Literature DB >> 15857889

Human muscle gene expression responses to endurance training provide a novel perspective on Duchenne muscular dystrophy.

James A Timmons1, Ola Larsson, Eva Jansson, Helene Fischer, Thomas Gustafsson, Paul L Greenhaff, John Ridden, Jonathan Rachman, Myriam Peyrard-Janvid, Claes Wahlestedt, Carl Johan Sundberg.   

Abstract

Global gene expression profiling is used to generate novel insight into a variety of disease states. Such studies yield a bewildering number of data points, making it a challenge to validate which genes specifically contribute to a disease phenotype. Aerobic exercise training represents a plausible model for identification of molecular mechanisms that cause metabolic-related changes in human skeletal muscle. We carried out the first transcriptome-wide characterization of human skeletal muscle responses to 6 wk of supervised aerobic exercise training in 8 sedentary volunteers. Biopsy samples before and after training allowed us to identify approximately 470 differentially regulated genes using the Affymetrix U95 platform (80 individual hybridization steps). Gene ontology analysis indicated that extracellular matrix and calcium binding gene families were most up-regulated after training. An electronic reanalysis of a Duchenne muscular dystrophy (DMD) transcript expression dataset allowed us to identify approximately 90 genes modulated in a nearly identical fashion to that observed in the endurance exercise dataset. Trophoblast noncoding RNA, an interfering RNA species, was the singular exception-being up-regulated by exercise and down-regulated in DMD. The common overlap between gene expression datasets may be explained by enhanced alpha7beta1 integrin signaling, and specific genes in this signaling pathway were up-regulated in both datasets. In contrast to these common features, OXPHOS gene expression is subdued in DMD yet elevated by exercise, indicating that more than one major mechanism must exist in human skeletal muscle to sense activity and therefore regulate gene expression. Exercise training modulated diabetes-related genes, suggesting our dataset may contain additional and novel gene expression changes relevant for the anti-diabetic properties of exercise. In conclusion, gene expression profiling after endurance exercise training identified a range of processes responsible for the physiological remodeling of human skeletal muscle tissue, many of which were similarly regulated in DMD. Furthermore, our analysis demonstrates that numerous genes previously suggested as being important for the DMD disease phenotype may principally reflect compensatory integrin signaling.

Entities:  

Mesh:

Substances:

Year:  2005        PMID: 15857889     DOI: 10.1096/fj.04-1980com

Source DB:  PubMed          Journal:  FASEB J        ISSN: 0892-6638            Impact factor:   5.191


  52 in total

1.  Transcriptome signature of resistance exercise adaptations: mixed muscle and fiber type specific profiles in young and old adults.

Authors:  Ulrika Raue; Todd A Trappe; Shawn T Estrem; Hui-Rong Qian; Leah M Helvering; Rosamund C Smith; Scott Trappe
Journal:  J Appl Physiol (1985)       Date:  2012-02-02

2.  Myogenic gene expression signature establishes that brown and white adipocytes originate from distinct cell lineages.

Authors:  James A Timmons; Kristian Wennmalm; Ola Larsson; Tomas B Walden; Timo Lassmann; Natasa Petrovic; D Lee Hamilton; Ruth E Gimeno; Claes Wahlestedt; Keith Baar; Jan Nedergaard; Barbara Cannon
Journal:  Proc Natl Acad Sci U S A       Date:  2007-03-05       Impact factor: 11.205

Review 3.  Genomics and genetics in the biology of adaptation to exercise.

Authors:  Claude Bouchard; Tuomo Rankinen; James A Timmons
Journal:  Compr Physiol       Date:  2011-07       Impact factor: 9.090

4.  A muscle-specific knockout implicates nuclear receptor coactivator MED1 in the regulation of glucose and energy metabolism.

Authors:  Wei Chen; Xiaoting Zhang; Kivanc Birsoy; Robert G Roeder
Journal:  Proc Natl Acad Sci U S A       Date:  2010-05-17       Impact factor: 11.205

5.  Effects of mild-exercise training cessation in human skeletal muscle.

Authors:  Jonny St-Amand; Mayumi Yoshioka; Yuichiro Nishida; Takuro Tobina; Naoko Shono; Hiroaki Tanaka
Journal:  Eur J Appl Physiol       Date:  2011-06-17       Impact factor: 3.078

6.  Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans.

Authors:  James A Timmons; Steen Knudsen; Tuomo Rankinen; Lauren G Koch; Mark Sarzynski; Thomas Jensen; Pernille Keller; Camilla Scheele; Niels B J Vollaard; Søren Nielsen; Thorbjörn Akerström; Ormond A MacDougald; Eva Jansson; Paul L Greenhaff; Mark A Tarnopolsky; Luc J C van Loon; Bente K Pedersen; Carl Johan Sundberg; Claes Wahlestedt; Steven L Britton; Claude Bouchard
Journal:  J Appl Physiol (1985)       Date:  2010-02-04

7.  Increased 24-hour ad libitum food intake is associated with lower plasma irisin concentrations the following morning in adult humans.

Authors:  Mathias Schlögl; Paolo Piaggi; Susanne B Votruba; Mary Walter; Jonathan Krakoff; Marie S Thearle
Journal:  Appetite       Date:  2015-03-09       Impact factor: 3.868

8.  Integration of microRNA changes in vivo identifies novel molecular features of muscle insulin resistance in type 2 diabetes.

Authors:  Iain J Gallagher; Camilla Scheele; Pernille Keller; Anders R Nielsen; Judit Remenyi; Christian P Fischer; Karim Roder; John Babraj; Claes Wahlestedt; Gyorgy Hutvagner; Bente K Pedersen; James A Timmons
Journal:  Genome Med       Date:  2010-02-01       Impact factor: 11.117

9.  Using transcriptomics to identify and validate novel biomarkers of human skeletal muscle cancer cachexia.

Authors:  Nathan A Stephens; Iain J Gallagher; Olav Rooyackers; Richard J Skipworth; Ben H Tan; Troels Marstrand; James A Ross; Denis C Guttridge; Lars Lundell; Kenneth C Fearon; James A Timmons
Journal:  Genome Med       Date:  2010-01-15       Impact factor: 11.117

10.  Muscle Research and Gene Ontology: New standards for improved data integration.

Authors:  Erika Feltrin; Stefano Campanaro; Alexander D Diehl; Elisabeth Ehler; Georgine Faulkner; Jennifer Fordham; Chiara Gardin; Midori Harris; David Hill; Ralph Knoell; Paolo Laveder; Lorenza Mittempergher; Alessandra Nori; Carlo Reggiani; Vincenzo Sorrentino; Pompeo Volpe; Ivano Zara; Giorgio Valle; Jennifer Deegan
Journal:  BMC Med Genomics       Date:  2009-01-29       Impact factor: 3.063

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.