The complex genetics of gait speed: Genome-wide meta-analysis approach

Dan Ben-Avraham, David Karasik, Joe Verghese, Kathryn L. Lunetta, Jennifer A. Smith, John D. Eicher, Rotem Vered, Joris Deelen, Alice M. Arnold, Aron S. Buchman, Toshiko Tanaka, Jessica D. Faul, Maria Nethander, Myriam Fornage, Hieab H. Adams, Amy M. Matteini, Michele L. Callisaya, Albert V. Smith, Lei Yu, Philip L. De JagerDenis A. Evans, Vilmundur Gudnason, Albert Hofman, Alison Pattie, Janie Corley, Lenore J. Launer, Davis S. Knopman, Neeta Parimi, Stephen T. Turner, Stefania Bandinelli, Marian Beekman, Danielle Gutman, Lital Sharvit, Simon P. Mooijaart, David C. Liewald, Jeanine J. Houwing-Duistermaat, Claes Ohlsson, Matthijs Moed, Vincent J. Verlinden, Dan Mellström, Jos N. van der Geest, Magnus Karlsson, Dena Hernandez, Rebekah McWhirter, Yongmei Liu, Russell Thomson, Gregory J. Tranah, Andre G. Uitterlinden, David R. Weir, Wei Zhao, John M. Starr, Andrew D. Johnson, M. Arfan Ikram, David A. Bennett, Steven R. Cummings, Ian J. Deary, Tamara B. Harris, Sharon L. Sharon, Thomas H. Mosley, Velandai K. Srikanth, Beverly G. Windham, Ann B. Newman, Jeremy D. Walston, Gail Davies, Daniel S. Evans, Eline P. Slagboom, Luigi Ferrucci, Douglas P. Kiel, Joanne M. Murabito, Gil Atzmon

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

Emerging evidence suggests that the basis for variation in late-life mobility is attributable, in part, to genetic factors, which may become increasingly important with age. Our objective was to systematically assess the contribution of genetic variation to gait speed in older individuals. We conducted a meta-analysis of gait speed GWASs in 31,478 older adults from 17 cohorts of the CHARGE consortium, and validated our results in 2,588 older adults from 4 independent studies. We followed our initial discoveries with network and eQTL analysis of candidate signals in tissues. The meta-analysis resulted in a list of 536 suggestive genome wide significant SNPs in or near 69 genes. Further interrogation with Pathway Analysis placed gait speed as a polygenic complex trait in five major networks. Subsequent eQTL analysis revealed several SNPs significantly associated with the expression of PRSS16, WDSUB1 and PTPRT, which in addition to the meta-analysis and pathway suggested that genetic effects on gait speed may occur through synaptic function and neuronal development pathways. No genome-wide significant signals for gait speed were identified from this moderately large sample of older adults, suggesting that more refined physical function phenotypes will be needed to identify the genetic basis of gait speed in aging.

Original languageEnglish (US)
Pages (from-to)209-246
Number of pages38
JournalAging
Volume9
Issue number1
DOIs
StatePublished - Jan 1 2017

Keywords

  • Aging
  • GWAS
  • Gait speed
  • Meta-analysis

ASJC Scopus subject areas

  • Aging
  • Cell Biology

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    Ben-Avraham, D., Karasik, D., Verghese, J., Lunetta, K. L., Smith, J. A., Eicher, J. D., Vered, R., Deelen, J., Arnold, A. M., Buchman, A. S., Tanaka, T., Faul, J. D., Nethander, M., Fornage, M., Adams, H. H., Matteini, A. M., Callisaya, M. L., Smith, A. V., Yu, L., ... Atzmon, G. (2017). The complex genetics of gait speed: Genome-wide meta-analysis approach. Aging, 9(1), 209-246. https://doi.org/10.18632/aging.101151