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Gene expression profiling reveals potential prognostic biomarkers associated with the progression of heart failure

Overview of attention for article published in Genome Medicine, March 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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1 patent
wikipedia
1 Wikipedia page

Citations

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99 Dimensions

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55 Mendeley
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Title
Gene expression profiling reveals potential prognostic biomarkers associated with the progression of heart failure
Published in
Genome Medicine, March 2015
DOI 10.1186/s13073-015-0149-z
Pubmed ID
Authors

Agata Maciejak, Marek Kiliszek, Marcin Michalak, Dorota Tulacz, Grzegorz Opolski, Krzysztof Matlak, Slawomir Dobrzycki, Agnieszka Segiet, Monika Gora, Beata Burzynska

Abstract

Heart failure (HF) is the most common cause of morbidity and mortality in developed countries. Here, we identify biologically relevant transcripts that are significantly altered in the early phase of myocardial infarction and are associated with the development of post-myocardial infarction HF. We collected peripheral blood samples from patients with ST-segment elevation myocardial infarction (STEMI): n = 111 and n = 41 patients from the study and validation groups, respectively. Control groups comprised patients with a stable coronary artery disease and without a history of myocardial infarction. Based on plasma NT-proBNP level and left ventricular ejection fraction parameters the STEMI patients were divided into HF and non-HF groups. Microarrays were used to analyze mRNA levels in peripheral blood mononuclear cells (PBMCs) isolated from the study group at four time points and control group. Microarray results were validated by RT-qPCR using whole blood RNA from the validation group. Samples from the first three time points (admission, discharge, and 1 month after AMI) were compared with the samples from the same patients collected 6 months after AMI (stable phase) and with the control group. The greatest differences in transcriptional profiles were observed on admission and they gradually stabilized during the follow-up. We have also identified a set of genes the expression of which on the first day of STEMI differed significantly between patients who developed HF after 6 months of observation and those who did not. RNASE1, FMN1, and JDP2 were selected for further analysis and their early up-regulation was confirmed in HF patients from both the study and validation groups. Significant correlations were found between expression levels of these biomarkers and clinical parameters. The receiver operating characteristic (ROC) curves indicated a good prognostic value of the genes chosen. This study demonstrates an altered gene expression profile in PBMCs during acute myocardial infarction and through the follow-up. The identified gene expression changes at the early phase of STEMI that differentiated the patients who developed HF from those who did not could serve as a convenient tool contributing to the prognosis of heart failure.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 2%
Unknown 54 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 20%
Student > Ph. D. Student 9 16%
Student > Doctoral Student 6 11%
Student > Bachelor 6 11%
Student > Master 6 11%
Other 5 9%
Unknown 12 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 12 22%
Medicine and Dentistry 12 22%
Agricultural and Biological Sciences 7 13%
Immunology and Microbiology 2 4%
Chemistry 2 4%
Other 5 9%
Unknown 15 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 10 January 2016.
All research outputs
#4,707,896
of 22,837,982 outputs
Outputs from Genome Medicine
#930
of 1,442 outputs
Outputs of similar age
#59,415
of 261,626 outputs
Outputs of similar age from Genome Medicine
#12
of 18 outputs
Altmetric has tracked 22,837,982 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,442 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.7. This one is in the 34th percentile – i.e., 34% 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 261,626 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.