Evidence map›Paper›PMID 22990943›Full record

Trial reportNeuropsychopharmacology : official publication of the American College of Neuropsychopharmacology2013

Candidate genes expression profile associated with antidepressants response in the GENDEP study: differentiating between baseline 'predictors' and longitudinal 'targets'.

Annamaria Cattaneo, Massimo Gennarelli, Rudolf Uher, Gerome Breen, Anne Farmer, Katherine J Aitchison, Ian W Craig, Christoph Anacker, Patricia A Zunsztain, Peter McGuffin and 1 more

Open access · hybridAbstract readComparative StudyMulticenter StudyRandomized Controlled Trial
In one paragraph

Trial report in Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 190 papers, 13 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
190citing papers in PubMed, 13 pooled it
9.2field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

190 citing papers in PubMed, 13 syntheses or guidelines pooled it, 426 citations in OpenAlex.

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  5. Changes in RNA expression levels during antidepressant treatment: a systematic review.Journal of neural transmission (Vienna, Austria : 1996) · 2021
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  10. Genetic Contributions of Inflammation to Depression.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2017
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  20. Testing the predictive value of peripheral gene expression for nonremission following citalopram treatment for major depression.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2015
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130 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 3 countries.

Annamaria CattaneoDepartment of Biomedical Sciences and Biotechnology, Genetic and Biology Section, University of Brescia, Brescia, Italy.
Massimo Gennarelli
Rudolf Uher
Gerome Breen
Anne Farmer
Katherine J Aitchison
Ian W Craig
Christoph Anacker
Patricia A Zunsztain
Peter McGuffin
Carmine M Pariante
King's College London · GBUniversity of Brescia · IT

Funding

Medical Research Council G108/603Medical Research Council MR/J002739/1
6 · The paper itself

Abstract

To improve the 'personalized-medicine' approach to the treatment of depression, we need to identify biomarkers that, assessed before starting treatment, predict future response to antidepressants ('predictors'), as well as biomarkers that are targeted by antidepressants and change longitudinally during the treatment ('targets'). In this study, we tested the leukocyte mRNA expression levels of genes belonging to glucocorticoid receptor (GR) function (FKBP-4, FKBP-5, and GR), inflammation (interleukin (IL)-1α, IL-1β, IL-4, IL-6, IL-7, IL-8, IL-10, macrophage inhibiting factor (MIF), and tumor necrosis factor (TNF)-α), and neuroplasticity (brain-derived neurotrophic factor (BDNF), p11 and VGF), in healthy controls (n=34) and depressed patients (n=74), before and after 8 weeks of treatment with escitalopram or nortriptyline, as part of the Genome-based Therapeutic Drugs for Depression study. Non-responders had higher baseline mRNA levels of IL-1β (+33%), MIF (+48%), and TNF-α (+39%). Antidepressants reduced the levels of IL-1β (-6%) and MIF (-24%), and increased the levels of GR (+5%) and p11 (+8%), but these changes were not associated with treatment response. In contrast, successful antidepressant response was associated with a reduction in the levels of IL-6 (-9%) and of FKBP5 (-11%), and with an increase in the levels of BDNF (+48%) and VGF (+20%)-that is, response was associated with changes in genes that did not predict, at the baseline, the response. Our findings indicate a dissociation between 'predictors' and 'targets' of antidepressant responders. Indeed, while higher levels of proinflammatory cytokines predict lack of future response to antidepressants, changes in inflammation associated with antidepressant response are not reflected by all cytokines at the same time. In contrast, modulation of the GR complex and of neuroplasticity is needed to observe a therapeutic antidepressant effect.

Indexed as

AdultAgedAntidepressive AgentsDepressive DisorderDrug Delivery SystemsFemaleGenetic Association StudiesGenome-Wide Association StudyHumansInterleukin-1betaIntramolecular OxidoreductasesLongitudinal StudiesMacrophage Migration-Inhibitory FactorsMaleMiddle AgedPredictive Value of TestsAntidepressive AgentsInterleukin-1betaIntramolecular OxidoreductasesMacrophage Migration-Inhibitory FactorsMIF protein, humanTumor Necrosis Factor-alpha

Identifiers

PMID22990943
PMCPMC3547188
OpenAlexW2136812855

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.