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

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Author
Ben-Avraham, Dan
Karasik, David
Verghese, Joe
Lunetta, Kathryn L.
Smith, Jennifer A.
Eicher, John D.
Vered, Rotem
Deelen, Joris
Arnold, Alice M.
Buchman, Aron S.
Tanaka, Toshiko
Faul, Jessica D.
Nethander, Maria
Fornage, Myriam
Adams, Hieab H.
Matteini, Amy M.
Callisaya, Michele L.
Smith, Albert V.
Yu, Lei
Evans, Denis A.
Gudnason, Vilmundur
Pattie, Alison
Corley, Janie
Launer, Lenore J.
Knopman, Davis S.
Parimi, Neeta
Turner, Stephen T.
Bandinelli, Stefania
Beekman, Marian
Gutman, Danielle
Sharvit, Lital
Mooijaart, Simon P.
Liewald, David C.
Houwing-Duistermaat, Jeanine J.
Ohlsson, Claes
Moed, Matthijs
Verlinden, Vincent J.
Mellström, Dan
van der Geest, Jos N.
Karlsson, Magnus
Hernandez, Dena
McWhirter, Rebekah
Liu, Yongmei
Thomson, Russell
Tranah, Gregory J.
Uitterlinden, Andre G.
Weir, David R.
Zhao, Wei
Starr, John M.
Johnson, Andrew D.
Ikram, M. Arfan
Bennett, David A.
Cummings, Steven R.
Deary, Ian J.
Harris, Tamara B.
Kardia, Sharon L. R.
Mosley, Thomas H.
Srikanth, Velandai K.
Windham, Beverly G.
Newman, Ann B.
Walston, Jeremy D.
Davies, Gail
Evans, Daniel S.
Slagboom, Eline P.
Ferrucci, Luigi
Murabito, Joanne M.
Atzmon, Gil
Note: Order does not necessarily reflect citation order of authors.
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https://doi.org/10.18632/aging.101151Metadata
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Ben-Avraham, D., D. Karasik, J. Verghese, K. L. Lunetta, J. A. Smith, J. D. Eicher, R. Vered, et al. 2017. “The complex genetics of gait speed: genome-wide meta-analysis approach.” Aging (Albany NY) 9 (1): 209-228. doi:10.18632/aging.101151. http://dx.doi.org/10.18632/aging.101151.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.Other Sources
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5310665/pdf/Terms of Use
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http://nrs.harvard.edu/urn-3:HUL.InstRepos:31731901
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