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Obesity: HELP
Articles by Albert Hofman
Based on 69 articles published since 2009
(Why 69 articles?)
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Between 2009 and 2019, A. Hofman wrote the following 69 articles about Obesity.
 
+ Citations + Abstracts
Pages: 1 · 2 · 3
1 Clinical Trial Gene × dietary pattern interactions in obesity: analysis of up to 68 317 adults of European ancestry. 2015

Nettleton, Jennifer A / Follis, Jack L / Ngwa, Julius S / Smith, Caren E / Ahmad, Shafqat / Tanaka, Toshiko / Wojczynski, Mary K / Voortman, Trudy / Lemaitre, Rozenn N / Kristiansson, Kati / Nuotio, Marja-Liisa / Houston, Denise K / Perälä, Mia-Maria / Qi, Qibin / Sonestedt, Emily / Manichaikul, Ani / Kanoni, Stavroula / Ganna, Andrea / Mikkilä, Vera / North, Kari E / Siscovick, David S / Harald, Kennet / Mckeown, Nicola M / Johansson, Ingegerd / Rissanen, Harri / Liu, Yongmei / Lahti, Jari / Hu, Frank B / Bandinelli, Stefania / Rukh, Gull / Rich, Stephen / Booij, Lisanne / Dmitriou, Maria / Ax, Erika / Raitakari, Olli / Mukamal, Kenneth / Männistö, Satu / Hallmans, Göran / Jula, Antti / Ericson, Ulrika / Jacobs, David R / Van Rooij, Frank J A / Deloukas, Panos / Sjögren, Per / Kähönen, Mika / Djousse, Luc / Perola, Markus / Barroso, Inês / Hofman, Albert / Stirrups, Kathleen / Viikari, Jorma / Uitterlinden, André G / Kalafati, Ioanna P / Franco, Oscar H / Mozaffarian, Dariush / Salomaa, Veikko / Borecki, Ingrid B / Knekt, Paul / Kritchevsky, Stephen B / Eriksson, Johan G / Dedoussis, George V / Qi, Lu / Ferrucci, Luigi / Orho-Melander, Marju / Zillikens, M Carola / Ingelsson, Erik / Lehtimäki, Terho / Renström, Frida / Cupples, L Adrienne / Loos, Ruth J F / Franks, Paul W. ·Division of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas, Health Science Center, Houston, TX, USA. · Department of Mathematics, University of St. Thomas, Houston, TX, USA. · Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA. · Jean Mayer USDA Human Nutrition Research Center on Aging, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA. · Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit. · Clinical Research Branch, National Institute on Aging, Baltimore, MD, USA. · Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA. · Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands, Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands. · Department of Medicine, University of Washington, Seattle, WA, USA. · Unit of Public Health Genomics. · Unit of Public Health Genomics, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Tukholmankatu 8, Helsinki 00290, Finland. · Department of Internal Medicine. · Department of Chronic Disease Prevention, National Institute for Health and Welfare, Haartmaninkatu 8, Helsinki 00290, Finland. · Department of Nutrition, Harvard Chan School of Public Health, Boston, MA, USA, Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA. · Department of Clinical Sciences-Malmö, Lund University, Malmö, Sweden. · Center for Public Health Genomics, Department of Public Health Sciences, Division of Biostatistics and Epidemiology, University of Virginia, Charlottesville, VA, USA. · William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK. · Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. · Department of Food and Environmental Sciences, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland. · Department of Epidemiology and Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA. · The New York Academy of Medicine, New York, NY, USA. · THL-National Institute for Health and Welfare, Mannerheimintie 166, Helsinki 00300, Finland. · Department of Odontology. · Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston Salem, NC, USA. · Institute of Behavioral Sciences, Folkhälsan Research Centre, Helsinki, Finland. · Department of Nutrition, Harvard Chan School of Public Health, Boston, MA, USA. · Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence, Italy. · Center for Public Health Genomics. · Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands. · Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece. · Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism. · Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland, Department of Clinical Physiology and Nuclear Medicine. · Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA. · Department of Public Health and Clinical Medicine, Nutritional Research. · Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA. · Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK. · Department of Clinical Physiology, University of Tampere and Tampere University Hospital, Tampere, Finland. · Division of Aging, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA, Harvard Medical School and Boston VA Healthcare System, Boston, MA, USA. · Unit of Public Health Genomics, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Tukholmankatu 8, Helsinki 00290, Finland, University of Tartu, Estonian Genome Center, Ülikooli 18, Tartu 50090, Estonia. · Metabolic Disease Group, Wellcome Trust Sanger Institute, Hinxton, UK, University of Cambridge Metabolic Research Labs, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK. · Department of Medicine, University of Turku and Division of Medicine, Turku University Hospital, Turku, Finland. · Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA. · Department of Chronic Disease Prevention, National Institute for Health and Welfare, Haartmaninkatu 8, Helsinki 00290, Finland, Folkhälsan Research Centre, Helsinki, Finland, Department of General Practice and Primary Health Care, Institute of Clinical Medicine, University of Helsinki, Helsinki, Finland, Unit of General Practice, Helsinki University Central Hospital, Helsinki, Finland. · Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden. · Department of Clinical Chemistry, Fimlab Laboratories and School of Medicine, University of Tampere, Tampere, Finland. · Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Department of Biobank Research. · The Genetics of Obesity and Related Metabolic Traits Program, The Charles Bronfman Institute for Personalized Medicine and The Mindich Child Health and Development Institute, The Icahn School of Medicine at Mount Sinai, New York, NY, USA. · Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Department of Nutrition, Harvard Chan School of Public Health, Boston, MA, USA, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden, paul.franks@med.lu.se. ·Hum Mol Genet · Pubmed #25994509.

ABSTRACT: Obesity is highly heritable. Genetic variants showing robust associations with obesity traits have been identified through genome-wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist-hip ratio (WHR)-associated single nucleotide polymorphisms were genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GRS with BMI and BMI-adjusted WHR and (b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P = 0.006-0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567) and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjusted WHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance.

2 Article An Epigenome-Wide Association Study of Obesity-Related Traits. 2018

Dhana, Klodian / Braun, Kim V E / Nano, Jana / Voortman, Trudy / Demerath, Ellen W / Guan, Weihua / Fornage, Myriam / van Meurs, Joyce B J / Uitterlinden, Andre G / Hofman, Albert / Franco, Oscar H / Dehghan, Abbas. ·Department of Epidemiology, Erasmus University Medical Center. · Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts. · Rotterdam Intergenerational Ageing Research Center. · Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota. · Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota. · Human Genetics Center, School of Public Health, University of Texas Health Sciences Center at Houston, Houston, Texas. · Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas. · Department of Internal Medicine, Erasmus University Medical Center. · Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts. · Department of Epidemiology, Imperial College London, London, United Kingdom. ·Am J Epidemiol · Pubmed #29762635.

ABSTRACT: We conducted an epigenome-wide association study on obesity-related traits. We used data from 2 prospective, population-based cohort studies: the Rotterdam Study (RS) (2006-2013) and the Atherosclerosis Risk in Communities (ARIC) Study (1990-1992). We used the RS (n = 1,450) as the discovery panel and the ARIC Study (n = 2,097) as the replication panel. Linear mixed-effect models were used to assess the cross-sectional associations between genome-wide DNA methylation in leukocytes and body mass index (BMI) and waist circumference (WC), adjusting for sex, age, smoking, leukocyte proportions, array number, and position on array. The latter 2 variables were modeled as random effects. Fourteen 5'-C-phosphate-G-3' (CpG) sites were associated with BMI and 26 CpG sites with WC in the RS after Bonferroni correction (P < 1.07 × 10-7), of which 12 and 13 CpGs were replicated in the ARIC Study, respectively. The most significant novel CpGs were located on the Musashi RNA binding protein 2 gene (MSI2; cg21139312) and the leucyl-tRNA synthetase 2, mitochondrial gene (LARS2; cg18030453) and were associated with both BMI and WC. CpGs at BRDT, PSMD1, IFI44L, MAP1A, and MAP3K5 were associated with BMI. CpGs at LGALS3BP, MAP2K3, DHCR24, CPSF4L, and TMEM49 were associated with WC. We report novel associations between methylation at MSI2 and LARS2 and obesity-related traits. These results provide further insight into mechanisms underlying obesity-related traits, which can enable identification of new biomarkers in obesity-related chronic diseases.

3 Article Ethnic and sex-specific cut-off values for adult obesity in the Suriname Health Study. 2018

Krishnadath, Ingrid S K / Toelsie, Jerry R / Nahar-van Venrooij, Lenny / Hofman, Albert / Jaddoe, Vincent W V. ·Department of Public Health, Faculty of Medical Sciences, Anton de Kom University of Suriname, Paramaribo, Suriname. Electronic address: Ingrid.Krishnadath@uvs.edu. · Department of Physiology, Faculty of Medical Sciences, Anton de Kom University of Suriname, Paramaribo, Suriname. Electronic address: j.toelsie@uvs.edu. · Department of Public Health, Faculty of Medical Sciences, Anton de Kom University of Suriname, Paramaribo, Suriname. Electronic address: Lenny.Nahar@uvs.edu. · Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. Electronic address: a.hofman@erasmusmc.nl. · Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands; Department of Pediatrics, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. Electronic address: v.jaddoe@erasmusmc.nl. ·Obes Res Clin Pract · Pubmed #27720693.

ABSTRACT: BACKGROUND: Sex-specific body mass index (BMI) and waist circumference (WC) cut-off values have been validated for a limited number of ethnic groups. We aimed to derive these cut-off values for Amerindians, Creoles, Hindustani, Javanese, Maroons and Mixed living in Suriname. METHODS: Data from individuals aged 20-65, in the Suriname Health Study was used to derive optimal cut-off values for BMI and WC for the prediction of hypertension (n=4910) and cardio-metabolic risk (n=2924). Results from the analysis with Receiver Operating Curves were calculated and compared these with recommended values. RESULTS: The area under the ROC curve was consistently higher for WC compared to BMI among Creoles, Hindustani, Maroons and Mixed. The BMI cut-off values ranged from 24.8kg/m CONCLUSION: In most ethnic groups, we found better discriminatory power for WC compared to BMI in the relation with cardiovascular risk factors. The estimated BMI and WC cut-off values differed between ethnic groups. Further studies are needed to identify cut-off values related to the future risk of cardiovascular disease and mortality.

4 Article Helicobacter pylori colonization and obesity - a Mendelian randomization study. 2017

den Hollander, Wouter J / Broer, Linda / Schurmann, Claudia / Meyre, David / den Hoed, Caroline M / Mayerle, Julia / Hofman, Albert / Homuth, Georg / Uitterlinden, André G / Lerch, Markus M / Kuipers, Ernst J. ·Department of Gastroenterology and Hepatology, Erasmus MC University Medical Centre, Rotterdam, The Netherlands. w.j.denhollander@gmail.com. · Internal Medicine, Erasmus MC University Medical Centre, Rotterdam, The Netherlands. · The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA. · The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA. · Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada. · Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada. · Department of Gastroenterology and Hepatology, Erasmus MC University Medical Centre, Rotterdam, The Netherlands. · Department of Medicine A, University Medicine Greifswald, Greifswald, Germany. · Epidemiology, Erasmus MC University Medical Centre, Rotterdam, The Netherlands. · Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. · Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany. ·Sci Rep · Pubmed #29089580.

ABSTRACT: Obesity is associated with substantial morbidity, costs, and decreased life expectancy, and continues to rise worldwide. While etiological understanding is needed for prevention, epidemiological studies indicated that colonization with Helicobacter pylori (H. pylori) may affect body mass index (BMI), but with inconsistent results. Here, we examine the relationship between H. pylori colonization and BMI/obesity. Cross-sectional analyses were performed in two independent population-based cohorts of elderly from the Netherlands and Germany (n = 13,044). Genetic risk scores were conducted based on genetic loci associated with either H. pylori colonization or BMI/obesity. We performed a bi-directional Mendelian randomization. Meta-analysis of cross-sectional data revealed no association between anti-H. pylori IgG titer and BMI, nor of H. pylori positivity and BMI. Anti-H. pylori IgG titer was negatively associated with obesity (OR 0.99972; 95% CI 0.99946-0.99997, p = 0.03) and with obesity classes (Beta -6.91 •10

5 Article Maternal thyroid function, prepregnancy obesity and gestational weight gain-The Generation R Study: A prospective cohort study. 2017

Collares, Fernanda M / Korevaar, Tim I M / Hofman, Albert / Steegers, Eric A P / Peeters, Robin P / Jaddoe, Vincent W V / Gaillard, Romy. ·The Generation R Study Group, Erasmus University Medical Center, Rotterdam, The Netherlands. · Department of Paediatrics, Erasmus University Medical Center-Sophia Children's Hospital, Rotterdam, The Netherlands. · Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands. · Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands. · Rotterdam Thyroid Center, Erasmus University Medical Center, Rotterdam, The Netherlands. · Department of Obstetrics and Gynaecology, Erasmus University Medical Center, Rotterdam, The Netherlands. ·Clin Endocrinol (Oxf) · Pubmed #28666083.

ABSTRACT: OBJECTIVE: Maternal prepregnancy obesity and excessive gestational weight gain are associated with pregnancy complications. Thyroid function is related to differences in body mass index (BMI) in adult populations. We examined the associations of maternal thyroid function in early pregnancy with maternal BMI and weight gain during pregnancy. DESIGN AND METHODS: In a population-based prospective cohort study among 5726 mothers, we measured maternal TSH and FT4 levels at 13.5 weeks of gestation (95% range: 9.7-17.6 weeks). Maternal weight was assessed before pregnancy and in each trimester. RESULTS: Higher maternal TSH levels were associated with higher prepregnancy BMI (difference: 0.18 kg/m CONCLUSIONS: Higher maternal TSH level and lower FT4 level in early pregnancy are associated with higher prepregnancy BMI and higher gestational weight gain. Further studies are needed to explore maternal and foetal consequences.

6 Article Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits. 2017

Tachmazidou, Ioanna / Süveges, Dániel / Min, Josine L / Ritchie, Graham R S / Steinberg, Julia / Walter, Klaudia / Iotchkova, Valentina / Schwartzentruber, Jeremy / Huang, Jie / Memari, Yasin / McCarthy, Shane / Crawford, Andrew A / Bombieri, Cristina / Cocca, Massimiliano / Farmaki, Aliki-Eleni / Gaunt, Tom R / Jousilahti, Pekka / Kooijman, Marjolein N / Lehne, Benjamin / Malerba, Giovanni / Männistö, Satu / Matchan, Angela / Medina-Gomez, Carolina / Metrustry, Sarah J / Nag, Abhishek / Ntalla, Ioanna / Paternoster, Lavinia / Rayner, Nigel W / Sala, Cinzia / Scott, William R / Shihab, Hashem A / Southam, Lorraine / St Pourcain, Beate / Traglia, Michela / Trajanoska, Katerina / Zaza, Gialuigi / Zhang, Weihua / Artigas, María S / Bansal, Narinder / Benn, Marianne / Chen, Zhongsheng / Danecek, Petr / Lin, Wei-Yu / Locke, Adam / Luan, Jian'an / Manning, Alisa K / Mulas, Antonella / Sidore, Carlo / Tybjaerg-Hansen, Anne / Varbo, Anette / Zoledziewska, Magdalena / Finan, Chris / Hatzikotoulas, Konstantinos / Hendricks, Audrey E / Kemp, John P / Moayyeri, Alireza / Panoutsopoulou, Kalliope / Szpak, Michal / Wilson, Scott G / Boehnke, Michael / Cucca, Francesco / Di Angelantonio, Emanuele / Langenberg, Claudia / Lindgren, Cecilia / McCarthy, Mark I / Morris, Andrew P / Nordestgaard, Børge G / Scott, Robert A / Tobin, Martin D / Wareham, Nicholas J / Anonymous1431035 / Anonymous1441035 / Burton, Paul / Chambers, John C / Smith, George Davey / Dedoussis, George / Felix, Janine F / Franco, Oscar H / Gambaro, Giovanni / Gasparini, Paolo / Hammond, Christopher J / Hofman, Albert / Jaddoe, Vincent W V / Kleber, Marcus / Kooner, Jaspal S / Perola, Markus / Relton, Caroline / Ring, Susan M / Rivadeneira, Fernando / Salomaa, Veikko / Spector, Timothy D / Stegle, Oliver / Toniolo, Daniela / Uitterlinden, André G / Anonymous1451035 / Anonymous1461035 / Anonymous1471035 / Barroso, Inês / Greenwood, Celia M T / Perry, John R B / Walker, Brian R / Butterworth, Adam S / Xue, Yali / Durbin, Richard / Small, Kerrin S / Soranzo, Nicole / Timpson, Nicholas J / Zeggini, Eleftheria. ·The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK. · MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK. · The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK; Usher Institute of Population Health Sciences & Informatics, University of Edinburgh, Edinburgh EH16 4UX, UK; MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH16 4UX, UK. · The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK. · Boston VA Research Institute, Boston, MA 02130, USA. · MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK; BHF Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh EH16 4TJ, UK. · Department of Neurological, Biomedical and Movement Sciences, University of Verona, Verona 37134, Italy. · Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste 34100, Italy. · Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens 17671, Greece. · Department of Health, National Institute for Health and Welfare, Helsinki 00271, Finland. · The Generation R Study Group, Erasmus Medical Center, University Medical Center, Rotterdam 3000 CA, the Netherlands; Department of Epidemiology, Erasmus Medical Center, University Medical Center, Rotterdam 3000 CA, the Netherlands; Department of Pediatrics, Erasmus Medical Center, University Medical Center, Rotterdam 3000 CA, the Netherlands. · Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK. · Department of Epidemiology, Erasmus Medical Center, University Medical Center, Rotterdam 3000 CA, the Netherlands; Department of Internal Medicine, Erasmus Medical Center, University Medical Center, Rotterdam 3000 CA, the Netherlands. · Department of Twin Research and Genetic Epidemiology, King's College London, London SE1 7EH, UK. · William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK. · The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK; Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford OX3 7LJ, UK. · Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan 20132, Italy. · Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK; Department of Cardiology, Ealing Hospital NHS Trust, Middlesex UB1 3EU, UK. · The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK. · MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK; Max Planck Institute for Psycholinguistics, Nijmegen 6500, the Netherlands. · Renal Unit, Department of Medicine, Verona University Hospital, Verona 37126, Italy. · Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester LE1 7RH, UK. · Cardiovascular Epidemiology Unit, Department of Public Health & Primary Care, University of Cambridge, Cambridge CB1 8RN, UK. · Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark; Department of Clinical Biochemistry, Rigshospitalet, Copenhagen University Hospital, Copenhagen 2100, Denmark. · Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA. · Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA; McDonnell Genome Institute, Washington University School of Medicine, Saint Louis, MO 63108, USA. · MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK. · Center for Human Genetics Research, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Department of Medicine, Harvard University Medical School, Boston, MA 02115, USA. · Istituto di Ricerca Genetica e Biomedica (IRGB-CNR), Cagliari 09100, Italy; Università degli Studi di Sassari, Sassari 07100, Italy. · Istituto di Ricerca Genetica e Biomedica (IRGB-CNR), Cagliari 09100, Italy. · Institute of Cardiovascular Science, Faculty of Population Health, University College London, London WC1E 6BT, UK. · The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK; Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA. · MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK; University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, QLD 4072, Australia. · Department of Twin Research and Genetic Epidemiology, King's College London, London SE1 7EH, UK; Institute of Health Informatics, University College London, London NW1 2DA, UK. · Department of Twin Research and Genetic Epidemiology, King's College London, London SE1 7EH, UK; School of Medicine and Pharmacology, The University of Western Australia, Crawley, WA 6009, Australia; Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA 6009, Australia. · Cardiovascular Epidemiology Unit, Department of Public Health & Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; The National Institute for Health Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics at the University of Cambridge, Cambridge CB1 8RN, UK. · Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK; Li Ka Shing Centre for Health Information and Discovery, The Big Data Institute, University of Oxford, Oxford OX3 7BN, UK. · Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK; Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford OX3 7LJ, UK; Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford OX3 7LJ, UK. · Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK; Department of Biostatistics, University of Liverpool, Liverpool L69 3GL, UK; Estonian Genome Center, University of Tartu, Tartu, Tartumaa 51010, Estonia. · Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester LE1 7RH, UK; National Institute for Health Research (NIHR) Leicester Respiratory Biomedical Research Unit, Glenfield Hospital, Leicester LE3 9QP, UK. · D2K Research Group, School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK. · Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK; Department of Cardiology, Ealing Hospital NHS Trust, Middlesex UB1 3EU, UK; Imperial College Healthcare NHS Trust, London W2 1NY, UK. · Department of Epidemiology, Erasmus Medical Center, University Medical Center, Rotterdam 3000 CA, the Netherlands. · Division of Nephrology and Dialysis, Columbus-Gemelli University Hospital, Catholic University, Rome 00168, Italy. · Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste 34100, Italy; Medical Genetics, Institute for Maternal and Child Health IRCCS "Burlo Garofolo", Trieste 34100, Italy. · Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim 68167, Germany. · Department of Cardiology, Ealing Hospital NHS Trust, Middlesex UB1 3EU, UK; Imperial College Healthcare NHS Trust, London W2 1NY, UK; National Heart and Lung Institute, Imperial College London, Hammersmith Hospital Campus, London W12 0NN, UK. · Department of Health, National Institute for Health and Welfare, Helsinki 00271, Finland; Estonian Genome Center, University of Tartu, Tartu, Tartumaa 51010, Estonia; Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki 00290, Finland. · European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK. · The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK; University of Cambridge Metabolic Research Laboratories, and NIHR Cambridge Biomedical Research Centre, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK. · Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, QC H3T 1E2, Canada; Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, QC H3A 1A2, Canada; Department of Oncology, McGill University, Montréal, QC H2W 1S6, Canada. · Department of Twin Research and Genetic Epidemiology, King's College London, London SE1 7EH, UK; MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK. · BHF Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh EH16 4TJ, UK. · The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK; The National Institute for Health Research Blood and Transplant Unit (NIHR BTRU) in Donor Health and Genomics at the University of Cambridge, Cambridge CB1 8RN, UK; Department of Haematology, University of Cambridge, Cambridge CB2 0AH, UK. · The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK. Electronic address: eleftheria@sanger.ac.uk. ·Am J Hum Genet · Pubmed #28552196.

ABSTRACT: Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and polygenic anthropometric traits and find signal enrichment in cis expression QTLs in relevant tissues. Our results highlight the potential of WGS strategies to enhance biologically relevant discoveries across the frequency spectrum.

7 Article Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults. 2017

Graff, Mariaelisa / Scott, Robert A / Justice, Anne E / Young, Kristin L / Feitosa, Mary F / Barata, Llilda / Winkler, Thomas W / Chu, Audrey Y / Mahajan, Anubha / Hadley, David / Xue, Luting / Workalemahu, Tsegaselassie / Heard-Costa, Nancy L / den Hoed, Marcel / Ahluwalia, Tarunveer S / Qi, Qibin / Ngwa, Julius S / Renström, Frida / Quaye, Lydia / Eicher, John D / Hayes, James E / Cornelis, Marilyn / Kutalik, Zoltan / Lim, Elise / Luan, Jian'an / Huffman, Jennifer E / Zhang, Weihua / Zhao, Wei / Griffin, Paula J / Haller, Toomas / Ahmad, Shafqat / Marques-Vidal, Pedro M / Bien, Stephanie / Yengo, Loic / Teumer, Alexander / Smith, Albert Vernon / Kumari, Meena / Harder, Marie Neergaard / Justesen, Johanne Marie / Kleber, Marcus E / Hollensted, Mette / Lohman, Kurt / Rivera, Natalia V / Whitfield, John B / Zhao, Jing Hua / Stringham, Heather M / Lyytikäinen, Leo-Pekka / Huppertz, Charlotte / Willemsen, Gonneke / Peyrot, Wouter J / Wu, Ying / Kristiansson, Kati / Demirkan, Ayse / Fornage, Myriam / Hassinen, Maija / Bielak, Lawrence F / Cadby, Gemma / Tanaka, Toshiko / Mägi, Reedik / van der Most, Peter J / Jackson, Anne U / Bragg-Gresham, Jennifer L / Vitart, Veronique / Marten, Jonathan / Navarro, Pau / Bellis, Claire / Pasko, Dorota / Johansson, Åsa / Snitker, Søren / Cheng, Yu-Ching / Eriksson, Joel / Lim, Unhee / Aadahl, Mette / Adair, Linda S / Amin, Najaf / Balkau, Beverley / Auvinen, Juha / Beilby, John / Bergman, Richard N / Bergmann, Sven / Bertoni, Alain G / Blangero, John / Bonnefond, Amélie / Bonnycastle, Lori L / Borja, Judith B / Brage, Søren / Busonero, Fabio / Buyske, Steve / Campbell, Harry / Chines, Peter S / Collins, Francis S / Corre, Tanguy / Smith, George Davey / Delgado, Graciela E / Dueker, Nicole / Dörr, Marcus / Ebeling, Tapani / Eiriksdottir, Gudny / Esko, Tõnu / Faul, Jessica D / Fu, Mao / Færch, Kristine / Gieger, Christian / Gläser, Sven / Gong, Jian / Gordon-Larsen, Penny / Grallert, Harald / Grammer, Tanja B / Grarup, Niels / van Grootheest, Gerard / Harald, Kennet / Hastie, Nicholas D / Havulinna, Aki S / Hernandez, Dena / Hindorff, Lucia / Hocking, Lynne J / Holmens, Oddgeir L / Holzapfel, Christina / Hottenga, Jouke Jan / Huang, Jie / Huang, Tao / Hui, Jennie / Huth, Cornelia / Hutri-Kähönen, Nina / James, Alan L / Jansson, John-Olov / Jhun, Min A / Juonala, Markus / Kinnunen, Leena / Koistinen, Heikki A / Kolcic, Ivana / Komulainen, Pirjo / Kuusisto, Johanna / Kvaløy, Kirsti / Kähönen, Mika / Lakka, Timo A / Launer, Lenore J / Lehne, Benjamin / Lindgren, Cecilia M / Lorentzon, Mattias / Luben, Robert / Marre, Michel / Milaneschi, Yuri / Monda, Keri L / Montgomery, Grant W / De Moor, Marleen H M / Mulas, Antonella / Müller-Nurasyid, Martina / Musk, A W / Männikkö, Reija / Männistö, Satu / Narisu, Narisu / Nauck, Matthias / Nettleton, Jennifer A / Nolte, Ilja M / Oldehinkel, Albertine J / Olden, Matthias / Ong, Ken K / Padmanabhan, Sandosh / Paternoster, Lavinia / Perez, Jeremiah / Perola, Markus / Peters, Annette / Peters, Ulrike / Peyser, Patricia A / Prokopenko, Inga / Puolijoki, Hannu / Raitakari, Olli T / Rankinen, Tuomo / Rasmussen-Torvik, Laura J / Rawal, Rajesh / Ridker, Paul M / Rose, Lynda M / Rudan, Igor / Sarti, Cinzia / Sarzynski, Mark A / Savonen, Kai / Scott, William R / Sanna, Serena / Shuldiner, Alan R / Sidney, Steve / Silbernagel, Günther / Smith, Blair H / Smith, Jennifer A / Snieder, Harold / Stančáková, Alena / Sternfeld, Barbara / Swift, Amy J / Tammelin, Tuija / Tan, Sian-Tsung / Thorand, Barbara / Thuillier, Dorothée / Vandenput, Liesbeth / Vestergaard, Henrik / van Vliet-Ostaptchouk, Jana V / Vohl, Marie-Claude / Völker, Uwe / Waeber, Gérard / Walker, Mark / Wild, Sarah / Wong, Andrew / Wright, Alan F / Zillikens, M Carola / Zubair, Niha / Haiman, Christopher A / Lemarchand, Loic / Gyllensten, Ulf / Ohlsson, Claes / Hofman, Albert / Rivadeneira, Fernando / Uitterlinden, André G / Pérusse, Louis / Wilson, James F / Hayward, Caroline / Polasek, Ozren / Cucca, Francesco / Hveem, Kristian / Hartman, Catharina A / Tönjes, Anke / Bandinelli, Stefania / Palmer, Lyle J / Kardia, Sharon L R / Rauramaa, Rainer / Sørensen, Thorkild I A / Tuomilehto, Jaakko / Salomaa, Veikko / Penninx, Brenda W J H / de Geus, Eco J C / Boomsma, Dorret I / Lehtimäki, Terho / Mangino, Massimo / Laakso, Markku / Bouchard, Claude / Martin, Nicholas G / Kuh, Diana / Liu, Yongmei / Linneberg, Allan / März, Winfried / Strauch, Konstantin / Kivimäki, Mika / Harris, Tamara B / Gudnason, Vilmundur / Völzke, Henry / Qi, Lu / Järvelin, Marjo-Riitta / Chambers, John C / Kooner, Jaspal S / Froguel, Philippe / Kooperberg, Charles / Vollenweider, Peter / Hallmans, Göran / Hansen, Torben / Pedersen, Oluf / Metspalu, Andres / Wareham, Nicholas J / Langenberg, Claudia / Weir, David R / Porteous, David J / Boerwinkle, Eric / Chasman, Daniel I / Anonymous3281104 / Anonymous3291104 / Anonymous3301104 / Abecasis, Gonçalo R / Barroso, Inês / McCarthy, Mark I / Frayling, Timothy M / O'Connell, Jeffrey R / van Duijn, Cornelia M / Boehnke, Michael / Heid, Iris M / Mohlke, Karen L / Strachan, David P / Fox, Caroline S / Liu, Ching-Ti / Hirschhorn, Joel N / Klein, Robert J / Johnson, Andrew D / Borecki, Ingrid B / Franks, Paul W / North, Kari E / Cupples, L Adrienne / Loos, Ruth J F / Kilpeläinen, Tuomas O. ·Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America. · MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom. · Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America. · Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America. · Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany. · National Heart, Lung, and Blood Institute, Framingham Heart Study, Framingham, Massachusetts, United States of America. · Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America. · Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom. · Division of Population Health Sciences and Education, St. George's, University of London, London, United Kingdom. · Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America. · Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America. · Department of Neurology, Boston University School of Medicine, Boston, Massachusetts, United States of America. · Department of Immunology, Genetics and Pathology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden. · Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. · Steno Diabetes Center, Gentofte, Denmark. · Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, United States of America. · Howard University, Department of Internal Medicine, Washington DC, United States of America. · Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University, Malmö, Sweden. · Department of Biobank Research, Umeå University, Umeå, Sweden. · Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom. · Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, The Framingham Heart Study, Framingham, Massachusetts, United States of America. · Cell and Developmental Biology Graduate Program, Weill Cornell Graduate School of Medical Sciences, Cornell University, New York, New York, United States of America. · Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America. · Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America. · Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States of America. · Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland. · Swiss Institute of Bioinformatics, Lausanne, Switzerland. · MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom. · Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom. · Department of Cardiology, Ealing Hospital HNS Trust, Middlesex, United Kingdom. · Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America. · Estonian Genome Center, University of Tartu, Tartu, Estonia. · Department of Internal Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland. · Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America. · University of Lille, CNRS, Institut Pasteur de Lille, UMR 8199 - EGID, Lille, France. · Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany. · DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany. · Icelandic Heart Association, Kopavogur, Iceland. · Faculty of Medicine, University of Iceland, Reykjavik, Iceland. · ISER, University of Essex, Colchester, Essex, United Kingdom. · Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany. · Institute of Nutrition, Friedrich Schiller University Jena, Jena, Germany. · Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America. · Karolinska Institutet, Respiratory Unit, Department of Medicine Solna, Stockholm, Sweden. · Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia. · Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America. · Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland. · Department of Clinical Chemistry, University of Tampere School of Medicine, Tampere, Finland. · Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands. · EMGO+ Institute, Vrije Universiteit & VU University Medical Center, Amsterdam, The Netherlands. · Department of Public and Occupational Health, VU University Medical Center, Amsterdam, The Netherlands. · Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ InGeest, Amsterdam, The Netherlands. · Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America. · National Institute for Health and Welfare, Department of Health, Helsinki, Finland. · Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland. · Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands. · Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands. · Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, Texas, United States of America. · Division of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, Texas, United States of America. · Kuopio Research Institute of Exercise Medicine, Kuopio, Finland. · Centre for Genetic Origins of Health and Disease, University of Western Australia, Crawley, Western Australia, Australia. · Translational Gerontology Branch, National Institute on Aging, Baltimore, Maryland, United States of America. · Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. · Human Genetics, Genome Institute of Singapore, Agency for Science, Technology and Research of Singapore, Singapore. · Genomics Research Centre, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia. · Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom. · Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden. · Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, United States of America. · Veterans Affairs Maryland Health Care System, University of Maryland, Baltimore, Maryland, United States of America. · Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. · Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, United States of America. · Research Centre for Prevention and Health, Glostrup University Hospital, Glostrup, Denmark. · Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. · Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America. · INSERM U-1018, CESP, Renal and Cardiovascular Epidemiology, UVSQ-UPS, Villejuif, France. · Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland. · Unit of Primary Care, Oulu University Hospital, Oulu, Finland. · Busselton Population Medical Research Institute, Nedlands, Western Australia, Australia. · PathWest Laboratory Medicine of WA, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia. · School of Pathology and Laboratory Medicine, The University of Western Australia, Crawley, Western Australia, Australia. · Diabetes and Obesity Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America. · Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland. · Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America. · Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America. · Texas Biomedical Research Institute, San Antonio, Texas, United States of America. · Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland, United States of America. · USC-Office of Population Studies Foundation, Inc., University of San Carlos, Cebu City, Philippines. · Department of Nutrition and Dietetics, University of San Carlos, Cebu City, Philippines. · Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale Delle Ricerche (CNR), Cittadella Universitaria di Monserrato, Monserrato, Italy. · Department of Genetics, Rutgers University, Piscataway, New Jersey, United States of America. · Department of Statistics and Biostatistics, Rutgers University, Piscataway, New Jersey, United States of America. · Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, Edinburgh, Scotland. · MRC Integrative Epidemiology Unit & School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom. · University of Maryland School of Medicine, Department of Epidemiology & Public Health, Baltimore, Maryland, United States of America. · Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany. · Department of Medicine, Oulu University Hospital, Oulu, Finland. · Institute of Clinical Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland. · Division of Endocrinology, Boston Children's Hospital, Boston, Massachusetts, United States of America. · Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America. · Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, United States of America. · Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, United States of America. · Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany. · Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. · Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany. · German Center for Diabetes Research (DZD), München-Neuherberg, Germany. · Laboratory of Neurogenetics, National Institute on Aging, Bethesda, Maryland, United States of America. · Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America. · Musculoskeletal Research Programme, Division of Applied Medicine, University of Aberdeen, Foresterhill, Aberdeen, United Kingdom. · Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom. · St. Olav Hospital, Trondheim University Hospital, Trondheim, Norway. · Institute for Nutritional Medicine, Klinikum Rechts der Isar, Technische Universität München, Munich, Germany. · NCA Institute, VU University & VU Medical Center, Amsterdam, The Netherlands. · Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom. · School of Population Health, The University of Western Australia, Crawley, Western Australia, Australia. · Department of Pediatrics, Tampere University Hospital, Tampere, Finland. · Department of Pediatrics, University of Tampere School of Medicine, Tampere, Finland. · Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia. · School of Medicine and Pharmacology, The University of Western Australia, Crawley, Western Australia, Australia. · Department of Physiology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. · Department of Medicine, University of Turku, Turku, Finland. · Division of Medicine, Turku University Hospital, Turku, Finland. · Department of Medicine and Abdominal Center: Endocrinology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland. · Minerva Foundation Institute for Medical Research, Helsinki, Finland. · Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia. · Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland. · HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Levanger, Norway. · Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland. · Department of Clinical Physiology, University of Tampere School of Medicine, Tampere, Finland. · Institute of Biomedicine, Physiology, University of Eastern Finland, Kuopio Campus, Finland. · Neuroepidemiology Section, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America. · Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America. · The Big Data Institute, University of Oxford, Oxford, United Kingdom. · Geriatric Medicine, Sahlgrenska University Hospital, Mölndal, Sweden. · Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom. · INSERM U-1138, Équipe 2: Pathophysiology and Therapeutics of Vascular and Renal diseases Related to Diabetes, Centre de Recherche des Cordeliers, Paris, France. · Department of Endocrinology, Diabetology, Nutrition, and Metabolic Diseases, Bichat Claude Bernard Hospital, Paris, France. · Center for Observational Research, Amgen Inc., Thousand Oaks, California, United States of America. · Section of Clinical Child and Family Studies, Department of Educational and Family Studies, Vrije Universiteit, Amsterdam, The Netherlands. · Dipartimento di Scienze Biomediche, Università degli Studi di Sassari, Sassari, Italy. · Department of Medicine I, Ludwig-Maximilians-Universität, Munich, Germany. · DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany. · Department of Respiratory Medicine, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia. · Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany. · Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. · Institute of Cardiovascular and Medical Sciences, BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, United Kingdom. · University of Tartu, Estonian Genome Centre, Tartu, Estonia. · Genomics of Common Disease, Imperial College London, London, United Kingdom. · South Ostrobothnia Central Hospital, Seinäjoki, Finland. · Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland. · Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland. · Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States of America. · Harvard Medical School, Boston, Massachusetts, United States of America. · Social Services and Health Care Department, City of Helsinki, Helsinki, Finland. · Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America. · Division of Angiology, Department of Internal Medicine, Medical University Graz, Austria. · School of Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, Scotland. · LIKES Research Center for Sport and Health Sciences, Jyväskylä, Finland. · National Heart and Lung Institute, Imperial College London, United Kingdom. · Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. · Institute of Nutrition and Functional Foods, Quebec, Canada. · School of Nutrition, Laval University, Quebec, Canada. · Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Germany. · Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom. · Centre for Population Health Sciences, Usher Institute for Population Health Sciences and Informatics, Teviot Place, Edinburgh, Scotland. · MRC Unit for Lifelong Health and Ageing at UCL, London, United Kingdom. · Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands. · Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America. · Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands. · Netherlands Consortium for Healthy Aging, Leiden University Medical Center, Leiden, The Netherlands. · Department of Kinesiology, Laval University, Quebec, Canada. · Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. · University of Leipzig, Medical Department, Leipzig, Germany. · Geriatric Unit, Azienda Sanitaria Firenze, Florence, Italy. · School of Public Health, University of Adelaide, Adelaide, South Australia, Australia. · Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland. · Department of Clinical Epidemiology, Bispebjerg and Frederiksberg Hospitals, The Capital Region, Copenhagen, Denmark. · Centre for Vascular Prevention, Danube-University Krems, Krems, Austria. · Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia. · National Institute for Health Research Biomedical Research Centre at Guy's and St. Thomas' Foundation Trust, London, United Kingdom. · Department of Clinical Experimental Research, Rigshospitalet, Glostrup, Denmark. · Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. · Synlab Academy, Synlab Services LLC, Mannheim, Germany. · Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria. · Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany. · Department of Epidemiology and Public Health, University College London, London, United Kingdom. · Laboratory of Epidemiology and Population Science, National Institute on Aging, Bethesda, Maryland, United States of America. · Biocenter Oulu, University of Oulu, Oulu, Finland. · MRC-PHE Centre for Environment and Health, Imperial College London, London, United Kingdom. · Imperial College Healthcare NHS Trust, London, United Kingdom. · Hammersmith Hospital, London, United Kingdom. · Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom. · Wellcome Trust Sanger Institute, Hinxton, United Kingdom. · NIHR Cambridge Biomedical Research Centre, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom. · The University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Cambridge, United Kingdom. · Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, United Kingdom. · Oxford NIHR Biomedical Research Centre, Oxford, United Kingdom. · Center of Medical Systems Biology, Leiden, The Netherlands. · Population Health Research Institute, St. George's University of London, London, United Kingdom. · Divisions of Endocrinology and Genetics and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, Massachusetts, United States of America. · Department of Public Health & Clinical Medicine, Umeå University, Umeå, Sweden. · Carolina Center for Genome Sciences, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America. · Genetics of Obesity and Related Metabolic Traits Program, Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America. · The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America. · The Department of Preventive Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York, United States of America. ·PLoS Genet · Pubmed #28448500.

ABSTRACT: Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.

8 Article Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity. 2017

Wahl, Simone / Drong, Alexander / Lehne, Benjamin / Loh, Marie / Scott, William R / Kunze, Sonja / Tsai, Pei-Chien / Ried, Janina S / Zhang, Weihua / Yang, Youwen / Tan, Sili / Fiorito, Giovanni / Franke, Lude / Guarrera, Simonetta / Kasela, Silva / Kriebel, Jennifer / Richmond, Rebecca C / Adamo, Marco / Afzal, Uzma / Ala-Korpela, Mika / Albetti, Benedetta / Ammerpohl, Ole / Apperley, Jane F / Beekman, Marian / Bertazzi, Pier Alberto / Black, S Lucas / Blancher, Christine / Bonder, Marc-Jan / Brosch, Mario / Carstensen-Kirberg, Maren / de Craen, Anton J M / de Lusignan, Simon / Dehghan, Abbas / Elkalaawy, Mohamed / Fischer, Krista / Franco, Oscar H / Gaunt, Tom R / Hampe, Jochen / Hashemi, Majid / Isaacs, Aaron / Jenkinson, Andrew / Jha, Sujeet / Kato, Norihiro / Krogh, Vittorio / Laffan, Michael / Meisinger, Christa / Meitinger, Thomas / Mok, Zuan Yu / Motta, Valeria / Ng, Hong Kiat / Nikolakopoulou, Zacharoula / Nteliopoulos, Georgios / Panico, Salvatore / Pervjakova, Natalia / Prokisch, Holger / Rathmann, Wolfgang / Roden, Michael / Rota, Federica / Rozario, Michelle Ann / Sandling, Johanna K / Schafmayer, Clemens / Schramm, Katharina / Siebert, Reiner / Slagboom, P Eline / Soininen, Pasi / Stolk, Lisette / Strauch, Konstantin / Tai, E-Shyong / Tarantini, Letizia / Thorand, Barbara / Tigchelaar, Ettje F / Tumino, Rosario / Uitterlinden, Andre G / van Duijn, Cornelia / van Meurs, Joyce B J / Vineis, Paolo / Wickremasinghe, Ananda Rajitha / Wijmenga, Cisca / Yang, Tsun-Po / Yuan, Wei / Zhernakova, Alexandra / Batterham, Rachel L / Smith, George Davey / Deloukas, Panos / Heijmans, Bastiaan T / Herder, Christian / Hofman, Albert / Lindgren, Cecilia M / Milani, Lili / van der Harst, Pim / Peters, Annette / Illig, Thomas / Relton, Caroline L / Waldenberger, Melanie / Järvelin, Marjo-Riitta / Bollati, Valentina / Soong, Richie / Spector, Tim D / Scott, James / McCarthy, Mark I / Elliott, Paul / Bell, Jordana T / Matullo, Giuseppe / Gieger, Christian / Kooner, Jaspal S / Grallert, Harald / Chambers, John C. ·Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany. · Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. · German Center for Diabetes Research (DZD), München-Neuherberg, Germany. · Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK. · Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, UK. · Institute of Health Sciences, P.O. Box 5000, FI-90014 University of Oulu, Finland. · Translational Laboratory in Genetic Medicine (TLGM), Agency for Science, Technology and Research (A*STAR), 8A Biomedical Grove, Immunos, Level 5, Singapore 138648, Singapore. · National Heart and Lung Institute, Imperial College London, London W12 0NN, UK. · Department of Twin Research and Genetic Epidemiology, King's College London, London SE1 7EH, UK. · Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. · Ealing Hospital NHS Trust, Middlesex UB1 3HW, UK. · Cancer Science Institute of Singapore, National University of Singapore, Singapore. · Human Genetics Foundation-Torino, Torino, Italy. · Medical Sciences Department, University of Torino, Torino, Italy. · University of Groningen, University Medical Center Groningen, Department of Genetics, 9700 RB Groningen, The Netherlands. · Estonian Genome Center, University of Tartu, Riia 23b, 51010 Tartu, Estonia. · Department of Biotechnology, Institute of Molecular and Cell Biology, University of Tartu, Riia 23, 51010 Tartu, Estonia. · MRC Integrative Epidemiology Unit (IEU), School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK. · UCLH Bariatric Centre for Weight Loss, Weight Management and Metabolic and Endocrine Surgery, University College London Hospitals, Ground Floor West Wing, 250 Euston Road, London NW1 2PG, UK. · Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland. · NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland. · Computational Medicine, School of Social and Community Medicine, University of Bristol and Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK. · EPIGET Lab, Department of Clinical Sciences and Community Health, Università degli Studi di Milano and Fondazione IRCCS Ca'Granda Ospedale Maggiore Policlinico, Milan, Italy. · Institute of Human Genetics, University Hospital Schleswig-Holstein, Kiel Campus, Kiel, Germany. · Centre for Haematology, Department of Medicine, Faculty of Medicine, Imperial College London, Hammersmith Campus, London W12 0NN, UK. · Molecular Epidemiology, Leiden University Medical Center, Leiden, 2333 ZC, The Netherlands. · Section of Infectious Diseases and Immunity, Department of Medicine, Imperial College London, London W12 0NN, UK. · High Throughput Genomics-Oxford Genomic Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK. · Medical Department 1, University Hospital of the Technical University Dresden, Dresden, Germany. · Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany. · Gerontology and Geriatrics, Leiden University Medical Center, Leiden 2300 RC, The Netherlands. · Department of Clinical and Experimental Medicine, University of Surrey, Guildford GU2 7PX, UK. · Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands. · Clinical and Experimental Surgery Department, Medical Research Institute, University of Alexandria, Hadara, Alexandria 21561, Egypt. · Department of Endocrinology, Diabetes and Obesity, Max Healthcare, New Delhi 110 017, India. · Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo 1628655, Japan. · Epidemiology and Prevention Unit, Fondazione IRCSS Istituto Nazionale Tumori, Milano, Italy. · Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. · Institute of Human Genetics, Technical University Munich, München, Germany. · DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany. · Vascular Biology Section, National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London SW3 6LY, UK. · Dipartmento Di Medicina Clinica E Chirurgia Federio II University, Naples, Italy. · Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany. · Department of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Hospital Düsseldorf, Düsseldorf, Germany. · Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK. · Department of Medical Sciences, Molecular Medicine and Science for Life Laboratory, Uppsala University, 751 44 Uppsala, Sweden. · Department of Visceral and Thoracic Surgery, University Hospital Schleswig-Holstein, Kiel Campus, Kiel, Germany. · Institute of Human Genetics, University Hospital of Ulm, Albert-Einstein-Allee 11, D-89081 Ulm, Germany. · Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands. · Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany. · Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore. · Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117597, Singapore. · Duke-National University of Singapore Graduate Medical School, Singapore 169857, Singapore. · Cancer Registry and Histopathology Unit, 'Civile-M.P. Arezzo' Hospital, ASP 7, Ragusa, Italy. · Departments of Internal Medicine and Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands. · Epidemiology and Public Health, Imperial College London, London, UK. · Department of Public Health, Faculty of Medicine, University of Kelaniya, PO Box 6, Thalagolla Road, Ragama 11010, Sri Lanka. · The Institute of Cancer Research, Surrey SM2 5NG, UK. · Centre for Obesity Research, Rayne Institute, Department of Medicine, University College London, London WC1E 6JJ, UK. · William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK. · Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah 21589, Saudi Arabia. · Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts 02142, USA. · University of Groningen, University Medical Center Groningen, Department of Cardiology, 9700 RB Groningen, The Netherlands. · Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, 3511 GC Utrecht, The Netherlands. · Hannover Unified Biobank, Hannover Medical School, Feodor-Lynen-Strasse 15, D-30625 Hanover, Germany. · Institute of Human Genetics, Hannover Medical School, Carl-Neuberg-Strasse 1, D-30625 Hanover, Germany. · Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPE) Centre for Environment and Health, School of Public Health, Imperial College London, London, UK. · Biocenter Oulu, P.O. Box 5000, Aapistie 5A, FI-90014 University of Oulu, Finland. · Center for Life Course Epidemiology, Faculty of Medicine, P.O. Box 5000, FI-90014 University of Oulu, Finland. · Unit of Primary Care, Oulu University Hospital, Kajaanintie 50, PO Box 20, FI-90220 Oulu, 90029 OYS, Finland. · Department of Pathology, National University Hospital, Singapore. · Oxford Centre for Diabetes Endocrinology and Metabolism, University of Oxford, Oxford, UK. · Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford OX3 7LJ, UK. · Imperial College Healthcare NHS Trust, London W12 0HS, UK. · Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore. ·Nature · Pubmed #28002404.

ABSTRACT: Approximately 1.5 billion people worldwide are overweight or affected by obesity, and are at risk of developing type 2 diabetes, cardiovascular disease and related metabolic and inflammatory disturbances. Although the mechanisms linking adiposity to associated clinical conditions are poorly understood, recent studies suggest that adiposity may influence DNA methylation, a key regulator of gene expression and molecular phenotype. Here we use epigenome-wide association to show that body mass index (BMI; a key measure of adiposity) is associated with widespread changes in DNA methylation (187 genetic loci with P < 1 × 10

9 Article Ethnic disparities in the prevalence of metabolic syndrome and its risk factors in the Suriname Health Study: a cross-sectional population study. 2016

Krishnadath, Ingrid S K / Toelsie, Jerry R / Hofman, Albert / Jaddoe, Vincent W V. ·Department of Public Health, Faculty of Medical Sciences, Anton de Kom University of Suriname, Paramaribo, Suriname. · Department of Physiology, Faculty of Medical Sciences, Anton de Kom University of Suriname, Paramaribo, Suriname. · Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands. · Department of Pediatrics, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. ·BMJ Open · Pubmed #27927663.

ABSTRACT: BACKGROUND: The metabolic syndrome (MetS) indicates increased risk for cardiovascular disease and type 2 diabetes. We estimated the overall and ethnic-specific prevalence of MetS and explored the associations of risk factors with MetS among Amerindian, Creole, Hindustani, Javanese, Maroon and Mixed ethnic groups. METHOD: We used the 2009 Joint Interim Statement (JIS) to define MetS in a subgroup of 2946 participants of the Suriname Health Study, a national survey designed according to the WHO Steps guidelines. The prevalences of MetS and its components were determined for all ethnicities. Hierarchical logistic regressions were used to determine the associations of ethnicity, sex, age, marital status, educational level, income status, employment, smoking status, residence, physical activity, fruit and vegetable intake with MetS. RESULTS: The overall estimated prevalence of MetS was 39.2%. From MetS components, central obesity and low high-density lipoprotein cholesterol (HDL-C) had the highest prevalences. The prevalence of MetS was highest for the Hindustanis (52.7%) and lowest for Maroons (24.2%). The analyses showed that in the overall population sex (women: OR 1.4; 95% CI 1.2 to 1.6), age (OR 5.5 CI 4.3 to 7.2), education (OR 0.7 CI 0.6 to 0.9), living area (OR 0.6 CI 0.5 to 0.8), income (OR 0.7 CI 0.5 to 0.9) and marital status (OR 1.3 CI 1.1 to 1.6) were associated with MetS. Variations observed in the associations of the risk factors with MetS in the ethnic groups did not materially influence the associations of ethnicities with MetS. CONCLUSIONS: The prevalence of MetS was high and varied widely among ethnicities. Overall, central obesity and low HDL-C contributed most to MetS. Further studies are needed to assess the prospective associations of risk factors with MetS in different ethnic groups.

10 Article Obesity and Life Expectancy with and without Diabetes in Adults Aged 55 Years and Older in the Netherlands: A Prospective Cohort Study. 2016

Dhana, Klodian / Nano, Jana / Ligthart, Symen / Peeters, Anna / Hofman, Albert / Nusselder, Wilma / Dehghan, Abbas / Franco, Oscar H. ·Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands. · Deakin University, Geelong, Victoria, Australia. · Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America. · Public Health Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands. ·PLoS Med · Pubmed #27433939.

ABSTRACT: BACKGROUND: Overweight and obesity are associated with increased risk of type 2 diabetes. Limited evidence exists regarding the effect of excess weight on years lived with and without diabetes. We aimed to determine the association of overweight and obesity with the number of years lived with and without diabetes in a middle-aged and elderly population. METHODS AND FINDINGS: The study included 6,499 individuals (3,656 women) aged 55 y and older from the population-based Rotterdam Study. We developed a multistate life table to calculate life expectancy for individuals who were normal weight, overweight, and obese and the difference in years lived with and without diabetes. For life table calculations, we used prevalence, incidence rate, and hazard ratios (HRs) for three transitions (healthy to diabetes, healthy to death, and diabetes to death), stratifying by body mass index (BMI) at baseline and adjusting for confounders. During a median follow-up of 11.1 y, we observed 697 incident diabetes events and 2,192 overall deaths. Obesity was associated with an increased risk of developing diabetes (HR: 2.13 [p < 0.001] for men and 3.54 [p < 0.001] for women). Overweight and obesity were not associated with mortality in men and women with or without diabetes. Total life expectancy remained unaffected by overweight and obesity. Nevertheless, men with obesity aged 55 y and older lived 2.8 (95% CI -6.1 to -0.1) fewer y without diabetes than normal weight individuals, whereas, for women, the difference between obese and normal weight counterparts was 4.7 (95% CI -9.0 to -0.6) y. Men and women with obesity lived 2.8 (95% CI 0.6 to 6.2) and 5.3 (95% CI 1.6 to 9.3) y longer with diabetes, respectively, compared to their normal weight counterparts. Since the implications of these findings could be limited to middle-aged and older white European populations, our results need confirmation in other populations. CONCLUSIONS: Obesity in the middle aged and elderly is associated with a reduction in the number of years lived free of diabetes and an increase in the number of years lived with diabetes. Those extra years lived with morbidity might place a high toll on individuals and health care systems.

11 Article Association of Serum Thyrotropin with Anthropometric Markers of Obesity in the General Population. 2016

Tiller, Daniel / Ittermann, Till / Greiser, Karin H / Meisinger, Christa / Agger, Carsten / Hofman, Albert / Thuesen, Betina / Linneberg, Allan / Peeters, Robin / Franco, Oscar / Heier, Margit / Kluttig, Alexander / Werdan, Karl / Stricker, Bruno / Schipf, Sabine / Markus, Marcello / Dörr, Marcus / Völzke, Henry / Haerting, Johannes. ·1 Institute of Medical Epidemiology, Biostatistics and Informatics, Martin-Luther-University Halle-Wittenberg , Halle (Saale), Germany . · 2 Department of Study of Health in Pomerania/Clinical-Epidemiological Research, Institute for Community Medicine, University Medicine Greifswald , Greifswald, Germany . · 3 German Cancer Research Centre , Division of Cancer Epidemiology, Heidelberg, Germany . · 4 Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health , München, Germany . · 5 Research Centre for Prevention and Health , the Capital Region, Denmark . · 6 Department of Epidemiology, Department of Internal Medicine; Erasmus Medical Center , Rotterdam, The Netherlands . · 7 Department of Clinical Experimental Research, Rigshospitalet , Glostrup, Denmark . · 8 Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen , Copenhagen, Denmark . · 9 Rotterdam Thyroid Center, Department of Internal Medicine; Erasmus Medical Center , Rotterdam, The Netherlands . · 10 Department of Medicine III, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany . · 11 Department of Internal Medicine B, University Medicine Greifswald , Greifswald, Germany . · 12 DZHK (German Centre for Cardiovascular Research) , partner site Greifswald, Greifswald, Germany . ·Thyroid · Pubmed #27393002.

ABSTRACT: BACKGROUND: Except from associations study with body weight, there are few longitudinal data regarding the association between thyroid function and anthropometric measurements such as waist circumference, waist-to-hip ratio, or waist-to height ratio. OBJECTIVE: This study aimed to investigate the association of thyrotropin (TSH) at baseline with changes in different anthropometric markers between baseline and follow-up in the general population. METHOD: Data were used from four population-based longitudinal cohort studies and one population-based cross-sectional study. A total of 16,902 (8204 males) subjects aged 20-95 years from the general population were studied. Body mass index, waist circumference, waist-to-hip ratio, and waist-to-height ratio were measured. Multivariable median regression models were calculated adjusting for the following covariates: age, sex, baseline value of the respective anthropometric marker, smoking status, follow-up-time period, and study site. RESULTS: In cross-sectional analyses, serum TSH within the reference range was positively associated with waist circumference (β = 0.94 cm [confidence interval (CI) 0.56-1.32]) and waist-to-height-ratio (β = 0.029 [CI 0.017-0.042]). These associations were also present for the full range of TSH. In the longitudinal analyses, serum TSH at baseline was inversely associated with a five-year change of all considered anthropometric measures within the prior defined study-specific reference range, as well as in the full range of serum TSH. CONCLUSION: High TSH serum levels were positively associated with current anthropometric markers, even in the study-specific reference ranges. In contrast, high TSH serum levels were associated with decreased anthropometric markers over a time span of approximately five years. Further research is needed to determine possible clinical implications as well as public health consequences of these findings.

12 Article Maternal plasma n-3 and n-6 polyunsaturated fatty acid concentrations during pregnancy and subcutaneous fat mass in infancy. 2016

Jelena Vidakovic, Aleksandra / Santos, Susana / Williams, Michelle A / Duijts, Liesbeth / Hofman, Albert / Demmelmair, Hans / Koletzko, Berthold / Jaddoe, Vincent W V / Gaillard, Romy. ·The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. · Department of Pediatrics, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. · Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. · EPI-Unit, Institute of Public Health, University of Porto, Porto, Portugal. · Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA. · Department of Pediatrics, Divisions of Respiratory Medicine and Neonatology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. · Department of Pediatrics, Division of Metabolic Medicine, Dr. Von Hauner Children's Hospital, Ludwig-Maximilians-University of Munich Medical Center, München, Germany. ·Obesity (Silver Spring) · Pubmed #27356181.

ABSTRACT: OBJECTIVE: The associations of maternal plasma n-3 and n-6 polyunsaturated fatty acid (PUFA) concentrations during pregnancy with infant subcutaneous fat were examined. METHODS: In a population-based prospective cohort study among 904 mothers and their infants, maternal plasma n-3 and n-6 PUFA concentrations were measured at midpregnancy. Body mass index, total subcutaneous fat, and central-to-total subcutaneous fat ratio were calculated at 1.5, 6, and 24 months. RESULTS: Maternal n-3 PUFA levels were not consistently associated with infant body mass index or total subcutaneous fat. Higher maternal total n-3 PUFA levels, and specifically eicosapentaenoic acid, docosapentaenoic acid, and docosahexaenoic acid, were associated with higher central-to-total subcutaneous fat ratio at 1.5 months, whereas higher maternal total n-3 PUFA levels were associated with lower central-to-total subcutaneous fat ratio at 6 months (all P values < 0.05). These associations were not present at 24 months. Maternal n-6 PUFA levels were not consistently associated with infant subcutaneous fat. A higher n-6/n-3 ratio was associated with lower central-to-total subcutaneous fat ratio at 1.5 months only (P value < 0.05). CONCLUSIONS: Maternal n-3 PUFA levels during pregnancy may have transient effects on infant subcutaneous fat. Further studies are needed to assess the effects of maternal PUFA concentrations on fat mass development during early infancy.

13 Article Associations of Infant Subcutaneous Fat Mass with Total and Abdominal Fat Mass at School-Age: The Generation R Study. 2016

Santos, Susana / Gaillard, Romy / Oliveira, Andreia / Barros, Henrique / Abrahamse-Berkeveld, Marieke / van der Beek, Eline M / Hofman, Albert / Jaddoe, Vincent W V. ·EPI-Unit, Institute of Public Health, University of Porto, Porto, Portugal. · The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. · Department of Pediatrics, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. · Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. · Department of Clinical Epidemiology, Predictive Medicine and Public Health, University of Porto Medical School, Porto, Portugal. · Nutricia Research, Danone Nutricia Early Life Nutrition, Utrecht, The Netherlands. ·Paediatr Perinat Epidemiol · Pubmed #27225335.

ABSTRACT: BACKGROUND: Skinfold thickness enables the measurement of overall and regional subcutaneous fatness in infancy and may be associated with total and abdominal body fat in later childhood. We examined the associations of subcutaneous fat in infancy with total and abdominal fat at school-age. METHODS: In a population-based prospective cohort study among 821 children, we calculated total subcutaneous fat (sum of biceps, triceps, suprailiacal, and subscapular skinfold thicknesses) and central-to-total subcutaneous fat ratio (sum of suprailiacal and subscapular skinfold thicknesses/total subcutaneous fat) at 1.5 and 24 months. At 6 years, we measured fat mass index (total fat/height(3) ), central-to-total fat ratio (trunk fat/total fat), and android-to-gynoid fat ratio (android fat/gynoid fat) by dual-energy X-ray absorptiometry and preperitoneal fat mass area by abdominal ultrasound. RESULTS: Central-to-total subcutaneous fat ratio at 1.5 months was positively associated with fat mass index and central-to-total fat ratio at 6 years, whereas both total and central-to-total subcutaneous fat ratio at 24 months were positively associated with all childhood adiposity measures. A 1-standard-deviation scores higher total subcutaneous fat at 24 months was associated with an increased risk of childhood overweight (odds ratio 1.70, 95% confidence interval 1.36, 2.12). These associations were weaker than those for body mass index and stronger among girls than boys. CONCLUSIONS: Subcutaneous fat in infancy is positively associated with total and abdominal fat at school-age. Our results also suggest that skinfold thicknesses add little value to estimate later body fat, as compared with body mass index.

14 Article Obesity in older adults and life expectancy with and without cardiovascular disease. 2016

Dhana, K / Berghout, M A / Peeters, A / Ikram, M A / Tiemeier, H / Hofman, A / Nusselder, W / Kavousi, M / Franco, O H. ·Department of Epidemiology, Erasmus Medical Center, University Medical Center, Rotterdam, the Netherlands. · Department of Obesity and Population Health, Baker IDI Heart and Diabetes Institute, Melbourne, Australia. · Department of Neurology, Erasmus Medical Center, Rotterdam, the Netherlands. · Department of Radiology, Erasmus Medical Center, Rotterdam, the Netherlands. · Department of Child and Adolescent Psychiatry, Erasmus Medical Center, Rotterdam, the Netherlands. · Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA. · Department of Public Health, Erasmus Medical Center, Rotterdam, the Netherlands. ·Int J Obes (Lond) · Pubmed #27163746.

ABSTRACT: BACKGROUND: The prevalence of overweight and obesity is increasing globally and is an established risk factor for cardiovascular disease (CVD). Our objective was to evaluate the impact of overweight and obesity on life expectancy and years lived with and without CVD in older adults. METHODS: The study included 6636 individuals (3750 women) aged 55 years and older from the population-based Rotterdam Study. We developed multistate life tables by using prevalence, incidence rate and hazard ratios (HR) for three transitions (free-of-CVD-to-CVD, free-of-CVD-to-death and CVD-to-death), stratifying by the categories of body mass index (BMI) at baseline and adjusting for confounders. RESULTS: During 12 years of follow-up, we observed 1035 incident CVD events and 1902 overall deaths. Obesity was associated with an increased risk of CVD among men (HR 1.57 (95% confidence interval (CI) 1.17, 2.11)) and women (HR 1.49 (95% CI 1.19, 1.86)), compared with normal weight individuals. Overweight and obesity were not associated with mortality in men and women without CVD. Among men with CVD, obesity compared with normal weight, was associated with a lower risk of mortality (HR 0.67 (95% CI 0.49, 0.90)). Overweight and obesity did not influence total life expectancy. However, obesity was associated with 2.6 fewer years (95% CI -4.8, -0.4) lived free from CVD in men and 1.9 (95% CI -3.3, -0.9) in women. Moreover, men and women with obesity lived 2.9 (95% CI 1.1, 4.8) and 1.7 (95% CI 0.6, 2.8) more years suffering from CVD compared with normal weight counterparts. CONCLUSIONS: Obesity had no effect on total life expectancy in older individuals, but increased the risk of having CVD earlier in life and consequently extended the number of years lived with CVD. Owing to increasing prevalence of obesity and improved treatment of CVD, we might expect more individuals living with CVD and for a longer period of time.

15 Article Metabolically Healthy Obesity and the Risk of Cardiovascular Disease in the Elderly Population. 2016

Dhana, Klodian / Koolhaas, Chantal M / van Rossum, Elisabeth F C / Ikram, M Arfan / Hofman, Albert / Kavousi, Maryam / Franco, Oscar H. ·Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands. · Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands. · Department of Neurology Erasmus Medical Center, Rotterdam, The Netherlands. · Department of Radiology Erasmus Medical Center, Rotterdam, The Netherlands. · Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America. ·PLoS One · Pubmed #27100779.

ABSTRACT: BACKGROUND: Whether being metabolically healthy obese (MHO)-defined by the presence of obesity in the absence of metabolic syndrome-is associated with subsequent cardiovascular disease (CVD) remains unclear and may depend on the participants' age. We examined the association of being MHO with CVD risk in the elderly. METHODS AND FINDINGS: This study included 5,314 individuals (mean age 68 years) from the prospective population-based Rotterdam Study. We categorized our population in groups according to body mass index (BMI) and presence and absence of metabolic syndrome, and estimated the hazard ratio (HR) and 95% confidence interval (95%CI) for every group by using Cox proportional hazard models. Among 1048 (19.7%) obese individuals we identified 260 (24.8%) MHO subjects. Over 14 years of follow-up there were 861 incident CVD cases. In the multivariable adjusted analysis, we did not observe an increased CVD risk in MHO individuals (HR 1.07, 95%CI 0.75-1.53), compared to normal weight individuals without metabolic syndrome. CVD risk was increased by the presence of metabolic syndrome in normal weight (HR 1.35, 95%CI 1.02-1.80), overweight (HR 1.32, 95%CI 1.09-1.60) and obese (HR 1.33, 95%CI 1.07-1.66) individuals, compared to those with normal weight without metabolic syndrome. In a mediation analysis, 71.3% of the association between BMI and CVD was explained by the presence of metabolic syndrome. CONCLUSIONS: In our elderly population, we found that the presence of obesity without metabolic syndrome did not confer a higher CVD risk. However, metabolic syndrome was strongly associated with CVD risk, and was associated with an increased risk in all BMI categories. Therefore, preventive interventions targeting cardiometabolic risk factors could be considered in elderly, regardless of weight status.

16 Article Genetic Evidence for Causal Relationships Between Maternal Obesity-Related Traits and Birth Weight. 2016

Tyrrell, Jessica / Richmond, Rebecca C / Palmer, Tom M / Feenstra, Bjarke / Rangarajan, Janani / Metrustry, Sarah / Cavadino, Alana / Paternoster, Lavinia / Armstrong, Loren L / De Silva, N Maneka G / Wood, Andrew R / Horikoshi, Momoko / Geller, Frank / Myhre, Ronny / Bradfield, Jonathan P / Kreiner-Møller, Eskil / Huikari, Ville / Painter, Jodie N / Hottenga, Jouke-Jan / Allard, Catherine / Berry, Diane J / Bouchard, Luigi / Das, Shikta / Evans, David M / Hakonarson, Hakon / Hayes, M Geoffrey / Heikkinen, Jani / Hofman, Albert / Knight, Bridget / Lind, Penelope A / McCarthy, Mark I / McMahon, George / Medland, Sarah E / Melbye, Mads / Morris, Andrew P / Nodzenski, Michael / Reichetzeder, Christoph / Ring, Susan M / Sebert, Sylvain / Sengpiel, Verena / Sørensen, Thorkild I A / Willemsen, Gonneke / de Geus, Eco J C / Martin, Nicholas G / Spector, Tim D / Power, Christine / Järvelin, Marjo-Riitta / Bisgaard, Hans / Grant, Struan F A / Nohr, Ellen A / Jaddoe, Vincent W / Jacobsson, Bo / Murray, Jeffrey C / Hocher, Berthold / Hattersley, Andrew T / Scholtens, Denise M / Davey Smith, George / Hivert, Marie-France / Felix, Janine F / Hyppönen, Elina / Lowe, William L / Frayling, Timothy M / Lawlor, Debbie A / Freathy, Rachel M / Anonymous4990861. ·Institute of Biomedical and Clinical Science, University of Exeter Medical School, Royal Devon and Exeter Hospital, Exeter, United Kingdom2European Centre for Environment and Human Health, University of Exeter, the Knowledge Spa, Truro, United Kingdom. · School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol, United Kingdom4The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands5Medical Research Council Inte. · Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, United Kingdom7Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom. · Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark. · Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois. · Department of Twin Research, King's College London, St Thomas' Hospital, London, United Kingdom. · Centre for Environmental and Preventive Medicine, Wolfson Institute of Preventive Medicine, Barts, and the London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom12Population, Policy and Practice, UCL Institute of Child He. · Medical Research Council Integrative Epidemiology Unit at the University of Bristol, United Kingdom. · Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois. · Institute of Biomedical and Clinical Science, University of Exeter Medical School, Royal Devon and Exeter Hospital, Exeter, United Kingdom. · Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, United Kingdom15Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom. · Division of Epidemiology, Department of Genes and Environment, Norwegian Institute of Public Health, Oslo, Norway. · Center for Applied Genomics, the Children's Hospital of Philadelphia, Philadelphia, Pennsylvania. · Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark, and Danish Pediatric Asthma Center, Copenhagen University Hospital, Gentofte, Denmark. · Institute of Health Sciences, University of Oulu, Oulu, Finland. · QIMR Berghofer Medical Research Institute, Royal Brisbane Hospital, Herston, Australia. · EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands22Department of Biological Psychology, VU University Amsterdam, Amsterdam, the Netherlands. · Department of Mathematics, Universite de Sherbrooke, Quebec City, Quebec, Canada24Centre de recherché du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Quebec City, Quebec, Canada. · Population, Policy and Practice, UCL Institute of Child Health, University College London, United Kingdom. · Centre de recherché du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Quebec City, Quebec, Canada25ECOGENE-21 and Lipid Clinic, Chicoutimi Hospital, Saguenay, Quebec City, Quebec, Canada26Department of Biochemistry, Université de Sherbrooke. · Department of Primary Care and Public Health, Imperial College London, United Kingdom. · School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol, United Kingdom5Medical Research Council Integrative Epidemiology Unit at the University of Bristol, United Kingdom28University of Queensland Diamantin. · Center for Applied Genomics, the Children's Hospital of Philadelphia, Philadelphia, Pennsylvania29Division of Human Genetics, the Children's Hospital of Philadelphia, Philadelphia, Pennsylvania30Department of Pediatrics, Perelman School of Medicine, Unive. · FIMM Institute for Molecular Medicine Finland, Helsinki University, Helsinki, Finland. · Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, the Netherlands54Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts. · Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, United Kingdom15Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom33Oxford National Institute for Health Research (NIHR) Biomedical Researc. · School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol, United Kingdom. · Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark34Department of Medicine, Stanford University School of Medicine, Stanford, California. · Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom35Department of Biostatistics, University of Liverpool, Liverpool, United Kingdom. · Institute of Nutritional Science, University of Potsdam, Germany37Center for Cardiovascular Research/Charité, Berlin, Germany. · School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol, United Kingdom5Medical Research Council Integrative Epidemiology Unit at the University of Bristol, United Kingdom. · Institute of Health Sciences, University of Oulu, Oulu, Finland38Department of Epidemiology and Biostatistics, School of Public Health, Medical Research Council-Health Protection Agency Centre for Environment and Health, Faculty of Medicine, Imperial Coll. · Department of Obstetrics and Gynecology, Sahlgrenska Academy, Sahgrenska University Hospital, Gothenburg, Sweden. · Medical Research Council Integrative Epidemiology Unit at the University of Bristol, United Kingdom40Institute of Preventive Medicine, Bispebjerg and Frederiksberg University Hospital, Capital Region, Copenhagen, Denmark41Novo Nordisk Foundation Center fo. · Research Unit of Obstetrics & Gynecology, Institute of Clinical Research, University of Southern Denmark, Odense. · The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands32Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, the Netherlands46Department of Pediatrics, Erasmus MC, University Medic. · Division of Epidemiology, Department of Genes and Environment, Norwegian Institute of Public Health, Oslo, Norway39Department of Obstetrics and Gynecology, Sahlgrenska Academy, Sahgrenska University Hospital, Gothenburg, Sweden. · Department of Pediatrics, University of Iowa, Iowa City. · Institute of Nutritional Science, University of Potsdam, Germany48The First Affiliated Hospital of Jinan University, Guangzhou, China. · Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, Massachusetts50Diabetes Center, Massachusetts General Hospital, Boston51Department of Medicine, Universite de Sherbrooke, Quebec City, Quebec, Canada. · Population, Policy and Practice, UCL Institute of Child Health, University College London, United Kingdom52Centre for Population Health Research, School of Health Sciences, and Sansom Institute, University of South Australia, Adelaide53South Australian He. · Institute of Biomedical and Clinical Science, University of Exeter Medical School, Royal Devon and Exeter Hospital, Exeter, United Kingdom5Medical Research Council Integrative Epidemiology Unit at the University of Bristol, United Kingdom. ·JAMA · Pubmed #26978208.

ABSTRACT: IMPORTANCE: Neonates born to overweight or obese women are larger and at higher risk of birth complications. Many maternal obesity-related traits are observationally associated with birth weight, but the causal nature of these associations is uncertain. OBJECTIVE: To test for genetic evidence of causal associations of maternal body mass index (BMI) and related traits with birth weight. DESIGN, SETTING, AND PARTICIPANTS: Mendelian randomization to test whether maternal BMI and obesity-related traits are potentially causally related to offspring birth weight. Data from 30,487 women in 18 studies were analyzed. Participants were of European ancestry from population- or community-based studies in Europe, North America, or Australia and were part of the Early Growth Genetics Consortium. Live, term, singleton offspring born between 1929 and 2013 were included. EXPOSURES: Genetic scores for BMI, fasting glucose level, type 2 diabetes, systolic blood pressure (SBP), triglyceride level, high-density lipoprotein cholesterol (HDL-C) level, vitamin D status, and adiponectin level. MAIN OUTCOME AND MEASURE: Offspring birth weight from 18 studies. RESULTS: Among the 30,487 newborns the mean birth weight in the various cohorts ranged from 3325 g to 3679 g. The maternal genetic score for BMI was associated with a 2-g (95% CI, 0 to 3 g) higher offspring birth weight per maternal BMI-raising allele (P = .008). The maternal genetic scores for fasting glucose and SBP were also associated with birth weight with effect sizes of 8 g (95% CI, 6 to 10 g) per glucose-raising allele (P = 7 × 10(-14)) and -4 g (95% CI, -6 to -2 g) per SBP-raising allele (P = 1×10(-5)), respectively. A 1-SD ( ≈ 4 points) genetically higher maternal BMI was associated with a 55-g higher offspring birth weight (95% CI, 17 to 93 g). A 1-SD ( ≈ 7.2 mg/dL) genetically higher maternal fasting glucose concentration was associated with 114-g higher offspring birth weight (95% CI, 80 to 147 g). However, a 1-SD ( ≈ 10 mm Hg) genetically higher maternal SBP was associated with a 208-g lower offspring birth weight (95% CI, -394 to -21 g). For BMI and fasting glucose, genetic associations were consistent with the observational associations, but for systolic blood pressure, the genetic and observational associations were in opposite directions. CONCLUSIONS AND RELEVANCE: In this mendelian randomization study, genetically elevated maternal BMI and blood glucose levels were potentially causally associated with higher offspring birth weight, whereas genetically elevated maternal SBP was potentially causally related to lower birth weight. If replicated, these findings may have implications for counseling and managing pregnancies to avoid adverse weight-related birth outcomes.

17 Article Trajectories of body mass index before the diagnosis of cardiovascular disease: a latent class trajectory analysis. 2016

Dhana, Klodian / van Rosmalen, Joost / Vistisen, Dorte / Ikram, M Arfan / Hofman, Albert / Franco, Oscar H / Kavousi, Maryam. ·Department of Epidemiology, Erasmus Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands. · Department of Biostatistics, Erasmus Medical Center, Rotterdam, The Netherlands. · Steno Diabetes Center, Gentofte, Denmark. · Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands. · Department of Radiology, Erasmus Medical Center, Rotterdam, The Netherlands. · Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. · Department of Epidemiology, Erasmus Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands. m.kavousi@erasmusmc.nl. ·Eur J Epidemiol · Pubmed #26955830.

ABSTRACT: Patients with cardiovascular disease (CVD) are a heterogeneous group regarding their body mass index (BMI) levels at the time of diagnosis. To address the heterogeneity of CVD, we examined the trajectories of change in body mass index (BMI) and in other cardio-metabolic risk factors before CVD diagnosis. The study included 6126 participants from the prospective population-based Rotterdam Study, followed over 22 years with clinical examinations every 4 years. Latent class trajectory analysis and mixed-effect models were used to develop trajectories of BMI and other cardio-metabolic risk factors respectively. During follow-up, 1748 participants developed CVD, among whom we identified 3 distinct BMI trajectories. The majority of participants (n = 1534, 87.8 %) had steady BMI levels during follow-up, comprising the "stable weight" group. This group showed decrease in mean high-density lipoprotein (HDL) cholesterol over time. The second group, the "progressive weight gain" group (n = 112, 6.4 %), showed a progressive increase in BMI levels. In this group, mean waist circumference increased, mean HDL cholesterol decreased and mean fasting glucose levels were fluctuating over follow-up. In the third group, the "progressive weight loss" group (n = 102, 5.8 %), BMI levels decreased during follow-up. This group showed a decrease in mean waist circumference and in fasting glucose. In conclusion, the majority of individuals who developed CVD had a stable weight during follow-up, suggesting that BMI alone is not a good indicator for identifying middle-aged and elderly individuals at high risk of CVD. Waist circumference, HDL cholesterol, and glucose trajectories differed between the identified BMI subgroups, further highlighting that CVD is a heterogeneous disease with different pathophysiological pathways.

18 Article Maternal plasma PUFA concentrations during pregnancy and childhood adiposity: the Generation R Study. 2016

Vidakovic, Aleksandra Jelena / Gishti, Olta / Voortman, Trudy / Felix, Janine F / Williams, Michelle A / Hofman, Albert / Demmelmair, Hans / Koletzko, Berthold / Tiemeier, Henning / Jaddoe, Vincent W V / Gaillard, Romy. ·The Generation R Study Group and Departments of Pediatrics, Epidemiology, and. · The Generation R Study Group and Epidemiology, and. · Harvard School of Public Health, Boston, MA; and. · Epidemiology, and. · Division of Metabolic Medicine, Department of Pediatrics, Dr. von Hauner Children's Hospital, Ludwig-Maximilians-University of Munich Medical Center, Munich, Germany. · Epidemiology, and Child and Adolescent Psychiatry, Erasmus University Medical Center, Rotterdam, Netherlands; · The Generation R Study Group and Departments of Pediatrics, Epidemiology, and r.gaillard@erasmusmc.nl. ·Am J Clin Nutr · Pubmed #26912493.

ABSTRACT: BACKGROUND: Maternal polyunsaturated fatty acid (PUFA) concentrations during pregnancy may have persistent effects on growth and adiposity in the offspring. A suboptimal maternal diet during pregnancy might lead to fetal cardiometabolic adaptations with persistent consequences in the offspring. OBJECTIVE: We examined the associations of maternal PUFA concentrations during pregnancy with childhood general and abdominal fat-distribution measures. DESIGN: In a population-based, prospective cohort study of 4830 mothers and their children, we measured maternal second-trimester plasma n-3 (ω-3) and n-6 (ω-6) PUFA concentrations. At the median age of 6.0 y (95% range: 5.6, 7.9 y), we measured childhood body mass index (BMI), the fat mass percentage, and the android:gynoid fat ratio with the use of dual-energy X-ray absorptiometry and measured the preperitoneal abdominal fat area with the use of ultrasound. Analyses were adjusted for maternal and childhood sociodemographic- and lifestyle-related characteristics. RESULTS: We observed that higher maternal total n-3 PUFA concentrations, and specifically those of eicosapentaenoic acid, docosapentaenoic acid, and docosahexaenoic acid, were associated with a lower childhood total-body fat percentage and a lower android:gynoid fat mass ratio (P< 0.05) but not with childhood BMI and the abdominal preperitoneal fat mass area. Higher maternal total n-6 PUFA concentrations, and specifically those of dihomo-γ-linolenic acid, were associated with a higher childhood total-body fat percentage, android:gynoid fat mass ratio, and abdominal preperitoneal fat mass area (P< 0.05) but not with childhood BMI. In line with these findings, a higher maternal n-6:n-3 PUFA ratio was associated with higher childhood total-body and abdominal fat mass. CONCLUSIONS: Lower maternal n-3 PUFA concentrations and higher n-6 PUFA concentrations during pregnancy are associated with higher body fat and abdominal fat in childhood. Additional studies are needed to replicate these observations and to explore the causality, the underlying pathways, and the long-term cardiometabolic consequences.

19 Article Subcutaneous fat mass in infancy and cardiovascular risk factors at school-age: The generation R study. 2016

Santos, Susana / Gaillard, Romy / Oliveira, Andreia / Barros, Henrique / Hofman, Albert / Franco, Oscar H / Jaddoe, Vincent W V. ·EPI-Unit, Institute of Public Health, University of Porto, Porto, Portugal. · The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. · Department of Pediatrics, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. · Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. · Department of Clinical Epidemiology, Predictive Medicine and Public Health, University of Porto Medical School, Porto, Portugal. ·Obesity (Silver Spring) · Pubmed #26813529.

ABSTRACT: OBJECTIVE: To examine the associations of infant subcutaneous fat with cardiovascular risk factors at school-age. METHODS: In a population-based prospective cohort study among 808 children, total subcutaneous fat (sum of biceps, triceps, suprailiacal, and subscapular skinfold thicknesses) and central-to-total subcutaneous fat ratio (sum of suprailiacal and subscapular skinfold thicknesses/total subcutaneous fat) at 1.5 and 24 months were estimated. At 6 years, body mass index, blood pressure, cholesterol, triglycerides, and insulin levels were measured. RESULTS: Infant subcutaneous fat measures were not associated with childhood blood pressure, triglycerides, or insulin levels. A 1-standard-deviation score (SDS) higher total subcutaneous fat at 1.5 months was, independently of body mass index, associated with lower low-density lipoprotein (LDL)-cholesterol levels at 6 years. In contrast, a 1-SDS higher total subcutaneous fat at 24 months was associated with higher total-cholesterol [difference 0.13 (95% confidence interval (CI) 0.03, 0.23) SDS] and LDL-cholesterol levels [difference 0.12 (95% CI 0.02, 0.21) SDS] at 6 years. There were no associations of central-to-total subcutaneous fat ratio with childhood cholesterol levels. CONCLUSIONS: These results suggest that infant total subcutaneous fat is weakly associated with cholesterol levels at school-age. Further studies are needed to assess the long-term cardiometabolic consequences of infant body fat.

20 Article Tracking of abdominal subcutaneous and preperitoneal fat mass during childhood. The Generation R Study. 2016

Vogelezang, S / Gishti, O / Felix, J F / van der Beek, E M / Abrahamse-Berkeveld, M / Hofman, A / Gaillard, R / Jaddoe, V W V. ·The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. · Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. · Department of Paediatrics, Erasmus MC, University Medical Center, Rotterdam, the Netherlands. · Nutricia Research, Utrecht, The Netherlands. ·Int J Obes (Lond) · Pubmed #26686002.

ABSTRACT: BACKGROUND: Overweight and obesity in early life tends to track into later life. Not much is known about tracking of abdominal fat. Our objective was to examine the extent of tracking of abdominal fat measures during the first six years of life. DESIGN: We performed a prospective cohort study among 393 Dutch children followed from the age of 2 years (90% range 1.9; 2.3) until the age of 6 years (90% range 5.7; 6.2). At both ages, we performed abdominal ultrasound to measure abdominal subcutaneous and preperitoneal fat distances and areas, and we calculated the preperitoneal/subcutaneous fat distance ratio. High abdominal fat measures were defined as values in the upper 15%. RESULTS: Abdominal subcutaneous fat distance and area, and preperitoneal fat area at 2 years were correlated with their corresponding measures at 6 years (all P-values <0.01), with the strongest coefficients for abdominal subcutaneous fat measures. Preperitoneal fat distance at the age of 2 years was not correlated with the corresponding measure at 6 years. The tracking coefficient for preperitoneal/subcutaneous fat distance ratio from 2 to 6 years was r=0.36 (P<0.01). Children with high abdominal subcutaneous fat measures at 2 years had increased risk of having high abdominal subcutaneous fat measures at 6 years (odds ratios 9.2 (95% confidence interval (CI) 4.1-20.8) and 12.4 (95% CI 5.4-28.6) for subcutaneous fat distance and area, respectively). These associations were not observed for preperitoneal fat measures. CONCLUSIONS: Our findings suggest that both abdominal subcutaneous and preperitoneal fat mass measures track during childhood, but with stronger tracking for abdominal subcutaneous fat measures. An adverse abdominal fat distribution in early life may have long-term consequences.

21 Article Genome-wide association analysis identifies three new susceptibility loci for childhood body mass index. 2016

Felix, Janine F / Bradfield, Jonathan P / Monnereau, Claire / van der Valk, Ralf J P / Stergiakouli, Evie / Chesi, Alessandra / Gaillard, Romy / Feenstra, Bjarke / Thiering, Elisabeth / Kreiner-Møller, Eskil / Mahajan, Anubha / Pitkänen, Niina / Joro, Raimo / Cavadino, Alana / Huikari, Ville / Franks, Steve / Groen-Blokhuis, Maria M / Cousminer, Diana L / Marsh, Julie A / Lehtimäki, Terho / Curtin, John A / Vioque, Jesus / Ahluwalia, Tarunveer S / Myhre, Ronny / Price, Thomas S / Vilor-Tejedor, Natalia / Yengo, Loïc / Grarup, Niels / Ntalla, Ioanna / Ang, Wei / Atalay, Mustafa / Bisgaard, Hans / Blakemore, Alexandra I / Bonnefond, Amelie / Carstensen, Lisbeth / Anonymous1040850 / Anonymous1050850 / Eriksson, Johan / Flexeder, Claudia / Franke, Lude / Geller, Frank / Geserick, Mandy / Hartikainen, Anna-Liisa / Haworth, Claire M A / Hirschhorn, Joel N / Hofman, Albert / Holm, Jens-Christian / Horikoshi, Momoko / Hottenga, Jouke Jan / Huang, Jinyan / Kadarmideen, Haja N / Kähönen, Mika / Kiess, Wieland / Lakka, Hanna-Maaria / Lakka, Timo A / Lewin, Alexandra M / Liang, Liming / Lyytikäinen, Leo-Pekka / Ma, Baoshan / Magnus, Per / McCormack, Shana E / McMahon, George / Mentch, Frank D / Middeldorp, Christel M / Murray, Clare S / Pahkala, Katja / Pers, Tune H / Pfäffle, Roland / Postma, Dirkje S / Power, Christine / Simpson, Angela / Sengpiel, Verena / Tiesler, Carla M T / Torrent, Maties / Uitterlinden, André G / van Meurs, Joyce B / Vinding, Rebecca / Waage, Johannes / Wardle, Jane / Zeggini, Eleftheria / Zemel, Babette S / Dedoussis, George V / Pedersen, Oluf / Froguel, Philippe / Sunyer, Jordi / Plomin, Robert / Jacobsson, Bo / Hansen, Torben / Gonzalez, Juan R / Custovic, Adnan / Raitakari, Olli T / Pennell, Craig E / Widén, Elisabeth / Boomsma, Dorret I / Koppelman, Gerard H / Sebert, Sylvain / Järvelin, Marjo-Riitta / Hyppönen, Elina / McCarthy, Mark I / Lindi, Virpi / Harri, Niinikoski / Körner, Antje / Bønnelykke, Klaus / Heinrich, Joachim / Melbye, Mads / Rivadeneira, Fernando / Hakonarson, Hakon / Ring, Susan M / Smith, George Davey / Sørensen, Thorkild I A / Timpson, Nicholas J / Grant, Struan F A / Jaddoe, Vincent W V / Anonymous1060850 / Anonymous1070850. ·The Generation R Study Group, Department of Pediatrics, Department of Epidemiology, j.felix@erasmusmc.nl. · Center for Applied Genomics. · The Generation R Study Group, Department of Pediatrics, Department of Epidemiology. · Department of Pulmonology, GRIAC (Groningen Research Institute for Asthma and COPD). · MRC Integrative Epidemiology Unit at the University of Bristol. · Division of Human Genetics. · Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark. · Institute of Epidemiology I, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany, Division of Metabolic and Nutritional Medicine, Dr von Hauner Children's Hospital, University of Munich Medical Center, Munich, Germany. · COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital. · Wellcome Trust Centre for Human Genetics. · Research Centre of Applied and Preventive Cardiovascular Medicine, Institute of Clinical Medicine, Neurology. · Institute of Biomedicine, Physiology, University of Eastern Finland, Kuopio, Finland. · Centre for Environmental and Preventive Medicine, Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, UK, Population, Policy and Practice, UCL Institute of Child Health. · Centre for Life Course Epidemiology. · Institute of Reproductive and Developmental Biology. · Department of Biological Psychology, VU University Amsterdam, NCA Neuroscience Campus Amsterdam, EMGO+ Institute for Health and Care Research, Amsterdam, the Netherlands. · Institute for Molecular Medicine, Finland (FIMM), University of Helsinki, Helsinki, Finland. · School of Women's and Infants' Health, The University of Western Australia, Perth, Australia. · Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland, Department of Clinical Chemistry. · Centre for Respiratory Medicine and Allergy, Institute of Inflammation and Repair, University of Manchester and University Hospital of South Manchester, Manchester Academic Health Sciences Centre, Manchester, UK. · Universidad Miguel Hernandez, Elche-Alicante, Spain, CIBER Epidemiología y Salud Pública (CIBERESP), Spain. · COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, Novo Nordisk Foundation Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, Steno Diabetes Center, Gentofte, Denmark. · Department of Genes and Envrionment, Division of Epidemiology. · Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, USA. · CIBER Epidemiología y Salud Pública (CIBERESP), Spain, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain, Pompeu Fabra University (UPF), Barcelona, Spain. · CNRS UMR8199, Pasteur Institute Lille, France, European Genomic Institute for Diabetes (EGID), Lille, France. · Novo Nordisk Foundation Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. · Department of Health Sciences, University of Leicester, Leicester, UK, Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece. · Section of Investigative Medicine, Division of Diabetes, Endocrinology, and Metabolism, Faculty of Medicine, Imperial College, London, UK. · National Institute for Health and Welfare, Helsinki, Finland. · Institute of Epidemiology I, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany. · Department of Genetics. · Center of Pediatric Research, Department of Women's and Child Health, LIFE Child (Leipzig Research Center for Civilization Diseases). · Institute of Clinical Medicine/Obstetrics and Gynecology. · Department of Psychology, University of Warwick, UK. · Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, USA, Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, USA, Department of Genetics, Harvard Medical School, Boston, USA. · The Generation R Study Group, Department of Epidemiology. · The Children's Obesity Clinic, Department of Pediatrics, Copenhagen University Hospital Holbæk, The Danish Childhood Obesity Biobank, Denmark, Institute of Medicine, Copenhagen University, Copenhagen, Denmark. · Wellcome Trust Centre for Human Genetics, Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK. · State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, Rui Jin Hospital Affiliated with Shanghai Jiao Tong University School of Medicine, Shanghai, China. · Department of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg C, Denmark. · Department of Clinical Physiology, University of Tampere School of Medicine, Tampere, Finland, Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland. · Center of Pediatric Research, Department of Women's and Child Health. · Institute of Biomedicine, Physiology, University of Eastern Finland, Kuopio, Finland, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland, Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland. · Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPE) Centre for Environment and Health, School of Public Health, Imperial College London, UK. · Department of Epidemiology, Department of Biostatistics, Harvard School of Public Health, Boston, USA. · College of Information Science and Technology, Dalian Maritime University, Dalian, Liaoning Province, China. · Division of Epidemiology, Norwegian Institute of Public Health, Oslo, Norway. · Division of Human Genetics, Division of Endocrinology, Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. · Research Centre of Applied and Preventive Cardiovascular Medicine, Department of Health and Physical Activity, Paavo Nurmi Centre, Sports and Exercise Medicine Unit. · Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, USA, Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, USA. · Center of Pediatric Research, Department of Women's and Child Health, CrescNet, Medical Faculty, University of Leipzig, Germany. · Population, Policy and Practice, UCL Institute of Child Health. · Centre for Respiratory Medicine and Allergy, Institute of Inflammation and Repair, University of Manchester and. · Department of Obstetrics and Gynecology, Sahlgrenska Academy, Sahlgrenska University Hosptial, Gothenburg, Sweden. · CIBER Epidemiología y Salud Pública (CIBERESP), Spain, Area de Salut de Menorca, ib-salut, Menorca, Spain. · The Generation R Study Group, Department of Epidemiology, Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands. · Department of Epidemiology, Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands. · Department of Pediatrics, Naestved Hospital, Naestved, Denmark, COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital. · Department of Epidemiology and Public Health, University College London, UK. · Wellcome Trust Sanger Institute, The Morgan Building, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, UK. · Division of Gastroenterology, Hepatology and Nutrition, The Children's Hospital of Philadelphia, Philadelphia, PA, USA, Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. · Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece. · CNRS UMR8199, Pasteur Institute Lille, France, Department of Genomics of Common Disease, School of Public Health, Imperial College London, Hammersmith Hospital, London, UK. · CIBER Epidemiología y Salud Pública (CIBERESP), Spain, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain, Pompeu Fabra University (UPF), Barcelona, Spain, IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain. · King's College London, MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, De Crespigny Park, London, UK. · Department of Genes and Envrionment, Division of Epidemiology, Department of Obstetrics and Gynecology, Sahlgrenska Academy, Sahlgrenska University Hosptial, Gothenburg, Sweden. · Research Centre of Applied and Preventive Cardiovascular Medicine, Department of Clinical Physiology and Nuclear Medicine. · Department of Pediatric Pulmonology and Pediatric Allergology, Beatrix Children's Hospital, GRIAC (Groningen Research Institute for Asthma and COPD), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. · Centre for Life Course Epidemiology, Biocenter Oulu, University of Oulu, Oulu, Finland. · Centre for Life Course Epidemiology, Biocenter Oulu, University of Oulu, Oulu, Finland, Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPE) Centre for Environment and Health, School of Public Health, Imperial College London, UK, Unit of Primary Care, Oulu University Hospital, Oulu, Finland, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland. · Population, Policy and Practice, UCL Institute of Child Health, School of Population Health and Sansom Institute, University of South Australia, Adelaide, Australia, South Australian Health and Medical Research Institute, Adelaide, Australia. · Wellcome Trust Centre for Human Genetics, Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK, Oxford National Institute for Health Research (NIHR) Biomedical Research Centre, Churchill Hospital, Oxford, UK. · Department of Pediatrics, Turku University Hospital, University of Turku, Turku, Finland. · Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA and. · Center for Applied Genomics, Division of Human Genetics, Department of Obstetrics and Gynecology, Sahlgrenska Academy, Sahlgrenska University Hosptial, Gothenburg, Sweden. · MRC Integrative Epidemiology Unit at the University of Bristol, Avon Longitudinal Study of Parents and Children (ALSPAC), School of Social and Community Medicine, University of Bristol, Bristol, UK. · MRC Integrative Epidemiology Unit at the University of Bristol, Novo Nordisk Foundation Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, Institute of Preventive Medicine, Bispebjerg and Frederiksberg Hospital, The Capital Region, Copenhagen, Denmark. · Center for Applied Genomics, Division of Human Genetics, Division of Endocrinology, Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. ·Hum Mol Genet · Pubmed #26604143.

ABSTRACT: A large number of genetic loci are associated with adult body mass index. However, the genetics of childhood body mass index are largely unknown. We performed a meta-analysis of genome-wide association studies of childhood body mass index, using sex- and age-adjusted standard deviation scores. We included 35 668 children from 20 studies in the discovery phase and 11 873 children from 13 studies in the replication phase. In total, 15 loci reached genome-wide significance (P-value < 5 × 10(-8)) in the joint discovery and replication analysis, of which 12 are previously identified loci in or close to ADCY3, GNPDA2, TMEM18, SEC16B, FAIM2, FTO, TFAP2B, TNNI3K, MC4R, GPR61, LMX1B and OLFM4 associated with adult body mass index or childhood obesity. We identified three novel loci: rs13253111 near ELP3, rs8092503 near RAB27B and rs13387838 near ADAM23. Per additional risk allele, body mass index increased 0.04 Standard Deviation Score (SDS) [Standard Error (SE) 0.007], 0.05 SDS (SE 0.008) and 0.14 SDS (SE 0.025), for rs13253111, rs8092503 and rs13387838, respectively. A genetic risk score combining all 15 SNPs showed that each additional average risk allele was associated with a 0.073 SDS (SE 0.011, P-value = 3.12 × 10(-10)) increase in childhood body mass index in a population of 1955 children. This risk score explained 2% of the variance in childhood body mass index. This study highlights the shared genetic background between childhood and adult body mass index and adds three novel loci. These loci likely represent age-related differences in strength of the associations with body mass index.

22 Article Protein intake in early childhood and cardiometabolic health at school age: the Generation R Study. 2016

Voortman, Trudy / van den Hooven, Edith H / Tielemans, Myrte J / Hofman, Albert / Kiefte-de Jong, Jessica C / Jaddoe, Vincent W V / Franco, Oscar H. ·Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. trudy.voortman@erasmusmc.nl. · The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. trudy.voortman@erasmusmc.nl. · Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. · The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. · Department of Pediatrics, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. ·Eur J Nutr · Pubmed #26329684.

ABSTRACT: PURPOSE: High protein intake in infancy has been linked to obesity. We aimed to examine the associations of protein intake in early childhood with cardiovascular and metabolic outcomes at school age. METHODS: This study was performed in 2965 children participating in a population-based prospective cohort study. Protein intake at 1 year was assessed with a food frequency questionnaire and was adjusted for energy intake. At the children's age of 6 years, we measured their body fat percentage (BF%), blood pressure (BP), and insulin, HDL cholesterol, and triglyceride serum levels. These measures were incorporated into a cardiometabolic risk factor score, using age- and sex-specific SD scores. RESULTS: In covariate-adjusted models, higher protein intake was associated with a higher BF%, lower diastolic BP, and lower triglyceride levels. We observed a significant interaction of protein intake with child sex on metabolic outcomes. Stratified analyses showed that protein intake was positively associated with BF% [0.07 SD (95 % CI 0.02; 0.13) per 10 g/day] and insulin levels in girls, but not in boys. In boys, but not in girls, higher protein intake was associated with lower triglyceride levels [-0.12 SD (95 % CI -0.20; -0.04) per 10 g/day] and a lower cardiometabolic risk factor score. Protein intake was not consistently associated with systolic BP or HDL cholesterol levels. CONCLUSION: Protein intake in early childhood was associated with a higher BF% and higher insulin levels at 6 years in girls and with lower triglyceride levels in boys. Further studies are needed to explore these sex differences and to investigate whether the observed changes persist into adulthood.

23 Article Body mass index, gestational weight gain and fatty acid concentrations during pregnancy: the Generation R Study. 2015

Vidakovic, Aleksandra Jelena / Jaddoe, Vincent W V / Gishti, Olta / Felix, Janine F / Williams, Michelle A / Hofman, Albert / Demmelmair, Hans / Koletzko, Berthold / Tiemeier, Henning / Gaillard, Romy. ·The Generation R Study Group (Na29-15), Erasmus MC, University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands. · Department of Pediatrics, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. · Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. · The Generation R Study Group (Na29-15), Erasmus MC, University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands. v.jaddoe@erasmusmc.nl. · Department of Pediatrics, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. v.jaddoe@erasmusmc.nl. · Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. v.jaddoe@erasmusmc.nl. · Harvard T.H. Chan School of Public Health, Boston, MA, USA. · Division of Metabolic Medicine, Department of Pediatrics, Dr. von Hauner Children's Hospital, Ludwig-Maximilians-University of Munich Medical Center, Munich, Germany. · Department of Child and Adolescent Psychiatry, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. · The Generation R Study Group (Na29-15), Erasmus MC, University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands. r.gaillard@erasmusmc.nl. · Department of Pediatrics, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. r.gaillard@erasmusmc.nl. · Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. r.gaillard@erasmusmc.nl. ·Eur J Epidemiol · Pubmed #26666541.

ABSTRACT: Obesity during pregnancy may be correlated with an adverse nutritional status affecting pregnancy and offspring outcomes. We examined the associations of prepregnancy body mass index and gestational weight gain with plasma fatty acid concentrations in mid-pregnancy. This study was embedded in a population-based prospective cohort study among 5636 women. We obtained prepregnancy body mass index and maximum weight gain during pregnancy by questionnaires. We measured concentrations of saturated fatty acid (SFA), monounsaturated fatty acid (MUFA), n-3 polyunsaturated fatty acid (n-3 PUFA) and n-6 polyunsaturated fatty acid (n-6 PUFA) at a median gestational age of 20.5 (95% range 17.1-24.9) weeks. We used multivariate linear regression models. As compared to normal weight women, obese women had higher total SFA concentrations [difference: 0.10 standard deviation (SD) (95% Confidence Interval (CI) 0, 0.19)] and lower total n-3 PUFA concentrations [difference: - 0.11 SD (95% CI - 0.20, - 0.02)]. As compared to women with sufficient gestational weight gain, those with excessive gestational weight gain had higher SFA concentrations [difference: 0.16 SD (95% CI 0.08, 0.25)], MUFA concentrations [difference: 0.16 SD (95% CI 0.08, 0.24)] and n-6 PUFA concentrations [difference: 0.12 SD (95% CI 0.04, 0.21)]. These results were not materially affected by adjustment for maternal characteristics. Our results suggest that obesity and excessive weight gain during pregnancy are associated with an adverse fatty acids profile. Further studies are needed to assess causality and direction of the observed associations.

24 Article Ethnic disparities in maternal obesity and weight gain during pregnancy. The Generation R Study. 2015

Bahadoer, Sunayna / Gaillard, Romy / Felix, Janine F / Raat, Hein / Renders, Carry M / Hofman, Albert / Steegers, Eric A P / Jaddoe, Vincent W V. ·The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, The Netherlands; Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, The Netherlands. · The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, The Netherlands; Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, The Netherlands; Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, The Netherlands. · The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, The Netherlands; Department of Public Health, Erasmus MC, University Medical Center Rotterdam, The Netherlands. · Department of Health Sciences, Section Prevention and Public Health, VU University Amsterdam, The Netherlands. · Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, The Netherlands. · Department of Obstetrics and Gynaecology, Erasmus MC, University Medical Center Rotterdam, The Netherlands. · The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, The Netherlands; Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, The Netherlands; Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, The Netherlands. Electronic address: v.jaddoe@erasmusmc.nl. ·Eur J Obstet Gynecol Reprod Biol · Pubmed #26232727.

ABSTRACT: OBJECTIVE: To examine ethnic disparities in maternal prepregnancy obesity and gestational weight gain, and to examine to which extent these differences can be explained by socio-demographic, lifestyle and pregnancy related characteristics. METHODS: In a multi-ethnic population-based prospective cohort study among 6444 pregnant women in Rotterdam, the Netherlands, maternal anthropometrics were repeatedly measured throughout pregnancy. Ethnicity, socio-demographic, lifestyle and pregnancy related characteristics were assessed by physical examinations and questionnaires. RESULTS: The prevalence of prepregnancy overweight and obesity was 23.1% among Dutch-origin women. Statistically higher prevalences were observed among Dutch Antillean-origin (40.8%), Moroccan-origin (49.9%), Surinamese-Creole-origin (38.6%) and Turkish-origin (41.1%) women (all p-values <0.05). Only Dutch Antillean-origin, Moroccan-origin, Surinamese-Creole-origin and Turkish-origin women had higher risks of maternal prepregnancy overweight and obesity as compared to Dutch-origin women (p-values <0.05). Socio-demographic and lifestyle related characteristics explained up to 45% of the ethnic differences in body mass index. Compared to Dutch-origin women, total gestational weight gain was lower in all ethnic minority groups, except for Cape Verdean-origin and Surinamese-Creole-origin women (p-values <0.05). Lifestyle and pregnancy related characteristics explained up to 33% and 40% of these associations, respectively. The largest ethnic differences in gestational weight gain were observed in late pregnancy. CONCLUSION: We observed moderate ethnic differences in maternal prepregnancy overweight, obesity and gestational weight gain. Socio-demographic, lifestyle and pregnancy related characteristics partly explained these differences. Whether these differences also lead to ethnic differences in maternal and childhood outcomes should be further studied.

25 Article Body fat distribution, metabolic and inflammatory markers and retinal microvasculature in school-age children. The Generation R Study. 2015

Gishti, O / Jaddoe, V W V / Hofman, A / Wong, T Y / Ikram, M K / Gaillard, R. ·The Generation R Study Group, Erasmus University Medical Center, Rotterdam, The Netherlands. · Department of Pediatrics, Erasmus University Medical Center, Rotterdam, The Netherlands. · Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands. · Singapore Eye Research Institute, Singapore. · Duke-NUS Graduate Medical School, National University of Singapore, Singapore. · Memeory Aging & Cognition Centre (MACC), National University Health System, Singapore. · Department of Ophthalmology, Erasmus University Medical Center, Rotterdam, The Netherlands. ·Int J Obes (Lond) · Pubmed #26028060.

ABSTRACT: OBJECTIVE: To examine the associations of body fatness, metabolic and inflammatory markers with retinal vessel calibers among children. DESIGN: We performed a population-based cohort study among 4145 school-age children. At the median age of 6.0 years (95% range 5.8, 8.0 years), we measured body mass index, total and abdominal fat mass, metabolic and inflammatory markers (blood levels of lipids, insulin and C-peptide and C-reactive protein) and retinal vascular calibers from retinal photographs. RESULTS: We observed that compared with normal weight children, obese children had narrower retinal arteriolar caliber (difference -0.21 s.d. score (SDS; 95% confidence interval (CI) -0.35, -0.06)), but not venular caliber. Continuous analyses showed that higher body mass index and total body fat mass, but not android/gynoid fat mass ratio and pre-peritoneal fat mass, were associated with narrower retinal arteriolar caliber (P<0.05 for body mass index and total body fat mass), but not with retinal venular caliber. Lipid and insulin levels were not associated with retinal vessel calibers. Higher C-reactive protein was associated with only wider retinal venular caliber (difference 0.10 SDS (95% CI 0.06, 0.14) per SDS increase in C-reactive protein). This latter association was not influenced by body mass index. CONCLUSIONS: Higher body fatness is associated with narrower retinal arteriolar caliber, whereas increased C-reactive protein levels are associated with wider retinal venular caliber. Increased fat mass and inflammation correlate with microvascular development from school-age onwards.

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