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Multi-omic integrated networks connect DNA methylation and miRNA with skeletal muscle plasticity to chronic exercise in Type 2 diabetic obesity

Overview of attention for article published in Physiological Genomics, August 2014
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

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Title
Multi-omic integrated networks connect DNA methylation and miRNA with skeletal muscle plasticity to chronic exercise in Type 2 diabetic obesity
Published in
Physiological Genomics, August 2014
DOI 10.1152/physiolgenomics.00024.2014
Pubmed ID
Authors

David S Rowlands, Rachel A Page, William R Sukala, Mamta Giri, Svetlana D Ghimbovschi, Irum Hayat, Birinder S Cheema, Isabelle Lys, Murray Leikis, Phillip W Sheard, St John Wakefield, Bernhard Breier, Yetrib Hathout, Kristy Brown, Ramya Marathi, Funda E Orkunoglu-Suer, Joseph M Devaney, Benjamin Leiken, Gina Many, Jeremy Krebs, Will G Hopkins, Eric P Hoffman

Abstract

Epigenomic regulation of the transcriptome by DNA methylation and post-transcriptional gene silencing by miRNAs are potential environmental modulators of skeletal muscle plasticity to chronic exercise in healthy and diseased populations. We utilised transcriptome networks to connect exercise-induced differential methylation and miRNA with functional skeletal muscle plasticity. Biopsies of the Vastus lateralis were collected from middle aged Polynesian men and women with morbid obesity (44 kg/m(2) ± 10) and Type-2 diabetes before and following 16 weeks of resistance (n=9) or endurance training (n=8). Longitudinal transcriptome, methylome, and miRNA responses were obtained via microarray, filtered by novel effect-size based false discovery rate probe selection preceding bioinformatic interrogation. Metabolic and microvascular transcriptome topology dominated the network landscape following endurance exercise. Lipid and glucose metabolism modules were connected to: miR-29a; promoter region hypomethylation of nuclear receptor factor (NRF1) and fatty-acid transporter (SLC27A4), and hypermethylation of fatty acid synthase, and to exon hypomethylation of 6-phosphofructo-2-kinase and Ser/Thr protein kinase. Directional change in the endurance networks was validated by lower intramyocellular lipid, increased capillarity, GLUT4, hexokinase and mitochondrial enzyme activity and proteome. Resistance training also lowered lipid, increased enzyme activity, and caused GLUT4-promoter hypomethylation; however, training was inconsequential to GLUT4, capillarity, and metabolic transcriptome. miR-195 connected to negative regulation of vascular development. To conclude, integrated molecular network modelling revealed differential DNA methylation and miRNA expression changes occur in skeletal muscle in response to chronic exercise training that are most pronounced with endurance training and topographically associated with functional metabolic and microvascular plasticity relevant to diabetes rehabilitation.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 329 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 <1%
Sweden 1 <1%
Unknown 326 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 53 16%
Student > Bachelor 43 13%
Student > Master 42 13%
Researcher 35 11%
Student > Postgraduate 15 5%
Other 55 17%
Unknown 86 26%
Readers by discipline Count As %
Medicine and Dentistry 54 16%
Biochemistry, Genetics and Molecular Biology 50 15%
Nursing and Health Professions 38 12%
Agricultural and Biological Sciences 37 11%
Sports and Recreations 31 9%
Other 26 8%
Unknown 93 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 September 2014.
All research outputs
#6,996,781
of 25,371,288 outputs
Outputs from Physiological Genomics
#315
of 1,142 outputs
Outputs of similar age
#63,261
of 247,165 outputs
Outputs of similar age from Physiological Genomics
#3
of 10 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 1,142 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one has gotten more attention than average, scoring higher than 72% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 247,165 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 7 of them.