Height is a classic polygenic trait, reflecting the combined influence of multiple as-yet-undiscovered genetic factors. We carried out a meta-analysis of genome-wide association study data of height from 15,821 individuals at 2.2 million SNPs, and followed up the strongest findings in >10,000 subjects. Ten newly identified and two previously reported loci were strongly associated with variation in height (P values from 4 × 10−7 to 8 × 10−22). Together, these 12 loci account for ∼2% of the population variation in height. Individuals with ≤8 height-increasing alleles and ≥16 height-increasing alleles differ in height by ∼3.5 cm. The newly identified loci, along with several additional loci with strongly suggestive associations, encompass both strong biological candidates and unexpected genes, and highlight several pathways (let-7 targets, chromatin remodeling proteins and Hedgehog signaling) as important regulators of human stature. These results expand the picture of the biological regulation of human height and of the genetic architecture of this classical complex trait.
Access optionsAccess options
Subscribe to Journal
Get full journal access for 1 year
only $18.75 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
We thank members of our laboratories for helpful discussion, and gratefully acknowledge all of the participants in the studies. Contributing members for the DGI, FUSION, KORA and SardiNIA GWA scans are listed in the Supplementary Note. The authors acknowledge C. Chen of Bioinformed Consulting Services Inc. for expert programming, and L. Qi for his assistance. The authors thank C. Berg and P. Prorok, Division of Cancer Prevention, National Cancer Institute, the Screening Center investigators and staff of the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial, T. Riley and staff, Information Management Services, Inc., and B. O'Brien and staff, Westat, Inc. KORA gratefully acknowledges the contribution of T. Meitinger and all other members of the GSF genotyping staff in generating the SNP dataset. We thank the Mayor and the administration in Lanusei for providing and furnishing the clinic site; and the mayors of Ilbono, Arzana and Elini, the head of the local Public Health Unit ASL4. Support for this work was provided by the following: US National Institutes of Health grants 5P01CA087969 and CA49449 (S.E. Hankinson), 5UO1CA098233 (D.J.H.), DK62370 (M.B.), DK72193 (K.L.M.), HG02651 and HL084729 (G.R.A.); Novartis Institutes for BioMedical Research (D. Altshuler); March of Dimes grant 6-FY04-61 (J.N.H.); EU Projects GenomEUtwin grant QLG2-CT-2002-01254 and the Center of Excellence in Complex Disease Genetics of the Academy of Finland (L.P.); the Sigrid Juselius Foundation (L.C.G., V.S. and PPP); the Finnish Diabetes Research Foundation and the Folkhälsan Research Foundation and Clinical Research Institute HUCH (L.C.G.); this research was supported (in part) by the intramural Research Program of the NIH, National Institute on Aging; the PLCO research was supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics and by contracts from the Division of Cancer Prevention, National Cancer Institute, NIH, DHHS; KORA/MONICA Augsburg studies were financed by the GSF-National Research Center for Environment and Health, Munich/Neuherberg, Germany and supported by grants from the German Federal Ministry of Education and Research (BMBF); part of this work by KORA was supported by the German National Genome Research Network (NGFN), the Munich Center of Health Sciences (MC Health) as part of LMUinnovativ, and a subcontract of the 5 R01 DK 075787 by the NIH/NIDDK to the GSF-National Research Center for Environment and Health (to J.N.H.).
Supplementary Methods, Supplementary Tables 1–9, Supplementary Note, Supplementary Figures 1 and 2
About this article
Journal of Veterinary Internal Medicine (2019)