Genome-wide association study identifies 112 new loci for body mass index in the Japanese population

Nature Genetics

Volumn 49, Issue 10, 2017, Pages 1458-1467

  Akiyama, Masato ^a   Okada, Yukinori ^a,b,c   Kanai, Masahiro ^a   Takahashi, Atsushi ^a,d   Momozawa, Yukihide ^a   Ikeda, Masashi ^e   Iwata, Nakao ^e   Ikegawa, Shiro ^a   Hirata, Makoto ^f   Matsuda, Koichi ^f   Iwasaki, Motoki ^g   Yamaji, Taiki ^g   Sawada, Norie ^g   Hachiya, Tsuyoshi ^h   Tanno, Kozo ^h   Shimizu, Atsushi ^h   Hozawa, Atsushi ^i,j   Minegishi, Naoko ^i,j   Tsugane, Shoichiro ^g   Yamamoto, Masayuki ^i,j   Kubo, Michiaki ^a   Kamatani, Yoichiro ^a,k   more..

^a RIKEN Center for Integrative Medical Sciences   (Japan)

^b OSAKA UNIVERSITY GRADUATE SCHOOL OF MEDICINE   (Japan)

^c OSAKA UNIVERSITY   (Japan)

^d NATIONAL CEREBRAL AND CARDIOVASCULAR CENTER   (Japan)

^e FUJITA HEALTH UNIVERSITY SCHOOL OF MEDICINE   (Japan)

^f UNIVERSITY OF TOKYO   (Japan)

^g NATIONAL CANCER CENTER   (Japan)

^h IWATE MEDICAL UNIVERSITY   (Japan)

ⁱ TOHOKU UNIVERSITY   (Japan)

^j TOHOKU UNIVERSITY GRADUATE SCHOOL OF MEDICINE   (Japan)

^k KYOTO UNIVERSITY GRADUATE SCHOOL OF MEDICINE   (Japan)

more..

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AGED; ARTICLE; BODY HEIGHT; BODY MASS; BODY WEIGHT; ENHANCER REGION; FEMALE; GENE FREQUENCY; GENE LINKAGE DISEQUILIBRIUM; GENE LOCUS; GENETIC ASSOCIATION; GENETIC CORRELATION; GENETIC IDENTIFICATION; GENETIC VARIABILITY; GENOME-WIDE ASSOCIATION STUDY; HUMAN; JAPANESE (PEOPLE); LYMPHOCYTE COUNT; MAJOR CLINICAL STUDY; MALE; MIDDLE AGED; NON INSULIN DEPENDENT DIABETES MELLITUS; OBESITY; PLEIOTROPY; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; RISK FACTOR; WHOLE GENOME SEQUENCING; ASIAN CONTINENTAL ANCESTRY GROUP; CAUCASIAN; COMORBIDITY; COMPARATIVE STUDY; EPIDEMIOLOGY; ETHNOLOGY; EUROPE; GENETICS; IMMUNOLOGY; JAPAN; META ANALYSIS; PHYSIOLOGY; SINGLE NUCLEOTIDE POLYMORPHISM;

ASIAN CONTINENTAL ANCESTRY GROUP; BODY MASS INDEX; BODY WEIGHT; COMORBIDITY; DIABETES MELLITUS, TYPE 2; EUROPE; EUROPEAN CONTINENTAL ANCESTRY GROUP; GENOME-WIDE ASSOCIATION STUDY; HUMANS; JAPAN; LYMPHOCYTE COUNT; OBESITY; POLYMORPHISM, SINGLE NUCLEOTIDE;

EID: 85030155140     PISSN: 10614036     EISSN: 15461718     Source Type: Journal    
DOI: 10.1038/ng.3951     Document Type: Article

References (54)

1. Haslam, D.W. & James, W.P.T. Obesity. Lancet 366, 1197-1209 (2005).
2. Wilson, P.W.F., D'Agostino, R.B., Sullivan, L., Parise, H. & Kannel, W.B. Overweight and obesity as determinants of cardiovascular risk: the Framingham experience. Arch. Intern. Med. 162, 1867-1872 (2002).
3. Renehan, A.G., Tyson, M., Egger, M., Heller, R.F. & Zwahlen, M. Body-mass index and incidence of cancer: A systematic review and meta-analysis of prospective observational studies. Lancet 371, 569-578 (2008).
4. Speliotes, E.K. et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat. Genet. 42, 937-948 (2010).
5. Wen, W. et al. Meta-analysis of genome-wide association studies in East Asian-ancestry populations identifies four new loci for body mass index. Hum. Mol. Genet. 23, 5492-5504 (2014).
6. Locke, A.E. et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 518, 197-206 (2015).
7. Winkler, T.W. et al. The influence of age and sex on genetic associations with adult body size and shape: A large-scale genome-wide interaction study. PLoS Genet. 11, e1005378 (2015).
8. Yang, J. et al. Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index. Nat. Genet. 47, 1114-1120 (2015).
9. Yoon, K.H. et al. Epidemic obesity and type 2 diabetes in Asia. Lancet 368, 1681-1688 (2006).
10. Nakamura, Y. The BioBank Japan Project. Clin. Adv. Hematol. Oncol. 5, 696-697 (2007).
11. Nagai, A. et al. Overview of the BioBank Japan Project: study design and profile. J. Epidemiol. 27, S2-S8 (2017).
12. Hirata, M. et al. Cross-sectional analysis of BioBank Japan clinical data: A large cohort of 200,000 patients with 47 common diseases. J. Epidemiol. 27, S9-S21 (2017).
13. Abecasis, G.R. et al. A map of human genome variation from population-scale sequencing. Nature 467, 1061-1073 (2010).
14. Bulik-Sullivan, B.K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291-295 (2015).
15. Bulik-Sullivan, B. et al. An atlas of genetic correlations across human diseases and traits. Nat. Genet. 47, 1236-1241 (2015).
16. Trivellin, G. et al. Gigantism and acromegaly due to Xq26 microduplications and GPR101 mutation. N. Engl. J. Med. 371, 2363-2374 (2014).
17. Lek, M. et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature 536, 285-291 (2016).
18. Morris, A.P. Transethnic meta-analysis of genomewide association studies. Genet. Epidemiol. 35, 809-822 (2011).
19. Wang, X. et al. Comparing methods for performing trans-ethnic meta-analysis of genome-wide association studies. Hum. Mol. Genet. 22, 2303-2311 (2013).
20. Roadmap Epigenomics Consortium. Integrative analysis of 111 reference human epigenomes. Nature 518, 317-330 (2015).
21. Trynka, G. et al. Chromatin marks identify critical cell types for fine mapping complex trait variants. Nat. Genet. 45, 124-130 (2013).
22. Finucane, H.K. et al. Partitioning heritability by functional annotation using genomewide association summary statistics. Nat. Genet. 47, 1228-1235 (2015).
23. GTEx Consortium. The Genotype-Tissue Expression (GTEx) project. Nat. Genet. 45, 580-585 (2013).
24. Westra, H.-J. et al. Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat. Genet. 45, 1238-1243 (2013).
25. Yang, J., Lee, S.H., Goddard, M.E. & Visscher, P.M. GCTA: A tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76-82 (2011).
26. Yang, J. et al. Genome partitioning of genetic variation for complex traits using common SNPs. Nat. Genet. 43, 519-525 (2011).
27. Segrè, A.V., Groop, L., Mootha, V.K., Daly, M.J. & Altshuler, D. Common inherited variation in mitochondrial genes is not enriched for associations with type 2 diabetes or related glycemic traits. PLoS Genet. 6, e1001058 (2010).
28. Okada, Y. et al. Common variants at CDKAL1 and KLF9 are associated with body mass index in east Asian populations. Nat. Genet. 44, 302-306 (2012).
29. Scott, R.A. et al. Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways. Nat. Genet. 44, 991-1005 (2012).
30. Dimas, A.S. et al. Impact of type 2 diabetes susceptibility variants on quantitative glycemic traits reveals mechanistic heterogeneity. Diabetes 63, 2158-2171 (2014).
31. Zheng, J. et al. LD Hub: A centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis. Bioinformatics 33, 272-279 (2017).
32. Julius, S., Egan, B.M., Kaciroti, N.A., Nesbitt, S.D. & Chen, A.K. In prehypertension leukocytosis is associated with body mass index but not with blood pressure or incident hypertension. J. Hypertens. 32, 251-259 (2014).
33. Ilavská, S. et al. Association between the human immune response and body mass index. Hum. Immunol. 73, 480-485 (2012).
34. Okada, Y. et al. Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature 506, 376-381 (2014).
35. Liu, J.Z. et al. Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat. Genet. 47, 979-986 (2015).
36. Oota, H. et al. The evolution and population genetics of the ALDH2 locus: random genetic drift, selection, and low levels of recombination. Ann. Hum. Genet. 68, 93-109 (2004).
37. Han, Y. et al. Evidence of positive selection on A class I ADH locus. Am. J. Hum. Genet. 80, 441-456 (2007).
38. Johnson, A.M.F. & Olefsky, J.M. The origins and drivers of insulin resistance. Cell 152, 673-684 (2013).
39. Winer, D.A. et al. B cells promote insulin resistance through modulation of T cells and production of pathogenic IgG antibodies. Nat. Med. 17, 610-617 (2011).
40. Winer, D.A., Winer, S., Chng, M.H., Shen, L. & Engleman, E.G. B lymphocytes in obesity-related adipose tissue inflammation and insulin resistance. Cell. Mol. Life Sci. 71, 1033-1043 (2014).
41. Claussnitzer, M. et al. FTO obesity variant circuitry and adipocyte browning in humans. N. Engl. J. Med. 373, 895-907 (2015).
42. Hjellvik, V., Tverdal, A. & Furu, K. Body mass index as predictor for asthma: A cohort study of 118,723 males and females. Eur. Respir. J. 35, 1235-1242 (2010).
43. Inamasu, J., Guiot, B.H. & Sachs, D.C. Ossification of the posterior longitudinal ligament: an update on its biology, epidemiology, and natural history. Neurosurgery 58, 1027-1039, discussion 1027-1039 (2006).
44. Tam, E.M. et al. Lower muscle mass and body fat in adolescent idiopathic scoliosis are associated with abnormal leptin bioavailability. Spine 41, 940-946 (2016).
45. Turesson, C., Bergström, U., Pikwer, M., Nilsson, J.-A. & Jacobsson, L.T.H. A high body mass index is associated with reduced risk of rheumatoid arthritis in men, but not in women. Rheumatology 55, 307-314 (2016).
46. Qin, B. et al. Body mass index and the risk of rheumatoid arthritis: A systematic review and dose-response meta-analysis. Arthritis Res. Ther. 17, 86 (2015).
47. Zammit, S. et al. Height and body mass index in young adulthood and risk of schizophrenia: A longitudinal study of 1 347 520 Swedish men. Acta Psychiatr. Scand. 116, 378-385 (2007).
48. Wyatt, R.J., Henter, I.D., Mojtabai, R. & Bartko, J.J. Height, weight and body mass index (BMI) in psychiatrically ill US Armed Forces personnel. Psychol. Med. 33, 363-368 (2003).
49. Price, A.L. et al. Principal components analysis corrects for stratification in genomewide association studies. Nat. Genet. 38, 904-909 (2006).
50. Purcell, S. et al. PLINK: A tool set for whole-genome association and populationbased linkage analyses. Am. J. Hum. Genet. 81, 559-575 (2007).
51. Li, Y., Willer, C.J., Ding, J., Scheet, P. & Abecasis, G.R. MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. Genet. Epidemiol. 34, 816-834 (2010).
52. Delaneau, O., Marchini, J. & Zagury, J.-F.Alinear complexity phasing method for thousands of genomes. Nat. Methods 9, 179-181 (2011).
53. Pruim, R.J. et al. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics 26, 2336-2337 (2010).
54. Wang, K., Li, M. & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38, e164 (2010).