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


Ben-Avraham, D and Karasik, D and Verghese, J and Lunetta, KL and Smith, JA and Eicher, JD and Vered, R and Deelen, J and Arnold, AM and Buchman, AS and Tanaka, T and Faul, JD and Nethander, M and Fornage, M and Adams, HH and Matteini, AM and Callisaya, ML and Smith, AV and Yu, L and De Jager, PL and Evans, DA and Gudnason, V and Hofman, A and Pattie, A and Corley, J and Launer, LJ and Knopman, DS and Parimi, N and Turner, ST and Bandinelli, S and Beekman, M and Gutman, D and Sharvit, L and Mooijaart, SP and Liewald, DC and Houwing-Duistermaat, JJ and Ohlsson, C and Moed, M and Verlinden, VJ and Mellstrom, D and van der Geest, JN and Karlsson, M and Hernandez, D and McWhirter, R and Liu, Y and Thomson, R and Tranah, GJ and Uitterlinden, AG and Weir, DR and Zhao, W and Starr, JM and Johnson, AD and Ikram, MA and Bennett, DA and Cummings, SR and Deary, IJ and Harris, TB and Kardia, SLR and Mosley, TH and Srikanth, VK and Windham, BG and Newman, AB and Walston, JD and Davies, G and Evans, DS and Slagboom, EP and Ferrucci, L and Kiel, DP and Murabito, JM and Atzmon, G, The complex genetics of gait speed: genome-wide meta-analysis approach, Aging, 9, (1) pp. 209-246. ISSN 1945-4589 (2017) [Refereed Article]


Copyright Statement

Copyright 2017 the Author Licenced under Creative Commons Attribution 3.0 Unported (CC BY 3.0)

DOI: doi:10.18632/aging.101151


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.

Item Details

Item Type:Refereed Article
Keywords:gait speed, meta‐analysis, aging, GWAS
Research Division:Biological Sciences
Research Group:Genetics
Research Field:Gene mapping
Objective Division:Health
Objective Group:Specific population health (excl. Indigenous health)
Objective Field:Health related to ageing
UTAS Author:Callisaya, ML (Dr Michele Callisaya)
UTAS Author:McWhirter, R (Dr Rebekah McWhirter)
UTAS Author:Thomson, R (Dr Russell Thomson)
UTAS Author:Srikanth, VK (Dr Velandai Srikanth)
ID Code:115911
Year Published:2017
Web of Science® Times Cited:16
Deposited By:Menzies Institute for Medical Research
Deposited On:2017-04-20
Last Modified:2019-09-25
Downloads:169 View Download Statistics

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