The complex genetics of gait speed : Genome-wide meta-analysis approach
(2017) In Aging 9(1). p.209-246- 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... (More)
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.
(Less)
- author
- organization
- publishing date
- 2017
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Aging, Gait speed, GWAS, Meta-analysis
- in
- Aging
- volume
- 9
- issue
- 1
- pages
- 38 pages
- publisher
- Impact Journals
- external identifiers
-
- scopus:85013436860
- pmid:28077804
- ISSN
- 1945-4589
- DOI
- 10.18632/aging.101151
- language
- English
- LU publication?
- yes
- id
- 2a540d9f-73ba-41d7-8442-fe16f20afb72
- date added to LUP
- 2017-03-09 09:54:31
- date last changed
- 2024-12-09 07:42:28
@article{2a540d9f-73ba-41d7-8442-fe16f20afb72,
abstract = {{<p>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.</p>}},
author = {{Ben-Avraham, Dan and Karasik, David and Verghese, Joe and Lunetta, Kathryn L and Smith, Jennifer A and Eicher, John D. and Vered, Rotem and Deelen, Joris and Arnold, Alice M and Buchman, Aron S and Tanaka, Toshiko and Faul, Jessica D and Nethander, Maria and Fornage, Myriam and Adams, Hieab H. and Matteini, Amy M. and Callisaya, Michele L. and Smith, Albert V and Yu, Lei and De Jager, Philip L and Evans, Denis A and Gudnason, Vilmundur and Hofman, Albert and Pattie, Alison and Corley, Janie and Launer, Lenore J. and Knopman, Davis S. and Parimi, Neeta and Turner, Stephen T. and Bandinelli, Stefania and Beekman, Marian and Gutman, Danielle and Sharvit, Lital and Mooijaart, Simon P and Liewald, David C M and Houwing-Duistermaat, Jeanine J and Ohlsson, Claes and Moed, Matthijs and Verlinden, Vincent J. and Mellström, Dan and van der Geest, Jos N. and Karlsson, Magnus and Hernandez, Dena and McWhirter, Rebekah and Liu, Yongmei and Thomson, Russell and Tranah, Gregory J and Uitterlinden, Andre G. and Weir, David R and Zhao, Wei and Starr, John M and Johnson, Andrew D and Arfan Ikram, M. and Bennett, David A and Cummings, Steven R and Deary, Ian J and Harris, Tamara B. and Kardia, Sharon L. and Mosley, Thomas H. and Srikanth, Velandai K. and Windham, Beverly G. and Newman, Ann B. and Walston, Jeremy D. and Davies, Gail and Evans, Daniel S and Slagboom, P. Eline and Ferrucci, Luigi and Kiel, Douglas P and Murabito, Joanne M. and Atzmon, Gil}},
issn = {{1945-4589}},
keywords = {{Aging; Gait speed; GWAS; Meta-analysis}},
language = {{eng}},
number = {{1}},
pages = {{209--246}},
publisher = {{Impact Journals}},
series = {{Aging}},
title = {{The complex genetics of gait speed : Genome-wide meta-analysis approach}},
url = {{http://dx.doi.org/10.18632/aging.101151}},
doi = {{10.18632/aging.101151}},
volume = {{9}},
year = {{2017}},
}