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

Nature

Volumn 538, Issue 7624, 2016, Pages 248-252

  Horikoshi, Momoko ^a,b   Beaumont, Robin N ^c   Day, Felix R ^d   Warrington, Nicole M ^e,f   Kooijman, Marjolein N ^g   Fernandez Tajes, Juan ^a   Feenstra, Bjarke ^h   Van Zuydam, Natalie R ^a,b   Gaulton, Kyle J ^a,i   Grarup, Niels ^j   Bradfield, Jonathan P ^k   Strachan, David P ^l   Li Gao, Ruifang ^m   Ahluwalia, Tarunveer S ^j,n,o   Kreiner, Eskil ⁿ   Rueedi, Rico ^p,q   Lyytikaïnen, Leo Pekka ^r,s   Cousminer, Diana L ^k,t,u   Wu, Ying ^v   Thiering, Elisabeth ^w,x   Wang, Carol A ^f   Have, Christian T ^j   Hottenga, Jouke Jan ^y   Vilor Tejedor, Natalia ^z,aa,ab   Joshi, Peter K ^ac   Boh, Eileen Tai Hui ^ad   Ntalla, Ioanna ^ae,af   Pitkänen, Niina ^ag   Mahajan, Anubha ^a   Van Leeuwen, Elisabeth M ^g   Joro, Raimo ^ah   Lagou, Vasiliki ^a,ai,aj   Nodzenski, Michael ^ak   Diver, Louise A ^al   Zondervan, Krina T ^a,b   Bustamante, Mariona ^z,aa,ab,am   Marques Vidal, Pedro ^p   Mercader, Josep M ^an   Bennett, Amanda J ^b   Rahmioglu, Nilufer ^a   Nyholt, Dale R ^ao   Ma, Ronald C W ^ap   Tam, Claudia H T ^ap   Tam, Wing Hung ^aq   Ganesh, Santhi K ^g   Van Rooij, Frank J A ^c   Jones, Samuel E ^ar,as   Loh, Po Ru ^c   Ruth, Katherine S ^c   Tuke, Marcus A ^c,at   Tyrrell, Jessica ^c,at   Wood, Andrew R ^c   Yaghootkar, Hanieh ^c   Scholtens, Denise M ^ak   Paternoster, Lavinia ^au   Prokopenko, Inga ^a,av   Kovacs, Peter ^aw   Atalay, Mustafa ^ah   Willems, Sara M ^g   Panoutsopoulou, Kalliope ^ax   Wang, Xu ^ad   Carstensen, Lisbeth ^h   Geller, Frank ^h   Schraut, Katharina E ^ac   Murcia, Mario ^ab,ay   Van Beijsterveldt, Catharina E M ^y   Willemsen, Gonneke ^y   Appel, Emil V R ^j   Fonvig, Cilius E ^j,n   Trier, Caecilie ^j,n   Tiesler, Carla M T ^w,x   Standl, Marie ^w   Kutalik, Zoltán ^q,az   Bonàs Guarch, Sílvia ^an   Hougaard, David M ^h   Sánchez, Friman ^an,ba,bb   Torrents, David ^an,ba   Waage, Johannes ⁿ   Hollegaard, Mads V ^h   De Haan, Hugoline G ^m   Rosendaal, Frits R ^m   Medina Gomez, Carolina ^g   Ring, Susan M ^au   Hemani, Gibran ^au   McMahon, George ^au   Robertson, Neil R ^a,b   Groves, Christopher J ^b   Langenberg, Claudia ^d   Luan, Jian'An ^d   Scott, Robert A ^d   Zhao, Jing Hua ^d   Mentch, Frank D ^k   MacKenzie, Scott M ^al   Reynolds, Rebecca M ^ak   Lowe, William L ^aw   Tönjes, Anke ^aw   Stumvoll, Michael ^ah   Lindi, Virpi ^ah   Lakka, Timo A ^ah   Van Duijn, Cornelia M ^g   Kiess, Wieland ^aw   Körner, Antje ^aw   Sørensen, Thorkild I A ^j,au,bc   Niinikoski, Harri ^bd,be   Pahkala, Katja ^ag,bf   Raitakari, Olli T ^ag,bg   Zeggini, Eleftheria ^ax   Dedoussis, George V ^af   Teo, Yik Ying ^ad,bh   Saw, Seang Mei ^ad,bi   Melbye, Mads ^h,n,bj   Campbell, Harry ^ac   Wilson, James F ^ac,bk   Vrijheid, Martine ^z,aa,ab   De Geus, Eco J C N ^y,bl   Boomsma, Dorret I ^y   Kadarmideen, Haja N ^bm   Holm, Jens Christian ^j,n   Hansen, Torben ^j   Sebert, Sylvain ^av,bn,bo   Hattersley, Andrew T ^c   Beilin, Lawrence J ^bp   Newnham, John P ^f   Pennell, Craig E ^f   Heinrich, Joachim ^w,x   Adair, Linda S ^bq   Borja, Judith B ^br   Mohlke, Karen L ^v   Eriksson, Johan G ^t,bs,bt   Widén, Elisabeth ^t   Kähönen, Mika ^s,bu   Viikari, Jorma S ^bd,be   Lehtimäki, Terho ^r,s   Vollenweider, Peter ^p   Bønnelykke, Klaus ⁿ   Bisgaard, Hans ⁿ   Mook Kanamori, Dennis O ^m,bv   Hofman, Albert ^g   Rivadeneira, Fernando ^g   Uitterlinden, André G ^g   Pisinger, Charlotta ⁿ   Pedersen, Oluf ^j   Power, Christine ^bw   Hyppönen, Elina ^bw,bx,by   Wareham, Nicholas J ^d   Hakonarson, Hakon ^k,u   Davies, Eleanor ^al   Walker, Brian R ^ac   Jaddoe, Vincent W V ^g   Järvelin, Marjo Riitta ^av,bn,bo,bz   Grant, Struan F A ^k,u   Vaag, Allan A ^n,ca,cb   Lawlor, Debbie A ^au   Frayling, Timothy M ^c   Smith, George Davey ^au   Morris, Andrew P ^a,cc,cd   Ong, Ken K ^d,ce   Felix, Janine F ^g   Timpson, Nicholas J ^au   Perry, John R B ^d   Evans, David M ^e,au   McCarthy, Mark I ^a,b,cf   Freathy, Rachel M ^c,au   more..

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b UNIVERSITY OF OXFORD   (United Kingdom)

^c UNIVERSITY OF EXETER   (United Kingdom)

^d UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^e UNIVERSITY OF QUEENSLAND   (Australia)

^f UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

^g ERASMUS MEDICAL CENTER   (Netherlands)

^h STATENS SERUM INSTITUT   (Denmark)

ⁱ UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

^j Capital Region   (Denmark)

^k CHILDREN S HOSPITAL OF PHILADELPHIA   (United States)

^l ST GEORGE'S UNIVERSITY OF LONDON   (United Kingdom)

^m LEIDEN UNIVERSITY MEDICAL CENTER   (Netherlands)

ⁿ UNIVERSITY OF COPENHAGEN   (Denmark)

^o STENO DIABETES CENTER   (Denmark)

^p UNIVERSITY OF LAUSANNE   (Switzerland)

^q SWISS INSTITUTE OF BIOINFORMATICS   (Switzerland)

^r FIMLAB LABORATORIES   (Finland)

^s TAMPERE UNIVERSITY OF TECHNOLOGY   (Finland)

^t UNIVERSITY OF HELSINKI   (Finland)

^u UNIVERSITY OF PENNSYLVANIA   (United States)

^v UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

^w INSTITUTE OF EPIDEMIOLOGY   (Germany)

^x LUDWIG MAXIMILIANS UNIVERSITY   (Germany)

^y VU UNIVERSITY AMSTERDAM   (Netherlands)

^z CENTRE FOR RESEARCH IN ENVIRONMENTAL EPIDEMIOLOGY CREAL   (Spain)

^aa UNIVERSITAT POMPEU FABRA   (Spain)

^ab CIBER EPIDEMIOLOGÍA Y SALUD PÚBLICA CIBERESP   (Spain)

^ac UNIVERSITY OF EDINBURGH   (United Kingdom)

^ad NATIONAL UNIVERSITY HEALTH SYSTEM   (Singapore)

^ae QUEEN MARY UNIVERSITY OF LONDON   (United Kingdom)

^af HAROKOPIO UNIVERSITY   (Greece)

^ag UNIVERSITY OF TURKU   (Finland)

^ah UNIVERSITY OF EASTERN FINLAND   (Finland)

^ai KU LEUVEN UNIVERSITY OF LEUVEN   (Belgium)

^aj DEPARTMENT OF PLANT SYSTEMS BIOLOGY   (Belgium)

^ak NORTHWESTERN UNIVERSITY   (United States)

^al UNIVERSITY OF GLASGOW   (United Kingdom)

^am CENTRE FOR GENOMIC REGULATION CRG   (Spain)

^an INSTITUTE FOR RESEARCH IN BIOMEDICINE   (Spain)

^ao QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

^ap CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

^aq UNIVERSITY OF MICHIGAN MEDICAL SCHOOL   (United States)

^ar HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^as BROAD INSTITUTE OF MIT AND HARVARD   (United States)

^at UNIVERSITY OF EXETER MEDICAL SCHOOL   (United Kingdom)

^au UNIVERSITY OF BRISTOL   (United Kingdom)

^av Faculty of Medicine   (United Kingdom)

^aw UNIVERSITY OF LEIPZIG   (Germany)

^ax WELLCOME TRUST SANGER INSTITUTE   (United Kingdom)

^ay UNIVERSITY OF VALENCIA   (Spain)

^az UNIVERSITY OF LAUSANNE   (Switzerland)

^ba BARCELONA SUPERCOMPUTING CENTER   (Spain)

^bb INSTITUCIÓ CATALANA DE RECERCA I ESTUDIS AVANÇATS ICREA   (Spain)

^bc The Capital Region   (Denmark)

^bd TURKU UNIVERSITY HOSPITAL   (Finland)

^be UNIVERSITY OF TURKU   (Finland)

^bf Paavo Nurmi Centre   (Finland)

^bg Turku University   (Finland)

^bh NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^bi SINGAPORE EYE RESEARCH INSTITUTE   (Singapore)

^bj STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^bk UNIVERSITY OF EDINBURGH   (United Kingdom)

^bl VU UNIVERSITY MEDICAL CENTER   (Netherlands)

^bm UNIVERSITY OF COPENHAGEN   (Denmark)

^bn UNIVERSITY OF OULU   (Finland)

^bo UNIVERSITY OF OULU   (Finland)

^bp UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

^bq IL   (United States)

^br UNIVERSITY OF SAN CARLOS   (Philippines)

^bs NATIONAL PUBLIC HEALTH INSTITUTE   (Finland)

^bt FOLKHÄLSAN RESEARCH CENTER   (Finland)

^bu TAMPERE UNIVERSITY HOSPITAL   (Finland)

^bv KING FAISAL SPECIALIST HOSPITAL AND RESEARCH CENTER   (Saudi Arabia)

^bw UNIVERSITY COLLEGE LONDON   (United Kingdom)

^bx UNIVERSITY OF SOUTH AUSTRALIA   (Australia)

^by DEPARTMENT OF HUMAN SERVICES   (Australia)

^bz OULU UNIVERSITY HOSPITAL   (Finland)

^ca Rigshospitalet   (Denmark)

^cb ASTRAZENECA R AND D   (Sweden)

^cc UNIVERSITY OF LIVERPOOL   (United Kingdom)

^cd UNIVERSITY OF TARTU   (Estonia)

^ce UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^cf NIHR OXFORD BIOMEDICAL RESEARCH CENTRE   (United Kingdom)

more..

Author keywords

[No Author keywords available]

Indexed keywords

HIGH MOBILITY GROUP A1A PROTEIN; PROTEIN KINASE FES; PROTEIN PATCHED 1; RECEPTOR INTERACTING PROTEIN 140; GLUCOSE; GLYCOGEN; INSULIN;

BLOOD; CARDIOVASCULAR DISEASE; CORRELATION; DATA SET; DIABETES; GENETIC ANALYSIS; GENOME; HOMEOSTASIS; MATERNAL EFFECT; META-ANALYSIS; METABOLISM; PHENOTYPE; PROTEIN; WEIGHT;

ADCY5 GENE; ADRB1 GENE; ADULT; ADULT DISEASE; ANCESTRY GROUP; ANK1 GENE; ARTICLE; BIRTH LENGTH; BIRTH WEIGHT; BODY HEIGHT; BODY MASS; CARDIOMETABOLIC RISK; CDKAL1 GENE; CORONARY ARTERY DISEASE; EBF1 GENE; FES GENE; GENE; GENE LINKAGE DISEQUILIBRIUM; GENE LOCUS; GENETIC ASSOCIATION; GENETIC RISK; GENETIC VARIATION; GENOTYPE; GLUCOSE HOMEOSTASIS; GLYCOGEN SYNTHESIS; GNA12 GENE; HEREDITY; HHEX IDE GENE; HHIP GENE; HIGH RISK POPULATION; HMGA1 GENE; HUMAN; INTRACELLULAR SIGNALING; NON INSULIN DEPENDENT DIABETES MELLITUS; NRIP1 GENE; NT5C2 GENE; PARAMETERS CONCERNING THE FETUS, NEWBORN AND PREGNANCY; PHENOTYPE; PRIORITY JOURNAL; PTCH1 GENE; PTH1R GENE; RISK ASSESSMENT; SINGLE NUCLEOTIDE POLYMORPHISM; SYSTOLIC BLOOD PRESSURE; WAIST CIRCUMFERENCE; ZBTB7B GENE; AGING; ANTHROPOMETRY; BIOSYNTHESIS; BLOOD PRESSURE; CHROMATIN ASSEMBLY AND DISASSEMBLY; COHORT ANALYSIS; FEMALE; FETUS; GENETIC PREDISPOSITION; GENETICS; GENOME IMPRINTING; GENOME-WIDE ASSOCIATION STUDY; INFORMATION PROCESSING; MALE; META ANALYSIS; METABOLISM; SIGNAL TRANSDUCTION;

ADULT; AGING; ANTHROPOMETRY; BIRTH WEIGHT; BLOOD PRESSURE; CHROMATIN ASSEMBLY AND DISASSEMBLY; COHORT STUDIES; CORONARY ARTERY DISEASE; DATASETS AS TOPIC; DIABETES MELLITUS, TYPE 2; FEMALE; FETUS; GENETIC LOCI; GENETIC PREDISPOSITION TO DISEASE; GENETIC VARIATION; GENOME-WIDE ASSOCIATION STUDY; GENOMIC IMPRINTING; GENOTYPE; GLUCOSE; GLYCOGEN; HUMANS; INSULIN; MALE; PHENOTYPE; SIGNAL TRANSDUCTION;

EID: 84991665514     PISSN: 00280836     EISSN: 14764687     Source Type: Journal    
DOI: 10.1038/nature19806     Document Type: Article

References (82)

1. Barker, D. J. The developmental origins of chronic adult disease. Acta Paediatr. Suppl. 93, 26-33 (2004).
2. The 1000 Genomes Project Consortium An integrated map of genetic variation from 1, 092 human genomes. Nature 491, 56-65 (2012).
3. The UK10K Project Consortium The UK10K project identifies rare variants in health and disease. Nature 526, 82-90 (2015).
4. Tyrrell, J. S., Yaghootkar, H., Freathy, R. M., Hattersley, A. T., Frayling, T. M. Parental diabetes and birthweight in 236, 030 individuals in the UK Biobank study. Int. J. Epidemiol. 42, 1714-1723 (2013).
5. Horikoshi, M. et al. New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism. Nat. Genet. 45, 76-82 (2013).
6. Eaves, L. J., Pourcain, B. S., Smith, G. D., York, T. P., Evans, D. M. Resolving the effects of maternal and offspring genotype on dyadic outcomes in genome wide complex trait analysis ("M-GCTA"). Behav. Genet. 44, 445-455 (2014).
7. Feenstra, B., et al. Maternal genome-wide association study identifies a fasting glucose variant associated with offspring birth weight. Preprint at: http://biorxiv. org/content/early/2015/12/11/034207 (2015).
8. Bulik-Sullivan, B. K. et al. LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291-295 (2015).
9. Segrè, A. V. et al. Common inherited variation in mitochondrial genes is not enriched for associations with type 2 diabetes or related glycemic traits. PLoS Genet. 6, e1001058 (2010).
10. Baran, Y. et al. The landscape of genomic imprinting across diverse adult human tissues. Genome Res. 25, 927-936 (2015).
11. Haig, D., Westoby, M. Parent-specific gene expression and the triploid endosperm. Am. Nat. 134, 147-155 (1989).
12. Peters, J. The role of genomic imprinting in biology and disease: an expanding view. Nat. Rev. Genet. 15, 517-530 (2014).
13. Johnson, T. et al. Blood pressure loci identified with a gene-centric array. Am. J. Hum. Genet. 89, 688-700 (2011).
14. International Consortium for Blood Pressure Genome-Wide Association Studies et al. Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk. Nature 478, 103-109 (2011).
15. Zhang, G. et al. Assessing the causal relationship of maternal height on birth size and gestational age at birth: a Mendelian randomization analysis. PLoS Med. 12, e1001865 (2015).
16. Tyrrell, J. et al. Genetic evidence for causal relationships between maternal obesityrelated traits and birth weight. J. Am. Med. Assoc. 315, 1129-1140 (2016).
17. Locke, A. E. et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 518, 197-206 (2015).
18. Diver, L. A. et al. Common polymorphisms at the CYP17A1 locus associate with steroid phenotype: support for blood pressure genome-wide association study signals at this locus. Hypertension 67, 724-732 (2016).
19. Picado-Leonard, J., Miller, W. L. Cloning and sequence of the human gene for P450c17 (steroid 17 alpha-hydroxylase/17, 20 lyase): similarity with the gene for P450c21. DNA 6, 439-448 (1987).
20. Pezzi, V., Mathis, J. M., Rainey, W. E., Carr, B. R. Profiling transcript levels for steroidogenic enzymes in fetal tissues. J. Steroid Biochem. Mol. Biol. 87, 181-189 (2003).
21. Escobar, J. C., Patel, S. S., Beshay, V. E., Suzuki, T., Carr, B. R. The human placenta expresses CYP17 and generates androgens de novo. J. Clin. Endocrinol. Metab. 96, 1385-1392 (2011).
22. Reynolds, R. M. et al. Programming of hypertension: associations of plasma aldosterone in adult men and women with birthweight, cortisol, and blood pressure. Hypertension 53, 932-936 (2009).
23. CARDIoGRAMplusC4D Consortium et al. Large-scale association analysis identifies new risk loci for coronary artery disease. Nat Genet. 45, 25-33 (2013).
24. DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium et al. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility. Nat. Genet. 46, 234-244 (2014).
25. Wood, A. R. et al. Defining the role of common variation in the genomic and biological architecture of adult human height. Nat. Genet. 46, 1173-1186 (2014).
26. Hattersley, A. T., Tooke, J. E. The fetal insulin hypothesis: an alternative explanation of the association of low birth weight with diabetes and vascular disease. Lancet 353, 1789-1792 (1999).
27. Dimas, A. S. et al. Impact of type 2 diabetes susceptibility variants on quantitative glycemic traits reveals mechanistic heterogeneity. Diabetes 63, 2158-2171 (2014).
28. Morris, A. P. et al. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat. Genet. 44, 981-990 (2012).
29. Hattersley, A. T. et al. Mutations in the glucokinase gene of the fetus result in reduced birth weight. Nat. Genet. 19, 268-270 (1998).
30. Marchini, J., Howie, B. Genotype imputation for genome-wide association studies. Nat. Rev. Genet. 11, 499-511 (2010).
31. Howie, B., Fuchsberger, C., Stephens, M., Marchini, J., Abecasis, G. R. Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nat. Genet. 44, 955-959 (2012).
32. Winkler, T. W. et al. Quality control and conduct of genome-wide association meta-analyses. Nat. Protoc. 9, 1192-1212 (2014).
33. Price, A. L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904-909 (2006).
34. Devlin, B., Roeder, K. Genomic control for association studies. Biometrics 55, 997-1004 (1999).
35. Kang, H. M. et al. Variance component model to account for sample structure in genome-wide association studies. Nat. Genet. 42, 348-354 (2010).
36. Allen, N. E., Sudlow, C., Peakman, T., Collins, R. UK Biobank data: come and get it. Sci. Transl. Med. 6, 224ed4 (2014).
37. Loh, P. R. et al. Efficient Bayesian mixed-model analysis increases association power in large cohorts. Nat. Genet. 47, 284-290 (2015).
38. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559-575 (2007).
39. Mägi, R., Morris, A. P. GWAMA: software for genome-wide association meta-analysis. BMC Bioinformatics 11, 288 (2010).
40. Willer, C. J., Li, Y., Abecasis, G. R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190-2191 (2010).
41. Ioannidis, J. P., Patsopoulos, N. A., Evangelou, E. Heterogeneity in metaanalyses of genome-wide association investigations. PLoS One 2, e841 (2007).
42. Yang, J. et al. Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nat. Genet. 44, 369-375, S1-S3 (2012).
43. GTEx Consortium. Human genomics. The genotype-tissue expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348, 648-660 (2015).
44. Lappalainen, T. et al. Transcriptome and genome sequencing uncovers functional variation in humans. Nature 501, 506-511 (2013).
45. Montgomery, S. B. et al. Transcriptome genetics using second generation sequencing in a Caucasian population. Nature 464, 773-777 (2010).
46. Schadt, E. E. et al. Mapping the genetic architecture of gene expression in human liver. PLoS Biol. 6, e107 (2008).
47. Gibbs, J. R. et al. Abundant quantitative trait loci exist for DNA methylation and gene expression in human brain. PLoS Genet. 6, e1000952 (2010).
48. Stranger, B. E. et al. Population genomics of human gene expression. Nat. Genet. 39, 1217-1224 (2007).
49. Li, Q. et al. Expression QTL-based analyses reveal candidate causal genes and loci across five tumor types. Hum. Mol. Genet. 23, 5294-5302 (2014).
50. Westra, H. J. et al. Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat. Genet. 45, 1238-1243 (2013).
51. Zou, F. et al. Brain expression genome-wide association study (eGWAS) identifies human disease-associated variants. PLoS Genet. 8, e1002707 (2012).
52. Hao, K. et al. Lung eQTLs to help reveal the molecular underpinnings of asthma. PLoS Genet. 8, e1003029 (2012).
53. Koopmann, T. T. et al. Genome-wide identification of expression quantitative trait loci (eQTLs) in human heart. PLoS One 9, e97380 (2014).
54. Fairfax, B. P. et al. Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression. Science 343, 1246949 (2014).
55. Grundberg, E. et al. Global analysis of the impact of environmental perturbation on cis-regulation of gene expression. PLoS Genet. 7, e1001279 (2011).
56. Ward, L. D., Kellis, M. HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants. Nucleic Acids Res. 40, D930-D934 (2012).
57. Flicek, P. et al. Ensembl 2014. Nucleic Acids Res. 42, D749-D755 (2014).
58. Kumar, P., Henikoff, S., Ng, P. C. Predicting the effects of coding nonsynonymous variants on protein function using the SIFT algorithm. Nat. Protoc. 4, 1073-1081 (2009).
59. Adzhubei, I. A. et al. A method and server for predicting damaging missense mutations. Nat. Methods 7, 248-249 (2010).
60. Szklarczyk, D. et al. STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res. 43, D447-D452 (2015).
61. The International HapMap 3 Consortium. Integrating common and rare genetic variation in diverse human populations. Nature 467, 52-58 (2010).
62. Morris, A. P. Transethnic meta-analysis of genome-wide association studies. Genet. Epidemiol. 35, 809-822 (2011).
63. The Wellcome Trust Case Control Consortium. Bayesian refinement of association signals for 14 loci in 3 common diseases. Nat. Genet. 44, 1294-1301 (2012).
64. Wang, X. et al. Comparing methods for performing trans-ethnic meta-analysis of genome-wide association studies. Hum. Mol. Genet. 22, 2303-2311 (2013).
65. ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57-74 (2012).
66. Harrow, J. et al. GENCODE: the reference human genome annotation for The ENCODE Project. Genome Res. 22, 1760-1774 (2012).
67. Pickrell, J. K. Joint analysis of functional genomic data and genome-wide association studies of 18 human traits. Am. J. Hum. Genet. 94, 559-573 (2014).
68. Yang, J. et al. Common SNPs explain a large proportion of the heritability for human height. Nat. Genet. 42, 565-569 (2010).
69. Urbanek, M. et al. The chromosome 3q25 genomic region is associated with measures of adiposity in newborns in a multi-ethnic genome-wide association study. Hum. Mol. Genet. 22, 3583-3596 (2013).
70. Bulik-Sullivan, B. et al. An atlas of genetic correlations across human diseases and traits. Nat. Genet. 47, 1236-1241 (2015).
71. The International HapMap Consortium et al. A second generation human haplotype map of over 3. 1 million SNPs. Nature 449, 851-861 (2007).
72. Aschard, H., Vilhjálmsson, B. J., Joshi, A. D., Price, A. L., Kraft, P. Adjusting for heritable covariates can bias effect estimates in genome-wide association studies. Am. J. Hum. Genet. 96, 329-339 (2015).
73. Wang, L., Mousavi, P., Baranzini, S. E. iPINBPA: an integrative network-based functional module discovery tool for genome-wide association studies. Pac. Symp. Biocomput. 255-266 (2015).
74. Mishra, A., Macgregor, S. VEGAS2: software for more flexible gene-based testing. Twin Res. Hum. Genet. 18, 86-91 (2015).
75. Lage, K. et al. A human phenome-interactome network of protein complexes implicated in genetic disorders. Nat. Biotechnol. 25, 309-316 (2007).
76. Whitlock, M. C. Combining probability from independent tests: the weighted Z-method is superior to Fisher's approach. J. Evol. Biol. 18, 1368-1373 (2005).
77. Hoggart, C. J. et al. Novel approach identifies SNPs in SLC2A10 and KCNK9 with evidence for parent-of-origin effect on body mass index. PLoS Genet. 10, e1004508 (2014).
78. Wang, S., Yu, Z., Miller, R. L., Tang, D., Perera, F. P. Methods for detecting interactions between imprinted genes and environmental exposures using birth cohort designs with mother-offspring pairs. Hum. Hered. 71, 196-208 (2011).
79. Painter, J. N. et al. Genome-wide association study identifies a locus at 7p15. 2 associated with endometriosis. Nat. Genet. 43, 51-54 (2011).
80. Ganesh, S. K. et al. Multiple loci influence erythrocyte phenotypes in the CHARGE Consortium. Nat. Genet. 41, 1191-1198 (2009).
81. Xu, X. H. et al. Two functional loci in the promoter of EPAS1 gene involved in high-altitude adaptation of Tibetans. Sci. Rep. 4, 7465 (2014).
82. Huerta-Sánchez, E. et al. Altitude adaptation in Tibetans caused by introgression of Denisovan-like DNA. Nature 512, 194-197 (2014).