Literature DB >> 20459472

Genome-wide linkage scan for resistance to muscle fatigue.

M A Thomis1, G De Mars, A Windelinckx, M W Peeters, W Huygens, J Aerssens, G P Beunen.   

Abstract

Repeated, intense use of muscles leads to a decline in performance known as muscle fatigue. Resistance to muscle fatigue depends on age, sex, muscle fiber type, activation by the nervous system and training. Heritability of muscle strength phenotypes ranges between 31% and 78%, although little is known about heritability of muscle fatigue. A first aim of this study was to estimate the heritability for fatigue resistance after a short bout of intense exercise of the knee musculature. The main purpose was to identify chromosomal regions linked to muscle fatigue applying genome-wide linkage analyses. A selection of 283 informative male siblings (17-36 years old), belonging to 105 families, was used to conduct a genome-wide SNP-based multipoint linkage analysis. Heritabilities for resistance to muscle fatigue ranged from 21% to 54%. The strongest linkage signal was found at 19q13.11 (LOD=2.158; P<0.0001) and at 1q32.1 (LOD=2.142; P<0.0001) for resistance to fatigue of the knee flexors; however, no marker reached genome-wide significance. Several other regions with LOD>1.5 were found (1p31.3, 3q29, 8p22, 11q25 and 19q12). When replicated in an independent sample, these results warrant further fine mapping studies aiming to detect genes that underlie variation in muscle fatigue.
© 2010 John Wiley & Sons A/S.

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Year:  2010        PMID: 20459472     DOI: 10.1111/j.1600-0838.2009.01082.x

Source DB:  PubMed          Journal:  Scand J Med Sci Sports        ISSN: 0905-7188            Impact factor:   4.221


  4 in total

1.  Identification and prioritization of NUAK1 and PPP1CC as positional candidate loci for skeletal muscle strength phenotypes.

Authors:  An Windelinckx; Gunther De Mars; Wim Huygens; Maarten W Peeters; Barbara Vincent; Cisca Wijmenga; Diether Lambrechts; Jeroen Aerssens; Robert Vlietinck; Gaston Beunen; Martine A I Thomis
Journal:  Physiol Genomics       Date:  2011-07-12       Impact factor: 3.107

2.  Comprehensive fine mapping of chr12q12-14 and follow-up replication identify activin receptor 1B (ACVR1B) as a muscle strength gene.

Authors:  An Windelinckx; Gunther De Mars; Wim Huygens; Maarten W Peeters; Barbara Vincent; Cisca Wijmenga; Diether Lambrechts; Christophe Delecluse; Stephen M Roth; E Jeffrey Metter; Luigi Ferrucci; Jeroen Aerssens; Robert Vlietinck; Gaston P Beunen; Martine A Thomis
Journal:  Eur J Hum Genet       Date:  2010-11-10       Impact factor: 4.246

Review 3.  Endocrine crosstalk between muscle and bone.

Authors:  Marco Brotto; Mark L Johnson
Journal:  Curr Osteoporos Rep       Date:  2014-06       Impact factor: 5.096

4.  Genome-wide linkage analysis of cardiovascular disease biomarkers in a large, multigenerational family.

Authors:  Daniel Nolan; William E Kraus; Elizabeth Hauser; Yi-Ju Li; Dana K Thompson; Jessica Johnson; Hsiang-Cheng Chen; Sarah Nelson; Carol Haynes; Simon G Gregory; Virginia B Kraus; Svati H Shah
Journal:  PLoS One       Date:  2013-08-02       Impact factor: 3.240

  4 in total

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