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miRNAs and sports: tracking training status and potentially confounding diagnoses

Overview of attention for article published in Journal of Translational Medicine, July 2016
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  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

Mentioned by

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3 tweeters

Citations

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17 Dimensions

Readers on

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47 Mendeley
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Title
miRNAs and sports: tracking training status and potentially confounding diagnoses
Published in
Journal of Translational Medicine, July 2016
DOI 10.1186/s12967-016-0974-x
Pubmed ID
Authors

Anne Hecksteden, Petra Leidinger, Christina Backes, Stefanie Rheinheimer, Mark Pfeiffer, Alexander Ferrauti, Michael Kellmann, Farbod Sedaghat, Benjamin Meder, Eckart Meese, Tim Meyer, Andreas Keller

Abstract

The dependency of miRNA abundance from physiological processes such as exercises remains partially understood. We set out to analyze the effect of physical exercises on miRNA profiles in blood and plasma of endurance and strength athletes in a systematic manner and correlated differentially abundant miRNAs in athletes to disease miRNAs biomarkers towards a better understanding of how physical exercise may confound disease diagnosis by miRNAs. We profiled blood and plasma of 29 athletes before and after exercise. With four samples analyzed for each individual we analyzed 116 full miRNomes. The study set-up enabled paired analyses of individuals. Affected miRNAs were investigated for known disease associations using network analysis. MiRNA patterns in blood and plasma of endurance and strength athletes vary significantly with differences in blood outreaching variations in plasma. We found only moderate differences between the miRNA levels before training and the RNA levels after training as compared to the more obvious variations found between strength athletes and endurance athletes. We observed significant variations in the abundance of miR-140-3p that is a known circulating disease markers (raw and adjusted p value of 5 × 10(-12) and 4 × 10(-7)). Similarly, the levels of miR-140-5p and miR-650, both of which have been reported as makers for a wide range of human pathologies significantly depend on the training mode. Among the most affected disease categories we found acute myocardial infarction. MiRNAs, which are up-regulated in endurance athletes inhibit VEGFA as shown by systems biology analysis of experimentally validated target genes. We provide evidence that the mode and the extent of training are important confounding factors for a miRNA based disease diagnosis.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Indonesia 1 2%
Canada 1 2%
Unknown 45 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 19%
Student > Bachelor 7 15%
Researcher 7 15%
Student > Doctoral Student 4 9%
Student > Master 4 9%
Other 9 19%
Unknown 7 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 21%
Medicine and Dentistry 7 15%
Nursing and Health Professions 7 15%
Sports and Recreations 7 15%
Agricultural and Biological Sciences 3 6%
Other 3 6%
Unknown 10 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 21 October 2017.
All research outputs
#6,915,409
of 12,022,940 outputs
Outputs from Journal of Translational Medicine
#1,059
of 2,331 outputs
Outputs of similar age
#125,375
of 266,468 outputs
Outputs of similar age from Journal of Translational Medicine
#37
of 90 outputs
Altmetric has tracked 12,022,940 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,331 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one is in the 46th percentile – i.e., 46% of its peers scored the same or lower than it.
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 266,468 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 90 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.