Meta-Analysis of Genomewide Association Studies Reveals Genetic Variants for Hip Bone Geometry

Yi Hsiang Hsu, Karol Estrada, Evangelos Evangelou, Cheryl Ackert-Bicknell, Kristina Akesson, Thomas Beck, Suzanne J. Brown, Terence Capellini, Laura Carbone, Jane Cauley, Ching Lung Cheung, Steven R. Cummings, Stefan Czerwinski, Serkalem Demissie, Michael Econs, Daniel Evans, Charles Farber, Kaare Gautvik, Tamara Harris, Candace KammererJohn Kemp, Daniel L. Koller, Annie Kung, Debbie Lawlor, Miryoung Lee, Mattias Lorentzon, Fiona McGuigan, Carolina Medina-Gomez, Braxton Mitchell, Anne Newman, Carrie Nielson, Claes Ohlsson, Munro Peacock, Sjur Reppe, J. Brent Richards, John Robbins, Gunnar Sigurdsson, Timothy D. Spector, Kari Stefansson, Elizabeth Streeten, Unnur Styrkarsdottir, Jonathan Tobias, Katerina Trajanoska, André Uitterlinden, Liesbeth Vandenput, Scott G. Wilson, Laura Yerges-Armstrong, Mariel Young, M. Carola Zillikens, Fernando Rivadeneira, Douglas P. Kiel, David Karasik*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

26 Citations (Scopus)
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Abstract

Hip geometry (HG) is an important predictor of fracture. We performed a meta-analysis of GWAS studies in adults to identify genetic variants that are associated with proximal femur geometry phenotypes. We analyzed four phenotypes: 1) Femoral neck length; 2) Neck-shaft angle; 3) Femoral neck width, and 4) Femoral neck section modulus, estimated from DXA scans using algorithms of hip structure analysis. In the Discovery stage, 10 cohort studies were included in the fixed-effect meta-analysis, with up to 18,719 men and women ages 16-93 years. Association analyses were performed with ~ 2.5 million polymorphisms
under an additive model adjusted for age and body mass index; an additional analysis also adjusted for height. Replication analyses of meta-GWAS significant loci (at genome-wide significance, GWS, threshold p≤5x10-8) were performed in 7 additional cohorts in-silico. In meta-analysis not adjusting for height (combined Discovery and Replication stages), GWS associations were found on chr. 4 (in HHIP), chr. 8 (C8orf34), chr. 13 (FAM10A4 and DLEU2), and chr. 20 (in
DDX27). The height-adjusted meta-analysis showed significant associations at 5p15 (IRX1 and ADAMTS16); 5q35 near FGFR4; at 12p11 (in CCDC91); 11q13 (near LRP5 and PPP6R3 (rs7102273)). Several HG signals overlapped with bone mineral density (BMD), including JAG1 on chr. 20, near TNFRSF11B (chr. 8), SOX6 and LRP5 (chr. 11). Chr. 11 SNP rs7102273 was associated with any-type fracture (p = 7.5 x 10-5). We used bone transcriptome data and discovered
several significant eQTLs, including rs7102273 and PPP6R3 expression (p=0.0007), and rs6556301 (intergenic, chr.5) and PDLIM7 expression
(p=0.005).

In conclusion, we found associations between HG measures and several genes being part of biological pathways relevant to BMD and fractures. The results provide a defined set of genes facilitating further experimental exploration and validation to understand biological mechanisms underlying human bone geometry and etiology of bone fragility.
Original languageEnglish
Article numbere3698
Pages (from-to)1284-1296
Number of pages13
JournalJournal of Bone and Mineral Research
Volume34
Issue number7
Early online date19 Mar 2019
DOIs
Publication statusPublished - 1 Jul 2019

Keywords

  • DXA
  • Analysis/quantitation of bone
  • osteoporosis
  • diseases and sisorders of/related to bone
  • human association studies
  • genetic research

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