TY - JOUR
T1 - The Clinical Utility of Biomarkers in Diagnosing Major Depressive Disorder in Adults
T2 - A Systematic Review of Literature From 2013 to 2023
AU - Ang, Shi Han
AU - Ho, Roger C.
AU - McIntyre, Roger S.
AU - Zhang, Zhisong
AU - Chang, Soon Kiat
AU - Teopiz, Kayla M.
AU - Ho, Cyrus S.H.
N1 - Publisher Copyright:
© 2025 Korean Neuropsychiatric Association.
PY - 2025/4
Y1 - 2025/4
N2 - Objective The 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. Methods The 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. Results Forty-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. Conclusion A 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.
AB - Objective The 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. Methods The 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. Results Forty-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. Conclusion A 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.
KW - Biomarker
KW - Blood
KW - Depression
KW - Machine learning
KW - Neuroimaging
KW - Neurophysiology
UR - https://www.webofscience.com/wos/woscc/full-record/WOS:001469639900001
UR - https://openalex.org/W4409400041
UR - https://www.scopus.com/pages/publications/105003928529
U2 - 10.30773/pi.2024.0152
DO - 10.30773/pi.2024.0152
M3 - Review article
SN - 1738-3684
VL - 22
SP - 341
EP - 356
JO - Psychiatry Investigation
JF - Psychiatry Investigation
IS - 4
ER -