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Validation of whole-blood transcriptome signature during microdose recombinant human erythropoietin (rHuEpo) administration

Overview of attention for article published in BMC Genomics, November 2017
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  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

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Title
Validation of whole-blood transcriptome signature during microdose recombinant human erythropoietin (rHuEpo) administration
Published in
BMC Genomics, November 2017
DOI 10.1186/s12864-017-4191-7
Pubmed ID
Authors

Guan Wang, Jérôme Durussel, Jonathan Shurlock, Martin Mooses, Noriyuki Fuku, Georgie Bruinvels, Charles Pedlar, Richard Burden, Andrew Murray, Brendan Yee, Anne Keenan, John D. McClure, Pierre-Edouard Sottas, Yannis P. Pitsiladis

Abstract

Recombinant human erythropoietin (rHuEpo) can improve human performance and is therefore frequently abused by athletes. As a result, the World Anti-Doping Agency (WADA) introduced the Athlete Biological Passport (ABP) as an indirect method to detect blood doping. Despite this progress, challenges remain to detect blood manipulations such as the use of microdoses of rHuEpo. Forty-five whole-blood transcriptional markers of rHuEpo previously derived from a high-dose rHuEpo administration trial were used to assess whether microdoses of rHuEpo could be detected in 14 trained subjects and whether these markers may be confounded by exercise (n = 14 trained subjects) and altitude training (n = 21 elite runners and n = 4 elite rowers, respectively). Differential gene expression analysis was carried out following normalisation and significance declared following application of a 5% false discovery rate (FDR) and a 1.5 fold-change. Adaptive model analysis was also applied to incorporate these markers for the detection of rHuEpo. ALAS2, BCL2L1, DCAF12, EPB42, GMPR, SELENBP1, SLC4A1, TMOD1 and TRIM58 were differentially expressed during and throughout the post phase of microdose rHuEpo administration. The CD247 and TRIM58 genes were significantly up- and down-regulated, respectively, immediately following exercise when compared with the baseline both before and after rHuEpo/placebo. No significant gene expression changes were found 30 min after exercise in either rHuEpo or placebo groups. ALAS2, BCL2L1, DCAF12, SLC4A1, TMOD1 and TRIM58 tended to be significantly expressed in the elite runners ten days after arriving at altitude and one week after returning from altitude (FDR > 0.059, fold-change varying from 1.39 to 1.63). Following application of the adaptive model, 15 genes showed a high sensitivity (≥ 93%) and specificity (≥ 71%), with BCL2L1 and CSDA having the highest sensitivity (93%) and specificity (93%). Current results provide further evidence that transcriptional biomarkers can strengthen the ABP approach by significantly prolonging the detection window and improving the sensitivity and specificity of blood doping detection. Further studies are required to confirm, and if necessary, integrate the confounding effects of altitude training on blood doping.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 75 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 16%
Student > Master 9 12%
Student > Bachelor 9 12%
Researcher 8 11%
Professor > Associate Professor 4 5%
Other 9 12%
Unknown 24 32%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 11%
Medicine and Dentistry 8 11%
Agricultural and Biological Sciences 7 9%
Sports and Recreations 7 9%
Pharmacology, Toxicology and Pharmaceutical Science 4 5%
Other 12 16%
Unknown 29 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 29 November 2017.
All research outputs
#12,997,573
of 23,007,887 outputs
Outputs from BMC Genomics
#4,557
of 10,698 outputs
Outputs of similar age
#152,293
of 325,276 outputs
Outputs of similar age from BMC Genomics
#85
of 208 outputs
Altmetric has tracked 23,007,887 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,698 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 57% 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 325,276 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 52% of its contemporaries.
We're also able to compare this research output to 208 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 57% of its contemporaries.