Evidence map›Paper›PMID 39343996›Full record

ArticleBJPsych open2024

Inflammatory biomarkers in depression: scoping review.

Walter Paganin, Sabrina Signorini

Abstract readScoping Review
In one paragraph

Article in BJPsych open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
–field-weighted citation impact
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

27 citing papers in PubMed.

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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

2 authors.

Walter PaganinSchool of Neuroscience, University of Tor Vergata, Italy.ORCID https://orcid.org/0000-0001-9007-0712
Sabrina SignoriniStudio Psicologia Signorini, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInflammation is increasingly recognised as a fundamental component of the pathophysiology of major depressive disorder (MDD), with a variety of inflammatory biomarkers playing pivotal roles. These markers are closely linked to both the severity of symptoms and the responsiveness to treatments in MDD.

aimsThis scoping review aims to explore the scientific literature investigating the complex relationships between inflammatory biomarkers and depression, by identifying new studies and critical issues in current research.

methodFollowing the PRISMA Extension for Scoping Reviews guidelines, we systematically searched databases including PubMed, Scopus, PsycINFO, Open Grey and Cochrane Library. Our search focused on articles published from 1 January 2020 to 1 May 2024. We included studies evaluating inflammatory biomarkers in adult patients with MDD, utilising observational and randomised controlled trial designs, and review studies.

resultsOur analysis examined 44 studies on the complex interplay between inflammation and its multiple effects on MDD. Significant associations between specific inflammatory biomarkers and depression severity were found, requiring cautious interpretation. We also highlight several methodological limitations in the current studies, which warrant caution in directly applying these findings to clinical practice. However, identified methodologies show potential for using these biomarkers as diagnostic tools or therapeutic targets, including anti-inflammatory interventions.

conclusionsThe findings emphasise the need for sophisticated, integrative research to understand inflammation's role in MDD. Future studies should identify specific biomarker panels for diagnosing depression and bridging peripheral biomarker measurements with central neuroinflammatory processes, leading to better diagnostic and treatment strategies.

Indexed as

biomarkersDepressionneuroinflammationpro-inflammatory cytokinesreview

Identifiers

PMID39343996
PMCPMC11536280

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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.