Evidence map›Paper›PMID 34477887›Full record

ArticlePsychopharmacology2022

Resting state functional connectivity patterns as biomarkers of treatment response to escitalopram in patients with major depressive disorder.

Marieke A G Martens, Nicola Filippini, Catherine J Harmer, Beata R Godlewska

Open access · hybridAbstract read
In one paragraph

Article in Psychopharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 3 pooled it
3.1field-weighted citation impact, top 8% 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

24 citing papers in PubMed, 3 syntheses or guidelines pooled it, 47 citations in OpenAlex.

  1. Pooled it
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  5. Towards causal inference-based antidepressant selection with brain and blood biomarkers.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026
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  8. Resting-state functional connectivity of the default mode network as a predictor for escitalopram response in adolescents with depression.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026
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  15. Breakthroughs and challenges for generating brain network-based biomarkers of treatment response in depression.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024
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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

4 authors at 2 institutions in 1 country.

Marieke A G Martens *Department of Psychiatry, University of Oxford, Oxford, UK.
Nicola Filippini *Wellcome Center for Integrative Neuroimaging, University of Oxford, OX3 9DU, Oxford, UK.
Catherine J HarmerDepartment of Psychiatry, University of Oxford, Oxford, UK.
Beata R GodlewskaDepartment of Psychiatry, University of Oxford, Oxford, UK. beata.godlewska@psych.ox.ac.uk.
Wellcome Centre for Integrative Neuroimaging · GBUniversity of Oxford · GB

Funding

Medical Research Council MR/K022202/1
6 · The paper itself

Abstract

rationalWith no available response biomarkers, matching an appropriate antidepressant to an individual can be a lengthy process. Improving understanding of processes underlying treatment responsivity in depression is crucial for facilitating work on response biomarkers.

objectivesTo identify differences in patterns of pre-treatment resting-state functional connectivity (rsFC) that may underlie response to antidepressant treatment.

methodsAfter a baseline MRI scan, thirty-four drug-free patients with depression were treated with an SSRI escitalopram 10 mg daily for 6 weeks; response was defined as ≥ 50% decrease in Hamilton Depression Rating Scale (HAMD) score. Thirty-one healthy controls had a baseline clinical assessment and scan. Healthy participants did not receive treatment.

resultsTwenty-one (62%) of patients responded to escitalopram. Treatment responsivity was associated with enhanced rsFC of the right fronto-parietal network (FPN)-with the posterior DMN, somatomotor network (SMN) and somatosensory association cortex. The lack of treatment response was characterized by reduced rsFC: of the bilateral FPN with the contralateral SMN, of the right FPN with the posterior DMN, and of the extended sensorimotor auditory area with the inferior parietal lobule (IPL) and posterior DMN. Reduced rsFC of the posterior DMN with IPL was seen in treatment responders, although only when compared with HC.

conclusionsThe study supports the role of resting-state networks in response to antidepressant treatment, and in particular the central role of the frontoparietal and default mode networks.

Indexed as

Major Depressive DisorderBiomarkersBrain MappingEscitalopramHumansMagnetic Resonance ImagingBiomarkersEscitalopramEscitalopramIndependent component analysisMajor depressive disorderResting-state fMRIResting-state networksTreatment biomarkersTreatment response

Identifiers

PMID34477887
PMCPMC9584978
OpenAlexW3196904352

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.