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      Genome-wide association study of offspring birth weight in 86 577 women identifies five novel loci and highlights maternal genetic effects that are independent of fetal genetics

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      1 , 2 , 3 , 1 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 10 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 28 , 33 , 23 , 34 , 35 , 33 , Early Growth Genetics (EGG) Consortium, 13 , 36 , 37 , 38 , 39 , 39 , 41 , 42 , 43 , 44 , 24 , 45 , 1 , 25 , 26 , 27 , 20 , 46 , 20 , 1 , 47 , 39 , 40 , 48 , 43 , 49 , 10 , 11 , 1 , 27 , 50 , 51 , 5 , 16 , 52 , 53 , 1 , 39 , 1 , 21 , 22 , 1 , 1 , 31 , 32 , 21 , 22 , 10 , 11 , 29 , 28 , 54 , 25 , 27 , 55 , 21 , 22 , 20 , 19 , 56 , 17 , 33 , 16 , 52 , 57 , 58 , 59 , 14 , 15 , 13 , 36 , 37 , 10 , 60 , 61 , 12 , 44 , 62 , 9 , 53 ,   8 , 63 , 6 , 7 , 64 , 1 , 65 , 1 , 66 , 67 , 68 , 12 , 44 , 62 , 33 , 69 , 70 , 65 , 2 , 10 , 11 , 10 , 11 , 8 , 1 , 10
      Human Molecular Genetics
      Oxford University Press

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          Abstract

          Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother–child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci ( MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P < 5 × 10 −8. In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose ( MTNR1B, GCK and TCF7L2) and sex hormone levels ( CYP3A7), and one ( EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.

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          Most cited references44

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          Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis.

          By combining genome-wide association data from 8,130 individuals with type 2 diabetes (T2D) and 38,987 controls of European descent and following up previously unidentified meta-analysis signals in a further 34,412 cases and 59,925 controls, we identified 12 new T2D association signals with combined P<5x10(-8). These include a second independent signal at the KCNQ1 locus; the first report, to our knowledge, of an X-chromosomal association (near DUSP9); and a further instance of overlap between loci implicated in monogenic and multifactorial forms of diabetes (at HNF1A). The identified loci affect both beta-cell function and insulin action, and, overall, T2D association signals show evidence of enrichment for genes involved in cell cycle regulation. We also show that a high proportion of T2D susceptibility loci harbor independent association signals influencing apparently unrelated complex traits.
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            Fetal and infant growth and impaired glucose tolerance at age 64.

            To discover whether reduced fetal and infant growth is associated with non-insulin dependent diabetes and impaired glucose tolerance in adult life. Follow up study of men born during 1920-30 whose birth weights and weights at 1 year were known. Hertfordshire, England. 468 men born in east Hertfordshire and still living there. Fasting plasma glucose, insulin, proinsulin, and 32-33 split pro-insulin concentrations and plasma glucose and insulin concentrations 30 and 120 minutes after a 75 g glucose drink. 93 men had impaired glucose tolerance or hitherto undiagnosed diabetes. They had had a lower mean birth weight and a lower weight at 1 year. The proportion of men with impaired glucose tolerance fell progressively from 26% (6/23) among those who had weighted 18 lb (8.16 kg) or less at 1 year to 13% (3/24) among those who had weighed 27 lb (12.25 kg) or more. Corresponding figures for diabetes were 17% (4/23) and nil (0/24). Plasma glucose concentrations at 30 and 120 minutes fell with increasing birth weight and weight at 1 year. Plasma 32-33 split proinsulin concentration fell with increasing weight at 1 year. All these trends were significant and independent of current body mass. Blood pressure was inversely related to birth weight and strongly related to plasma glucose and 32-33 split proinsulin concentrations. Reduced growth in early life is strongly linked with impaired glucose tolerance and non-insulin dependent diabetes. Reduced early growth is also related to a raised plasma concentration of 32-33 split proinsulin, which is interpreted as a sign of beta cell dysfunction. Reduced intrauterine growth is linked with high blood pressure, which may explain the association between hypertension and impaired glucose tolerance.
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              Variants in MTNR1B influence fasting glucose levels.

              To identify previously unknown genetic loci associated with fasting glucose concentrations, we examined the leading association signals in ten genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95% CI = 0.06-0.08) mmol/l in fasting glucose levels (P = 3.2 x 10(-50)) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P = 1.1 x 10(-15)). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05-1.12), per G allele P = 3.3 x 10(-7)) in a meta-analysis of 13 case-control studies totaling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P = 1.1 x 10(-57)) and GCK (rs4607517, P = 1.0 x 10(-25)) loci.
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                Author and article information

                Journal
                Hum Mol Genet
                Hum. Mol. Genet
                hmg
                Human Molecular Genetics
                Oxford University Press
                0964-6906
                1460-2083
                15 February 2018
                03 January 2018
                03 January 2018
                : 27
                : 4
                : 742-756
                Affiliations
                [1 ]Institute of Biomedical and Clinical Science, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Exeter EX2 5DW, UK,
                [2 ]Translational Research Institute, University of Queensland Diamantina Institute, Brisbane, QLD, Australia,
                [3 ]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, London, UK,
                [4 ]European Centre for Environment and Human Health, University of Exeter, The Knowledge Spa, Truro TR1 3HD, UK,
                [5 ]Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA,
                [6 ]Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK,
                [7 ]Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK,
                [8 ]Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark,
                [9 ]Division of Epidemiology, Department of Genes and Environment, Norwegian Institute of Public Health, Oslo, Norway,
                [10 ]Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK,
                [11 ]Population Health Science, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK,
                [12 ]The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands,
                [13 ]Center for Applied Genomics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA,
                [14 ]Copenhagen Prospective Studies on Asthma in Childhood (COPSAC), Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark,
                [15 ]Danish Pediatric Asthma Center, Copenhagen University Hospital, Gentofte, Denmark
                [16 ]Institute of Health Sciences, University of Oulu, Oulu, Finland,
                [17 ]Department of Twin Research, King's College London, St. Thomas' Hospital, London, UK,
                [18 ]Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA,
                [19 ]Framingham Heart Study, Framingham, MA, USA,
                [20 ]QIMR Berghofer Medical Research Institute, Royal Brisbane Hospital, Herston, QLD 4029, Australia,
                [21 ]EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands,
                [22 ]Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 BT Amsterdam, The Netherlands,
                [23 ]Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC, Canada,
                [24 ]Medical Research Council Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK,
                [25 ]Pompeu Fabra University (UPF), Barcelona, Spain,
                [26 ]IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain,
                [27 ]ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain,
                [28 ]Division of Obstetrics and Gynaecology, The University of Western Australia, Perth, Australia,
                [29 ]Institute of Genetic Medicine, Newcastle University, Central Parkway, Newcastle upon Tyne NE1 3BZ, UK,
                [30 ]Human Genetics Division, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA,
                [31 ]Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center, OH, USA,
                [32 ]March of Dimes Prematurity Research Center Ohio Collaborative, Cincinnati, OH, USA,
                [33 ]Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, University College London, London, UK,
                [34 ]ECOGENE-21 and Lipid Clinic, Chicoutimi Hospital, Saguenay, QC, Canada,
                [35 ]Department of Biochemistry, Université de Sherbrooke, Sherbrooke, QC, Canada,
                [36 ]Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA,
                [37 ]Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA,
                [38 ]FIMM Institute for Molecular Medicine Finland, Helsinki University, Helsinki FI-00014, Finland,
                [39 ]Department of Clinical Science, KG Jebsen Center for Diabetes Research, University of Bergen, Bergen, Norway,
                [40 ]Department of Pediatrics, Haukeland University Hospital, Bergen 5021, Norway,
                [41 ]Department of Genetics and Bioinformatics, Domain of Health Data and Digitalisation, Institute of Public Health, Oslo, Norway,
                [42 ]The First Affiliated Hospital of Jinan University, Guangzhou 510630, China,
                [43 ]Institute of Nutritional Science, University of Potsdam, Potsdam, Germany,
                [44 ]Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands,
                [45 ]NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK,
                [46 ]Genetic Section, Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy,
                [47 ]Department of Pediatrics, University of Iowa, Iowa City, IA, USA,
                [48 ]Research Unit of Obstetrics & Gynecology, Institute of Clinical Research, University of Southern Denmark, Odense, Denmark,
                [49 ]Center for Cardiovascular Research, Charité, Berlin, Germany,
                [50 ]Subdirección de Salud Pública y Adicciones de Gipuzkoa, Donostia/San Sebastián, Spain,
                [51 ]Instituto de Investigación Sanitaria BIODONOSTIA, Donostia/San Sebastián, Spain,
                [52 ]Department of Epidemiology and Biostatistics, School of Public Health, Medical Research Council-Health Protection Agency Centre for Environment and Health, Faculty of Medicine, Imperial College London, London, UK,
                [53 ]Department of Obstetrics and Gynecology, Sahlgrenska Academy, Sahgrenska University Hospital, Gothenburg, Sweden,
                [54 ]Department of Social Medicine, University of Crete, Crete, Greece,
                [55 ]Human Development & Health, Faculty of Medicine, University of Southampton, Southampton, UK,
                [56 ]Section of General Internal Medicine, Boston University School of Medicine, Boston, MA, USA,
                [57 ]Biocenter Oulu, University of Oulu, Oulu, Finland,
                [58 ]Unit of Primary Care, Oulu University Hospital, FI-90220 Oulu, 90029 OYS, Finland,
                [59 ]Department of Children and Young People and Families, National Institute for Health and Welfare, FI-90101 Oulu, Finland,
                [60 ]Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark,
                [61 ]Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark,
                [62 ]Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands,
                [63 ]Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA,
                [64 ]Oxford National Institute for Health Research (NIHR) Biomedical Research Centre, Churchill Hospital, Oxford, UK,
                [65 ]Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA,
                [66 ]Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, USA,
                [67 ]Diabetes Center, Massachussetts General Hospital, Boston, MA, USA,
                [68 ]Department of Medicine, Universite de Sherbrooke, QC, Canada,
                [69 ]Centre for School of Population Health Research, School of Health Sciences, and Sansom Institute, University of South Australia, Adelaide, Australia
                [70 ]South Australian Health and Medical Research Institute, Adelaide, Australia
                Author notes

                Robin N. Beaumont and Nicole M. Warrington contributed equally to this work.

                David M. Evans, Debbie A. Lawlor, Bjarke Feenstra and Rachel M. Freathy jointly directed this work.

                A full list of consortium members is included in the Supplementary Material.

                To whom correspondence should be addressed at: University of Exeter Medical School, RILD Building Royal Devon and Exeter Hospital, Barrack Road, Exeter EX2 5DW, UK. Tel: +44 1392408238; Email: r.freathy@ 123456ex.ac.uk (R.M.F.); Department of Epidemiology Research, Statens Serum Institut, Artillerivej 5, DK-2300 Copenhagen S, Denmark. Tel: +45 32683852; Email: fee@ 123456ssi.dk (B.F.); MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Road, Bristol BS8 2BN, UK. Tel: +44 1173310096; Email: d.a.lawlor@ 123456bristol.ac.uk (D.A.L.); The University of Queensland Diamantina Institute, Brisbane, QLD, Australia. Tel: +61 734437051; Email: d.evans1@ 123456uq.edu.au (D.M.E.)
                Author information
                http://orcid.org/0000-0003-4152-2238
                Article
                ddx429
                10.1093/hmg/ddx429
                5886200
                29309628
                cc9f7361-d6d0-4e88-8ef7-8e93f58bc400
                © The Author(s) 2018. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 02 November 2017
                : 12 December 2017
                : 15 December 2017
                Page count
                Pages: 15
                Funding
                Funded by: European Research Council 10.13039/100010663
                Award ID: SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC
                Award ID: ERC-2014-CoG-648916
                Funded by: Wellcome Trust 10.13039/100004440
                Award ID: WT098395
                Award ID: WT098381
                Funded by: National Institute for Health Research 10.13039/501100000272
                Award ID: NF-SI-0611–10219
                Funded by: Wellcome Trust 10.13039/100004440
                Award ID: WT104150
                Award ID: WT083431MF
                Funded by: Wellcome Trust 10.13039/100004440
                Award ID: WT088806
                Funded by: NIHR 10.13039/100006662
                Award ID: NF-SI-0611–10196
                Funded by: Wellcome Trust 10.13039/100004440
                Award ID: WT097835MF
                Funded by: Medical Research Council 10.13039/501100000265
                Award ID: MR/M005070/1
                Funded by: National Institute on Aging 10.13039/100000049
                Award ID: R01AG29451
                Categories
                Association Studies Articles

                Genetics
                Genetics

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