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Molecular serum signature of treatment resistant depression

Overview of attention for article published in Psychopharmacology, June 2016
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

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1 tweeter
1 patent


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48 Mendeley
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Molecular serum signature of treatment resistant depression
Published in
Psychopharmacology, June 2016
DOI 10.1007/s00213-016-4348-0
Pubmed ID

Tillmann Ruland, Man K. Chan, Pawel Stocki, Laura Grosse, Matthias Rothermundt, Jason D. Cooper, Volker Arolt, Sabine Bahn


A substantial number of patients suffering from major depressive disorder (MDD) do not respond to multiple trials of anti-depressants, develop a chronic course of disease and become treatment resistant. Most of the studies investigating molecular changes in treatment-resistant depression (TRD) have only examined a limited number of molecules and genes. Consequently, biomarkers associated with TRD are still lacking. This study aimed to use recently advanced high-throughput proteomic platforms to identify peripheral biomarkers of TRD defined by two staging models, the Thase and Rush staging model (TRM) and the Maudsley Staging Model (MSM). Serum collected from an inpatient cohort of 65 individuals suffering from MDD was analysed using two different mass spectrometric-based platforms, label-free liquid chromatography mass spectrometry (LC-MS(E)) and selective reaction monitoring (SRM), as well as a multiplex bead based assay. In the LC-MS(E) analysis, proteins involved in the acute phase response and complement activation and coagulation were significantly different between the staging groups in both models. In the multiplex bead-based assay analysis TNF-α levels (log(odds) = -4.95, p = 0.045) were significantly different in the TRM comparison. Using SRM, significant changes of three apolipoproteins A-I (β = 0.029, p = 0.035), M (β = -0.017, p = 0.009) and F (β = -0.031, p = 0.024) were associated with the TRM but not the MSM. Overall, our findings suggest that proteins, which are involved in immune and complement activation, may represent potential biomarkers that could be used by clinicians to identify high-risk patients. Nevertheless, given that the molecular changes between the staging groups were subtle, the results need to be interpreted cautiously.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 19%
Student > Ph. D. Student 7 15%
Researcher 6 13%
Student > Bachelor 5 10%
Other 2 4%
Other 7 15%
Unknown 12 25%
Readers by discipline Count As %
Medicine and Dentistry 8 17%
Neuroscience 7 15%
Psychology 7 15%
Biochemistry, Genetics and Molecular Biology 3 6%
Agricultural and Biological Sciences 2 4%
Other 5 10%
Unknown 16 33%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 16 October 2018.
All research outputs
of 14,834,764 outputs
Outputs from Psychopharmacology
of 4,545 outputs
Outputs of similar age
of 262,380 outputs
Outputs of similar age from Psychopharmacology
of 43 outputs
Altmetric has tracked 14,834,764 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 4,545 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has gotten more attention than average, scoring higher than 67% 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 262,380 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 67% of its contemporaries.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.