Evidence map›Paper›PMID 41134434›Full record

ReviewThe Psychiatric quarterly2025

Towards Objective Major Depressive Disorder Detection: a Systematic Review and Meta-Analysis of Diagnostic Biomarkers.

Zain-Ul-Abideen Gulbaz, Shaper Mirza, Sadiq Naveed, Muhammad Waqar Azeem, Nusrat Husain, M Imran Cheema

Abstract readReview
PubMed Publisher
In one paragraph

Review in The Psychiatric quarterly, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

6 authors.

Zain-Ul-Abideen GulbazElectrical Engineering Department, Lahore University of Management Sciences, Lahore, Pakistan.
Shaper MirzaLife Sciences Department, Lahore University of Management Sciences, Lahore, Pakistan.
Sadiq NaveedDepartment of Psychiatry, Eastern Connecticut Health Network, Manchester, USA.
Muhammad Waqar AzeemDepartment of Psychiatry, Sidra Medicine, Weill Cornell Medicine Qatar, Doha, Qatar.
Nusrat HusainThe University of Manchester, Manchester, UK.
M Imran CheemaElectrical Engineering Department, Lahore University of Management Sciences, Lahore, Pakistan. imran.cheema@lums.edu.pk.ORCID http://orcid.org/0000-0002-9415-4291

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite extensive research, identifying reliable diagnostic biomarkers for MDD remains an open question. This systematic review quantifies the most promising diagnostic biomarkers for major depressive disorder (MDD) that can be utilized in clinical settings. We performed a comprehensive electronic search across PubMed, PsycINFO, ScienceDirect, and Google Scholar, covering the literature from January 2013 to December 2023. Inclusion criteria consisted of studies with human participants ages 18 and above, focusing on diagnostic biomarkers in bodily fluids and comparing patients with MDD with healthy controls. Exclusion criteria included comorbid physical or psychological illnesses, animal studies, and neuroimaging studies. We quantified 312 diagnostic biomarkers of MDD from 175 selected studies and found that interleukin-6 (IL-6), brain-derived neurotrophic factor (BDNF), cortisol, C-reactive protein (CRP), and tumor necrosis factor-alpha (TNF-α) were the most frequently appearing biomarkers in the selected studies. Meta-analyses of these top five biomarkers indicated that IL-6, BDNF, cortisol, and TNF-α were significantly associated with MDD, but further validation in different populations needs more work. Future research may focus on developing panels of diagnostic biomarkers and standardizing methodologies for diverse populations to enhance the diagnostic accuracy for MDD.

Indexed as

BDNFCortisolDiagnostic biomarkersIL-6Major depressive disorder

Identifiers

What Socratic holds

Textmetadata
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 Socratic graph.