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1. DNA methylation and body mass index from birth to adolescence: meta-analyses of epigenome-wide association studies

Author

Vehmeijer, Florianne OL, Küpers, Leanne K, Sharp, Gemma C, Salas, Lucas A, Lent, Samantha, Jima, Dereje D, Tindula, Gwen, Reese, Sarah, Qi, Cancan, Gruzieva, Olena, Page, Christian, Rezwan, Faisal I, Melton, Philip E, Nohr, Ellen, Escaramís, Geòrgia, Rzehak, Peter, Heiskala, Anni, Gong, Tong, Tuominen, Samuli T, Gao, Lu, Ross, Jason P, Starling, Anne P, Holloway, John W, Yousefi, Paul, Aasvang, Gunn Marit, Beilin, Lawrence J, Bergström, Anna, Binder, Elisabeth, Chatzi, Leda, Corpeleijn, Eva, Czamara, Darina, Eskenazi, Brenda, Ewart, Susan, Ferre, Natalia, Grote, Veit, Gruszfeld, Dariusz, Håberg, Siri E, Hoyo, Cathrine, Huen, Karen, Karlsson, Robert, Kull, Inger, Langhendries, Jean-Paul, Lepeule, Johanna, Magnus, Maria C, Maguire, Rachel L, Molloy, Peter L, Monnereau, Claire, Mori, Trevor A, Oken, Emily, Räikkönen, Katri, Rifas-Shiman, Sheryl, Ruiz-Arenas, Carlos, Sebert, Sylvain, Ullemar, Vilhelmina, Verduci, Elvira, Vonk, Judith M, Xu, Cheng-jian, Yang, Ivana V, Zhang, Hongmei, Zhang, Weiming, Karmaus, Wilfried, Dabelea, Dana, Muhlhausler, Beverly S, Breton, Carrie V, Lahti, Jari, Almqvist, Catarina, Jarvelin, Marjo-Riitta, Koletzko, Berthold, Vrijheid, Martine, Sørensen, Thorkild IA, Huang, Rae-Chi, Arshad, Syed Hasan, Nystad, Wenche, Melén, Erik, Koppelman, Gerard H, London, Stephanie J, Holland, Nina, Bustamante, Mariona, Murphy, Susan K, Hivert, Marie-France, Baccarelli, Andrea, Relton, Caroline L, Snieder, Harold, Jaddoe, Vincent WV, and Felix, Janine F

Subjects
Biological Sciences, Genetics, Pediatric, Nutrition, Prevention, Human Genome, Obesity, 2.3 Psychological, social and economic factors, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Cardiovascular, Cancer, Stroke, Oral and gastrointestinal, Adolescent, Body Mass Index, Child, Child, Preschool, CpG Islands, Cross-Sectional Studies, DNA Methylation, Epigenesis, Genetic, Epigenome, Female, Fetal Blood, Humans, Male, Parturition, Pediatric Obesity, Pregnancy, Body mass index, Childhood obesity, DNA methylation, Epigenetics, Clinical Sciences
Abstract

BackgroundDNA methylation has been shown to be associated with adiposity in adulthood. However, whether similar DNA methylation patterns are associated with childhood and adolescent body mass index (BMI) is largely unknown. More insight into this relationship at younger ages may have implications for future prevention of obesity and its related traits.MethodsWe examined whether DNA methylation in cord blood and whole blood in childhood and adolescence was associated with BMI in the age range from 2 to 18 years using both cross-sectional and longitudinal models. We performed meta-analyses of epigenome-wide association studies including up to 4133 children from 23 studies. We examined the overlap of findings reported in previous studies in children and adults with those in our analyses and calculated enrichment.ResultsDNA methylation at three CpGs (cg05937453, cg25212453, and cg10040131), each in a different age range, was associated with BMI at Bonferroni significance, P

Published
2020

2. Meta-analysis of epigenome-wide association studies in neonates reveals widespread differential DNA methylation associated with birthweight

Author

Küpers, Leanne K, Monnereau, Claire, Sharp, Gemma C, Yousefi, Paul, Salas, Lucas A, Ghantous, Akram, Page, Christian M, Reese, Sarah E, Wilcox, Allen J, Czamara, Darina, Starling, Anne P, Novoloaca, Alexei, Lent, Samantha, Roy, Ritu, Hoyo, Cathrine, Breton, Carrie V, Allard, Catherine, Just, Allan C, Bakulski, Kelly M, Holloway, John W, Everson, Todd M, Xu, Cheng-Jian, Huang, Rae-Chi, van der Plaat, Diana A, Wielscher, Matthias, Merid, Simon Kebede, Ullemar, Vilhelmina, Rezwan, Faisal I, Lahti, Jari, van Dongen, Jenny, Langie, Sabine AS, Richardson, Tom G, Magnus, Maria C, Nohr, Ellen A, Xu, Zongli, Duijts, Liesbeth, Zhao, Shanshan, Zhang, Weiming, Plusquin, Michelle, DeMeo, Dawn L, Solomon, Olivia, Heimovaara, Joosje H, Jima, Dereje D, Gao, Lu, Bustamante, Mariona, Perron, Patrice, Wright, Robert O, Hertz-Picciotto, Irva, Zhang, Hongmei, Karagas, Margaret R, Gehring, Ulrike, Marsit, Carmen J, Beilin, Lawrence J, Vonk, Judith M, Jarvelin, Marjo-Riitta, Bergström, Anna, Örtqvist, Anne K, Ewart, Susan, Villa, Pia M, Moore, Sophie E, Willemsen, Gonneke, Standaert, Arnout RL, Håberg, Siri E, Sørensen, Thorkild IA, Taylor, Jack A, Räikkönen, Katri, Yang, Ivana V, Kechris, Katerina, Nawrot, Tim S, Silver, Matt J, Gong, Yun Yun, Richiardi, Lorenzo, Kogevinas, Manolis, Litonjua, Augusto A, Eskenazi, Brenda, Huen, Karen, Mbarek, Hamdi, Maguire, Rachel L, Dwyer, Terence, Vrijheid, Martine, Bouchard, Luigi, Baccarelli, Andrea A, Croen, Lisa A, Karmaus, Wilfried, Anderson, Denise, de Vries, Maaike, Sebert, Sylvain, Kere, Juha, Karlsson, Robert, Arshad, Syed Hasan, Hämäläinen, Esa, Routledge, Michael N, Boomsma, Dorret I, Feinberg, Andrew P, Newschaffer, Craig J, Govarts, Eva, Moisse, Matthieu, Fallin, M Daniele, Melén, Erik, and Prentice, Andrew M

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Health Sciences, Reproductive Medicine, Pediatric, Human Genome, Infant Mortality, 2.1 Biological and endogenous factors, Aetiology, Reproductive health and childbirth, Good Health and Well Being, Adolescent, Adult, Birth Weight, Body Mass Index, Child, CpG Islands, DNA, DNA Methylation, Epigenesis, Genetic, Female, Fetal Development, Fetus, Folic Acid, Genome, Human, Genome-Wide Association Study, Humans, Infant, Newborn, Male, Pregnancy, Prenatal Exposure Delayed Effects, Smoking
Abstract

Birthweight is associated with health outcomes across the life course, DNA methylation may be an underlying mechanism. In this meta-analysis of epigenome-wide association studies of 8,825 neonates from 24 birth cohorts in the Pregnancy And Childhood Epigenetics Consortium, we find that DNA methylation in neonatal blood is associated with birthweight at 914 sites, with a difference in birthweight ranging from -183 to 178 grams per 10% increase in methylation (PBonferroni

Published
2019

3. Maternal BMI at the start of pregnancy and offspring epigenome-wide DNA methylation: findings from the pregnancy and childhood epigenetics (PACE) consortium

Author

Sharp, Gemma C, Salas, Lucas A, Monnereau, Claire, Allard, Catherine, Yousefi, Paul, Everson, Todd M, Bohlin, Jon, Xu, Zongli, Huang, Rae-Chi, Reese, Sarah E, Xu, Cheng-Jian, Baïz, Nour, Hoyo, Cathrine, Agha, Golareh, Roy, Ritu, Holloway, John W, Ghantous, Akram, Merid, Simon K, Bakulski, Kelly M, Küpers, Leanne K, Zhang, Hongmei, Richmond, Rebecca C, Page, Christian M, Duijts, Liesbeth, Lie, Rolv T, Melton, Phillip E, Vonk, Judith M, Nohr, Ellen A, Williams-DeVane, ClarLynda, Huen, Karen, Rifas-Shiman, Sheryl L, Ruiz-Arenas, Carlos, Gonseth, Semira, Rezwan, Faisal I, Herceg, Zdenko, Ekström, Sandra, Croen, Lisa, Falahi, Fahimeh, Perron, Patrice, Karagas, Margaret R, Quraishi, Bilal M, Suderman, Matthew, Magnus, Maria C, Jaddoe, Vincent WV, Taylor, Jack A, Anderson, Denise, Zhao, Shanshan, Smit, Henriette A, Josey, Michele J, Bradman, Asa, Baccarelli, Andrea A, Bustamante, Mariona, Håberg, Siri E, Pershagen, Göran, Hertz-Picciotto, Irva, Newschaffer, Craig, Corpeleijn, Eva, Bouchard, Luigi, Lawlor, Debbie A, Maguire, Rachel L, Barcellos, Lisa F, Smith, George Davey, Eskenazi, Brenda, Karmaus, Wilfried, Marsit, Carmen J, Hivert, Marie-France, Snieder, Harold, Fallin, M Daniele, Melén, Erik, Munthe-Kaas, Monica C, Arshad, Hasan, Wiemels, Joseph L, Annesi-Maesano, Isabella, Vrijheid, Martine, Oken, Emily, Holland, Nina, Murphy, Susan K, Sørensen, Thorkild IA, Koppelman, Gerard H, Newnham, John P, Wilcox, Allen J, Nystad, Wenche, London, Stephanie J, Felix, Janine F, and Relton, Caroline L

Subjects
Biological Sciences, Genetics, Perinatal Period - Conditions Originating in Perinatal Period, Contraception/Reproduction, Pediatric, Human Genome, Obesity, 2.1 Biological and endogenous factors, Aetiology, Reproductive health and childbirth, Adult, Body Mass Index, Cohort Studies, DNA Methylation, Epigenesis, Genetic, Epigenomics, Female, Humans, Infant, Newborn, Male, Maternal Inheritance, Mothers, Pregnancy, Pregnancy Outcome, Prenatal Exposure Delayed Effects, Medical and Health Sciences, Genetics & Heredity
Abstract

Pre-pregnancy maternal obesity is associated with adverse offspring outcomes at birth and later in life. Individual studies have shown that epigenetic modifications such as DNA methylation could contribute. Within the Pregnancy and Childhood Epigenetics (PACE) Consortium, we meta-analysed the association between pre-pregnancy maternal BMI and methylation at over 450,000 sites in newborn blood DNA, across 19 cohorts (9,340 mother-newborn pairs). We attempted to infer causality by comparing the effects of maternal versus paternal BMI and incorporating genetic variation. In four additional cohorts (1,817 mother-child pairs), we meta-analysed the association between maternal BMI at the start of pregnancy and blood methylation in adolescents. In newborns, maternal BMI was associated with small (

Published
2017

4. Large-scale genome-wide analysis identifies genetic variants associated with cardiac structure and function

Author

Wild, Philipp S, Felix, Janine F, Schillert, Arne, Teumer, Alexander, Chen, Ming-Huei, Leening, Maarten JG, Völker, Uwe, Großmann, Vera, Brody, Jennifer A, Irvin, Marguerite R, Shah, Sanjiv J, Pramana, Setia, Lieb, Wolfgang, Schmidt, Reinhold, Stanton, Alice V, Malzahn, Dörthe, Smith, Albert Vernon, Sundström, Johan, Minelli, Cosetta, Ruggiero, Daniela, Lyytikäinen, Leo-Pekka, Tiller, Daniel, Smith, J Gustav, Monnereau, Claire, Di Tullio, Marco R, Musani, Solomon K, Morrison, Alanna C, Pers, Tune H, Morley, Michael, Kleber, Marcus E, Aragam, Jayashri, Benjamin, Emelia J, Bis, Joshua C, Bisping, Egbert, Broeckel, Ulrich, Cheng, Susan, Deckers, Jaap W, Del Greco M, Fabiola, Edelmann, Frank, Fornage, Myriam, Franke, Lude, Friedrich, Nele, Harris, Tamara B, Hofer, Edith, Hofman, Albert, Huang, Jie, Hughes, Alun D, Kähönen, Mika, investigators, KNHI, Kruppa, Jochen, Lackner, Karl J, Lannfelt, Lars, Laskowski, Rafael, Launer, Lenore J, Leosdottir, Margrét, Lin, Honghuang, Lindgren, Cecilia M, Loley, Christina, MacRae, Calum A, Mascalzoni, Deborah, Mayet, Jamil, Medenwald, Daniel, Morris, Andrew P, Müller, Christian, Müller-Nurasyid, Martina, Nappo, Stefania, Nilsson, Peter M, Nuding, Sebastian, Nutile, Teresa, Peters, Annette, Pfeufer, Arne, Pietzner, Diana, Pramstaller, Peter P, Raitakari, Olli T, Rice, Kenneth M, Rivadeneira, Fernando, Rotter, Jerome I, Ruohonen, Saku T, Sacco, Ralph L, Samdarshi, Tandaw E, Schmidt, Helena, Sharp, Andrew SP, Shields, Denis C, Sorice, Rossella, Sotoodehnia, Nona, Stricker, Bruno H, Surendran, Praveen, Thom, Simon, Töglhofer, Anna M, Uitterlinden, André G, Wachter, Rolf, Völzke, Henry, Ziegler, Andreas, Münzel, Thomas, März, Winfried, Cappola, Thomas P, Hirschhorn, Joel N, Mitchell, Gary F, Smith, Nicholas L, and Fox, Ervin R

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Human Genome, Clinical Research, Prevention, Heart Disease, Cardiovascular, 2.1 Biological and endogenous factors, Aetiology, Female, Genetic Loci, Genome-Wide Association Study, Heart Diseases, Humans, Male, Myocardium, Polymorphism, Single Nucleotide, Quantitative Trait, Heritable, Medical and Health Sciences, Immunology, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundUnderstanding the genetic architecture of cardiac structure and function may help to prevent and treat heart disease. This investigation sought to identify common genetic variations associated with inter-individual variability in cardiac structure and function.MethodsA GWAS meta-analysis of echocardiographic traits was performed, including 46,533 individuals from 30 studies (EchoGen consortium). The analysis included 16 traits of left ventricular (LV) structure, and systolic and diastolic function.ResultsThe discovery analysis included 21 cohorts for structural and systolic function traits (n = 32,212) and 17 cohorts for diastolic function traits (n = 21,852). Replication was performed in 5 cohorts (n = 14,321) and 6 cohorts (n = 16,308), respectively. Besides 5 previously reported loci, the combined meta-analysis identified 10 additional genome-wide significant SNPs: rs12541595 near MTSS1 and rs10774625 in ATXN2 for LV end-diastolic internal dimension; rs806322 near KCNRG, rs4765663 in CACNA1C, rs6702619 near PALMD, rs7127129 in TMEM16A, rs11207426 near FGGY, rs17608766 in GOSR2, and rs17696696 in CFDP1 for aortic root diameter; and rs12440869 in IQCH for Doppler transmitral A-wave peak velocity. Findings were in part validated in other cohorts and in GWAS of related disease traits. The genetic loci showed associations with putative signaling pathways, and with gene expression in whole blood, monocytes, and myocardial tissue.ConclusionThe additional genetic loci identified in this large meta-analysis of cardiac structure and function provide insights into the underlying genetic architecture of cardiac structure and warrant follow-up in future functional studies.FundingFor detailed information per study, see Acknowledgments.

Published
2017

5. The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia : design, results and future prospects

Author

Middeldorp, Christel M., Mahajan, Anubha, Horikoshi, Momoko, Robertson, Neil R., Beaumont, Robin N., Bradfield, Jonathan P., Bustamante, Mariona, Cousminer, Diana L., Day, Felix R., De Silva, N. Maneka, Guxens, Monica, Mook-Kanamori, Dennis O., St Pourcain, Beate, Warrington, Nicole M., Adair, Linda S., Ahlqvist, Emma, Ahluwalia, Tarunveer S., Almgren, Peter, Ang, Wei, Atalay, Mustafa, Auvinen, Juha, Bartels, Meike, Beckmann, Jacques S., Bilbao, Jose Ramon, Bond, Tom, Borja, Judith B., Cavadino, Alana, Charoen, Pimphen, Chen, Zhanghua, Coin, Lachlan, Cooper, Cyrus, Curtin, John A., Custovic, Adnan, Das, Shikta, Davies, Gareth E., Dedoussis, George V., Duijts, Liesbeth, Eastwood, Peter R., Eliasen, Anders U., Elliott, Paul, Eriksson, Johan G., Estivill, Xavier, Fadista, Joao, Fedko, Iryna O., Frayling, Timothy M., Gaillard, Romy, Gauderman, W. James, Geller, Frank, Gilliland, Frank, Gilsanz, Vincente, Granell, Raquel, Grarup, Niels, Groop, Leif, Hadley, Dexter, Hakonarson, Hakon, Hansen, Torben, Hartman, Catharina A., Hattersley, Andrew T., Hayes, M. Geoffrey, Hebebrand, Johannes, Heinrich, Joachim, Helgeland, Oyvind, Henders, Anjali K., Henderson, John, Henriksen, Tine B., Hirschhorn, Joel N., Hivert, Marie-France, Hocher, Berthold, Holloway, John W., Holt, Patrick, Hottenga, Jouke-Jan, Hypponen, Elina, Iniguez, Carmen, Johansson, Stefan, Jugessur, Astanand, Kahonen, Mika, Kalkwarf, Heidi J., Kaprio, Jaakko, Karhunen, Ville, Kemp, John P., Kerkhof, Marjan, Koppelman, Gerard H., Korner, Antje, Kotecha, Sailesh, Kreiner-Moller, Eskil, Kulohoma, Benard, Kumar, Ashish, Kutalik, Zoltan, Lahti, Jari, Lappe, Joan M., Larsson, Henrik, Lehtimaki, Terho, Lewin, Alexandra M., Li, Jin, Lichtenstein, Paul, Lindgren, Cecilia M., Lindi, Virpi, Linneberg, Allan, Liu, Xueping, Liu, Jun, Lowe, William L., Jr., Lundstrom, Sebastian, Lyytikainen, Leo-Pekka, Ma, Ronald C. W., Mace, Aurelien, Magi, Reedik, Magnus, Per, Mamun, Abdullah A., Mannikko, Minna, Martin, Nicholas G., Mbarek, Hamdi, McCarthy, Nina S., Medland, Sarah E., Melbye, Mads, Melen, Erik, Mohlke, Karen L., Monnereau, Claire, Morgen, Camilla S., Morris, Andrew P., Murray, Jeffrey C., Myhre, Ronny, Najman, Jackob M., Nivard, Michel G., Nohr, Ellen A., Nolte, Ilja M., Ntalla, Ioanna, O'Reilly, Paul, Oberfield, Sharon E., Oken, Emily, Oldehinkel, Albertine J., Pahkala, Katja, Palviainen, Teemu, Panoutsopoulou, Kalliope, Pedersen, Oluf, Pennell, Craig E., Pershagen, Goran, Pitkanen, Niina, Plomin, Robert, Power, Christine, Prasad, Rashmi B., Prokopenko, Inga, Pulkkinen, Lea, Raikkonen, Katri, Raitakari, Olli T., Reynolds, Rebecca M., Richmond, Rebecca C., Rivadeneira, Fernando, Rodriguez, Alina, Rose, Richard J., Salem, Rany, Santa-Marina, Loreto, Saw, Seang-Mei, Schnurr, Theresia M., Scott, James G., Selzam, Saskia, Shepherd, John A., Simpson, Angela, Skotte, Line, Sleiman, Patrick M. A., Snieder, Harold, Sørensen, Thorkild I. A., Standl, Marie, Steegers, Eric A. P., Strachan, David P., Straker, Leon, Strandberg, Timo, Taylor, Michelle, Teo, Yik-Ying, Thiering, Elisabeth, Torrent, Maties, Tyrrell, Jessica, Uitterlinden, Andre G., van Beijsterveldt, Toos, van der Most, Peter J., van Duijn, Cornelia M., Viikari, Jorma, Vilor-Tejedor, Natalia, Vogelezang, Suzanne, Vonk, Judith M., Vrijkotte, Tanja G. M., Vuoksimaa, Eero, Wang, Carol A., Watkins, William J., Wichmann, H-Erich, Willemsen, Gonneke, Williams, Gail M., Wilson, James F., Wray, Naomi R., Xu, Shujing, Xu, Cheng-Jian, Yaghootkar, Hanieh, Yi, Lu, Zafarmand, Mohammad Hadi, Zeggini, Eleftheria, Zemel, Babette S., Hinney, Anke, Lakka, Timo A., Whitehouse, Andrew J. O., Sunyer, Jordi, Widen, Elisabeth E., Feenstra, Bjarke, Sebert, Sylvain, Jacobsson, Bo, Njolstad, Pal R., Stoltenberg, Camilla, Smith, George Davey, Lawlor, Debbie A., Paternoster, Lavinia, Timpson, Nicholas J., Ong, Ken K., Bisgaard, Hans, Bonnelykke, Klaus, Jaddoe, Vincent W. V., Tiemeier, Henning, Jarvelin, Marjo-Riitta, Evans, David M., Perry, John R. B., Grant, Struan F. A., Boomsma, Dorret I., Freathy, Rachel M., McCarthy, Mark I., Felix, Janine F., Sorensen, Thorkild I. A., Tiemeier, Hen-Ning, Biological Psychology, APH - Mental Health, APH - Personalized Medicine, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Methodology, APH - Health Behaviors & Chronic Diseases, Pediatrics, Epidemiology, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Groningen Research Institute for Asthma and COPD (GRIAC), Life Course Epidemiology (LCE), Public and occupational health, APH - Aging & Later Life, ARD - Amsterdam Reproduction and Development, ACS - Atherosclerosis & ischemic syndromes, APH - Global Health, Epidemiology and Data Science, Medical Research Council (MRC), Johan Eriksson / Principal Investigator, Department of General Practice and Primary Health Care, Centre of Excellence in Complex Disease Genetics, Institute for Molecular Medicine Finland, University of Helsinki, Department of Public Health, Clinicum, Doctoral Programme in Cognition, Learning, Instruction and Communication, Department of Psychology and Logopedics, Helsinki Collegium for Advanced Studies, Faculty of Medicine, Timo Strandberg / Principal Investigator, Department of Medicine, Elisabeth Ingrid Maria Widen / Principal Investigator, HUS Internal Medicine and Rehabilitation, HUS Abdominal Center, Developmental Psychology Research Group, Genetic Epidemiology, Genomic Discoveries and Clinical Translation, Cognitive and Brain Aging, Middeldorp, Christel M [0000-0002-6218-0428], and Apollo - University of Cambridge Repository

Subjects
Male, Netherlands Twin Register (NTR), embarazo, Epidemiology, C840 Clinical Psychology, LD SCORE REGRESSION, humanos, LOCI, Medizin, adolescente, Genome-wide association study, BLOOD-PRESSURE, Disease, 030204 cardiovascular system & hematology, Cohort Studies, 0302 clinical medicine, Pregnancy, Medicine, 030212 general & internal medicine, Early childhood, C820 Developmental Psychology, estudios de cohortes, Child, C440 Molecular Genetics, Public, Environmental & Occupational Health, Genetics, education.field_of_study, United Kingdom/epidemiology, COMMON VARIANTS, Hälsovetenskaper, adulto, A900 Others in Medicine and Dentistry, 3142 Public health care science, environmental and occupational health, 3. Good health, predicción, ddc, Childhood traits and disorders, Phenotype, Disease/genetics, Research Design, Child, Preschool, fenotipo, Female, ICEP, medicine.symptom, CHILDHOOD OBESITY, Life Sciences & Biomedicine, EArly Genetics Lifecourse Epidemiology (EAGLE) consortium, Adult, medicine.medical_specialty, Adolescent, Birth weight, Population, Consortium, Childhood Traits And Disorders, Longitudinal, enfermedad, Childhood obesity, 1117 Public Health and Health Services, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Health Sciences, Humans, Genetic Predisposition to Disease, GENOME-WIDE ASSOCIATION, education, LONGITUDINAL TWIN, METAANALYSIS, lactante, Science & Technology, Early Growth Genetics (EGG) consortium, business.industry, Infant, Newborn, Infant, predisposición genética a la enfermedad, medicine.disease, BODY-MASS, C800 Psychology, BIRTH-WEIGHT, C420 Human Genetics, United Kingdom, Low birth weight, business, diseño de la investigación, Forecasting
Abstract

The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites., We are grateful to all families and participants who took part in these studies. We also acknowledge and appreciate the unique efforts of the research teams and practitioners contributing to the collection of this wealth of data. C. M. M. is supported by funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no. 721567. J. F. F. has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 633595 (DynaHEALTH) and 733206 (LifeCycle). R. M. F. and R. N. B. are supported by Sir Henry Dale Fellowship (Wellcome Trust and Royal Society grant: WT104150). D. L. C. is funded by the American Diabetes Association Grant 1-17-PDF-077. D. O. M-K. was supported by Dutch Science Organization (ZonMW-VENI Grant 916.14.023). N. M. W. is supported by an Australian National Health and Medical Research Council Early Career Fellowship (APP1104818). T. S. A. was partially funded by the Gene-Diet Interactions in Obesity (GENDINOB) project on behalf of GOYA male cohort data management and analyses and acknowledges the same. S. D. was supported by National Institute of Health Research. T. M. F. is supported by the European Research Council grant: 323195 SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC. The Novo Nordisk Foundation Center for Basic Metabolic Research is an independent Research Center at the University of Copenhagen partially funded by an unrestricted donation from the Novo Nordisk Foundation (www.metabol.ku.dk).H.H.is funded by The Children's Hospital of Philadelphia Endowed Chair in Genomic Research. A. T. H. is supported by the Wellcome Trust Senior Investigator Awards (WT098395), National Institute for Health Research (NIHR) Senior Investigator Award (NF-SI-0611-10219). J. Hebebrand received grants from German Research Society, German Ministry of Education and Research. M-F. H. is currently supported by an American Diabetes Association (ADA) Pathway Program Accelerator Early Investigator Award (1-15-ACE-26). S. J. is supported by Helse Vest no. 23929, Bergen Forskningsstiftelse and KG Jebsen Foundation and University of Bergen. J. K. has been supported by the Academy of Finland Research Professor program (grants 265240 & 263278). J. P. K. is funded by a University of Queensland Development Fellowship (UQFEL1718945). H. L. has served as a speaker for Eli-Lilly and Shire and has received research grants from Shire; all outside the submitted work. C. M. L is supported by the Li Ka Shing Foundation, WT-SSI/John Fell funds and by the NIHR Biomedical Research Centre, Oxford, by Widenlife and NIH (5P50HD028138-27). S. E. M. was funded by an NHMRC Senior Reseach Fellowship (APP1103623). K. Panoutsopoulou is funded by a career development fellowship (grant 20308) and by the Wellcome Trust (WT098051). C. P. at UCL Institute of Child Health, with support from the National Institute for Health Research Biomedical Research Centre at Great Ormond Street Hospital for Children NHS Foundation Trust and University College London. I. P. was funded in part by the Wellcome Trust (WT205915), and the European Union's Horizon 2020 research, the European Union FP7-IDEAS-ERC Advanced Grant (GEPIDIAB, ERC-AG -ERC-294785), and innovation programme (DYNAhealth, H2020-PHC-2014-633595). R. C. R. is supported by CRUK (grant number C18281/A19169). J. G. S. is supported by an NHMRC Practitioner Fellowship Grant (APP1105807). J. T.; r is funded by the European Regional Development Fund (ERDF), the European Social Fund (ESF), Convergence Programme for Cornwall and the Isles of Scilly and the Diabetes Research and Wellness Foundation Non-Clinical Fellowship. N. V-T. is funded by a pre-doctoral grant from the Agencia de Gestio d'Ajuts Universitaris i de Recerca (AGAUR) (2015 FI_B 00636), Generalitat de Catalunya. T. G. M. V was supported by ZonMW (TOP 40-00812-98-11010. J. F. W. is supported by the MRC Human Genetics Unit quinquennial programme QTL in Health and Disease. H. Y. is funded by Diabetes UK RD Lawrence fellowship (grant: 17/0005594). M. H. Z was supported by BBMRI-NL (CP2013-50). E. Z. is supported by the Wellcome Trust (098051). B. F. is supported by Novo Nordisk Foundation (12955) and an Oak Foundation Fellowship. S. S. and M-R. J. have received funding from the European Union's Horizon 2020 research and innovation programme [under grant agreement No 633595] for the DynaHEALTH action. P. R. N. was supported by the European Research Council (ERC), University of Bergen, KG Jebsen and Helse Vest. G. D. S. works within the MRC Integrative Epidemiology Unit at the University of Bristol (MC_UU_12013/1). D. A. L was supported by the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement (Grant number 669545; DevelopObese), US National Institute of Health (grant: R01 DK10324), the UK Medical Research Council (grant: MC_UU_00011/6), Wellcome Trust GWAS grant (WT088806), an NIHR Senior Investigator Award (NF-SI-0611-10196) and the NIHR Biomedical Research Centre at University Hospitals Bristol NHS Foundation Trust and the University of Bristol. L. Paternoster was supported by the UK Medical Research Council Unit grants MC_UU_12013_5. N. J. T. is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 102215/2/13/2), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC) and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). V.W.V.J. received an additional grant from the Netherlands Organization for Health Research and Development (NWO, ZonMw-VIDI 016.136.361), a European Research Council Consolidator Grant (ERC-2014-CoG-648916) and funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 633595 (DynaHEALTH) and 733206 (LifeCycle). D. M. E. is funded by the UK Medical Research Council Unit grant MC_UU_12013_4, Australian Research Council Future Fellowship (FT130101709) and a NHMRC Senior Research Fellowship (GNT1137714). S. F. A. G. is funded by the Daniel B. Burke Endowed Chair for Diabetes Research and R01 HD056465. D. I. B. is supported by Spinozapremie (NWO-56-464-14192) and the Royal Netherlands Academy of Science Professor Award (PAH/6635) to DIB. M. I. M. is a Wellcome Senior Investgator and NIHR Senior Investigator supported by the Wellcome (090532, 098381, 203141), NIHR (NF-SI-0617-10090) and the US National Institute of Health (grant: R01 DK10324), the UK Medical Research Council (grant: MCiabetes UK RD Lawrence fellowship (grant: 17/0005594). M. H. Z was supported by BBMRI-NLNIHR Biomedical Research Centre, Oxford. The views expressed in this article are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health.

Published
2019
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6. Associations of genetic risk scores based on adult adiposity pathways with childhood growth and adiposity measures.

Author

Monnereau, Claire, Vogelezang, Suzanne, Kruithof, Claudia J., Jaddoe, Vincent W. V., and Felix, Janine F.

Subjects
*OBESITY, *GROWTH of children, *BODY mass index, *REGRESSION analysis, *MEMBRANE proteins, *HOMEOSTASIS
Abstract

Background: Results from genome-wide association studies (GWAS) identified many loci and biological pathways that influence adult body mass index (BMI). We aimed to identify if biological pathways related to adult BMI also affect infant growth and childhood adiposity measures. Methods: We used data from a population-based prospective cohort study among 3,975 children with a mean age of 6 years. Genetic risk scores were constructed based on the 97 SNPs associated with adult BMI previously identified with GWAS and on 28 BMI related biological pathways based on subsets of these 97 SNPs. Outcomes were infant peak weight velocity, BMI at adiposity peak and age at adiposity peak, and childhood BMI, total fat mass percentage, android/ gynoid fat ratio, and preperitoneal fat area. Analyses were performed using linear regression models. Results: A higher overall adult BMI risk score was associated with infant BMI at adiposity peak and childhood BMI, total fat mass, android/gynoid fat ratio, and preperitoneal fat area (all p-values < 0.05). Analyses focused on specific biological pathways showed that the membrane proteins genetic risk score was associated with infant peak weight velocity, and the genetic risk scores related to neuronal developmental processes, hypothalamic processes, cyclicAMP, WNT-signaling, membrane proteins, monogenic obesity and/or energy homeostasis, glucose homeostasis, cell cycle, and muscle biology pathways were associated with childhood adiposity measures (all p-values <0.05). None of the pathways were associated with childhood preperitoneal fat area. Conclusions: A genetic risk score based on 97 SNPs related to adult BMI was associated with peak weight velocity during infancy and general and abdominal fat measurements at the age of 6 years. Risk scores based on genetic variants linked to specific biological pathways, including central nervous system and hypothalamic processes, influence body fat development from early life onwards. [ABSTRACT FROM AUTHOR]

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

Author

Virpi Lindi, Clare S. Murray, Liming Liang, Wieland Kiess, Philippe Froguel, Tarunveer S. Ahluwalia, Hakon Hakonarson, Dorret I. Boomsma, Pitkänen Niina Pitkänen, Romy Gaillard, Mandy Geserick, John A. Curtin, Shana E. McCormack, Niinikoski Harri, Jens-Christian Holm, Vicente Gilsanz, Ville Huikari, Maties Torrent, Nicholas J. Timpson, George Dedoussis, Angela Simpson, Struan F.A. Grant, Klaus Bønnelykke, Anubha Mahajan, George McMahon, Raimo Joro, Christel M. Middeldorp, Johan G. Eriksson, Vilor-Tejedor Natalia Vilor-Tejedor, Gerard H. Koppelman, Frank Geller, Amélie Bonnefond, Hanna Maaria Lakka, Jinyan Huang, Craig E. Pennell, Johannes Waage, Jane Wardle, Torben Hansen, Olli T. Raitakari, John A. Shepherd, Lisbeth Carstensen, Andrea Kelly, Katja Pahkala, Jordi Sunyer, Claire M. A. Haworth, Per Magnus, Juan R. González, Babette S. Zemel, Mads Melbye, Steve Franks, Carla M. T. Tiesler, Roland Pfäffle, Momoko Horikoshi, Susan M. Ring, Adnan Custovic, Claudia Flexeder, Claire Monnereau, Heidi J. Kalkwarf, Janine F. Felix, Julie A. Marsh, Thorkild I. A. Sørensen, André G. Uitterlinden, Mustafa Atalay, Jouke-Jan Hottenga, Mark I. McCarthy, Joel N. Hirschhorn, Niels Grarup, Lude Franke, Diana L. Cousminer, Timo A. Lakka, Robert Plomin, Ronny Myhre, Albert Hofman, Baoshan Ma, Eskil Kreiner-Møller, Jesús Vioque, Vincent W. V. Jaddoe, Hans Bisgaard, Bjarke Feenstra, Sylvain Sebert, Evie Stergiakouli, Eleftheria Zeggini, Joachim Heinrich, Bo Jacobsson, Tune H. Pers, Dirkje S. Postma, Elina Hyppönen, Loic Yengo, Haja N. Kadarmideen, Alana Cavadino, Jonathan P. Bradfield, Elisabeth Thiering, Ralf J. P. van der Valk, George Davey Smith, Alexandra I. F. Blakemore, Christine Power, Marjo-Riitta Järvelin, Wei Ang, Ioanna Ntalla, Sharon E. Oberfield, Fernando Rivadeneira, Rebecca K. Vinding, Alexandra M. Lewin, Mika Kähönen, Verena Sengpiel, Maria M. Groen-Blokhuis, Anna-Liisa Hartikainen, Antje Körner, Oluf Pedersen, Joyce B. J. van Meurs, Alessandra Chesi, Widén Elisabeth Widén, Terho Lehtimäki, Thomas S. Price, Frank D. Mentch, Joan M. Lappe, Leo-Pekka Lyytikäinen, Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Groningen Research Institute for Asthma and COPD (GRIAC), Stem Cell Aging Leukemia and Lymphoma (SALL), Early Growth Genetics (EGG) Consortium, Bone Mineral Density in Childhood Study (BMDCS), Early Genetics and Lifecourse Epidemiology (EAGLE) consortium, Felix, Janine F, Bradfield, Jonathan P, Monnereau, Claire, van der Valk, Ralf JP, Hypponen, Elina, Jaddoe, Vincent WV, Biological Psychology, EMGO+ - Lifestyle, Overweight and Diabetes, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Erasmus MC other, Epidemiology, Pediatrics, Child and Adolescent Psychiatry / Psychology, Internal Medicine, and Public Health

Subjects
0301 basic medicine, Netherlands Twin Register (NTR), Male, ADAM23, Genome-wide association study, VARIANTS, ENVIRONMENTAL-FACTORS, Body Mass Index, Child, Genetics (clinical), 2. Zero hunger, Genetics, education.field_of_study, Association Studies Articles, General Medicine, INSIGHTS, Child, Preschool, Female, childhood obesity, EXPRESSION, Adult, Risk, Adolescent, Population, body mass index, Single-nucleotide polymorphism, Biology, ta3111, Polymorphism, Single Nucleotide, Childhood obesity, White People, 03 medical and health sciences, Young Adult, children, SDG 3 - Good Health and Well-being, medicine, Humans, Obesity, Allele, education, Molecular Biology, METAANALYSIS, Genetic association, FAT DISTRIBUTION, ta3121, medicine.disease, ta3123, GENE, 030104 developmental biology, Genetic Loci, WEIGHT, Body mass index, Genome-Wide Association Study
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. Refereed/Peer-reviewed

Published
2015
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