Data de publicació electrònica: 11-01-2021 ; Altered maternal haemoglobin levels during pregnancy are associated with pre-clinical and clinical conditions affecting the fetus. Evidence from animal models suggests that these associations may be partially explained by differential DNA methylation in the newborn with possible long-term consequences. To test this in humans, we meta-analyzed the epigenome-wide associations of maternal haemoglobin levels during pregnancy with offspring DNA methylation in 3,967 newborn cord blood and 1,534 children and 1,962 adolescent whole-blood samples derived from 10 cohorts. DNA methylation was measured using Illumina Infinium Methylation 450K or MethylationEPIC arrays covering 450,000 and 850,000 methylation sites, respectively. There was no statistical support for the association of maternal haemoglobin levels with offspring DNA methylation either at individual methylation sites or clustered in regions. For most participants, maternal haemoglobin levels were within the normal range in the current study, whereas adverse perinatal outcomes often arise at the extremes. Thus, this study does not rule out the possibility that associations with offspring DNA methylation might be seen in studies with more extreme maternal haemoglobin levels. ; Study-specific funding information can be found in the Supplementary Methods. JR, AH, EL, and SS were supported by the European Union's Horizon 2020 research and innovation program [grant numbers 633595 (DynaHEALTH) and 733206 (LifeCycle)], Academy of Finland [grant number 285547 (EGEA)] and the Biocenter Oulu. ACJ was funded by the National Institute of Environmental Health Sciences [grant number R00ES023450]. AK was supported by the National Institute of Environmental Health Sciences [grant number R01ES021357]. DCa was funded by the UK Medical Research Council [grant number MC_UU_00011/7]. EKa received funding from the Horizon2020 grant for RECAP Research on Children and Adults Born Preterm [grant number 733280], Academy of Finland [grant number 315690], Foundation for Pediatric Research, Novo Nordisk Foundation, Signe and Ane Gyllenberg Foundation and Sigrid Jusélius Foundation. EKe received funding from the Finnish Medical Association. MG was supported by Miguel Servet fellowship from the Institute of Health Carlos III [grant numbers MS13/00054, CP18/00018]. MVä received funding from the Research Funds of Oulu University Hospital, Juho Vainio Foundation and Signe and Ane Gyllenberg Foundation. RCH was supported by the National Health and Medical Research Council Fellowship Grants [grant number 1053384]. SJL was supported by the intramural research program of the National Institutes of Health, National Institute of Environmental Health Sciences. SM received funding from the University of Oulu Graduate School. SR was supported by National Health and Medical Research Council EU [grant number 1142858] and the Department of Health, Western Australia FutureHealth fund in connection with the European Union's Horizon 2020 [grant number 733206].
International audience ; Introduction: Depression, cardiovascular diseases and diabetes are among the major non-communicable diseases, leading to significant disability and mortality worldwide. These diseases may share environmental and genetic determinants associated with multimorbid patterns. Stressful early-life events are among the primary factors associated with the development of mental and physical diseases. However, possible causative mechanisms linking early life stress (ELS) with psycho-cardio-metabolic (PCM) multi-morbidity are not well understood. This prevents a full understanding of causal pathways towards the shared risk of these diseases and the development of coordinated preventive and therapeutic interventions.Methods and analysis: This paper describes the study protocol for EarlyCause, a large-scale and inter-disciplinary research project funded by the European Union's Horizon 2020 research and innovation programme. The project takes advantage of human longitudinal birth cohort data, animal studies and cellular models to test the hypothesis of shared mechanisms and molecular pathways by which ELS shapes an individual's physical and mental health in adulthood. The study will research in detail how ELS converts into biological signals embedded simultaneously or sequentially in the brain, the cardiovascular and metabolic systems. The research will mainly focus on four biological processes including possible alterations of the epigenome, neuroendocrine system, inflammatome, and the gut microbiome. Life-course models will integrate the role of modifying factors as sex, socioeconomics, and lifestyle with the goal to better identify groups at risk as well as inform promising strategies to reverse the possible mechanisms and/or reduce the impact of ELS on multi-morbidity development in high-risk individuals. These strategies will help better manage the impact of multi-morbidity on human health and the associated risk.
International audience ; Introduction: Depression, cardiovascular diseases and diabetes are among the major non-communicable diseases, leading to significant disability and mortality worldwide. These diseases may share environmental and genetic determinants associated with multimorbid patterns. Stressful early-life events are among the primary factors associated with the development of mental and physical diseases. However, possible causative mechanisms linking early life stress (ELS) with psycho-cardio-metabolic (PCM) multi-morbidity are not well understood. This prevents a full understanding of causal pathways towards the shared risk of these diseases and the development of coordinated preventive and therapeutic interventions.Methods and analysis: This paper describes the study protocol for EarlyCause, a large-scale and inter-disciplinary research project funded by the European Union's Horizon 2020 research and innovation programme. The project takes advantage of human longitudinal birth cohort data, animal studies and cellular models to test the hypothesis of shared mechanisms and molecular pathways by which ELS shapes an individual's physical and mental health in adulthood. The study will research in detail how ELS converts into biological signals embedded simultaneously or sequentially in the brain, the cardiovascular and metabolic systems. The research will mainly focus on four biological processes including possible alterations of the epigenome, neuroendocrine system, inflammatome, and the gut microbiome. Life-course models will integrate the role of modifying factors as sex, socioeconomics, and lifestyle with the goal to better identify groups at risk as well as inform promising strategies to reverse the possible mechanisms and/or reduce the impact of ELS on multi-morbidity development in high-risk individuals. These strategies will help better manage the impact of multi-morbidity on human health and the associated risk.
International audience ; Introduction: Depression, cardiovascular diseases and diabetes are among the major non-communicable diseases, leading to significant disability and mortality worldwide. These diseases may share environmental and genetic determinants associated with multimorbid patterns. Stressful early-life events are among the primary factors associated with the development of mental and physical diseases. However, possible causative mechanisms linking early life stress (ELS) with psycho-cardio-metabolic (PCM) multi-morbidity are not well understood. This prevents a full understanding of causal pathways towards the shared risk of these diseases and the development of coordinated preventive and therapeutic interventions.Methods and analysis: This paper describes the study protocol for EarlyCause, a large-scale and inter-disciplinary research project funded by the European Union's Horizon 2020 research and innovation programme. The project takes advantage of human longitudinal birth cohort data, animal studies and cellular models to test the hypothesis of shared mechanisms and molecular pathways by which ELS shapes an individual's physical and mental health in adulthood. The study will research in detail how ELS converts into biological signals embedded simultaneously or sequentially in the brain, the cardiovascular and metabolic systems. The research will mainly focus on four biological processes including possible alterations of the epigenome, neuroendocrine system, inflammatome, and the gut microbiome. Life-course models will integrate the role of modifying factors as sex, socioeconomics, and lifestyle with the goal to better identify groups at risk as well as inform promising strategies to reverse the possible mechanisms and/or reduce the impact of ELS on multi-morbidity development in high-risk individuals. These strategies will help better manage the impact of multi-morbidity on human health and the associated risk.
In: Mariani , N , Borsini , A , Cecil , C A M , Felix , J F , Sebert , S , Cattaneo , A , Walton , E , Milaneschi , Y , Cochrane , G , Amid , C , Rajan , J , Giacobbe , J , Sanz , Y , Agustí , A , Sorg , T , Herault , Y , Miettunen , J , Parmar , P , Cattane , N , Jaddoe , V , Lötjönen , J , Buisan , C , González Ballester , M A , Piella , G , Gelpi , J L , Lamers , F , Penninx , B W J H , Tiemeier , H , von Tottleben , M , Thiel , R , Heil , K F , Järvelin , M-R , Pariante , C , Mansuy , I M & Lekadir , K 2021 , ' Identifying causative mechanisms linking early-life stress to psycho-cardio-metabolic multi-morbidity: The EarlyCause project ' , PLoS ONE , vol. 16 , no. 1 January , e0245475 . https://doi.org/10.1371/journal.pone.0245475
Introduction Depression, cardiovascular diseases and diabetes are among the major non-communicable diseases, leading to significant disability and mortality worldwide. These diseases may share environmental and genetic determinants associated with multimorbid patterns. Stressful early-life events are among the primary factors associated with the development of mental and physical diseases. However, possible causative mechanisms linking early life stress (ELS) with psycho-cardio-metabolic (PCM) multi-morbidity are not well understood. This prevents a full understanding of causal pathways towards the shared risk of these diseases and the development of coordinated preventive and therapeutic interventions. Methods and analysis This paper describes the study protocol for EarlyCause, a large-scale and inter-disciplinary research project funded by the European Union's Horizon 2020 research and innovation programme. The project takes advantage of human longitudinal birth cohort data, animal studies and cellular models to test the hypothesis of shared mechanisms and molecular pathways by which ELS shapes an individual's physical and mental health in adulthood. The study will research in detail how ELS converts into biological signals embedded simultaneously or sequentially in the brain, the cardiovascular and metabolic systems. The research will mainly focus on four biological processes including possible alterations of the epigenome, neuroendocrine system, inflammatome, and the gut microbiome. Life-course models will integrate the role of modifying factors as sex, socioeconomics, and lifestyle with the goal to better identify groups at risk as well as inform promising strategies to reverse the possible mechanisms and/or reduce the impact of ELS on multi-morbidity development in high-risk individuals. These strategies will help better manage the impact of multi-morbidity on human health and the associated risk.
Depression, cardiovascular diseases and diabetes are among the major non-communicable diseases, leading to significant disability and mortality worldwide. These diseases may share environmental and genetic determinants associated with multimorbid patterns. Stressful early-life events are among the primary factors associated with the development of mental and physical diseases. However, possible causative mechanisms linking early life stress (ELS) with psycho-cardio-metabolic (PCM) multi-morbidity are not well understood. This prevents a full understanding of causal pathways towards the shared risk of these diseases and the development of coordinated preventive and therapeutic interventions. ; This work is supported by the European Union's Horizon 2020 research and innovation programme (grant n ̊ 848158). ; Peer reviewed
Introduction: Depression, cardiovascular diseases and diabetes are among the major non-communicable diseases, leading to significant disability and mortality worldwide. These diseases may share environmental and genetic determinants associated with multimorbid patterns. Stressful early-life events are among the primary factors associated with the development of mental and physical diseases. However, possible causative mechanisms linking early life stress (ELS) with psycho-cardio-metabolic (PCM) multi-morbidity are not well understood. This prevents a full understanding of causal pathways towards the shared risk of these diseases and the development of coordinated preventive and therapeutic interventions. Methods and analysis: This paper describes the study protocol for EarlyCause, a large-scale and inter-disciplinary research project funded by the European Union's Horizon 2020 research and innovation programme. The project takes advantage of human longitudinal birth cohort data, animal studies and cellular models to test the hypothesis of shared mechanisms and molecular pathways by which ELS shapes an individual's physical and mental health in adulthood. The study will research in detail how ELS converts into biological signals embedded simultaneously or sequentially in the brain, the cardiovascular and metabolic systems. The research will mainly focus on four biological processes including possible alterations of the epigenome, neuroendocrine system, inflammatome, and the gut microbiome. Life-course models will integrate the role of modifying factors as sex, socioeconomics, and lifestyle with the goal to better identify groups at risk as well as inform promising strategies to reverse the possible mechanisms and/or reduce the impact of ELS on multi-morbidity development in high-risk individuals. These strategies will help better manage the impact of multi-morbidity on human health and the associated risk.
Introduction: Depression, cardiovascular diseases and diabetes are among the major non-communicable diseases, leading to significant disability and mortality worldwide. These diseases may share environmental and genetic determinants associated with multimorbid patterns. Stressful early-life events are among the primary factors associated with the development of mental and physical diseases. However, possible causative mechanisms linking early life stress (ELS) with psycho-cardio-metabolic (PCM) multi-morbidity are not well understood. This prevents a full understanding of causal pathways towards shared risk of these diseases and the development of coordinated preventive and therapeutic interventions. Methods and analysis: This paper describes the study protocol for EarlyCause, a large-scale and inter-disciplinary research project funded by the European Union's Horizon 2020 research and innovation programme. The project takes advantage of human longitudinal birth cohort data, animal studies and cellular models to test the hypothesis of shared mechanisms and molecular pathways by which ELS shape an individual's physical and mental health in adulthood. The study will research in detail how ELS converts into biological signals embedded simultaneously or sequentially in the brain, the cardiovascular and metabolic systems. The research will mainly focus on four biological processes including possible alterations of the epigenome, neuroendocrine system, inflammatome, and the gut microbiome. Life course models will integrate the role of modifying factors as sex, socioeconomics, and lifestyle with the goal to better identify groups at risk as well as inform promising strategies to reverse the possible mechanisms and/or reduce the impact of ELS on multi-morbidity development in high-risk individuals. These strategies will help better manage the impact of multi-morbidity on human health and the associated risk. Ethics and dissemination: The study has been approved by the Ethics Board of the European Commission. The results ...
In: Parmar , P , Lowry , E , Cugliari , G , Suderman , M , Wilson , R , Karhunen , V , Andrew , T , Wiklund , P , Wielscher , M , Guarrera , S , Teumer , A , Lehne , B , Milani , L , de Klein , N , Mishra , P , Melton , P , Mandaviya , P , Kasela , S , Nano , J , Zhang , W , Zhang , Y , Uitterlinden , A , Peters , A , Schottker , B , Gieger , C , Anderson , D , Boomsma , D , Grabe , H , Panico , S , Veldink , J , van Meurs , J , van den Berg , L , Beilin , L , Franke , L , Loh , M , van Greevenbroek , M , Nauck , M , Kahonen , M , Hurme , M , Raitakari , O , Franco , O , Slagboom , P , van der Harst , P , Kunze , S , Felix , S , Zhang , T , Chen , W , Mori , T , Bonnefond , A , Heijmans , B , Muka , T , Kooner , J , Fischer , K , Waldenberger , M , Froguel , P , Huang , R , Lehtimaki , T , Rathman , W , Relton , C , Matullo , G , Brenner , H , Verweij , N , Li , S , Chambers , J , Jarvelin , M-R & Sebert , S 2018 , ' Association of maternal prenatal smoking GFI1-locus and cardio-metabolic phenotypes in 18,212 adults ' , EBioMedicine , vol. 38 , pp. 206-216 . https://doi.org/10.1016/j.ebiom.2018.10.066
Background:DNA methylation at theGFI1-locus has been repeatedly associated with exposure to smoking fromthe foetal period onwards. We explored whether DNA methylation may be a mechanism that links exposure tomaternal prenatal smoking with offspring's adult cardio-metabolic health.Methods:We meta-analysed the association between DNA methylation atGFI1-locus with maternal prenatalsmoking, adult own smoking, and cardio-metabolic phenotypes in 22 population-based studies from Europe,Australia, and USA (n= 18,212). DNA methylation at theGFI1-locus was measured in whole-blood. Multivari-able regression models werefitted to examine its association with exposure to prenatal and own adult smoking.DNA methylation levels were analysed in relation to body mass index (BMI), waist circumference (WC), fastingglucose (FG), high-density lipoprotein cholesterol (HDL—C), triglycerides (TG), diastolic, and systolic blood pres-sure (BP).Findings:Lower DNA methylation at three out of eightGFI1-CpGs was associated with exposure to maternal pre-natal smoking, whereas, all eight CpGs were associated with adult own smoking. Lower DNA methylation atcg14179389, the strongest maternal prenatal smoking locus, was associated with increased WC and BP when ad-justed for sex, age, and adult smoking with Bonferroni-correctedPb0·012. In contrast, lower DNA methylationatcg09935388,thestrongest adultownsmokinglocus, wasassociated with decreasedBMI, WC,and BP (adjusted1×10−7bPb0.01). Similarly, lower DNA methylation at cg12876356, cg18316974, cg09662411, andcg18146737 was associated with decreased BMI and WC (5 × 10−8bPb0.001). Lower DNA methylation at allthe CpGs was consistently associated with higher TG levels.Interpretation:Epigenetic changes at theGFI1were linked to smoking exposurein-utero/in-adulthood and ro-bustly associated with cardio-metabolic risk factors.Fund:European Union's Horizon 2020 research and innovation programme under grant agreement no. 633595DynaHEALTH.
Background: DNA methylation at the GFI1-locus has been repeatedly associated with exposure to smoking from the foetal period onwards. We explored whether DNA methylation may be a mechanism that links exposure to maternal prenatal smoking with offspring's adult cardio-metabolic health. Methods: We meta-analysed the association between DNA methylation at GFI1-locus with maternal prenatal smoking, adult own smoking, and cardio-metabolic phenotypes in 22 population-based studies from Europe, Australia, and USA (n= 18,212). DNA methylation at the GFI1-locus was measured in whole-blood. Multivariable regression models were fitted to examine its association with exposure to prenatal and own adult smoking. DNA methylation levels were analysed in relation to body mass index (BMI), waist circumference (WC), fasting glucose (FG), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), diastolic, and systolic blood pressure (BP). Findings: Lower DNA methylation at three out of eight GFI1-CpGs was associated with exposure to maternal prenatal smoking, whereas, all eight CpGs were associated with adult own smoking. Lower DNA methylation at cg14179389, the strongest maternal prenatal smoking locus, was associated with increased WC and BP when adjusted for sex, age, and adult smoking with Bonferroni-corrected P < 0.012. In contrast, lower DNA methylation at cg09935388, the strongest adult own smoking locus, was associated with decreased BMI, WC, and BP (adjusted 1 x 10(-7) < P < 0.01). Similarly, lower DNA methylation at cg12876356, cg18316974, cg09662411, and cg18146737 was associated with decreased BMI and WC (5 x 10(-8) < P < 0.001). Lower DNA methylation at all the CpGs was consistently associated with higher TG levels. Interpretation: Epigenetic changes at the GFI1 were linked to smoking exposure in-utero/in-adulthood and robustly associated with cardio-metabolic risk factors. Fund: European Union's Horizon 2020 research and innovation programme under grant agreement no. 633595 DynaHEALTH.
Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age-and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to similar to 2.8M SNPs with BMI and WHRadjBMI in four strata (men 50y, women 50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR= 50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may providefurther insights into the biology that underlies weight change with age or the sexually dimorphism of body shape. ; Funding: Funding for this study was provided by the Aarne Koskelo Foundation; the Aase and Ejner Danielsens Foundation; the Academy of Finland (40758, 41071, 77299, 102318, 104781, 117787, 117844, 118590, 120315, 121584, 123885, 124243, 124282, 126925, 129269, 129293, 129378, 130326, 134309, 134791, 136895, 139635, 211497, 263836, 263924, 1114194, 24300796); the Agency for Health Care Policy Research (HS06516); the Agency for Science, Technology and Research of Singapore (A*STAR); the Ahokas Foundation; the ALF/LUA research grant in Gothenburg; the ALK-Abello A/S (Horsholm, Denmark), Timber Merchant Vilhelm Bangs Foundation, MEKOS Laboratories Denmark; the Althingi (the Icelandic Parliament); the American Heart Association (AHA; 13POST16500011); the ANR ("Agence Nationale de la 359 Recherche"); the Ark (NHMRC Enabling Facility); the Arthritis Research UK (19542, 18030); the AstraZeneca; the Augustinus Foundation; the Australian National Health and Medical Research Council (NHMRC; 241944, 389875, 389891, 389892, 389938, 442915, 442981, 496739, 496688, 552485, 613672, 613601 and 1011506); the Australian Research Council (ARC; DP0770096 and DP1093502); the Becket Foundation; the bi-national BMBF/ANR funded project CARDomics (01KU0908A); the Biobanking and Biomolecular Resources Research Infrastructure (BBMRINL; 184.021.007, CP 32); the Biocentrum Helsinki; the Boehringer Ingelheim Foundation; the British Heart Foundation (RG/10/12/28456, SP/04/ 002); the Canadian Institutes for Health Reseaerch (FRCN-CCT-83028); the Cancer Research UK (C490/A10124, C490/A10119); the Center for Medical Systems Biology (CMSB; NWO Genomics); the Centers for Disease Control and Prevention and Association of Schools of Public Health (1734, S043, S3486); the Centre of Excellence Baden-Wurttemberg Metabolic Disorders; the Chief Scientist Office of the Scottish Government; the Clinical Research Facility at Guys & St Thomas NHS Foundation Trust; the Contrat de Projets Etat-Region (CPER); the Croatian Science Council (Grant no. 8875); the CVON (GENIUS); the Danish Agency for Science, Technology and Innovation; the Danish Centre for Health Technology Assessment, Novo Nordisk Inc.; the Danish Council for Independent Research (DFF 1333-00124); the Danish Diabetes Association; Danish Heart Foundation; the Danish Medical Research Council; the Danish Ministry of Internal Affairs and Health; the Danish National Research Foundation; the Danish Pharmaceutical Association; Danish Pharmacists Fund; the Danish Research Council; the Deutsche Forschungsgemeinschaft; the Diabetes Hilfs-und Forschungsfonds Deutschland (DHFD); the Dr. Robert Pfleger-Stiftung; the Dresden University of Technology Funding Grant, Med Drive; the Dutch Brain Foundation; the Dutch Diabetes Research Foundation; the Dutch Economic Structure Enhancing Fund (FES); the Dutch Kidney Foundation; the Dutch Ministry for Health, Welfare and Sports; the Dutch Ministry of Economic Affairs; the Dutch Ministry of Education, Culture and Science; the Egmont Foundation; the Else Kraner-Fresenius Stiftung (2012_A147, P48/08//A11/08); the Emil Aaltonen Foundation; the Erasmus Medical Center and Erasmus University, Rotterdam; the Estonian Ministry of Science and Education (SF0180142s08); the European Commission (223004, 2004310, DGXII, FP6-EUROSPAN, FP6-EXGENESIS, FP6-LSHG-CT2006-018947, FP6-LSHG-CT-2006-01947, FP6-LSHM- CT-2004-503485, FP6-LSHM-CT-2006037593, FP6-LSHM-CT-2007-037273, FP7-201379, FP7-201668, FP7-279143, FP7-305739, FP7313010, FP7-ENGAGE-HEALTH-F4-2007-201413, FP7-EurHEALTHAgeing-277849, FP7-HEALTH-F42007-201550, HEALTH-2011.2.4.2-2-EU-MASCARA, HEALTH-F2-2008-201865-GEFOS, HEALTH-F7305507 HOMAGE, LSHM-CT-2006-037593, QLG1CT-2001-01252, QLG1-CT-2002-00896, QLG2-CT2002-01254); the European Regional Development Fund (ERDF) and the Wissenschaftsoffensive TMO; the European Regional Development Fund to the Centre of Excellence in Genomics (EXCEGEN; 3.2.0304.11-0312); the European Research Council (ERC; 2011-StG-280559-SEPI, 2011-294713-EPLORE, 230374); the European Science Foundation (ESF; EU/QLRT-2001-01254); the EuroSTRESS project FP-006; the Finlands Slottery Machine Association; the Finnish Centre for Pensions (ETK); the Finnish Cultural Foundation; the Finnish Diabetes Association; the Finnish Diabetes Research Foundation; the Finnish Foundation for Cardiovascular Research; the Finnish Foundation for Pediatric Research; the Finnish Funding Agency for Technology and Innovation (40058/07); the Finnish Medical Society; the Finnish Ministry of Education and Culture (627; 2004-2011); the Finnish Ministry of Health and Social Affairs (5254); the Finnish National Public Health Institute (current National Institute for Health and Welfare); the Finnish Special Governmental Subsidy for Health Sciences; the Finska Lakaresallskapet, Signe and Ane Gyllenberg Foundation; the Flemish League against Cancer, ITEA2 (project Care4Me); the Folkhalsan Research Foundation; the Fonds voor Wetenschappelijk Onderzoek (FWO) Vlaanderen; the Foundation for Life and Health in Finland; the Foundation for Strategic Research (SSF) and the Stockholm County Council (560283); the G. Ph. Verhagen Foundation; the Gene-diet Interactions in Obesity' project (GENDINOB); the Genetic Association Information Network (GAIN); the GENEVA Coordinating Center (U01 HG 004446); the GenomEUtwin (EU/QLRT2001-01254; QLG2-CT-2002-01254); the German Bundesministerium fuer Forschung und Technology (01 AK 803 A-H, 01 IG 07015 G); the German Diabetes Association; the German Ministry of Cultural Affairs; the German Federal Ministry of Education and Research (BMBF; 03IS2061A, 03ZIK012, 01ZZ9603, 01ZZ0103, 01ZZ0403); the German National Genome Research Network (NGFN-2 and NGFN-plus); the German Research Council (SFB1052 "Obesity mechanisms"); the Great Wine Estates of the Margaret River region of Western Australia; the Greek General Secretary of Research and Technology research grant (PENED 2003); the Gyllenberg Foundation; the Health Care Centers in Vasa, Narpes and Korsholm; the Health Fund of the Danish Health Insurance Societies; the Helmholtz Zentrum Munchen-German Research Center for Environmental Health; the Helsinki University Central Hospital special government funds (EVO #TYH7215, #TKK2012005, #TYH2012209); the Hjartavernd (the Icelandic Heart Association); the Ib Henriksen Foundation; the Illinois Department of Public Health, and the Translational Genomics Research Institute; the INTERREG IV Oberrhein Program (Project A28); the Interuniversity Cardiology Institute of the Netherlands (ICIN; 09.001); the Italian Ministry of Health "targeted project" (ICS110.1/RF97.71); the Italian National Centre of Research InterOmics PB05_ SP3; the John D and Catherine T MacArthur Foundation Research Networks on Successful Midlife Development and Socio-economic Status and Health; the Johns Hopkins University Center for Inherited Disease Research (CIDR); the Joint grant from Siemens Healthcare, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania; the Juho Vainio Foundation; the Juselius Foundation (Helsinki, Finland); the Juvenile Diabetes Research Foundation International (JDRF); the KfH Stiftung Praventivmedizin e. V.; the Knut and Alice Wallenberg Foundation; the Kuopio University Hospital; the Leenaards Foundation; the Leiden University Medical Center; the Liv och Halsa; the Local Government Pensions Institution (KEVA); the Lokaal Gezondheids Overleg (LOGO) Leuven and Hageland; the LudwigMaximilians- Universitat, as part of LMUinnovativ; the Lundberg Foundation; the March of Dimes Birth Defects Foundation; the Medical Research Council (G0601966; G0700931; G0000934; G0500539; G0600705; G1002319; G0701863; PrevMetSyn/SALVE; MC_ U106179471; MC_ UU_ 12019/1); the MRC centre for Causal Analyses in Translational Epidemiology (MRC CAiTE); the MRC Centre for Obesity and Related Metabolic Diseases; the MRC Human Genetics Unit; the Medical Research Council of Canada; the Mid-Atlantic Nutrition and Obesity Research Center (P30 DK072488); the Ministry of the Flemish Community, Brussels, Belgium (G. 0881.13 and G. 0880. 13); the MIUR-CNR Italian Flagship Project; the Montreal Heart Institute Foundation; the Munich Center of Health Sciences (MC Health); the Municipal Health Care Center and Hospital in Jakobstad; the Narpes Health Care Foundation; the National Alliance for Research on Schizophrenia and Depression (NARSAD); the National Cancer Institute (CA047988); the National Center for Advancing Translational Sciences (UL1TR000124); the National Center for Research Resources (U54RR020278); the National Heart, Lung and Blood Institute (NHLBI, 1RL1MH083268-01, 5R01HL087679-02, HHSN268200800007C, HHSN268201200036C, HL043851, HL080467, HL087647, HL36310, HL45670, N01HC25195, N01HC55015, N01HC55016, N01HC55018, N01HC55019, N01HC55020, N01HC55021, N01HC55022, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, N02HL64278, R01HL086694, R01HL087641, R01HL087652, R01HL087676, R01HL59367, R01HL103612, R01HL105756, R01HL120393, U01HL080295); the National Human Genome Research Institute (NHGRI, U01HG004402); the National Institute for Health and Welfare (THL); the National Institute for Health Research (NIHR, RP-PG-0407-10371); the National Institute of Allergy and Infectious Diseases (NIAID); the National Institute of Child Health and Human Development (NICHD); the National Institute of Diabetes and Digestive and Kidney Disease (NIDDKDRC, 1R01DK8925601, DK063491, R01DK089256, P30 DK072488); the National Institute of Food and Agriculture (2007-35205-17883); the National Institute of Neurological Disorders and Stroke (NINDS); the National Institute on Aging (NIA; 263-MA-410953, 263-MD-821336, 263-MD-9164, AG023629, AG13196, NO1AG12109, P30AG10161, R01AG15819, R01AG17917, R01AG023629, R01AG30146); the National Institute of Arthritis and Musculoskeletal and Skin Diseases (5-P60-AR30701, 5-P60-AR49465-03); the National Institutes of Health (NIH; 1R01DK8925601, 1RC2MH089951, 1RC2MH089995, 1Z01HG000024, 2T32 HL 00705536, 5R01DK075681, 5R01MH63706: 02, AA014041, AA07535, AA10248, AA13320, AA13321, AA13326, AG028555, AG08724, AG04563, AG10175, AG08861, DA12854, DK046200, DK091718, F32AR059469, HG002651, HHSN268200625226C, HHSN268200782096C, HL084729, MH081802, N01AG12100, N01HG65403, R01AG011101, R01AG030146, R01D0042157-01A, R01DK062370, R01DK072193, R01DK093757, R01DK075787, R01DK075787, R01HL71981, R01MH59565, R01MH59566, R01MH59571, R01MH59586, R01MH59587, R01MH59588, R01MH60870, R01MH60879, R01MH61675, R01MH67257, R01MH81800, R01NS45012, U01066134, U01CA098233, U01DK062418, U01GM074518, U01HG004423, U01HG004436, U01HG004438, U01HL072515-06, U01HL105198, U01HL84756, U01MH79469, U01MH79470, U01NS069208-01, UL1RR025005); the NIHR Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust; the NIHR Cambridge Biomedical research Centre; the Netherlands Heart Foundation (2001 D 032); the Netherlands Organisation for Scientific Research (NWO; Geestkracht program grant 10-000-1002; 050-060-810; 100-001-004; 175.010.2003.005; 175.010.2005.011; 175.010.2007. 006; 261-98-710; 40-0056-98-9032; 400-05-717; 452-04-314; 452-06-004; 480-01-006; 480-04-004; 480-05-003; 480-07-001; 481-08-013; 60-60600-97-118; 904-61-090; 904-61-193; 911-03012; 985-10-002; Addiction-31160008; GB-MW 94038- 011; SPI 56-464-14192); the Netherlands Organization for the Health Research and Development (ZonMw; 91111025); the Nordic Center of Excellence in Disease Genetics; the Nordic Centre of Excellence on Systems biology in controlled dietary interventions and cohort studies, SYSDIET (070014); the Northern Netherlands Collaboration of Provinces (SNN); the Novo Nordisk Foundation; the Office of Research and Development, Medical Research Service, and the Baltimore Geriatrics Research, Education, and Clinical Center of the Department of Veterans Affairs; the Ollqvist Foundation; the Paavo Nurmi Foundation; the Pahlssons Foundation; the Paivikki and Sakari Sohlberg Foundation; the Perklen Foundation; the Republic of Croatia Ministry of Science, Education and Sports research (108-1080315-0302); the Research Centre for Prevention and Health, the Capital Region of Denmark; the Research Foundation of Copenhagen County; the Research Institute for Diseases in the Elderly (014-93-015; RIDE2); the Reynold's Foundation; the Rotterdam Oncologic Thoracic Study Group, Erasmus Trust Fund, Foundation against Cancer; the Royal Swedish Academy of Science; the Russian Foundation for Basic Research (NWO-RFBR 047.017.043); the Rutgers University Cell and DNA Repository cooperative agreement (NIMH U24 MH068457-06); the Samfundet Folkhalsan; the Sigrid Juselius Foundation; the Social Insurance Institution of Finland, Kuopio, Tampere and Turku University Hospital Medical Funds (9M048, 9N035); the Social Ministry of the Federal State of Mecklenburg-West Pomerania; the Societe Francophone du 358 Diabste (SFD); the South Tyrolean Sparkasse Foundation; the Stichting Nationale Computerfaciliteiten (National Computing Facilities Foundation, NCF); the Strategic Cardiovascular Programme of Karolinska Institutet and the Stockholm County Council (560183); the Susan G. Komen Breast Cancer Foundation; the Swedish Cancer Society; the Swedish Cultural Foundation in Finland; the Swedish Diabetes Association; the Swedish Diabetes Foundation (grant no. 2013-024); the Swedish Foundation for Strategic Research (SSF; ICA08-0047); the Swedish HeartLung Foundation (20120197); the Swedish Medical Research Council (K2007-66X-20270-01-3, 20121397); the Swedish Ministry for Higher Education; the Swedish Research Council (8691, M-2005-1112, 2009-2298); the Swedish Society for Medical Research; the Swiss National Science Foundation (31003A-143914, 3200B0105993, 3200B0-118308, 33CSCO-122661, 33CS30-139468, 33CS30148401); SystemsX. ch (51RTP0_151019); the Tampere Tuberculosis Foundation; the TEKES (70103/06, 40058/07); the The Paul Michael Donovan Charitable Foundation; the Torsten and Ragnar Sderberg Foundation; the Umea Medical Research Foundation; the United Kingdom NIHR Cambridge Biomedical Research Centre; the Universities and Research of the Autonomous Province of Bolzano, South Tyrol; the University Hospital of Regensburg (ReForM A, ReForM C); the University Hospital Oulu, Biocenter, University of Oulu, Finland (75617); the University Medical Center Groningen; the University of Groningen; the University of Maryland General Clinical Research Center (M01RR16500, AG000219); the University of Tartu (SP1GVARENG); the University of Tromso, Norwegian Research Council (185764); the Vasterbottens Intervention Programme; the Velux Foundation; the VU University Institute for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam (NCA); the Wellcome Trust (064890, 068545/Z/02, 076113/B/04/Z, 077016/Z/05/Z, 079895, 084723/Z/08/Z, 086596/Z/ 08/Z, 088869/B/09/Z, 089062, 090532, 098017, 098051, 098381); the Western Australian DNA Bank (NHMRC Enabling Facility); the Yrjo Jahnsson Foundation (56358); and the Zorg Onderzoek Nederland-Medische Wetenschappen, KWF Kankerbestrijding, Stichting Centraal Fonds Reserves van voormalig Vrijwillige Ziekenfondsverzekeringen. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. More details of acknowledgements can be found in S2 Text.