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The CODATwins Project: The Current Status and Recent Findings of COllaborative Project of Development of Anthropometrical Measures in Twins. Twin Res Hum Genet 2019; 22:800-808. [PMID: 31364586 DOI: 10.1017/thg.2019.35] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
The COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) project is a large international collaborative effort to analyze individual-level phenotype data from twins in multiple cohorts from different environments. The main objective is to study factors that modify genetic and environmental variation of height, body mass index (BMI, kg/m2) and size at birth, and additionally to address other research questions such as long-term consequences of birth size. The project started in 2013 and is open to all twin projects in the world having height and weight measures on twins with information on zygosity. Thus far, 54 twin projects from 24 countries have provided individual-level data. The CODATwins database includes 489,981 twin individuals (228,635 complete twin pairs). Since many twin cohorts have collected longitudinal data, there is a total of 1,049,785 height and weight observations. For many cohorts, we also have information on birth weight and length, own smoking behavior and own or parental education. We found that the heritability estimates of height and BMI systematically changed from infancy to old age. Remarkably, only minor differences in the heritability estimates were found across cultural-geographic regions, measurement time and birth cohort for height and BMI. In addition to genetic epidemiological studies, we looked at associations of height and BMI with education, birth weight and smoking status. Within-family analyses examined differences within same-sex and opposite-sex dizygotic twins in birth size and later development. The CODATwins project demonstrates the feasibility and value of international collaboration to address gene-by-exposure interactions that require large sample sizes and address the effects of different exposures across time, geographical regions and socioeconomic status.
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202
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Gene-Environment Interactions on Body Fat Distribution. Int J Mol Sci 2019; 20:ijms20153690. [PMID: 31357654 PMCID: PMC6696304 DOI: 10.3390/ijms20153690] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Revised: 07/18/2019] [Accepted: 07/19/2019] [Indexed: 02/08/2023] Open
Abstract
The prevalence of obesity has been increasing markedly in the U.S. and worldwide in the past decades; and notably, the obese populations are signified by not only the overall elevated adiposity but also particularly harmful accumulation of body fat in the central region of the body, namely, abdominal obesity. The profound shift from “traditional” to “obesogenic” environments, principally featured by the abundance of palatable, energy-dense diet, reduced physical activity, and prolonged sedentary time, promotes the obesity epidemics and detrimental body fat distribution. Recent advances in genomics studies shed light on the genetic basis of obesity and body fat distribution. In addition, growing evidence from investigations in large cohorts and clinical trials has lent support to interactions between genetic variations and environmental factors, e.g., diet and lifestyle factors, in relation to obesity and body fat distribution. This review summarizes the recent discoveries from observational studies and randomized clinical trials on the gene–environment interactions on obesity and body fat distribution.
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203
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Lamiquiz-Moneo I, Mateo-Gallego R, Bea AM, Dehesa-García B, Pérez-Calahorra S, Marco-Benedí V, Baila-Rueda L, Laclaustra M, Civeira F, Cenarro A. Genetic predictors of weight loss in overweight and obese subjects. Sci Rep 2019; 9:10770. [PMID: 31341224 PMCID: PMC6656717 DOI: 10.1038/s41598-019-47283-5] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2018] [Accepted: 07/03/2019] [Indexed: 12/24/2022] Open
Abstract
The aim of our study was to investigate a large cohort of overweight subjects consuming a homogeneous diet to identify the genetic factors associated with weight loss that could be used as predictive markers in weight loss interventions. We retrospectively recruited subjects (N = 788) aged over 18 years with a Body Mass Index (BMI) between 25 and 40 kg/m2 who were treated at our lipid unit for at least one year from 2008 to 2016, and we also recruited a control group (168 patients) with normal BMIs. All participants received counselling from a nutritionist that included healthy diet and physical activity recommendations. We genotyped 25 single nucleotide variants (SNVs) in 25 genes that were previously associated with obesity and calculated genetic scores that were derived from 25 SNVs. The risk allele in CADM2 showed a higher frequency in overweight and obese subjects than in controls (p = 0.007). The mean follow-up duration was 5.58 ± 2.68 years. Subjects with lower genetic scores showed greater weight loss during the follow-up period. The genetic score was the variable that best explained the variations in weight from the baseline. The genetic score explained 2.4% of weight change variance at one year and 1.6% of weight change variance at the end of the follow-up period after adjusting for baseline weight, sex, age and years of follow-up.
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Affiliation(s)
- Itziar Lamiquiz-Moneo
- Unidad Clínica y de Investigación en Lípidos y Arteriosclerosis, Hospital Universitario Miguel Servet, Instituto de Investigación Sanitaria Aragón (IIS Aragón), CIBERCV, Zaragoza, Spain
| | - Rocío Mateo-Gallego
- Unidad Clínica y de Investigación en Lípidos y Arteriosclerosis, Hospital Universitario Miguel Servet, Instituto de Investigación Sanitaria Aragón (IIS Aragón), CIBERCV, Zaragoza, Spain. .,Universidad de Zaragoza, Zaragoza, Spain.
| | - Ana M Bea
- Unidad Clínica y de Investigación en Lípidos y Arteriosclerosis, Hospital Universitario Miguel Servet, Instituto de Investigación Sanitaria Aragón (IIS Aragón), CIBERCV, Zaragoza, Spain
| | - Blanca Dehesa-García
- Unidad Clínica y de Investigación en Lípidos y Arteriosclerosis, Hospital Universitario Miguel Servet, Instituto de Investigación Sanitaria Aragón (IIS Aragón), CIBERCV, Zaragoza, Spain
| | - Sofía Pérez-Calahorra
- Unidad Clínica y de Investigación en Lípidos y Arteriosclerosis, Hospital Universitario Miguel Servet, Instituto de Investigación Sanitaria Aragón (IIS Aragón), CIBERCV, Zaragoza, Spain
| | - Victoria Marco-Benedí
- Unidad Clínica y de Investigación en Lípidos y Arteriosclerosis, Hospital Universitario Miguel Servet, Instituto de Investigación Sanitaria Aragón (IIS Aragón), CIBERCV, Zaragoza, Spain
| | - Lucía Baila-Rueda
- Unidad Clínica y de Investigación en Lípidos y Arteriosclerosis, Hospital Universitario Miguel Servet, Instituto de Investigación Sanitaria Aragón (IIS Aragón), CIBERCV, Zaragoza, Spain
| | - Martín Laclaustra
- Unidad Clínica y de Investigación en Lípidos y Arteriosclerosis, Hospital Universitario Miguel Servet, Instituto de Investigación Sanitaria Aragón (IIS Aragón), CIBERCV, Zaragoza, Spain
| | - Fernando Civeira
- Unidad Clínica y de Investigación en Lípidos y Arteriosclerosis, Hospital Universitario Miguel Servet, Instituto de Investigación Sanitaria Aragón (IIS Aragón), CIBERCV, Zaragoza, Spain.,Universidad de Zaragoza, Zaragoza, Spain
| | - Ana Cenarro
- Unidad Clínica y de Investigación en Lípidos y Arteriosclerosis, Hospital Universitario Miguel Servet, Instituto de Investigación Sanitaria Aragón (IIS Aragón), CIBERCV, Zaragoza, Spain
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204
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Clifford SA, Gillespie AN, Olds T, Grobler AC, Wake M. Body composition: population epidemiology and concordance in Australian children aged 11-12 years and their parents. BMJ Open 2019; 9:95-105. [PMID: 31273020 PMCID: PMC6624063 DOI: 10.1136/bmjopen-2018-023698] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Revised: 10/22/2018] [Accepted: 04/04/2019] [Indexed: 12/30/2022] Open
Abstract
OBJECTIVES Overweight and obesity remain at historically high levels, cluster within families and are established risk factors for multiple diseases. We describe the epidemiology and cross-generational concordance of body composition among Australian children aged 11-12 years and their parents. DESIGN The population-based cross-sectional Child Health CheckPoint study, nested within the Longitudinal Study of Australian Children (LSAC). SETTING Assessment centres in seven major Australian cities and eight regional cities, or home visits; February 2015-March 2016. PARTICIPANTS Of all participating CheckPoint families (n=1874), body composition data were available for 1872 children (49% girls) and 1852 parents (mean age 43.7 years; 88% mothers), including 1830 biological parent-child pairs. MEASURES Height, weight, body mass index (BMI), waist circumference and waist-to-height ratio for all participants; body fat and fat-free mass by four-limb bioimpedence analysis (BIA) at assessment centres, or body fat percentage by two-limb BIA at home visits. Analysis: parent-child concordance was assessed using (i) Pearson's correlation coefficients, and (ii) partial correlation coefficients adjusted for age, sex and socioeconomic disadvantage. Survey weights and methods accounted for LSAC's complex sample design. RESULTS 20.7% of children were overweight and 6.2% obese, as were 33.5% and 31.6% of parents. Boys and girls showed similar distributions for all body composition measures but, despite similar BMI and waist-to-height ratio, mothers had higher proportions of total and truncal fat than fathers. Parent-child partial correlations were greatest for height (0.37, 95% CI 0.33 to 0.42). Other anthropometric and fat/lean measures showed strikingly similar partial correlations, ranging from 0.25 (95% CI 0.20 to 0.29) for waist circumference to 0.30 (95% CI 0.25 to 0.34) for fat-free percentage. Whole-sample and sex-specific percentile values are provided for all measures. CONCLUSIONS Excess adiposity remains prevalent in Australian children and parents. Moderate cross-generational concordance across all measures of leanness and adiposity is already evident by late childhood.
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Affiliation(s)
- Susan A Clifford
- Murdoch Children’s Research Institute, Parkville, Victoria, Australia
- Department of Paediatrics, The University of Melbourne, Parkville, Victoria, Australia
| | - Alanna N Gillespie
- Murdoch Children’s Research Institute, Parkville, Victoria, Australia
- Department of Paediatrics, The University of Melbourne, Parkville, Victoria, Australia
| | - Timothy Olds
- Murdoch Children’s Research Institute, Parkville, Victoria, Australia
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia
| | - Anneke C Grobler
- Murdoch Children’s Research Institute, Parkville, Victoria, Australia
| | - Melissa Wake
- Murdoch Children’s Research Institute, Parkville, Victoria, Australia
- Department of Paediatrics, The University of Melbourne, Parkville, Victoria, Australia
- Department of Paediatrics and The Liggins Institute, The University of Auckland, Auckland, New Zealand
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205
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Blomquist GE. Unpacking the heritability of body mass index and other ratios. Am J Hum Biol 2019; 31:e23289. [PMID: 31243841 DOI: 10.1002/ajhb.23289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Revised: 04/20/2019] [Accepted: 06/09/2019] [Indexed: 11/10/2022] Open
Abstract
OBJECTIVES Ratios of weight to height, especially body mass index (BMI = kg/m2 ), are often used in epidemiological and genetic studies of health, but the limitations of quantitative genetic analysis of ratios are not widely known. The heritability of these ratios can be closely approximated from a bivariate quantitative genetic model of weight and height which clarifies how BMI heritabilities change. METHODS I explored this bivariate approximation and alternative measures through simulated datasets fit with linear mixed models. Simulated data were based on published heritabilities and other statistics for BMI and related anthropometric dimensions from four human samples. RESULTS Inspection of the bivariate approximation and analysis of simulated data show the heritability of weight/height crucially depends on the phenotypic (rP ) and genetic correlations (rA ) between weight and height. Changes in these correlations can have dramatic effects on the heritability of BMI. For example, when rP ≪ rA heritability of BMI is reduced to 35-50% of its value when the correlations are equal. DISCUSSION Increasing adiposity likely decreases the phenotypic correlations more than the genetic correlation resulting in reduced heritability of the ratio. This contrasts with the commonly reported stability or increase of BMI heritability and implies it may result from increased genetic variance in weight in obesogenic environments. The bivariate model offers other advantages over ratios, including estimating the conditional genetic variance or heritability of weight that is unassociated with height, which may prove useful in quantitative and molecular genetic studies.
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206
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Potabattula R, Dittrich M, Schorsch M, Hahn T, Haaf T, El Hajj N. Male obesity effects on sperm and next-generation cord blood DNA methylation. PLoS One 2019; 14:e0218615. [PMID: 31246962 PMCID: PMC6597061 DOI: 10.1371/journal.pone.0218615] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Accepted: 06/05/2019] [Indexed: 12/20/2022] Open
Abstract
The prevalence of metabolic disorders, in particular obesity has dramatically increased worldwide. Genetic variants explain only a minor part of the obesity epidemic induced by physical inactivity and over-nutrition. Epidemiological studies in humans and animal models indicate that epigenetic changes associated with adverse parental and/or intrauterine factors may contribute to the missing heritability of metabolic disorders. Possible adverse paternal effects are likely transmitted by sperm to the next-generation. To investigate this hypothesis, we have systematically analyzed the effects of male body mass index (BMI) on sperm epigenome and its association with next-generation fetal cord blood (FCB) DNA methylation. Methylation levels of maternally imprinted (PEG1, PEG4, PEG5, and PEG10), paternally imprinted (H19-IG DMR, IGF2-DMR0, and MEG3-IG DMR) regions, and obesity-related non-imprinted HIF3A gene were quantified by bisulphite pyrosequencing in sperm samples of 294 human donors undergoing in vitro fertilization or intracytoplasmic sperm injection, and in 113 FCBs of the resulting offspring. Multivariable regression analyses revealed that MEG3 intergenic differentially methylated region (IG DMR) showed positive correlation between sperm methylation and donor’s BMI. A gender-specific correlation between paternal BMI and FCB methylation was observed for MEG3-IG DMR, HIF3A, and IGF2-DMR0. The former two genes displayed same directional nominal association (as sperm) between paternal BMI and FCB methylation in male offspring. Hypomethylation of IGF2-DMR0 with increased paternal BMI was observed in FCBs from female offsprings. Our results suggest that male obesity is nominally associated with modification of sperm DNA methylome in humans, which may affect the epigenome of the next-generation. Nevertheless, it is important to note that none of the associated p-values survived multiple testing adjustments. Future work should test the effect of associated methylation aberrations in the offspring as DNA methylation was shown to control expression and/or imprint establishment across the studied genes.
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Affiliation(s)
- Ramya Potabattula
- Institute of Human Genetics, Julius Maximilians University, Würzburg, Germany
- * E-mail: (RP); , (NEH)
| | - Marcus Dittrich
- Institute of Human Genetics, Julius Maximilians University, Würzburg, Germany
| | | | | | - Thomas Haaf
- Institute of Human Genetics, Julius Maximilians University, Würzburg, Germany
| | - Nady El Hajj
- Institute of Human Genetics, Julius Maximilians University, Würzburg, Germany
- College of Health and Life Sciences, Hamad Bin Khalifa University, Education City, Doha, Qatar
- * E-mail: (RP); , (NEH)
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207
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Ortiz-Dosal A, Rodil-García P, Salazar-Olivo LA. Circulating microRNAs in human obesity: a systematic review. Biomarkers 2019; 24:499-509. [PMID: 30990364 DOI: 10.1080/1354750x.2019.1606279] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Context: Differential expression profiles of microRNAs have been reported in human obesity suggesting a miRNAs role in the development of obesity and associated disorders. Objective: To review circulating microRNAs (c-miRNAs) dysregulated in human obesity and to predict their possible target genes. Methods: We performed a systematic review on PubMed database (PROSPERO, CRD42017077742) for original works on c-miRNAs and human obesity and recorded c-miRNAs with differential expression profiles. Potential target genes and metabolic pathways for dysregulated miRNAs with at least two independent reports were searched using bioinformatic tools. Results: Twenty-two c-miRNAs are overexpressed, nine underexpressed and two c-miRNAs dysregulated in both directions in people with obesity compared to lean controls. Bioinformatic analyses suggest these c-miRNAs target on genes associated with fatty acid metabolism and PI3k/Akt pathway. Conclusion: Literature records 33 c-miRNAs confirmedly dysregulated in human obesity. Their predicted target genes are involved in pathways that could explain the development of obesity and its comorbidities. Further research will clarify the role of these miRNAs on metabolic diseases and their usefulness for the prognosis, prevention and treatment of obesity.
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Affiliation(s)
- Alejandra Ortiz-Dosal
- a Division of Molecular Biology, Institute Potosino of Scientific and Technological Research , San Luis Potosí , México
| | - Patricia Rodil-García
- a Division of Molecular Biology, Institute Potosino of Scientific and Technological Research , San Luis Potosí , México
| | - Luis A Salazar-Olivo
- a Division of Molecular Biology, Institute Potosino of Scientific and Technological Research , San Luis Potosí , México
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208
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Bogl LH, Mehlig K, Intemann T, Masip G, Keski-Rahkonen A, Russo P, Michels N, Reisch L, Pala V, Johnson L, Molnár D, Tornaritis M, Veidebaum T, Moreno L, Ahrens W, Lissner L, Kaprio J, Hebestreit A. A within-sibling pair analysis of lifestyle behaviours and BMI z-score in the multi-centre I.Family study. Nutr Metab Cardiovasc Dis 2019; 29:580-589. [PMID: 30952577 DOI: 10.1016/j.numecd.2019.01.017] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Revised: 01/15/2019] [Accepted: 01/30/2019] [Indexed: 12/19/2022]
Abstract
BACKGROUND AND AIMS By investigating differences in lifestyle behaviours and BMI in sibling pairs, family-level confounding is minimized and causal inference is improved, compared to cross-sectional studies of unrelated children. Thus, we aimed to investigate within-sibling pair differences in different lifestyle behaviours and differences in BMI z-scores in children and adolescents. METHODS AND RESULTS We examined three groups of sibling pairs 1) all same-sex sibling pairs with maximum 4 years age difference (n = 1209 pairs from 1072 families in 8 countries, mean age 10.7 years, standard deviation 2.4 years), 2) sibling pairs discordant for overweight (n = 262) and 3) twin pairs (n = 85). Usual dietary intake was estimated by 24-h recalls and time spent in light (LPA) and moderate-to-vigorous physical activity (MVPA) was measured by accelerometers. Screen time, sleep and dieting for weight loss were assessed by questionnaires. Within all 3 groups of sibling pairs, more time in MVPA was associated with lower BMI z-score. Higher energy intake was associated with higher BMI z-score within twin pairs and within all sibling pairs who were not currently dieting for weight loss. Regarding LPA, screen time or sleep duration, no or inconsistent associations were observed for the three groups of sibling pairs. CONCLUSIONS MVPA and energy intake were associated with BMI differences within sibling and twin pairs growing up in the same home, thus independent of family-level confounding factors. Future studies should explore whether genetic variants regulating appetite or energy expenditure behaviours account for weight differences in sibling pairs.
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Affiliation(s)
- L H Bogl
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
| | - K Mehlig
- Department of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden.
| | - T Intemann
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany; Institute of Statistics, Faculty of Mathematics and Computer Science, University of Bremen, Bremen, Germany.
| | - G Masip
- Department of Public Health, University of Helsinki, Helsinki, Finland.
| | - A Keski-Rahkonen
- Department of Public Health, University of Helsinki, Helsinki, Finland.
| | - P Russo
- Institute of Food Sciences, National Research Council, Avellino, Italy.
| | - N Michels
- Department of Public Health, Ghent University, Ghent, Belgium.
| | - L Reisch
- Copenhagen Business School, Department of Management, Society and Communication, Frederiksberg, Denmark.
| | - V Pala
- Epidemiology and Prevention Unit Fondazione IRCCS Istituto Nazionale dei Tumori - Milan, Italy.
| | - L Johnson
- Centre for Exercise, Nutrition and Health Sciences, School for Policy Studies, University of Bristol, Bristol, UK.
| | - D Molnár
- Department of Pediatrics, Medical School, University of Pécs, Pécs, Hungary.
| | - M Tornaritis
- Research and Education Institute of Child Health, Strovolos, Cyprus.
| | - T Veidebaum
- Department of Chronic Diseases, National Institute for Health Development, Tallinn, Estonia.
| | - L Moreno
- GENUD (Growth, Exercise, Nutrition and Development) Research Group, Faculty of Health Sciences, University of Zaragoza, Zaragoza, Spain.
| | - W Ahrens
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany; Institute of Statistics, Faculty of Mathematics and Computer Science, University of Bremen, Bremen, Germany.
| | - L Lissner
- Department of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden.
| | - J Kaprio
- Department of Public Health, University of Helsinki, Helsinki, Finland; Institute of Molecular Medicine FIMM, University of Helsinki, Helsinki, Finland.
| | - A Hebestreit
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
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209
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Ranzenhofer LM, Mayer LES, Davis HA, Mielke-Maday HK, McInerney H, Korn R, Gupta N, Brown AJ, Schebendach J, Tanofsky-Kraff M, Thaker V, Chung WK, Leibel RL, Walsh BT, Rosenbaum M. The FTO Gene and Measured Food Intake in 5- to 10-Year-Old Children Without Obesity. Obesity (Silver Spring) 2019; 27:1023-1029. [PMID: 31119882 PMCID: PMC6561098 DOI: 10.1002/oby.22464] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Accepted: 02/15/2019] [Indexed: 11/09/2022]
Abstract
OBJECTIVE Genetic variation in the first intron of FTO (e.g., single-nucleotide polymorphism [SNP] rs9939609) is strongly associated with adiposity. This effect is thought to be mediated (at least in part) via increasing caloric intake, although the precise molecular genetic mechanisms are not fully understood. Prior pediatric studies of FTO have included youth with overweight and obesity; however, they have not informed whether a genotypic effect on ingestive behavior is present prior to obesity onset. Therefore, this study investigated the association between FTO and caloric intake in children aged 5 to 10 years without obesity (adiposity ≤ 95th percentile). METHODS A total of 122 children were genotyped for rs9939609 and ate ad libitum from a laboratory lunch buffet following a standardized breakfast. Linear regressions, adjusting for body mass, were used to examine the association between FTO "dose" (number of copies of SNP rs9939609) and intake variables. RESULTS There was a significant association between FTO and total intake. Each risk allele predicted an additional 64 calories, accounting for 3% of the variance. There were no associations between FTO and macronutrient preference, energy density, or diet variety. Results were influenced by race. CONCLUSIONS Results corroborate and extend prior work by showing a dose-dependent effect on food intake in children without obesity.
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Affiliation(s)
- Lisa M Ranzenhofer
- Department of Psychiatry, Columbia University Irving Medical Center and New York State Psychiatric Institute, New York, New York, USA
| | - Laurel E S Mayer
- Department of Psychiatry, Columbia University Irving Medical Center and New York State Psychiatric Institute, New York, New York, USA
| | - Haley A Davis
- Department of Psychiatry, Columbia University Irving Medical Center and New York State Psychiatric Institute, New York, New York, USA
| | - Hanna K Mielke-Maday
- Department of Psychiatry, Columbia University Irving Medical Center and New York State Psychiatric Institute, New York, New York, USA
| | - Hailey McInerney
- Department of Psychiatry, Columbia University Irving Medical Center and New York State Psychiatric Institute, New York, New York, USA
| | - Rachel Korn
- Department of Psychiatry, Columbia University Irving Medical Center and New York State Psychiatric Institute, New York, New York, USA
| | - Nikita Gupta
- Department of Psychiatry, Columbia University Irving Medical Center and New York State Psychiatric Institute, New York, New York, USA
| | - Amanda J Brown
- Department of Psychiatry, Columbia University Irving Medical Center and New York State Psychiatric Institute, New York, New York, USA
| | - Janet Schebendach
- Department of Psychiatry, Columbia University Irving Medical Center and New York State Psychiatric Institute, New York, New York, USA
| | | | - Vidhu Thaker
- Division of Molecular Genetics, Department of Pediatrics, Columbia University Irving Medical Center, New York, New York, USA
| | - Wendy K Chung
- Division of Molecular Genetics, Department of Pediatrics, Columbia University Irving Medical Center, New York, New York, USA
| | - Rudolph L Leibel
- Division of Molecular Genetics, Department of Pediatrics, Columbia University Irving Medical Center, New York, New York, USA
| | - B Timothy Walsh
- Department of Psychiatry, Columbia University Irving Medical Center and New York State Psychiatric Institute, New York, New York, USA
| | - Michael Rosenbaum
- Division of Molecular Genetics, Department of Pediatrics, Columbia University Irving Medical Center, New York, New York, USA
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210
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Kennedy JT, Astafiev SV, Golosheykin S, Korucuoglu O, Anokhin AP. Shared genetic influences on adolescent body mass index and brain structure: A voxel-based morphometry study in twins. Neuroimage 2019; 199:261-272. [PMID: 31163268 DOI: 10.1016/j.neuroimage.2019.05.053] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2019] [Revised: 05/17/2019] [Accepted: 05/19/2019] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Previous research has demonstrated significant relationships between obesity and brain structure. Both phenotypes are heritable, but it is not known whether they are influenced by common genetic factors. We investigated the genetic etiology of the relationship between individual variability in brain morphology and BMIz using structural MRI in adolescent twins. METHOD The sample (n = 258) consisted of 54 monozygotic and 75 dizygotic twin pairs (mean(SD) age = 13.61(0.505), BMIz = 0.608(1.013). Brain structure (volume and density of gray and white matter) was assessed using VBM. Significant voxelwise heritability of brain structure was established using the Accelerated Permutation inference for ACE models (APACE) program, with structural heritability varying from 15 to 97%, depending on region. Bivariate heritability analyses were carried out comparing additive genetic and unique environment models with and without shared genetics on BMIz and the voxels showing significant heritability in the APACE analyses. RESULTS BMIz was positively related to gray matter volume in the brainstem and thalamus and negatively related to gray matter volume in the bilateral uncus and medial orbitofrontal cortex, gray matter density in the cerebellum, prefrontal lobe, temporal lobe, and limbic system, and white matter density in the brainstem. Bivariate heritability analyses showed that BMIz and brain structure share ∼1/3 of their genes and that ∼95% of the phenotypic correlation between BMIz and brain structure is due to shared additive genetic influences. These regions included areas related to decision-making, motivation, liking vs. wanting, taste, interoception, reward processing/learning, caloric evaluation, and inhibition. CONCLUSION These results suggested genetic factors are responsible for the relationship between BMIz and heritable BMIz related brain structure in areas related to eating behavior.
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Affiliation(s)
- James T Kennedy
- Department of Psychiatry, Washington University School of Medicine, United States.
| | - Serguei V Astafiev
- Department of Psychiatry, Washington University School of Medicine, United States
| | - Semyon Golosheykin
- Department of Psychiatry, Washington University School of Medicine, United States
| | - Ozlem Korucuoglu
- Department of Psychiatry, Washington University School of Medicine, United States
| | - Andrey P Anokhin
- Department of Psychiatry, Washington University School of Medicine, United States
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211
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Li W, Zhang D, Wang W, Wu Y, Mohammadnejad A, Lund J, Baumbach J, Christiansen L, Tan Q. DNA methylome profiling in identical twin pairs discordant for body mass index. Int J Obes (Lond) 2019; 43:2491-2499. [PMID: 31152155 DOI: 10.1038/s41366-019-0382-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Revised: 04/01/2019] [Accepted: 04/05/2019] [Indexed: 02/07/2023]
Abstract
OBJECTIVE Body mass index (BMI) serves as an important measurement of obesity and adiposity, which are highly correlated with cardiometabolic diseases. Although high heritability has been estimated, the identified genetic variants by genetic association studies only explain a small proportion of BMI variation. As an active effort for further exploring the molecular basis of BMI variation, large-scale epigenome-wide association studies have been conducted but with limited number of loci reported, perhaps due to poorly controlled confounding factors, including genetic factors. Being genetically identical, monozygotic twins discordant for BMI are ideal subjects for analyzing the epigenetic association between DNA methylation and BMI, providing perfect control on their genetic makeups largely responsible for BMI variation. SUBJECTS We performed an epigenome-wide association study on BMI using 30 identical twin pairs (15 male and 15 female pairs) with age ranging from 39 to 72 years and degree of BMI discordance ranging from 3-7.5 kg/m2. Methylation data from whole blood samples were collected using the reduced representation bisulfite sequencing technique. RESULTS After adjusting for blood cell composition and clinical variables, we identified 136 CpGs with p-value < 1e-4, 30 CpGs with p < 1e-05 but no CpGs reached genome-wide significance. Genomic region-based analysis found 11 differentially methylated regions harboring coding and non-coding genes some of which were validated by gene expression analysis on independent samples. CONCLUSIONS Our DNA methylation sequencing analysis on identical twins provides new references for the epigenetic regulation on BMI and obesity.
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Affiliation(s)
- Weilong Li
- Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Dongfeng Zhang
- Division of Epidemiology and Health Statistics, Qingdao University Medical College, Qingdao, China
| | - Weijing Wang
- Division of Epidemiology and Health Statistics, Qingdao University Medical College, Qingdao, China
| | - Yili Wu
- Division of Epidemiology and Health Statistics, Qingdao University Medical College, Qingdao, China
| | - Afsaneh Mohammadnejad
- Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Jesper Lund
- Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Jan Baumbach
- Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany.,Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark
| | - Lene Christiansen
- Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, Odense, Denmark.,Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Qihua Tan
- Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, Odense, Denmark. .,Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
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212
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Bermingham KM, Brennan L, Segurado R, Barron RE, Gibney ER, Ryan MF, Gibney MJ, O’Sullivan AM. Exploring Covariation between Traditional Markers of Metabolic Health and the Plasma Metabolomic Profile: A Classic Twin Design. J Proteome Res 2019; 18:2613-2623. [DOI: 10.1021/acs.jproteome.9b00126] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Affiliation(s)
- Kate M. Bermingham
- UCD Institute of Food and Health, School of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Lorraine Brennan
- UCD Institute of Food and Health, School of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Ricardo Segurado
- School of Public Health, Physiotherapy, and Sports Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Rebecca E. Barron
- UCD Institute of Food and Health, School of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Eileen R. Gibney
- UCD Institute of Food and Health, School of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Miriam F. Ryan
- UCD Institute of Food and Health, School of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Michael J. Gibney
- UCD Institute of Food and Health, School of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Aifric M. O’Sullivan
- UCD Institute of Food and Health, School of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, Ireland
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213
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Doucet GE, Rasgon N, McEwen BS, Micali N, Frangou S. Elevated Body Mass Index is Associated with Increased Integration and Reduced Cohesion of Sensory-Driven and Internally Guided Resting-State Functional Brain Networks. Cereb Cortex 2019; 28:988-997. [PMID: 28119342 DOI: 10.1093/cercor/bhx008] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2016] [Indexed: 12/11/2022] Open
Abstract
Elevated body mass index (BMI) is associated with increased multi-morbidity and mortality. The investigation of the relationship between BMI and brain organization has the potential to provide new insights relevant to clinical and policy strategies for weight control. Here, we quantified the association between increasing BMI and the functional organization of resting-state brain networks in a sample of 496 healthy individuals that were studied as part of the Human Connectome Project. We demonstrated that higher BMI was associated with changes in the functional connectivity of the default-mode network (DMN), central executive network (CEN), sensorimotor network (SMN), visual network (VN), and their constituent modules. In siblings discordant for obesity, we showed that person-specific factors contributing to obesity are linked to reduced cohesiveness of the sensory networks (SMN and VN). We conclude that higher BMI is associated with widespread alterations in brain networks that balance sensory-driven (SMN, VN) and internally guided (DMN, CEN) states which may augment sensory-driven behavior leading to overeating and subsequent weight gain. Our results provide a neurobiological context for understanding the association between BMI and brain functional organization while accounting for familial and person-specific influences.
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Affiliation(s)
- Gaelle E Doucet
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, USA
| | - Natalie Rasgon
- Center for Neuroscience in Women's Health, Stanford University, Palo Alto, CA 91304, USA
| | - Bruce S McEwen
- Harold and Margaret Milliken Hatch Laboratory of Neuroendocrinology, The Rockefeller University, New York, NY 10065, USA
| | - Nadia Micali
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, USA
| | - Sophia Frangou
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, USA
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214
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Russell CG, Russell A. A biopsychosocial approach to processes and pathways in the development of overweight and obesity in childhood: Insights from developmental theory and research. Obes Rev 2019; 20:725-749. [PMID: 30768750 DOI: 10.1111/obr.12838] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Revised: 12/16/2018] [Accepted: 01/07/2019] [Indexed: 12/12/2022]
Abstract
Childhood obesity has reached alarming proportions in many countries. There is consensus that both biological (especially genetic) and environmental (including psychosocial) factors contribute to weight gain and obesity in childhood. Research has identified extensive risk or predictive factors for childhood obesity from both of these domains. There is less consensus about the developmental processes or pathways showing how these risk factors lead to overweigh/obesity (OW/OB) in childhood. We outline a biopsychosocial process model of the development of OW/OB in childhood. The model and associated scholarship from developmental theory and research guide an analysis of research on OW/OB in childhood. The model incorporates biological factors such as genetic predispositions or susceptibility genes, temperament, and homeostatic and allostatic processes with the psychosocial and behavioral factors of parenting, parental feeding practices, child appetitive traits, food liking, food intakes, and energy expenditure. There is an emphasis on bidirectional and transactional processes linking child biology and behavior with psychosocial processes and environment. Insights from developmental theory and research include implications for conceptualization, measurement, research design, and possible multiple pathways to OW/OB. Understanding the developmental processes and pathways involved in childhood OW/OB should contribute to more targeted prevention and intervention strategies in childhood.
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Affiliation(s)
- Catherine G Russell
- Faculty of Health, School of Exercise and Nutrition Sciences, Centre for Advanced Sensory Science, Deakin University, Burwood, Australia
| | - Alan Russell
- College of Education, Psychology and Social Work, Flinders University, Bedford Park, South Australia
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215
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Barbosa JPDAS, Basso L, Bartholomeu T, Rezende JAS, de Oliveira JA, Prista A, Tani G, Maia JAR, Forjaz CLDM. Familial aggregation and heritability of markers of metabolic risk, physical activity, and physical fitness in nuclear families from Muzambinho (Minas Gerais, Brazil). ARCHIVES OF ENDOCRINOLOGY AND METABOLISM 2019; 63:215-221. [PMID: 31066762 PMCID: PMC10522208 DOI: 10.20945/2359-3997000000137] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2017] [Accepted: 03/11/2019] [Indexed: 11/23/2022]
Abstract
OBJECTIVE This study investigated the familial aggregation and heritability of markers of metabolic risk, physical activity, and physical fitness in nuclear families from Muzambinho (Minas Gerais, Brazil). SUBJECTS AND METHODS The study included members of 139 families, comprising 97 fathers (aged 40 ± 7 years), 129 mothers (35 ± 6 years), 136 sons (12 ± 4 years), and 121 daughters (12 ± 5 years). Evaluated markers included (A) body mass index, waist circumference, glycemia, and cholesterolemia, as metabolic risk markers; (B) total weekly volume of physical activity, as a physical activity marker; and (C) relative muscle strength, as a physical fitness marker. Correlations between family members and heritability (h2) were estimated using the software S.A.G.E. RESULTS Significant familial correlations were obtained between parents-offspring for glycemia and cholesterolemia (both ρ = 0.21, p < 0.05) and relative muscle strength (ρ = 0.23, p < 0.05), and between siblings for waist circumference, glycemia, total weekly volume of physical activity, and relative muscle strength (ρ variation 0.25 to 0.36, p < 0.05). Heritability values were significant for almost all variables (h2 variations: 20% to 57% for metabolic risk markers, 22% for the total weekly volume of physical activity, and 50% for relative muscle strength), except for waist circumference (h2 = 15%, p = 0.059). CONCLUSION The presence of significant correlations between family members and/or significant heritability strengthens the possible genetic and/or common familial environment influence on metabolic risk markers, total weekly volume of physical activity, and relative muscle strength.
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Affiliation(s)
- João Paulo dos Anjos Souza Barbosa
- Universidade de São PauloLaboratório de Hemodinâmica da Atividade MotoraEscola de Educação Física e EsporteUniversidade de São PauloSPBrasilLaboratório de Hemodinâmica da Atividade Motora, Escola de Educação Física e Esporte, Universidade de São Paulo, SP, Brasil
| | - Luciano Basso
- Universidade de São PauloLaboratório de Comportamento MotorEscola de Educação Física e EsporteUniversidade de São PauloSPBrasilLaboratório de Comportamento Motor, Escola de Educação Física e Esporte, Universidade de São Paulo, SP, Brasil
| | - Teresa Bartholomeu
- Universidade de São PauloLaboratório de Hemodinâmica da Atividade MotoraEscola de Educação Física e EsporteUniversidade de São PauloSPBrasilLaboratório de Hemodinâmica da Atividade Motora, Escola de Educação Física e Esporte, Universidade de São Paulo, SP, Brasil
| | - Januária Andrea Souza Rezende
- Instituto Federal do Sul de Minas GeraisInstituto Federal do Sul de MinasMuzambinhoMGBrasilInstituto Federal do Sul de Minas – Campus Muzambinho, Muzambinho, MG, Brasil
| | - Jorge Alberto de Oliveira
- Universidade de São PauloLaboratório de Comportamento MotorEscola de Educação Física e EsporteUniversidade de São PauloSPBrasilLaboratório de Comportamento Motor, Escola de Educação Física e Esporte, Universidade de São Paulo, SP, Brasil
| | - António Prista
- Centro de Investigação e Desenvolvimento do Desporto e Actividade FísicaFaculdade de Educação Física e DesportoUniversidade PedagógicaMaputoMoçambique Núcleo de Investigação em Actividade Física e Saúde, Centro de Investigação e Desenvolvimento do Desporto e Actividade Física (CIDAF), Faculdade de Educação Física e Desporto (FEFD), Universidade Pedagógica, Maputo, Moçambique
| | - Go Tani
- Universidade de São PauloLaboratório de Comportamento MotorEscola de Educação Física e EsporteUniversidade de São PauloSPBrasilLaboratório de Comportamento Motor, Escola de Educação Física e Esporte, Universidade de São Paulo, SP, Brasil
| | - José António Ribeiro Maia
- Universidade do PortoCentro de Investigação, Formação, Intervenção e Inovação em DesportoFaculdade de DesportoUniversidade do PortoPortoPortugal Laboratório de Cineantropometria e Gabinete de Estatística Aplicada, Centro de Investigação, Formação, Intervenção e Inovação em Desporto (CIFI2D), Faculdade de Desporto, Universidade do Porto, Porto, Portugal
| | - Cláudia Lúcia de Moraes Forjaz
- Universidade de São PauloLaboratório de Hemodinâmica da Atividade MotoraEscola de Educação Física e EsporteUniversidade de São PauloSPBrasilLaboratório de Hemodinâmica da Atividade Motora, Escola de Educação Física e Esporte, Universidade de São Paulo, SP, Brasil
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216
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Khera AV, Chaffin M, Wade KH, Zahid S, Brancale J, Xia R, Distefano M, Senol-Cosar O, Haas ME, Bick A, Aragam KG, Lander ES, Smith GD, Mason-Suares H, Fornage M, Lebo M, Timpson NJ, Kaplan LM, Kathiresan S. Polygenic Prediction of Weight and Obesity Trajectories from Birth to Adulthood. Cell 2019; 177:587-596.e9. [PMID: 31002795 PMCID: PMC6661115 DOI: 10.1016/j.cell.2019.03.028] [Citation(s) in RCA: 411] [Impact Index Per Article: 82.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Revised: 11/07/2018] [Accepted: 03/12/2019] [Indexed: 12/30/2022]
Abstract
Severe obesity is a rapidly growing global health threat. Although often attributed to unhealthy lifestyle choices or environmental factors, obesity is known to be heritable and highly polygenic; the majority of inherited susceptibility is related to the cumulative effect of many common DNA variants. Here we derive and validate a new polygenic predictor comprised of 2.1 million common variants to quantify this susceptibility and test this predictor in more than 300,000 individuals ranging from middle age to birth. Among middle-aged adults, we observe a 13-kg gradient in weight and a 25-fold gradient in risk of severe obesity across polygenic score deciles. In a longitudinal birth cohort, we note minimal differences in birthweight across score deciles, but a significant gradient emerged in early childhood and reached 12 kg by 18 years of age. This new approach to quantify inherited susceptibility to obesity affords new opportunities for clinical prevention and mechanistic assessment.
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Affiliation(s)
- Amit V Khera
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Division of Cardiology, Massachusetts General Hospital, Boston, MA 02114, USA; Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA.
| | - Mark Chaffin
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Kaitlin H Wade
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 1TH, UK; Population Health Science, Bristol Medical School, Bristol, Bristol BS8 1TH, UK; Avon Longitudinal Study of Parents and Children, Bristol BS8 1TH, UK
| | - Sohail Zahid
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Joseph Brancale
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Obesity, Metabolism, and Nutrition Institute, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Rui Xia
- The Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Marina Distefano
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Cambridge, MA 02139, USA; Department of Pathology, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Pathology, Harvard Medical School, Cambridge, MA 02115, USA
| | - Ozlem Senol-Cosar
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Cambridge, MA 02139, USA; Department of Pathology, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Pathology, Harvard Medical School, Cambridge, MA 02115, USA
| | - Mary E Haas
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Alexander Bick
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Krishna G Aragam
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Division of Cardiology, Massachusetts General Hospital, Boston, MA 02114, USA; Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Eric S Lander
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Program in Health Sciences and Technology, Harvard Medical School, Boston, MA 02115, USA
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 1TH, UK; Population Health Science, Bristol Medical School, Bristol, Bristol BS8 1TH, UK
| | - Heather Mason-Suares
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Cambridge, MA 02139, USA; Department of Pathology, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Pathology, Harvard Medical School, Cambridge, MA 02115, USA
| | - Myriam Fornage
- The Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Matthew Lebo
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Cambridge, MA 02139, USA; Department of Pathology, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Pathology, Harvard Medical School, Cambridge, MA 02115, USA
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 1TH, UK; Population Health Science, Bristol Medical School, Bristol, Bristol BS8 1TH, UK; Avon Longitudinal Study of Parents and Children, Bristol BS8 1TH, UK
| | - Lee M Kaplan
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Obesity, Metabolism, and Nutrition Institute, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Sekar Kathiresan
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Division of Cardiology, Massachusetts General Hospital, Boston, MA 02114, USA; Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA.
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217
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Magnusson K, Turkiewicz A, Englund M. Nature vs nurture in knee osteoarthritis - the importance of age, sex and body mass index. Osteoarthritis Cartilage 2019; 27:586-592. [PMID: 30634033 DOI: 10.1016/j.joca.2018.12.018] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Revised: 12/06/2018] [Accepted: 12/19/2018] [Indexed: 02/08/2023]
Abstract
OBJECTIVE (1) To estimate the life-time genetic contribution for knee osteoarthritis (OA) surgery and (2) to explore any differences in the genetic contribution across age, sex and body mass index (BMI). METHODS We studied the sex-specific genetic contribution to knee OA surgery in a prospective cohort study of 62,490 twins aged 35 years or older with a follow-up period of up to 47 years (10,092 identical and 21,153 non-identical twin pairs, 54% women). To study interactions with age, we graphed the heritabilities over the lifespan for men and women. We also studied the sex-specific heritability across strata of the median BMI to explore any interactions with BMI. RESULTS The overall heritability of knee OA surgery was 0.53 (95% confidence intervals [CI] = 0.31-0.75), with higher heritability among women (H2 = 0.80 (95% CI = 0.73-0.87)) than men (H2 = 0.39 (95% CI = 0.10-0.69)). For men, the heritability started to rise after age 68. The genetic contribution was particularly low in men above median BMI (H2≥23.7 kg/m2 = 0.08, 95% CI = -0.32-0.48). For women, the heritability was consistently high from age 50 to death, independently of BMI (H2≥22.5 kg/m2 = 0.77, 95% CI = 0.66-0.87). CONCLUSION There is a higher and more consistent genetic contribution for knee OA surgery in women than men. In men the genetic contribution was relatively low and varied with age and BMI.
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Affiliation(s)
- K Magnusson
- Lund University, Faculty of Medicine, Department of Clinical Sciences Lund, Orthopaedics, Clinical Epidemiology Unit, Lund, Sweden; Diakonhjemmet Hospital, Department of Rheumatology, National Advisory Unit on Rehabilitation in Rheumatology, Oslo, Norway.
| | - A Turkiewicz
- Lund University, Faculty of Medicine, Department of Clinical Sciences Lund, Orthopaedics, Clinical Epidemiology Unit, Lund, Sweden.
| | - M Englund
- Lund University, Faculty of Medicine, Department of Clinical Sciences Lund, Orthopaedics, Clinical Epidemiology Unit, Lund, Sweden; Clinical Epidemiology Research and Training Unit, Boston University School of Medicine, Boston, MA, USA.
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218
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Reply to Moossavi and Azad, "Quantifying and Interpreting the Association between Early-Life Gut Microbiota Composition and Childhood Obesity". mBio 2019; 10:mBio.00047-19. [PMID: 30755504 PMCID: PMC6372791 DOI: 10.1128/mbio.00047-19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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219
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Kong X, Xing X, Zhang X, Hong J, Yang W. Sexual Dimorphism of a Genetic Risk Score for Obesity and Related Traits among Chinese Patients with Type 2 Diabetes. Obes Facts 2019; 12:328-343. [PMID: 31167208 PMCID: PMC6696887 DOI: 10.1159/000500490] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2019] [Accepted: 04/16/2019] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Obesity is more prevalent in men than in women in China, especially within the middle-aged population. OBJECTIVES The present study aims to determine the contribution of sexual dimorphisms to obesity and related traits in terms of the mechanisms involving the obesity-related genetic variants among patients of Chinese Han ancestry with type 2 diabetes. METHOD In the Chinese National Diabetes and Metabolic Disorders Study, 2,555 out of 4,036 patients with type 2 diabetes were treatment naive, including 1,142 men and 1,413 women. Single-nucleotide polymorphisms (SNP) from 18 genomic loci previously found to be associated with obesity-related traits were successfully genotyped, and a genetic risk score (GRS) was constructed by summing the risk alleles for obesity. RESULTS Single SNP analysis showed that genetic variants in SLC30A10, TMEM18, GNPDA2, PRL, TFAP2B, BDNF, MTCH2, FTO, and MC4R were nominally associated with waist circumference (WC), BMI, and risk for abdominal or general obesity in the untreated patients with type 2 diabetes, as well as in the total group of patients with type 2 diabetes (untreated and treated) (p < 0.05). Interactions between sex and SNP in PRL, MTCH2,and FTO were detected (p < 0.05). In the untreated patients with diabetes, the GRS was nominally associated with WC (β = 0.0032, SE = 0.0011; p = 0.003), BMI (β = 0.0030, SE = 0.0013; p = 0.027), and increased risk for abdominal (OR = 1.08; 95% CI 1.02-1.13; p = 0.004) or general obesity (OR = 1.07; 95% CI 1.02-1.13; p = 0.011) in men but not in women. GRS-sex interactions were detected in the determinant of WC (p = 0.019) and abdominal obesity (p = 0.016). Among patients aged 30-60 years, GRS was found to be significantly associated with WC (β = 0.0050, SE = 0.0016; p = 0.002) and abdominal obesity (OR = 1.10; 95% CI 1.04-1.17; p = 0.001) and nominally associated with BMI (β = 0.0057, SE = 0.0020; p = 0.005) and general obesity (OR = 1.07; 95% CI 1.01-1.14; p = 0.027) in men, whereas in women none of the associations were detected. GRS-sex interactions were present in the determinant of WC (p = 0.015), BMI (p = 0.032), and abdominal obesity (p = 0.012). Among patients aged 60 years or older, neither an association of GRS with obesity-related traits nor GRS-sex interactions were detected. CONCLUSIONS Genetic factors contribute to obesity-related traits in a sex-dependent pattern among middle-aged Chinese, and men tend to be more susceptible to the genetic risk of obesity.
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Affiliation(s)
- Xiaomu Kong
- Department of Endocrinology, China-Japan Friendship Hospital, Beijing, China
| | - Xiaoyan Xing
- Department of Endocrinology, China-Japan Friendship Hospital, Beijing, China
| | - Xuelian Zhang
- Department of Endocrinology, China-Japan Friendship Hospital, Beijing, China
| | - Jing Hong
- Department of Endocrinology, China-Japan Friendship Hospital, Beijing, China
| | - Wenying Yang
- Department of Endocrinology, China-Japan Friendship Hospital, Beijing, China,
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220
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Pereira S, Katzmarzyk PT, Hedeker D, Maia J. Change and Stability in Sibling Resemblance in Obesity Markers: The Portuguese Sibling Study on Growth, Fitness, Lifestyle, and Health. J Obes 2019; 2019:2432131. [PMID: 31827922 PMCID: PMC6886354 DOI: 10.1155/2019/2432131] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Accepted: 10/19/2019] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND/OBJECTIVES Obesity markers evolve over time and these changes are shared within the family orbit and governed by individual and environmental characteristics. Available reports often lack an integrated approach, in contrast to a multilevel framework that considers their concurrent influence. Hence, this study aims to (1) describe mean changes in obesity markers (body fat (%BF), body mass index (BMI), and waist circumference (WC)) across sib-ships; (2) analyze tracking of individuals within their sib-ship in these markers during 2 years of follow-up; (3) probe consistency in sibling resemblance in these markers; and (4) analyze the joint influence of individual and familial characteristics in these markers. SUBJECTS/METHODS The sample comprises 168 biological Portuguese siblings (brother-brother (BB), sister-sister (SS), and brother-sister (BS)) aged 9-17 years. %BF, BMI, and WC were measured using standardized protocols, and biological maturation was assessed. Physical activity, diet, screen time, and familial characteristics were obtained by questionnaires. Multilevel models were used to analyze the clustered longitudinal data. Sibling resemblance was estimated with the intraclass correlation. RESULTS On average, all sib types increased in BMI and WC over 2 years of follow-up, and SS pairs increased in %BF. Individuals within sib-ships track high in all obesity markers across time. Consistency in siblings' resemblance was also noted, except for BB pairs in %BF which decreased at follow-up. More maturing siblings tend to have higher values in all markers. Greater screen time was associated with higher %BF, whereas those consuming more sugary drinks had lower %BF and BMI values. Siblings whose mothers had less qualified occupations tended to have lower BMI values. CONCLUSIONS Longitudinal individual tracking and sibling resemblance for obesity markers were found. Yet, different trajectories were also identified depending on the marker and sib type. Individual and familial characteristics exert different influences on each obesity marker.
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Affiliation(s)
- Sara Pereira
- CIFI2D, Faculty of Sport, University of Porto, Porto 4200-450, Portugal
| | - Peter T. Katzmarzyk
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA 70808, USA
| | - Donald Hedeker
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
| | - José Maia
- CIFI2D, Faculty of Sport, University of Porto, Porto 4200-450, Portugal
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221
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Qasim A, Mayhew AJ, Ehtesham S, Alyass A, Volckmar AL, Herpertz S, Hinney A, Hebebrand J, Meyre D. Gain-of-function variants in the melanocortin 4 receptor gene confer susceptibility to binge eating disorder in subjects with obesity: a systematic review and meta-analysis. Obes Rev 2019; 20:13-21. [PMID: 30306707 DOI: 10.1111/obr.12761] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Revised: 07/20/2018] [Accepted: 08/02/2018] [Indexed: 01/21/2023]
Abstract
The association between coding variants in the melanocortin 4 receptor gene (MC4R) and binge eating disorder (BED) in patients with obesity is controversial. Two independent reviewers systematically searched MEDLINE, Embase, PsycINFO, BIOSIS Previews, Web of Science Core Collection and Google Scholar up to February 2018, using terms describing the MC4R gene and BED. Six of 103 identified references were included. Studies examined associations between at least one coding variant/mutation in MC4R and BED and screened for BED as per the Diagnostic and Statistical Manual of Mental Disorders. Risk of bias was assessed using a modified version of the Q-Genie tool, and overall quality of evidence was assessed using Grading of Recommendations Assessment, Development and Evaluation guidance. Meta-analysis was conducted via logistic regression models. A positive association between gain-of-function (GOF) variants in the MC4R and BED was observed (odds ratio [OR] = 3.05; 95% confidence interval [CI]: 1.82, 5.04; p = 1.7 × 10-5 ), while no association was detected between loss-of-function (LOF) mutations and BED (OR = 1.50; 95% CI: 0.73, 2.96; p = 0.25). Similar results were found after accounting for study quality (GOF variants: OR = 3.15; 95% CI: 1.76, 5.66; p = 1.1 × 10-4 ; LOF mutations: OR = 1.50; 95% CI: 0.73, 2.97; p = 0.25). Our systematic review and meta-analysis provides evidence that GOF variants as opposed to LOF mutations in MC4R are associated with BED in subjects with obesity.
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Affiliation(s)
- A Qasim
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - A J Mayhew
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - S Ehtesham
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - A Alyass
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - A-L Volckmar
- Department of Child and Adolescent Psychiatry, University Hospital Essen, University of Duisburg - Essen, Essen, Germany
| | - S Herpertz
- Department of Psychosomatic Medicine and Psychotherapy, LWL University Clinic, Ruhr University Bochum, Bochum, Germany
| | - A Hinney
- Department of Child and Adolescent Psychiatry, University Hospital Essen, University of Duisburg - Essen, Essen, Germany
| | - J Hebebrand
- Department of Child and Adolescent Psychiatry, University Hospital Essen, University of Duisburg - Essen, Essen, Germany
| | - D Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
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222
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Hollensted M, Fogh M, Schnurr TM, Kloppenborg JT, Have CT, Ruest Haarmark Nielsen T, Rask J, Asp Vonsild Lund M, Frithioff-Bøjsøe C, Østergaard Johansen M, Vincent Rosenbaum Appel E, Mahendran Y, Grarup N, Kadarmideen HN, Pedersen O, Holm JC, Hansen T. Genetic Susceptibility for Childhood BMI has no Impact on Weight Loss Following Lifestyle Intervention in Danish Children. Obesity (Silver Spring) 2018; 26:1915-1922. [PMID: 30460774 DOI: 10.1002/oby.22308] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Accepted: 08/10/2018] [Indexed: 01/27/2023]
Abstract
OBJECTIVE This study aimed to investigate the effect of a genetic risk score (GRS) comprising 15 single-nucleotide polymorphisms, previously shown to associate with childhood BMI, on the baseline cardiometabolic traits and the response to a lifestyle intervention in Danish children and adolescents. METHODS Children and adolescents with overweight or obesity (n = 920) and a population-based control sample (n = 698) were recruited. Anthropometric and biochemical measures were obtained at baseline and in a subgroup of children and adolescents with overweight or obesity again after 6 to 24 months of lifestyle intervention (n = 754). The effects of the GRS were examined by multiple linear regressions using additive genetic models. RESULTS At baseline, the GRS associated with BMI standard deviation score (SDS) both in children and adolescents with overweight or obesity (β = 0.033 [SE = 0.01]; P = 0.001) and in the population-based sample (β = 0.065 [SE = 0.02]; P = 0.001). No associations were observed for cardiometabolic traits. The GRS did not influence changes in BMI SDS or cardiometabolic traits following lifestyle intervention. CONCLUSIONS A GRS for childhood BMI was associated with BMI SDS but not with other cardiometabolic traits in Danish children and adolescents. The GRS did not influence treatment response following lifestyle intervention.
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Affiliation(s)
- Mette Hollensted
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- The Danish Diabetes Academy, Odense, Denmark
| | - Mette Fogh
- The Children's Obesity Clinic, Department of Pediatrics, Copenhagen University Hospital Holbaek, Holbaek, Denmark
- Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
| | - Theresia M Schnurr
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- The Danish Diabetes Academy, Odense, Denmark
| | - Julie T Kloppenborg
- The Children's Obesity Clinic, Department of Pediatrics, Copenhagen University Hospital Holbaek, Holbaek, Denmark
| | - Christian T Have
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Tenna Ruest Haarmark Nielsen
- The Children's Obesity Clinic, Department of Pediatrics, Copenhagen University Hospital Holbaek, Holbaek, Denmark
| | - Johanne Rask
- The Children's Obesity Clinic, Department of Pediatrics, Copenhagen University Hospital Holbaek, Holbaek, Denmark
| | - Morten Asp Vonsild Lund
- The Children's Obesity Clinic, Department of Pediatrics, Copenhagen University Hospital Holbaek, Holbaek, Denmark
- Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Christine Frithioff-Bøjsøe
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- The Children's Obesity Clinic, Department of Pediatrics, Copenhagen University Hospital Holbaek, Holbaek, Denmark
| | - Mia Østergaard Johansen
- The Children's Obesity Clinic, Department of Pediatrics, Copenhagen University Hospital Holbaek, Holbaek, Denmark
| | | | - Yuvaraj Mahendran
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Haja N Kadarmideen
- Department of Bio and Health Informatics, Section of Systems Genomics, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Jens-Christian Holm
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- The Children's Obesity Clinic, Department of Pediatrics, Copenhagen University Hospital Holbaek, Holbaek, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
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223
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Schrempft S, van Jaarsveld CHM, Fisher A, Herle M, Smith AD, Fildes A, Llewellyn CH. Variation in the Heritability of Child Body Mass Index by Obesogenic Home Environment. JAMA Pediatr 2018; 172:1153-1160. [PMID: 30285028 PMCID: PMC6396810 DOI: 10.1001/jamapediatrics.2018.1508] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Accepted: 04/23/2018] [Indexed: 12/24/2022]
Abstract
Importance The early obesogenic home environment is consistently identified as a key influence on child weight trajectories, but little research has examined the mechanisms of that influence. Such research is essential for the effective prevention and treatment of overweight and obesity. Objective To test behavioral susceptibility theory's hypothesis that the heritability of body mass index (BMI) is higher among children who live in more obesogenic home environments. Design, Setting, and Participants This study was a gene-environment interaction twin study that used cross-sectional data from 925 families (1850 twins) in the Gemini cohort (a population-based prospective cohort of twins born in England and Wales between March and December 2007). Data were analyzed from July to October 2013 and in June 2018. Exposures Parents completed the Home Environment Interview, a comprehensive measure of the obesogenic home environment in early childhood. Three standardized composite scores were created to capture food, physical activity, and media-related influences in the home; these were summed to create an overall obesogenic risk score. The 4 composite scores were split on the mean, reflecting higher-risk and lower-risk home environments. Main Outcomes and Measures Quantitative genetic model fitting was used to estimate heritability of age-adjusted and sex-adjusted BMI (BMI SD score, estimated using British 1990 growth reference data) for children living in lower-risk and higher-risk home environments. Results Among 1850 twins (915 [49.5%] male and 935 [50.5%] female; mean [SD] age, 4.1 [0.4] years), the heritability of BMI SD score was significantly higher among children living in overall higher-risk home environments (86%; 95% CI, 68%-89%) compared with those living in overall lower-risk home environments (39%; 95% CI, 21%-57%). The findings were similar when examining the heritability of BMI in the separate food and physical activity environment domains. Conclusions and Relevance These findings support the hypothesis that obesity-related genes are more strongly associated with BMI in more obesogenic home environments. Modifying the early home environment to prevent weight gain may be particularly important for children genetically at risk for obesity.
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Affiliation(s)
- Stephanie Schrempft
- Department of Behavioural Science and Health, University College London, London, United Kingdom
| | - Cornelia H. M. van Jaarsveld
- Departments for Health Evidence and Primary and Community Care, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Abigail Fisher
- Department of Behavioural Science and Health, University College London, London, United Kingdom
| | - Moritz Herle
- University College London Great Ormond Street Institute of Child Health, London, United Kingdom
| | - Andrea D. Smith
- Department of Behavioural Science and Health, University College London, London, United Kingdom
| | - Alison Fildes
- School of Psychology, University of Leeds, Leeds, United Kingdom
| | - Clare H. Llewellyn
- Department of Behavioural Science and Health, University College London, London, United Kingdom
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224
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Monsivais P, Francis O, Lovelace R, Chang M, Strachan E, Burgoine T. Data visualisation to support obesity policy: case studies of data tools for planning and transport policy in the UK. Int J Obes (Lond) 2018; 42:1977-1986. [PMID: 30470805 PMCID: PMC6291420 DOI: 10.1038/s41366-018-0243-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Revised: 09/14/2018] [Accepted: 10/21/2018] [Indexed: 11/13/2022]
Abstract
Data visualisation is becoming an established way to drive discovery and develop theory and hypotheses among researchers. Data visualisations can also serve as tools for knowledge translation with policy makers, who are increasingly using data and evidence to inform and implement policy. For obesity policy, data visualisation tools can help policy makers and other professionals understand the socio-spatial distribution of risk factors and quantify social and environmental conditions that are recognised upstream determinants of diet, activity and obesity. The demand for and use of data visualisation tools can be driven by an identified policy need, which can be met by researchers and data scientists. Alternatively, researchers are developing and testing data visualisations, which may be subsequently adapted for, and adopted by policy users.Two recently-released interactive data visualisation tools in the UK illustrate these points. The Propensity to Cycle Tool (PCT) was developed with funding from the UK government to inform the investment of cycling infrastructure in England. The Food environment assessment tool (Feat) evolved as a translational output from a programme of epidemiological research. This article uses PCT and Feat as case studies, drawing parallels and contrasts between them. We discuss these two tools from policy context and scientific underpinnings, to product launch and evaluation. We review challenges inherent in the development and dissemination of data tools for policy, including the need for technical expertise, feedback integration, long-term sustainability, and provision of training and user support. Finally, we attempt to derive learning points that may help overcome challenges associated with the creation, dissemination and sustaining of data tools for policy. We contend that, despite a number of challenges, data tools provide a novel gateway between researchers and a range of stakeholders, who are seeking ways of accessing and using evidence to inform obesity programs and policies.
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Affiliation(s)
- Pablo Monsivais
- UKCRC Centre for Diet and Activity Research (CEDAR), MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
- Department of Nutrition and Exercise Physiology, Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, 99210, USA.
| | - Oliver Francis
- UKCRC Centre for Diet and Activity Research (CEDAR), MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - Robin Lovelace
- Institute for Transport Studies, University of Leeds, Leeds, LS2 9JT, UK
| | - Michael Chang
- Town & Country Planning Association, London, SW1Y 5AS, UK
- Carnegie School of Sport, Leeds Beckett University, Leeds, LS6 3QT, UK
| | - Emma Strachan
- Health Improvement, Leeds City Council, Leeds, LS2 9JT, UK
| | - Thomas Burgoine
- UKCRC Centre for Diet and Activity Research (CEDAR), MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
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225
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Faith MS, Epstein LH. Healthy Homes and Obesogenic Genes in Young Children: Rigorous Behavioral Theory and Measurement and the Detection of Gene-Environment Interactions. JAMA Pediatr 2018; 172:1121-1122. [PMID: 30285036 DOI: 10.1001/jamapediatrics.2018.1945] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Affiliation(s)
- Myles S Faith
- Department of Counseling, School and Educational Psychology, Graduate School of Education, University at Buffalo, State University of New York
| | - Leonard H Epstein
- Department of Pediatrics, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York
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226
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Lieske JC, Wang X. Heritable traits that contribute to nephrolithiasis. Urolithiasis 2018; 47:5-10. [PMID: 30460525 DOI: 10.1007/s00240-018-1095-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Accepted: 11/08/2018] [Indexed: 02/07/2023]
Abstract
Urinary stones tend to cluster in families. Of the known risk factors, evidence is strongest for heritability of urinary calcium excretion. Recent studies suggest that other stone risk factors may have heritable components including urinary pH, citrate and magnesium excretion, and circulating vitamin D concentration. Several risk factors assumed purely environmental may also have heritable components, including dietary intake and thirst. Thus, future studies may reveal that genetics plays an even stronger role in urinary stone pathogenesis than previously known.
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Affiliation(s)
- John C Lieske
- Division of Nephrology and Hypertension, Mayo Clinic, 200 First Street SW, Rochester, MN, 55901, USA. .,Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
| | - Xiangling Wang
- Genomic Medicine Institute, Department of Nephrology and Hypertension, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
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227
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Evidence for gene-environment correlation in child feeding: Links between common genetic variation for BMI in children and parental feeding practices. PLoS Genet 2018; 14:e1007757. [PMID: 30457987 PMCID: PMC6245504 DOI: 10.1371/journal.pgen.1007757] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Accepted: 10/11/2018] [Indexed: 12/11/2022] Open
Abstract
The parental feeding practices (PFPs) of excessive restriction of food intake (‘restriction’) and pressure to increase food consumption (‘pressure’) have been argued to causally influence child weight in opposite directions (high restriction causing overweight; high pressure causing underweight). However child weight could also ‘elicit’ PFPs. A novel approach is to investigate gene-environment correlation between child genetic influences on BMI and PFPs. Genome-wide polygenic scores (GPS) combining BMI-associated variants were created for 10,346 children (including 3,320 DZ twin pairs) from the Twins Early Development Study using results from an independent genome-wide association study meta-analysis. Parental ‘restriction’ and ‘pressure’ were assessed using the Child Feeding Questionnaire. Child BMI standard deviation scores (BMI-SDS) were calculated from children’s height and weight at age 10. Linear regression and fixed family effect models were used to test between- (n = 4,445 individuals) and within-family (n = 2,164 DZ pairs) associations between the GPS and PFPs. In addition, we performed multivariate twin analyses (n = 4,375 twin pairs) to estimate the heritabilities of PFPs and the genetic correlations between BMI-SDS and PFPs. The GPS was correlated with BMI-SDS (β = 0.20, p = 2.41x10-38). Consistent with the gene-environment correlation hypothesis, child BMI GPS was positively associated with ‘restriction’ (β = 0.05, p = 4.19x10-4), and negatively associated with ‘pressure’ (β = -0.08, p = 2.70x10-7). These results remained consistent after controlling for parental BMI, and after controlling for overall family contributions (within-family analyses). Heritabilities for ‘restriction’ (43% [40–47%]) and ‘pressure’ (54% [50–59%]) were moderate-to-high. Twin-based genetic correlations were moderate and positive between BMI-SDS and ‘restriction’ (rA = 0.28 [0.23–0.32]), and substantial and negative between BMI-SDS and ‘pressure’ (rA = -0.48 [-0.52 - -0.44]. Results suggest that the degree to which parents limit or encourage children’s food intake is partly influenced by children’s genetic predispositions to higher or lower BMI. These findings point to an evocative gene-environment correlation in which heritable characteristics in the child elicit parental feeding behaviour. It is widely believed that parents influence their child’s BMI via certain feeding practices. For example, rigid restriction has been argued to cause overweight, and pressuring to eat to cause underweight. However, recent longitudinal research has not supported this model. An alternative hypothesis is that child BMI, which has a strong genetic basis, evokes parental feeding practices (‘gene-environment correlation’). To test this, we applied two genetic methods in a large sample of 10-year-old children from the Twins Early Development Study: a polygenic score analysis (DNA-based score of common genetic variants associated with BMI in genome-wide meta-analyses), and a twin analysis (comparing resemblance between identical and non-identical twin pairs). Polygenic scores correlated positively with parental restriction of food intake (‘restriction’; β = 0.05, p = 4.19x10-4), and negatively with parental pressure to increase food intake (‘pressure’; β = -0.08, p = 2.70x10-7). Associations were unchanged after controlling for all genetic and environmental effects shared within families. Results from twin analyses were consistent. ‘Restriction’ (43%) and ‘pressure’ (54%) were substantially heritable, and a positive genetic correlation between child BMI and ‘restriction’ (rA = 0.28), and negative genetic correlation between child BMI and ‘pressure’ (rA = -0.48) emerged. These findings challenge the prevailing view that parental behaviours are the sole cause of child BMI by supporting an alternate hypothesis that child BMI also causes parental feeding behaviour.
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228
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Shrestha D, Rahman ML, Workalemahu T, Zhu C, Tekola-Ayele F. Influence of Fetal and Maternal Genetic Susceptibility to Obesity on Birthweight in African Ancestry Populations. Front Genet 2018; 9:511. [PMID: 30450111 PMCID: PMC6224338 DOI: 10.3389/fgene.2018.00511] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2018] [Accepted: 10/12/2018] [Indexed: 02/02/2023] Open
Abstract
Fetal and maternal genetic propensity to obesity can influence birthweight. We investigated the effects of fetal and maternal genetic risk of obesity on birthweight and evaluated whether these genetic influences modify the well-known association between maternal pre-pregnancy body mass index (BMI) and birthweight. In 950 mother-baby pairs of African ancestry, a genetic risk score for adulthood obesity was generated for mothers (mGRS) and their babies (bGRS) as the weighted sum of BMI-increasing alleles of 97 single nucleotide polymorphisms known to be associated with BMI. The median GRS value was used as a cut-off to define high or low bGRS and mGRS. High bGRS was significantly associated with 70 g lower birthweight (95% Confidence Interval [CI] = −127.4 to −12.4) compared to low bGRS. mGRS was positively correlated with birthweight but the association was not significant. mGRS modified the significant birthweight-increasing effect of maternal pre-pregnancy BMI (P-for-interaction = 0.03); among mothers with low mGRS, those who were overweight or obese had 127.7 g heavier babies (95% CI = 27.1 to 228.2) compared to those who had normal weight. In summary, fetal obesity genetic risk loci exert direct influence on birthweight, and maternal loci modify the effect of pre-pregnancy BMI on birthweight.
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Affiliation(s)
- Deepika Shrestha
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States
| | - Mohammad L Rahman
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States
| | - Tsegaselassie Workalemahu
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States
| | - Chunming Zhu
- Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States
| | - Fasil Tekola-Ayele
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States
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229
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Boswell N, Byrne R, Davies PSW. Aetiology of eating behaviours: A possible mechanism to understand obesity development in early childhood. Neurosci Biobehav Rev 2018; 95:438-448. [PMID: 30391377 DOI: 10.1016/j.neubiorev.2018.10.020] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2018] [Revised: 10/24/2018] [Accepted: 10/28/2018] [Indexed: 11/15/2022]
Abstract
Childhood obesity is an issue of public health concern that is understood to emerge due to disequilibrium in energy homeostasis. This commentary explores literature regarding neuro-biological mechanisms of energy homeostasis and the relationship between subjective measures of children's eating behaviours and objective measures of appetite, in order to better understand the aetiology of childhood obesity. Early life influences, such as in utero exposure, breastfeeding, and general disadvantage, appear to have an important influence on neuro-biological mechanisms of appetite and may contribute to inequitable distributions of obesity within the population. Subject measures of eating behaviours appear to capture various aspects of neuro-biologically driven (objective) appetite systems, however, these systems are complex, interdependent and not yet fully understood. Future research focusing attention on early life influences on appetite and eating behaviours is warranted to increase understanding of differences in rates of obesity within the population, to determine opportunities for targeted obesity prevention initiatives, and to explore the potential to measure change in eating behaviours as a marker of appetite and obesity risk.
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Affiliation(s)
- Nikki Boswell
- The University of Queensland, Brisbane QLD, Australia.
| | - Rebecca Byrne
- Queensland University of Technology, Brisbane QLD, Australia.
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230
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León-Mimila P, Villamil-Ramírez H, López-Contreras BE, Morán-Ramos S, Macias-Kauffer LR, Acuña-Alonzo V, Del Río-Navarro BE, Salmerón J, Velazquez-Cruz R, Villarreal-Molina T, Aguilar-Salinas CA, Canizales-Quinteros S. Low Salivary Amylase Gene ( AMY1) Copy Number Is Associated with Obesity and Gut Prevotella Abundance in Mexican Children and Adults. Nutrients 2018; 10:nu10111607. [PMID: 30388780 PMCID: PMC6266693 DOI: 10.3390/nu10111607] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Revised: 10/20/2018] [Accepted: 10/23/2018] [Indexed: 12/22/2022] Open
Abstract
Genome-wide association studies (GWAS) have identified copy number variants (CNVs) associated with obesity in chromosomal regions 1p31.1, 10q11.22, 11q11, 16p12.3, and recently 1p21.1, which contains the salivary amylase gene (AMY1). Recent evidence suggests this enzyme may influence gut microbiota composition through carbohydrate (mainly starch) degradation. The role of these CNVs in obesity has been scarcely explored in the Latino population, and thus the aim of our study was to evaluate the association of 1p31.1, 10q11.22, 11q11, 16p12.3 and 1p21.1 CNVs with obesity in 921 Mexican children, to replicate significant associations in 920 Mexican adults, and to analyze the association of AMY1 copy number with gut microbiota in 75 children and 45 adults. Of the five CNVs analyzed, 1q11 CNV was significantly associated with obesity in children, but not in adults. Only AMY1 CNV was significantly associated with obesity in both age groups. Moreover, gut microbiota analyses revealed a positive correlation between AMY1 copy number and Prevotella abundance. This genus has enzymes and gene clusters essential for complex polysaccharide degradation and utilization. To our knowledge, this is the first study to analyze the association of these five CNVs in the Mexican population and to report a correlation between AMY1 CN and gut microbiota in humans.
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Affiliation(s)
- Paola León-Mimila
- Facultad de Química, Unidad de Genómica de Poblaciones Aplicada a la Salud, Universidad Nacional Autónoma de México (UNAM)/Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City 14610, Mexico.
| | - Hugo Villamil-Ramírez
- Facultad de Química, Unidad de Genómica de Poblaciones Aplicada a la Salud, Universidad Nacional Autónoma de México (UNAM)/Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City 14610, Mexico.
| | - Blanca E López-Contreras
- Facultad de Química, Unidad de Genómica de Poblaciones Aplicada a la Salud, Universidad Nacional Autónoma de México (UNAM)/Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City 14610, Mexico.
| | - Sofía Morán-Ramos
- Facultad de Química, Unidad de Genómica de Poblaciones Aplicada a la Salud, Universidad Nacional Autónoma de México (UNAM)/Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City 14610, Mexico.
- Consejo Nacional de Ciencia y Tecnología (CONACYT), Mexico City 03940, Mexico.
| | - Luis R Macias-Kauffer
- Facultad de Química, Unidad de Genómica de Poblaciones Aplicada a la Salud, Universidad Nacional Autónoma de México (UNAM)/Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City 14610, Mexico.
| | - Víctor Acuña-Alonzo
- Escuela Nacional de Antropología e Historia, Laboratorio de genética molecular, Mexico City 14030, Mexico.
| | - Blanca E Del Río-Navarro
- Departamento de Alergia e Inmunología Clínica, Hospital Infantil de México Federico Gómez, Mexico City 06720, Mexico.
| | - Jorge Salmerón
- Unidad Académica de Investigación Epidemiológica del Centro de Investigación en Políticas, Población y Salud, Facultad de Medicina-UNAM, Mexico City 04510, Mexico.
| | | | | | - Carlos A Aguilar-Salinas
- Unidad de Investigación en Enfermedades Metabólicas and Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City 14000, Mexico.
- Tecnológico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Monterrey, Nuevo León 64710, Mexico.
| | - Samuel Canizales-Quinteros
- Facultad de Química, Unidad de Genómica de Poblaciones Aplicada a la Salud, Universidad Nacional Autónoma de México (UNAM)/Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City 14610, Mexico.
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231
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Leońska-Duniec A, Jastrzębski Z, Zarębska A, Maciejewska A, Ficek K, Cięszczyk P. Assessing effect of interaction between the FTO A/T polymorphism (rs9939609) and physical activity on obesity-related traits. JOURNAL OF SPORT AND HEALTH SCIENCE 2018; 7:459-464. [PMID: 30450255 PMCID: PMC6226419 DOI: 10.1016/j.jshs.2016.08.013] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 11/03/2015] [Revised: 06/02/2016] [Accepted: 08/10/2016] [Indexed: 06/09/2023]
Abstract
BACKGROUND The first described obesity-susceptibility gene was the fat mass and obesity-associated (FTO) gene. However, knowledge about FTO's potential modifying effect on changes in body weight achieved through a training program is still limited. We decided to study the association between the FTO A/T polymorphism (rs9939609) and obesity-related traits. Additionally, we investigated whether body mass and body composition, as well as metabolic variables observed in physically active participants, are modulated by the FTO polymorphism. METHODS A group of 201 young Polish women were recruited for the study. The genotype distribution was examined in participants measured for selected changes before and after the completion of a 12-week training program. RESULTS Our results confirm the association between the common FTO A/T polymorphism and increased body mass index (BMI). Subjects with AA and AT genotypes had higher BMI during the entire study period compared with the TT genotype. Although parameters such as BMI, basal metabolism rate, tissue independence, fat mass percentage, fat mass, fat-free mass, total body water, high-density lipoprotein, and glucose changed significantly during the training program, none of the examined parameters changed significantly across the FTO genotypes (genotype × training interaction). CONCLUSION We confirm an association between the FTO A/T polymorphism and increased BMI; this polymorphism is therefore a candidate for influencing obesity and other disease-related phenotypes. Although the gene × physical activity interaction was not shown, we want to point out that promoting physical activity is an important approach to controlling the increasing obesity epidemic.
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Affiliation(s)
- Agata Leońska-Duniec
- Faculty of Physical Culture and Health Promotion, Centre for Human Structural and Functional Research, University of Szczecin, Szczecin 71-065, Poland
- Faculty of Tourism and Recreation, Gdansk University of Physical Education and Sport, Gdańsk 80-336, Poland
| | - Zbigniew Jastrzębski
- Faculty of Tourism and Recreation, Gdansk University of Physical Education and Sport, Gdańsk 80-336, Poland
| | - Aleksandra Zarębska
- Faculty of Tourism and Recreation, Gdansk University of Physical Education and Sport, Gdańsk 80-336, Poland
| | - Agnieszka Maciejewska
- Faculty of Physical Culture and Health Promotion, Centre for Human Structural and Functional Research, University of Szczecin, Szczecin 71-065, Poland
- Faculty of Physical Education, Gdansk University of Physical Education and Sport, Gdańsk 80-336, Poland
| | | | - Paweł Cięszczyk
- Faculty of Physical Culture and Health Promotion, Centre for Human Structural and Functional Research, University of Szczecin, Szczecin 71-065, Poland
- Faculty of Physical Education, Gdansk University of Physical Education and Sport, Gdańsk 80-336, Poland
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232
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Pinho S, Padez C, Manco L. High AMY1 copy number protects against obesity in Portuguese young adults. Ann Hum Biol 2018; 45:435-439. [DOI: 10.1080/03014460.2018.1490452] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Affiliation(s)
- Simão Pinho
- Research Centre for Anthropology and Health (CIAS), University of Coimbra, Coimbra, Portugal
| | - Cristina Padez
- Research Centre for Anthropology and Health (CIAS), University of Coimbra, Coimbra, Portugal
- Department of Life Sciences, University of Coimbra, Coimbra, Portugal
| | - Licínio Manco
- Research Centre for Anthropology and Health (CIAS), University of Coimbra, Coimbra, Portugal
- Department of Life Sciences, University of Coimbra, Coimbra, Portugal
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233
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Albuquerque D, González LM, Ferrer FG, Bruna M, Sánchez C, Benito GM, Rodríguez-López R, Manco L. Association study of six single nucleotide polymorphisms with obesity in two independent Iberian samples. Meta Gene 2018. [DOI: 10.1016/j.mgene.2018.04.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022] Open
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234
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Llewellyn CH. Genetic susceptibility to the "obesogenic" environment: the role of eating behavior in obesity and an appetite for change. Am J Clin Nutr 2018; 108:429-430. [PMID: 30124743 DOI: 10.1093/ajcn/nqy210] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Affiliation(s)
- Clare H Llewellyn
- Department of Behavioural Science & Health, University College London, London, United Kingdom
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235
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Abstract
Obesity is a widespread heritable health condition. Evidence from psychology, cognitive neuroscience, and genetics has proposed links between obesity and the brain. The current study tested whether the heritable variance in body mass index (BMI) is explained by brain and behavioral factors in a large brain imaging cohort that included multiple related individuals. We found that the heritable variance in BMI had genetic correlations 0.25–0.45 with cognitive tests, cortical thickness, and regional brain volume. In particular, BMI was associated with frontal lobe asymmetry and differences in temporal-parietal perceptual systems. Further, we found genetic overlap between certain brain and behavioral factors. In summary, the genetic vulnerability to BMI is expressed in the brain. This may inform intervention strategies. Recent molecular genetic studies have shown that the majority of genes associated with obesity are expressed in the central nervous system. Obesity has also been associated with neurobehavioral factors such as brain morphology, cognitive performance, and personality. Here, we tested whether these neurobehavioral factors were associated with the heritable variance in obesity measured by body mass index (BMI) in the Human Connectome Project (n = 895 siblings). Phenotypically, cortical thickness findings supported the “right brain hypothesis” for obesity. Namely, increased BMI is associated with decreased cortical thickness in right frontal lobe and increased thickness in the left frontal lobe, notably in lateral prefrontal cortex. In addition, lower thickness and volume in entorhinal-parahippocampal structures and increased thickness in parietal-occipital structures in participants with higher BMI supported the role of visuospatial function in obesity. Brain morphometry results were supported by cognitive tests, which outlined a negative association between BMI and visuospatial function, verbal episodic memory, impulsivity, and cognitive flexibility. Personality–BMI correlations were inconsistent. We then aggregated the effects for each neurobehavioral factor for a behavioral genetics analysis and estimated each factor’s genetic overlap with BMI. Cognitive test scores and brain morphometry had 0.25–0.45 genetic correlations with BMI, and the phenotypic correlations with BMI were 77–89% explained by genetic factors. Neurobehavioral factors also had some genetic overlap with each other. In summary, obesity as measured by BMI has considerable genetic overlap with brain and cognitive measures. This supports the theory that obesity is inherited via brain function and may inform intervention strategies.
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236
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Speakman JR, Loos RJF, O'Rahilly S, Hirschhorn JN, Allison DB. GWAS for BMI: a treasure trove of fundamental insights into the genetic basis of obesity. Int J Obes (Lond) 2018; 42:1524-1531. [PMID: 29980761 PMCID: PMC6115287 DOI: 10.1038/s41366-018-0147-5] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2018] [Accepted: 04/10/2018] [Indexed: 01/16/2023]
Abstract
Muller et al. [1] have provided a strong critique of the Genome-Wide Association Studies (GWAS) of body-mass index (BMI), arguing that the GWAS approach for the study of BMI is flawed, and has provided us with few biological insights. They suggest that what is needed instead is a new start, involving GWAS for more complex energy balance related traits. In this invited counter-point, we highlight the substantial advances that have occurred in the obesity field, directly stimulated by the GWAS of BMI. We agree that GWAS for BMI is not perfect, but consider that the best route forward for additional discoveries will likely be to expand the search for common and rare variants linked to BMI and other easily obtained measures of obesity, rather than attempting to perform new, much smaller GWAS for energy balance traits that are complex and expensive to measure. For GWAS in general, we emphasise that the power from increasing the sample size of a crude but easily measured phenotype outweighs the benefits of better phenotyping.
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Affiliation(s)
- J R Speakman
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China.
- Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, Scotland, UK.
| | - R J F Loos
- The Charles Bronfman Insititute for Personalized Medicine at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - S O'Rahilly
- Wellcome Trust-MRC Institute of Metabolic Science,Addenbrookes Treatment, Centre University of Cambridge, Cambridge, CB2 OQQ, UK
| | - J N Hirschhorn
- Division of Endocrinology and Center for Basic and Translational Research, Boston Children's Hospital, Boston, MA, USA
- Broad institute, Cambridge, MA, USA
| | - D B Allison
- School of Public Health, University of Indiana Bloomington, Bloomington, IN, USA
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237
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Chen B, Li Z, Chen J, Ji J, Shen J, Xu Y, Zhao Y, Liu D, Shen Y, Zhang W, Shen J, Wang Y, Shi Y. Association of fat mass and obesity-associated and retinitis pigmentosa guanosine triphosphatase (GTPase) regulator-interacting protein-1 like polymorphisms with body mass index in Chinese women. Endocr J 2018; 65:783-791. [PMID: 29657248 DOI: 10.1507/endocrj.ej17-0554] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Body mass index (BMI) is the most commonly used quantitative measure of adiposity. It is a kind of complex genetic diseases which are caused by multiple susceptibility genes. The first intron of fat mass and obesity-associated (FTO) has been widely discovered to be associated with BMI. Retinitis pigmentosa GTPase regulator-interacting protein-1 like (RPGRIP1L) is located in the upstream region of FTO and has been proved to be linked with obesity through functional tests. We carried out a genetic association analysis to figure out the role of the FTO gene and the RPGRIP1L gene in BMI. A quantitative traits study with 6,102 Chinese female samples, adjusted for age, was performed during our project. Among the twelve SNPs, rs1421085, rs1558902, rs17817449, rs8050136, rs9939609, rs7202296, rs56137030, rs9930506 and rs12149832 in the FTO gene were significantly associated with BMI after Bonferroni correction. Meanwhile, rs9934800 in the RPGRIP1L gene showed significance with BMI before Bonferroni correction, but this association was eliminated after Bonferroni correction. Our results suggested that genetic variants in the FTO gene were strongly associated with BMI in Chinese women, which may serve as targets of pharmaceutical research and development concerning BMI. Meanwhile, we didn't found the significant association between RPGRIP1L and BMI in Chinese women.
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Affiliation(s)
- Boyu Chen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Zhiqiang Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
- The Affiliated Hospital of Qingdao University & The Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao 266003, China
- Institute of Social Cognitive and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai 200240, China
- Institute of Neuropsychiatric Science and Systems Biological Medicine, Shanghai Jiao Tong University, Shanghai 200042, China
| | - Jianhua Chen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
- Institute of Social Cognitive and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai 200240, China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Jue Ji
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Jingyi Shen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Yufeng Xu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Yingying Zhao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Danping Liu
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Yinhuan Shen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Weijie Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Jiawei Shen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Yonggang Wang
- Department of Neurology, School of Medicine, Renji Hospital, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Yongyong Shi
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai 200030, China
- The Affiliated Hospital of Qingdao University & The Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao 266003, China
- Institute of Social Cognitive and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai 200240, China
- Institute of Neuropsychiatric Science and Systems Biological Medicine, Shanghai Jiao Tong University, Shanghai 200042, China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
- Changning Mental Health Center, Shanghai 200042, China
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238
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Wiklund CA, Kuja-Halkola R, Thornton LM, Bälter K, Welch E, Bulik CM. Childhood body mass index and development of eating disorder traits across adolescence. EUROPEAN EATING DISORDERS REVIEW 2018; 26:462-471. [PMID: 29927002 DOI: 10.1002/erv.2612] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Revised: 05/14/2018] [Accepted: 05/23/2018] [Indexed: 01/04/2023]
Abstract
OBJECTIVE Understanding the role of premorbid body mass index (BMI) in the emergence of eating disorders may be key to identifying effective prevention strategies. We explore relations between BMI and eating disorders traits in young twins. METHOD The effect of BMI at age 9/12 and 15 on eating disorder traits measured using the Eating Disorders Inventory-2 (EDI) at ages 15 and 18 was examined using bivariate modelling in a longitudinal population sample of Swedish twins. RESULTS The correlation between BMI and EDI within individuals was stable across all ages and remained significant after adjusting for later BMI. Bivariate analysis indicated significant positive genetic correlations between BMI ages 9/12 and 15 and subsequent EDI scores. The relationship remained significant for BMI age 9/12 and EDI age 15 in the adjusted model, indicating a longitudinal association. CONCLUSION Our results have implications for conceptualizing the interrelation of BMI and eating disorders across childhood and adolescence.
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Affiliation(s)
- Camilla A Wiklund
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ralf Kuja-Halkola
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Laura M Thornton
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Katarina Bälter
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Division of Public Health Sciences, School of Health, Care and Social Welfare, Mälardalen University, Västerås, Sweden
| | - Elisabeth Welch
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Stockholm Center for Eating Disorders, Stockholm, Sweden
| | - Cynthia M Bulik
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
- Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
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239
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Loos RJ. The genetics of adiposity. Curr Opin Genet Dev 2018; 50:86-95. [PMID: 29529423 PMCID: PMC6089650 DOI: 10.1016/j.gde.2018.02.009] [Citation(s) in RCA: 78] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2018] [Revised: 02/09/2018] [Accepted: 02/14/2018] [Indexed: 02/08/2023]
Abstract
Genome-wide discovery efforts have identified more than 500 genetic loci associated with adiposity traits. The vast majority of these loci were found through large-scale meta-analyses for body mass index (BMI) and waist-to-hip ratio (WHR), and in European ancestry populations. However, alternative approaches, focusing on non-European ancestry populations, more refined adiposity measures, and low-frequency (minor allele frequency (MAF)<5%) coding variants, identified additional novel loci that had not been identified before. Loci associated with overall obesity implicate pathways that act in the brain, whereas loci associated with fat distribution point to pathways involved in adipocyte biology. Pinpointing the causal gene within each locus remains challenging, but is a critical step towards translation of genome-wide association study (GWAS) loci into new biology. Ultimately, new genes may provide pharmacological targets for the development of weight loss drugs.
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Affiliation(s)
- Ruth Jf Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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240
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Panzeri I, Pospisilik JA. Epigenetic control of variation and stochasticity in metabolic disease. Mol Metab 2018; 14:26-38. [PMID: 29909200 PMCID: PMC6034039 DOI: 10.1016/j.molmet.2018.05.010] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Revised: 05/11/2018] [Accepted: 05/14/2018] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND The alarming rise of obesity and its associated comorbidities represents a medical burden and a major global health and economic issue. Understanding etiological mechanisms underpinning susceptibility and therapeutic response is of primary importance. Obesity, diabetes, and metabolic diseases are complex trait disorders with only partial genetic heritability, indicating important roles for environmental programing and epigenetic effects. SCOPE OF THE REVIEW We will highlight some of the reasons for the scarce predictability of metabolic diseases. We will outline how genetic variants generate phenotypic variation in disease susceptibility across populations. We will then focus on recent conclusions about epigenetic mechanisms playing a fundamental role in increasing variability and subsequently disease triggering. MAJOR CONCLUSIONS Currently, we are unable to predict or mechanistically define how "missing heritability" drives disease. Unravelling this black box of regulatory processes will allow us to move towards a truly personalized and precision medicine.
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Affiliation(s)
- Ilaria Panzeri
- Max Planck Institute of Immunobiology and Epigenetics, Stuebeweg 51, 79108, Freiburg, Germany
| | - John Andrew Pospisilik
- Max Planck Institute of Immunobiology and Epigenetics, Stuebeweg 51, 79108, Freiburg, Germany.
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241
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Hsueh WC, Bennett PH, Esparza-Romero J, Urquidez-Romero R, Valencia ME, Ravussin E, Williams RC, Knowler WC, Baier LJ, Schulz LO, Hanson RL. Analysis of type 2 diabetes and obesity genetic variants in Mexican Pima Indians: Marked allelic differentiation among Amerindians at HLA. Ann Hum Genet 2018; 82:287-299. [PMID: 29774533 DOI: 10.1111/ahg.12252] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2017] [Revised: 02/11/2018] [Accepted: 03/08/2018] [Indexed: 01/21/2023]
Abstract
Prevalence of diabetes and obesity in Mexican Pima Indians is low, while prevalence in US Pima Indians is high. Although lifestyle likely accounts for much of the difference, the role of genetic factors is not well explored. To examine this, we genotyped 359 single nucleotide polymorphisms, including established type 2 diabetes and obesity variants from genome-wide association studies (GWAS) and 96 random markers, in 342 Mexican Pimas. A multimarker risk score of obesity variants was associated with body mass index (BMI; β = 0.81 kg/m2 per SD, P = 0.0066). The mean value of the score was lower in Mexican Pimas than in US Pimas (P = 4.3 × 10-11 ), and differences in allele frequencies at established loci could account for approximately 7% of the population difference in BMI; however, the difference in risk scores was consistent with evolutionary neutrality given genetic distance. To identify loci potentially under recent natural selection, allele frequencies at 283 variants were compared between US and Mexican Pimas, accounting for genetic distance. The largest differences were seen at HLA markers (e.g., rs9271720, difference = 0.75, P = 8.7 × 10-9 ); genetic distances at HLA were greater than at random markers (P = 1.6 × 10-46 ). Analyses of GWAS data in 937 US Pimas also showed sharing of alleles identical by descent at HLA that exceeds its genomic expectation (P = 7.0 × 10-10 ). These results suggest that, in addition to the widely recognized balancing selection at HLA, recent directional selection may also occur, resulting in marked allelic differentiation between closely related populations.
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Affiliation(s)
- Wen-Chi Hsueh
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Peter H Bennett
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Julian Esparza-Romero
- Departamento de Nutrición Pública y Salud, Coordinación de Nutrición, Centro de Investigación en Alimentación y Desarrollo, Hermosillo, Sonora, México
| | - Rene Urquidez-Romero
- Instituto de Ciencias Biomédicas, Departamento de Ciencias de la Salud, Universidad Autónoma de Ciudad Juárez, Ciudad Juárez, Chihuahua, México
| | - Mauro E Valencia
- Departamento de Nutrición Pública y Salud, Coordinación de Nutrición, Centro de Investigación en Alimentación y Desarrollo, Hermosillo, Sonora, México
| | - Eric Ravussin
- Pennington Biomedical Research Center, Louisiana State University Systems, Baton Rouge, LA, USA
| | - Robert C Williams
- 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
| | - Leslie J Baier
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
| | - Leslie O Schulz
- College of Health and Human Services, Northern Arizona University, Flagstaff, AZ, USA
| | - Robert L Hanson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ, USA
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Wang T, Zhang R, Ma X, Wang S, He Z, Huang Y, Xu B, Li Y, Zhang H, Jiang F, Bao Y, Hu C, Jia W. Causal Association of Overall Obesity and Abdominal Obesity with Type 2 Diabetes: A Mendelian Randomization Analysis. Obesity (Silver Spring) 2018; 26:934-942. [PMID: 29630776 DOI: 10.1002/oby.22167] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Revised: 02/01/2018] [Accepted: 02/14/2018] [Indexed: 12/28/2022]
Abstract
OBJECTIVE This study aimed to compare the causal effect of overall obesity and abdominal obesity on type 2 diabetes among Chinese Han individuals. METHODS The causal relationship of BMI and waist-to-hip ratio (WHR) with the risk of glucose deterioration and glycemic traits was compared using two different genetic instruments based on 30 BMI loci and 6 WHR loci with Mendelian randomization (MR) in three prospective cohorts (n = 6,476). RESULTS Each 1-SD genetically instrumented higher WHR was associated with a 65.7% higher risk of glucose deterioration (95% CI = 1.069-2.569, P = 0.024), whereas no significant association of BMI with glucose deterioration was observed. Furthermore, a causal relationship was found only between BMI and homeostatic model assessment β-cell function (HOMA-B) (β = 0.143, P = 0.001), and there was a nominal association with Stumvoll second-phase insulin secretion traits (β = 0.074, P = 0.022). The significance level did not persist in sensitivity analyses, except in the causal estimate of WHR on the Gutt index in MR-Egger (β = -0.379, P = 0.022) and the causal estimate of BMI on homeostatic model assessment β-cell function in weighted median MR (β = 0.128, P = 0.017). CONCLUSIONS The data from this study support the potential causal relationship between abdominal obesity and hyperglycemia, which may be driven by aggravated insulin resistance, in contrast with the potential causal relationship between overall obesity and insulin secretion.
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Affiliation(s)
- Tao Wang
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Centre for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Rong Zhang
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Centre for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Xiaojing Ma
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Centre for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Shiyun Wang
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Centre for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Zhen He
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Centre for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Yeping Huang
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Centre for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Bo Xu
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Centre for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Yangyang Li
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Centre for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Hong Zhang
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Centre for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Feng Jiang
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Centre for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Yuqian Bao
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Centre for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Cheng Hu
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Centre for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
- Institute for Metabolic Disease, Fengxian Central Hospital Affiliated to Southern Medical University, Shanghai, China
| | - Weiping Jia
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Centre for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
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243
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Is the Association Between Obesity and Hip Osteoarthritis Surgery Explained by Familial Confounding? Epidemiology 2018; 29:414-420. [DOI: 10.1097/ede.0000000000000806] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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244
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Piirtola M, Kaprio J, Waller K, Heikkilä K, Koskenvuo M, Svedberg P, Silventoinen K, Kujala UM, Ropponen A. Leisure-time physical inactivity and association with body mass index: a Finnish Twin Study with a 35-year follow-up. Int J Epidemiol 2018; 46:116-127. [PMID: 26979986 DOI: 10.1093/ije/dyw007] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/14/2016] [Indexed: 01/29/2023] Open
Abstract
Background We investigated the stability and change of leisure-time physical inactivity in adult men and women during a 35-year follow-up. We also analysed the impact of long-term physical inactivity on the development of body mass index (BMI). Methods : In this population-based cohort study, 5254 Finnish twin individuals (59% women) participated in four surveys in 1975, 1981, 1990 and 2011. Mean age at baseline was 23.9 years. Individual long-term leisure-time physical activity (LTPA) was categorized into seven classes varying from 'persistently inactive' to 'persistently active'. We used the multivariate multilevel mixed-effects linear regression model and paired-sample t-test in the analyses. Co-twin control design was used for examining within-pair associations. Results : Of men 11%, and of women 8%, were persistently inactive. Among both sexes, the mean BMI slope trajectories were steeper among the persistently inactive and those who became inactive than among those who were persistently active. Overall, the inactive participants gained 1.4 kg/m 2 [95% confidence interval (CI) 1.2 to 1.7] more in weight than did the active participants from 1975 to 2011. Among twin pairs discordant for LTPA, the corresponding difference was 1.4 kg/m 2 (95% CI 0.83 to 2.0) in dizygotic pairs and 0.68 kg/m 2 (95% CI 0.05 to1.3) in monozygotic pairs. Conclusions Over a 35-year time span from young adulthood, persistently inactive participants and those who had become inactive had greater weight increases than those who were persistently active. This association was also found in twin-pair analyses, although attenuated in monozygotic pairs. This may support the importance of LTPA in weight management, although further causal inference is required.
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Affiliation(s)
- Maarit Piirtola
- University of Helsinki, Department of Public Health, Helsinki, Finland
| | - Jaakko Kaprio
- University of Helsinki, Department of Public Health, Helsinki, Finland
| | - Katja Waller
- University of Helsinki, Department of Public Health, Helsinki, Finland
| | - Kauko Heikkilä
- University of Helsinki, Department of Public Health, Helsinki, Finland
| | - Markku Koskenvuo
- University of Helsinki, Department of Public Health, Helsinki, Finland
| | - Pia Svedberg
- University of Helsinki, Department of Public Health, Helsinki, Finland
| | | | - Urho M Kujala
- University of Helsinki, Department of Public Health, Helsinki, Finland
| | - Annina Ropponen
- University of Helsinki, Department of Public Health, Helsinki, Finland
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245
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Shebanits K, Andersson-Assarsson JC, Larsson I, Carlsson LMS, Feuk L, Larhammar D. Copy number of pancreatic polypeptide receptor gene NPY4R correlates with body mass index and waist circumference. PLoS One 2018; 13:e0194668. [PMID: 29621259 PMCID: PMC5886410 DOI: 10.1371/journal.pone.0194668] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2017] [Accepted: 03/07/2018] [Indexed: 01/14/2023] Open
Abstract
Multiple genetic studies have linked copy number variation (CNV) in different genes to body mass index (BMI) and obesity. A CNV on chromosome 10q11.22 has been associated with body weight. This CNV region spans NPY4R, the gene encoding the pancreatic polypeptide receptor Y4, which has been described as a satiety-stimulating receptor. We have investigated CNV of the NPY4R gene and analysed its relationship to BMI, waist circumference and self-reported dietary intake from 558 individuals (216 men and 342 women) representing a wide BMI range. The copy number for NPY4R ranged from 2 to 8 copies (average 4.6±0.8). Rather than the expected negative correlation, we observed a positive correlation between NPY4R copy number and BMI as well as waist circumference in women (Pearson’s r = 0.267, p = 2.65×10−7 and r = 0.256, p = 8×10−7, respectively). Each additional copy of NPY4R correlated with 2.6 kg/m2 increase in BMI and 5.67 cm increase in waist circumference (p = 2.8×10−5 and p = 6.2×10−5, respectively) for women. For men, there was no statistically significant correlation between CNV and BMI. Our results suggest that NPY4R genetic variation influences body weight in women, but the exact role of this receptor appears to be more complex than previously proposed.
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Affiliation(s)
| | | | - Ingrid Larsson
- Dept. of Gastroenterology and Hepatology, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Lena M. S. Carlsson
- Dept. of Molecular and Clinical Medicine, Sahlgrenska Academy at Gothenburg University, Gothenburg, Sweden
| | - Lars Feuk
- Dept. of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Dan Larhammar
- Dept. of Neuroscience, Uppsala University, Uppsala, Sweden
- * E-mail:
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246
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Lamri A, Pigeyre M, Garver WS, Meyre D. The Extending Spectrum of NPC1-Related Human Disorders: From Niemann-Pick C1 Disease to Obesity. Endocr Rev 2018; 39:192-220. [PMID: 29325023 PMCID: PMC5888214 DOI: 10.1210/er.2017-00176] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Accepted: 01/02/2018] [Indexed: 12/22/2022]
Abstract
The Niemann-Pick type C1 (NPC1) protein regulates the transport of cholesterol and fatty acids from late endosomes/lysosomes and has a central role in maintaining lipid homeostasis. NPC1 loss-of-function mutations in humans cause NPC1 disease, a rare autosomal-recessive lipid-storage disorder characterized by progressive and lethal neurodegeneration, as well as liver and lung failure, due to cholesterol infiltration. In humans, genome-wide association studies and post-genome-wide association studies highlight the implication of common variants in NPC1 in adult-onset obesity, body fat mass, and type 2 diabetes. Heterozygous human carriers of rare loss-of-function coding variants in NPC1 display an increased risk of morbid adult obesity. These associations have been confirmed in mice models, showing an important interaction with high-fat diet. In this review, we describe the current state of knowledge for NPC1 variants in relationship to pleiotropic effects on metabolism. We provide evidence that NPC1 gene variations may predispose to common metabolic diseases by modulating steroid hormone synthesis and/or lipid homeostasis. We also propose several important directions of research to further define the complex roles of NPC1 in metabolism. This review emphasizes the contribution of NPC1 to obesity and its metabolic complications.
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Affiliation(s)
- Amel Lamri
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Marie Pigeyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada.,INSERM 1190, European Genomics Institute for Diabetes, University of Lille, CHRU Lille, Lille, France
| | - William S Garver
- Department of Biochemistry and Molecular Biology, School of Medicine, University of New Mexico, Albuquerque, New Mexico
| | - David Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada.,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
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247
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Tsang S, Duncan GE, Dinescu D, Turkheimer E. Differential models of twin correlations in skew for body-mass index (BMI). PLoS One 2018; 13:e0194968. [PMID: 29590176 PMCID: PMC5874062 DOI: 10.1371/journal.pone.0194968] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2017] [Accepted: 03/14/2018] [Indexed: 12/29/2022] Open
Abstract
Background Body Mass Index (BMI), like most human phenotypes, is substantially heritable. However, BMI is not normally distributed; the skew appears to be structural, and increases as a function of age. Moreover, twin correlations for BMI commonly violate the assumptions of the most common variety of the classical twin model, with the MZ twin correlation greater than twice the DZ correlation. This study aimed to decompose twin correlations for BMI using more general skew-t distributions. Methods Same sex MZ and DZ twin pairs (N = 7,086) from the community-based Washington State Twin Registry were included. We used latent profile analysis (LPA) to decompose twin correlations for BMI into multiple mixture distributions. LPA was performed using the default normal mixture distribution and the skew-t mixture distribution. Similar analyses were performed for height as a comparison. Our analyses are then replicated in an independent dataset. Results A two-class solution under the skew-t mixture distribution fits the BMI distribution for both genders. The first class consists of a relatively normally distributed, highly heritable BMI with a mean in the normal range. The second class is a positively skewed BMI in the overweight and obese range, with lower twin correlations. In contrast, height is normally distributed, highly heritable, and is well-fit by a single latent class. Results in the replication dataset were highly similar. Conclusions Our findings suggest that two distinct processes underlie the skew of the BMI distribution. The contrast between height and weight is in accord with subjective psychological experience: both are under obvious genetic influence, but BMI is also subject to behavioral control, whereas height is not.
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Affiliation(s)
- Siny Tsang
- Department of Epidemiology, Columbia University, New York, NY, United States of America
- * E-mail:
| | - Glen E. Duncan
- Department of Nutrition & Exercise Physiology, Washington State University–Health Sciences, Spokane, WA, United States of America
| | - Diana Dinescu
- Kennedy Krieger Institute and Johns Hopkins School of Medicine, Baltimore, MD, United States of America
| | - Eric Turkheimer
- Department of Psychology, University of Virginia, Charlottesville, VA, United States of America
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248
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Pigeyre M, Saqlain M, Turcotte M, Raja GK, Meyre D. Obesity genetics: insights from the Pakistani population. Obes Rev 2018; 19:364-380. [PMID: 29265593 DOI: 10.1111/obr.12644] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Revised: 10/10/2017] [Accepted: 10/15/2017] [Indexed: 01/26/2023]
Abstract
The Pakistani population is extensively diverse, indicating a genetic admixture of European and Central/West Asian migrants with indigenous South Asian gene pools. Pakistanis are organized in different ethnicities/castes based on cultural, linguistic and geographical origin. While Pakistan is facing a rapid nutritional transition, the rising prevalence of obesity is driving a growing burden of health complications and mortality. This represents a unique opportunity for the research community to study the interplay between obesogenic environmental changes and obesity predisposing genes in the time frame of one generation. This review recapitulates the ancestral origins of Pakistani population, the societal determinants of the rise in obesity and its governmental management. We describe the contribution of syndromic, monogenic non-syndromic and polygenic obesity genes identified in the Pakistani population. We then discuss the utility of gene identification approaches based on large consanguineous families and original gene × environment interaction study designs in discovering new obesity genes and causal pathways. Elucidation of the genetic basis of obesity in the Pakistani population may result in improved methods of obesity prevention and treatment globally.
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Affiliation(s)
- M Pigeyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada.,Department of Nutrition, CHRU Lille, University of Lille, Lille, France
| | - M Saqlain
- Department of Biochemistry, PMAS-Arid Agriculture University Rawalpindi, Rawalpindi, Pakistan
| | - M Turcotte
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - G K Raja
- Department of Biochemistry, PMAS-Arid Agriculture University Rawalpindi, Rawalpindi, Pakistan
| | - D Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada.,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada
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249
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Goodarzi MO. Genetics of obesity: what genetic association studies have taught us about the biology of obesity and its complications. Lancet Diabetes Endocrinol 2018; 6:223-236. [PMID: 28919064 DOI: 10.1016/s2213-8587(17)30200-0] [Citation(s) in RCA: 252] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2017] [Revised: 05/24/2017] [Accepted: 05/24/2017] [Indexed: 01/01/2023]
Abstract
Genome-wide association studies (GWAS) for BMI, waist-to-hip ratio, and other adiposity traits have identified more than 300 single-nucleotide polymorphisms (SNPs). Although there is reason to hope that these discoveries will eventually lead to new preventive and therapeutic agents for obesity, this will take time because such developments require detailed mechanistic understanding of how an SNP influences phenotype (and this information is largely unavailable). Fortunately, absence of functional information has not prevented GWAS findings from providing insights into the biology of obesity. Genes near loci regulating total body mass are enriched for expression in the CNS, whereas genes for fat distribution are enriched in adipose tissue itself. Gene by environment and lifestyle interaction analyses have revealed that our increasingly obesogenic environment might be amplifying genetic risk for obesity, yet those at highest risk could mitigate this risk by increasing physical activity and possibly by avoiding specific dietary components. GWAS findings have also been used in mendelian randomisation analyses probing the causal association between obesity and its many putative complications. In supporting a causal association of obesity with diabetes, coronary heart disease, specific cancers, and other conditions, these analyses have clinical relevance in identifying which outcomes could be preventable through weight loss interventions.
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Affiliation(s)
- Mark O Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
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250
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Qasim A, Turcotte M, de Souza RJ, Samaan MC, Champredon D, Dushoff J, Speakman JR, Meyre D. On the origin of obesity: identifying the biological, environmental and cultural drivers of genetic risk among human populations. Obes Rev 2018; 19:121-149. [PMID: 29144594 DOI: 10.1111/obr.12625] [Citation(s) in RCA: 125] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2017] [Revised: 08/28/2017] [Accepted: 09/08/2017] [Indexed: 12/12/2022]
Abstract
Genetic predisposition to obesity presents a paradox: how do genetic variants with a detrimental impact on human health persist through evolutionary time? Numerous hypotheses, such as the thrifty genotype hypothesis, attempt to explain this phenomenon yet fail to provide a justification for the modern obesity epidemic. In this critical review, we appraise existing theories explaining the evolutionary origins of obesity and explore novel biological and sociocultural agents of evolutionary change to help explain the modern-day distribution of obesity-predisposing variants. Genetic drift, acting as a form of 'blind justice,' may randomly affect allele frequencies across generations while gene pleiotropy and adaptations to diverse environments may explain the rise and subsequent selection of obesity risk alleles. As an adaptive response, epigenetic regulation of gene expression may impact the manifestation of genetic predisposition to obesity. Finally, exposure to malnutrition and disease epidemics in the wake of oppressive social systems, culturally mediated notions of attractiveness and desirability, and diverse mating systems may play a role in shaping the human genome. As an important first step towards the identification of important drivers of obesity gene evolution, this review may inform empirical research focused on testing evolutionary theories by way of population genetics and mathematical modelling.
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Affiliation(s)
- A Qasim
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - M Turcotte
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - R J de Souza
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - M C Samaan
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.,Department of Pediatrics, McMaster University, Hamilton, ON, Canada.,Division of Pediatric Endocrinology, McMaster Children's Hospital, Hamilton, ON, Canada
| | - D Champredon
- Department of Biology, McMaster University, Hamilton, ON, Canada.,Agent-Based Modelling Laboratory, York University, Toronto, ON, Canada
| | - J Dushoff
- Department of Biology, McMaster University, Hamilton, ON, Canada
| | - J R Speakman
- Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, UK.,State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - D Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
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