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Biomarkers for depression: recent insights, current challenges and future prospects

Overview of attention for article published in Neuropsychiatric Disease and Treatment, May 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 (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

news
2 news outlets
twitter
23 tweeters
patent
1 patent
facebook
4 Facebook pages
googleplus
1 Google+ user

Citations

dimensions_citation
162 Dimensions

Readers on

mendeley
386 Mendeley
citeulike
2 CiteULike
Title
Biomarkers for depression: recent insights, current challenges and future prospects
Published in
Neuropsychiatric Disease and Treatment, May 2017
DOI 10.2147/ndt.s114542
Pubmed ID
Authors

Rebecca Strawbridge, Allan H Young, Anthony J Cleare

Abstract

A plethora of research has implicated hundreds of putative biomarkers for depression, but has not yet fully elucidated their roles in depressive illness or established what is abnormal in which patients and how biologic information can be used to enhance diagnosis, treatment and prognosis. This lack of progress is partially due to the nature and heterogeneity of depression, in conjunction with methodological heterogeneity within the research literature and the large array of biomarkers with potential, the expression of which often varies according to many factors. We review the available literature, which indicates that markers involved in inflammatory, neurotrophic and metabolic processes, as well as neurotransmitter and neuroendocrine system components, represent highly promising candidates. These may be measured through genetic and epigenetic, transcriptomic and proteomic, metabolomic and neuroimaging assessments. The use of novel approaches and systematic research programs is now required to determine whether, and which, biomarkers can be used to predict response to treatment, stratify patients to specific treatments and develop targets for new interventions. We conclude that there is much promise for reducing the burden of depression through further developing and expanding these research avenues.

Twitter Demographics

The data shown below were collected from the profiles of 23 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 386 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 386 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 66 17%
Student > Ph. D. Student 65 17%
Student > Bachelor 49 13%
Researcher 39 10%
Student > Doctoral Student 25 6%
Other 62 16%
Unknown 80 21%
Readers by discipline Count As %
Medicine and Dentistry 59 15%
Neuroscience 51 13%
Psychology 45 12%
Biochemistry, Genetics and Molecular Biology 36 9%
Agricultural and Biological Sciences 24 6%
Other 74 19%
Unknown 97 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 40. 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 25 June 2020.
All research outputs
#728,845
of 20,009,828 outputs
Outputs from Neuropsychiatric Disease and Treatment
#77
of 2,806 outputs
Outputs of similar age
#17,801
of 280,237 outputs
Outputs of similar age from Neuropsychiatric Disease and Treatment
#3
of 74 outputs
Altmetric has tracked 20,009,828 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 2,806 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one has done particularly well, scoring higher than 97% 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 280,237 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 93% of its contemporaries.
We're also able to compare this research output to 74 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.