Article open access publication

Genome-wide associations for birth weight and correlations with adult disease

Nature, Springer Nature, ISSN 1476-4687

Volume 538, 7624, 2016

DOI:10.1038/nature19806, Dimensions: pub.1047510296, PMC: PMC5164934, PMID: 27680694,

Authors

Ahluwalia, Tarunveer S. (10) (14) (15)
Rueedi, Rico (16) (17)
Cousminer, Diana L (11) (19) (20)
Wu, Ying (21)
Vilor-Tejedor, Natalia (25) (26) (27)
Ntalla, Ioanna (30) (31)
Lagou, Vasiliki (1) (34) (35)
Bustamante, Mariona (25) (26) (27) (38)
Loh, Po-Ru (44) (45)
Tyrrell, Jessica (3) (46)
Prokopenko, Inga (1) (49)
Wang, Xu (29)
Murcia, M Antonia (27) (52)
Fonvig, Cilius E. (10) (53)
Trier, Caecilie (10) (53)
Tiesler, Carla M T (22) (23)
Kutalik, Zoltán (17) (54)
Torrents, David (40) (55)
Ring, Susan M. (47) (48)
Hemani, Gibran (47) (48)
Lakka, Timo A. (33) (57) (58)
Sørensen, Thorkild I A (10) (47) (48) (59)
Niinikoski, Harri (32) (60)
Pahkala, Katja (32) (61)
Raitakari, Olli T. (32) (60)
Saw, Seang-Mei (29) (62)
Melbye, Mads (8) (10) (63)
Vrijheid, Martine (25) (26) (27)
De Geus, Eco J C N (24) (64)
Sebert, Sylvain (49) (65)
Heinrich, Joachim (23) (66)
Eriksson, Johan G. (69) (70) (71)
Viikari, Jorma S A (32) (60)
Hyppönen, Elina (74) (75) (76)
Hakonarson, Hakon (11) (20)
Järvelin, Marjo-Riitta (49) (65) (77)
Grant, Struan F A (11) (20)
Vaag, Allan A. (10) (78) (79)
Lawlor, Debbie A. (47) (48)
Morris, Andrew P. (1) (80) (81)
Evans, David M (5) (47) (48)
McCarthy, Mark I. * (1) (2) (82)
Freathy, Rachel M * (3) (47)

* Corresponding author

Affiliations

Organisations

  1. (1) Wellcome Centre for Human Genetics, grid.270683.8
  2. (2) University of Oxford, grid.4991.5
  3. (3) Institute of Biomedical and Clinical Science, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, EX2 5DW, Exeter, UK
  4. (4) University of Cambridge, grid.5335.0
  5. (5) University of Queensland, grid.1003.2
  6. (6) University of Western Australia, grid.1012.2
  7. (7) Erasmus University Medical Center, grid.5645.2
  8. (8) State Serum Institute, grid.6203.7
  9. (9) University of California, San Diego, grid.266100.3
  10. (10) University of Copenhagen, grid.5254.6, KU
  11. (11) Children's Hospital of Philadelphia, grid.239552.a
  12. (12) St George's, University of London, grid.264200.2
  13. (13) Leiden University Medical Center, grid.10419.3d
  14. (14) Steno Diabetes Center, grid.419658.7, Capital Region
  15. (15) COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Gentofte, Copenhagen, 2820, Denmark
  16. (16) University of Lausanne, grid.9851.5
  17. (17) Swiss Institute of Bioinformatics, grid.419765.8
  18. (18) Tampere University, grid.502801.e
  19. (19) University of Helsinki, grid.7737.4
  20. (20) University of Pennsylvania, grid.25879.31
  21. (21) University of North Carolina at Chapel Hill, grid.10698.36
  22. (22) Klinikum der Universität München, grid.411095.8
  23. (23) Institute of Epidemiology I, Helmholtz Zentrum München- German Research Center for Environmental Health, 85764, Neuherberg, Germany
  24. (24) VU Amsterdam, grid.12380.38
  25. (25) ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), 08003, Barcelona, Spain
  26. (26) Pompeu Fabra University, grid.5612.0
  27. (27) Institute of Health Carlos III, grid.413448.e
  28. (28) University of Edinburgh, grid.4305.2
  29. (29) National University of Singapore, grid.4280.e
  30. (30) Queen Mary University of London, grid.4868.2
  31. (31) Harokopio University, grid.15823.3d
  32. (32) University of Turku, grid.1374.1
  33. (33) University of Eastern Finland, grid.9668.1
  34. (34) KU Leuven, grid.5596.f
  35. (35) Translational Immunology Laboratory, 3000, Leuven, VIB, Belgium
  36. (36) Northwestern University, grid.16753.36
  37. (37) University of Glasgow, grid.8756.c
  38. (38) Centre for Genomic Regulation, grid.11478.3b
  39. (39) University Hospital of Lausanne, grid.8515.9
  40. (40) Barcelona Supercomputing Center, grid.10097.3f
  41. (41) Queensland University of Technology, grid.1024.7
  42. (42) Chinese University of Hong Kong, grid.10784.3a
  43. (43) University of Michigan, grid.214458.e
  44. (44) Broad Institute, grid.66859.34
  45. (45) Harvard University, grid.38142.3c
  46. (46) University of Exeter, grid.8391.3
  47. (47) Medical Research Council, grid.14105.31
  48. (48) University of Bristol, grid.5337.2
  49. (49) Imperial College London, grid.7445.2
  50. (50) Leipzig University, grid.9647.c
  51. (51) Wellcome Sanger Institute, grid.10306.34
  52. (52) FISABIO–Universitat Jaume I–Universitat de València, Joint Research Unit of Epidemiology and Environmental Health, 46020, Valencia, Spain
  53. (53) Department of Pediatrics, The Children’s Obesity Clinic, Copenhagen University Hospital Holbæk, DK-4300, Holbæk, Denmark
  54. (54) Institute of Social and Preventive Medicine, grid.482968.9
  55. (55) Catalan Institution for Research and Advanced Studies, grid.425902.8
  56. (56) Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, 3015 CE, Rotterdamthe Netherlands
  57. (57) Kuopio University Hospital, grid.410705.7
  58. (58) Kuopion Liikuntalääketieteen Tutkimuslaitos, grid.419013.e
  59. (59) Institute of Preventive Medicine, Bispebjerg and Frederiksberg Hospital, DK-2000, The Capital Region, Copenhagen, Denmark
  60. (60) Turku University Hospital, grid.410552.7
  61. (61) Department of Physical Activity and Health, Paavo Nurmi Centre, Sports and Exercise Medicine Unit, 20014, Turku, Finland
  62. (62) Singapore Eye Research Institute, grid.272555.2
  63. (63) Stanford University, grid.168010.e
  64. (64) EMGO Institute for Health and Care Research, grid.466632.3
  65. (65) University of Oulu, grid.10858.34
  66. (66) Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, Inner City Clinic, University Hospital Munich, Ludwig Maximilian University of Munich, 80336, Munich, Germany
  67. (67) University of North Carolina System, grid.410711.2
  68. (68) University of San Carlos, grid.267101.3
  69. (69) Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, 00014, Helsinki, Finland
  70. (70) Folkhälsans Forskningscentrum, grid.428673.c
  71. (71) National Institute for Health and Welfare, grid.14758.3f
  72. (72) King Faisal Specialist Hospital & Research Centre, grid.415310.2
  73. (73) Research Center for Prevention and Health Capital Region, Center for Sundhed, Rigshospitalet – Glostrup, Copenhagen University, DK-2600, Glostrup, Denmark
  74. (74) University College London, grid.83440.3b
  75. (75) South Australian Health and Medical Research Institute, grid.430453.5
  76. (76) University of South Australia, grid.1026.5
  77. (77) Oulu University Hospital, grid.412326.0
  78. (78) AstraZeneca (Sweden), grid.418151.8
  79. (79) Rigshospitalet, grid.475435.4, Capital Region
  80. (80) University of Liverpool, grid.10025.36
  81. (81) University of Tartu, grid.10939.32
  82. (82) Churchill Hospital, grid.415719.f

Description

Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P < 5 × 10-8). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (Rg = -0.22, P = 5.5 × 10-13), T2D (Rg = -0.27, P = 1.1 × 10-6) and coronary artery disease (Rg = -0.30, P = 6.5 × 10-9). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions (P = 1.9 × 10-4). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated.

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University of Copenhagen

Danish Open Access Indicator

2016: Unused

Research area: Medicine

Danish Bibliometrics Indicator

2016: Level 2

Research area: Medicine

Dimensions Citation Indicators

Times Cited: 211

Field Citation Ratio (FCR): 35.41

Relative Citation ratio (RCR): 11.6

Open Access Info

Green, Accepted