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Jacob R, Bertrand C, Llewellyn C, Couture C, Labonté MÈ, Tremblay A, Bouchard C, Drapeau V, Pérusse L. Dietary Mediators of the Genetic Susceptibility to Obesity-Results from the Quebec Family Study. J Nutr 2021; 152:49-58. [PMID: 34610139 PMCID: PMC8754573 DOI: 10.1093/jn/nxab356] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 09/07/2021] [Accepted: 09/23/2021] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Recent studies showed that eating behaviors such as disinhibition, emotional and external eating, and snacking mediate genetic susceptibility to obesity. It remains unknown if diet quality and intake of specific food groups also mediate the genetic susceptibility to obesity. OBJECTIVE This study aimed to assess if diet quality and intakes of specific food groups mediate the association between a polygenic risk score (PRS) for BMI and BMI and waist circumference (WC). We hypothesized that poor diet quality, high intakes of energy-dense food groups, and low intakes of nutrient-dense food groups mediate the genetic susceptibility to obesity. METHODS This cross-sectional study included 750 participants (56.3% women, aged 41.5 ± 14.9 y, BMI 27.8 ± 7.5 kg/m2) from the Quebec Family Study. A PRSBMI based on >500,000 genetic variants was calculated using LDpred2. Dietary intakes were assessed with a 3-d food record from which a diet quality score (i.e. Nutrient Rich Food Index 6.3) and food groups were derived. Mediation analyses were conducted using a regression-based and bootstrapping approach. RESULTS The PRSBMI explained 25.7% and 19.8% of the variance in BMI and WC, respectively. The association between PRSBMI and BMI was partly mediated by poor diet quality (β = 0.33 ± 0.12; 95% CI: 0.13, 0.60), high intakes of fat and high-fat foods (β = 0.46 ± 0.16; 95% CI: 0.19, 0.79) and sugar-sweetened beverages (β = 0.25 ± 0.14; 95% CI: 0.05, 0.60), and low intakes of vegetables (β = 0.15 ± 0.08; 95% CI: 0.03, 0.32), fruits (β = 0.37 ± 0.12; 95% CI: 0.17, 0.64), and dairy products (β = 0.17 ± 0.09; 95% CI: 0.02, 0.37). The same trends were observed for WC. CONCLUSIONS The genetic susceptibility to obesity was partly mediated by poor diet quality and intakes of specific food groups. These results suggest that improvement in diet quality may reduce obesity risk among individuals with high genetic susceptibility and emphasize the need to intervene on diet quality among these individuals.
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Affiliation(s)
- Raphaëlle Jacob
- Centre Nutrition, santé et société (NUTRISS), Institute of Nutrition and Functional Foods (INAF), Université Laval, Quebec, Canada,School of Nutrition, Université Laval, Quebec, Canada,Quebec Heart and Lung Institute Research Center, Université Laval, Quebec, Canada
| | - Catherine Bertrand
- Centre Nutrition, santé et société (NUTRISS), Institute of Nutrition and Functional Foods (INAF), Université Laval, Quebec, Canada,Department of Kinesiology, Faculty of Medicine, Université Laval, Quebec, Canada
| | - Clare Llewellyn
- Department of Behavioural Science and Health, University College London, London, United Kingdom
| | - Christian Couture
- Quebec Heart and Lung Institute Research Center, Université Laval, Quebec, Canada,Department of Kinesiology, Faculty of Medicine, Université Laval, Quebec, Canada
| | - Marie-Ève Labonté
- Centre Nutrition, santé et société (NUTRISS), Institute of Nutrition and Functional Foods (INAF), Université Laval, Quebec, Canada,School of Nutrition, Université Laval, Quebec, Canada
| | - Angelo Tremblay
- Centre Nutrition, santé et société (NUTRISS), Institute of Nutrition and Functional Foods (INAF), Université Laval, Quebec, Canada,Quebec Heart and Lung Institute Research Center, Université Laval, Quebec, Canada,Department of Kinesiology, Faculty of Medicine, Université Laval, Quebec, Canada
| | | | - Vicky Drapeau
- Centre Nutrition, santé et société (NUTRISS), Institute of Nutrition and Functional Foods (INAF), Université Laval, Quebec, Canada,Quebec Heart and Lung Institute Research Center, Université Laval, Quebec, Canada,Department of Physical Education, Faculty of Education, Université Laval, Quebec, Canada
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Dou Z, Son JE, Hui CC. Irx3 and Irx5 - Novel Regulatory Factors of Postnatal Hypothalamic Neurogenesis. Front Neurosci 2021; 15:763856. [PMID: 34795556 PMCID: PMC8593166 DOI: 10.3389/fnins.2021.763856] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 10/07/2021] [Indexed: 12/27/2022] Open
Abstract
The hypothalamus is a brain region that exhibits highly conserved anatomy across vertebrate species and functions as a central regulatory hub for many physiological processes such as energy homeostasis and circadian rhythm. Neurons in the arcuate nucleus of the hypothalamus are largely responsible for sensing of peripheral signals such as leptin and insulin, and are critical for the regulation of food intake and energy expenditure. While these neurons are mainly born during embryogenesis, accumulating evidence have demonstrated that neurogenesis also occurs in postnatal-adult mouse hypothalamus, particularly in the first two postnatal weeks. This second wave of active neurogenesis contributes to the remodeling of hypothalamic neuronal populations and regulation of energy homeostasis including hypothalamic leptin sensing. Radial glia cell types, such as tanycytes, are known to act as neuronal progenitors in the postnatal mouse hypothalamus. Our recent study unveiled a previously unreported radial glia-like neural stem cell (RGL-NSC) population that actively contributes to neurogenesis in the postnatal mouse hypothalamus. We also identified Irx3 and Irx5, which encode Iroquois homeodomain-containing transcription factors, as genetic determinants regulating the neurogenic property of these RGL-NSCs. These findings are significant as IRX3 and IRX5 have been implicated in FTO-associated obesity in humans, illustrating the importance of postnatal hypothalamic neurogenesis in energy homeostasis and obesity. In this review, we summarize current knowledge regarding postnatal-adult hypothalamic neurogenesis and highlight recent findings on the radial glia-like cells that contribute to the remodeling of postnatal mouse hypothalamus. We will discuss characteristics of the RGL-NSCs and potential actions of Irx3 and Irx5 in the regulation of neural stem cells in the postnatal-adult mouse brain. Understanding the behavior and regulation of neural stem cells in the postnatal-adult hypothalamus will provide novel mechanistic insights in the control of hypothalamic remodeling and energy homeostasis.
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Affiliation(s)
- Zhengchao Dou
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Joe Eun Son
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Chi-chung Hui
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
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Abstract
Obesity is one of the risk factors for the development and progression of chronic kidney disease (CKD). Several studies have shown the association between increased body mass index and kidney function decline. Obesity leads to CKD directly by acting as an independent risk factor and indirectly through increasing risks for diabetes, hypertension, and atherosclerosis, a group of well-established independent risk factors for CKD. Alterations in renal hemodynamics, inflammation, and in hormones and growth factors results in hyperfiltration injury and focal segmental glomerulosclerosis. In recent years, many studies have shown that the gut microbiome may play a role in the pathogenesis of obesity. Dysbiosis has been noted in obese subjects in both human and animal studies. Changes in the gut microbiome in obese patients promote weight gain by effectively extracting energy from diet, and induction of low-grade inflammation. Evidence also points to the role of inflammation within the adipose tissue in obesity as a key factor in the pathogenesis of obesity-related complications. Thus, obesity is the net result of complex interactions between behavioral, genetic, and environmental factors. In terms of management, conservative approaches are often the first option, but they often are unsuccessful in achieving and/or maintaining weight loss, particularly in severe obesity. Consequently, nonmedical management with bariatric surgery is the most effective treatment option for morbid obesity and has shown mitigation of multiple risk factors for the progression of CKD. The most frequently performed interventions are vertical sleeve gastrectomy and Roux-en-Y gastric bypass. Studies have shown that bariatric surgery is associated with beneficial effects on CKD by mitigating its risk factors by weight loss, reducing insulin resistance, hemoglobin A1c, and proteinuria, in addition to positive long-term outcomes. Because of the epidemic of obesity, the prevalence of obesity in kidney transplant recipients also is increasing. The maximal body mass index (BMI) threshold for kidney transplantation is not clear. The Organ Procurement Transplant Network/Scientific Registry of Transplant Recipients 2019 annual data report showed that the proportion of kidney transplant recipient candidates with a BMI of 30 kg/m2 or greater is increasing steadily. Morbid obesity is linked to adverse graft outcomes including delayed graft function, primary nonfunction, and decreased graft survival. Obesity is also an independent risk factor for cardiovascular death in kidney transplant recipients, suggesting that these patients should not be excluded from transplantation based on their BMI because transplantation is associated with lower mortality compared with dialysis. However, many centers exclude obese patients (with different BMI cut-off values) from transplantation to avoid postoperative complications. To minimize the surgical complications of kidney transplantation in obese patients, our center has adopted the robot-assisted kidney transplantation procedure. Our data show that this approach is comparable with historical nonobese controls in the United Network for Organ Sharing database in terms of patient and graft survival. Another surgical option for this group of patients at our center is a combined robotic sleeve gastrectomy and robotic-assisted kidney transplant. In a recent study, this approach showed promising results in terms of weight loss, patient survival, and graft survival, and might become more common in the future.
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Kittel-Schneider S, Arteaga-Henriquez G, Vasquez AA, Asherson P, Banaschewski T, Brikell I, Buitelaar J, Cormand B, Faraone SV, Freitag CM, Ginsberg Y, Haavik J, Hartman CA, Kuntsi J, Larsson H, Matura S, McNeill RV, Ramos-Quiroga JA, Ribases M, Romanos M, Vainieri I, Franke B, Reif A. Non-mental diseases associated with ADHD across the lifespan: Fidgety Philipp and Pippi Longstocking at risk of multimorbidity? Neurosci Biobehav Rev 2021; 132:1157-1180. [PMID: 34757108 DOI: 10.1016/j.neubiorev.2021.10.035] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 10/24/2021] [Accepted: 10/25/2021] [Indexed: 12/16/2022]
Abstract
Several non-mental diseases seem to be associated with an increased risk of ADHD and ADHD seems to be associated with increased risk for non-mental diseases. The underlying trajectories leading to such brain-body co-occurrences are often unclear - are there direct causal relationships from one disorder to the other, or does the sharing of genetic and/or environmental risk factors lead to their occurring together more frequently or both? Our goal with this narrative review was to provide a conceptual synthesis of the associations between ADHD and non-mental disease across the lifespan. We discuss potential shared pathologic mechanisms, genetic background and treatments in co-occurring diseases. For those co-occurrences for which published studies with sufficient sample sizes exist, meta-analyses have been published by others and we discuss those in detail. We conclude that non-mental diseases are common in ADHD and vice versa and add to the disease burden of the patient across the lifespan. Insufficient attention to such co-occurring conditions may result in missed diagnoses and suboptimal treatment in the affected individuals.
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Affiliation(s)
- Sarah Kittel-Schneider
- Center of Mental Health, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Würzburg, Margarete-Höppel-Platz 1, D-97080 Würzburg, Germany; Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Goethe University, Heinrich-Hoffmann-Str. 10, D-60528 Frankfurt am Main, Germany.
| | - Gara Arteaga-Henriquez
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Catalonia, Spain; Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addictions, Vall d'Hebron Research Institute (VHIR), Universitat Autonoma de Barcelona, Barcelona, Catalonia, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Madrid, Spain; Department of Psychiatry and Forensic Medicine, Universitat Autonoma de Barcelona, Barcelona, Catalonia, Spain
| | - Alejandro Arias Vasquez
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, PO Box 9101, 6500 HB Nijmegen, the Netherlands; Departments of Psychiatry and Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Phil Asherson
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, SE5 8AF, London, UK
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Heidelberg University, Medical Faculty Mannheim, Mannheim, Germany
| | - Isabell Brikell
- National Centre for Register-based Research, Department of Economics and Business Economics Aarhus BSS, Aarhus University, Fuglesangs Allé 26, DK-8210 Aarhus V, Aarhus, Denmark; iPSYCH - The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen and Aarhus, Denmark; Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Box 281, 171 77, Stockholm, Sweden
| | - Jan Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Karakter Child and Adolescent Psychiatry University Center, Nijmegen, the Netherlands
| | - Bru Cormand
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Catalonia, Spain; Institut de Biomedicina de la Universitat de Barcelona (IBUB), Catalonia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Spain; Institut de Recerca Sant Joan de Déu (IR-SJD), Esplugues de Llobregat, Catalonia, Spain
| | - Stephen V Faraone
- Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Christine M Freitag
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Goethe University, Deutschordenstraße 50, D-60528 Frankfurt am Main, Germany
| | - Ylva Ginsberg
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Region Stockholm, Norra Stationsgatan 69, SE-113 64 Stockholm, Sweden
| | - Jan Haavik
- Bergen Center of Brain Plasticity, Division of Psychiatry, Haukeland University Hospital, Postboks 1400, 5021 Bergen, Norway; Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Catharina A Hartman
- University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), PO Box 30.001, 9700 RB, Groningen, the Netherlands
| | - Jonna Kuntsi
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, SE5 8AF, London, UK
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Box 281, 171 77, Stockholm, Sweden; Örebro University, School of Medical Sciences, Campus USÖ, S-701 82 Örebro, Sweden
| | - Silke Matura
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Goethe University, Heinrich-Hoffmann-Str. 10, D-60528 Frankfurt am Main, Germany
| | - Rhiannon V McNeill
- Center of Mental Health, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Würzburg, Margarete-Höppel-Platz 1, D-97080 Würzburg, Germany
| | - J Antoni Ramos-Quiroga
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Catalonia, Spain; Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addictions, Vall d'Hebron Research Institute (VHIR), Universitat Autonoma de Barcelona, Barcelona, Catalonia, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Madrid, Spain; Department of Psychiatry and Forensic Medicine, Universitat Autonoma de Barcelona, Barcelona, Catalonia, Spain
| | - Marta Ribases
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Catalonia, Spain; Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addictions, Vall d'Hebron Research Institute (VHIR), Universitat Autonoma de Barcelona, Barcelona, Catalonia, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Madrid, Spain; Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Catalonia, Spain
| | - Marcel Romanos
- Center of Mental Health, Department of Child and Adolescent Psychiatry, Psychotherapy and Psychosomatic Medicine, University Hospital of Würzburg, Margarete-Höppel-Platz 1, D-97080 Würzburg, Germany
| | - Isabella Vainieri
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, SE5 8AF, London, UK
| | - Barbara Franke
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, PO Box 9101, 6500 HB Nijmegen, the Netherlands; Departments of Psychiatry and Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Goethe University, Heinrich-Hoffmann-Str. 10, D-60528 Frankfurt am Main, Germany
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Wei Q. ACE and ACTN3 Gene Polymorphisms and Genetic Traits of Rowing Athletes in the Northern Han Chinese Population. Front Genet 2021; 12:736876. [PMID: 34721527 PMCID: PMC8551674 DOI: 10.3389/fgene.2021.736876] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Accepted: 09/20/2021] [Indexed: 01/12/2023] Open
Abstract
This investigation aimed to explore the effects of ACE I/D and ACTN3 R577X gene polymorphisms on specific quantitative variables, including height, weight, arm span, biacromial breadth, forced vital capacity (FVC), FVC/weight, maximal oxygen uptake (VO2max), prone bench pull (PBP), loaded barbell squat (LBS), and 3,000-m run, in 243 Chinese rowing athletes. The ACE and ACTN3 genotypes were obtained for each athlete via polymerase chain reaction on saliva samples, and the genotype frequency was analyzed. The ACE genotype frequency of rowing athletes were 45.8% II, 42.2% ID, and 12% DD for males and 33.6% II, 48% ID, and 18.4% DD for females. There were significant differences in weight in male athletes, PBP in female athletes, and ACE genotypes. A linear regression analysis using PBP and LBS as different dependent variables and ACE genotypes as independent variables based on the ACE I allele additive genetic effect showed a statistical significance in female athletes (p < 0.05). There was a significant difference in the distribution of the three genotypes among male athletes (36.7% XX, 38.5% RX, and 24.8% RR, χ2 = 5.191, df = 2, p = 0.022 < 0.05). There were no significant differences in the distribution of the three genotypes among female athletes (23.8% XX, 47.8% RX, 28.4% RR, χ 2 = 0.24, df = 2, p = 0.619 > 0.05). The ACTN3 gene polymorphism of male rowing athletes was dominated by the ACTN3 577X allele. There were significant differences in the χ 2 test between groups of male athletes. The ACTN3 R577 allele was dominant in female athletes. There were significant differences between PBP and FVC/body weight and ACTN3 genotypes in male athletes by ANOVA, respectively (p < 0.05). A linear regression analysis using FVC and FVC/body weight as dependent variables and ACTN3 genotypes as independent variables based on the ACTN3 577X allele recessive genetic effect showed statistical significance in male athletes (p < 0.05). These results suggested that ACE and ACTN3 gene polymorphisms may be used as biomarkers of genetic traits in Chinese rowing athletes.
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Affiliation(s)
- Qi Wei
- Key Laboratory of General Administration of Sport of China, Wuhan, China
- Hubei Institute of Sports Science, Wuhan, China
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Xu Y, Hiyoshi A, Smith KA, Piehl F, Olsson T, Fall K, Montgomery S. Association of Infectious Mononucleosis in Childhood and Adolescence With Risk for a Subsequent Multiple Sclerosis Diagnosis Among Siblings. JAMA Netw Open 2021; 4:e2124932. [PMID: 34633426 PMCID: PMC8506233 DOI: 10.1001/jamanetworkopen.2021.24932] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
IMPORTANCE Epstein-Barr virus and its acute manifestation, infectious mononucleosis (IM), are associated with an increased risk of multiple sclerosis (MS). Whether this association is confounded by susceptibility to infection is still debated. OBJECTIVE To assess whether hospital-diagnosed IM during childhood, adolescence, or young adulthood is associated with subsequent MS diagnosis independent of shared familial factors. DESIGN, SETTING, AND PARTICIPANTS This population-based cohort study used the Swedish Total Population Register to identify individuals born in Sweden from January 1, 1958, to December 31, 1994. Participants aged 20 years were followed up from January 1, 1978, to December 31, 2018, with a median follow-up of 15.38 (IQR, 8.68-23.55; range, 0.01-40.96) years. Data were analyzed from October 2020 to July 2021. EXPOSURE Hospital-diagnosed IM before 25 years of age. MAIN OUTCOMES AND MEASURES Diagnoses of MS from 20 years of age were identified. Risk of an MS diagnosis associated with IM in childhood (birth to 10 years of age), adolescence (11-19 years of age), and early adulthood (20-24 years of age [time-dependent variable]) were estimated using conventional and stratified (to address familial environmental or genetic confounding) Cox proportional hazards regression. RESULTS Of the 2 492 980 individuals (1 312 119 men [52.63%] and 1 180 861 women [47.37%]) included, 5867 (0.24%) had an MS diagnosis from 20 years of age (median age, 31.50 [IQR, 26.78-37.54] years). Infectious mononucleosis in childhood (hazard ratio [HR], 1.98; 95% CI, 1.21-3.23) and adolescence (HR, 3.00; 95% CI, 2.48-3.63) was associated with an increased risk of an MS diagnosis that remained significant after controlling for shared familial factors in stratified Cox proportional hazards regression (HRs, 2.87 [95% CI, 1.44-5.74] and 3.19 [95% CI, 2.29-4.46], respectively). Infectious mononucleosis in early adulthood was also associated with risk of a subsequent MS diagnosis (HR, 1.89; 95% CI, 1.18-3.05), but this risk was attenuated and was not significant after controlling for shared familial factors (HR, 1.51; 95% CI, 0.82-2.76). CONCLUSIONS AND RELEVANCE These findings suggest that IM in childhood and particularly adolescence is a risk factor associated with a diagnosis of MS, independent of shared familial factors.
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Affiliation(s)
- Yin Xu
- Clinical Epidemiology and Biostatistics, School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Ayako Hiyoshi
- Clinical Epidemiology and Biostatistics, School of Medical Sciences, Örebro University, Örebro, Sweden
- Department of Public Health Sciences, Stockholm University, Stockholm, Sweden
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - Kelsi A. Smith
- Clinical Epidemiology Division, Karolinska Institute, Stockholm, Sweden
| | - Fredrik Piehl
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Tomas Olsson
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Katja Fall
- Clinical Epidemiology and Biostatistics, School of Medical Sciences, Örebro University, Örebro, Sweden
- Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden
| | - Scott Montgomery
- Clinical Epidemiology and Biostatistics, School of Medical Sciences, Örebro University, Örebro, Sweden
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
- Clinical Epidemiology Division, Karolinska Institute, Stockholm, Sweden
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Gjermeni E, Kirstein AS, Kolbig F, Kirchhof M, Bundalian L, Katzmann JL, Laufs U, Blüher M, Garten A, Le Duc D. Obesity-An Update on the Basic Pathophysiology and Review of Recent Therapeutic Advances. Biomolecules 2021; 11:1426. [PMID: 34680059 PMCID: PMC8533625 DOI: 10.3390/biom11101426] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 09/16/2021] [Accepted: 09/22/2021] [Indexed: 12/13/2022] Open
Abstract
Obesity represents a major public health problem with a prevalence increasing at an alarming rate worldwide. Continuous intensive efforts to elucidate the complex pathophysiology and improve clinical management have led to a better understanding of biomolecules like gut hormones, antagonists of orexigenic signals, stimulants of fat utilization, and/or inhibitors of fat absorption. In this article, we will review the pathophysiology and pharmacotherapy of obesity including intersection points to the new generation of antidiabetic drugs. We provide insight into the effectiveness of currently approved anti-obesity drugs and other therapeutic avenues that can be explored.
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Affiliation(s)
- Erind Gjermeni
- Department of Electrophysiology, Heart Center Leipzig at University of Leipzig, 04289 Leipzig, Germany;
- Department of Cardiology, Median Centre for Rehabilitation Schmannewitz, 04774 Dahlen, Germany;
| | - Anna S. Kirstein
- Pediatric Research Center, University Hospital for Children and Adolescents, Leipzig University, 04103 Leipzig, Germany; (A.S.K.); (F.K.); (A.G.)
| | - Florentien Kolbig
- Pediatric Research Center, University Hospital for Children and Adolescents, Leipzig University, 04103 Leipzig, Germany; (A.S.K.); (F.K.); (A.G.)
| | - Michael Kirchhof
- Department of Cardiology, Median Centre for Rehabilitation Schmannewitz, 04774 Dahlen, Germany;
| | - Linnaeus Bundalian
- Institute of Human Genetics, University Medical Center Leipzig, 04103 Leipzig, Germany;
| | - Julius L. Katzmann
- Klinik und Poliklinik für Kardiologie, University Clinic Leipzig, 04103 Leipzig, Germany; (J.L.K.); (U.L.)
| | - Ulrich Laufs
- Klinik und Poliklinik für Kardiologie, University Clinic Leipzig, 04103 Leipzig, Germany; (J.L.K.); (U.L.)
| | - Matthias Blüher
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Zentrum München at the University of Leipzig and University Hospital Leipzig, 04103 Leipzig, Germany;
| | - Antje Garten
- Pediatric Research Center, University Hospital for Children and Adolescents, Leipzig University, 04103 Leipzig, Germany; (A.S.K.); (F.K.); (A.G.)
| | - Diana Le Duc
- Institute of Human Genetics, University Medical Center Leipzig, 04103 Leipzig, Germany;
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Zentrum München at the University of Leipzig and University Hospital Leipzig, 04103 Leipzig, Germany;
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, 04103 Leipzig, Germany
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Dashti HS, Levy DE, Hivert MF, Alimenti K, McCurley JL, Saxena R, Thorndike AN. Genetic risk for obesity and the effectiveness of the ChooseWell 365 workplace intervention to prevent weight gain and improve dietary choices. Am J Clin Nutr 2021; 115:180-188. [PMID: 34581769 PMCID: PMC8755032 DOI: 10.1093/ajcn/nqab303] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Accepted: 08/26/2021] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND It is unknown whether behavioral interventions to improve diet are effective in people with a genetic predisposition to obesity. OBJECTIVES To examine associations between BMI genetic risk and changes in weight and workplace purchases by employees participating in a randomized controlled trial of an automated behavioral workplace intervention to promote healthy food choices. METHODS Participants were hospital employees enrolled in a 12-mo intervention followed by a 12-mo follow-up. Hospital cafeterias utilized a traffic-light labeling system (e.g., green = healthy, red = unhealthy) that was used to calculate a validated Healthy Purchasing Score (HPS; higher = healthier). A weighted genome-wide BMI genetic score was generated by summing BMI-increasing alleles. RESULTS The study included 397 adults of European ancestry (mean age, 44.9 y; 80.9% female). Participants in the highest genetic quartile (Q4) had a lower HPS and higher purchases of red-labeled items relative to participants in the lowest quartile (Q1) at baseline [Q4-Q1 Beta HPS, -4.66 (95% CI, -8.01 to -1.32); red-labeled items, 4.26% (95% CI, 1.45%-7.07%)] and at the 12-mo [HPS, -3.96 (95% CI, -7.5 to -0.41); red-labeled items, 3.20% (95% CI, 0.31%-6.09%)] and 24-mo [HPS, -3.70 (95% CI, -7.40 to 0.00); red-labeled items, 3.48% (95% CI, 0.54%-6.41%)] follow-up periods. In the intervention group, increases in HPS were similar in Q4 and Q1 at 12 mo (Q4-Q1 Beta, 1.04; 95% CI, -2.42 to 4.50). At the 24-mo follow-up, the change in BMI from baseline was similar between Q4 and Q1 (0.17 kg/m2; 95% CI, -0.55 to 0.89 kg/m2) in the intervention group, but higher in Q4 than Q1 (1.20 kg/m2; 95% CI, 0.26-2.13 kg/m2) in the control group. No interaction was evident between the treatment arm and genetic score for BMI or HPS. CONCLUSIONS Having a high BMI genetic risk was associated with greater increases in BMI and lower quality purchases over 2 y. The 12-mo behavioral intervention improved employees' food choices, regardless of the genetic burden, and may have attenuated weight gain conferred by having the genetic risk.
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Affiliation(s)
| | - Douglas E Levy
- Mongan Institute Health Policy Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA,Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Kaitlyn Alimenti
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Jessica L McCurley
- Division of General Internal Medicine, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Richa Saxena
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA,Department of Medical and Population Genetics, Broad Institute, Cambridge, MA, USA,Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Anne N Thorndike
- Division of General Internal Medicine, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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Yudkovicz JJ, Minster RL, Barinas-Mitchell E, Christensen K, Feitosa M, Barker MS, Newman AB, Kuipers AL. Pleiotropic effects between cardiovascular disease risk factors and measures of cognitive and physical function in long-lived adults. Sci Rep 2021; 11:17980. [PMID: 34504188 PMCID: PMC8429644 DOI: 10.1038/s41598-021-97298-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 08/17/2021] [Indexed: 11/16/2022] Open
Abstract
Cardiovacular disease (CVD) is the leading cause of death among older adults and is often accompanied by functional decline. It is unclear what is driving this co-occurrence, but it may be behavioral, environmental and/or genetic. We used a family-based study to estimate the phenotypic and shared genetic correlation between CVD risk factors and physical and cognitive functional measures. Participants (n = 1,881) were from the Long Life Family Study, which enrolled families based on their exceptional longevity (sample mean age = 69.4 years, 44% female). Cardiovascular disease risk factors included carotid vessel measures [intima-media thickness and inter-adventitial diameter], obesity [body mass index (BMI) and waist circumference], and hypertension [systolic and diastolic blood pressures]. Function was measured in the physical [gait speed, grip strength, chair stand] and cognitive [digital symbol substitution test, retained and working memory, semantic fluency, and trail making tests] domains. We used SOLAR to estimate the genetic, environmental, and phenotypic correlation between each pair adjusting for age, age2, sex, field center, smoking, height, and weight. There were significant phenotypic correlations (range |0.05–0.22|) between CVD risk factors and physical and cognitive function (all P < 0.05). Most significant genetic correlations (range |0.21–0.62|) were between CVD risk factorsand cognitive function, although BMI and waist circumference had significant genetic correlation with gait speed and chair stand time (range |0.29–0.53|; all P < 0.05). These results suggest that CVD risk factors may share a common genetic-and thus, biologic-basis with both cognitive and physical function. This is particularly informative for research into the genetic determinants of chronic disease.
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Affiliation(s)
- Julia J Yudkovicz
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ryan L Minster
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Kaare Christensen
- Department of Epidemiology, Biostatistics and Biodemography, Danish Aging Research Center, University of Southern Denmark, Odense C, Denmark
| | - Mary Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Megan S Barker
- Department of Neurology, Columbia University, New York, NY, USA
| | - Anne B Newman
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Allison L Kuipers
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA.
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Guerra JVS, Dias MMG, Brilhante AJVC, Terra MF, García-Arévalo M, Figueira ACM. Multifactorial Basis and Therapeutic Strategies in Metabolism-Related Diseases. Nutrients 2021; 13:nu13082830. [PMID: 34444990 PMCID: PMC8398524 DOI: 10.3390/nu13082830] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 08/09/2021] [Accepted: 08/11/2021] [Indexed: 12/11/2022] Open
Abstract
Throughout the 20th and 21st centuries, the incidence of non-communicable diseases (NCDs), also known as chronic diseases, has been increasing worldwide. Changes in dietary and physical activity patterns, along with genetic conditions, are the main factors that modulate the metabolism of individuals, leading to the development of NCDs. Obesity, diabetes, metabolic associated fatty liver disease (MAFLD), and cardiovascular diseases (CVDs) are classified in this group of chronic diseases. Therefore, understanding the underlying molecular mechanisms of these diseases leads us to develop more accurate and effective treatments to reduce or mitigate their prevalence in the population. Given the global relevance of NCDs and ongoing research progress, this article reviews the current understanding about NCDs and their related risk factors, with a focus on obesity, diabetes, MAFLD, and CVDs, summarizing the knowledge about their pathophysiology and highlighting the currently available and emerging therapeutic strategies, especially pharmacological interventions. All of these diseases play an important role in the contamination by the SARS-CoV-2 virus, as well as in the progression and severity of the symptoms of the coronavirus disease 2019 (COVID-19). Therefore, we briefly explore the relationship between NCDs and COVID-19.
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Affiliation(s)
- João V. S. Guerra
- Brazilian Center for Research in Energy and Materials (CNPEM), Brazilian Biosciences National Laboratory (LNBio), Polo II de Alta Tecnologia—R. Giuseppe Máximo Scolfaro, Campinas 13083-100, Brazil; (J.V.S.G.); (M.M.G.D.); (M.F.T.)
- Graduate Program in Pharmaceutical Sciences, Faculty Pharmaceutical Sciences, University of Campinas, Campinas 13083-970, Brazil
| | - Marieli M. G. Dias
- Brazilian Center for Research in Energy and Materials (CNPEM), Brazilian Biosciences National Laboratory (LNBio), Polo II de Alta Tecnologia—R. Giuseppe Máximo Scolfaro, Campinas 13083-100, Brazil; (J.V.S.G.); (M.M.G.D.); (M.F.T.)
- Graduate Program in Functional and Molecular Biology, Institute of Biology, State University of Campinas (Unicamp), Campinas 13083-970, Brazil;
| | - Anna J. V. C. Brilhante
- Graduate Program in Functional and Molecular Biology, Institute of Biology, State University of Campinas (Unicamp), Campinas 13083-970, Brazil;
- Brazilian Center for Research in Energy and Materials (CNPEM), Brazilian Biorenewables National Laboratory (LNBR), Polo II de Alta Tecnologia—R. Giuseppe Máximo Scolfaro, Campinas 13083-100, Brazil
| | - Maiara F. Terra
- Brazilian Center for Research in Energy and Materials (CNPEM), Brazilian Biosciences National Laboratory (LNBio), Polo II de Alta Tecnologia—R. Giuseppe Máximo Scolfaro, Campinas 13083-100, Brazil; (J.V.S.G.); (M.M.G.D.); (M.F.T.)
- Graduate Program in Functional and Molecular Biology, Institute of Biology, State University of Campinas (Unicamp), Campinas 13083-970, Brazil;
| | - Marta García-Arévalo
- Brazilian Center for Research in Energy and Materials (CNPEM), Brazilian Biosciences National Laboratory (LNBio), Polo II de Alta Tecnologia—R. Giuseppe Máximo Scolfaro, Campinas 13083-100, Brazil; (J.V.S.G.); (M.M.G.D.); (M.F.T.)
- Correspondence: or (M.G.-A.); (A.C.M.F.)
| | - Ana Carolina M. Figueira
- Brazilian Center for Research in Energy and Materials (CNPEM), Brazilian Biosciences National Laboratory (LNBio), Polo II de Alta Tecnologia—R. Giuseppe Máximo Scolfaro, Campinas 13083-100, Brazil; (J.V.S.G.); (M.M.G.D.); (M.F.T.)
- Correspondence: or (M.G.-A.); (A.C.M.F.)
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111
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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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112
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Тимашева ЯР, Балхиярова ЖР, Кочетова ОВ. [Current state of the obesity research: genetic aspects, the role of microbiome, and susceptibility to COVID-19]. PROBLEMY ENDOKRINOLOGII 2021; 67:20-35. [PMID: 34533011 PMCID: PMC9753850 DOI: 10.14341/probl12775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 07/21/2021] [Accepted: 08/02/2021] [Indexed: 11/06/2022]
Abstract
Obesity affects over 700 million people worldwide and its prevalence keeps growing steadily. The problem is particularly relevant due to the increased risk of COVID-19 complications and mortality in obese patients. Obesity prevalence increase is often associated with the influence of environmental and behavioural factors, leading to stigmatization of people with obesity due to beliefs that their problems are caused by poor lifestyle choices. However, hereditary predisposition to obesity has been established, likely polygenic in nature. Morbid obesity can result from rare mutations having a significant effect on energy metabolism and fat deposition, but the majority of patients does not present with monogenic forms. Microbiome low diversity significantly correlates with metabolic disorders (inflammation, insulin resistance), and the success of weight loss (bariatric) surgery. However, data on the long-term consequences of bariatric surgery and changes in the microbiome composition and genetic diversity before and after surgery are currently lacking. In this review, we summarize the results of studies of the genetic characteristics of obesity patients, molecular mechanisms of obesity, contributing to the unfavourable course of coronavirus infection, and the evolution of their microbiome during bariatric surgery, elucidating the mechanisms of disease development and creating opportunities to identify potential new treatment targets and design effective personalized approaches for the diagnosis, management, and prevention of obesity.
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Affiliation(s)
- Я. Р. Тимашева
- Институт биохимии и генетики Уфимского федерального исследовательского центра Российской академии наук;
Башкирский государственный медицинский университет
| | - Ж. Р. Балхиярова
- Институт биохимии и генетики Уфимского федерального исследовательского центра Российской академии наук;
Башкирский государственный медицинский университет;
Университет Суррея
| | - О. В. Кочетова
- Институт биохимии и генетики Уфимского федерального исследовательского центра Российской академии наук
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113
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Fisher V, Sebastiani P, Cupples LA, Liu CT. ANNORE: Genetic fine mapping with functional annotation. Hum Mol Genet 2021; 31:32-40. [PMID: 34302344 DOI: 10.1093/hmg/ddab210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 06/30/2021] [Accepted: 07/19/2021] [Indexed: 11/13/2022] Open
Abstract
Genome-wide association studies (GWAS) have successfully identified loci of the human genome implicated in numerous complex traits. However, the limitations of this study design make it difficult to identify specific causal variants or biological mechanisms of association. We propose a novel method, AnnoRE, which uses GWAS summary statistics, local correlation structure among genotypes, and functional annotation from external databases to prioritize the most plausible causal SNPs in each trait-associated locus. Our proposed method improves upon previous fine mapping approaches by estimating the effects of functional annotation from genome-wide summary statistics, allowing for the inclusion of many annotation categories. By implementing a multiple regression model with differential shrinkage via random effects, we avoid reductive assumptions on the number of causal SNPs per locus. Application of this method to a large GWAS meta-analysis of body mass index identified six loci with significant evidence in favor of one or more variants. In an additional 24 loci, one or two variants were strongly prioritized over others in the region. The use of functional annotation in genetic fine mapping studies helps to distinguish between variants in high LD, and to identify promising targets for follow-up studies.
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Affiliation(s)
- Virginia Fisher
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Paola Sebastiani
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA.,Tufts Medical Center, Boston, MA 02111, USA
| | - L Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
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114
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Martikainen P, Korhonen K, Jelenkovic A, Lahtinen H, Havulinna A, Ripatti S, Borodulin K, Salomaa V, Davey Smith G, Silventoinen K. Joint association between education and polygenic risk score for incident coronary heart disease events: a longitudinal population-based study of 26 203 men and women. J Epidemiol Community Health 2021; 75:651-657. [PMID: 33408166 DOI: 10.1136/jech-2020-214358] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 11/03/2020] [Accepted: 12/16/2020] [Indexed: 12/28/2022]
Abstract
BACKGROUND Genetic vulnerability to coronary heart disease (CHD) is well established, but little is known whether these effects are mediated or modified by equally well-established social determinants of CHD. We estimate the joint associations of the polygenetic risk score (PRS) for CHD and education on CHD events. METHODS The data are from the 1992, 1997, 2002, 2007 and 2012 surveys of the population-based FINRISK Study including measures of social, behavioural and metabolic factors and genome-wide genotypes (N=26 203). Follow-up of fatal and non-fatal incident CHD events (N=2063) was based on nationwide registers. RESULTS Allowing for age, sex, study year, region of residence, study batch and principal components, those in the highest quartile of PRS for CHD had strongly increased risk of CHD events compared with the lowest quartile (HR=2.26; 95% CI: 1.97 to 2.59); associations were also observed for low education (HR=1.58; 95% CI: 1.32 to 1.89). These effects were largely independent of each other. Adjustment for baseline smoking, alcohol use, body mass index, igh-density lipoprotein (HDL) and total cholesterol, blood pressure and diabetes attenuated the PRS associations by 10% and the education associations by 50%. We do not find strong evidence of interactions between PRS and education. CONCLUSIONS PRS and education predict CHD events, and these associations are independent of each other. Both can improve CHD prediction beyond behavioural risks. The results imply that observational studies that do not have information on genetic risk factors for CHD do not provide confounded estimates for the association between education and CHD.
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Affiliation(s)
- Pekka Martikainen
- Population Research Unit, University of Helsinki Faculty of Social Sciences, Helsinki, Finland
- Centre for Health Equity Studies, Stockholm University, Stockholm, Sweden
- Max Planck Institute for Demographic Research, Rostock, Germany
| | - Kaarina Korhonen
- Population Research Unit, University of Helsinki Faculty of Social Sciences, Helsinki, Finland
| | - Aline Jelenkovic
- Department of Physiology, University of the Basque Country, Bilbao, País Vasco, Spain
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Hannu Lahtinen
- Population Research Unit, University of Helsinki Faculty of Social Sciences, Helsinki, Finland
| | - Aki Havulinna
- Institute for Molecular Medicine Finland, Helsinki, Finland
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Uusimaa, Finland
| | - Samuli Ripatti
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine Finland, Helsinki, Finland
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Katja Borodulin
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Uusimaa, Finland
- Age Institute, Helsinki, Finland
| | - Veikko Salomaa
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Uusimaa, Finland
| | - George Davey Smith
- Department of Social Medicine, University of Bristol, Bristol, Bristol, UK
| | - Karri Silventoinen
- Population Research Unit, University of Helsinki Faculty of Social Sciences, Helsinki, Finland
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Cawley J, Biener A, Meyerhoefer C, Ding Y, Zvenyach T, Smolarz BG, Ramasamy A. Job Absenteeism Costs of Obesity in the United States: National and State-Level Estimates. J Occup Environ Med 2021; 63:565-573. [PMID: 33769330 DOI: 10.1097/jom.0000000000002198] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
OBJECTIVE To estimate the causal effect of obesity on job absenteeism and the associated lost productivity in the United States, both nationwide and by state. METHODS We conducted a retrospective pooled cross-sectional analysis using the 2001 to 2016 Medical Expenditure Panel Survey and estimated two-part models of instrumental variables. RESULTS Obesity, relative to normal weight, raises job absenteeism due to injury or illness by 3.0 days per year (128%). Annual productivity loss due to obesity ranges from $271 to $542 (lower/upper bound) per employee with obesity, with national productivity losses ranging from $13.4 to $26.8 billion in 2016. Trends in state-level estimates mirror those at the national level, varying across states. CONCLUSIONS Obesity significantly raises job absenteeism. Reductions in job absenteeism should be included when calculating the cost-effectiveness of interventions to prevent or reduce obesity among employed adults.
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Affiliation(s)
- John Cawley
- Department of Policy Analysis and Management and Department of Economics, Cornell University, Ithaca, New York (Dr Cawley); Department of Economics, Lafayette College, Easton, Pennsylvania (Dr Biener); College of Business, Lehigh University, Bethlehem, Pennsylvania (Dr Meyerhoefer); Bluebird Bio, Inc., Cambridge, Massachusetts (Dr Ding); Nurse Disrupted, LLC, Madison, Wisconsin (Dr Zvenyach); Novo Nordisk Inc., Plainsboro, NJ (Dr Smolarz and Ms Ramasamy)
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116
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Justice AE, Young K, Gogarten SM, Sofer T, Graff M, Love SAM, Wang Y, Klimentidis YC, Cruz M, Guo X, Hartwig F, Petty L, Yao J, Allison MA, Below JE, Buchanan TA, Chen YDI, Goodarzi MO, Hanis C, Highland HM, Hsueh WA, Ipp E, Parra E, Palmas W, Raffel LJ, Rotter JI, Tan J, Taylor KD, Valladares A, Xiang AH, Sánchez-Johnsen L, Isasi CR, North KE. Genome-wide association study of body fat distribution traits in Hispanics/Latinos from the HCHS/SOL. Hum Mol Genet 2021; 30:2190-2204. [PMID: 34165540 PMCID: PMC8561424 DOI: 10.1093/hmg/ddab166] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 06/16/2021] [Accepted: 06/17/2021] [Indexed: 01/02/2023] Open
Abstract
Central obesity is a leading health concern with a great burden carried by ethnic minority populations, especially Hispanics/Latinos. Genetic factors contribute to the obesity burden overall and to inter-population differences. We aimed to identify the loci associated with central adiposity measured as waist-to-hip ratio (WHR), waist circumference (WC) and hip circumference (HIP) adjusted for body mass index (adjBMI) by using the Hispanic Community Health Study/Study of Latinos (HCHS/SOL); determine if differences in associations differ by background group within HCHS/SOL and determine whether previously reported associations generalize to HCHS/SOL. Our analyses included 7472 women and 5200 men of mainland (Mexican, Central and South American) and Caribbean (Puerto Rican, Cuban and Dominican) background residing in the USA. We performed genome-wide association analyses stratified and combined across sexes using linear mixed-model regression. We identified 16 variants for waist-to-hip ratio adjusted for body mass index (WHRadjBMI), 22 for waist circumference adjusted for body mass index (WCadjBMI) and 28 for hip circumference adjusted for body mass index (HIPadjBMI), which reached suggestive significance (P < 1 × 10-6). Many loci exhibited differences in strength of associations by ethnic background and sex. We brought a total of 66 variants forward for validation in cohorts (N = 34 161) with participants of Hispanic/Latino, African and European descent. We confirmed four novel loci (P < 0.05 and consistent direction of effect, and P < 5 × 10-8 after meta-analysis), including two for WHRadjBMI (rs13301996, rs79478137); one for WCadjBMI (rs3168072) and one for HIPadjBMI (rs28692724). Also, we generalized previously reported associations to HCHS/SOL, (8 for WHRadjBMI, 10 for WCadjBMI and 12 for HIPadjBMI). Our study highlights the importance of large-scale genomic studies in ancestrally diverse Hispanic/Latino populations for identifying and characterizing central obesity susceptibility that may be ancestry-specific.
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Affiliation(s)
- Anne E Justice
- Department of Population Health Sciences, Geisinger Health System, Danville, PA 17822, USA,Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA,To whom correspondence should be addressed at: Department of Population Health Sciences, Geisinger Health System, Danville, PA 17822, USA. Tel: +1 5702141009; Fax: +1 5702143071;
| | - Kristin Young
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
| | | | - Tamar Sofer
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Misa Graff
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
| | - Shelly Ann M Love
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
| | - Yujie Wang
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
| | - Yann C Klimentidis
- Department of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ 85724, USA
| | - Miguel Cruz
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI (CMNSXX1)-IMSS, Mexico City 06720, Mexico
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Fernando Hartwig
- Center for Epidemiological Research, Universidade Federal de Pelotas, Pelotas 96020, Brazil
| | - Lauren Petty
- Division of Genetic Medicine, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Matthew A Allison
- Division of Preventive Medicine, Department of Family Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Jennifer E Below
- Division of Genetic Medicine, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Thomas A Buchanan
- Department of Medicine, Keck School of Medicine and Diabetes and Obesity Research Institute, University of Southern California, Los Angeles, CA 90033, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Mark O Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Craig Hanis
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Heather M Highland
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
| | - Willa A Hsueh
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Wexner Medical Center, The Ohio State University, Columbus, OH 43210, USA
| | - Eli Ipp
- Department of Medicine, Endocrinology, Diabetes & Metabolism, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Esteban Parra
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, ON L5L 1C6, Canada
| | - Walter Palmas
- Department of Medicine, Columbia University Medical Center, New York, NY 10032, USA
| | - Leslie J Raffel
- Department of PediatrIcs, Division of Genetic and Genomic Medicine, University of California, Irvine, CA 92868, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Jingyi Tan
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Adan Valladares
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI (CMNSXX1)-IMSS, Mexico City 06720, Mexico
| | - Anny H Xiang
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA 91101, USA
| | - Lisa Sánchez-Johnsen
- Department of Family Medicine, Rush University Medical Center, Chicago, IL 60612, USA
| | - Carmen R Isasi
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY 10467, USA,Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY 10467, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
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117
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Morales E, Torres-Castillo N, Garaulet M. Infancy and Childhood Obesity Grade Predicts Weight Loss in Adulthood: The ONTIME Study. Nutrients 2021; 13:nu13072132. [PMID: 34206431 PMCID: PMC8308354 DOI: 10.3390/nu13072132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 06/03/2021] [Accepted: 06/17/2021] [Indexed: 11/16/2022] Open
Abstract
We examined the relationships between intergenerational obesity, weight and size at birth, and obesity from infancy to adolescence with weight loss in response to a dietary intervention. We studied 4264 participants (3369 women; mean age 41.5 ± 12.9 years) of the ONTIME study. Participants followed a weight-loss treatment based on a Mediterranean diet. Associations between grandparental and parental obesity grade, birth weight and size, and obesity grade in infancy, childhood and adolescence with total weight loss in response to treatment were assessed, using multivariate linear regression models. A lower weight loss (kg) in response to treatment was found among participants who were obese during infancy (beta coefficient -2.13 kg; 95% CI, -3.96, -0.30; p = 0.023). Furthermore, obesity during infancy and also during childhood was associated with a slower weekly rate of weight loss during treatment (p < 0.05). In conclusion, obesity in infancy and in childhood impairs the weight-loss response to dietary treatments in adulthood. Tackling obesity throughout early life may improve the effectiveness of weight-loss interventions in adulthood.
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Affiliation(s)
- Eva Morales
- Biomedical Research Institute of Murcia (IMIB-Arrixaca), 30120 Murcia, Spain;
- Department of Public Health Sciences, University of Murcia, 30100 Murcia, Spain
| | - Nathaly Torres-Castillo
- Department of Molecular Biology and Genomics, Institute for Translational Nutrigenetics and Nutrigenomics, Health Sciences University Center, University of Guadalajara, Guadalajara 44340, Jalisco, Mexico;
| | - Marta Garaulet
- Biomedical Research Institute of Murcia (IMIB-Arrixaca), 30120 Murcia, Spain;
- Department of Physiology, Regional Campus of International Excellence, University of Murcia, 30100 Murcia, Spain
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, and Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA
- Correspondence: ; Tel.: +34-868883930
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118
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Sewaybricker LE, Melhorn SJ, Rosenbaum JL, Askren MK, Tyagi V, Webb MF, De Leon MRB, Grabowski TJ, Schur EA. Reassessing relationships between appetite and adiposity in people at risk of obesity: A twin study using fMRI. Physiol Behav 2021; 239:113504. [PMID: 34147511 DOI: 10.1016/j.physbeh.2021.113504] [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: 03/05/2021] [Revised: 06/03/2021] [Accepted: 06/16/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND Neuroimaging studies suggest that appetitive drive is enhanced in obesity. OBJECTIVE To test if appetitive drive varies in direct proportion to the level of body adiposity after accounting for genetic factors that contribute to both brain response and obesity risk. SUBJECTS/METHODS Participants were adult monozygotic (n = 54) and dizygotic (n = 30) twins with at least one member of the pair with obesity. Body composition was assessed by dual-energy X-ray absorptiometry. Hormonal and appetite measures were obtained in response to a standardized meal that provided 20% of estimated daily caloric needs and to an ad libitum buffet meal. Pre- and post-meal functional magnetic resonance imaging (fMRI) assessed brain response to visual food cues in a set of a priori appetite-regulating regions. Exploratory voxelwise analyses outside a priori regions were performed with correction for multiple comparisons. RESULTS In a group of 84 adults, the majority with obesity (75%), body fat mass was not associated with hormonal responses to a meal (glucose, insulin, glucagon-like peptide-1 and ghrelin, all P>0.40), subjective feelings of hunger (β=-0.01 mm [95% CI -0.35, 0.34] P = 0.97) and fullness (β=0.15 mm [-0.15, 0.44] P = 0.33), or buffet meal intake in relation to estimated daily caloric needs (β=0.28% [-0.05, 0.60] P = 0.10). Body fat mass was also not associated with brain response to high-calorie food cues in appetite-regulating regions (Pre-meal β=-0.12 [-0.32, 0.09] P = 0.26; Post-meal β=0.18 [-0.02, 0.37] P = 0.09; Change by a meal β=0.29 [-0.02, 0.61] P = 0.07). Conversely, lower fat mass was associated with being weight reduced (β=-0.05% [-0.07, -0.03] P<0.001) and greater pre-meal activation to high-calorie food cues in the dorsolateral prefrontal cortex (Z = 3.63 P = 0.017). CONCLUSIONS In a large study of adult twins, the majority with overweight or obesity, the level of adiposity was not associated with excess appetitive drive as assessed by behavioral, hormonal, or fMRI measures.
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Affiliation(s)
- Leticia E Sewaybricker
- Department of Medicine, University of Washington, 1959 NE Pacific St. Box 356420, Seattle, WA, 98195 USA
| | - Susan J Melhorn
- Department of Medicine, University of Washington, 1959 NE Pacific St. Box 356420, Seattle, WA, 98195 USA
| | - Jennifer L Rosenbaum
- Department of Medicine, University of Washington, 1959 NE Pacific St. Box 356420, Seattle, WA, 98195 USA
| | - Mary K Askren
- Departments of Radiology and Neurology, University of Washington, 1959 NE Pacific St. Seattle, WA, 98195 USA
| | - Vidhi Tyagi
- Department of Medicine, University of Washington, 1959 NE Pacific St. Box 356420, Seattle, WA, 98195 USA
| | - Mary F Webb
- Department of Medicine, University of Washington, 1959 NE Pacific St. Box 356420, Seattle, WA, 98195 USA
| | - Mary Rosalynn B De Leon
- Department of Medicine, University of Washington, 1959 NE Pacific St. Box 356420, Seattle, WA, 98195 USA
| | - Thomas J Grabowski
- Departments of Radiology and Neurology, University of Washington, 1959 NE Pacific St. Seattle, WA, 98195 USA
| | - Ellen A Schur
- Department of Medicine, University of Washington, 1959 NE Pacific St. Box 356420, Seattle, WA, 98195 USA.
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119
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Dashti HS, Ordovás JM. Genetics of Sleep and Insights into Its Relationship with Obesity. Annu Rev Nutr 2021; 41:223-252. [PMID: 34102077 DOI: 10.1146/annurev-nutr-082018-124258] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Considerable recent advancements in elucidating the genetic architecture of sleep traits and sleep disorders may provide insight into the relationship between sleep and obesity. Despite the considerable involvement of the circadian clock in sleep and metabolism, few shared genes, including FTO, were implicated in genome-wide association studies (GWASs) of sleep and obesity. Polygenic scores composed of signals from GWASs of sleep traits show largely null associations with obesity, suggesting lead variants are unique to sleep. Modest genome-wide genetic correlations are observed between many sleep traits and obesity and are largest for snoring.Notably, U-shaped positive genetic correlations with body mass index (BMI) exist for both short and long sleep durations. Findings from Mendelian randomization suggest robust causal effects of insomnia on higher BMI and, conversely, of higher BMI on snoring and daytime sleepiness. Bidirectional effects between sleep duration and daytime napping with obesity may also exist. Limited gene-sleep interaction studies suggest that achieving favorable sleep, as part of a healthy lifestyle, may attenuate genetic predisposition to obesity, but whether these improvements produce clinically meaningful reductions in obesity risk remains unclear. Investigations of the genetic link between sleep and obesity for sleep disorders other than insomnia and in populations of non-European ancestry are currently limited. Expected final online publication date for the Annual Review of Nutrition, Volume 41 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Hassan S Dashti
- Center for Genomic Medicine and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, USA; .,Broad Institute, Cambridge, Massachusetts 02142, USA
| | - José M Ordovás
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, Massachusetts 02111, USA.,Precision Nutrition and Obesity Program, IMDEA Alimentación, 28049 Madrid, Spain
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120
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Vallis M, Macklin D. When behaviour meets biology: if obesity is a chronic medical disease what is obesity management? Clin Obes 2021; 11:e12443. [PMID: 33590712 DOI: 10.1111/cob.12443] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 12/07/2020] [Accepted: 01/12/2021] [Indexed: 12/15/2022]
Affiliation(s)
- M Vallis
- Department of Family Medicine, Dalhousie University, Halifax, Nova Scotia, Canada
| | - D Macklin
- Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada
- Medcan Clinic, Toronto, Ontario, Canada
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121
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Tsukahara Y, Namba A, Kamada H, Torii S, Tabata S, Yamasawa F, Sato K. Factors that affect menarche in Japanese national-level track-and-field athletes. Am J Hum Biol 2021; 34:e23622. [PMID: 34048626 DOI: 10.1002/ajhb.23622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Revised: 05/08/2021] [Accepted: 05/18/2021] [Indexed: 11/12/2022] Open
Abstract
OBJECTIVES The minimum body mass index (BMI) required to menarche and the relationship between the training onset age of sports and menarche is not fully understood. The aim of this study is to elucidate the minimum BMI required to attain menarche in female adolescent athletes competing at a national level, and to determine how the occurrence of menarche is associated with training onset age in track-and-field athletes. METHODS Overall, 134 sprinters and 44 long-distance (LD) runners of ninth-grade females at a national level were enrolled and an anonymous questionnaire was administered. RESULTS As BMI increased, the proportion of athletes who had attained menarche increased. The BMI cutoff values for menarche were 17.3 and 17.1 kg/m2 for sprinters and LD runners, respectively. Menarche had not occurred in almost 50% of the LD runners who began training at elementary school, and among LD runners, those who began training at elementary school had 18.4 higher odds of not attaining menarche until the age of 15 years as opposed to those who started training after elementary school. CONCLUSIONS The BMI cutoff values could be an indicator for menarche in sprinters and LD runners. For LD runners, starting to compete at elementary school could be a risk factor for delayed menarche.
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Affiliation(s)
- Yuka Tsukahara
- Institute for Integrated Sports Medicine, Keio University School of Medicine, Tokyo, Japan.,Medical Committee, Japan Association of Athletics Federations (JAAF), Tokyo, Japan.,Waseda Institute for Sport Sciences, Waseda University, Saitama, Japan
| | - Akira Namba
- Medical Committee, Japan Association of Athletics Federations (JAAF), Tokyo, Japan.,Department of Clinical Genomics, Saitama Medical University, Saitama, Japan
| | - Hiroshi Kamada
- Medical Committee, Japan Association of Athletics Federations (JAAF), Tokyo, Japan.,Department of Orthopaedic Surgery, University of Tsukuba, Ibaraki, Japan
| | - Suguru Torii
- Medical Committee, Japan Association of Athletics Federations (JAAF), Tokyo, Japan.,Faculty of Sport Sciences, Waseda University, Saitama, Japan
| | - Shogo Tabata
- Medical Committee, Japan Association of Athletics Federations (JAAF), Tokyo, Japan
| | - Fumihiro Yamasawa
- Medical Committee, Japan Association of Athletics Federations (JAAF), Tokyo, Japan
| | - Kazuki Sato
- Institute for Integrated Sports Medicine, Keio University School of Medicine, Tokyo, Japan
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122
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Brener A, Waksman Y, Rosenfeld T, Levy S, Peleg I, Raviv A, Interator H, Lebenthal Y. The heritability of body composition. BMC Pediatr 2021; 21:225. [PMID: 33964919 PMCID: PMC8105919 DOI: 10.1186/s12887-021-02695-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 04/29/2021] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Physical growth during childhood and adolescence is influenced by both genetic and environmental factors. Heritability, the proportion of phenotypic variance explained by genetic factors, has been demonstrated for stature and weight status. The aim of this study was to explore the heritability of body composition. METHODS A real-life, observational study of the children and adolescents referred to the Endocrine Unit in a tertiary medical center. In January 2018, body composition by means of bioimpedance analysis (BIA) was implemented as part of the standard intake assessment of subjects referred for endocrine consultation. The clinic BIA database was searched for subjects with the term "observation of growth" as the sole reason for referral. BIA of 114 triads of healthy subjects aged 5-18 years and their parents were analyzed. The BIA report included the following data: fat mass, fat percentage, truncal fat percentage and muscle mass. Calculated variables included: appendicular skeletal muscle mass (ASMM = the sum of muscle mass of four limbs), muscle-to-fat ratio [MFR = ASMM (kg)/fat mass (kg)] and sarcopenic index [(SI = ASMM(kg)/height (meter)²]. Data collection from medical files included pubertal stage and home address for socioeconomic position grading. RESULTS There were sex differences in body composition parameters in both the prepubertal and pubertal subjects. The boys among the prepubertal subjects had a lower fat percentage on average than girls (p = 0.020). Among the adolescents, boys on average had lower fat percentage (p = 0.011), higher sarcopenic index (p = 0.021), and higher muscle-to-fat ratio (p < 0.001), than adolescent girls. Correlation analyses between body composition parameters of all participants revealed significant correlations in the sarcopenic index of prepubertal children and their parents (boys-fathers: r = 0.380, p = 0.050; boys-mothers: r = 0.435, p = 0.026; girls-fathers: r = 0.462, p = 0.012; girls-mothers: r = 0.365, p = 0.050) and adiposity indices (fat percentage, truncal fat percentage and muscle-to-fat ratio) of prepubertal boys and their mothers (r = 0.438, p = 0.025; r = 0.420, p = 0.033, and r = 0.478, p = 0.014, respectively). There were no associations between body composition parameters of adolescents and their parents. Socioeconomic position adversely affected fat percentage in adolescent girls and mothers. CONCLUSIONS Heritable body composition traits were demonstrated in childhood but not in adolescence, suggesting that environmental influence has a more telling effect during teenage years.
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Affiliation(s)
- Avivit Brener
- Pediatric Endocrinology and Diabetes Unit, Dana-Dwek Children's Hospital, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel. .,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
| | - Yarden Waksman
- Pediatric Endocrinology and Diabetes Unit, Dana-Dwek Children's Hospital, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Talya Rosenfeld
- Pediatric Endocrinology and Diabetes Unit, Dana-Dwek Children's Hospital, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.,The Nutrition & Dietetics Unit, Dana-Dwek Children's Hospital, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Sigal Levy
- Statistical Education Unit, The Academic College of Tel Aviv Yaffo, Tel Aviv, Israel
| | - Itai Peleg
- Pediatric Endocrinology and Diabetes Unit, Dana-Dwek Children's Hospital, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Adi Raviv
- Pediatric Endocrinology and Diabetes Unit, Dana-Dwek Children's Hospital, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Hagar Interator
- Pediatric Endocrinology and Diabetes Unit, Dana-Dwek Children's Hospital, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.,The Nutrition & Dietetics Unit, Dana-Dwek Children's Hospital, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Yael Lebenthal
- Pediatric Endocrinology and Diabetes Unit, Dana-Dwek Children's Hospital, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
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123
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Bouchard C. Genetics of Obesity: What We Have Learned Over Decades of Research. Obesity (Silver Spring) 2021; 29:802-820. [PMID: 33899337 DOI: 10.1002/oby.23116] [Citation(s) in RCA: 60] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 12/15/2020] [Accepted: 12/16/2020] [Indexed: 12/14/2022]
Abstract
There is a genetic component to human obesity that accounts for 40% to 50% of the variability in body weight status but that is lower among normal weight individuals (about 30%) and substantially higher in the subpopulation of individuals with obesity and severe obesity (about 60%-80%). The appreciation that heritability varies across classes of BMI represents an important advance. After controlling for BMI, ectopic fat and fat distribution traits are characterized by heritability levels ranging from 30% to 55%. Defects in at least 15 genes are the cause of monogenic obesity cases, resulting mostly from deficiencies in the leptin-melanocortin signaling pathway. Approximately two-thirds of the BMI heritability can be imputed to common DNA variants, whereas low-frequency and rare variants explain the remaining fraction. Diminishing allele effect size is observed as the number of obesity-associated variants expands, with most BMI-increasing or -decreasing alleles contributing only a few grams or less to body weight. Obesity-promoting alleles exert minimal effects in normal weight individuals but have larger effects in individuals with a proneness to obesity, suggesting a higher penetrance; however, it is not known whether these larger effect sizes precede obesity or are caused by an obese state. The obesity genetic risk is conditioned by thousands of DNA variants that make genetically based obesity prevention and treatment a major challenge.
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Affiliation(s)
- Claude Bouchard
- Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA
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124
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Rana S, Bhatti AA. Predicting anthropometric and metabolic traits with a genetic risk score for obesity in a sample of Pakistanis. Sci Rep 2021; 11:8320. [PMID: 33859285 PMCID: PMC8050295 DOI: 10.1038/s41598-021-87702-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 04/01/2021] [Indexed: 12/18/2022] Open
Abstract
Obesity is an outcome of multiple factors including environmental and genetic influences. Common obesity is a polygenic trait indicating that multiple genetic variants act synergistically to influence its expression. We constructed a genetic risk score (GRS) based on five genetic variants (MC4R rs17782313, BDNF rs6265, FTO rs1421085, TMEM18 rs7561317, and NEGR1 rs2815752) and examined its association with obesity-related traits in a sample of Pakistanis. The study involved 306 overweight/obese (OW/OB) and 300 normal-weight (NW) individuals. The age range of the study participants was 12-63 years. All anthropometric and metabolic parameters were measured for each participant via standard procedures and biochemical assays, respectively. The genetic variants were genotyped by allelic discrimination assays. The age- and gender-adjusted associations between the GRS and obesity-related anthropometric and metabolic measures were determined using linear regression analyses. The results showed that OW/OB individuals had significantly higher mean ranks of GRS than NW individuals. Moreover, a significant association of the GRS with obesity-related anthropometric traits was seen. However, the GRS did not appear to affect any obesity-related metabolic parameter. In conclusion, our findings indicate the combined effect of multiple genetic variants on the obesity-related anthropometric phenotypes in Pakistanis.
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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.
| | - 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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125
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Loos RJF, Burant C, Schur EA. Strategies to Understand the Weight-Reduced State: Genetics and Brain Imaging. Obesity (Silver Spring) 2021; 29 Suppl 1:S39-S50. [PMID: 33759393 PMCID: PMC8500189 DOI: 10.1002/oby.23101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 12/03/2020] [Accepted: 12/03/2020] [Indexed: 11/09/2022]
Abstract
Most individuals with obesity or overweight have difficulty maintaining weight loss. The weight-reduced state induces changes in many physiological processes that appear to drive weight regain. Here, we review the use of cell biology, genetics, and imaging techniques that are being used to begin understanding why weight regain is the normal response to dieting. As with obesity itself, weight regain has both genetic and environmental drivers. Genetic drivers for "thinness" and "obesity" largely overlap, but there is evidence for specific genetic loci that are different for each of these weight states. There is only limited information regarding the genetics of weight regain. Currently, most genetic loci related to weight point to the central nervous system as the organ responsible for determining the weight set point. Neuroimaging tools have proved useful in studying the contribution of the central nervous system to the weight-reduced state in humans. Neuroimaging technologies fall into three broad categories: functional, connectivity, and structural neuroimaging. Connectivity and structural imaging techniques offer unique opportunities for testing mechanistic hypotheses about changes in brain function or tissue structure in the weight-reduced state.
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Affiliation(s)
- Ruth J. F. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Charles Burant
- Department of Internal Medicine, University of Washington, Seattle, Washington, USA
| | - Ellen A. Schur
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
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126
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Conrad Z, Hatfield DP, Hennessy E, Maneval E, Ty E, Pankey CL. Evaluating Moderation of Parent-Teen Overweight/Obesity Relation by Household Socioeconomic Status. Curr Dev Nutr 2021; 5:nzab030. [PMID: 33959690 PMCID: PMC8085476 DOI: 10.1093/cdn/nzab030] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 03/24/2021] [Accepted: 03/31/2021] [Indexed: 12/15/2022] Open
Abstract
Evidence links parent-offspring weight status, but few studies have evaluated whether markers of socioeconomic status moderate this relation. The 2014 Family Life, Activity, Sun, Health, and Eating study was used to assess intergenerational weight status in a national sample of parent-teen dyads. Multivariable logistic regression models assessed the relation between parent-teen weight status, controlling for teen and parent dietary factors, physical activity, demographic factors, and socioeconomic factors. Models with interaction assessed moderation by household food security status and participation in federal assistance programs. In fully adjusted models, sons were 2.66 (95% CI: 1.56, 4.55) times more likely to have overweight/obesity if their mother had overweight/obesity, and daughters were 3.35 (95% CI: 1.91, 5.86) times more likely. This relation was stronger in mother-son pairs in households with lower food security. These findings provide important new information that can be used to inform nutritional counseling efforts and educational programs that support families with socioeconomic disadvantage.
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Affiliation(s)
- Zach Conrad
- Department of Health Sciences, William & Mary, Williamsburg, VA, USA
| | - Daniel P Hatfield
- Division of Nutrition Interventions, Communication and Behavior Change, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
- ChildObesity180, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Erin Hennessy
- Division of Nutrition Interventions, Communication and Behavior Change, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
- ChildObesity180, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | | | - Esther Ty
- College of Arts & Sciences, William & Mary, Williamsburg, VA, USA
| | - Christopher L Pankey
- Department of Biomedical Sciences, West Virginia School of Osteopathic Medicine, Lewisburg, WV, USA
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127
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Pillon NJ, Loos RJF, Marshall SM, Zierath JR. Metabolic consequences of obesity and type 2 diabetes: Balancing genes and environment for personalized care. Cell 2021; 184:1530-1544. [PMID: 33675692 PMCID: PMC9191863 DOI: 10.1016/j.cell.2021.02.012] [Citation(s) in RCA: 100] [Impact Index Per Article: 33.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Revised: 11/25/2020] [Accepted: 02/03/2021] [Indexed: 02/07/2023]
Abstract
The prevalence of type 2 diabetes and obesity has risen dramatically for decades and is expected to rise further, secondary to the growing aging, sedentary population. The strain on global health care is projected to be colossal. This review explores the latest work and emerging ideas related to genetic and environmental factors influencing metabolism. Translational research and clinical applications, including the impact of the COVID-19 pandemic, are highlighted. Looking forward, strategies to personalize all aspects of prevention, management and care are necessary to improve health outcomes and reduce the impact of these metabolic diseases.
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Affiliation(s)
- Nicolas J Pillon
- Department of Physiology and Pharmacology, Karolinska Institute, Stockholm, Sweden
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York; The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Sally M Marshall
- Diabetes Research Group, Translational and Clinical Research Institute, Faculty of Clinical Medical Sciences, Newcastle University, 4(th) Floor William Leech Building, Framlington Place, Newcastle upon Tyne, NE2 4HH, UK
| | - Juleen R Zierath
- Department of Physiology and Pharmacology, Karolinska Institute, Stockholm, Sweden; Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden; Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark.
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128
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Differences and Correlation Analysis of Birth Weight and Overweight/Obesity in Shanghai Twin Cohort. Twin Res Hum Genet 2021; 24:29-36. [PMID: 33645497 DOI: 10.1017/thg.2021.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The objective of this study was to analyze differences in birth weight and overweight/obesity in a Shanghai twin cohort. We also wanted to study their association and explore possible risk factors for the discordance of overweight/obesity within twins. This was an internal case-control study designed for twins. The 2012 Shanghai Twin Registration System baseline survey data of a total of 3417 twin pairs were statistically analyzed using SPSS22 software. Results show that the body mass index (BMI) of the Shanghai twin population increased with age. Twins with a high birth weight had a higher BMI and a higher rate of overweight and obesity; 0- to 6-year-old twins, male twins and dizygotic (DZ) twins had higher rates of overweight/obesity than other groups. The greater the discordant birth weight rate of twins, the more obvious the difference in BMI (p < .05). There was a significant difference in overweight/obesity between twins with a relative difference of birth weight ≥15% in DZ twins (p < .05). DZ twins, male twins and 0- to 6-year-old twins were more likely to be discordant in overweight/obese than others. The discordant birth weight within twins was not a risk factor for discordant overweight/obesity. However, attention should be paid to childhood obesity, and appropriate interventions should be made at the appropriate time. Genetics may play an important role in the occurrence and development of overweight/obesity. In conclusion, discordant growth and development in the uterus early in life may not lead to discordant weight development in the future.
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129
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Davidson T, Vinneau-Palarino J, Goode JA, Boardman JD. Utilizing genome wide data to highlight the social behavioral pathways to health: The case of obesity and cardiovascular health among older adults. Soc Sci Med 2021; 273:113766. [PMID: 33621753 PMCID: PMC8005483 DOI: 10.1016/j.socscimed.2021.113766] [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] [Revised: 02/04/2021] [Accepted: 02/07/2021] [Indexed: 10/22/2022]
Abstract
We use genome-wide data from the 1992-2016 Health and Retirement Study (n = 12,090) to characterize obesity among older adults as genetically or socially oriented. To illustrate the significance of this approach for social epidemiological research, we deem those with the lowest genetic risk for obesity to be socially-behaviorally obese and obesity among those with the highest polygenic risk is characterized as genetically oriented. We then examine the association between obesity and four indicators of cardiovascular health (type-2 diabetes, hypertension, heart problems, and stroke) among those with low, average, and high genetic risk. Our results show that the association between obesity and cardiovascular health is significantly higher for those with the lowest genetic risk (e.g., social-behavioral obesity). We also demonstrate important sex differences such that this association is particularly strong for heart problems among men and hypertension and stroke among women. Our results further demonstrate the centrality of the social and behavioral determinants of health by utilizing detailed information across the human genome and add to both social and genetic epidemiology literatures.
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Affiliation(s)
- Trent Davidson
- Department of Sociology, University of Colorado Boulder, Boulder, CO, USA; Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO, USA; Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA.
| | - Justin Vinneau-Palarino
- Department of Sociology, University of Colorado Boulder, Boulder, CO, USA; Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO, USA; Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
| | - Joshua A Goode
- Department of Sociology, University of Colorado Boulder, Boulder, CO, USA; Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO, USA; Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
| | - Jason D Boardman
- Department of Sociology, University of Colorado Boulder, Boulder, CO, USA; Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO, USA; Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
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130
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Kemper KE, Yengo L, Zheng Z, Abdellaoui A, Keller MC, Goddard ME, Wray NR, Yang J, Visscher PM. Phenotypic covariance across the entire spectrum of relatedness for 86 billion pairs of individuals. Nat Commun 2021; 12:1050. [PMID: 33594080 PMCID: PMC7886899 DOI: 10.1038/s41467-021-21283-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 12/10/2020] [Indexed: 01/18/2023] Open
Abstract
Attributing the similarity between individuals to genetic and non-genetic factors is central to genetic analyses. In this paper we use the genomic relationship ([Formula: see text]) among 417,060 individuals to investigate the phenotypic covariance between pairs of individuals for 32 traits across the spectrum of relatedness, from unrelated pairs through to identical twins. We find linear relationships between phenotypic covariance and [Formula: see text] that agree with the SNP-based heritability ([Formula: see text]) in unrelated pairs ([Formula: see text]), and with pedigree-estimated heritability in close relatives ([Formula: see text]). The covariance increases faster than [Formula: see text] in distant relatives ([Formula: see text]), and we attribute this to imperfect linkage disequilibrium between causal variants and the common variants used to construct [Formula: see text]. We also examine the effect of assortative mating on heritability estimates from different experimental designs. We find that full-sib identity-by-descent regression estimates for height (0.66 s.e. 0.07) are consistent with estimates from close relatives (0.82 s.e. 0.04) after accounting for the effect of assortative mating.
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Affiliation(s)
- Kathryn E Kemper
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia.
| | - Loic Yengo
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Zhili Zheng
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Abdel Abdellaoui
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Matthew C Keller
- Department of Psychology & Neuroscience, University of Colorado at Boulder, Boulder, CO, USA.,Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
| | - Michael E Goddard
- Faculty of Veterinary and Agricultural Science, University of Melbourne, Parkville, VIC, Australia.,Biosciences Research Division, Department of Economic Development, Jobs, Transport and Resources, Bundoora, VIC, Australia
| | - Naomi R Wray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia.,Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
| | - Jian Yang
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Peter M Visscher
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia. .,Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia.
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131
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Validation of BMI genetic risk score and DNA methylation in a Korean population. Int J Legal Med 2021; 135:1201-1212. [PMID: 33594455 DOI: 10.1007/s00414-021-02517-y] [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] [Received: 08/26/2020] [Accepted: 01/27/2021] [Indexed: 12/19/2022]
Abstract
When DNA profiles obtained from biological evidence at a crime scene fail to match suspects or anyone in the database, forensic DNA phenotyping, which is the prediction of externally visible characteristics, can facilitate a traced search for an unknown suspect by limiting the search range. Therefore, age, trait, or lifestyle predictors, as well as the predictor for colorations, have been researched in the forensic field. In the present study, for the development of a prediction model for BMI or obesity, we investigated several previously reported BMI- or obesity-associated genetic and epigenetic markers that included four CpGs (cg06500161, cg00574958, cg12593793, and cg10505902 of the ABCG1, CPT1A, LMNA, and PDE4DIP genes, respectively), and eight SNPs (rs12463617, rs1558902, rs591166, rs11030104, rs11671664, rs6545814, rs16858082, and rs574367 near the TMEM18, FTO, MC4R, BDNF, GIPR/QPCTL, ADCY3/RBJ, GNPDA2, and SEC16B genes, respectively) in 700 Koreans within the BMI ranging from 16.1 to 40.6 (27.6 ± 4.5) kg/m2. Linear regression analysis showed that DNA methylation of the four CpG sites explained 10.9% total variance in BMI, and the model constructed using age information, genetic score from eight SNPs, and DNA methylation at four CpG sites could account for 17.4% of BMI variance. Using data mining techniques, i.e., decision tree (Entropy and Gini), random forest, and bagging, a total of eight models with BMI 31 or 32 as a cutoff value were also constructed based on the data obtained from 490 training samples with age and sex as a covariate. Among them, a random forest model with a cutoff value of 31 showed the best performance with 63.3% accuracy and the AUC value of 0.682 in 210 test set samples. In the present study, we could replicate the previous finding that DNA methylation contributes more to BMI than do genetic factors. In addition, although the accuracy for the prediction of BMI was not high, our study is meaningful in respect of the ability to use a small number of markers to achieve similar prediction accuracy to that obtained from a model composed of more than a thousand markers, which adds support to continued research to identify a small set of predictive markers for practical application in the forensic field.
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132
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Burgoine T, Monsivais P, Sharp SJ, Forouhi NG, Wareham NJ. Independent and combined associations between fast-food outlet exposure and genetic risk for obesity: a population-based, cross-sectional study in the UK. BMC Med 2021; 19:49. [PMID: 33588846 PMCID: PMC7885578 DOI: 10.1186/s12916-021-01902-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 01/05/2021] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Characteristics of the built environment, such as neighbourhood fast-food outlet exposure, are increasingly recognised as risk factors for unhealthy diet and obesity. Obesity also has a genetic component, with common genetic variants explaining a substantial proportion of population-level obesity susceptibility. However, it is not known whether and to what extent associations between fast-food outlet exposure and body weight are modified by genetic predisposition to obesity. METHODS We used data from the Fenland Study, a population-based sample of 12,435 UK adults (mean age 48.6 years). We derived a genetic risk score associated with BMI (BMI-GRS) from 96 BMI-associated single nucleotide polymorphisms. Neighbourhood fast-food exposure was defined as quartiles of counts of outlets around the home address. We used multivariable regression models to estimate the associations of each exposure, independently and in combination, with measured BMI, overweight and obesity, and investigated interactions. RESULTS We found independent associations between BMI-GRS and risk of overweight (RR = 1.34, 95% CI 1.23-1.47) and obesity (RR = 1.73, 95% CI 1.55-1.93), and between fast-food outlet exposure and risk of obesity (highest vs lowest quartile RR = 1.58, 95% CI 1.21-2.05). There was no evidence of an interaction of fast-food outlet exposure and genetic risk on BMI (P = 0.09), risk of overweight (P = 0.51), or risk of obesity (P = 0.27). The combination of higher BMI-GRS and highest fast-food outlet exposure was associated with 2.70 (95% CI 1.99-3.66) times greater risk of obesity. CONCLUSIONS Our study demonstrated independent associations of both genetic obesity risk and neighbourhood fast-food outlet exposure with adiposity. These important drivers of the obesity epidemic have to date been studied in isolation. Neighbourhood fast-food outlet exposure remains a potential target of policy intervention to prevent obesity and promote the public's health.
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Affiliation(s)
- Thomas Burgoine
- UKCRC Centre for Diet and Activity Research (CEDAR), MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
| | - Pablo Monsivais
- UKCRC Centre for Diet and Activity Research (CEDAR), MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
- Present address: Department of Nutrition and Exercise Physiology, Elson S. Floyd College of Medicine, Washington State University, Spokane, Washington, USA
| | - Stephen J Sharp
- UKCRC Centre for Diet and Activity Research (CEDAR), MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - Nita G Forouhi
- UKCRC Centre for Diet and Activity Research (CEDAR), MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - Nicholas J Wareham
- UKCRC Centre for Diet and Activity Research (CEDAR), MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
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133
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Li Z, Wang W, Tian X, Duan H, Xu C, Zhang D. Bivariate genome-wide association study (GWAS) of body mass index and blood pressure phenotypes in northern Chinese twins. PLoS One 2021; 16:e0246436. [PMID: 33539483 PMCID: PMC7861438 DOI: 10.1371/journal.pone.0246436] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 01/20/2021] [Indexed: 12/12/2022] Open
Abstract
Recently, new loci related to body mass index (BMI) or blood pressure (BP) have been identified respectively in genome-wide association studies (GWAS). However, limited studies focused on jointly associated genetic variance between systolic pressure (SBP), diastolic pressure (DBP) and BMI. Therefore, a bivariate twin study was performed to explore the genetic variants associated with BMI-SBP, BMI-DBP and SBP-DBP. A total of 380 twin pairs (137 dizygotic pairs and 243 monozygotic pairs) recruited from Qingdao Twin Registry system were used to access the genetic correlations (0.2108 for BMI-SBP, 0.2345 for BMI-DBP, and 0.6942 for SBP-DBP, respectively) by bivariate Cholesky decomposition model. Bivariate GWAS in 137 dizygotic pairs nominated 27 single identified 27 quantitative trait nucleotides (QTNs) for BMI and SBP, 27 QTNs for BMI and DBP, and 25 QTNs for SBP and DBP with the suggestive P-value threshold of 1×10−5. After imputation, we found eight SNPs, one for both BMI-SBP and SBP-DBP, and eight for SBP-DBP, exceed significant statistic level. Expression quantitative trait loci analysis identified rs4794029 as new significant eQTL in tissues related to BMI and SBP. Also, we found 6 new significant eQTLs (rs4400367, rs10113750, rs11776003, rs3739327, rs55978930, and rs4794029) in tissues were related to SBP and DBP. Gene-based analysis identified nominally associated genes (P < 0.05) with BMI-SBP, BMI-DBP, and SBP-DBP, respectively, such as PHOSPHO1, GNGT2, KEAP1, and S1PR5. In the pathway analysis, we found some pathways associated with BMI-SBP, BMI-DBP and SBP-DBP, such as prion diseases, IL5 pathway, cyclin E associated events during G1/S transition, TGF beta signaling pathway, G βγ signaling through PI3Kγ, prolactin receptor signaling etc. These findings may enrich the results of genetic variants related to BMI and BP traits, and provide some evidences to future study the pathogenesis of hypertension and obesity in the northern Chinese population.
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Affiliation(s)
- Zhaoying Li
- Department of Epidemiology and Health Statistics, the College of Public Health of Qingdao University, Qingdao, Shandong Province, People’s Republic of China
| | - Weijing Wang
- Department of Epidemiology and Health Statistics, the College of Public Health of Qingdao University, Qingdao, Shandong Province, People’s Republic of China
| | - Xiaocao Tian
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, Shandong Province, People’s Republic of China
- Qingdao Institute of Preventive Medicine, Qingdao, Shandong Province, People’s Republic of China
| | - Haiping Duan
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, Shandong Province, People’s Republic of China
- Qingdao Institute of Preventive Medicine, Qingdao, Shandong Province, People’s Republic of China
| | - Chunsheng Xu
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, Shandong Province, People’s Republic of China
- Qingdao Institute of Preventive Medicine, Qingdao, Shandong Province, People’s Republic of China
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, the College of Public Health of Qingdao University, Qingdao, Shandong Province, People’s Republic of China
- * E-mail:
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134
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Warner ET, Jiang L, Adjei DN, Turman C, Gordon W, Wang L, Tamimi R, Kraft P, Lindström S. A Genome-Wide Association Study of Childhood Body Fatness. Obesity (Silver Spring) 2021; 29:446-453. [PMID: 33491310 PMCID: PMC7842657 DOI: 10.1002/oby.23070] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Revised: 10/18/2020] [Accepted: 10/20/2020] [Indexed: 11/05/2022]
Abstract
OBJECTIVE This study aimed to uncover genetic contributors to adiposity in early life. METHODS A genome-wide association study of childhood body fatness in 34,401 individuals within the Nurses' Health Studies and the Health Professionals Follow-up Study was conducted. Data were imputed to the 1000 Genomes Phase 3 version 5 reference panel. RESULTS A total of 1,354 single-nucleotide polymorphisms (P < 10-4 ) were selected for replication in a previously published genome-wide association study of childhood BMI. Nineteen significant genome-wide (P < 5 × 10-8 ) regions were observed, fourteen of which were previously associated with childhood obesity and five were novel: BNDF (P = 7.58 × 10-13 ), PRKD1 (P = 1.43 × 10-10 ), 20p13 (P = 2.05 × 10-10 ), FHIT (P = 1.77 × 10-8 ), and LOC101927575 (P = 3.22 × 10-8 ). The BNDF, FHIT, and PRKD1 regions were previously associated with adult BMI. LOC101927575 and 20p13 regions have not previously been associated with adiposity phenotypes. In a transcriptome-wide analysis, associations for POMC at 2p23.3 (P = 3.36 × 10-6 ) and with TMEM18 at 2p25.3 (P = 3.53 × 10-7 ) were observed. Childhood body fatness was genetically correlated with hip (rg = 0.42, P = 4.44 × 10-16 ) and waist circumference (rg = 0.39, P = 5.56 × 10-16 ), as well as age at menarche (rg = -0.37, P = 7.96 × 10-19 ). CONCLUSIONS Additional loci that contribute to childhood adiposity were identified, further explicating its genetic architecture.
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Affiliation(s)
- Erica T. Warner
- Clinical Translational Epidemiology Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Lai Jiang
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA
| | - David Nana Adjei
- Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, MA
| | - Constance Turman
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA
| | - William Gordon
- Department of Epidemiology, University of Washington, Seattle, WA
| | - Lu Wang
- Department of Environmental & Occupational Health Sciences, University of Washington, Seattle, WA
| | - Rulla Tamimi
- Department of Epidemiology, Harvard TH 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
| | - Peter Kraft
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA
- Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, MA
| | - Sara Lindström
- Department of Epidemiology, University of Washington, Seattle, WA
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA
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135
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Cawley J, Biener A, Meyerhoefer C, Ding Y, Zvenyach T, Smolarz BG, Ramasamy A. Direct medical costs of obesity in the United States and the most populous states. J Manag Care Spec Pharm 2021; 27:354-366. [PMID: 33470881 PMCID: PMC10394178 DOI: 10.18553/jmcp.2021.20410] [Citation(s) in RCA: 83] [Impact Index Per Article: 27.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
BACKGROUND: After a dramatic increase in prevalence over several decades, obesity has become a major public health crisis in the United States. Research to date has consistently demonstrated a correlation between obesity and higher medical costs for a variety of U.S. subpopulations and specific categories of care. However, by examining associations rather than causal effects, previous studies likely underestimated the effect of obesity on medical expenditures. OBJECTIVE: To estimate the causal effect of obesity on direct medical care costs at the national and state levels. METHODS: This study is a pooled cross-sectional analysis of retrospective data from the 2001-2016 Medical Expenditure Panel Surveys. Adults aged 20-65 years with a biological child living in the household were included in the study sample. Primary outcomes were individual-level medical expenditures due to obesity, overall, as well as separately by type of payer and category of medical care. Results were reported at the national level and separately for the 20 most populous states. The expenditure estimates were obtained from 2-part models of instrumental variables in which the respondent's body mass index (BMI) was instrumented using the BMI of their biological child. RESULTS: Adults with obesity in the United States compared with those with normal weight experienced higher annual medical care costs by $2,505 or 100%, with costs increasing significantly with class of obesity, from 68.4% for class 1 to 233.6% for class 3. The effects of obesity raised costs in every category of care: inpatient, outpatient, and prescription drugs. Increases in medical expenditures due to obesity were higher for adults covered by public health insurance programs ($2,868) than for those having private health insurance ($2,058). In 2016, the aggregate medical cost due to obesity among adults in the United States was $260.6 billion. The increase in individual-level expenditures due to obesity varied considerably by state (e.g., 24.0% in Florida, 66.4% in New York, and 104.9% in Texas). CONCLUSIONS: The 2-part models of instrumental variables, which estimate the causal effects of obesity on direct medical costs, showed that the effect of obesity is greater than suggested by previous studies, which estimated only correlations. Much of the aggregate national cost of obesity-$260.6 billion-represents external costs, providing a rationale for interventions to prevent and reduce obesity. DISCLOSURES: Novo Nordisk financed the development of the study design, analysis, and interpretation of data, as well as writing support of the manuscript. Cawley, Biener, and Meyerhoefer received financial support from Novo Nordisk to conduct the research study on which this manuscript is based. Smolarz and Ramasamy are employees of Novo Nordisk. Ding and Zvenyach have no conflicts to declare. Our research has been presented as a poster at the 2020 Academy Health Annual Research Meeting (Virtual), July 28-August 6, 2020.
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Affiliation(s)
- John Cawley
- Department of Policy Analysis and Management and Department of Economics, Cornell University, Ithaca, NY
| | - Adam Biener
- Department of Economics, Lafayette College, Easton, PA
| | | | | | - Tracy Zvenyach
- Independent Advisor, Healthcare and Obesity Public Policy, Madison, WI
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136
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Brunner EJ, Maruyama K, Shipley M, Cable N, Iso H, Hiyoshi A, Stallone D, Kumari M, Tabak A, Singh-Manoux A, Wilson J, Langenberg C, Wareham N, Boniface D, Hingorani A, Kivimäki M, Llewellyn C. Appetite disinhibition rather than hunger explains genetic effects on adult BMI trajectory. Int J Obes (Lond) 2021; 45:758-765. [PMID: 33446837 PMCID: PMC8005371 DOI: 10.1038/s41366-020-00735-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 10/19/2020] [Accepted: 12/16/2020] [Indexed: 11/17/2022]
Abstract
Background/objectives The mediating role of eating behaviors in genetic susceptibility to weight gain during mid-adult life is not fully understood. This longitudinal study aims to help us understand contributions of genetic susceptibility and appetite to weight gain. Subjects/methods We followed the body-mass index (BMI) trajectories of 2464 adults from 45 to 65 years of age by measuring weight and height on four occasions at 5-year intervals. Genetic risk of obesity (gene risk score: GRS) was ascertained, comprising 92 BMI-associated single-nucleotide polymorphisms and split at a median (=high and low risk). At the baseline, the Eating Inventory was used to assess appetite-related traits of ‘disinhibition’, indicative of opportunistic eating or overeating and ‘hunger’ which is susceptibility to/ability to cope with the sensation of hunger. Roles of the GRS and two appetite-related scores for BMI trajectories were examined using a mixed model adjusted for the cohort effect and sex. Results Disinhibition was associated with higher BMI (β = 2.96; 95% CI: 2.66–3.25 kg/m2), and accounted for 34% of the genetically-linked BMI difference at age 45. Hunger was also associated with higher BMI (β = 1.20; 0.82–1.59 kg/m2) during mid-life and slightly steeper weight gain, but did not attenuate the effect of disinhibition. Conclusions Appetite disinhibition is most likely to be a defining characteristic of genetic susceptibility to obesity. High levels of appetite disinhibition, rather than hunger, may underlie genetic vulnerability to obesogenic environments in two-thirds of the population of European ancestry.
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Affiliation(s)
- Eric J Brunner
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Koutatsu Maruyama
- Institute of Epidemiology and Health Care, University College London, London, UK. .,Public Health, Department of Social Medicine, Osaka University Graduate School of Medicine, Suita, Japan. .,Laboratory of Community Health and Nutrition, Department of Bioscience, Graduate School of Agriculture, Ehime University, Matsuyama, Japan.
| | - Martin Shipley
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Noriko Cable
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Hiroyasu Iso
- Public Health, Department of Social Medicine, Osaka University Graduate School of Medicine, Suita, Japan
| | - Ayako Hiyoshi
- Clinical Epidemiology and Biostatistics, School of Medical Sciences, Örebro University, Örebro, Sweden
| | | | - Meena Kumari
- Institute of Epidemiology and Health Care, University College London, London, UK.,Institute for Social and Economic Research, University of Essex, Colchester, UK
| | - Adam Tabak
- Institute of Epidemiology and Health Care, University College London, London, UK.,Department of Internal Medicine and Ocology, Faculty of Medicine, Semmelweis University, Budapest, Hungary.,Department of Public Health, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Archana Singh-Manoux
- Institute of Epidemiology and Health Care, University College London, London, UK.,Epidemiology of Ageing and Neurodegenerative diseases, Université de Paris, Paris, France
| | - John Wilson
- North Devon Medical Education Centre, North Devon District Hospital, Barnstaple, UK
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Nick Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - David Boniface
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Aroon Hingorani
- Institute of Cardiovascular Science, University College London, London, UK
| | - Mika Kivimäki
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Clare Llewellyn
- Institute of Epidemiology and Health Care, University College London, London, UK
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137
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Chatterjee S, Ouidir M, Tekola-Ayele F. Pleiotropic genetic influence on birth weight and childhood obesity. Sci Rep 2021; 11:48. [PMID: 33420178 PMCID: PMC7794220 DOI: 10.1038/s41598-020-80084-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 12/09/2020] [Indexed: 01/09/2023] Open
Abstract
Childhood obesity is a global public health problem. Understanding the molecular mechanisms that underlie early origins of childhood obesity can facilitate interventions. Consistent phenotypic and genetic correlations have been found between childhood obesity traits and birth weight (a proxy for in-utero growth), suggesting shared genetic influences (pleiotropy). We aimed to (1) investigate whether there is significant shared genetic influence between birth weight and childhood obesity traits, and (2) to identify genetic loci with shared effects. Using a statistical approach that integrates summary statistics and functional annotations for paired traits, we found strong evidence of pleiotropy (P < 3.53 × 10–127) and enrichment of functional annotations (P < 1.62 × 10–39) between birth weight and childhood body mass index (BMI)/obesity. The pleiotropic loci were enriched for regulatory features in skeletal muscle, adipose and brain tissues and in cell lines derived from blood lymphocytes. At 5% false discovery rate, 6 loci were associated with birth weight and childhood BMI and 13 loci were associated with birth weight and childhood obesity. Out of these 19 loci, one locus (EBF1) was novel to childhood obesity and one locus (LMBR1L) was novel to both birth weight and childhood BMI/obesity. These findings give evidence of substantial shared genetic effects in the regulation of both fetal growth and childhood obesity.
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Affiliation(s)
- Suvo Chatterjee
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, 6710B Rockledge Drive, Room 3204, Bethesda, 20892-7004, USA
| | - Marion Ouidir
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, 6710B Rockledge Drive, Room 3204, Bethesda, 20892-7004, USA
| | - 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, 6710B Rockledge Drive, Room 3204, Bethesda, 20892-7004, USA.
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138
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Silventoinen K, Konttinen H. Obesity and eating behavior from the perspective of twin and genetic research. Neurosci Biobehav Rev 2021; 109:150-165. [PMID: 31959301 DOI: 10.1016/j.neubiorev.2019.12.012] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 11/11/2019] [Accepted: 12/09/2019] [Indexed: 12/21/2022]
Abstract
Obesity has dramatically increased during the last decades and is currently one of the most serious global health problems. We present a hypothesis that obesity is a neuro-behavioral disease having a strong genetic background mediated largely by eating behavior and is sensitive to the macro-environment; we study this hypothesis from the perspective of genetic research. Genetic family and genome-wide-association studies have shown well that body mass index (BMI, kg/m2) is a highly heritable and polygenic trait. New genetic variation of BMI emerges after early childhood. Candidate genes of BMI notably express in brain tissue, supporting that this new variation is related to behavior. Obesogenic environments at both childhood family and societal levels reinforce the genetic susceptibility to obesity. Genetic factors have a clear influence on macro-nutrient intake and appetite-related eating behavior traits. Results on the gene-by-diet interactions in obesity are mixed, but emerging evidence suggests that eating behavior traits partly mediate the effect of genes on BMI. However, more rigorous prospective study designs controlling for measurement bias are still needed.
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Affiliation(s)
- Karri Silventoinen
- Department of Social Research, University of Helsinki, Helsinki, Finland; Department of Public Health, University of Helsinki, Helsinki, Finland.
| | - Hanna Konttinen
- Department of Social Research, University of Helsinki, Helsinki, Finland
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139
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Direct and Indirect Effects of Maternal, Paternal, and Offspring Genotypes: Trio-GCTA. Behav Genet 2021; 51:154-161. [PMID: 33387132 DOI: 10.1007/s10519-020-10036-6] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 12/07/2020] [Indexed: 10/22/2022]
Abstract
Indirect genetic effects from relatives may result in misleading quantifications of heritability, but can also be of interest in their own right. In this paper we propose Trio-GCTA, a model for separating direct and indirect genetic effects when genome-wide single nucleotide polymorphism data have been collected from parent-offspring trios. The model is applicable to phenotypes obtained from any of the family members. We discuss appropriate parameter interpretations and apply the method to three exemplar phenotypes: offspring birth weight, maternal relationship satisfaction, and paternal body-mass index, using real data from the Norwegian Mother, Father and Child Cohort Study (MoBa).
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140
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Odintsova VV, Rebattu V, Hagenbeek FA, Pool R, Beck JJ, Ehli EA, van Beijsterveldt CEM, Ligthart L, Willemsen G, de Geus EJC, Hottenga JJ, Boomsma DI, van Dongen J. Predicting Complex Traits and Exposures From Polygenic Scores and Blood and Buccal DNA Methylation Profiles. Front Psychiatry 2021; 12:688464. [PMID: 34393852 PMCID: PMC8357987 DOI: 10.3389/fpsyt.2021.688464] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 06/15/2021] [Indexed: 11/13/2022] Open
Abstract
We examined the performance of methylation scores (MS) and polygenic scores (PGS) for birth weight, BMI, prenatal maternal smoking exposure, and smoking status to assess the extent to which MS could predict these traits and exposures over and above the PGS in a multi-omics prediction model. MS may be seen as the epigenetic equivalent of PGS, but because of their dynamic nature and sensitivity of non-genetic exposures may add to complex trait prediction independently of PGS. MS and PGS were calculated based on genotype data and DNA-methylation data in blood samples from adults (Illumina 450 K; N = 2,431; mean age 35.6) and in buccal samples from children (Illumina EPIC; N = 1,128; mean age 9.6) from the Netherlands Twin Register. Weights to construct the scores were obtained from results of large epigenome-wide association studies (EWASs) based on whole blood or cord blood methylation data and genome-wide association studies (GWASs). In adults, MSs in blood predicted independently from PGSs, and outperformed PGSs for BMI, prenatal maternal smoking, and smoking status, but not for birth weight. The largest amount of variance explained by the multi-omics prediction model was for current vs. never smoking (54.6%) of which 54.4% was captured by the MS. The two predictors captured 16% of former vs. never smoking initiation variance (MS:15.5%, PGS: 0.5%), 17.7% of prenatal maternal smoking variance (MS:16.9%, PGS: 0.8%), 11.9% of BMI variance (MS: 6.4%, PGS 5.5%), and 1.9% of birth weight variance (MS: 0.4%, PGS: 1.5%). In children, MSs in buccal samples did not show independent predictive value. The largest amount of variance explained by the two predictors was for prenatal maternal smoking (2.6%), where the MSs contributed 1.5%. These results demonstrate that blood DNA MS in adults explain substantial variance in current smoking, large variance in former smoking, prenatal smoking, and BMI, but not in birth weight. Buccal cell DNA methylation scores have lower predictive value, which could be due to different tissues in the EWAS discovery studies and target sample, as well as to different ages. This study illustrates the value of combining polygenic scores with information from methylation data for complex traits and exposure prediction.
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Affiliation(s)
- Veronika V Odintsova
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Valerie Rebattu
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Fiona A Hagenbeek
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - René Pool
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Jeffrey J Beck
- Avera Institute for Human Genetics, Sioux Falls, SD, United States
| | - Erik A Ehli
- Avera Institute for Human Genetics, Sioux Falls, SD, United States
| | - Catharina E M van Beijsterveldt
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Lannie Ligthart
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Jenny van Dongen
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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141
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Mao K, Zhang M, Cao J, Zhao X, Gao L, Fu L, Cheng H, Yan C, Xu X, Shi X, Jiang Z, Wang B, Zhang YB, Mi J. Coding Variants are Relevant to the Expression of Obesity-Related Genes for Pediatric Adiposity. Obesity (Silver Spring) 2021; 29:194-203. [PMID: 34494379 DOI: 10.1002/oby.23046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 09/09/2020] [Accepted: 09/09/2020] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Heredity has a remarkable effect on obesity in an obesogenic environment. Despite the numerous genetic variants that contribute to obesity-related traits, none has been identified in Chinese children. This study aimed to identify novel variants associated with childhood obesity in China. METHODS Promising single-nucleotide variants were obtained using whole-exome sequencing from 76 children who had obesity and 74 children with normal weight, and their associations with obesity-related traits in an additional 6,334-child cohort were investigated. The effects of the genome-wide significant (P < 5E-8) variants on the expression of the implicated genes in blood and adipose tissue were then depicted using transcriptome sequencing. RESULTS Two coding variants associated with obesity with genome-wide significance were identified: rs1059491 (P = 2.57E-28) in SULT1A2 and rs189326455 (P = 8.98E-12) in MAP3K21. In addition, rs1059491 was also significantly associated with several obesity traits. Transcriptome sequencing demonstrated that rs1059491 and rs189326455 were expression quantitative trait loci relevant to the expression levels of several obesity-related genes, such as SULT1A2, ATXN2L, TUFM, and MAP3K21. CONCLUSIONS This work identified two coding variants that were significantly associated with pediatric adiposity and were expression quantitative trait loci for obesity-related genes. This study provides new insights into the pathophysiology of Chinese childhood obesity.
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Affiliation(s)
- Ke Mao
- Interdisciplinary Innovation Institute of Medicine and Engineering, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Meixian Zhang
- Department of Epidemiology, Capital Institute of Pediatrics, Beijing, China
| | - Jinshuai Cao
- Interdisciplinary Innovation Institute of Medicine and Engineering, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Xiaoyuan Zhao
- Department of Epidemiology, Capital Institute of Pediatrics, Beijing, China
| | - Liwang Gao
- Department of Epidemiology, Capital Institute of Pediatrics, Beijing, China
| | - Liwan Fu
- National Center for Children's Health, Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - Hong Cheng
- Department of Epidemiology, Capital Institute of Pediatrics, Beijing, China
| | - Chun Yan
- Interdisciplinary Innovation Institute of Medicine and Engineering, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Xiaopeng Xu
- Interdisciplinary Innovation Institute of Medicine and Engineering, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Xiaofeng Shi
- Interdisciplinary Innovation Institute of Medicine and Engineering, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Zhuoyuan Jiang
- Interdisciplinary Innovation Institute of Medicine and Engineering, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Bingqing Wang
- Plastic Surgery Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Yong-Biao Zhang
- Interdisciplinary Innovation Institute of Medicine and Engineering, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Jie Mi
- National Center for Children's Health, Beijing Children's Hospital, Capital Medical University, Beijing, China
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142
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do Carmo AS, Mendes LL, Pessoa MC, Meireles AL, da Silva AAM, Dos Santos LC. Family characteristics, perceived environment for physical activity, and childhood obesity: An approach with structural equation models. Am J Hum Biol 2020; 33:e23560. [PMID: 33377256 DOI: 10.1002/ajhb.23560] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 12/08/2020] [Accepted: 12/16/2020] [Indexed: 01/11/2023] Open
Abstract
OBJECTIVES To evaluate the direct and indirect effects of family characteristics and the perceived neighborhood environment on obesity risks among schoolchildren. METHODS Through phone contact with the child's mothers/guardians, the perceptions about the aspects of the neighborhood that could limit or promote health. Physical activity, socioeconomic data, self-reported weight and height, and ultra-processed consumption of the respondents were evaluated, in addition to the screen time of both mothers and children. A hybrid model of structural equations was used to test the direct and indirect effects of family and environmental variables on childhood obesity. SETTING Belo Horizonte, Minas Gerais, Brazil. SUBJECTS A total of 322 children from 9 to 10 years old from municipal schools and their respective mothers/guardians. RESULTS Childhood obesity was positively associated with obesity among mothers/guardians and with the latent variable "socioeconomic status (SES)." It was observed that the child's guardians positively influenced childhood obesity through their own habits, such as screen time and consumption of ultra-processed products, with obesity of mothers/guardians as mediators of both associations. There were no direct and indirect effects of the latent variables of the perceived environment in childhood obesity. CONCLUSION Family characteristics are important determinants of childhood obesity and should be considered when designing prevention strategies. Parental perceptions of neighborhood characteristics did not have an influence on childhood obesity.
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Affiliation(s)
- Ariene Silva do Carmo
- Programa de Pós-Graduação em Ciências da Saúde - Saúde da Criança e do Adolescente, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Larissa Loures Mendes
- Departamento de Nutrição, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Milene Cristine Pessoa
- Departamento de Nutrição, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Adriana Lucia Meireles
- Departamento de Nutrição Clínica e Social, Universidade Federal de Ouro Preto, Ouro Preto, Minas Gerais, Brazil
| | | | - Luana Caroline Dos Santos
- Departamento de Nutrição, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
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143
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Calvo-Serra B, Maitre L, Lau CHE, Siskos AP, Gützkow KB, Andrušaitytė S, Casas M, Cadiou S, Chatzi L, González JR, Grazuleviciene R, McEachan R, Slama R, Vafeiadi M, Wright J, Coen M, Vrijheid M, Keun HC, Escaramís G, Bustamante M. Urinary metabolite quantitative trait loci in children and their interaction with dietary factors. Hum Mol Genet 2020; 29:3830-3844. [PMID: 33283231 DOI: 10.1093/hmg/ddaa257] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 11/26/2020] [Accepted: 11/30/2020] [Indexed: 11/14/2022] Open
Abstract
Human metabolism is influenced by genetic and environmental factors. Previous studies have identified over 23 loci associated with more than 26 urine metabolites levels in adults, which are known as urinary metabolite quantitative trait loci (metabQTLs). The aim of the present study is the identification for the first time of urinary metabQTLs in children and their interaction with dietary patterns. Association between genome-wide genotyping data and 44 urine metabolite levels measured by proton nuclear magnetic resonance spectroscopy was tested in 996 children from the Human Early Life Exposome project. Twelve statistically significant urine metabQTLs were identified, involving 11 unique loci and 10 different metabolites. Comparison with previous findings in adults revealed that six metabQTLs were already known, and one had been described in serum and three were involved the same locus as other reported metabQTLs but had different urinary metabolites. The remaining two metabQTLs represent novel urine metabolite-locus associations, which are reported for the first time in this study [single nucleotide polymorphism (SNP) rs12575496 for taurine, and the missense SNP rs2274870 for 3-hydroxyisobutyrate]. Moreover, it was found that urinary taurine levels were affected by the combined action of genetic variation and dietary patterns of meat intake as well as by the interaction of this SNP with beverage intake dietary patterns. Overall, we identified 12 urinary metabQTLs in children, including two novel associations. While a substantial part of the identified loci affected urinary metabolite levels both in children and in adults, the metabQTL for taurine seemed to be specific to children and interacted with dietary patterns.
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Affiliation(s)
- Beatriz Calvo-Serra
- ISGlobal, Barcelona 08003, Spain.,Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Madrid 28029, Spain
| | - Léa Maitre
- ISGlobal, Barcelona 08003, Spain.,Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Madrid 28029, Spain
| | - Chung-Ho E Lau
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, UK
| | - Alexandros P Siskos
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, UK.,Cancer Metabolism and Systems Toxicology Group, Division of Cancer, Department of Surgery and Cancer, Imperial College London, Hammersmith Hospital Campus, London W12 0NN, UK
| | - Kristine B Gützkow
- Department of Environmental Health, Norwegian Institute of Public Health, Oslo 0213, Norway
| | - Sandra Andrušaitytė
- Department of Environmental Science, Vytautas Magnus University, Kaunas 44248, Lithuania
| | - Maribel Casas
- ISGlobal, Barcelona 08003, Spain.,Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Madrid 28029, Spain
| | - Solène Cadiou
- Team of Environmental Epidemiology, IAB, Institute for Advanced Biosciences, Inserm, CNRS, CHU-Grenoble-Alpes, University Grenoble-Alpes, Grenoble 38000, France
| | - Leda Chatzi
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles 90033, USA
| | - Juan R González
- ISGlobal, Barcelona 08003, Spain.,Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Madrid 28029, Spain
| | - Regina Grazuleviciene
- Department of Environmental Science, Vytautas Magnus University, Kaunas 44248, Lithuania
| | | | - Rémy Slama
- Team of Environmental Epidemiology, IAB, Institute for Advanced Biosciences, Inserm, CNRS, CHU-Grenoble-Alpes, University Grenoble-Alpes, Grenoble 38000, France
| | - Marina Vafeiadi
- Department of Social Medicine, Faculty of Medicine, University of Crete, Heraklion 71003, Greece
| | - John Wright
- Bradford Institute for Health Research, Bradford BD9 6RJ, UK
| | - Murieann Coen
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, UK.,Oncology Safety, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge CB2 0RE, UK
| | - Martine Vrijheid
- ISGlobal, Barcelona 08003, Spain.,Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Madrid 28029, Spain
| | - Hector C Keun
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, UK.,Cancer Metabolism and Systems Toxicology Group, Division of Cancer, Department of Surgery and Cancer, Imperial College London, Hammersmith Hospital Campus, London W12 0NN, UK
| | - Geòrgia Escaramís
- Departament de Biomedicina, Institut de Neurociències, Universitat de Barcelona (UB), Barcelona 08036, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Madrid 28029, Spain
| | - Mariona Bustamante
- ISGlobal, Barcelona 08003, Spain.,Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Madrid 28029, Spain
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Abstract
PURPOSE OF REVIEW Eating behaviours are hypothesised to be the behavioural expression of genetic risk of obesity. In this review, we summarise findings from behavioural genetic research on the association between genetic risk for obesity and validated psychometrics measures of eating behaviours in children and adults (published in the past 10 years). RECENT FINDINGS Twin studies have produced some evidence for a shared genetic aetiology underlying body mass index and eating behaviours. Studies using measured genetic susceptibility to obesity have suggested that increased genetic liability for obesity is associated with variation in obesogenic eating behaviours such as emotional and uncontrolled eating. More research on this topic is needed. Especially longitudinal studies using genetically sensitive designs to investigate the direction of genetic pathways between genetic liability of eating behaviours to weight and vice versa, as well as the potential subsequent link to eating disorders.
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Affiliation(s)
- Moritz Herle
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, Kings College London, 16 De Crespigny Park, London, SE5 8AF, UK.
| | - Andrea D Smith
- Research Department of Behavioural Science and Health, University College London, London, UK
| | | | - Clare Llewellyn
- Research Department of Behavioural Science and Health, University College London, London, UK
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145
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Hanson RL, Van Hout CV, Hsueh WC, Shuldiner AR, Kobes S, Sinha M, Baier LJ, Knowler WC. Assessment of the potential role of natural selection in type 2 diabetes and related traits across human continental ancestry groups: comparison of phenotypic with genotypic divergence. Diabetologia 2020; 63:2616-2627. [PMID: 32886191 PMCID: PMC7642101 DOI: 10.1007/s00125-020-05272-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Accepted: 07/22/2020] [Indexed: 11/30/2022]
Abstract
AIMS/HYPOTHESIS Prevalence of type 2 diabetes differs among human ancestry groups, and many hypotheses invoke differential natural selection to account for these differences. We sought to assess the potential role of differential natural selection across major continental ancestry groups for diabetes and related traits, by comparison of genetic and phenotypic differences. METHODS This was a cross-sectional comparison among 734 individuals from an urban sample (none of whom was more closely related to another than third-degree relatives), including 83 African Americans, 523 American Indians and 128 European Americans. Participants were not recruited based on diabetes status or other traits. BMI was calculated, and diabetes was diagnosed by a 75 g oral glucose tolerance test. In those with normal glucose tolerance (n = 434), fasting insulin and 30 min post-load insulin, adjusted for 30 min glucose, were taken as measures of insulin resistance and secretion, respectively. Whole exome sequencing was performed, resulting in 97,388 common (minor allele frequency ≥ 5%) variants; the coancestry coefficient (FST) was calculated across all markers as a measure of genetic divergence among ancestry groups. The phenotypic divergence index (PST) was also calculated from the phenotypic differences and heritability (which was estimated from genetic relatedness calculated empirically across all markers in 761 American Indian participants prior to the exclusion of close relatives). Under evolutionary neutrality, the expectation is PST = FST, while for traits under differential selection PST is expected to be significantly greater than FST. A bootstrap procedure was used to test the hypothesis PST = FST. RESULTS: With adjustment for age and sex, prevalence of type 2 diabetes was 34.0% in American Indians, 12.4% in African Americans and 10.4% in European Americans (p = 2.9 × 10-10 for difference among groups). Mean BMI was 36.3, 33.4 and 33.0 kg/m2, respectively (p = 1.9 × 10-7). Mean fasting insulin was 63.8, 48.4 and 45.2 pmol/l (p = 9.2 × 10-5), while mean 30 min insulin was 559.8, 553.5 and 358.8 pmol/l, respectively (p = 5.7 × 10-8). FST across all markers was 0.130, while PST for liability to diabetes, adjusted for age and sex, was 0.149 (p = 0.35 for difference with FST). PST was 0.094 for BMI (p = 0.54), 0.095 for fasting insulin (p = 0.54) and 0.216 (p = 0.18) for 30 min insulin. For type 2 diabetes and BMI, the maximum divergence between populations was observed between American Indians and European Americans (PST-MAX = 0.22, p = 0.37, and PST-MAX = 0.14, p = 0.61), which suggests that a relatively modest 22% or 14% of the genetic variance, respectively, can potentially be explained by differential selection (assuming the absence of neutral drift). CONCLUSIONS/INTERPRETATION These analyses suggest that while type 2 diabetes and related traits differ significantly among continental ancestry groups, the differences are consistent with neutral expectations based on heritability and genetic distances. While these analyses do not exclude a modest role for natural selection, they do not support the hypothesis that differential natural selection is necessary to explain the phenotypic differences among these ancestry groups. Graphical abstract.
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Affiliation(s)
- Robert L Hanson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA.
| | | | - Wen-Chi Hsueh
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | | | - Sayuko Kobes
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Madhumita Sinha
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Leslie J Baier
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | | | - William C Knowler
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
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146
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Maugeri A. The Effects of Dietary Interventions on DNA Methylation: Implications for Obesity Management. Int J Mol Sci 2020; 21:ijms21228670. [PMID: 33212948 PMCID: PMC7698434 DOI: 10.3390/ijms21228670] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 10/28/2020] [Accepted: 11/16/2020] [Indexed: 12/13/2022] Open
Abstract
Previous evidence from in vivo and observational research suggested how dietary factors might affect DNA methylation signatures involved in obesity risk. However, findings from experimental studies are still scarce and, if present, not so clear. The current review summarizes studies investigating the effect of dietary interventions on DNA methylation in the general population and especially in people at risk for or with obesity. Overall, these studies suggest how dietary interventions may induce DNA methylation changes, which in turn are likely related to the risk of obesity and to different response to weight loss programs. These findings might explain the high interindividual variation in weight loss after a dietary intervention, with some people losing a lot of weight while others much less so. However, the interactions between genetic, epigenetic, environmental and lifestyle factors make the whole framework even more complex and further studies are needed to support the hypothesis of personalized interventions against obesity.
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Affiliation(s)
- Andrea Maugeri
- Department of Medical and Surgical Sciences and Advanced Technologies "GF Ingrassia", University of Catania, 95123 Catania, Italy
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Best JR, Dao E, Churchill R, Cosco TD. Associations Between Physical Fitness and Brain Structure in Young Adulthood. Front Psychol 2020; 11:608049. [PMID: 33281692 PMCID: PMC7705380 DOI: 10.3389/fpsyg.2020.608049] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Accepted: 10/30/2020] [Indexed: 11/18/2022] Open
Abstract
A comprehensive analysis of associations between physical fitness and brain structure in young adulthood is lacking, and further, it is unclear the degree to which associations between physical fitness and brain health can be attributed to a common genetic pathway or to environmental factors that jointly influences physical fitness and brain health. This study examined genotype-confirmed monozygotic and dizygotic twins, along with non-twin full-siblings to estimate the contribution of genetic and environmental factors to variation within, and covariation between, physical fitness and brain structure. Participants were 1,065 young adults between the ages of 22 and 36 from open-access Young Adult Human Connectome Project (YA-HCP). Physical fitness was assessed by submaximal endurance (2-min walk test), grip strength, and body mass index. Brain structure was assessed using magnetic resonance imaging on a Siemens 3T customized 'Connectome Skyra' at Washington University in St. Louis, using a 32-channel Siemens head coil. Acquired T1-weighted images provided measures of cortical surface area and thickness, and subcortical volume following processing by the YA-HCP structural FreeSurfer pipeline. Diffusion weighted imaging was acquired to assess white matter tract integrity, as measured by fractional anisotropy, following processing by the YA-HCP diffusion pipeline and tensor fit. Following correction for multiple testing, body mass index was negatively associated with fractional anisotropy in various white matter regions of interest (all | z| statistics > 3.9) and positively associated with cortical thickness within the right superior parietal lobe (z statistic = 4.6). Performance-based measures of fitness (i.e., endurance and grip strength) were not associated with any structural neuroimaging markers. Behavioral genetic analysis suggested that heritability of white matter integrity varied by region, but consistently explained >50% of the phenotypic variation. Heritability of right superior parietal thickness was large (∼75% variation). Heritability of body mass index was also fairly large (∼60% variation). Generally, 1 2 to 2 3 of the correlation between brain structure and body mass index could be attributed to heritability effects. Overall, this study suggests that greater body mass index is associated with lower white matter integrity, which may be due to common genetic effects that impact body composition and white matter integrity.
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Affiliation(s)
- John R. Best
- Gerontology Research Centre, Simon Fraser University, Vancouver, BC, Canada
- Department of Gerontology, Simon Fraser University, Vancouver, BC, Canada
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Elizabeth Dao
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Ryan Churchill
- Department of Gerontology, Simon Fraser University, Vancouver, BC, Canada
| | - Theodore D. Cosco
- Gerontology Research Centre, Simon Fraser University, Vancouver, BC, Canada
- Department of Gerontology, Simon Fraser University, Vancouver, BC, Canada
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148
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Abstract
Obesity is associated with an increased risk of various diseases and mortality. Although nearly 50 % of adults have been reported trying to lose weight, the prevalence of obesity has increased. One factor that hinders weight loss-induced decrease in obesity prevalence is weight regain. Although behavioural, psychological and physiological factors associated with weight regain have been reviewed, the information regarding the relationship between weight regain and genetics has not been previously summarised. In this paper, we comprehensively review the association between genetic polymorphisms and weight regain in adults and children with obesity after weight loss. Based on this information, identification of genetic polymorphism in patients who undergo weight loss intervention might be used to estimate their risks of weight regain. Additionally, the genetic-based risk estimation may be used as a guide for physicians and dietitians to provide each of their patients with the most appropriate strategies for weight loss and weight maintenance.
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149
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Masip G, Silventoinen K, Keski-Rahkonen A, Palviainen T, Sipilä PN, Kaprio J, Bogl LH. The genetic architecture of the association between eating behaviors and obesity: combining genetic twin modeling and polygenic risk scores. Am J Clin Nutr 2020; 112:956-966. [PMID: 32685959 PMCID: PMC7528566 DOI: 10.1093/ajcn/nqaa181] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 06/12/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Obesity susceptibility genes are highly expressed in the brain suggesting that they might exert their influence on body weight through eating-related behaviors. OBJECTIVES To examine whether the genetic susceptibility to obesity is mediated by eating behavior patterns. METHODS Participants were 3977 twins (33% monozygotic, 56% females), aged 31-37 y, from wave 5 of the FinnTwin16 study. They self-reported their height and weight, eating behaviors (15 items), diet quality, and self-measured their waist circumference (WC). For 1055 twins with genome-wide data, we constructed a polygenic risk score for BMI (PRSBMI) using almost 1 million single nucleotide polymorphisms. We used principal component analyses to identify eating behavior patterns, twin modeling to decompose correlations into genetic and environmental components, and structural equation modeling to test mediation models between the PRSBMI, eating behavior patterns, and obesity measures. RESULTS We identified 4 moderately heritable (h2 = 36-48%) eating behavior patterns labeled "snacking," "infrequent and unhealthy eating," "avoidant eating," and "emotional and external eating." The highest phenotypic correlation with obesity measures was found for the snacking behavior pattern (r = 0.35 for BMI and r = 0.32 for WC; P < 0.001 for both), largely due to genetic factors in common (bivariate h2 > 70%). The snacking behavior pattern partially mediated the association between the PRSBMI and obesity measures (βindirect = 0.06; 95% CI: 0.02, 0.09; P = 0.002 for BMI; and βindirect = 0.05; 95% CI: 0.02, 0.08; P = 0.003 for WC). CONCLUSIONS Eating behavior patterns share a common genetic liability with obesity measures and are moderately heritable. Genetic susceptibility to obesity can be partly mediated by an eating pattern characterized by frequent snacking. Obesity prevention efforts might therefore benefit from focusing on eating behavior change, particularly in genetically susceptible individuals.
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Affiliation(s)
- Guiomar Masip
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Karri Silventoinen
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | | | - Teemu Palviainen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Pyry N Sipilä
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Leonie H Bogl
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Epidemiology, Center for Public Health, Medical University of Vienna, Vienna, Austria
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150
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Kan C, Herle M, Treasure J, Jones A, Rijsdijk F, Llewellyn C. Common etiological architecture underlying reward responsiveness, externally driven eating behaviors, and BMI in childhood: findings from the Gemini twin cohort. Int J Obes (Lond) 2020; 44:2064-2074. [PMID: 32467612 PMCID: PMC7610375 DOI: 10.1038/s41366-020-0605-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Revised: 04/15/2020] [Accepted: 05/14/2020] [Indexed: 01/09/2023]
Abstract
BACKGROUND Studies have reported that impulsivity predicts childhood BMI and that the association is mediated by eating behaviors. One aspect of impulsivity-potentially crucial in the obesity context-is reward responsiveness, which may predispose to responsiveness to palatable food cues. The behavioral susceptibility theory hypothesizes that genetic susceptibility to obesity operates partly via genetically determined differences in appetite regulation. Reward responsiveness may therefore be one of the neuro-endophenotypes that mediates genetic susceptibility to obesity. OBJECTIVE To test whether reward responsiveness, eating behaviors, and child BMI share common genetic architecture. METHODS We examined reward responsiveness, eating behaviors, and BMI in 5-year-old children from Gemini, a UK birth cohort of 2402 twin pairs born in 2007. All measures were collected by parent report. Reward responsiveness was derived from the Behavioral Approach System. Compulsion to eat and eating for pleasure was measured with the "food responsiveness" scale of the Child Eating Behavior Questionnaire. Wanting to eat in response to environmental food cues was measured with the "external eating" scale of the Dutch Eating Behavior Questionnaire. Maximum-likelihood structural equation modeling was used to establish underlying common genetic and environmental influences. RESULTS There were significant positive phenotypic correlations between all traits except for reward responsiveness and BMI. Genetic factors explained the majority of the association between food responsiveness and external eating (74%, 95% CI: 61, 87), whereas common shared environmental factors explained the majority of the associations between reward responsiveness with both food responsiveness (55%, 95% CI: 20, 90) and external eating (70%, 95% CI: 39, 100). CONCLUSIONS Our study demonstrates the importance of common environmental factors in the shared etiology between reward responsiveness and childhood eating behaviors. However, the common etiology underlying both reward responsiveness and BMI is unclear, as there was no phenotypic correlation between reward responsiveness and BMI at this age. Further longitudinal research needs to detangle this complex relationship throughout development.
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Affiliation(s)
- Carol Kan
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
| | - Moritz Herle
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Janet Treasure
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Andrew Jones
- Institute of Population Health Sciences, University of Liverpool, Liverpool, UK
| | - Frühling Rijsdijk
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Clare Llewellyn
- Research Department of Behavioral Science and Health, University College London, London, UK
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