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Circulating brain-enriched microRNAs as novel biomarkers for detection and differentiation of neurodegenerative diseases

Overview of attention for article published in Alzheimer's Research & Therapy, November 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

news
5 news outlets
blogs
1 blog
twitter
3 tweeters
patent
3 patents

Citations

dimensions_citation
105 Dimensions

Readers on

mendeley
223 Mendeley
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Title
Circulating brain-enriched microRNAs as novel biomarkers for detection and differentiation of neurodegenerative diseases
Published in
Alzheimer's Research & Therapy, November 2017
DOI 10.1186/s13195-017-0316-0
Pubmed ID
Authors

Kira S. Sheinerman, Jon B. Toledo, Vladimir G. Tsivinsky, David Irwin, Murray Grossman, Daniel Weintraub, Howard I. Hurtig, Alice Chen-Plotkin, David A. Wolk, Leo F. McCluskey, Lauren B. Elman, John Q. Trojanowski, Samuil R. Umansky

Abstract

Minimally invasive specific biomarkers of neurodegenerative diseases (NDs) would facilitate patient selection and disease progression monitoring. We describe the assessment of circulating brain-enriched microRNAs as potential biomarkers for Alzheimer's disease (AD), frontotemporal dementia (FTD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS). In this case-control study, the plasma samples were collected from 250 research participants with a clinical diagnosis of AD, FTD, PD, and ALS, as well as from age- and sex-matched control subjects (n = 50 for each group), recruited from 2003 to 2015 at the University of Pennsylvania Health System, including the Alzheimer's Disease Center, the Parkinson's Disease and Movement Disorders Center, the Frontotemporal Degeneration Center, and the Amyotrophic Lateral Sclerosis Clinic. Each group was randomly divided into training and confirmation sets of equal size. To evaluate the potential of circulating microRNAs enriched in specific brain regions affected by NDs and present in synapses as biomarkers of NDs, the levels of 37 brain-enriched and inflammation-associated microRNAs in the plasma of all participants were measured using individual qRT-PCR. A "microRNA pair" approach was used for data normalization. MicroRNA pairs and their combinations (classifiers) capable of differentiating NDs from control and from each other were defined using independently and jointly analyzed training and confirmation datasets. AD, PD, FTD, and ALS are differentiated from control with accuracy of 0.89, 0.90, 0.88, and 0.83 (AUCs, 0.96, 0.96, 0.94, and 0.93), respectively; NDs are differentiated from each other with accuracy ranging from 0.77 (AUC, 0.87) for AD vs. FTD to 0.93 (AUC, 0.98) for AD vs. ALS. The data further indicate sex dependence of some microRNA markers. The average increase in accuracy in distinguishing ND from control for all and male/female groups is 0.06; the largest increase is for ALS, from 0.83 for all participants to 0.92/0.98 for male/female participants. The work presented here suggests the possibility of developing microRNA-based diagnostics for detection and differentiation of NDs. Larger multicenter clinical studies are needed to further evaluate circulating brain-enriched microRNAs as biomarkers for NDs and to investigate their association with other ND biomarkers in clinical trial settings.

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 223 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 223 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 36 16%
Student > Ph. D. Student 32 14%
Student > Bachelor 22 10%
Student > Master 21 9%
Unspecified 19 9%
Other 37 17%
Unknown 56 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 39 17%
Neuroscience 30 13%
Agricultural and Biological Sciences 23 10%
Medicine and Dentistry 20 9%
Unspecified 19 9%
Other 33 15%
Unknown 59 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 50. 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 15 September 2022.
All research outputs
#707,535
of 22,691,736 outputs
Outputs from Alzheimer's Research & Therapy
#81
of 1,202 outputs
Outputs of similar age
#16,746
of 330,046 outputs
Outputs of similar age from Alzheimer's Research & Therapy
#3
of 19 outputs
Altmetric has tracked 22,691,736 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,202 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 24.2. This one has done particularly well, scoring higher than 93% 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 330,046 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.