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 Jager; Denis 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 Mellstrom; 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. Andrew D. Johnson; M. Arfan Ikram; David A. Bennett; Steven R. Cummings; Ian J. Deary; Tamara B. Harris; Sharon L. R. Kardia; 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

doi:10.18632/aging.101151

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 Mellstrom, 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. Andrew D. Johnson, M. Arfan Ikram, David A. Bennett, Steven R. Cummings, Ian J. Deary, Tamara B. Harris, Sharon L. R. Kardia, 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

Western Sydney University

Research output: Contribution to journal › Article › peer-review

24 Citations (Scopus)

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 language	English
Pages (from-to)	209-246
Number of pages	38
Journal	Aging
Volume	9
Issue number	1
DOIs	https://doi.org/10.18632/aging.101151
Publication status	Published - 2017

Keywords

aging
gait

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10.18632/aging.101151

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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

@article{9e8888d242cb4a179881214f94f3ef1c,

title = "The complex genetics of gait speed : genome-wide meta-analysis approach",

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.",

keywords = "aging, gait",

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

year = "2017",

doi = "10.18632/aging.101151",

language = "English",

volume = "9",

pages = "209--246",

journal = "Aging",

issn = "0002-0966",

publisher = "US Administration on Aging: Department of Health & Human Services",

number = "1",

}

Ben-Avraham, D, Karasik, D, Verghese, J, Lunetta, KL, Smith, JA, Eicher, JD, Vered, R, Deelen, J, Arnold, AM, Buchman, AS, Tanaka, T, Faul, JD, Nethander, M, Fornage, M, Adams, HH, Matteini, AM, Callisaya, ML, Smith, AV, Yu, L, De Jager, PL, Evans, DA, Gudnason, V, Hofman, A, Pattie, A, Corley, J, Launer, LJ, Knopman, DS, Parimi, N, Turner, ST, Bandinelli, S, Beekman, M, Gutman, D, Sharvit, L, Mooijaart, SP, Liewald, DC, Houwing‐Duistermaat, JJ, Ohlsson, C, Moed, M, Verlinden, VJ, Mellstrom, D, Van der Geest, JN, Karlsson, M, Hernandez, D, McWhirter, R, Liu, Y, Thomson, R, Tranah, GJ, Uitterlinden, AG, Weir, DR, Zhao, W, Starr, JM, Andrew D. Johnson, AD, Ikram, MA, Bennett, DA, Cummings, SR, Deary, IJ, Harris, TB, Kardia, SLR, Mosley, TH, Srikanth, VK, Windham, BG, Newman, AB, Walston, JD, Davies, G, Evans, DS, Slagboom, EP, Ferrucci, L, Kiel, DP, Murabito, JM & Atzmon, G 2017, 'The complex genetics of gait speed : genome-wide meta-analysis approach', Aging, vol. 9, no. 1, pp. 209-246. https://doi.org/10.18632/aging.101151

TY - JOUR

T1 - The complex genetics of gait speed : genome-wide meta-analysis approach

AU - Ben-Avraham, Dan

AU - Karasik, David

AU - Verghese, Joe

AU - Lunetta, Kathryn L.

AU - Smith, Jennifer A.

AU - Eicher, John D.

AU - Vered, Rotem

AU - Deelen, Joris

AU - Arnold, Alice M.

AU - Buchman, Aron S.

AU - Tanaka, Toshiko

AU - Faul, Jessica D.

AU - Nethander, Maria

AU - Fornage, Myriam

AU - Adams, Hieab H.

AU - Matteini, Amy M.

AU - Callisaya, Michele L.

AU - Smith, Albert V.

AU - Yu, Lei

AU - De Jager, Philip L.

AU - Evans, Denis A.

AU - Gudnason, Vilmundur

AU - Hofman, Albert

AU - Pattie, Alison

AU - Corley, Janie

AU - Launer, Lenore J.

AU - Knopman, Davis S.

AU - Parimi, Neeta

AU - Turner, Stephen T.

AU - Bandinelli, Stefania

AU - Beekman, Marian

AU - Gutman, Danielle

AU - Sharvit, Lital

AU - Mooijaart, Simon P.

AU - Liewald, David C.

AU - Houwing‐Duistermaat, Jeanine J.

AU - Ohlsson, Claes

AU - Moed, Matthijs

AU - Verlinden, Vincent J.

AU - Mellstrom, Dan

AU - Van der Geest, Jos N.

AU - Karlsson, Magnus

AU - Hernandez, Dena

AU - McWhirter, Rebekah

AU - Liu, Yongmei

AU - Thomson, Russell

AU - Tranah, Gregory J.

AU - Uitterlinden, Andre G.

AU - Weir, David R.

AU - Zhao, Wei

AU - Starr, John M.

AU - Andrew D. Johnson, Andrew D.

AU - Ikram, M. Arfan

AU - Bennett, David A.

AU - Cummings, Steven R.

AU - Deary, Ian J.

AU - Harris, Tamara B.

AU - Kardia, Sharon L. R.

AU - Mosley, Thomas H.

AU - Srikanth, Velandai K.

AU - Windham, Beverly G.

AU - Newman, Ann B.

AU - Walston, Jeremy D.

AU - Davies, Gail

AU - Evans, Daniel S.

AU - Slagboom, Eline P.

AU - Ferrucci, Luigi

AU - Kiel, Douglas P.

AU - Murabito, Joanne M.

AU - Atzmon, Gil

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

KW - aging

KW - gait

UR - http://handle.westernsydney.edu.au:8081/1959.7/uws:39620

U2 - 10.18632/aging.101151

DO - 10.18632/aging.101151

M3 - Article

SN - 0002-0966

VL - 9

SP - 209

EP - 246

JO - Aging

JF - Aging

IS - 1

ER -

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

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