ArticlePsychiatry investigation2025
The Clinical Utility of Biomarkers in Diagnosing Major Depressive Disorder in Adults: A Systematic Review of Literature From 2013 to 2023.
Article in Psychiatry investigation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Aberrations in Peripheral Blood Neuron-Specific Enolase Levels in Depression: A Systematic Review and Meta-Analysis.Depression and anxiety · 2026Pooled it
- Knowledge Graph and Large Language Model-Based Analysis of fMRI Brain Functional Neuroimaging Research.Bioengineering (Basel, Switzerland) · 2026Article
- Special Issue: Molecular Research on Mental Disorders 2.0.International journal of molecular sciences · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
objectiveThe variety and efficacy of biomarkers available that may be used objectively to diagnose major depressive disorder (MDD) in adults are unclear. This systematic review aims to identify and evaluate the variety of objective markers used to diagnose MDD in adults.
methodsThe search strategy was applied via PubMed and PsycINFO over the past 10 years (2013-2023) to capture the latest available evidence supporting the use of biomarkers to diagnose MDD. Data was reported through narrative synthesis.
resultsForty-two studies were included in the review. Findings were synthesised based on the following measures: blood, neuroimaging/neurophysiology, urine, dermatological, auditory, vocal, cerebrospinal fluid and combinatory-and evaluated based on its sensitivity/specificity and area under the curve values. The best predictors of blood (MYT1 gene), neuroimaging/neurophysiological (5-HT1A auto-receptor binding in the dorsal and median raphe), urinary (combined albumin, AMBP, HSPB, APOA1), cerebrospinal fluid-based (neuron specific enolase, microRNA) biomarkers were found to be closely linked to the pathophysiology of MDD.
conclusionA large variety of biomarkers were available to diagnose MDD, with the best performing biomarkers intrinsically related to the pathophysiology of MDD. Potential for future research lies in investigating the joint sensitivity of the best performing biomarkers identified via machine learning methods and establishing the causal effect between these biomarkers and MDD.
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Registered trials
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.