk in South Asian youth: A review. Pediatr Diabetes 2021; 22:52-66. [PMID: 32666595 PMCID: PMC8191592 DOI: 10.1111/pedi.13078] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 05/22/2020] [Accepted: 06/02/2020] [Indexed: 12/15/2022] Open
Abstract
South Asians are at increased risk for developing type 2 diabetes and cardiovascular disease at lower body mass index compared to other ancestral groups. Many factors contribute to this increased risk, including genetics, maternal-fetal factors, diet, fitness, body composition, and unique pathophysiology. Increased cardiometabolic risk is also seen at younger ages in South Asian individuals as compared to their White counterparts. This risk persists in migrant communities outside of South Asia. With the growing prevalence of obesity, diabetes, and cardiovascular disease in the South Asian population, it is imperative that we had better understand the mechanisms underlying this increased risk and implement strategies to address this growing public health problem during childhood and adolescence.
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Affiliation(s)
- Risa M Wolf
- Department of Pediatrics, Division of Endocrinology and Diabetes, Johns Hopkins University School of Medicine
| | - Mohika Nagpal
- Department of Pediatrics, Division of Endocrinology and Diabetes, Johns Hopkins University School of Medicine
| | - Sheela N. Magge
- Department of Pediatrics, Division of Endocrinology and Diabetes, Johns Hopkins University School of Medicine
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16
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Body fatness in sedentary and active students with different body mass index. BIOMEDICAL HUMAN KINETICS 2021. [DOI: 10.2478/bhk-2021-0005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Abstract
Study aim: Numerous data have indicated that body fat stores undergo complicated regulation by genetic and environmental factors, including physical activity. However, the majority of studies did not take into account this aspect of lifestyle in proposed body fat limits. In this context it seems that a more precise and reliable classification of body fat is provided by the American Council on Exercise (ACE), which distinguishes individuals not only with respect to sex but also activity level.
Material and methods: A total of 793 students (312 sedentary and 481 active) volunteered to participate in the study. Among sedentary participants 147 were male and 165 female. Among active subjects 206 were male and 275 were female. Active subjects were engaged in different modes of physical activity according to the study program. In all participants body mass index (BMI) was calculated. In participants with BMI 18.5–24.9 and BMI ≥ 25 body fat was determined using four skinfold measurements. Thereafter participants were classified according to the percentage of body fat using ranges for males and females provided by the American Council on Exercise (ACE) (essential fat, athletes, fitness, average and obese fatness).
Results: None of the sedentary and active males with BMI 18.5–24.9 had high (obese) fat. In contrast, in sedentary males with BMI ≥ 25 16.4% were obese vs. 1.8% of obese active ones. In sedentary females BMI from 18.5 to 24.9 did not exclude obesity, which was found in 16.9% of participants. In sedentary females with BMI ≥ 25 most of the subjects (97.1%) were obese. In contrast, in active females with BMI ≥ 25 a similar percentage of participants had average and obese fat (53.3% and 46.7, respectively).
Discussion: Our study clearly demonstrated that BMI as a simple measure of body composition provides false information concerning true adiposity in physically active male and female students. A similar BMI did not exclude marked differences in the percentage of body fat in sedentary and active students.
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17
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Incretin Hormones in Obesity and Related Cardiometabolic Disorders: The Clinical Perspective. Nutrients 2021; 13:nu13020351. [PMID: 33503878 PMCID: PMC7910956 DOI: 10.3390/nu13020351] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 01/21/2021] [Accepted: 01/22/2021] [Indexed: 02/06/2023] Open
Abstract
The prevalence of obesity continues to grow rapidly worldwide, posing many public health challenges of the 21st century. Obese subjects are at major risk for serious diet-related noncommunicable diseases, including type 2 diabetes mellitus, cardiovascular disease, and non-alcoholic fatty liver disease. Understanding the mechanisms underlying obesity pathogenesis is needed for the development of effective treatment strategies. Dysregulation of incretin secretion and actions has been observed in obesity and related metabolic disorders; therefore, incretin-based therapies have been developed to provide new therapeutic options. Incretin mimetics present glucose-lowering properties, together with a reduction of appetite and food intake, resulting in weight loss. In this review, we describe the physiology of two known incretins—glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1), and their role in obesity and related cardiometabolic disorders. We also focus on the available and incoming incretin-based medications that can be used in the treatment of the above-mentioned conditions.
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18
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Aasdahl L, Nilsen TIL, Meisingset I, Nordstoga AL, Evensen KAI, Paulsen J, Mork PJ, Skarpsno ES. Genetic variants related to physical activity or sedentary behaviour: a systematic review. Int J Behav Nutr Phys Act 2021; 18:15. [PMID: 33482856 PMCID: PMC7821484 DOI: 10.1186/s12966-020-01077-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 12/16/2020] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Research shows that part of the variation in physical activity and sedentary behaviour may be explained by genetic factors. Identifying genetic variants associated with physical activity and sedentary behaviour can improve causal inference in physical activity research. The aim of this systematic review was to provide an updated overview of the evidence of genetic variants associated with physical activity or sedentary behaviour. METHODS We performed systematic literature searches in PubMed and Embase for studies published from 1990 to April 2020 using keywords relating to "physical activity", "exercise", "sedentariness" and "genetics". Physical activity phenotypes were either based on self-report (e.g., questionnaires, diaries) or objective measures (e.g., accelerometry, pedometer). We considered original studies aiming to i) identify new genetic variants associated with physical activity or sedentary behaviour (i.e., genome wide association studies [GWAS]), or ii) assess the association between known genetic variants and physical activity or sedentary behaviour (i.e., candidate gene studies). Study selection, data extraction, and critical appraisal were carried out by independent researchers, and risk of bias and methodological quality was assessed for all included studies. RESULTS Fifty-four out of 5420 identified records met the inclusion criteria. Six of the included studies were GWAS, whereas 48 used a candidate gene approach. Only one GWAS and three candidate gene studies were considered high-quality. The six GWAS discovered up to 10 single nucleotide polymorphisms (SNPs) associated with physical activity or sedentariness that reached genome-wide significance. In total, the candidate gene studies reported 30 different genes that were associated (p < 0.05) with physical activity or sedentary behaviour. SNPs in or close to nine candidate genes were associated with physical activity or sedentary behaviour in more than one study. CONCLUSION GWAS have reported up to 10 loci associated with physical activity or sedentary behaviour. Candidate gene studies have pointed to some interesting genetic variants, but few have been replicated. Our review highlights the need for high-quality GWAS in large population-based samples, and with objectively assessed phenotypes, in order to establish robust genetic instruments for physical activity and sedentary behaviour. Furthermore, consistent replications in GWAS are needed to improve credibility of genetic variants. TRIAL REGISTRATION Prospero CRD42019119456 .
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Affiliation(s)
- Lene Aasdahl
- Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Postboks 8905, MTFS, 7491, Trondheim, Norway. .,Unicare Helsefort Rehabilitation Centre, Rissa, Norway.
| | - Tom Ivar Lund Nilsen
- Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Postboks 8905, MTFS, 7491, Trondheim, Norway.,Clinic of Anaesthesia and Intensive Care, St. Olavs Hospital, Trondheim, Norway
| | - Ingebrigt Meisingset
- Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Postboks 8905, MTFS, 7491, Trondheim, Norway
| | - Anne Lovise Nordstoga
- Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Postboks 8905, MTFS, 7491, Trondheim, Norway
| | - Kari Anne I Evensen
- Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Postboks 8905, MTFS, 7491, Trondheim, Norway.,Department of Clinical and Molecular Medicine, NTNU, Trondheim, Norway.,Department of Physiotherapy, Oslo Metropolitan University, Oslo, Norway.,Unit for Physiotherapy Services, Trondheim, Norway
| | - Julie Paulsen
- Department of Medical Genetics, St. Olavs Hospital, Trondheim, Norway
| | - Paul Jarle Mork
- Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Postboks 8905, MTFS, 7491, Trondheim, Norway
| | - Eivind Schjelderup Skarpsno
- Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Postboks 8905, MTFS, 7491, Trondheim, Norway.,Department of Neurology and Clinical Neurophysiology, St. Olavs Hospital, Trondheim, Norway
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19
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Abstract
With change in global concern toward food quality over food quantity, consumer concern and choice of healthy food has become a matter of prime importance. It gave rise to concept of “personalized or precision nutrition”. The theory behind personalization of nutrition is supported by multiple factors including advances in food analytics, nutrition based diseases and public health programs, increasing use of information technology in nutrition science, concept of gene-diet interaction and growing consumer capacity or concern by better and healthy foods. The advances in “omics” tools and related analytical techniques have resulted into tremendous scope of their application in nutrition science. As a consequence, a better understanding of underlying interaction between diet and individual is expected with addressing of key challenges for successful implementation of this science. In this chapter, the above aspects are discussed to get an insight into driving factors for increasing concern in personalized nutrition.
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20
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Kucher AN. The FTO Gene and Diseases: The Role of Genetic Polymorphism, Epigenetic Modifications, and Environmental Factors. RUSS J GENET+ 2020. [DOI: 10.1134/s1022795420090136] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
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21
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Stephan Y, Sutin AR, Luchetti M, Caille P, Terracciano A. An examination of potential mediators of the relationship between polygenic scores of BMI and waist circumference and phenotypic adiposity. Psychol Health 2020; 35:1151-1161. [PMID: 32275177 DOI: 10.1080/08870446.2020.1743839] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Objective: The present study examined whether physical activity, personality, cognition, education, and depressive symptoms mediate the association between polygenic scores (PGS) for body mass index (BMI) and waist circumference and the corresponding phenotypic adiposity measures.Design: Participants were 9,139 individuals aged 50 to 107 years (57% women; Mean Age: 68.17, SD: 10.06) from the Health and Retirement Study who were genotyped. Trained staff measured their height, weight, and waist circumference, and participants answered questions on physical activity, personality, education, cognitive function, and depressive symptoms.Main Outcome Measures: BMI and waist circumference.Results: A higher PGS for both BMI and waist circumference were related to higher phenotypic BMI and waist circumference, respectively, in part through their association with lower physical activity, conscientiousness, education, and higher depressive symptoms but not cognition. The mediators accounted for 6.6% of the association between PGS and BMI and 9.6% of the association between PGS and waist circumference.Conclusion: The present study provides new evidence on the multiple, distinct pathways through which genetic propensity to higher BMI and waist circumference may lead to higher adiposity in adulthood. Individuals with a higher genetic predisposition to obesity may gain more weight through less adaptive behavioral, personality and educational profiles.
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Affiliation(s)
| | - Angelina R Sutin
- College of Medicine, Florida State University, Tallahassee, FL, USA
| | - Martina Luchetti
- College of Medicine, Florida State University, Tallahassee, FL, USA
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22
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Salem ESB, Vonberg AD, Borra VJ, Gill RK, Nakamura T. RNAs and RNA-Binding Proteins in Immuno-Metabolic Homeostasis and Diseases. Front Cardiovasc Med 2019; 6:106. [PMID: 31482095 PMCID: PMC6710452 DOI: 10.3389/fcvm.2019.00106] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Accepted: 07/17/2019] [Indexed: 12/16/2022] Open
Abstract
The increasing prevalence of worldwide obesity has emerged as a major risk factor for type 2 diabetes (T2D), hepatosteatosis, and cardiovascular disease. Accumulating evidence indicates that obesity has strong inflammatory underpinnings tightly linked to the development of metabolic diseases. However, the molecular mechanisms by which obesity induces aberrant inflammation associated with metabolic diseases are not yet clearly defined. Recently, RNAs have emerged as important regulators of stress responses and metabolism. RNAs are subject to changes in modification status, higher-order structure, and cellular localization; all of which could affect the affinity for RNA-binding proteins (RBPs) and thereby modify the RNA-RBP networks. Proper regulation and management of RNA characteristics are fundamental to cellular and organismal homeostasis, as well as paramount to health. Identification of multiple single nucleotide polymorphisms (SNPs) within loci of fat mass- and obesity-associated protein (FTO) gene, an RNA demethylase, through genome-wide association studies (GWAS) of T2D, and functional assessments of FTO in mice, support the concept that disruption in RNA modifications leads to the development of human diseases including obesity and metabolic disorder. In obesity, dynamic alterations in modification and localization of RNAs appear to modulate the RNA-RBP networks and activate proinflammatory RBPs, such as double-stranded RNA (dsRNA)-dependent protein kinase (PKR), Toll-like receptor (TLR) 3 and TLR7, and RNA silencing machinery. These changes induce aberrant inflammation and the development of metabolic diseases. This review will describe the current understanding of the underlying causes of these common and altered characteristics of RNA-RBP networks which will pave the way for developing novel approaches to tackle the pandemic issue of obesity.
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Affiliation(s)
- Esam S B Salem
- Division of Endocrinology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.,Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Andrew D Vonberg
- Division of Endocrinology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - Vishnupriya J Borra
- Division of Endocrinology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - Rupinder K Gill
- Division of Endocrinology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - Takahisa Nakamura
- Division of Endocrinology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.,Division of Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.,Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States.,Department of Metabolic Bioregulation, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
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23
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Lin WY, Chan CC, Liu YL, Yang AC, Tsai SJ, Kuo PH. Performing different kinds of physical exercise differentially attenuates the genetic effects on obesity measures: Evidence from 18,424 Taiwan Biobank participants. PLoS Genet 2019; 15:e1008277. [PMID: 31369549 PMCID: PMC6675047 DOI: 10.1371/journal.pgen.1008277] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Accepted: 06/26/2019] [Indexed: 12/17/2022] Open
Abstract
Obesity is a worldwide health problem that is closely linked to many metabolic disorders. Regular physical exercise has been found to attenuate the genetic predisposition to obesity. However, it remains unknown what kinds of exercise can modify the genetic risk of obesity. This study included 18,424 unrelated Han Chinese adults aged 30–70 years who participated in the Taiwan Biobank (TWB). A total of 5 obesity measures were investigated here, including body mass index (BMI), body fat percentage (BFP), waist circumference (WC), hip circumference (HC), and waist-to-hip ratio (WHR). Because there have been no large genome-wide association studies on obesity for Han Chinese, we used the TWB internal weights to construct genetic risk scores (GRSs) for each obesity measure, and then test the significance of GRS-by-exercise interactions. The significance level throughout this work was set at 0.05/550 = 9.1x10-5 because a total of 550 tests were performed. Performing regular exercise was found to attenuate the genetic effects on 4 obesity measures, including BMI, BFP, WC, and HC. Among the 18 kinds of self-reported regular exercise, 6 mitigated the genetic effects on at least one obesity measure. Regular jogging blunted the genetic effects on BMI, BFP, and HC. Mountain climbing, walking, exercise walking, international standard dancing, and a longer practice of yoga also attenuated the genetic effects on BMI. Exercises such as cycling, stretching exercise, swimming, dance dance revolution, and qigong were not found to modify the genetic effects on any obesity measure. Across all 5 obesity measures, regular jogging consistently presented the most significant interactions with GRSs. Our findings show that the genetic effects on obesity measures can be decreased to various extents by performing different kinds of exercise. The benefits of regular physical exercise are more impactful in subjects who are more predisposed to obesity. The complex interplay of genetics and lifestyle makes obesity a challenging issue. Previous studies have found performing regular physical exercise could blunt the genetic effects on body mass index (BMI). However, BMI does not take into account lean body mass or identify central obesity. Moreover, it remains unclear what kinds of exercise could more effectively attenuate the genetic effects on obesity measures. With a sample of 18,424 unrelated Han Chinese adults, we comprehensively investigated gene-exercise interactions on 5 obesity measures: BMI, body fat percentage, waist circumference, hip circumference, and waist-to-hip ratio. Moreover, we tested whether the genetic effects on obesity measures could be modified by any of 18 kinds of self-reported regular exercise. Because no large genome-wide association studies on obesity have been done for Han Chinese, we constructed genetic risk scores with internal weights for analyses. Among these exercises, regular jogging consistently presented the strongest evidence to mitigate the genetic effects on all 5 obesity measures. Moreover, mountain climbing, walking, exercise walking, international standard dancing, and a longer practice of yoga attenuated the genetic effects on BMI. The benefits of regularly performing these 6 kinds of exercise are more impactful in subjects who are more predisposed to obesity.
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Affiliation(s)
- Wan-Yu Lin
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
- Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan
- * E-mail: (WYL); (PHK)
| | - Chang-Chuan Chan
- Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan
- Institute of Occupational Medicine and Industrial Hygiene, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Yu-Li Liu
- Center for Neuropsychiatric Research, National Health Research Institutes, Zhunan, Miaoli County, Taiwan
| | - Albert C. Yang
- Division of Psychiatry, National Yang-Ming University, Taipei, Taiwan
- Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, Massachusetts, United States of America
- Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan
| | - Shih-Jen Tsai
- Division of Psychiatry, National Yang-Ming University, Taipei, Taiwan
- Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan
- Department of Psychiatry, Taipei Veterans General Hospital, Beitou District, Taipei, Taiwan
| | - Po-Hsiu Kuo
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
- Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan
- * E-mail: (WYL); (PHK)
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Celis-Morales CA, Lyall DM, Petermann F, Anderson J, Ward J, Iliodromiti S, Mackay DF, Welsh P, Bailey MES, Pell J, Sattar N, Gill JMR, Gray SR. Do physical activity, commuting mode, cardiorespiratory fitness and sedentary behaviours modify the genetic predisposition to higher BMI? Findings from a UK Biobank study. Int J Obes (Lond) 2019; 43:1526-1538. [PMID: 31168053 DOI: 10.1038/s41366-019-0381-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Revised: 03/01/2019] [Accepted: 03/10/2019] [Indexed: 12/15/2022]
Abstract
OBJECTIVE To investigate whether the association between a genetic profile risk score for obesity (GPRS-obesity) (based on 93 SNPs) and body mass index (BMI) was modified by physical activity (PA), cardiorespiratory fitness, commuting mode, walking pace and sedentary behaviours. METHODS For the analyses we used cross-sectional baseline data from 310,652 participants in the UK Biobank study. We investigated interaction effects of GPRS-obesity with objectively measured and self-reported PA, cardiorespiratory fitness, commuting mode, walking pace, TV viewing, playing computer games, PC-screen time and total sedentary behaviour on BMI. Body mass index (BMI) was the main outcome measure. RESULTS GPRS-obesity was associated with BMI (β:0.54 kg.m-2 per standard deviation (SD) increase in GPRS, [95% CI: 0.53; 0.56]; P = 2.1 × 10-241). There was a significant interaction between GPRS-obesity and objectively measured PA (P[interaction] = 3.3 × 10-11): among inactive individuals, BMI was higher by 0.58 kg.m-2 per SD increase in GPRS-obesity (p = 1.3 × 10-70) whereas among active individuals the relevant BMI difference was less (β:0.33 kg.m-2, p = 6.4 × 10-41). We observed similar patterns for fitness (Unfit β:0.72 versus Fit β:0.36 kg.m-2, P[interaction] = 1.4 × 10-11), walking pace (Slow β:0.91 versus Brisk β:0.38 kg.m-2, P[interaction] = 8.1 × 10-27), discretionary sedentary behaviour (High β:0.64 versus Low β:0.48 kg.m-2, P[interaction] = 9.1 × 10-12), TV viewing (High β:0.62 versus Low β:0.47 kg.m-2, P[interaction] = 1.7 × 10-11), PC-screen time (High β:0.82 versus Low β:0.54 kg.m-2, P[interaction] = 0.0004) and playing computer games (Often β:0.69 versus Low β:0.52 kg.m-2, P[interaction] = 8.9 × 10-10). No significant interactions were found for commuting mode (car, public transport, active commuters). CONCLUSIONS Physical activity, sedentary behaviours and fitness modify the extent to which a set of the most important known adiposity variants affect BMI. This suggests that the adiposity benefits of high PA and low sedentary behaviour may be particularly important in individuals with high genetic risk for obesity.
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Affiliation(s)
- Carlos A Celis-Morales
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, G12 8TA, UK.,Centro de Investigación en Fisiología del Ejercicio (CIFE), Universidad Mayor, Santiago, Chile
| | - Donald M Lyall
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, G12 8RZ, UK
| | - Fanny Petermann
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, G12 8TA, UK.,Institute of Health and Wellbeing, University of Glasgow, Glasgow, G12 8RZ, UK
| | - Jana Anderson
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, G12 8RZ, UK
| | - Joey Ward
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, G12 8RZ, UK
| | - Stamatina Iliodromiti
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, G12 8TA, UK
| | - Daniel F Mackay
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, G12 8RZ, UK
| | - Paul Welsh
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, G12 8TA, UK
| | - Mark E S Bailey
- School of Life Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Jill Pell
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, G12 8RZ, UK
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, G12 8TA, UK
| | - Jason M R Gill
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, G12 8TA, UK
| | - Stuart R Gray
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, G12 8TA, UK.
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Celis-Morales CA, Lyall DM, Bailey MES, Petermann-Rocha F, Anderson J, Ward J, Mackay DF, Welsh P, Pell JP, Sattar N, Gill JMR, Gray SR. The Combination of Physical Activity and Sedentary Behaviors Modifies the Genetic Predisposition to Obesity. Obesity (Silver Spring) 2019; 27:653-661. [PMID: 30900409 DOI: 10.1002/oby.22417] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2018] [Accepted: 11/08/2018] [Indexed: 01/19/2023]
Abstract
OBJECTIVE This study aimed to investigate whether the association between a validated genetic profile risk score for BMI (GPRS-BMI) (based on 93 single-nucleotide polymorphisms) and phenotypic obesity (BMI) was modified by the combined categories of physical activity (PA) and sedentary behaviors in a large population-based study. METHODS This study included cross-sectional baseline data from 338,216 white European adult men and women aged 37 to 73 years. Interaction effects of GPRS-BMI with the combined categories of PA and sedentary behaviors on BMI were investigated. RESULTS There was a significant interaction between GPRS-BMI and the combined categories of objectively measured PA and total sedentary behavior (P[interaction] = 3.5 × 10-6 ); among physically inactive and highly sedentary individuals, BMI was higher by 0.60 kg/m2 per 1-SD increase in GPRS-obesity (P = 8.9 × 10-50 ), whereas the relevant BMI difference was 38% lower among physically active individuals and those with low sedentary time (β: 0.37 kg/m2 ; P = 2.3 × 10-51 ). A similar pattern was observed for the combined categories of objective PA and TV viewing (inactive/high TV viewing β: 0.60 vs. active/low TV viewing β: 0.40 kg/m2 ; P[interaction] = 2.9 × 10-6 ). CONCLUSIONS This study provides evidence that combined categories of PA and sedentary behaviors modify the extent to which genetic predisposition to obesity results in higher BMI.
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Affiliation(s)
- Carlos A Celis-Morales
- British Heart Foundation Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
- Centre for Research in Exercise Physiology (CIFE), Universidad Mayor, Santiago, Chile
| | - Donald M Lyall
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Mark E S Bailey
- School of Life Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Fanny Petermann-Rocha
- British Heart Foundation Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Jana Anderson
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Joey Ward
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Daniel F Mackay
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Paul Welsh
- British Heart Foundation Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Jill P Pell
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Naveed Sattar
- British Heart Foundation Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Jason M R Gill
- British Heart Foundation Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Stuart R Gray
- British Heart Foundation Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
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26
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Janssen X, Basterfield L, Parkinson KN, Pearce MS, Reilly JK, Adamson AJ, Reilly JJ. Non-linear longitudinal associations between moderate-to-vigorous physical activity and adiposity across the adiposity distribution during childhood and adolescence: Gateshead Millennium Study. Int J Obes (Lond) 2019; 43:744-750. [PMID: 30108270 PMCID: PMC6484716 DOI: 10.1038/s41366-018-0188-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2018] [Revised: 06/10/2018] [Accepted: 07/02/2018] [Indexed: 01/02/2023]
Abstract
OBJECTIVE Insufficient moderate-to-vigorous intensity physical activity (MVPA) is harmful for youth; however, the evidence for differential effects by weight status is limited. The study aimed to examine associations between MVPA and adiposity by weight status across childhood and adolescence. METHODS Participants were from the Gateshead Millennium Study. Physical activity and body composition measures were taken at age 7 y (n = 502; measures taken between October 2006 and December 2007), 9 y (n = 506; October 2008-September 2009), 12 y (n = 420; October 2011-September 2012), and 15 y (n = 306; September 2014-September 2015). Participants wore an ActiGraph GT1M and epochs were classified as MVPA when accelerometer counts were ≥574 counts/15 s. Weight and height were measured using standardized methods and fat mass using bioelectrical impedance. Associations between MVPA and changes in BMI and FMI were examined by weight status using quantile regression. RESULTS Higher MVPA was associated with lower FMI for the 25th, 50th, 75th, and 90th percentile and lower BMI at the 50th, 75th, and 90th percentile, independent of accelerometer wear time, sex, and sedentary time. The association between MVPA and change in adiposity was stronger in the higher than lower FMI and BMI percentiles (e.g., 1 h/day more MVPA was associated with a 1.5 kg/m2 and 2.7 kg/m2 lower FMI at the 50th and 90th FMI percentiles, respectively). CONCLUSIONS The effect of MVPA on adiposity in the higher adiposity percentiles is stronger than reported to date. Given overweight and obese children are the highest risk group for later obesity, targeting MVPA might be a particularly effective obesity prevention strategy.
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Affiliation(s)
- Xanne Janssen
- University of Strathclyde, School of Psychological Science and Health, Glasgow, Scotland.
| | - Laura Basterfield
- Newcastle University, Institute of Health & Society, Newcastle upon Tyne, UK
- Newcastle University, Human Nutrition Research Centre, Newcastle upon Tyne, UK
| | - Kathryn N Parkinson
- Newcastle University, Institute of Health & Society, Newcastle upon Tyne, UK
- Newcastle University, Human Nutrition Research Centre, Newcastle upon Tyne, UK
| | - Mark S Pearce
- Newcastle University, Institute of Health & Society, Newcastle upon Tyne, UK
| | - Jessica K Reilly
- Newcastle University, Institute of Health & Society, Newcastle upon Tyne, UK
- Newcastle University, Human Nutrition Research Centre, Newcastle upon Tyne, UK
| | - Ashley J Adamson
- Newcastle University, Institute of Health & Society, Newcastle upon Tyne, UK
- Newcastle University, Human Nutrition Research Centre, Newcastle upon Tyne, UK
| | - John J Reilly
- University of Strathclyde, School of Psychological Science and Health, Glasgow, Scotland
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27
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Barroso I, McCarthy MI. The Genetic Basis of Metabolic Disease. Cell 2019; 177:146-161. [PMID: 30901536 PMCID: PMC6432945 DOI: 10.1016/j.cell.2019.02.024] [Citation(s) in RCA: 70] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Revised: 02/11/2019] [Accepted: 02/14/2019] [Indexed: 02/06/2023]
Abstract
Recent developments in genetics and genomics are providing a detailed and systematic characterization of the genetic underpinnings of common metabolic diseases and traits, highlighting the inherent complexity within systems for homeostatic control and the many ways in which that control can fail. The genetic architecture underlying these common metabolic phenotypes is complex, with each trait influenced by hundreds of loci spanning a range of allele frequencies and effect sizes. Here, we review the growing appreciation of this complexity and how this has fostered the implementation of genome-scale approaches that deliver robust mechanistic inference and unveil new strategies for translational exploitation.
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Affiliation(s)
- Inês Barroso
- Wellcome Sanger Institute, Hinxton, Cambridge CB10 1SA, UK.
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK; Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Churchill Hospital, Old Road, Headington, Oxford OX3 7LJ, UK; Oxford NIHR Biomedical Research Centre, Churchill Hospital, Old Road, Headington, Oxford OX3 7LJ, UK
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28
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Rana S, Mirza S, Rahmani S. The BDNF rs6265 variant may interact with overweight and obesity to influence obesity-related physical, metabolic and behavioural traits in Pakistani individuals. Ann Hum Biol 2019; 45:496-505. [DOI: 10.1080/03014460.2018.1561947] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Sobia Rana
- Dr. Panjwani Center for Molecular Medicine and Drug Research (PCMD), International Center for Chemical and Biological Sciences (ICCBS), University of Karachi, Karachi, Pakistan
| | - Saad Mirza
- Dr. Panjwani Center for Molecular Medicine and Drug Research (PCMD), International Center for Chemical and Biological Sciences (ICCBS), University of Karachi, Karachi, Pakistan
| | - Soma Rahmani
- Dr. Panjwani Center for Molecular Medicine and Drug Research (PCMD), International Center for Chemical and Biological Sciences (ICCBS), University of Karachi, Karachi, Pakistan
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29
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Ahmad S, Fatima SS, Rukh G, Smith CE. Gene Lifestyle Interactions With Relation to Obesity, Cardiometabolic, and Cardiovascular Traits Among South Asians. Front Endocrinol (Lausanne) 2019; 10:221. [PMID: 31024458 PMCID: PMC6465946 DOI: 10.3389/fendo.2019.00221] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2018] [Accepted: 03/20/2019] [Indexed: 01/05/2023] Open
Abstract
The rapid rise of obesity, type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD) during the last few decades among South Asians has been largely attributed to a major shift in lifestyles including physical inactivity, unhealthy dietary patterns, and an overall pattern of sedentary lifestyle. Genetic predisposition to these cardiometabolic risk factors may have interacted with these obesogenic environments in determining the higher cardiometabolic disease prevalence. Based on the premise that gene-environment interactions cause obesity and cardiometabolic diseases, we systematically searched the literature and considered the knowledge gaps that future studies might fulfill. We identified only seven published studies that focused specifically on gene-environment interactions for cardiometabolic traits in South Asians, most of which were limited by relatively small sample and lack of replication. Some studies reported that the differences in metabolic response to higher physical activity and low caloric diet might be modified by genetic risk related to these cardiometabolic traits. Although studies on gene lifestyle interactions in cardiometabolic traits report significant interactions, future studies must focus on more precise assessment of lifestyle factors, investigation of a larger set of genetic variants and the application of powerful statistical methods to facilitate translatable approaches. Future studies should also be integrated with findings both using mechanistic studies through laboratory settings and randomized clinical trials for clinical outcomes.
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Affiliation(s)
- Shafqat Ahmad
- Department of Medical Sciences, Molecular Epidemiology, Uppsala University, Uppsala, Sweden
- Preventive Medicine Division, Harvard Medical School, Brigham and Women's Hospital, Boston, MA, United States
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, United States
- *Correspondence: Shafqat Ahmad
| | - Syeda Sadia Fatima
- Department of Biological and Biomedical Sciences, Aga Khan University, Karachi, Pakistan
| | - Gull Rukh
- Department of Neuroscience, Functional Pharmacology, Uppsala University, Uppsala, Sweden
| | - Caren E. Smith
- Nutrition and Genomics Laboratory, Jean Mayer U. S. Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, United States
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30
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Shrestha D, Rahman ML, Workalemahu T, Zhu C, Tekola-Ayele F. Influence of Fetal and Maternal Genetic Susceptibility to Obesity on Birthweight in African Ancestry Populations. Front Genet 2018; 9:511. [PMID: 30450111 PMCID: PMC6224338 DOI: 10.3389/fgene.2018.00511] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2018] [Accepted: 10/12/2018] [Indexed: 02/02/2023] Open
Abstract
Fetal and maternal genetic propensity to obesity can influence birthweight. We investigated the effects of fetal and maternal genetic risk of obesity on birthweight and evaluated whether these genetic influences modify the well-known association between maternal pre-pregnancy body mass index (BMI) and birthweight. In 950 mother-baby pairs of African ancestry, a genetic risk score for adulthood obesity was generated for mothers (mGRS) and their babies (bGRS) as the weighted sum of BMI-increasing alleles of 97 single nucleotide polymorphisms known to be associated with BMI. The median GRS value was used as a cut-off to define high or low bGRS and mGRS. High bGRS was significantly associated with 70 g lower birthweight (95% Confidence Interval [CI] = −127.4 to −12.4) compared to low bGRS. mGRS was positively correlated with birthweight but the association was not significant. mGRS modified the significant birthweight-increasing effect of maternal pre-pregnancy BMI (P-for-interaction = 0.03); among mothers with low mGRS, those who were overweight or obese had 127.7 g heavier babies (95% CI = 27.1 to 228.2) compared to those who had normal weight. In summary, fetal obesity genetic risk loci exert direct influence on birthweight, and maternal loci modify the effect of pre-pregnancy BMI on birthweight.
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Affiliation(s)
- Deepika Shrestha
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States
| | - Mohammad L Rahman
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States
| | - Tsegaselassie Workalemahu
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States
| | - Chunming Zhu
- Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States
| | - Fasil Tekola-Ayele
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States
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Reddon H, Patel Y, Turcotte M, Pigeyre M, Meyre D. Revisiting the evolutionary origins of obesity: lazy versus peppy-thrifty genotype hypothesis. Obes Rev 2018; 19:1525-1543. [PMID: 30261552 DOI: 10.1111/obr.12742] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Revised: 06/26/2018] [Accepted: 07/01/2018] [Indexed: 12/31/2022]
Abstract
The recent global obesity epidemic is attributed to major societal and environmental changes, such as excessive energy intake and sedentary lifestyle. However, exposure to 'obesogenic' environments does not necessarily result in obesity at the individual level, as 40-75% of body mass index variation in population is attributed to genetic differences. The thrifty genotype theory posits that genetic variants promoting efficient food sequestering and optimal deposition of fat during periods of food abundance were evolutionarily advantageous for the early hunter-gatherer and were positively selected. However, the thrifty genotype is likely too simplistic and fails to provide a justification for the complex distribution of obesity predisposing gene variants and for the broad range of body mass index observed in diverse ethnic groups. This review proposes that gene pleiotropy may better account for the variability in the distribution of obesity susceptibility alleles across modern populations. We outline the lazy-thrifty versus peppy-thrifty genotype hypothesis and detail the body of evidence in the literature in support of this novel concept. Future population genetics and mathematical modelling studies that account for pleiotropy may further improve our understanding of the evolutionary origins of the current obesity epidemic.
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Affiliation(s)
- H Reddon
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada
| | - Y Patel
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada
| | - M Turcotte
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada
| | - M Pigeyre
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada.,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada
| | - D Meyre
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada.,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada
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Ochs-Balcom HM, Preus L, Nie J, Wactawski-Wende J, Agyemang L, Neuhouser ML, Tinker L, Zheng C, Kazlauskaite R, Qi L, Sucheston-Campbell LE. Physical activity modifies genetic susceptibility to obesity in postmenopausal women. Menopause 2018; 25:1131-1137. [PMID: 29762199 PMCID: PMC6136965 DOI: 10.1097/gme.0000000000001134] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVE We conducted a gene-environment interaction study to evaluate whether the association of body mass index (BMI) associated meta genome-wide association study single-nucleotide polymorphisms (SNPs) (as a genetic risk score) and BMI is modified by physical activity and age. METHODS In 8,206 women of European ancestry from the Women's Health Initiative (WHI), we used linear regression to examine main effects of the 95 SNP BMI genetic risk score (GRS) and physical activity on BMI, and evaluated whether genetic associations are modified by physical activity (two-way interaction) and age (three-way interaction). RESULTS We found evidence for modification of the BMI GRS-BMI association according to both physical activity and age. We observed a significant two-way interaction of BMI GRS × physical activity in the crude model (P interaction = 0.05), where a smaller effect of the BMI GRS on BMI with increasing physical activity. The beta coefficient was 0.05 (standard error [SE] = 0.02, P = 0.01) for the high-activity group compared with beta = 0.13 (SE = 0.02, P = 4.8 × 10) for the sedentary group. The three-way interaction was statistically significant (adjusted P interaction = 0.01). Notably, in the 70+ age group, the BMI GRS-BMI association was attenuated and no longer significant in the high-activity group; the beta coefficient for the 70+ high-activity group was relatively small and nonsignificant (beta = 0.02, SE = 0.03, P = 0.58) compared with 70+ sedentary group (beta = 0.17, SE = 0.03, P = 2.5 × 10). CONCLUSION Our study suggests that physical activity attenuates the influence of genetic predisposition to obesity, and this effect is more profound in the oldest age group.
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Affiliation(s)
- Heather M Ochs-Balcom
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY
| | - Leah Preus
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY
| | - Jing Nie
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY
| | - Jean Wactawski-Wende
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY
| | - Linda Agyemang
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY
| | - Marian L Neuhouser
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Lesley Tinker
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Cheng Zheng
- Joseph J. Zilber School of Public Health, University of Wisconsin, Milwaukee, Milwaukee, WI
| | - Rasa Kazlauskaite
- Department of Preventive Medicine, Rush University Medical Center, Chicago, IL
| | - Lihong Qi
- Department of Public Health Sciences, University of California Davis, Davis, CA
| | - Lara E Sucheston-Campbell
- College of Pharmacy, The Ohio State University, Columbus, OH
- Department of Veterinary Biosciences, College of Veterinary Medicine, The Ohio State University, Columbus, OH
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Antonio J, Knafo S, Kapoor R, Tartar JL. A fat mass and obesity-associated gene polymorphism influences fat mass in exercise-trained individuals. J Int Soc Sports Nutr 2018; 15:40. [PMID: 30124167 PMCID: PMC6102834 DOI: 10.1186/s12970-018-0246-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Accepted: 08/01/2018] [Indexed: 12/04/2022] Open
Abstract
Background A single nucleotide polymorphism (SNP) in the fat mass and obesity-associated (FTO) gene is a strong predictor of obesity in humans. The FTO SNP (rs1421085) results in a T to C nucleotide substitution that may result in an increased risk for obesity in individuals who carry at least one C allele. The purpose of this investigation was to characterize the FTO genotype in a cohort of exercise-trained men and women. Methods We tested 108 exercise-trained individuals that included professional mixed martial arts fighters, competitive distance runners, collegiate swimmers, stand-up paddlers as well as a cohort of recreational bodybuilders. Body composition was assessed via dual-energy x-ray absorptiometry (DXA). Saliva samples were collected in order to genotype participants and quantify cortisol levels. Results The physical characteristics of the subjects were as follows (mean±SD): body weight 74.5±15.6 kg; height 171.5±9.5 cm; bone mineral content 2.8±0.7 kg; fat mass 15.7±5.5 kg; lean body mass 55.9±14.4 kg; % body fat 21.6±7.0. Independent samples t tests showed that C allele carriers (n = 54) had significantly higher fat mass t(106) = 3.13, p < 0.01 and body fat percentage t(106) = 2.68, p < 0.01, relative to the TT group (n = 54) (i.e., fat mass: C/− 17.3 ±5.6 kg, TT 14.2±4.6 kg; body fat percentage: C/− group 23.4±7.4%, TT group 19.9±6.2). No other measures of body composition were associated with the FTO genotype (i.e., body mineral density, bone mineral content, or lean body mass). Moreover, cortisol levels were significantly higher in the TT group relative to the C allele carriers t(106) = 2.37, p = 0.02 (i.e., TT 0.35 ±0.35 μg/dL, C/− 0.22±0.16 μg/dL). Conclusions Our findings demonstrate a relationship between C allele carriers on the FTO gene and a predisposition to a higher fat mass and body fat percentage. In addition, we found no relationship between cortisol and fat mass. However, due to the cross-sectional nature of this investigation, we cannot infer causality regarding the FTO gene and body composition.
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Affiliation(s)
- Jose Antonio
- Department of Health and Human Performance, Nova Southeastern University, 3401 South University Drive, Davie, FL, 33328, USA.
| | - Sarah Knafo
- Department of Psychology and Neuroscience, Nova Southeastern University, Davie, FL, USA
| | - Ritishka Kapoor
- Department of Psychology and Neuroscience, Nova Southeastern University, Davie, FL, USA
| | - Jaime L Tartar
- Department of Psychology and Neuroscience, Nova Southeastern University, Davie, FL, USA
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Chen B, Li Z, Chen J, Ji J, Shen J, Xu Y, Zhao Y, Liu D, Shen Y, Zhang W, Shen J, Wang Y, Shi Y. Association of fat mass and obesity-associated and retinitis pigmentosa guanosine triphosphatase (GTPase) regulator-interacting protein-1 like polymorphisms with body mass index in Chinese women. Endocr J 2018; 65:783-791. [PMID: 29657248 DOI: 10.1507/endocrj.ej17-0554] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [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
Body mass index (BMI) is the most commonly used quantitative measure of adiposity. It is a kind of complex genetic diseases which are caused by multiple susceptibility genes. The first intron of fat mass and obesity-associated (FTO) has been widely discovered to be associated with BMI. Retinitis pigmentosa GTPase regulator-interacting protein-1 like (RPGRIP1L) is located in the upstream region of FTO and has been proved to be linked with obesity through functional tests. We carried out a genetic association analysis to figure out the role of the FTO gene and the RPGRIP1L gene in BMI. A quantitative traits study with 6,102 Chinese female samples, adjusted for age, was performed during our project. Among the twelve SNPs, rs1421085, rs1558902, rs17817449, rs8050136, rs9939609, rs7202296, rs56137030, rs9930506 and rs12149832 in the FTO gene were significantly associated with BMI after Bonferroni correction. Meanwhile, rs9934800 in the RPGRIP1L gene showed significance with BMI before Bonferroni correction, but this association was eliminated after Bonferroni correction. Our results suggested that genetic variants in the FTO gene were strongly associated with BMI in Chinese women, which may serve as targets of pharmaceutical research and development concerning BMI. Meanwhile, we didn't found the significant association between RPGRIP1L and BMI in Chinese women.
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Affiliation(s)
- Boyu Chen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Zhiqiang Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
- The Affiliated Hospital of Qingdao University & The Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao 266003, China
- Institute of Social Cognitive and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai 200240, China
- Institute of Neuropsychiatric Science and Systems Biological Medicine, Shanghai Jiao Tong University, Shanghai 200042, China
| | - Jianhua Chen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
- Institute of Social Cognitive and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai 200240, China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Jue Ji
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Jingyi Shen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Yufeng Xu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Yingying Zhao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Danping Liu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Yinhuan Shen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Weijie Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Jiawei Shen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Yonggang Wang
- Department of Neurology, School of Medicine, Renji Hospital, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Yongyong Shi
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
- The Affiliated Hospital of Qingdao University & The Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao 266003, China
- Institute of Social Cognitive and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai 200240, China
- Institute of Neuropsychiatric Science and Systems Biological Medicine, Shanghai Jiao Tong University, Shanghai 200042, China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
- Changning Mental Health Center, Shanghai 200042, China
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Chagnon M, O’Loughlin J, Engert JC, Karp I, Sylvestre MP. Missing single nucleotide polymorphisms in Genetic Risk Scores: A simulation study. PLoS One 2018; 13:e0200630. [PMID: 30024900 PMCID: PMC6053141 DOI: 10.1371/journal.pone.0200630] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Accepted: 06/29/2018] [Indexed: 12/20/2022] Open
Abstract
Using a genetic risk score (GRS) to predict a phenotype in a target sample can be complicated by missing data on the single nucleotide polymorphisms (SNPs) that comprise the GRS. This is usually addressed by imputation, omission of the SNPs or by replacing the missing SNPs with proxy SNPs. To assess the impact of the omission and proxy approaches on effect size estimation and predictive ability of weighted and unweighted GRS with small numbers of SNPs, we simulated a dichotomous phenotype conditional on real genotype data. We considered scenarios in which the proportion of missing SNPs ranged from 20-70%. We assessed the impact of omitting or replacing missing SNPs on the association between the GRS and phenotype, the corresponding statistical power and the area under the receiver operating curve. Omission resulted in a larger bias towards the null value of the effect size, a smaller predictive ability and greater loss of statistical power than proxy approaches. The predictive ability of a weighted GRS that includes SNPs with large weights depends of the availability of these large-weight SNPs.
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Affiliation(s)
- Miguel Chagnon
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Québec, Canada
- Department of Social and Preventive Medicine, School of Public Health, University of Montréal, Montréal, Québec, Canada
| | - Jennifer O’Loughlin
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Québec, Canada
- Department of Social and Preventive Medicine, School of Public Health, University of Montréal, Montréal, Québec, Canada
| | - James C. Engert
- Departments of Medicine and Human Genetics, McGill University, Montréal, Québec, Canada
| | - Igor Karp
- Department of Social and Preventive Medicine, School of Public Health, University of Montréal, Montréal, Québec, Canada
- Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Marie-Pierre Sylvestre
- Centre de recherche du Centre Hospitalier de l’Université de Montréal, Montréal, Québec, Canada
- Department of Social and Preventive Medicine, School of Public Health, University of Montréal, Montréal, Québec, Canada
- * E-mail:
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Liu HY, Alyass A, Abadi A, Peralta-Romero J, Suarez F, Gomez-Zamudio J, Audirac A, Parra EJ, Cruz M, Meyre D. Fine-mapping of 98 obesity loci in Mexican children. Int J Obes (Lond) 2018; 43:23-32. [PMID: 29769702 DOI: 10.1038/s41366-018-0056-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2017] [Revised: 12/29/2017] [Accepted: 01/31/2018] [Indexed: 11/09/2022]
Abstract
BACKGROUND/OBJECTIVES Mexico has one of the highest prevalence of childhood obesity in the world. Genome-wide association studies (GWAS) for obesity have identified multiple single-nucleotide polymorphisms (SNPs) in populations of European, East Asian, and African descent. The contribution of these loci to obesity in Mexican children is unclear. We assessed the transferability of 98 obesity loci in Mexican children and fine-mapped the association signals. SUBJECTS/METHODS The study included 405 and 390 Mexican children with normal weight and obesity. Participants were genotyped with a genome-wide dense SNP array designed for Latino populations, allowing for the analysis of GWAS index SNPs as well as fine-mapping SNPs, totaling 750 SNPs covering 98 loci. Two genetic risk scores (GRS) were constructed: a "discovery GRS" and a "best-associated GRS", representing the number of effect alleles at the GWAS index SNPs and at the best-associated SNPs after fine-mapping for each subject. RESULTS Seventeen obesity loci were significantly associated with obesity, and five had fine-mapping SNPs significantly better associated with obesity than their corresponding GWAS index SNPs in Mexican children. Six obesity-associated SNPs significantly departed from additive to dominant (N = 5) or recessive (N = 1) models, and a significant interaction was found between rs274609 (TNNI3K) and rs1010553 (ITIH4) on childhood obesity risk. The best-associated GRS was significantly more associated with childhood obesity (OR = 1.21 per additional risk allele [95%CI:1.17-1.25], P = 4.8 × 10-25) than the discovery GRS (OR = 1.05 per additional risk allele [95%CI:1.02-1.08], P = 8.0 × 10-4), and was also associated with waist-to-hip ratio, fasting glucose, fasting insulin and triglyceride levels, the association being mediated by obesity. An overall depletion of obesity risk alleles was observed in Mexican children with normal weight when compared to GWAS discovery populations. CONCLUSIONS Our study indicates a partial transferability of GWAS obesity loci in Mexican children, and supports the pertinence of post-GWAS fine-mapping experiments in the admixed Mexican population.
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Affiliation(s)
- Hsin Yen Liu
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Akram Alyass
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Arkan Abadi
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Jesus Peralta-Romero
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Fernando Suarez
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Jaime Gomez-Zamudio
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Astride Audirac
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Esteban J Parra
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, ON, Canada
| | - Miguel Cruz
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico.
| | - David Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada. .,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada.
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Goodarzi MO. Genetics of obesity: what genetic association studies have taught us about the biology of obesity and its complications. Lancet Diabetes Endocrinol 2018; 6:223-236. [PMID: 28919064 DOI: 10.1016/s2213-8587(17)30200-0] [Citation(s) in RCA: 259] [Impact Index Per Article: 43.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2017] [Revised: 05/24/2017] [Accepted: 05/24/2017] [Indexed: 01/01/2023]
Abstract
Genome-wide association studies (GWAS) for BMI, waist-to-hip ratio, and other adiposity traits have identified more than 300 single-nucleotide polymorphisms (SNPs). Although there is reason to hope that these discoveries will eventually lead to new preventive and therapeutic agents for obesity, this will take time because such developments require detailed mechanistic understanding of how an SNP influences phenotype (and this information is largely unavailable). Fortunately, absence of functional information has not prevented GWAS findings from providing insights into the biology of obesity. Genes near loci regulating total body mass are enriched for expression in the CNS, whereas genes for fat distribution are enriched in adipose tissue itself. Gene by environment and lifestyle interaction analyses have revealed that our increasingly obesogenic environment might be amplifying genetic risk for obesity, yet those at highest risk could mitigate this risk by increasing physical activity and possibly by avoiding specific dietary components. GWAS findings have also been used in mendelian randomisation analyses probing the causal association between obesity and its many putative complications. In supporting a causal association of obesity with diabetes, coronary heart disease, specific cancers, and other conditions, these analyses have clinical relevance in identifying which outcomes could be preventable through weight loss interventions.
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Affiliation(s)
- Mark O Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
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Impact of Genetic Variants on the Individual Potential for Body Fat Loss. Nutrients 2018; 10:nu10030266. [PMID: 29495392 PMCID: PMC5872684 DOI: 10.3390/nu10030266] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2017] [Revised: 02/09/2018] [Accepted: 02/23/2018] [Indexed: 12/21/2022] Open
Abstract
The past decade has witnessed the discovery of obesity-related genetic variants and their functions through genome-wide association studies. Combinations of risk alleles can influence obesity phenotypes with different degrees of effectiveness across various individuals by interacting with environmental factors. We examined the interaction between genetic variation and changes in dietary habits or exercise that influences body fat loss from a large Korean cohort (n = 8840). Out of 673 obesity-related SNPs, a total of 100 SNPs (37 for carbohydrate intake; 19 for fat intake; 44 for total calories intake; 25 for exercise onset) identified to have gene-environment interaction effect in generalized linear model were used to calculate genetic risk scores (GRS). Based on the GRS distribution, we divided the population into four levels, namely, “very insensitive”, “insensitive”, “sensitive”, and “very sensitive” for each of the four categories, “carbohydrate intake”, “fat intake”, “total calories intake”, and “exercise”. Overall, the mean body fat loss became larger when the sensitivity level was increased. In conclusion, genetic variants influence the effectiveness of dietary regimes for body fat loss. Based on our findings, we suggest a platform for personalized body fat management by providing the most suitable and effective nutrition or activity plan specific to an individual.
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Qasim A, Turcotte M, de Souza RJ, Samaan MC, Champredon D, Dushoff J, Speakman JR, Meyre D. On the origin of obesity: identifying the biological, environmental and cultural drivers of genetic risk among human populations. Obes Rev 2018; 19:121-149. [PMID: 29144594 DOI: 10.1111/obr.12625] [Citation(s) in RCA: 125] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2017] [Revised: 08/28/2017] [Accepted: 09/08/2017] [Indexed: 12/12/2022]
Abstract
Genetic predisposition to obesity presents a paradox: how do genetic variants with a detrimental impact on human health persist through evolutionary time? Numerous hypotheses, such as the thrifty genotype hypothesis, attempt to explain this phenomenon yet fail to provide a justification for the modern obesity epidemic. In this critical review, we appraise existing theories explaining the evolutionary origins of obesity and explore novel biological and sociocultural agents of evolutionary change to help explain the modern-day distribution of obesity-predisposing variants. Genetic drift, acting as a form of 'blind justice,' may randomly affect allele frequencies across generations while gene pleiotropy and adaptations to diverse environments may explain the rise and subsequent selection of obesity risk alleles. As an adaptive response, epigenetic regulation of gene expression may impact the manifestation of genetic predisposition to obesity. Finally, exposure to malnutrition and disease epidemics in the wake of oppressive social systems, culturally mediated notions of attractiveness and desirability, and diverse mating systems may play a role in shaping the human genome. As an important first step towards the identification of important drivers of obesity gene evolution, this review may inform empirical research focused on testing evolutionary theories by way of population genetics and mathematical modelling.
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Affiliation(s)
- A Qasim
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - M Turcotte
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - R J de Souza
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - M C Samaan
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.,Department of Pediatrics, McMaster University, Hamilton, ON, Canada.,Division of Pediatric Endocrinology, McMaster Children's Hospital, Hamilton, ON, Canada
| | - D Champredon
- Department of Biology, McMaster University, Hamilton, ON, Canada.,Agent-Based Modelling Laboratory, York University, Toronto, ON, Canada
| | - J Dushoff
- Department of Biology, McMaster University, Hamilton, ON, Canada
| | - J R Speakman
- Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, UK.,State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - D Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
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Gene-by-Activity Interactions on Obesity Traits of 6-Year-Old New Zealand European Children: A Children of SCOPE Study. Pediatr Exerc Sci 2018; 30:69-80. [PMID: 28661716 DOI: 10.1123/pes.2017-0077] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
PURPOSE The decline of physical activity in children is considered an important determinant to explain the rising rates of obesity. However, this risk may be augmented in children who are genetically susceptible to increased weight gain. We hypothesized that a sedentary lifestyle and moderate activity will interact with genetic loci, resulting in differential effects in relation to obesity risk. METHODS We recruited 643 European children born to participants in the New Zealand-based Screening for Pregnancy Endpoints (SCOPE) study. Seventy gene variants were evaluated by the Sequenom assay. Interaction analyses were performed between the genetic variants and the activity type derived from actigraphy, in relation to percentage body fat. RESULTS We found a statistically significant association between increased proportions of sedentary activity with increased percentage body fat scores (P = .012). The OLFM4-9568856 (P = .01) and GNPDA2-rs10938397 (P = .044) gene variants showed genotype differences with proportions of sedentary activity. Similarly, the OLFM4-9568856 (P = .021), CLOCK-rs4864548 (P = .029), and LEPR-1045895 (P = .047) showed genotype differences with proportions of moderate activity. We found evidence for unadjusted gene-by-activity interactions of SPACA3/SPRASA-rs16967845, PFKP-rs6602024, and SH2B1-rs7498665 on percentage body fat scores. CONCLUSIONS These findings indicate a differential effect of physical activity in relation to obesity risk, suggesting that children genetically predisposed to increased weight gain may benefit from higher levels of moderate activity.
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Zaharan NL, Muhamad NH, Jalaludin MY, Su TT, Mohamed Z, Mohamed MNA, A. Majid H. Non-Synonymous Single-Nucleotide Polymorphisms and Physical Activity Interactions on Adiposity Parameters in Malaysian Adolescents. Front Endocrinol (Lausanne) 2018; 9:209. [PMID: 29755414 PMCID: PMC5934415 DOI: 10.3389/fendo.2018.00209] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Accepted: 04/13/2018] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Several non-synonymous single-nucleotide polymorphisms (nsSNPs) have been shown to be associated with obesity. Little is known about their associations and interactions with physical activity (PA) in relation to adiposity parameters among adolescents in Malaysia. METHODS We examined whether (a) PA and (b) selected nsSNPs are associated with adiposity parameters and whether PA interacts with these nsSNPs on these outcomes in adolescents from the Malaysian Health and Adolescents Longitudinal Research Team study (n = 1,151). Body mass indices, waist-hip ratio, and percentage body fat (% BF) were obtained. PA was assessed using Physical Activity Questionnaire for Older Children (PAQ-C). Five nsSNPs were included: beta-3 adrenergic receptor (ADRB3) rs4994, FABP2 rs1799883, GHRL rs696217, MC3R rs3827103, and vitamin D receptor rs2228570, individually and as combined genetic risk score (GRS). Associations and interactions between nsSNPs and PAQ-C scores were examined using generalized linear model. RESULTS PAQ-C scores were associated with % BF (β = -0.44 [95% confidence interval -0.72, -0.16], p = 0.002). The CC genotype of ADRB3 rs4994 (β = -0.16 [-0.28, -0.05], corrected p = 0.01) and AA genotype of MC3R rs3827103 (β = -0.06 [-0.12, -0.00], p = 0.02) were significantly associated with % BF compared to TT and GG genotypes, respectively. Significant interactions with PA were found between ADRB3 rs4994 (β = -0.05 [-0.10, -0.01], p = 0.02) and combined GRS (β = -0.03 [-0.04, -0.01], p = 0.01) for % BF. CONCLUSION Higher PA score was associated with reduced % BF in Malaysian adolescents. Of the nsSNPs, ADRB3 rs4994 and MC3R rs3827103 were associated with % BF. Significant interactions with PA were found for ADRB3 rs4994 and combined GRS on % BF but not on measurements of weight or circumferences. Targeting body fat represent prospects for molecular studies and lifestyle intervention in this population.
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Affiliation(s)
- Nur Lisa Zaharan
- Department of Pharmacology, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- *Correspondence: Nur Lisa Zaharan, ,
| | - Nor Hanisah Muhamad
- Department of Pharmacology, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | | | - Tin Tin Su
- Centre for Population Health (CePH), Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Zahurin Mohamed
- Department of Pharmacology, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - M. N. A. Mohamed
- Sports Medicine Unit, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Hazreen A. Majid
- Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States
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Stryjecki C, Alyass A, Meyre D. Ethnic and population differences in the genetic predisposition to human obesity. Obes Rev 2018; 19:62-80. [PMID: 29024387 DOI: 10.1111/obr.12604] [Citation(s) in RCA: 86] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Revised: 06/17/2017] [Accepted: 08/02/2017] [Indexed: 12/22/2022]
Abstract
Obesity rates have escalated to the point of a global pandemic with varying prevalence across ethnic groups. These differences are partially explained by lifestyle factors in addition to genetic predisposition to obesity. This review provides a comprehensive examination of the ethnic differences in the genetic architecture of obesity. Using examples from evolution, heritability, admixture, monogenic and polygenic studies of obesity, we provide explanations for ethnic differences in the prevalence of obesity. The debate over definitions of race and ethnicity, the advantages and limitations of multi-ethnic studies and future directions of research are also discussed. Multi-ethnic studies have great potential to provide a better understanding of ethnic differences in the prevalence of obesity that may result in more targeted and personalized obesity treatments.
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Affiliation(s)
- C Stryjecki
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - A Alyass
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - D Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
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Morassut RE, Langlois C, Alyass A, Ishola AF, Yazdi FT, Mayhew AJ, Reddon H, MacKillop J, Pigeyre M, Meyre D. Rationale and design of GENEiUS: a prospective observational study on the genetic and environmental determinants of body mass index evolution in Canadian undergraduate students. BMJ Open 2017; 7:e019365. [PMID: 29229660 PMCID: PMC5778320 DOI: 10.1136/bmjopen-2017-019365] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
INTRODUCTION Obesity is a global epidemic and is a risk factor for developing other comorbidities. Young adulthood is a critical period for body weight change and establishing healthy lifestyle behaviours. The 'Freshman 15' suggests that undergraduate students gain 15 lbs (6.8 kg) during their first year of university, although evidence estimates a more modest weight gain of approximately 3-5 lbs (1.4-2.3 kg). Previous studies have only investigated weight change in the first year and do not study potential risk factors. Genetic and EnviroNmental Effects on weight in University Students (GENEiUS) is a prospective observational study which will investigate the environmental and biological determinants of weight change in undergraduate students over 4 years. METHODS AND ANALYSIS The GENEiUS study will recruit 2500 multiethnic undergraduates aged 17-25 years at McMaster University at the start of their first year and will follow them every 6 months for 4 years. Primary outcomes are obesity traits: body mass index, waist circumference, waist-to-hip ratio, body fat mass and body fat percentage. The contribution of well-established and novel genetic variants for obesity traits and heritability values will be derived from whole-genome single-nucleotide polymorphism genotyping arrays. Civil status, age, sex, ethnicity, length of residence in Canada, religiosity, energy intake, physical activity, exercise motivation, electronic screen time, sleep patterns, history of assault, smoking status, alcohol consumption, medication and drug use, stress, impulsivity, body image perception, self-esteem, anxiety, eating disorders and depression will be investigated for their effect on obesity traits. The findings of the GENEiUS study will be used to help design obesity prevention programme in North American universities with multiethnic populations. ETHICS AND DISSEMINATION Ethical approval of the study protocol has been obtained from the Hamilton Integrated Research Ethics Board. Study results will be disseminated through scientific publications, scholarly meetings, and collaborative meetings with university administration and student groups.
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Affiliation(s)
- Rita E Morassut
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Christine Langlois
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Akram Alyass
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Adeola F Ishola
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Fereshteh T Yazdi
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Alexandra J Mayhew
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Hudson Reddon
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - James MacKillop
- Peter Boris Centre for Addictions Research, McMaster University/St. Joseph’s Healthcare Hamilton, Hamilton, Ontario, Canada
| | - Marie Pigeyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
- Department of Nutrition, University of Lille, CHRU Lille, Lille, France
| | - David Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada
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Abadi A, Alyass A, Robiou du Pont S, Bolker B, Singh P, Mohan V, Diaz R, Engert JC, Yusuf S, Gerstein HC, Anand SS, Meyre D. Penetrance of Polygenic Obesity Susceptibility Loci across the Body Mass Index Distribution. Am J Hum Genet 2017; 101:925-938. [PMID: 29220676 PMCID: PMC5812888 DOI: 10.1016/j.ajhg.2017.10.007] [Citation(s) in RCA: 52] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2017] [Accepted: 10/12/2017] [Indexed: 12/17/2022] Open
Abstract
A growing number of single-nucleotide polymorphisms (SNPs) have been associated with body mass index (BMI) and obesity, but whether the effects of these obesity-susceptibility loci are uniform across the BMI distribution remains unclear. We studied the effects of 37 BMI-associated SNPs in 75,230 adults of European ancestry across BMI percentiles by using conditional quantile regression (CQR) and meta-regression (MR) models. The effects of nine SNPs (24%)-rs1421085 (FTO; p = 8.69 × 10-15), rs6235 (PCSK1; p = 7.11 × 10-6), rs7903146 (TCF7L2; p = 9.60 × 10-6), rs11873305 (MC4R; p = 5.08 × 10-5), rs12617233 (FANCL; p = 5.30 × 10-5), rs11672660 (GIPR; p = 1.64 × 10-4), rs997295 (MAP2K5; p = 3.25 × 10-4), rs6499653 (FTO; p = 6.23 × 10-4), and rs3824755 (NT5C2; p = 7.90 × 10-4)-increased significantly across the sample BMI distribution. We showed that such increases stemmed from unadjusted gene interactions that enhanced the effects of SNPs in persons with a high BMI. When 125 height-associated SNPs were analyzed for comparison, only one (<1%), rs6219 (IGF1, p = 1.80 × 10-4), showed effects that varied significantly across height percentiles. Cumulative gene scores of these SNPs (GS-BMI and GS-height) showed that only GS-BMI had effects that increased significantly across the sample distribution (BMI: p = 7.03 × 10-37; height: p = 0.499). Overall, these findings underscore the importance of gene-gene and gene-environment interactions in shaping the genetic architecture of BMI and advance a method for detecting such interactions by using only the sample outcome distribution.
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Affiliation(s)
- Arkan Abadi
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Akram Alyass
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Sebastien Robiou du Pont
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Ben Bolker
- Department of Mathematics and Statistics, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Pardeep Singh
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Viswanathan Mohan
- Madras Diabetes Research Foundation, Gopalapuram, Chennai 600086, India
| | - Rafael Diaz
- Estudios Clínicos Latino America, Paraguay 160, S2000CVD Rosario, Santa Fe, Argentina
| | | | - Salim Yusuf
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON L8S 4L8, Canada; Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton General Hospital, Hamilton, ON L8S 4L8, Canada; Department of Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Hertzel C Gerstein
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON L8S 4L8, Canada; Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton General Hospital, Hamilton, ON L8S 4L8, Canada; Department of Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Sonia S Anand
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON L8S 4L8, Canada; Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton General Hospital, Hamilton, ON L8S 4L8, Canada; Department of Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - David Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON L8S 4L8, Canada; Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada.
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45
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Gene-nutrient interactions and susceptibility to human obesity. GENES AND NUTRITION 2017; 12:29. [PMID: 29093760 PMCID: PMC5663124 DOI: 10.1186/s12263-017-0581-3] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Accepted: 07/04/2017] [Indexed: 12/28/2022]
Abstract
A large number of genome-wide association studies, transferability studies, and candidate gene studies performed in diverse populations around the world have identified gene variants that are associated with common human obesity. The mounting evidence suggests that these obesity gene variants interact with multiple environmental factors and increase susceptibility to this complex metabolic disease. The objective of this review article is to provide concise and updated information on energy balance, heritability of body weight, origins of gene variants, and gene-nutrient interactions in relation to human obesity. It is proposed that knowledge of these related topics will provide valuable insight for future preventative lifestyle intervention using targeted nutritional and medicinal therapies.
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Wang T, Huang T, Heianza Y, Sun D, Zheng Y, Ma W, Jensen MK, Kang JH, Wiggs JL, Pasquale LR, Rimm EB, Manson JE, Hu FB, Willett WC, Qi L. Genetic Susceptibility, Change in Physical Activity, and Long-term Weight Gain. Diabetes 2017; 66:2704-2712. [PMID: 28701334 PMCID: PMC5606317 DOI: 10.2337/db17-0071] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2017] [Accepted: 07/01/2017] [Indexed: 01/20/2023]
Abstract
Whether change in physical activity over time modifies the genetic susceptibility to long-term weight gain is unknown. We calculated a BMI-genetic risk score (GRS) based on 77 BMI-associated single nucleotide polymorphisms (SNPs) and a body fat percentage (BF%)-GRS based on 12 BF%-associated SNPs in 9,390 women from the Nurses' Health Study (NHS) and 5,291 men from the Health Professionals Follow-Up Study (HPFS). We analyzed the interactions between each GRS and change in physical activity on BMI/body weight change within five 4-year intervals from 1986 to 2006 using multivariable generalized linear models with repeated-measures analyses. Both the BMI-GRS and the BF%-GRS were associated with long-term increases in BMI/weight, and change in physical activity consistently interacted with the BF%-GRS on BMI change in the NHS (P for interaction = 0.025) and HPFS (P for interaction = 0.001). In the combined cohorts, 4-year BMI change per 10-risk allele increment was -0.02 kg/m2 among participants with greatest increase in physical activity and 0.24 kg/m2 among those with greatest decrease in physical activity (P for interaction < 0.001), corresponding to 0.01 kg versus 0.63 kg weight changes every 4 years (P for interaction = 0.001). Similar but marginal interactions were observed for the BMI-GRS (P for interaction = 0.045). Our data indicate that the genetic susceptibility to weight gain may be diminished by increasing physical activity.
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Affiliation(s)
- Tiange Wang
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA
- Shanghai Institute of Endocrine and Metabolic Disease, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tao Huang
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA
- Epidemiology Domain, Saw Swee Hock School of Public Health and Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Yoriko Heianza
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA
| | - Dianjianyi Sun
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA
| | - Yan Zheng
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Wenjie Ma
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Majken K Jensen
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Jae H Kang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Janey L Wiggs
- Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA
| | - Louis R Pasquale
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
- Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA
| | - Eric B Rimm
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - JoAnn E Manson
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Frank B Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Walter C Willett
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Lu Qi
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
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Rottensteiner M, Mäkelä S, Bogl LH, Törmäkangas T, Kaprio J, Kujala UM. Sport disciplines, types of sports, and waist circumference in young adulthood – a population-based twin study. Eur J Sport Sci 2017; 17:1184-1193. [DOI: 10.1080/17461391.2017.1356874] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Mirva Rottensteiner
- Health Sciences, Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Sara Mäkelä
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Leonie H. Bogl
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine FIMM, University of Helsinki, Helsinki, Finland
| | - Timo Törmäkangas
- Health Sciences, Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Jaakko Kaprio
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine FIMM, University of Helsinki, Helsinki, Finland
| | - Urho M. Kujala
- Health Sciences, Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
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48
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The importance of gene-environment interactions in human obesity. Clin Sci (Lond) 2017; 130:1571-97. [PMID: 27503943 DOI: 10.1042/cs20160221] [Citation(s) in RCA: 108] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2016] [Accepted: 05/23/2016] [Indexed: 12/16/2022]
Abstract
The worldwide obesity epidemic has been mainly attributed to lifestyle changes. However, who becomes obese in an obesity-prone environment is largely determined by genetic factors. In the last 20 years, important progress has been made in the elucidation of the genetic architecture of obesity. In parallel with successful gene identifications, the number of gene-environment interaction (GEI) studies has grown rapidly. This paper reviews the growing body of evidence supporting gene-environment interactions in the field of obesity. Heritability, monogenic and polygenic obesity studies provide converging evidence that obesity-predisposing genes interact with a variety of environmental, lifestyle and treatment exposures. However, some skepticism remains regarding the validity of these studies based on several issues, which include statistical modelling, confounding, low replication rate, underpowered analyses, biological assumptions and measurement precision. What follows in this review includes (1) an introduction to the study of GEI, (2) the evidence of GEI in the field of obesity, (3) an outline of the biological mechanisms that may explain these interaction effects, (4) methodological challenges associated with GEI studies and potential solutions, and (5) future directions of GEI research. Thus far, this growing body of evidence has provided a deeper understanding of GEI influencing obesity and may have tremendous applications in the emerging field of personalized medicine and individualized lifestyle recommendations.
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49
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A global evolutionary and metabolic analysis of human obesity gene risk variants. Gene 2017; 627:412-419. [PMID: 28687331 DOI: 10.1016/j.gene.2017.07.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2017] [Accepted: 07/02/2017] [Indexed: 01/20/2023]
Abstract
It is generally accepted that the selection of gene variants during human evolution optimized energy metabolism that now interacts with our obesogenic environment to increase the prevalence of obesity. The purpose of this study was to perform a global evolutionary and metabolic analysis of human obesity gene risk variants (110 human obesity genes with 127 nearest gene risk variants) identified using genome-wide association studies (GWAS) to enhance our knowledge of early and late genotypes. As a result of determining the mean frequency of these obesity gene risk variants in 13 available populations from around the world our results provide evidence for the early selection of ancestral risk variants (defined as selection before migration from Africa) and late selection of derived risk variants (defined as selection after migration from Africa). Our results also provide novel information for association of these obesity genes or encoded proteins with diverse metabolic pathways and other human diseases. The overall results indicate a significant differential evolutionary pattern for the selection of obesity gene ancestral and derived risk variants proposed to optimize energy metabolism in varying global environments and complex association with metabolic pathways and other human diseases. These results are consistent with obesity genes that encode proteins possessing a fundamental role in maintaining energy metabolism and survival during the course of human evolution.
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50
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Yang Q, Xiao T, Guo J, Su Z. Complex Relationship between Obesity and the Fat Mass and Obesity Locus. Int J Biol Sci 2017; 13:615-629. [PMID: 28539834 PMCID: PMC5441178 DOI: 10.7150/ijbs.17051] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2016] [Accepted: 03/24/2017] [Indexed: 12/15/2022] Open
Abstract
In the 21st century, obesity has become a serious problem because of increasing obese patients and numerous metabolic complications. The primary reasons for this situation are environmental and genetic factors. In 2007, FTO (fat mass and obesity associated) was the first gene identified through a genome-wide association study (GWAS) associated with obesity in humans. Subsequently, a cluster of single nucleotide polymorphisms (SNPs) in the first intron of the FTO gene was discovered to be associated with BMI and body composition. Various studies have explored the mechanistic basis behind this association. Thus, emerging evidence showed that FTO plays a key role regulating adipose tissue development and functions in body size and composition. Recent prevalent research topic concentrated in the three neighboring genes of FTO: RPGRIP1L, IRX3 and IRX5, as having a functional link between obesity-associated common variants within FTO and the observed human phenotypes. The purpose of this review is to present a comprehensive picture of the impact of FTO on obesity susceptibility and to illuminate these new studies of FTO function in adipose tissue.
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Affiliation(s)
- Qingyun Yang
- Key Research Center of Liver Regulation for Hyperlipidemia SATCM/Class III Laboratory of Metabolism SATCM, Guangdong TCM Key Laboratory for Metabolic Diseases, Guangdong Pharmaceutical University, Guangzhou, 510006, China
| | - Tiancun Xiao
- Inorganic Chemistry Laboratory, Oxford University, South Parks Road, OX1 3QR, United Kingdom.,Guangzhou Boxabio Technology Ltd, Guangzhou Science City, P R China
| | - Jiao Guo
- Key Research Center of Liver Regulation for Hyperlipidemia SATCM/Class III Laboratory of Metabolism SATCM, Guangdong TCM Key Laboratory for Metabolic Diseases, Guangdong Pharmaceutical University, Guangzhou, 510006, China
| | - Zhengquan Su
- Key Research Center of Liver Regulation for Hyperlipidemia SATCM/Class III Laboratory of Metabolism SATCM, Guangdong TCM Key Laboratory for Metabolic Diseases, Guangdong Pharmaceutical University, Guangzhou, 510006, China
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