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Han HY, Masip G, Meng T, Nielsen DE. Interactions between polygenic risk of obesity and dietary factors on anthropometric outcomes: A systematic review and meta-analysis of observational studies. J Nutr 2024:S0022-3166(24)01081-2. [PMID: 39393497 DOI: 10.1016/j.tjnut.2024.10.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2024] [Revised: 10/02/2024] [Accepted: 10/04/2024] [Indexed: 10/13/2024] Open
Abstract
BACKGROUND Diet is an important determinant of health and may moderate genetic susceptibility to obesity, but meta-analyses of available evidence are lacking. OBJECTIVES This study aimed to systematically review and meta-analyze evidence on the moderating effect of diet on genetic susceptibility to obesity, assessed with polygenic risk scores (PRS). METHODS A systematic search was conducted using MEDLINE, EMBASE, Web of Science, and the Cochrane library to retrieve observational studies that examined PRS-diet interactions on obesity-related outcomes. Dietary exposures of interest included diet quality/dietary patterns and consumption of specific food and beverage groups. Random effects meta-analyses were performed for pooled PRS-Healthy Eating Index (HEI) interaction coefficients on body mass index (BMI) (based on data from four cohort studies) and waist circumference (based on data from three cohort studies). RESULTS Out of 36 retrieved studies, 78% were conducted among European samples. Twelve out of 21 articles examining dietary indices/patterns, and 16 out of 21 articles examining food/beverage groups observed some significant PRS-diet interactions. However, within many articles, findings are inconsistent when testing different combinations of obesity PRS-dietary factors and outcomes. Nevertheless, higher HEI scores and adherence to plant-based dietary patterns emerged as the more prominent diet quality/patterns that moderated genetic susceptibility to obesity, while higher consumption of fruits and vegetables, and lower consumption of fried foods and sugar-sweetened beverages emerged as individual food/beverage moderators. Results from the meta-analysis suggest that a higher HEI attenuates genetic susceptibility on BMI (pooled PRS*HEI coefficient: -0.08; 95% confidence interval (CI): -0.15, 0.00; p=0.0392) and waist circumference (-0.37; 95% CI: -0.60, -0.15; p=0.0013). CONCLUSIONS Current observational evidence suggests a moderating role of overall diet quality in polygenic risk of obesity. Future research should aim to identify genetic loci that interact with dietary exposures on anthropometric outcomes and conduct analyses among diverse ethnic groups. PROSPERO CRD42022312289.
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Affiliation(s)
- Hannah Yang Han
- School of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, QC H9X 3V9, Canada
| | - Guiomar Masip
- School of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, QC H9X 3V9, Canada; GENUD (Growth, Exercise, Nutrition and Development) Research Group, Facultad de Ciencias de la Salud, Universidad de Zaragoza, Instituto Agroalimentario de Aragón (IA2), Instituto de Investigación Sanitaria de Aragón (IISA), Zaragoza, Spain; Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Tongzhu Meng
- School of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, QC H9X 3V9, Canada
| | - Daiva E Nielsen
- School of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, QC H9X 3V9, Canada.
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2
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Yen IW, Lin SY, Lin MW, Lee CN, Kuo CH, Chen SC, Tai YY, Kuo CH, Kuo HC, Lin HH, Juan HC, Lin CH, Fan KC, Wang CY, Li HY. The association between plasma angiopoietin-like protein 4, glucose and lipid metabolism during pregnancy, placental function, and risk of delivering large-for-gestational-age neonates. Clin Chim Acta 2024; 554:117775. [PMID: 38220135 DOI: 10.1016/j.cca.2024.117775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 12/18/2023] [Accepted: 01/08/2024] [Indexed: 01/16/2024]
Abstract
BACKGROUND Large-for-gestational-age (LGA) neonates have increased risk of adverse pregnancy outcomes and adult metabolic diseases. We aimed to investigate the relationship between plasma angiopoietin-like protein 4 (ANGPTL4), a protein involved in lipid and glucose metabolism during pregnancy, placental function, growth factors, and the risk of LGA. METHODS We conducted a prospective cohort study and recruited women with singleton pregnancies at the National Taiwan University Hospital between 2013 and 2018. First trimester maternal plasma ANGPTL4 concentrations were measured. RESULTS Among 353 pregnant women recruited, the LGA group had higher first trimester plasma ANGPTL4 concentrations than the appropriate-for-gestational-age group. Plasma ANGPTL4 was associated with hemoglobin A1c, post-load plasma glucose, plasma triglyceride, plasma free fatty acid concentrations, plasma growth hormone variant (GH-V), and birth weight, but was not associated with cord blood growth factors. After adjusting for age, body mass index, hemoglobin A1c, and plasma triglyceride concentrations, plasma ANGPTL4 concentrations were significantly associated with LGA risk, and its predictive performance, as measured by the area under the receiver operating characteristic curve, outperformed traditional risk factors for LGA. CONCLUSIONS Plasma ANGPTL4 is associated with glucose and lipid metabolism during pregnancy, plasma GH-V, and birth weight, and is an early biomarker for predicting the risk of LGA.
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Affiliation(s)
- I-Weng Yen
- Department of Internal Medicine, National Taiwan University Hospital, Hsin-Chu Branch, Hsin-Chu County, Taiwan; Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Shin-Yu Lin
- Department of Obstetrics and Gynecology, National Taiwan University Hospital, Taipei, Taiwan
| | - Ming-Wei Lin
- Department of Obstetrics and Gynecology, National Taiwan University Hospital Hsin-Chu Branch, Hsin-Chu County, Taiwan
| | - Chien-Nan Lee
- Department of Obstetrics and Gynecology, National Taiwan University Hospital, Taipei, Taiwan
| | - Chun-Heng Kuo
- Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan; Department of Internal Medicine, Fu Jen Catholic University Hospital, Fu Jen Catholic University, New Taipei City, Taiwan
| | | | - Yi-Yun Tai
- Department of Obstetrics and Gynecology, National Taiwan University Hospital, Taipei, Taiwan
| | - Ching-Hua Kuo
- School of Pharmacy, College of Medicine, National Taiwan University, Taipei 100, Taiwan; The Metabolomics Core Laboratory, Centers of Genomic and Precision Medicine, National Taiwan University, Taipei 100, Taiwan
| | - Han-Chun Kuo
- The Metabolomics Core Laboratory, Centers of Genomic and Precision Medicine, National Taiwan University, Taipei 100, Taiwan
| | - Heng-Huei Lin
- Department of Obstetrics and Gynecology, National Taiwan University Hospital, Taipei, Taiwan
| | - Hsien-Chia Juan
- Department of Internal Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Chia-Hung Lin
- Division of Endocrinology and Metabolism, Department of Internal Medicine, National Taiwan University Hospital, 7 Chung-Shan South Road, Taipei, Taiwan
| | - Kang-Chih Fan
- Department of Internal Medicine, National Taiwan University Hospital, Hsin-Chu Branch, Hsin-Chu County, Taiwan; Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Chih-Yuan Wang
- Department of Internal Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan; Division of Endocrinology and Metabolism, Department of Internal Medicine, National Taiwan University Hospital, 7 Chung-Shan South Road, Taipei, Taiwan
| | - Hung-Yuan Li
- Division of Endocrinology and Metabolism, Department of Internal Medicine, National Taiwan University Hospital, 7 Chung-Shan South Road, Taipei, Taiwan.
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Prone-Olazabal D, Davies I, González-Galarza FF. Metabolic Syndrome: An Overview on Its Genetic Associations and Gene-Diet Interactions. Metab Syndr Relat Disord 2023; 21:545-560. [PMID: 37816229 DOI: 10.1089/met.2023.0125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/12/2023] Open
Abstract
Metabolic syndrome (MetS) is a cluster of cardiometabolic risk factors that includes central obesity, hyperglycemia, hypertension, and dyslipidemias and whose inter-related occurrence may increase the odds of developing type 2 diabetes and cardiovascular diseases. MetS has become one of the most studied conditions, nevertheless, due to its complex etiology, this has not been fully elucidated. Recent evidence describes that both genetic and environmental factors play an important role on its development. With the advent of genomic-wide association studies, single nucleotide polymorphisms (SNPs) have gained special importance. In this review, we present an update of the genetics surrounding MetS as a single entity as well as its corresponding risk factors, considering SNPs and gene-diet interactions related to cardiometabolic markers. In this study, we focus on the conceptual aspects, diagnostic criteria, as well as the role of genetics, particularly on SNPs and polygenic risk scores (PRS) for interindividual analysis. In addition, this review highlights future perspectives of personalized nutrition with regard to the approach of MetS and how individualized multiomics approaches could improve the current outlook.
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Affiliation(s)
- Denisse Prone-Olazabal
- Postgraduate Department, Faculty of Medicine, Autonomous University of Coahuila, Torreon, Mexico
| | - Ian Davies
- Research Institute of Sport and Exercise Science, The Institute for Health Research, Liverpool John Moores University, Liverpool, United Kingdom
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Cross B, Turner R, Pirmohamed M. Polygenic risk scores: An overview from bench to bedside for personalised medicine. Front Genet 2022; 13:1000667. [PMID: 36437929 PMCID: PMC9692112 DOI: 10.3389/fgene.2022.1000667] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 10/24/2022] [Indexed: 11/13/2022] Open
Abstract
Since the first polygenic risk score (PRS) in 2007, research in this area has progressed significantly. The increasing number of SNPs that have been identified by large scale GWAS analyses has fuelled the development of a myriad of PRSs for a wide variety of diseases and, more recently, to PRSs that potentially identify differential response to specific drugs. PRSs constitute a composite genomic biomarker and potential applications for PRSs in clinical practice encompass risk prediction and disease screening, early diagnosis, prognostication, and drug stratification to improve efficacy or reduce adverse drug reactions. Nevertheless, to our knowledge, no PRSs have yet been adopted into routine clinical practice. Beyond the technical considerations of PRS development, the major challenges that face PRSs include demonstrating clinical utility and circumnavigating the implementation of novel genomic technologies at scale into stretched healthcare systems. In this review, we discuss progress in developing disease susceptibility PRSs across multiple medical specialties, development of pharmacogenomic PRSs, and future directions for the field.
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Affiliation(s)
- Benjamin Cross
- The Wolfson Centre for Personalised Medicine, Institute of Systems, Molecular and Integrative Biology, Faculty of Health & Life Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Richard Turner
- The Wolfson Centre for Personalised Medicine, Institute of Systems, Molecular and Integrative Biology, Faculty of Health & Life Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Munir Pirmohamed
- The Wolfson Centre for Personalised Medicine, Institute of Systems, Molecular and Integrative Biology, Faculty of Health & Life Sciences, University of Liverpool, Liverpool, United Kingdom
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Alsulami S, Cruvinel NT, da Silva NR, Antoneli AC, Lovegrove JA, Horst MA, Vimaleswaran KS. Effect of dietary fat intake and genetic risk on glucose and insulin-related traits in Brazilian young adults. J Diabetes Metab Disord 2021; 20:1337-1347. [PMID: 34900785 PMCID: PMC8630327 DOI: 10.1007/s40200-021-00863-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 07/16/2021] [Indexed: 12/27/2022]
Abstract
PURPOSE The development of metabolic diseases such as type 2 diabetes (T2D) is closely linked to a complex interplay between genetic and dietary factors. The prevalence of abdominal obesity, hyperinsulinemia, dyslipidaemia, and high blood pressure among Brazilian adolescents is increasing and hence, early lifestyle interventions targeting these factors might be an effective strategy to prevent or slow the progression of T2D. METHODS We aimed to assess the interaction between dietary and genetic factors on metabolic disease-related traits in 200 healthy Brazilian young adults. Dietary intake was assessed using 3-day food records. Ten metabolic disease-related single nucleotide polymorphisms (SNPs) were used to construct a metabolic-genetic risk score (metabolic-GRS). RESULTS We found significant interactions between the metabolic-GRS and total fat intake on fasting insulin level (Pinteraction = 0.017), insulin-glucose ratio (Pinteraction = 0.010) and HOMA-B (Pinteraction = 0.002), respectively, in addition to a borderline GRS-fat intake interaction on HOMA-IR (Pinteraction = 0.051). Within the high-fat intake category [37.98 ± 3.39% of total energy intake (TEI)], individuals with ≥ 5 risk alleles had increased fasting insulin level (P = 0.021), insulin-glucose ratio (P = 0.010), HOMA-B (P = 0.001) and HOMA-IR (P = 0.053) than those with < 5 risk alleles. CONCLUSION Our study has demonstrated a novel GRS-fat intake interaction in young Brazilian adults, where individuals with higher genetic risk and fat intake had increased glucose and insulin-related traits than those with lower genetic risk. Large intervention and follow-up studies with an objective assessment of dietary factors are needed to confirm our findings. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s40200-021-00863-7.
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Affiliation(s)
- Sooad Alsulami
- Department of Food and Nutritional Sciences, Hugh Sinclair Unit of Human Nutrition, University of Reading, Reading, RG6 6DZ UK
- Department of Clinical Nutrition, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Nathália Teixeira Cruvinel
- Nutritional Genomics Research Group, Faculty of Nutrition, Federal University of Goiás (UFG), Goiania, Goiás, Brazil
| | - Nara Rubia da Silva
- Nutritional Genomics Research Group, Faculty of Nutrition, Federal University of Goiás (UFG), Goiania, Goiás, Brazil
| | - Ana Carolina Antoneli
- Nutritional Genomics Research Group, Faculty of Nutrition, Federal University of Goiás (UFG), Goiania, Goiás, Brazil
| | - Julie A. Lovegrove
- Department of Food and Nutritional Sciences, Hugh Sinclair Unit of Human Nutrition, University of Reading, Reading, RG6 6DZ UK
- Institute for Cardiovascular and Metabolic Research, University of Reading, Reading, UK
| | - Maria Aderuza Horst
- Nutritional Genomics Research Group, Faculty of Nutrition, Federal University of Goiás (UFG), Goiania, Goiás, Brazil
| | - Karani Santhanakrishnan Vimaleswaran
- Department of Food and Nutritional Sciences, Hugh Sinclair Unit of Human Nutrition, University of Reading, Reading, RG6 6DZ UK
- Institute for Cardiovascular and Metabolic Research, University of Reading, Reading, UK
- Institute for Food, Nutrition, and Health, University of Reading, Reading, UK
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Marcos-Pasero H, Aguilar-Aguilar E, Ikonomopoulou MP, Loria-Kohen V. BDNF Gene as a Precision Skill of Obesity Management. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1331:233-248. [PMID: 34453302 DOI: 10.1007/978-3-030-74046-7_15] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The scarcity of the results obtained for the treatment of obesity leads us to consider new strategies, contemplating all the factors involved in the development of the disease. One of the key molecules for controlling body weight and energy homeostasis is the brain-derived neurotrophic factor (BDNF). This work summarizes the mechanisms in which BDNF gene regulates this multifactorial disease. In addition, we discuss the role of other BDNF polymorphisms as genetic determinants of obesity. In this context, a total of 14 SNPs near or inside BDNF/BDNF-AS related to BMI were identified in various GWASs. Finally, we assess gene-diet interaction as a novel tool to prevent obesity and formulate solid and personalized nutritional management. Our research group has performed the first study on the association of BDNF-AS rs925946 polymorphism and calcium intake as potential modulators of the nutritional status. Although these results should be confirmed in future studies, they open the path for new prevention opportunities.
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Affiliation(s)
- Helena Marcos-Pasero
- Nutrition and Clinical Trials Unit, GENYAL Platform, IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain
| | - Elena Aguilar-Aguilar
- Nutrition and Clinical Trials Unit, GENYAL Platform, IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain
| | - Maria P Ikonomopoulou
- Translational Venomics Group, IMDEA-Food, CEI UAM+CSIC, Madrid, Spain.,Institute for Molecular Bioscience, The University of Queensland, St Lucia, Australia
| | - Viviana Loria-Kohen
- Nutrition and Clinical Trials Unit, GENYAL Platform, IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain. .,Department of Nutrition and Food Science, Faculty of Pharmacy, Complutense University of Madrid, Madrid, Spain.
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7
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Interaction between Metabolic Genetic Risk Score and Dietary Fatty Acid Intake on Central Obesity in a Ghanaian Population. Nutrients 2020; 12:nu12071906. [PMID: 32605047 PMCID: PMC7400498 DOI: 10.3390/nu12071906] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 06/04/2020] [Accepted: 06/24/2020] [Indexed: 02/07/2023] Open
Abstract
Obesity is a multifactorial condition arising from the interaction between genetic and lifestyle factors. We aimed to assess the impact of lifestyle and genetic factors on obesity-related traits in 302 healthy Ghanaian adults. Dietary intake and physical activity were assessed using a 3 day repeated 24 h dietary recall and global physical activity questionnaire, respectively. Twelve single nucleotide polymorphisms (SNPs) were used to construct 4-SNP, 8-SNP and 12-SNP genetic risk scores (GRSs). The 4-SNP GRS showed significant interactions with dietary fat intakes on waist circumference (WC) (Total fat, Pinteraction = 0.01; saturated fatty acids (SFA), Pinteraction = 0.02; polyunsaturated fatty acids (PUFA), Pinteraction = 0.01 and monounsaturated fatty acids (MUFA), Pinteraction = 0.01). Among individuals with higher intakes of total fat (>47 g/d), SFA (>14 g/d), PUFA (>16 g/d) and MUFA (>16 g/d), individuals with ≥3 risk alleles had a significantly higher WC compared to those with <3 risk alleles. This is the first study of its kind in this population, suggesting that a higher consumption of dietary fatty acid may have the potential to increase the genetic susceptibility of becoming centrally obese. These results support the general dietary recommendations to decrease the intakes of total fat and SFA, to reduce the risk of obesity, particularly in individuals with a higher genetic predisposition to central obesity.
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de Toro-Martín J, Guénard F, Bouchard C, Tremblay A, Pérusse L, Vohl MC. The Challenge of Stratifying Obesity: Attempts in the Quebec Family Study. Front Genet 2019; 10:994. [PMID: 31649740 PMCID: PMC6796792 DOI: 10.3389/fgene.2019.00994] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Accepted: 09/18/2019] [Indexed: 01/23/2023] Open
Abstract
Background and aims: Obesity is a major health problem worldwide. Given the heterogeneous obesity phenotype, an optimal obesity stratification would improve clinical management. Since obesity has a strong genetic component, we aimed to develop a polygenic risk score (PRS) to stratify obesity according to the genetic background of the individuals. Methods: A total of 231 single nucleotide polymorphisms (SNP) significantly associated to body mass index (BMI) from 21 genome-wide association studies were genotyped or imputed in 881 subjects from the Quebec Family Study (QFS). The population was randomly split into discovery (80%; n = 704) and validation (20%; n = 177) samples with similar obesity (BMI ≥ 30) prevalence (27.8% and 28.2%, respectively). Family-based associations with obesity were tested for every SNP in the discovery sample and a weighed and continuous PRS231 was constructed. Generalized linear mixed effects models were used to test the association of PRS231 with obesity in the QFS discovery sample and validated in the QFS replication sample. Furthermore, the Fatty Acid Sensor (FAS) Study (n = 141; 27.7% obesity prevalence) was used as an independent sample to replicate the results. Results: The linear trend test demonstrated a significant association of PRS231 with obesity in the QFS discovery sample (ORtrend = 1.19 [95% CI, 1.14-1.24]; P = 2.0x10-16). We also found that the obesity prevalence was significantly greater in the higher PRS231 quintiles compared to the lowest quintile. Significant and consistent results were obtained in the QFS validation sample for both the linear trend test (ORtrend = 1.16 [95% CI, 1.07-1.26]; P = 6.7x10-4), and obesity prevalence across quintiles. These results were partially replicated in the FAS sample (ORtrend = 1.12 [95% CI, 1.02-1.24]; P = 2.2x10-2). PRS231 explained 7.5%, 3.2%, and 1.2% of BMI variance in QFS discovery, QFS validation, and FAS samples, respectively. Conclusions: These results revealed that genetic background in the form of a 231 BMI-associated PRS has a significant impact on obesity, but a limited potential to accurately stratify it. Further studies are encouraged on larger populations.
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Affiliation(s)
- Juan de Toro-Martín
- Institute of Nutrition and Functional Foods (INAF), Université Laval, Quebec, QC, Canada.,School of Nutrition, Université Laval, Quebec, QC, Canada
| | - Frédéric Guénard
- Institute of Nutrition and Functional Foods (INAF), Université Laval, Quebec, QC, Canada.,School of Nutrition, Université Laval, Quebec, QC, Canada
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, United States
| | - Angelo Tremblay
- Department of Kinesiology, Université Laval, Quebec, QC, Canada.,Quebec Heart and Lung Institute Research Center, Quebec, QC, Canada
| | - Louis Pérusse
- Institute of Nutrition and Functional Foods (INAF), Université Laval, Quebec, QC, Canada.,Department of Kinesiology, Université Laval, Quebec, QC, Canada
| | - Marie-Claude Vohl
- Institute of Nutrition and Functional Foods (INAF), Université Laval, Quebec, QC, Canada.,School of Nutrition, Université Laval, Quebec, QC, Canada
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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: 417] [Impact Index Per Article: 83.4] [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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10
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Franco-Tormo MJ, Salas-Crisostomo M, Rocha NB, Budde H, Machado S, Murillo-Rodríguez E. CRISPR/Cas9, the Powerful New Genome-Editing Tool for Putative Therapeutics in Obesity. J Mol Neurosci 2018; 65:10-16. [PMID: 29732484 DOI: 10.1007/s12031-018-1076-4] [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: 01/16/2018] [Accepted: 04/20/2018] [Indexed: 12/12/2022]
Abstract
The molecular technology known as clustered regularly interspaced palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) is revolutionizing the field of medical research and deepening our understanding of numerous biological processes. The attraction of CRISPR/Cas9 lies in its ability to efficiently edit DNA or modulate gene expression in living eukaryotic cells and organisms, a technology that was once considered either too expensive or scientifically risky. CRISPR/Cas9 has been successfully applied in agriculture to develop the next generation of disease-resistant plants. Now, the capability of gene editing has been translated to the biomedical area, focusing on the future of medicine faced with drug-resistant microbes by selectively targeting genes involved in antibiotic resistance, for example, or finding the ultimate strategy for cancer or HIV. In this regard, it was recently demonstrated that an injection of cancer-fighting CRISPR-modified white blood cells in a patient suffering from metastatic lung cancer could lead to promising results. Researchers and bioethicists are debating questions about the regulation of CRISPR/Cas9 that must be addressed. While legal challenges surround the use of this technique for genetically modifying cell lines in humans, we review the basic understanding of CRISPR/Cas9 and discuss how this technology could represent a candidate for treatment of non-communicable diseases in nutrition, such as obesity.
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Affiliation(s)
- María José Franco-Tormo
- Laboratorio de Neurociencias Moleculares e Integrativas, Escuela de Medicina División Ciencias de la Salud, Universidad Anáhuac Mayab, A.P. 96 Cordemex C.P, 97310, Mérida, Yucatán, Mexico.,Intercontinental Neuroscience Research Group, Mérida, Yucatán, Mexico
| | - Mireille Salas-Crisostomo
- Laboratorio de Neurociencias Moleculares e Integrativas, Escuela de Medicina División Ciencias de la Salud, Universidad Anáhuac Mayab, A.P. 96 Cordemex C.P, 97310, Mérida, Yucatán, Mexico.,Intercontinental Neuroscience Research Group, Mérida, Yucatán, Mexico
| | - Nuno Barbosa Rocha
- Intercontinental Neuroscience Research Group, Mérida, Yucatán, Mexico.,Health School, Polytechnic Institute of Porto, Porto, Portugal
| | - Henning Budde
- Intercontinental Neuroscience Research Group, Mérida, Yucatán, Mexico.,Faculty of Human Sciences, Medical School Hamburg, Hamburg, Germany.,Physical Activity, Physical Education, Health and Sport Research Centre (PAPESH), Sports Science Department, School of Science and Engineering, Reykjavik University, Reykjavik, Iceland.,Lithuanian Sports University, Kaunas, Lithuania
| | - Sérgio Machado
- Intercontinental Neuroscience Research Group, Mérida, Yucatán, Mexico.,Laboratory of Panic and Respiration, Institute of Psychiatry of Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.,Physical Activity Neuroscience Laboratory, Physical Activity Sciences Postgraduate Program of Salgado de Oliveira University, Niterói, Brazil
| | - Eric Murillo-Rodríguez
- Laboratorio de Neurociencias Moleculares e Integrativas, Escuela de Medicina División Ciencias de la Salud, Universidad Anáhuac Mayab, A.P. 96 Cordemex C.P, 97310, Mérida, Yucatán, Mexico. .,Intercontinental Neuroscience Research Group, Mérida, Yucatán, Mexico.
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11
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Lee JS, Cheong HS, Shin HD. BMI prediction within a Korean population. PeerJ 2017; 5:e3510. [PMID: 28674662 PMCID: PMC5493974 DOI: 10.7717/peerj.3510] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Accepted: 06/06/2017] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND Body Mass Index (BMI) is widely regarded as an important clinical trait for obesity and other diseases such as Type 2 diabetes, coronary heart disease, and osteoarthritis. METHODS This study uses 6,011 samples of genotype data from ethnic Korean subjects. The data was retrieved from the Korea Association Resource. To identify the BMI-related markers within the Korean population, we collected genome-wide association study (GWAS) markers using a GWAS catalog and also obtained other markers from nearby regions. Of the total 6,011 samples, 5,410 subjects were used as part of a single nucleotide polymorphism (SNP) selection set in order to identify the overlapping BMI-associated SNPs within a 10-fold cross validation. RESULTS We selected nine SNPs (rs12566985 (FPGT-TNNI3K), rs6545809 (ADCY3), rs2943634 (located near LOC646736), rs734597 (located near TFAP2B), rs11030104 (BDNF), rs7988412 (GTF3A), rs2241423 (MAP2K5), rs7202116 (FTO), and rs6567160 (located near LOC105372152) to assist in BMI prediction. The calculated weighted genetic risk scores based on the selected 9 SNPs within the SNP selection set were applied to the final validation set consisting of 601 samples. Our results showed upward trends in the BMI values (P < 0.0001) within the 10-fold cross validation process for R2 > 0.22. These trends were also observed within the validation set for all subjects, as well as within the validation sets divided by gender (P < 0.0001, R2 > 0.46). DISCUSSION The set of nine SNPs identified in this study may be useful for prospective predictions of BMI.
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Affiliation(s)
- Jin Sol Lee
- Research Institute for Basic Science, Sogang University, Seoul, Republic of Korea.,Department of Life Science, Sogang University, Seoul, South Korea
| | - Hyun Sub Cheong
- Department of Genetic Epidemiology, SNP Genetics, Inc., Seoul, Republic of Korea
| | - Hyoung-Doo Shin
- Research Institute for Basic Science, Sogang University, Seoul, Republic of Korea.,Department of Life Science, Sogang University, Seoul, South Korea.,Department of Genetic Epidemiology, SNP Genetics, Inc., Seoul, Republic of Korea
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12
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Mechaly AS, Richardson E, Rinkwitz S. Activity of etv5a and etv5b genes in the hypothalamus of fasted zebrafish is influenced by serotonin. Gen Comp Endocrinol 2017; 246:233-240. [PMID: 28041791 DOI: 10.1016/j.ygcen.2016.12.013] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Revised: 12/03/2016] [Accepted: 12/19/2016] [Indexed: 11/28/2022]
Abstract
Serotonin has been implicated in the inhibition of food intake in vertebrates. However, the mechanisms through which serotonin acts has yet to be elucidated. Recently, ETV5 (ets variant gene 5) has been associated with obesity and food intake control mechanisms in mammals. We have analyzed a putative physiological function of the two etv5 paralogous genes (etv5a and etv5b) in neuronal food intake control in adult zebrafish that have been exposed to different nutritional conditions. A feeding assay was established and fluoxetine, a selective serotonin re-uptake inhibitor (SSRI), was applied. Gene expression changes in the hypothalamus were determined using real-time PCR. Fasting induced an up-regulation of etv5a and etv5b in the hypothalamus, whereas increased serotonin levels in the fasted fish counteracted the increase in expression. To investigate potential mechanisms the expression of further food intake control genes was determined. The results show that an increase of serotonin in fasting fish causes a reduction in the activity of genes stimulating food intake. This is in line with a previously demonstrated anorexigenic function of serotonin. Our results suggest that obesity-associated ETV5 has a food intake stimulating function and that this function is modulated through serotonin.
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Affiliation(s)
- Alejandro S Mechaly
- Dept. of Physiology, Sydney Medical School, University of Sydney, Camperdown 2050, Australia.
| | - Ebony Richardson
- Dept. of Physiology, Sydney Medical School, University of Sydney, Camperdown 2050, Australia
| | - Silke Rinkwitz
- Dept. of Physiology, Sydney Medical School, University of Sydney, Camperdown 2050, Australia.
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13
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Abstract
Except in rare cases, obesity tends to be a consequence of both an unhealthy lifestyle and a genetic susceptibility to gain weight. With more than 200 common genetic variants identified, there is a growing interest in developing personalized preventive and treatment strategies to predict an individual's obesity risk. We review the literature on the prediction of obesity and show that models based on the established genetic variants have poorer predictive ability than traditional predictors, such as family history of obesity and childhood obesity. Current findings suggest that opportunities for precision medicine in common obesity may be limited.
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Affiliation(s)
- Ruth J F Loos
- The Genetics of Obesity and Related Metabolic Traits Program, The Charles Bronfman Institute for Personalized Medicine, The Mindich Child Health and Development Institute, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - A Cecile J W Janssens
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
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14
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Stijnen P, Ramos-Molina B, O'Rahilly S, Creemers JWM. PCSK1 Mutations and Human Endocrinopathies: From Obesity to Gastrointestinal Disorders. Endocr Rev 2016; 37:347-71. [PMID: 27187081 DOI: 10.1210/er.2015-1117] [Citation(s) in RCA: 90] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Prohormone convertase 1/3, encoded by the PCSK1 gene, is a serine endoprotease that is involved in the processing of a variety of proneuropeptides and prohormones. Humans who are homozygous or compound heterozygous for loss-of-function mutations in PCSK1 exhibit a variable and pleiotropic syndrome consisting of some or all of the following: obesity, malabsorptive diarrhea, hypogonadotropic hypogonadism, altered thyroid and adrenal function, and impaired regulation of plasma glucose levels in association with elevated circulating proinsulin-to-insulin ratio. Recently, more common variants in the PCSK1 gene have been found to be associated with alterations in body mass index, increased circulating proinsulin levels, and defects in glucose homeostasis. This review provides an overview of the endocrinopathies and other disorders observed in prohormone convertase 1/3-deficient patients, discusses the possible biochemical basis for these manifestations of the disease, and proposes a model whereby certain missense mutations in PCSK1 may result in proteins with a dominant negative action.
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Affiliation(s)
- Pieter Stijnen
- Laboratory for Biochemical Neuroendocrinology (P.S., B.R.-M., J.W.M.C.), Department of Human Genetics, KU Leuven, Leuven 3000, Belgium; and Medical Research Council (MRC) Metabolic Diseases Unit (S.O.), Wellcome Trust-MRC Institute of Metabolic Science, National Institute for Health Research, Cambridge Biomedical Research Centre, Addenbrooke's Hospital, University of Cambridge, Cambridge CB2 0QQ, United Kingdom
| | - Bruno Ramos-Molina
- Laboratory for Biochemical Neuroendocrinology (P.S., B.R.-M., J.W.M.C.), Department of Human Genetics, KU Leuven, Leuven 3000, Belgium; and Medical Research Council (MRC) Metabolic Diseases Unit (S.O.), Wellcome Trust-MRC Institute of Metabolic Science, National Institute for Health Research, Cambridge Biomedical Research Centre, Addenbrooke's Hospital, University of Cambridge, Cambridge CB2 0QQ, United Kingdom
| | - Stephen O'Rahilly
- Laboratory for Biochemical Neuroendocrinology (P.S., B.R.-M., J.W.M.C.), Department of Human Genetics, KU Leuven, Leuven 3000, Belgium; and Medical Research Council (MRC) Metabolic Diseases Unit (S.O.), Wellcome Trust-MRC Institute of Metabolic Science, National Institute for Health Research, Cambridge Biomedical Research Centre, Addenbrooke's Hospital, University of Cambridge, Cambridge CB2 0QQ, United Kingdom
| | - John W M Creemers
- Laboratory for Biochemical Neuroendocrinology (P.S., B.R.-M., J.W.M.C.), Department of Human Genetics, KU Leuven, Leuven 3000, Belgium; and Medical Research Council (MRC) Metabolic Diseases Unit (S.O.), Wellcome Trust-MRC Institute of Metabolic Science, National Institute for Health Research, Cambridge Biomedical Research Centre, Addenbrooke's Hospital, University of Cambridge, Cambridge CB2 0QQ, United Kingdom
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15
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Wang HJ, Hinney A, Song JY, Scherag A, Meng XR, Grallert H, Illig T, Hebebrand J, Wang Y, Ma J. Association of common variants identified by recent genome-wide association studies with obesity in Chinese children: a case-control study. BMC MEDICAL GENETICS 2016; 17:7. [PMID: 26800887 PMCID: PMC4724138 DOI: 10.1186/s12881-016-0268-4] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2014] [Accepted: 01/06/2016] [Indexed: 12/15/2022]
Abstract
Background Large-scale genome-wide association studies have identified multiple genetic variants that are associated with elevated body mass index (BMI) or the risk of obesity in Caucasian or Asian populations. We examined whether these variants are individually associated with obesity in Chinese children, and also assessed their cumulative effects and predictive value for obesity risk in Chinese children. Methods We genotyped 40 single nucleotide polymorphisms (SNPs) and conducted association analyses for 32/40 SNPs with an estimated minor allele frequency >1 % in 2 030 unrelated Chinese children, including 607 normal-weight, 718 overweight, and 705 obese individuals from two cross-sectional study groups. Logistic regression and linear regression under the additive model were used to examine associations, and the area under the receiver operating characteristic curve (AUCROC) was reported as prediction summary. Results We identified obesity association for 6 SNPs near SEC16B, RBJ, CDKAL1, TFAP2B, MAP2K5 and FTO (odds ratios (ORs) ranged from 1.19 to 1.41, nominal two-sided P-values < 0.05). Association (Bonferroni corrected) of rs543874 near SEC16B and rs2241423 near MAP2K5 had presumably stronger effects on obesity in Chinese children than in Caucasian populations. Their risk alleles were also associated with BMI standard deviation score (BMI-SDS) variability. We demonstrated the cumulative effects of the 32 SNPs on obesity risk (per risk allele: OR = 1.06, 95 % CI: 1.03-1.11, P = 4.84 × 10-4) and BMI-SDS (β = 0.04, 95 % CI: 0.02-0.06, P = 3.69 × 10-7). The difference in AUCROC for a model with covariates (age, age square, sex and study group) and the model including covariates and all 32 SNPs was 2.8 % (P = 0.0002). Conclusion While six SNPs were individually associated with obesity in Chinese children, the 32 common variants identified by recent GWA studies had cumulative effects and resulted in a limited increase in the AUCROC predictive value for childhood obesity. Electronic supplementary material The online version of this article (doi:10.1186/s12881-016-0268-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Hai-Jun Wang
- Institute of Child and Adolescent Health, Peking University, Beijing, China
| | - Anke Hinney
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Jie-Yun Song
- Institute of Child and Adolescent Health, Peking University, Beijing, China
| | - André Scherag
- Clinical Epidemiology, Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital, Jena, 07743, Germany
| | - Xiang-Rui Meng
- Institute of Child and Adolescent Health, Peking University, Beijing, China
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Diabetes Research, Neuherberg, Germany
| | - Thomas Illig
- Research Unit of Molecular Epidemiology, Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Hannover Unified Biobank, Hannover Medical School, Hannover, Germany
| | - Johannes Hebebrand
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Yan Wang
- Division of Maternal and Child Health, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Jun Ma
- Institute of Child and Adolescent Health, Peking University, Beijing, China.
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16
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Ahmad S, Zhao W, Renström F, Rasheed A, Samuel M, Zaidi M, Shah N, Mallick NH, Zaman KS, Ishaq M, Rasheed SZ, Memon FUR, Hanif B, Lakhani MS, Ahmed F, Kazmi SU, Frossard P, Franks PW, Saleheen D. Physical activity, smoking, and genetic predisposition to obesity in people from Pakistan: the PROMIS study. BMC MEDICAL GENETICS 2015; 16:114. [PMID: 26683835 PMCID: PMC4683724 DOI: 10.1186/s12881-015-0259-x] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/22/2015] [Accepted: 12/05/2015] [Indexed: 12/31/2022]
Abstract
Background Multiple genetic variants have been reliably associated with obesity-related traits in Europeans, but little is known about their associations and interactions with lifestyle factors in South Asians. Methods In 16,157 Pakistani adults (8232 controls; 7925 diagnosed with myocardial infarction [MI]) enrolled in the PROMIS Study, we tested whether: a) BMI-associated loci, individually or in aggregate (as a genetic risk score - GRS), are associated with BMI; b) physical activity and smoking modify the association of these loci with BMI. Analyses were adjusted for age, age2, sex, MI (yes/no), and population substructure. Results Of 95 SNPs studied here, 73 showed directionally consistent effects on BMI as reported in Europeans. Each additional BMI-raising allele of the GRS was associated with 0.04 (SE = 0.01) kg/m2 higher BMI (P = 4.5 × 10−14). We observed nominal evidence of interactions of CLIP1 rs11583200 (Pinteraction = 0.014), CADM2 rs13078960 (Pinteraction = 0.037) and GALNT10 rs7715256 (Pinteraction = 0.048) with physical activity, and PTBP2 rs11165643 (Pinteraction = 0.045), HIP1 rs1167827 (Pinteraction = 0.015), C6orf106 rs205262 (Pinteraction = 0.032) and GRID1 rs7899106 (Pinteraction = 0.043) with smoking on BMI. Conclusions Most BMI-associated loci have directionally consistent effects on BMI in Pakistanis and Europeans. There were suggestive interactions of established BMI-related SNPs with smoking or physical activity. Electronic supplementary material The online version of this article (doi:10.1186/s12881-015-0259-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Shafqat Ahmad
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Malmö, Sweden.
| | - Wei Zhao
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
| | - Frida Renström
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Malmö, Sweden.
| | - Asif Rasheed
- Center for Non-Communicable Diseases Pakistan, Karachi, Pakistan.
| | - Maria Samuel
- Center for Non-Communicable Diseases Pakistan, Karachi, Pakistan.
| | - Mozzam Zaidi
- Center for Non-Communicable Diseases Pakistan, Karachi, Pakistan.
| | - Nabi Shah
- Center for Non-Communicable Diseases Pakistan, Karachi, Pakistan. .,Department of Pharmacy, COMSATS Institute of Information Technology, Abbottabad, Pakistan.
| | | | - Khan Shah Zaman
- National Institute of Cardiovascular Diseases, Karachi, Pakistan.
| | | | | | | | | | | | - Faisal Ahmed
- Department of Cardiology, Liaquat National Hospital, Karachi, Pakistan.
| | | | - Philippe Frossard
- Center for Non-Communicable Diseases Pakistan, Karachi, Pakistan. .,Nazarbayev University, Astana, Kazakhstan.
| | - Paul W Franks
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Malmö, Sweden. .,Department of Public Health and Clinical Medicine, Section for Medicine, Umeå University, Umeå, Sweden. .,Department of Nutrition, Harvard School of Public Health, Boston, MA, USA.
| | - Danish Saleheen
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA. .,Center for Non-Communicable Diseases Pakistan, Karachi, Pakistan. .,Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, USA.
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17
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Andersen MK, Sandholt CH. Recent Progress in the Understanding of Obesity: Contributions of Genome-Wide Association Studies. Curr Obes Rep 2015; 4:401-10. [PMID: 26374640 DOI: 10.1007/s13679-015-0173-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Since 2007, discovery of genetic variants associated with general obesity and fat distribution has advanced tremendously through genome-wide association studies (GWAS). Currently, the number of robustly associated loci is 190. Even though these loci explain <3 % of the variance, they have provided us a still emerging picture of genomic localization, frequency and effect size spectra, and hints of functional implications. The translation into biological knowledge has turned out to be an immense task. However, in silico enrichment analyses of genes involved in specific pathways or expressed in specific tissues have the power to suggest biological mechanisms underlying obesity. Inspired by this, we highlight genes in five loci potentially mechanistically linked to leptin-receptor trafficking and signaling in primary cilia. The clinical application of genetic knowledge as prediction, prevention, or treatment strategies is unfortunately still far from reality. Thus, despite major advances, further research is warranted to solve one of the greatest health problems in modern society.
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Affiliation(s)
- Mette Korre Andersen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 1, 2.sal, 2100, Copenhagen, Denmark.
| | - Camilla Helene Sandholt
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 1, 2.sal, 2100, Copenhagen, Denmark.
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18
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Hung CF, Breen G, Czamara D, Corre T, Wolf C, Kloiber S, Bergmann S, Craddock N, Gill M, Holsboer F, Jones L, Jones I, Korszun A, Kutalik Z, Lucae S, Maier W, Mors O, Owen MJ, Rice J, Rietschel M, Uher R, Vollenweider P, Waeber G, Craig IW, Farmer AE, Lewis CM, Müller-Myhsok B, Preisig M, McGuffin P, Rivera M. A genetic risk score combining 32 SNPs is associated with body mass index and improves obesity prediction in people with major depressive disorder. BMC Med 2015; 13:86. [PMID: 25903154 PMCID: PMC4407390 DOI: 10.1186/s12916-015-0334-3] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2014] [Accepted: 03/24/2015] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Obesity is strongly associated with major depressive disorder (MDD) and various other diseases. Genome-wide association studies have identified multiple risk loci robustly associated with body mass index (BMI). In this study, we aimed to investigate whether a genetic risk score (GRS) combining multiple BMI risk loci might have utility in prediction of obesity in patients with MDD. METHODS Linear and logistic regression models were conducted to predict BMI and obesity, respectively, in three independent large case-control studies of major depression (Radiant, GSK-Munich, PsyCoLaus). The analyses were first performed in the whole sample and then separately in depressed cases and controls. An unweighted GRS was calculated by summation of the number of risk alleles. A weighted GRS was calculated as the sum of risk alleles at each locus multiplied by their effect sizes. Receiver operating characteristic (ROC) analysis was used to compare the discriminatory ability of predictors of obesity. RESULTS In the discovery phase, a total of 2,521 participants (1,895 depressed patients and 626 controls) were included from the Radiant study. Both unweighted and weighted GRS were highly associated with BMI (P < 0.001) but explained only a modest amount of variance. Adding 'traditional' risk factors to GRS significantly improved the predictive ability with the area under the curve (AUC) in the ROC analysis, increasing from 0.58 to 0.66 (95% CI, 0.62-0.68; χ(2) = 27.68; P < 0.0001). Although there was no formal evidence of interaction between depression status and GRS, there was further improvement in AUC in the ROC analysis when depression status was added to the model (AUC = 0.71; 95% CI, 0.68-0.73; χ(2) = 28.64; P <0.0001). We further found that the GRS accounted for more variance of BMI in depressed patients than in healthy controls. Again, GRS discriminated obesity better in depressed patients compared to healthy controls. We later replicated these analyses in two independent samples (GSK-Munich and PsyCoLaus) and found similar results. CONCLUSIONS A GRS proved to be a highly significant predictor of obesity in people with MDD but accounted for only modest amount of variance. Nevertheless, as more risk loci are identified, combining a GRS approach with information on non-genetic risk factors could become a useful strategy in identifying MDD patients at higher risk of developing obesity.
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Affiliation(s)
- Chi-Fa Hung
- MRC SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, Box PO82, De Crespigny Park, Denmark Hill, London, SE5 8AF, UK. .,Department of Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, 833, Taiwan.
| | - Gerome Breen
- MRC SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, Box PO82, De Crespigny Park, Denmark Hill, London, SE5 8AF, UK. .,National Institute for Health Research Biomedical Research Centre for Mental Health at the Maudsley and Institute of Psychiatry, King's College London, London, UK.
| | - Darina Czamara
- Max-Planck-Institute of Psychiatry, Kraepelinstraße 2, 80804, Munich, Germany.
| | - Tanguy Corre
- Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier, Universitaire Vaudois (CHUV), 1010, Lausanne, Switzerland. .,Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland.
| | - Christiane Wolf
- Max-Planck-Institute of Psychiatry, Kraepelinstraße 2, 80804, Munich, Germany.
| | - Stefan Kloiber
- Max-Planck-Institute of Psychiatry, Kraepelinstraße 2, 80804, Munich, Germany.
| | - Sven Bergmann
- Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier, Universitaire Vaudois (CHUV), 1010, Lausanne, Switzerland. .,Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland.
| | - Nick Craddock
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ, UK.
| | - Michael Gill
- Department of Psychiatry, Trinity Centre for Health Sciences, Dublin 8, Ireland.
| | - Florian Holsboer
- Max-Planck-Institute of Psychiatry, Kraepelinstraße 2, 80804, Munich, Germany.
| | - Lisa Jones
- Department of Psychiatry, School of Clinical and Experimental Medicine, University of Birmingham, Birmingham, B15 2TT, UK.
| | - Ian Jones
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Hadyn Ellis Building, Maindy Road, Cardiff, CF24 4HQ, UK.
| | - Ania Korszun
- Barts and The London School of Medicine and Dentistry, Queen Mary's University of London, London, E1 2AD, UK.
| | - Zoltan Kutalik
- Institute of Social and Preventive Medicine (IUMSP), Centre Hospitalier, Universitaire Vaudois (CHUV), 1010, Lausanne, Switzerland. .,Swiss Institute of Bioinformatics, Lausanne, 1015, Switzerland.
| | - Susanne Lucae
- Max-Planck-Institute of Psychiatry, Kraepelinstraße 2, 80804, Munich, Germany.
| | - Wolfgang Maier
- Department of Psychiatry, University of Bonn, 53127, Bonn, Germany.
| | - Ole Mors
- Research Department P, Aarhus University Hospital, Skovagervej 2, DK-8240, Risskov, Denmark.
| | - Michael J Owen
- MRC Centre for Neuropsychiatric Genetics and Genomics, Department of Psychological Medicine and Neurology, School of Medicine, Cardiff University, Henry Wellcome Building, Heath Park, Cardiff, CF14 4XN, UK.
| | - John Rice
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, 63130, USA.
| | | | - Rudolf Uher
- MRC SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, Box PO82, De Crespigny Park, Denmark Hill, London, SE5 8AF, UK. .,Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, NS, B3H 3J5, Canada.
| | - Peter Vollenweider
- Division of Internal Medicine, CHUV, Rue du Bugnon 21, 1011, Lausanne, Switzerland.
| | - Gerard Waeber
- Division of Internal Medicine, CHUV, Rue du Bugnon 21, 1011, Lausanne, Switzerland.
| | - Ian W Craig
- MRC SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, Box PO82, De Crespigny Park, Denmark Hill, London, SE5 8AF, UK.
| | - Anne E Farmer
- MRC SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, Box PO82, De Crespigny Park, Denmark Hill, London, SE5 8AF, UK.
| | - Cathryn M Lewis
- MRC SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, Box PO82, De Crespigny Park, Denmark Hill, London, SE5 8AF, UK. .,Department of Medical and Molecular Genetics, School of Medicine, King's College London, 8th Floor, Tower Wing, Guys Hospital, London, SE1 9RT, UK.
| | | | - Martin Preisig
- Department of Psychiatry, Lausanne University Hospital, 1008, Prilly-Lausanne, Switzerland.
| | - Peter McGuffin
- MRC SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, Box PO82, De Crespigny Park, Denmark Hill, London, SE5 8AF, UK.
| | - Margarita Rivera
- MRC SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, Box PO82, De Crespigny Park, Denmark Hill, London, SE5 8AF, UK. .,National Institute for Health Research Biomedical Research Centre for Mental Health at the Maudsley and Institute of Psychiatry, King's College London, London, UK. .,CIBERSAM-University of Granada and Institute of Neurosciences Federico Olóriz, Centro de Investigación Biomédica, University of Granada, Avda del Conocimiento s/n, 18100 Armilla, Granada, Spain. .,Instituto de Investigación Biosanitaria ibs.GRANADA, Hospitales Universitarios de Granada/Universidad de Granada, 18012, C/ Dr. Azpitarte, 4, 18012, Granada, Spain.
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Nead KT, Li A, Wehner MR, Neupane B, Gustafsson S, Butterworth A, Engert JC, Davis AD, Hegele RA, Miller R, den Hoed M, Khaw KT, Kilpeläinen TO, Wareham N, Edwards TL, Hallmans G, Varga TV, Kardia SLR, Smith JA, Zhao W, Faul JD, Weir D, Mi J, Xi B, Quinteros SC, Cooper C, Sayer AA, Jameson K, Grøntved A, Fornage M, Sidney S, Hanis CL, Highland HM, Häring HU, Heni M, Lasky-Su J, Weiss ST, Gerhard GS, Still C, Melka MM, Pausova Z, Paus T, Grant SFA, Hakonarson H, Price RA, Wang K, Scherag A, Hebebrand J, Hinney A, Franks PW, Frayling TM, McCarthy MI, Hirschhorn JN, Loos RJ, Ingelsson E, Gerstein HC, Yusuf S, Beyene J, Anand SS, Meyre D. Contribution of common non-synonymous variants in PCSK1 to body mass index variation and risk of obesity: a systematic review and meta-analysis with evidence from up to 331 175 individuals. Hum Mol Genet 2015; 24:3582-94. [PMID: 25784503 DOI: 10.1093/hmg/ddv097] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2014] [Accepted: 03/13/2015] [Indexed: 12/31/2022] Open
Abstract
Polymorphisms rs6232 and rs6234/rs6235 in PCSK1 have been associated with extreme obesity [e.g. body mass index (BMI) ≥ 40 kg/m(2)], but their contribution to common obesity (BMI ≥ 30 kg/m(2)) and BMI variation in a multi-ethnic context is unclear. To fill this gap, we collected phenotypic and genetic data in up to 331 175 individuals from diverse ethnic groups. This process involved a systematic review of the literature in PubMed, Web of Science, Embase and the NIH GWAS catalog complemented by data extraction from pre-existing GWAS or custom-arrays in consortia and single studies. We employed recently developed global meta-analytic random-effects methods to calculate summary odds ratios (OR) and 95% confidence intervals (CIs) or beta estimates and standard errors (SE) for the obesity status and BMI analyses, respectively. Significant associations were found with binary obesity status for rs6232 (OR = 1.15, 95% CI 1.06-1.24, P = 6.08 × 10(-6)) and rs6234/rs6235 (OR = 1.07, 95% CI 1.04-1.10, P = 3.00 × 10(-7)). Similarly, significant associations were found with continuous BMI for rs6232 (β = 0.03, 95% CI 0.00-0.07; P = 0.047) and rs6234/rs6235 (β = 0.02, 95% CI 0.00-0.03; P = 5.57 × 10(-4)). Ethnicity, age and study ascertainment significantly modulated the association of PCSK1 polymorphisms with obesity. In summary, we demonstrate evidence that common gene variation in PCSK1 contributes to BMI variation and susceptibility to common obesity in the largest known meta-analysis published to date in genetic epidemiology.
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Affiliation(s)
- Kevin T Nead
- Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK, Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Aihua Li
- Department of Clinical Epidemiology and Biostatistics
| | - Mackenzie R Wehner
- Stanford University School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Binod Neupane
- Department of Clinical Epidemiology and Biostatistics
| | - Stefan Gustafsson
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Adam Butterworth
- Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - James C Engert
- Population Health Research Institute, McMaster University, and Hamilton Health Sciences, Hamilton General Hospital, Hamilton, ON, Canada L8L 2X
| | | | - Robert A Hegele
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada L8S 4L8, Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala SE 751 05, Sweden
| | | | - Marcel den Hoed
- The Research Institute of the McGill University Health Centre, McGill University, Montreal, QC, Canada H3H 2R9, Six Nations Health Services, Ohsweken, Canada N0A 1M0
| | - Kay-Tee Khaw
- Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
| | - Tuomas O Kilpeläinen
- The Research Institute of the McGill University Health Centre, McGill University, Montreal, QC, Canada H3H 2R9, Blackburn Cardiovascular Genetics Laboratory, Robarts Research Institute, London, ON, Canada N6A 5K8
| | - Nick Wareham
- The Research Institute of the McGill University Health Centre, McGill University, Montreal, QC, Canada H3H 2R9
| | - Todd L Edwards
- Department of Medicine, University of Western Ontario, London, ON, Canada N6A 3K7
| | - Göran Hallmans
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Tibor V Varga
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Sharon L R Kardia
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, Copenhagen 2100, Denmark
| | - Jennifer A Smith
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, Copenhagen 2100, Denmark
| | - Wei Zhao
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, Copenhagen 2100, Denmark
| | - Jessica D Faul
- Center for Human Genetics Research, Vanderbilt Epidemiology Center, Department of Medicine, Vanderbilt University, Nashville, TN 37235, USA
| | - David Weir
- Center for Human Genetics Research, Vanderbilt Epidemiology Center, Department of Medicine, Vanderbilt University, Nashville, TN 37235, USA
| | - Jie Mi
- Department of Public Health and Clinical Medicine, Umeå University, Umeå 901 87, Sweden
| | - Bo Xi
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Skåne University Hospital Malmö, Malmö 205 02, Sweden
| | | | - Cyrus Cooper
- Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA, Department of Epidemiology, Capital Institute of Pediatrics, Beijing 100020, China, Department of Maternal and Child Health Care, School of Public Health, Shandong University, Jinan 250100, China
| | - Avan Aihie Sayer
- Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
| | - Karen Jameson
- Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
| | - Anders Grøntved
- Unidad de Genómica de Poblaciones Aplicada a la Salud, Facultad de Química, Universidad Nacional Autónoma de México, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Myriam Fornage
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton SO16 6YD, UK
| | - Stephen Sidney
- National Institute for Health Research Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton General Hospital, Southampton SO16 6YD, UK
| | - Craig L Hanis
- National Institute for Health Research Biomedical Research Unit, University of Oxford, Oxford OX3 7LE, UK
| | - Heather M Highland
- National Institute for Health Research Biomedical Research Unit, University of Oxford, Oxford OX3 7LE, UK
| | - Hans-Ulrich Häring
- Department of Sport Science and Clinical Biomechanics, University of Southern Denmark, Odense DK-5230, Denmark, University of Texas Health Science Center at Houston Institute of Molecular Medicine and Division of Epidemiology Human Genetics and Environmental Sciences, School of Public Health, Houston, TX 77030, USA
| | - Martin Heni
- Department of Sport Science and Clinical Biomechanics, University of Southern Denmark, Odense DK-5230, Denmark, University of Texas Health Science Center at Houston Institute of Molecular Medicine and Division of Epidemiology Human Genetics and Environmental Sciences, School of Public Health, Houston, TX 77030, USA
| | - Jessica Lasky-Su
- Division of Research, Kaiser Permanente of Northern California, Oakland, CA 94612, USA, The Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Scott T Weiss
- Division of Research, Kaiser Permanente of Northern California, Oakland, CA 94612, USA, The Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Glenn S Gerhard
- Internal Medicine IV (Endocrinology, Diabetology, Angiology, Nephrology, and Clinical Chemistry), University Hospital of Tuebingen, Tübingen 72076, Germany
| | | | - Melkaey M Melka
- The Department of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Zdenka Pausova
- The Department of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Tomáš Paus
- Center for Genomic Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Struan F A Grant
- Department of Biochemistry and Molecular Biology, Institute for Personalized Medicine, Department of Pathology and Laboratory Medicine, Pennsylvania State University, Hershey, PA 17033, USA, Geisinger Obesity Institute, Danville, PA 17822, USA
| | - Hakon Hakonarson
- Department of Biochemistry and Molecular Biology, Institute for Personalized Medicine, Department of Pathology and Laboratory Medicine, Pennsylvania State University, Hershey, PA 17033, USA, Geisinger Obesity Institute, Danville, PA 17822, USA
| | - R Arlen Price
- The Hospital for Sick Children, Department of Physiology, University of Toronto, Toronto, ON, Canada M5G 1X
| | - Kai Wang
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton SO16 6YD, UK, Rotman Research Institute, University of Toronto, Toronto, Canada M6A 2E1
| | - Andre Scherag
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | | | | | | | - Paul W Franks
- Department of Medicine, University of Western Ontario, London, ON, Canada N6A 3K7, MRC Epidemiology Unit, University of Cambridge, Cambridge, UK, Center for Neurobiology and Behavior, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Timothy M Frayling
- Zilkha Neurogenetic Institute, Department of Psychiatry and Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA
| | - Mark I McCarthy
- Clinical Epidemiology, Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital, Jena 07740, Germany
| | - Joel N Hirschhorn
- Department of Child and Adolescent Psychiatry, University of Duisburg-Essen, Essen 45141, Germany, Department of Nutrition, Harvard School of Public Health, Boston, MA 02115, USA, Genetics of Complex Traits, Peninsula College of Medicine and Dentistry, University of Exeter, Exeter EX2 4TH, UK
| | - Ruth J Loos
- The Research Institute of the McGill University Health Centre, McGill University, Montreal, QC, Canada H3H 2R9, Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford OX3 9DU, UK
| | - Erik Ingelsson
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Hertzel C Gerstein
- Department of Clinical Epidemiology and Biostatistics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA, Divisions of Genetics and Endocrinology, Children's Hospital, Boston, MA 02115, USA
| | - Salim Yusuf
- Department of Clinical Epidemiology and Biostatistics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA, Divisions of Genetics and Endocrinology, Children's Hospital, Boston, MA 02115, USA
| | - Joseph Beyene
- Department of Clinical Epidemiology and Biostatistics
| | - Sonia S Anand
- Department of Clinical Epidemiology and Biostatistics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA, Divisions of Genetics and Endocrinology, Children's Hospital, Boston, MA 02115, USA
| | - David Meyre
- Department of Clinical Epidemiology and Biostatistics, Divisions of Genetics and Endocrinology, Children's Hospital, Boston, MA 02115, USA, Department of Genetics, Harvard Medical School, Boston, MA 02115, USA,
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Apalasamy YD, Mohamed Z. Obesity and genomics: role of technology in unraveling the complex genetic architecture of obesity. Hum Genet 2015; 134:361-74. [PMID: 25687726 DOI: 10.1007/s00439-015-1533-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2014] [Accepted: 02/02/2015] [Indexed: 01/15/2023]
Abstract
Obesity is a complex and multifactorial disease that occurs as a result of the interaction between "obesogenic" environmental factors and genetic components. Although the genetic component of obesity is clear from the heritability studies, the genetic basis remains largely elusive. Successes have been achieved in identifying the causal genes for monogenic obesity using animal models and linkage studies, but these approaches are not fruitful for polygenic obesity. The developments of genome-wide association approach have brought breakthrough discovery of genetic variants for polygenic obesity where tens of new susceptibility loci were identified. However, the common SNPs only accounted for a proportion of heritability. The arrival of NGS technologies and completion of 1000 Genomes Project have brought other new methods to dissect the genetic architecture of obesity, for example, the use of exome genotyping arrays and deep sequencing of candidate loci identified from GWAS to study rare variants. In this review, we summarize and discuss the developments of these genetic approaches in human obesity.
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Affiliation(s)
- Yamunah Devi Apalasamy
- Department of Pharmacology, Pharmacogenomics Laboratory, Faculty of Medicine, University of Malaya, 50603, Kuala Lumpur, Malaysia,
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21
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Stijnen P, Tuand K, Varga TV, Franks PW, Aertgeerts B, Creemers JWM. The association of common variants in PCSK1 with obesity: a HuGE review and meta-analysis. Am J Epidemiol 2014; 180:1051-65. [PMID: 25355447 DOI: 10.1093/aje/kwu237] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Congenital deficiency of the proprotein convertase subtilisine/kexin type 1 gene (PCSK1), which encodes proprotein convertase 1/3, causes a severe multihormonal disorder marked by early-onset obesity. The single nucleotide polymorphisms (SNPs) rs6232 and rs6234-rs6235 in PCSK1 have been associated with obesity. However, case-control studies carried out in populations of different ethnicities have only partly replicated this association. Moreover, these SNPs have only weakly been associated with body mass index (weight (kg)/height (m)(2)) at a genome-wide level of significance. To investigate this discrepancy, we conducted a systematic search for studies published before December 2013 and extracted relevant data. Pooled estimates were calculated for overall and subgroup analyses. This meta-analysis confirmed the association of PCSK1 SNPs with obesity and provides the first evidence that the association between PCSK1 rs6232 and obesity is stronger for childhood obesity than for adult obesity. Moreover, we identified weak associations with body mass index and significantly stronger associations with waist circumference for rs6234-rs6235. No difference was found in the association with different obesity grades, and no association of PCSK1 rs6234-rs6235 with obesity was identified in Asian populations. This systematic Human Genome Epidemiology (HuGE) review showed convincingly that the SNPs rs6232, rs6234, and rs6235 in PCSK1 are associated with obesity in Caucasians.
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Hernandez-Escalante VM, Nava-Gonzalez EJ, Voruganti VS, Kent JW, Haack K, Laviada-Molina HA, Molina-Segui F, Gallegos-Cabriales EC, Lopez-Alvarenga JC, Cole SA, Mezzles MJ, Comuzzie AG, Bastarrachea RA. Replication of obesity and diabetes-related SNP associations in individuals from Yucatán, México. Front Genet 2014; 5:380. [PMID: 25477898 PMCID: PMC4235406 DOI: 10.3389/fgene.2014.00380] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2014] [Accepted: 10/15/2014] [Indexed: 12/28/2022] Open
Abstract
The prevalence of type 2 diabetes (T2D) is rising rapidly and in Mexicans is ~19%. T2D is affected by both environmental and genetic factors. Although specific genes have been implicated in T2D risk few of these findings are confirmed in studies of Mexican subjects. Our aim was to replicate associations of 39 single nucleotide polymorphisms (SNPs) from 10 genes with T2D-related phenotypes in a community-based Mexican cohort. Unrelated individuals (n = 259) living in southeastern Mexico were enrolled in the study based at the University of Yucatan School of Medicine in Merida. Phenotypes measured included anthropometric measurements, circulating levels of adipose tissue endocrine factors (leptin, adiponectin, pro-inflammatory cytokines), and insulin, glucose, and blood pressure. Association analyses were conducted by measured genotype analysis implemented in SOLAR, adapted for unrelated individuals. SNP Minor allele frequencies ranged from 2.2 to 48.6%. Nominal associations were found for CNR1, SLC30A8, GCK, and PCSK1 SNPs with systolic blood pressure, insulin and glucose, and for CNR1, SLC30A8, KCNJ11, and PCSK1 SNPs with adiponectin and leptin (p < 0.05). P-values greater than 0.0014 were considered significant. Association of SNPs rs10485170 of CNR1 and rs5215 of KCNJ11 with adiponectin and leptin, respectively, reached near significance (p = 0.002). Significant association (p = 0.001) was observed between plasma leptin and rs5219 of KCNJ11.
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Affiliation(s)
| | - Edna J Nava-Gonzalez
- Facultad de Salud Publica y Nutricion, Universidad Autonoma de Nuevo Leon Nuevo Leon, Monterrey, Mexico
| | - V Saroja Voruganti
- Nutrition and UNC Nutrition Research Institute, University of North Carolina Chapel Hill, NC, USA
| | - Jack W Kent
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
| | - Karin Haack
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
| | - Hugo A Laviada-Molina
- Departamento de Investigación, Escuela de Ciencias de la Salud, Universidad Marista de Merida Merida, Yucatan, Mexico
| | - Fernanda Molina-Segui
- Departamento de Investigación, Escuela de Ciencias de la Salud, Universidad Marista de Merida Merida, Yucatan, Mexico
| | | | | | - Shelley A Cole
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
| | - Marguerite J Mezzles
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
| | - Anthony G Comuzzie
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
| | - Raul A Bastarrachea
- Department of Genetics, Texas Biomedical Research Institute San Antonio, TX, USA
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24
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Chen J, Yang M, Zhao K, Xu A, Huang Q. Polymorphisms in FTO, TMEM18 and PCSK1 are associated with BMI in southern Chinese population. J Genet 2014; 93:509-512. [PMID: 25189249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Affiliation(s)
- Jie Chen
- College of Life Sciences, Central China Normal University, Wuhan 430079, People's Republic of China.
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25
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Grarup N, Sandholt CH, Hansen T, Pedersen O. Genetic susceptibility to type 2 diabetes and obesity: from genome-wide association studies to rare variants and beyond. Diabetologia 2014; 57:1528-41. [PMID: 24859358 DOI: 10.1007/s00125-014-3270-4] [Citation(s) in RCA: 127] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2013] [Accepted: 04/22/2014] [Indexed: 12/29/2022]
Abstract
During the past 7 years, genome-wide association studies have shed light on the contribution of common genomic variants to the genetic architecture of type 2 diabetes, obesity and related intermediate phenotypes. The discoveries have firmly established more than 175 genomic loci associated with these phenotypes. Despite the tight correlation between type 2 diabetes and obesity, these conditions do not appear to share a common genetic background, since they have few genetic risk loci in common. The recent genetic discoveries do however highlight specific details of the interplay between the pathogenesis of type 2 diabetes, insulin resistance and obesity. The focus is currently shifting towards investigations of data from targeted array-based genotyping and exome and genome sequencing to study the individual and combined effect of low-frequency and rare variants in metabolic disease. Here we review recent progress as regards the concepts, methodologies and derived outcomes of studies of the genetics of type 2 diabetes and obesity, and discuss avenues to be investigated in the future within this research field.
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Affiliation(s)
- Niels Grarup
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, DIKU Building, Universitetsparken 1, 2100, Copenhagen Ø, Denmark,
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26
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Crujeiras AB, Díaz-Lagares A, Abete I, Goyenechea E, Amil M, Martínez JA, Casanueva FF. Pre-treatment circulating leptin/ghrelin ratio as a non-invasive marker to identify patients likely to regain the lost weight after an energy restriction treatment. J Endocrinol Invest 2014; 37:119-26. [PMID: 24497210 DOI: 10.1007/s40618-013-0004-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2013] [Accepted: 11/17/2013] [Indexed: 12/14/2022]
Abstract
BACKGROUND Leptin and ghrelin appear to play a role in weight regain after a successful weight loss. The pre-treatment plasma levels of leptin/ghrelin ratio (L/G) could have power to predict this clinically relevant issue in the obesity treatment. OBJECTIVE To evaluate the ability of the L/G as a non-invasive tool for the early discrimination of obese patients who are more likely to regain weight after an energy restriction program (regainers) from those who maintain the lost weight (non-regainers). SUBJECTS AND METHODS Fasting leptin and ghrelin levels were evaluated in 88 overweight/obese patients who followed an 8-week hypocaloric diet program and were categorized as regainers (≥10 % weight-lost regain) and non-regainers (<10 % weight-lost regain) 6 months (32 weeks) after finishing the dietary treatment. A receiver operating characteristic (ROC) curve analysis was employed to evaluate the diagnostic value of the L/G ratio and to establish a cut-off point to differentiate regainers from non-regainers. RESULTS Regainers showed a statistically higher baseline (week 0) and after treatment (week 8) L/G ratio than non-regainers. The baseline L/G ratio was associated with an increased risk for weight regain (odds ratio 1.051; p = 0.008). Using the area under the ROC curve (AUC), the L/G ratio significantly identified female (AUC = 0.69; p = 0.040) and male regainers (AUC = 0.68; p = 0.030). The maximum combination of sensitivity and specificity was shown at the cut-off point of 26.0 for women and 9.5 for men. CONCLUSIONS The pre-intervention fasting leptin/ghrelin ratio could be a useful non-invasive approach to personalize obesity therapy and avoid unsuccessful treatment outcomes.
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Affiliation(s)
- A B Crujeiras
- Laboratory of Molecular and Cellular Endocrinology, Instituto de Investigación Sanitaria, Complejo Hospitalario Universitario de Santiago (CHUS) and Santiago de Compostela University (USC), C/Choupana, s/n, 15706, Santiago de Compostela, Spain,
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Hsiao TJ, Hwang Y, Chang HM, Lin E. Association of the rs6235 variant in the proprotein convertase subtilisin/kexin type 1 (PCSK1) gene with obesity and related traits in a Taiwanese population. Gene 2013; 533:32-7. [PMID: 24140494 DOI: 10.1016/j.gene.2013.10.016] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2013] [Revised: 09/25/2013] [Accepted: 10/09/2013] [Indexed: 12/22/2022]
Abstract
One particularly interesting single nucleotide polymorphism (SNP), rs6235 (encoding an S690T substitution), in the proprotein convertase subtilisin/kexin type 1 (PCSK1) gene has been widely associated with obesity in several European cohorts. The present study was intended to investigate the association between the PCSK1 rs6235 SNP and the prevalence of overweight or obesity, or obesity-related metabolic traits in a Taiwanese population. A total of 964 Taiwanese subjects with general health examinations were analyzed. Our data revealed no association of PCSK1 rs6235 with the risk of obesity or overweight in the complete subjects. However, the PCSK1 rs6235 SNP exhibited a significant association with overweight among the male subjects (P=0.03), but not among the female subjects. Furthermore, the carriers of GG variant had a significantly higher waist circumference than those with the CC variant (82.5 ± 11.5 vs. 81.2 ± 10.2 cm; P=0.01) and those with the CG variant (82.5 ± 11.5 vs. 81.4 ± 10.4 cm; P=0.021). In addition, the carriers of GG variant had a higher diastolic blood pressure than those with the CC variant (81.9 ± 14.2 vs. 80.3 ± 12.9 mm Hg; P=0.023). Our study indicates that the PCSK1 rs6235 SNP may contribute to the risk of overweight in men and predict obesity-related metabolic traits such as waist circumference and diastolic blood pressure in Taiwanese subjects.
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Affiliation(s)
- Tun-Jen Hsiao
- College of Public Health and Nutrition, Taipei Medical University, Taipei, Taiwan
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Garver WS, Newman SB, Gonzales-Pacheco DM, Castillo JJ, Jelinek D, Heidenreich RA, Orlando RA. The genetics of childhood obesity and interaction with dietary macronutrients. GENES AND NUTRITION 2013; 8:271-87. [PMID: 23471855 DOI: 10.1007/s12263-013-0339-5] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2012] [Accepted: 02/22/2013] [Indexed: 12/21/2022]
Abstract
The genes contributing to childhood obesity are categorized into three different types based on distinct genetic and phenotypic characteristics. These types of childhood obesity are represented by rare monogenic forms of syndromic or non-syndromic childhood obesity, and common polygenic childhood obesity. In some cases, genetic susceptibility to these forms of childhood obesity may result from different variations of the same gene. Although the prevalence for rare monogenic forms of childhood obesity has not increased in recent times, the prevalence of common childhood obesity has increased in the United States and developing countries throughout the world during the past few decades. A number of recent genome-wide association studies and mouse model studies have established the identification of susceptibility genes contributing to common childhood obesity. Accumulating evidence suggests that this type of childhood obesity represents a complex metabolic disease resulting from an interaction with environmental factors, including dietary macronutrients. The objective of this article is to provide a review on the origins, mechanisms, and health consequences of obesity susceptibility genes and interaction with dietary macronutrients that predispose to childhood obesity. It is proposed that increased knowledge of these obesity susceptibility genes and interaction with dietary macronutrients will provide valuable insight for individual, family, and community preventative lifestyle intervention, and eventually targeted nutritional and medicinal therapies.
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Affiliation(s)
- William S Garver
- Department of Biochemistry and Molecular Biology, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, 87131-0001, USA,
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McDonald D, Vázquez-Baeza Y, Walters WA, Caporaso JG, Knight R. From molecules to dynamic biological communities. BIOLOGY & PHILOSOPHY 2013; 28:241-259. [PMID: 23483075 PMCID: PMC3586164 DOI: 10.1007/s10539-013-9364-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2012] [Accepted: 01/23/2013] [Indexed: 05/22/2023]
Abstract
Microbial ecology is flourishing, and in the process, is making contributions to how the ecology and biology of large organisms is understood. Ongoing advances in sequencing technology and computational methods have enabled the collection and analysis of vast amounts of molecular data from diverse biological communities. While early studies focused on cataloguing microbial biodiversity in environments ranging from simple marine ecosystems to complex soil ecologies, more recent research is concerned with community functions and their dynamics over time. Models and concepts from traditional ecology have been used to generate new insight into microbial communities, and novel system-level models developed to explain and predict microbial interactions. The process of moving from molecular inventories to functional understanding is complex and challenging, and never more so than when many thousands of dynamic interactions are the phenomena of interest. We outline the process of how epistemic transitions are made from producing catalogues of molecules to achieving functional and predictive insight, and show how those insights not only revolutionize what is known about biological systems but also about how to do biology itself. Examples will be drawn primarily from analyses of different human microbiota, which are the microbial consortia found in and on areas of the human body, and their associated microbiomes (the genes of those communities). Molecular knowledge of these microbiomes is transforming microbiological knowledge, as well as broader aspects of human biology, health and disease.
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Affiliation(s)
- Daniel McDonald
- Department of Computer Science, University of Colorado at Boulder, Boulder, CO USA
- BioFrontiers Institute, University of Colorado at Boulder, Boulder, CO USA
| | - Yoshiki Vázquez-Baeza
- Department of Chemistry and Biochemistry, University of Colorado at Boulder, Boulder, CO USA
| | - William A. Walters
- Department of Molecular, Cellular and Developmental Biology, University of Colorado at Boulder, Boulder, CO USA
| | - J. Gregory Caporaso
- Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ USA
- Argonne National Laboratory, Institute for Genomics and Systems Biology, Argonne, IL USA
| | - Rob Knight
- Department of Computer Science, University of Colorado at Boulder, Boulder, CO USA
- BioFrontiers Institute, University of Colorado at Boulder, Boulder, CO USA
- Department of Chemistry and Biochemistry, University of Colorado at Boulder, Boulder, CO USA
- Howard Hughes Medical Institute, Boulder, CO USA
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Choquet H, Kasberger J, Hamidovic A, Jorgenson E. Contribution of common PCSK1 genetic variants to obesity in 8,359 subjects from multi-ethnic American population. PLoS One 2013; 8:e57857. [PMID: 23451278 PMCID: PMC3581482 DOI: 10.1371/journal.pone.0057857] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2012] [Accepted: 01/29/2013] [Indexed: 12/19/2022] Open
Abstract
Common PCSK1 variants (notably rs6232 and rs6235) have been shown to be associated with obesity in European, Asian and Mexican populations. To determine whether common PCSK1 variants contribute to obesity in American population, we conducted association analyses in 8,359 subjects using two multi-ethnic American studies: the Coronary Artery Risk Development in Young Adults (CARDIA) study and the Multi-Ethnic Study of Atherosclerosis (MESA). By evaluating the contribution of rs6232 and rs6235 in each ethnic group, we found that in European-American subjects from CARDIA, only rs6232 was associated with BMI (P = 0.006) and obesity (P = 0.018) but also increased the obesity incidence during the 20 years of follow-up (HR = 1.53 [1.07–2.19], P = 0.019). Alternatively, in African-American subjects from CARDIA, rs6235 was associated with BMI (P = 0.028) and obesity (P = 0.018). Further, by combining the two case-control ethnic groups from the CARDIA study in a meta-analysis, association between rs6235 and obesity risk remained significant (OR = 1.23 [1.05–1.45], P = 9.5×10−3). However, neither rs6232 nor rs6235 was associated with BMI or obesity in the MESA study. Interestingly, rs6232 was associated with BMI (P = 4.2×10−3) and obesity (P = 3.4×10−3) in the younger European-American group combining samples from the both studies [less than median age (53 years)], but not among the older age group (P = 0.756 and P = 0.935 for BMI and obesity, respectively). By combining all the case-control ethnic groups from CARDIA and MESA in a meta-analysis, we found no significant association for the both variants and obesity risk. Finally, by exploring the full PCSK1 locus, we observed that no variant remained significant after correction for multiple testing. These results indicate that common PCSK1 variants (notably rs6232 and rs6235) contribute modestly to obesity in multi-ethnic American population. Further, these results suggest that the association of rs6232 with obesity may be age-dependent in European-Americans. However, multiple replication studies in multi-ethnic American population are needed to confirm our findings.
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Affiliation(s)
- Hélène Choquet
- Ernest Gallo Clinic and Research Center, Emeryville, California, United States of America.
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Parks BW, Nam E, Org E, Kostem E, Norheim F, Hui ST, Pan C, Civelek M, Rau CD, Bennett BJ, Mehrabian M, Ursell LK, He A, Castellani LW, Zinker B, Kirby M, Drake TA, Drevon CA, Knight R, Gargalovic P, Kirchgessner T, Eskin E, Lusis AJ. Genetic control of obesity and gut microbiota composition in response to high-fat, high-sucrose diet in mice. Cell Metab 2013; 17:141-52. [PMID: 23312289 PMCID: PMC3545283 DOI: 10.1016/j.cmet.2012.12.007] [Citation(s) in RCA: 404] [Impact Index Per Article: 36.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2012] [Revised: 11/05/2012] [Accepted: 12/12/2012] [Indexed: 12/16/2022]
Abstract
Obesity is a highly heritable disease driven by complex interactions between genetic and environmental factors. Human genome-wide association studies (GWAS) have identified a number of loci contributing to obesity; however, a major limitation of these studies is the inability to assess environmental interactions common to obesity. Using a systems genetics approach, we measured obesity traits, global gene expression, and gut microbiota composition in response to a high-fat/high-sucrose (HF/HS) diet of more than 100 inbred strains of mice. Here we show that HF/HS feeding promotes robust, strain-specific changes in obesity that are not accounted for by food intake and provide evidence for a genetically determined set point for obesity. GWAS analysis identified 11 genome-wide significant loci associated with obesity traits, several of which overlap with loci identified in human studies. We also show strong relationships between genotype and gut microbiota plasticity during HF/HS feeding and identify gut microbial phylotypes associated with obesity.
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Affiliation(s)
- Brian W Parks
- Department of Medicine/Division of Cardiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.
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Abstract
Obesity and related complications are major health burdens. Almost 700 million adults are currently obese globally and the prevalence is predicted to rise towards 2030. The sudden change of lifestyle with physical inactivity and excessive calorie intake undoubtedly have a major part of the epidemic development; however, some individuals seem to be more prone to be affected by an unhealthy lifestyle than others. Hence, genetic predisposition also has an essential role in determining disease susceptibility and response to lifestyle factors. Since the introduction of genome-wide association studies (GWAS), the success of identifying obesity susceptibility variants have increased, and a total of 32 variants have been identified associating genome-wide significantly with body mass index (BMI) and 18 with measures of fat distribution during four overall obesity GWAS waves. However, the immediate success of the GWAS approach has eased off, but the proportion of explained variance for BMI by the identified obesity variants remains low. This review suggests and discusses new initiatives to take GWAS of obesity to the next level, including gene–environment interactions as modulating/masking factors, low-frequent or rare variants and ways to address such analyses, and finally reflections about the applicability of epigenetic modifications when elucidating the genetic background of obesity.
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Affiliation(s)
- C H Sandholt
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
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Villalobos-Comparán M, Villamil-Ramírez H, Villarreal-Molina T, Larrieta-Carrasco E, León-Mimila P, Romero-Hidalgo S, Jacobo-Albavera L, Liceaga-Fuentes AE, Campos-Pérez FJ, López-Contreras BE, Tusié-Luna T, del Río-Navarro BE, Aguilar-Salinas CA, Canizales-Quinteros S. PCSK1 rs6232 is associated with childhood and adult class III obesity in the Mexican population. PLoS One 2012; 7:e39037. [PMID: 22737226 PMCID: PMC3380862 DOI: 10.1371/journal.pone.0039037] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2012] [Accepted: 05/15/2012] [Indexed: 12/23/2022] Open
Abstract
Background Common variants rs6232 and rs6235 in the PCSK1 gene have been associated with obesity in European populations. We aimed to evaluate the contribution of these variants to obesity and related traits in Mexican children and adults. Methodology/Principal Findings Rs6232 and rs6235 were genotyped in 2382 individuals, 1206 children and 1176 adults. Minor allele frequencies were 0.78% for rs6232 and 19.99% for rs6235. Rs6232 was significantly associated with childhood obesity and adult class III obesity (OR = 3.01 95%CI 1.64–5.53; P = 4×10−4 in the combined analysis). In addition, this SNP was significantly associated with lower fasting glucose levels (P = 0.01) and with increased insulin levels and HOMA-B (P = 0.05 and 0.01, respectively) only in non-obese children. In contrast, rs6235 showed no significant association with obesity or with glucose homeostasis parameters in any group. Conclusion/Significance Although rs6232 is rare in the Mexican population, it should be considered as an important risk factor for extreme forms of obesity.
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Affiliation(s)
- Marisela Villalobos-Comparán
- Departamento de Biología, Facultad de Química, Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
- Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán” (INCMNSZ), Mexico City, Mexico
| | - Hugo Villamil-Ramírez
- Departamento de Biología, Facultad de Química, Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
- Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán” (INCMNSZ), Mexico City, Mexico
| | | | - Elena Larrieta-Carrasco
- Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán” (INCMNSZ), Mexico City, Mexico
| | - Paola León-Mimila
- Departamento de Biología, Facultad de Química, Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
- Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán” (INCMNSZ), Mexico City, Mexico
| | | | - Leonor Jacobo-Albavera
- Departamento de Biología, Facultad de Química, Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
- Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán” (INCMNSZ), Mexico City, Mexico
| | | | | | - Blanca E. López-Contreras
- Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán” (INCMNSZ), Mexico City, Mexico
- Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City, Mexico
| | - Teresa Tusié-Luna
- Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán” (INCMNSZ), Mexico City, Mexico
- Instituto de investigaciones Biomédicas, Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
| | - Blanca E. del Río-Navarro
- Departamento de Alergia e Inmunología Clínica, Hospital Infantil de México Federico Gómez, Mexico City, Mexico
| | | | - Samuel Canizales-Quinteros
- Departamento de Biología, Facultad de Química, Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
- Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán” (INCMNSZ), Mexico City, Mexico
- * E-mail:
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Abstract
OBJECTIVE Birth weight reflects prenatal metabolic adaption and has been related to later-life obesity risk. This study aimed to evaluate whether birth weight modifies the effect of genetic susceptibility on obesity risk in young Chinese. METHODS We recruited 540 young (14-30 years) and obese patients (body mass index, BMI30 kg m(-2)), and 500 age- and sex-matched normal-weight healthy individuals (BMI<23 kg m(-2)). We genotyped 23 BMI-associated genetic variants identified from recent genome-wide association studies (GWAS) in Caucasians with European ancestry with minor allele frequency>0.05 in HapMap Han Chinese in Beijing, China. RESULTS Six loci, including SEC16B, GNPDA2, BDNF, FTO, MC4R and TMEM160, were significantly associated with obesity risk, with odds ratio from 1.314 to 1.701. The 23 risk loci accounted for 6.38% of the genetic variance in obesity. We created two genetic risk scores (GRSs) by summing the risk alleles of all 23 (GRS1) and 6 obesity-associated (GRS2) genetic variants. Prediction of obesity was significantly improved (P<0.001) when the GRS1 and GRS2 were added to a model with age and gender, with improvement of discrimination for obesity by 0.8% and 2.7%, respectively. In addition, we found that the two GRSs interacted with birth weight in relation to obesity (Pinteraction<0.001). The genetic effect appeared to be more pronounced in individuals with normal range of birth weight (25-75%) than those with either low (<25%) or high (>75%) birth weight. CONCLUSION We confirmed the associations of the single-nucleotide polymorphism tagging six loci reported in recent GWAS with obesity in young Chinese. Our data also suggest birth weight may significantly modify genetic susceptibility to obesity risk.
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The frequent UCP2 -866G>A polymorphism protects against insulin resistance and is associated with obesity: a study of obesity and related metabolic traits among 17 636 Danes. Int J Obes (Lond) 2012; 37:175-81. [PMID: 22349573 DOI: 10.1038/ijo.2012.22] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
CONTEXT Uncoupling protein 2 (UCP2) is involved in regulating ATP synthesis, generation of reactive oxygen species and glucose-stimulated insulin secretion in β-cells. Polymorphisms in UCP2 may be associated with obesity and type 2 diabetes mellitus. OBJECTIVE To determine the influence of a functional UCP2 promoter polymorphism (-866G>A, rs659366) on obesity, type 2 diabetes and intermediary metabolic traits. Furthermore, to include these and previously published data in a meta-analysis of this variant with respect to its impact on obesity and type 2 diabetes. DESIGN We genotyped UCP2 rs659366 in a total of 17 636 Danish individuals and established case-control studies of obese and non-obese subjects and of type 2 diabetic and glucose-tolerant subjects. Meta-analyses were made in own data set and in publicly available data sets. Quantitative traits relevant for obesity and type 2 diabetes were analysed within separate study populations. RESULTS We found no consistent associations between the UCP2 -866G-allele and obesity or type 2 diabetes. Yet, a meta-analysis of data from 12 984 subjects showed an association with obesity (GA vs GG odds ratio (OR) (95% confidence interval (CI)): 0.894(0.826-0.968) P=0.00562, and AA vs GG OR(95% CI): 0.892(0.800-0.996), P=0.0415. Moreover, a meta-analysis for type 2 diabetes of 15 107 individuals showed no association. The -866G-allele was associated with elevated fasting serum insulin levels (P=0.002) and HOMA insulin resistance index (P=0.0007). Insulin sensitivity measured during intravenous glucose tolerance test in young Caucasian subjects (n=377) was decreased in carriers of the GG genotype (P=0.05). CONCLUSIONS The UCP2 -866G-allele is associated with decreased insulin sensitivity in Danish subjects and is associated with obesity in a combined meta-analysis.
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Rouskas K, Kouvatsi A, Paletas K, Papazoglou D, Tsapas A, Lobbens S, Vatin V, Durand E, Labrune Y, Delplanque J, Meyre D, Froguel P. Common variants in FTO, MC4R, TMEM18, PRL, AIF1, and PCSK1 show evidence of association with adult obesity in the Greek population. Obesity (Silver Spring) 2012; 20:389-95. [PMID: 21720444 DOI: 10.1038/oby.2011.177] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Twenty-four single-nucleotide polymorphisms (SNPs) have been reproducibly associated with obesity. We performed a follow-up study for obesity in the Greek adult population. A total of 510 obese and 469 lean adults were genotyped for 24 SNPs. We tested the association with obesity status using logistic regression and we evaluated the combined genetic risk of 24 SNPs by calculating the area under the receiver-operating characteristic (ROC) curves. We nominally replicated the association with obesity (BMI ≥30 kg/m(2)) of six SNPs in or near the FTO, MC4R, TMEM18, PRL, AIF1, and PCSK1 loci (1.28 ≤ odds ratio (OR) ≤ 1.35; 0.004 ≤ P ≤ 0.043). The discrimination ability for obesity was slightly stronger (P = 9.59 × 10(-6)) when the genetic information of the 24 SNPs was added to nongenetic risk factors (area under the curve (AUC) = 0.722) in comparison with nongenetic factors analyzed alone (AUC = 0.685). Our data suggest that SNPs in or near the FTO, MC4R, TMEM18, PRL, AIF1, and PCSK1 loci contribute to obesity risk in the Greek population.
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Affiliation(s)
- Konstantinos Rouskas
- Department of Genetics, Development and Molecular Biology, School of Biology, Aristotle University of Thessaloniki, Thessaloniki, Greece.
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Creemers JW, Choquet H, Stijnen P, Vatin V, Pigeyre M, Beckers S, Meulemans S, Than ME, Yengo L, Tauber M, Balkau B, Elliott P, Jarvelin MR, Van Hul W, Van Gaal L, Horber F, Pattou F, Froguel P, Meyre D. Heterozygous mutations causing partial prohormone convertase 1 deficiency contribute to human obesity. Diabetes 2012; 61:383-90. [PMID: 22210313 PMCID: PMC3266396 DOI: 10.2337/db11-0305] [Citation(s) in RCA: 81] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Null mutations in the PCSK1 gene, encoding the proprotein convertase 1/3 (PC1/3), cause recessive monogenic early onset obesity. Frequent coding variants that modestly impair PC1/3 function mildly increase the risk for common obesity. The aim of this study was to determine the contribution of rare functional PCSK1 mutations to obesity. PCSK1 exons were sequenced in 845 nonconsanguineous extremely obese Europeans. Eight novel nonsynonymous PCSK1 mutations were identified, all heterozygous. Seven mutations had a deleterious effect on either the maturation or the enzymatic activity of PC1/3 in cell lines. Of interest, five of these novel mutations, one of the previously described frequent variants (N221D), and the mutation found in an obese mouse model (N222D), affect residues at or near the structural calcium binding site Ca-1. The prevalence of the newly identified mutations was assessed in 6,233 obese and 6,274 lean European adults and children, which showed that carriers of any of these mutations causing partial PCSK1 deficiency had an 8.7-fold higher risk to be obese than wild-type carriers. These results provide the first evidence of an increased risk of obesity in heterozygous carriers of mutations in the PCSK1 gene. Furthermore, mutations causing partial PCSK1 deficiency are present in 0.83% of extreme obesity phenotypes.
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Affiliation(s)
- John W.M. Creemers
- Department of Human Genetics, University of Leuven, Leuven, Belgium
- Corresponding authors: John W.M. Creemers, , and Philippe Froguel,
| | - Hélène Choquet
- Centre National de la Recherche Scientifique (CNRS) 8199, Lille North of France University, Pasteur Institute, Lille, France
| | - Pieter Stijnen
- Department of Human Genetics, University of Leuven, Leuven, Belgium
| | - Vincent Vatin
- Centre National de la Recherche Scientifique (CNRS) 8199, Lille North of France University, Pasteur Institute, Lille, France
| | - Marie Pigeyre
- Department of Nutrition, Hospital University, Lille, France
| | - Sigri Beckers
- Department of Medical Genetics, University of Antwerp, Antwerp, Belgium
| | - Sandra Meulemans
- Department of Human Genetics, University of Leuven, Leuven, Belgium
| | - Manuel E. Than
- Leibniz Institute for Age Research, Fritz Lipmann Institute, Jena, Germany
| | - Loïc Yengo
- Centre National de la Recherche Scientifique (CNRS) 8199, Lille North of France University, Pasteur Institute, Lille, France
| | - Maithé Tauber
- INSERM U563, Children’s Hospital, Centre Hospitalier Universitaire, Toulouse, France
| | - Beverley Balkau
- INSERM U1018, Villejuif, France
- University Paris Sud 11, UMRS 1018, Villejuif, France
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, and MRC-HPA Centre for Environment and Health, Imperial College London, London, U.K
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, and MRC-HPA Centre for Environment and Health, Imperial College London, London, U.K
- Department of Child and Adolescent Health, National Public Health Institute, Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Wim Van Hul
- Department of Medical Genetics, University of Antwerp, Antwerp, Belgium
| | - Luc Van Gaal
- Department of Endocrinology, Antwerp University Hospital, Antwerp, Belgium
| | - Fritz Horber
- Department of Surgery and Internal Medicine, Clinic Lindberg, Winterthur, Switzerland
| | - François Pattou
- INSERM U859, Lille North of France University, Lille, France
| | - Philippe Froguel
- Centre National de la Recherche Scientifique (CNRS) 8199, Lille North of France University, Pasteur Institute, Lille, France
- Department of Genomics of Common Disease, School of Public Health, Imperial College London, London, U.K
- Corresponding authors: John W.M. Creemers, , and Philippe Froguel,
| | - David Meyre
- Centre National de la Recherche Scientifique (CNRS) 8199, Lille North of France University, Pasteur Institute, Lille, France
- Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada
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Choquet H, Meyre D. Molecular basis of obesity: current status and future prospects. Curr Genomics 2011; 12:154-68. [PMID: 22043164 PMCID: PMC3137001 DOI: 10.2174/138920211795677921] [Citation(s) in RCA: 75] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2011] [Revised: 03/30/2011] [Accepted: 03/31/2011] [Indexed: 12/15/2022] Open
Abstract
Obesity is a global health problem that is gradually affecting each continent of the world. Obesity is a heterogeneous disorder, and the biological causes of obesity are complex. The rapid increase in obesity prevalence during the past few decades is due to major societal changes (sedentary lifestyle, over-nutrition) but who becomes obese at the individual level is determined to a great extent by genetic susceptibility. In this review, we evidence that obesity is a strongly heritable disorder, and provide an update on the molecular basis of obesity. To date, nine loci have been involved in Mendelian forms of obesity and 58 loci contribute to polygenic obesity, and rare and common structural variants have been reliably associated with obesity. Most of the obesity genes remain to be discovered, but promising technologies, methodologies and the use of “deep phenotyping” lead to optimism to chip away at the ‘missing heritability’ of obesity in the near future. In the longer term, the genetic dissection of obesity will help to characterize disease mechanisms, provide new targets for drug design, and lead to an early diagnosis, treatment, and prevention of obesity.
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Affiliation(s)
- Hélène Choquet
- Ernest Gallo Clinic and Research Center, Department of Neurology, University of California, San Francisco, Emeryville, CA 94608, USA
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Choquet H, Meyre D. Genetics of Obesity: What have we Learned? Curr Genomics 2011; 12:169-79. [PMID: 22043165 PMCID: PMC3137002 DOI: 10.2174/138920211795677895] [Citation(s) in RCA: 139] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2011] [Revised: 03/31/2011] [Accepted: 03/31/2011] [Indexed: 12/14/2022] Open
Abstract
Candidate gene and genome-wide association studies have led to the discovery of nine loci involved in Mendelian forms of obesity and 58 loci contributing to polygenic obesity. These loci explain a small fraction of the heritability for obesity and many genes remain to be discovered. However, efforts in obesity gene identification greatly modified our understanding of this disorder. In this review, we propose an overlook of major lessons learned from 15 years of research in the field of genetics and obesity. We comment on the existence of the genetic continuum between monogenic and polygenic forms of obesity that pinpoints the role of genes involved in the central regulation of food intake and genetic predisposition to obesity. We explain how the identification of novel obesity predisposing genes has clarified unsuspected biological pathways involved in the control of energy balance that have helped to understand past human history and to explore causality in epidemiology. We provide evidence that obesity predisposing genes interact with the environment and influence the response to treatment relevant to disease prediction.
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Affiliation(s)
- Hélène Choquet
- Ernest Gallo Clinic and Research Center, Department of Neurology, University of California, San Francisco, Emeryville, California 94608, USA
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The effect of PCSK1 variants on waist, waist-hip ratio and glucose metabolism is modified by sex and glucose tolerance status. PLoS One 2011; 6:e23907. [PMID: 21935364 PMCID: PMC3173365 DOI: 10.1371/journal.pone.0023907] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2010] [Accepted: 07/29/2011] [Indexed: 12/25/2022] Open
Abstract
Background We aimed to evaluate the effects of the G-allele of rs6232 and the C-allele of rs6235 within PCSK1 on measures of body fat and glucose homeostasis in Danish individuals and to assess interactions of genotypes with age, sex and glucose tolerance status. Data were included in meta-analyses of additional Europeans. Methodology/Principal Findings Rs6232 and rs6235 were genotyped in 6,164 Danes from the Inter99 study of middle-aged people. Results from these analyses were combined with previously published studies in meta-analyses of a total of 27,786 individuals. The impact of the variants was also investigated in a subset of 62 glucose-tolerant men during a meal challenge including measures of serum incretins. In men we found an effect on body composition in sex-stratified analyses where the rs6235 C-allele conferred an increased waist circumference of 0.8 cm per allele (0.2–1.5, p = 0.008) and increased waist-to-hip ratio of 0.004 (0.0005–0.008, p = 0.027). In the meta-analyses where men and women were combined, the rs6232 G-allele associated with increased waist-to-hip ratio (p = 0.02) and the rs6235 C-allele associated with increased waist circumference (p = 0.01). Furthermore, the rs6235 C-allele was associated nominally with a 0.6% (0.1–1%, p = 0.01) reduction in fasting glucose, it interacted with glucose tolerance status for traits related to glucose metabolism and analysis among individuals having abnormal glucose tolerance revealed a 5% (−0.7–9%, p = 0.02) elevated level of acute insulin response for this variant. Finally, we found that the rs6232 G-allele associated with higher levels of GLP-1, GLP-2 and glucagon and that the rs6235 C-allele associated with higher levels of GIP and glucagon during a meal-test. Conclusions/Significance PCSK1 rs6232 G-allele and rs6235 C-allele have an effect on body composition which may be modified by sex, whereas the effect of rs6235 C-allele on fasting and stimulated circulating plasma glucose and hormone levels may be influenced by glucose tolerance status.
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Sandholt CH, Vestmar MA, Bille DS, Borglykke A, Almind K, Hansen L, Sandbæk A, Lauritzen T, Witte D, Jørgensen T, Pedersen O, Hansen T. Studies of metabolic phenotypic correlates of 15 obesity associated gene variants. PLoS One 2011; 6:e23531. [PMID: 21912638 PMCID: PMC3166286 DOI: 10.1371/journal.pone.0023531] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2011] [Accepted: 07/19/2011] [Indexed: 11/19/2022] Open
Abstract
AIMS Genome-wide association studies have identified novel BMI/obesity associated susceptibility loci. The purpose of this study is to determine associations with overweight, obesity, morbid obesity and/or general adiposity in a Danish population. Moreover, we want to investigate if these loci associate with type 2 diabetes and to elucidate potential underlying metabolic mechanisms. METHODS 15 gene variants in 14 loci including TMEM18 (rs7561317), SH2B1 (rs7498665), KCTD15 (rs29941), NEGR1 (rs2568958), ETV5 (rs7647305), BDNF (rs4923461, rs925946), SEC16B (rs10913469), FAIM2 (rs7138803), GNPDA2 (rs10938397), MTCH2 (rs10838738), BAT2 (rs2260000), NPC1 (rs1805081), MAF (rs1424233), and PTER (rs10508503) were genotyped in 18,014 middle-aged Danes. RESULTS Five of the 15 gene variants associated with overweight, obesity and/or morbid obesity. Per allele ORs ranged from 1.15-1.20 for overweight, 1.10-1.25 for obesity, and 1.41-1.46 for morbid obesity. Five of the 15 variants moreover associated with increased measures of adiposity. BDNF rs4923461 displayed a borderline BMI-dependent protective effect on type 2 diabetes (0.87 (0.78-0.96, p = 0.008)), whereas SH2B1 rs7498665 associated with nominally BMI-independent increased risk of type 2 diabetes (1.16 (1.07-1.27, p = 7.8×10(-4))). CONCLUSIONS Associations with overweight and/or obesity and measures of obesity were confirmed for seven out of the 15 gene variants. The obesity risk allele of BDNF rs4923461 protected against type 2 diabetes, which could suggest neuronal and peripheral distinctive ways of actions for the protein. SH2B1 rs7498665 associated with type 2 diabetes independently of BMI.
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Affiliation(s)
- Camilla Helene Sandholt
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.
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Kerr KF, McClelland RL, Brown ER, Lumley T. Evaluating the incremental value of new biomarkers with integrated discrimination improvement. Am J Epidemiol 2011; 174:364-74. [PMID: 21673124 PMCID: PMC3202159 DOI: 10.1093/aje/kwr086] [Citation(s) in RCA: 154] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2010] [Accepted: 02/28/2011] [Indexed: 12/31/2022] Open
Abstract
The integrated discrimination improvement (IDI) index is a popular tool for evaluating the capacity of a marker to predict a binary outcome of interest. Recent reports have proposed that the IDI is more sensitive than other metrics for identifying useful predictive markers. In this article, the authors use simulated data sets and theoretical analysis to investigate the statistical properties of the IDI. The authors consider the common situation in which a risk model is fitted to a data set with and without the new, candidate predictor(s). Results demonstrate that the published method of estimating the standard error of an IDI estimate tends to underestimate the error. The z test proposed in the literature for IDI-based testing of a new biomarker is not valid, because the null distribution of the test statistic is not standard normal, even in large samples. If a test for the incremental value of a marker is desired, the authors recommend the test based on the model. For investigators who find the IDI to be a useful measure, bootstrap methods may offer a reasonable option for inference when evaluating new predictors, as long as the added predictive capacity is large.
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Affiliation(s)
- Kathleen F Kerr
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, USA.
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Jiao H, Arner P, Hoffstedt J, Brodin D, Dubern B, Czernichow S, van't Hooft F, Axelsson T, Pedersen O, Hansen T, Sørensen TIA, Hebebrand J, Kere J, Dahlman-Wright K, Hamsten A, Clement K, Dahlman I. Genome wide association study identifies KCNMA1 contributing to human obesity. BMC Med Genomics 2011; 4:51. [PMID: 21708048 PMCID: PMC3148553 DOI: 10.1186/1755-8794-4-51] [Citation(s) in RCA: 67] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2010] [Accepted: 06/28/2011] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND Recent genome-wide association (GWA) analyses have identified common single nucleotide polymorphisms (SNPs) that are associated with obesity. However, the reported genetic variation in obesity explains only a minor fraction of the total genetic variation expected to be present in the population. Thus many genetic variants controlling obesity remain to be identified. The aim of this study was to use GWA followed by multiple stepwise validations to identify additional genes associated with obesity. METHODS We performed a GWA analysis in 164 morbidly obese subjects (BMI:body mass index>40 kg/m2) and 163 Swedish subjects (>45 years) who had always been lean. The 700 SNPs displaying the strongest association with obesity in the GWA were analyzed in a second cohort comprising 460 morbidly obese subjects and 247 consistently lean Swedish adults. 23 SNPs remained significantly associated with obesity (nominal P<0.05) and were in a step-wise manner followed up in five additional cohorts from Sweden, France, and Germany together comprising 4214 obese and 5417 lean or population-based control individuals. Three samples, n=4133, were used to investigate the population-based associations with BMI. Gene expression in abdominal subcutaneous adipose tissue in relation to obesity was investigated for14 adults. RESULTS Potassium channel, calcium activated, large conductance, subfamily M, alpha member (KCNMA1) rs2116830*G and BDNF rs988712*G were associated with obesity in five of six investigated case-control cohorts. In meta-analysis of 4838 obese and 5827 control subjects we obtained genome-wide significant allelic association with obesity for KCNMA1 rs2116830*G with P=2.82×10(-10) and an odds ratio (OR) based on cases vs controls of 1.26 [95% C.I. 1.12-1.41] and for BDNF rs988712*G with P=5.2×10(-17) and an OR of 1.36 [95% C.I. 1.20-1.55]. KCNMA1 rs2116830*G was not associated with BMI in the population-based samples. Adipose tissue (P=0.0001) and fat cell (P=0.04) expression of KCNMA1 was increased in obesity. CONCLUSIONS We have identified KCNMA1 as a new susceptibility locus for obesity, and confirmed the association of the BDNF locus at the genome-wide significant level.
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Affiliation(s)
- Hong Jiao
- Department of Biosciences and Nutrition, Karolinska Institutet, SE-141 83 Huddinge, Sweden
- Clinical Research Centre, Karolinska University Hospital, SE-141 57 Stockholm, Sweden
| | - Peter Arner
- Department of Medicine at Karolinska Institutet and Karolinska University Hospital, SE-141 86 Stockholm, Sweden
| | - Johan Hoffstedt
- Department of Medicine at Karolinska Institutet and Karolinska University Hospital, SE-141 86 Stockholm, Sweden
| | - David Brodin
- Department of Biosciences and Nutrition, Karolinska Institutet, SE-141 83 Huddinge, Sweden
| | - Beatrice Dubern
- INSERM, U-557/INRA U-1125, CNAM, UP13, CRNH-IdF, 93017 Bobigny, France; University Paris 13, 93017, Bobigny, France; AP-HP, Avicenne Hospital, 93017 Bobigny, France
| | - Sébastien Czernichow
- INSERM, U-557/INRA U-1125, CNAM, UP13, CRNH-IdF, 93017 Bobigny, France; University Paris 13, 93017, Bobigny, France; AP-HP, Avicenne Hospital, 93017 Bobigny, France
| | - Ferdinand van't Hooft
- Cardiovascular Genetics Group, Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, SE-17176 Stockholm, Sweden
| | - Tomas Axelsson
- Department of Medical Sciences, Molecular Medicine, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Oluf Pedersen
- Hagedorn Research Institute, Gentofte,, Copenhagen, Denmark
- Center of Basic Metabolic Research, Faculty of Health Sciences, University of Copenhagen, Denmark
| | - Torben Hansen
- Hagedorn Research Institute, Gentofte,, Copenhagen, Denmark
- Center of Basic Metabolic Research, Faculty of Health Sciences, University of Copenhagen, Denmark
| | - Thorkild IA Sørensen
- Institute for Preventive Medicine, Copenhagen University Hospital, Center for Health and Society, Copenhagen, Denmark
| | - Johannes Hebebrand
- Department of Child and Adolescent Psychiatry of the University of Duisburg-Essen, Essen, Germany
| | - Juha Kere
- Department of Biosciences and Nutrition, Karolinska Institutet, SE-141 83 Huddinge, Sweden
- Clinical Research Centre, Karolinska University Hospital, SE-141 57 Stockholm, Sweden
| | - Karin Dahlman-Wright
- Department of Biosciences and Nutrition, Karolinska Institutet, SE-141 83 Huddinge, Sweden
| | - Anders Hamsten
- Cardiovascular Genetics Group, Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, SE-17176 Stockholm, Sweden
| | - Karine Clement
- INSERM, U-872, Nutriomique (team 7) 75006 Paris, France; University Pierre and Marie Curie-Paris 6, Cordeliers Research Center, 75006 Paris, France; AP-HP, Pitié-Salpétrière Hospital, 75013 Paris, France
| | - Ingrid Dahlman
- Department of Medicine at Karolinska Institutet and Karolinska University Hospital, SE-141 86 Stockholm, Sweden
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Santos JL, De la Cruz R, Holst C, Grau K, Naranjo C, Maiz A, Astrup A, Saris WHM, MacDonald I, Oppert JM, Hansen T, Pedersen O, Sorensen TIA, Martinez JA. Allelic variants of melanocortin 3 receptor gene (MC3R) and weight loss in obesity: a randomised trial of hypo-energetic high- versus low-fat diets. PLoS One 2011; 6:e19934. [PMID: 21695122 PMCID: PMC3114803 DOI: 10.1371/journal.pone.0019934] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2010] [Accepted: 04/21/2011] [Indexed: 11/29/2022] Open
Abstract
Introduction The melanocortin system plays an important role in energy homeostasis. Mice genetically deficient in the melanocortin-3 receptor gene have a normal body weight with increased body fat, mild hypophagia compared to wild-type mice. In humans, Thr6Lys and Val81Ile variants of the melanocortin-3 receptor gene (MC3R) have been associated with childhood obesity, higher BMI Z-score and elevated body fat percentage compared to non-carriers. The aim of this study is to assess the association in adults between allelic variants of MC3R with weight loss induced by energy-restricted diets. Subjects and Methods This research is based on the NUGENOB study, a trial conducted to assess weight loss during a 10-week dietary intervention involving two different hypo-energetic (high-fat and low-fat) diets. A total of 760 obese patients were genotyped for 10 single nucleotide polymorphisms covering the single exon of MC3R gene and its flanking regions, including the missense variants Thr6Lys and Val81Ile. Linear mixed models and haplotype-based analysis were carried out to assess the potential association between genetic polymorphisms and differential weight loss, fat mass loss, waist change and resting energy expenditure changes. Results No differences in drop-out rate were found by MC3R genotypes. The rs6014646 polymorphism was significantly associated with weight loss using co-dominant (p = 0.04) and dominant models (p = 0.03). These p-values were not statistically significant after strict control for multiple testing. Haplotype-based multivariate analysis using permutations showed that rs3827103–rs1543873 (p = 0.06), rs6014646–rs6024730 (p = 0.05) and rs3746619–rs3827103 (p = 0.10) displayed near-statistical significant results in relation to weight loss. No other significant associations or gene*diet interactions were detected for weight loss, fat mass loss, waist change and resting energy expenditure changes. Conclusion The study provided overall sufficient evidence to support that there is no major effect of genetic variants of MC3R and differential weight loss after a 10-week dietary intervention with hypo-energetic diets in obese Europeans.
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Affiliation(s)
- José L. Santos
- Department of Nutrition, Diabetes and Metabolism, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Nutrition and Food Sciences, Physiology and Toxicology, University of Navarra, Pamplona, Spain
| | - Rolando De la Cruz
- Department of Public Health and Department of Statistics, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Claus Holst
- Centre for Health and Society, Institute of Preventive Medicine, Copenhagen University Hospital, Copenhagen, Denmark
| | - Katrine Grau
- Centre for Health and Society, Institute of Preventive Medicine, Copenhagen University Hospital, Copenhagen, Denmark
| | - Carolina Naranjo
- Department of Public Health and Department of Statistics, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Alberto Maiz
- Department of Nutrition, Diabetes and Metabolism, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Arne Astrup
- Department of Human Nutrition, Faculty of Life Science, University of Copenhagen, Copenhagen, Denmark
| | - Wim H. M. Saris
- Department of Human Biology, Nutrition and Toxicology Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands
| | - Ian MacDonald
- School of Biomedical Science, University of Nottingham Medical School, Queen's Medical Centre, Nottingham, United Kingdom
| | - Jean-Michel Oppert
- Department of Nutrition, Hotel-Dieu Hospital University Pierre-et-Marie Curie (Paris 6), Human Nutrition Research Center Ile-de-France, Paris, France
| | | | - Oluf Pedersen
- Hagedorn Research Institute, Gentofte, Denmark
- Institute of Biomedical Science, University of Copenhagen, Copenhagen, Denmark
| | - Thorkild I. A. Sorensen
- Centre for Health and Society, Institute of Preventive Medicine, Copenhagen University Hospital, Copenhagen, Denmark
| | - J. Alfredo Martinez
- Department of Nutrition and Food Sciences, Physiology and Toxicology, University of Navarra, Pamplona, Spain
- * E-mail:
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Travers ME, McCarthy MI. Type 2 diabetes and obesity: genomics and the clinic. Hum Genet 2011; 130:41-58. [PMID: 21647602 DOI: 10.1007/s00439-011-1023-8] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2011] [Accepted: 05/26/2011] [Indexed: 12/11/2022]
Abstract
Type 2 diabetes (T2D) and obesity represent major challenges for global public health. They are at the forefront of international efforts to identify the genetic variation contributing to complex disease susceptibility, and recent years have seen considerable success in identifying common risk-variants. Given the clinical impact of molecular diagnostics in rarer monogenic forms of these diseases, expectations have been high that genetic discoveries will transform the prospects for risk stratification, development of novel therapeutics and personalised medicine. However, so far, clinical translation has been limited. Difficulties in defining the alleles and transcripts mediating association effects have frustrated efforts to gain early biological insights, whilst the fact that variants identified account for only a modest proportion of observed familiarity has limited their value in guiding treatment of individual patients. Ongoing efforts to track causal variants through fine-mapping and to illuminate the biological mechanisms through which they act, as well as sequence-based discovery of lower-frequency alleles (of potentially larger effect), should provide welcome acceleration in the capacity for clinical translation. This review will summarise recent advances in identifying risk alleles for T2D and obesity, and existing contributions to understanding disease pathology. It will consider the progress made in translating genetic knowledge into clinical utility, the challenges remaining, and the realistic potential for further progress.
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Affiliation(s)
- Mary E Travers
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, University of Oxford, Old Road, Headington, Oxford OX3 7LJ, UK
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Blakemore AIF, Froguel P. Investigation of Mendelian forms of obesity holds out the prospect of personalized medicine. Ann N Y Acad Sci 2011; 1214:180-9. [PMID: 21175686 DOI: 10.1111/j.1749-6632.2010.05880.x] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Mendelian forms of obesity are already known to account for approximately 5% of the severely obese but are currently underinvestigated. In contrast, there has been much recent concentration on genome-wide single nucleotide polymorphism (SNP) associations in obesity, with particular emphasis given to the role of the fat mass and obesity associated (FTO) gene. Unfortunately, despite the enormous resources devoted to this work, none of the SNP markers in the ∼30 genes discovered to have associations with common obesity have meaningful predictive power. This is very different from the situation for Mendelian obesity, where mutations have very clear effects on phenotype. Study of Mendelian obesity has also added significantly to our understanding of mechanisms of appetite regulation, with all known causative genes being active in the brain and most forming part of the leptin-melanocortin signaling pathway. Investigation of genomic structural variation has also recently revealed deletions causing obesity, sometimes with concomitant neurocognitive dysfunction. Advances in next-generation sequencing are expected to uncover additional highly penetrant causes of obesity. Screening for Mendelian forms of obesity is rarely carried out but holds considerable promise for improved clinical care of these high-risk patients.
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Affiliation(s)
- Alexandra I F Blakemore
- Department of Genomics of Common Disease, School of Public Health, Imperial College London, London, United Kingdom.
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Andersson EA, Pilgaard K, Pisinger C, Harder MN, Grarup N, Færch K, Sandholt C, Poulsen P, Witte DR, Jørgensen T, Vaag A, Pedersen O, Hansen T. Do gene variants influencing adult adiposity affect birth weight? A population-based study of 24 loci in 4,744 Danish individuals. PLoS One 2010; 5:e14190. [PMID: 21152014 PMCID: PMC2995733 DOI: 10.1371/journal.pone.0014190] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2010] [Accepted: 11/09/2010] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Several obesity risk alleles affecting adult adiposity have been identified by the recent wave of genome wide association studies. We aimed to examine the potential effect of these variants on fetal body composition by investigating the variants in relation to birth weight and ponderal index of the newborn. METHODOLOGY/PRINCIPAL FINDINGS Midwife records from the Danish State Archives provided information on mother's age, parity, as well as birth weight, birth length and prematurity of the newborn in 4,744 individuals of the population-based Inter99 study. Twenty-four risk alleles showing genome-wide associations with adult BMI and/or waist circumference were genotyped. None of the 24 risk variants tested showed an association with birth weight or ponderal index after correction for multiple testing. Birth weight was divided into three categories low (≤10(th) percentile), normal (10(th)-90(th) percentile) and high birth weight (≥90th percentile) to allow for non-linear associations. There was no difference in the number of risk alleles between the groups (p = 0.57). No interactions between each risk allele and birth weight in the prediction of adult BMI were observed. An obesity risk score was created by summing up risk alleles. The risk score did not associate with fetal body composition. Moreover there was no interaction between the risk score and birth weight/ponderal index in the prediction of adult BMI. CONCLUSION 24 common variants associated with adult adiposity did not affect or interact with birth weight among Danes suggesting that the effects of these variants predominantly arise in the post-natal life.
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Affiliation(s)
| | | | - Charlotta Pisinger
- Research Centre for Prevention and Health, Glostrup University Hospital, Glostrup, Denmark
| | | | | | | | | | | | | | - Torben Jørgensen
- Research Centre for Prevention and Health, Glostrup University Hospital, Glostrup, Denmark
- Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
| | - Allan Vaag
- Steno Diabetes Center, Gentofte, Denmark
| | - Oluf Pedersen
- Hagedorn Research Institute, Gentofte, Denmark
- Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Torben Hansen
- Hagedorn Research Institute, Gentofte, Denmark
- Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
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Abstract
The biological causes of childhood obesity are complex. Environmental factors, such as massive marketing campaigns for food leading to over-nutrition and snacking and the decline in physical activity, have undoubtedly contributed to the increased prevalence of overweight and obesity in children, but these cannot be considered as the only causes. Susceptibility to obesity is also determined to a great extent by genetic factors. Furthermore, molecular mechanisms involved in the regulation of gene expression, such as epigenetic mechanisms, can increase the risk of developing early-onset obesity. There is evidence that early-onset obesity is a heritable disorder, and a range of genetic factors have recently been shown to cause monogenic, syndromic and polygenic forms of obesity, in some cases interacting with environmental exposures. Modifications of the transcriptome can lead to increased adiposity, and the gut microbiome has recently been shown to be key to the genesis of obesity. These new genomic discoveries complement previous knowledge on the development of early-onset obesity and provide new perspectives for research on the complex molecular and physiological mechanisms involved in this disease. Personalized preventive strategies and genomic medicine may become possible in the near future.
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Affiliation(s)
- Hélène Choquet
- CNRS UMR8199, Institute of Biology, Pasteur Institute, 1 Pr Calmette Street, 59000 Lille, France.
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