Advancing depression management through biomarker discovery with a focus on genetic and epigenetic aspects: a comprehensive study on neurobiological, neuroendocrine, metabolic, and inflammatory pathways
Open accessAbstract
Introduction: Depression is a pervasive global health issue, affecting millions worldwide and causing significant disability. Despite its prevalence, current diagnostic and treatment approaches often yield suboptimal outcomes. The complexity of depression, characterized by diverse causes and symptoms, highlights the urgent need for advanced diagnostic tools and personalized therapies. Biomarkers, particularly genetic and epigenetic depression biomarkers, offer promise in uncovering the biological mechanisms underlying depression, potentially revolutionizing its management. Aim: Primary aim: To identify biomarkers associated with depressive disorders, with a focus on genetic and epigenetic biomarkers. Secondary aim: To optimize the current classification of biomarkers associated with different types of depressive disorders, with a focus on genetic and epigenetic biomarkers. Methods: We integrated findings with strategic keywords extracted from relevant studies, conducting a thorough literature review across the Google Scholar, PubMed, and Web of Science databases. Lastly, final reference inclusion had stringent criteria: recent, diverse peer-reviewed articles in English, all study designs, ensuring up-to-date coverage of genetic and epigenetic depression biomarker research. Results: The review reveals the classification of genetic and epigenetic biomarkers in regard to the type of biomarker, the system of the human body it derives from, and the sampling entity. All of the findings show promise in diagnosing depression, with the potential of predicting treatment outcomes and guiding personalized therapeutic approaches. We defined the significant correlations between genetic and epigenetic biomarker profiles and clinical parameters such as symptom severity and treatment response, thereby enhancing diagnostic accuracy and guiding treatment strategies tailored to individual patient needs across diverse depressive subtypes and treatment responses. Conclusion: Identifying biomarkers associated with depressive disorders, with a focus on genetic and epigenetic biomarkers, represents a critical step toward improving diagnostic precision and treatment efficacy. By elucidating the complex biological underpinnings of depression, this study contributes to the development of targeted therapies that address the diverse needs of individuals affected by this debilitating group of disorders. Future research should focus on validating these genetic and epigenetic biomarkers in larger cohorts and clinical trials to facilitate their clinical implementation and enhance patient outcomes.
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Peripheral blood mononuclear cells (PBMCs) and other circulating molecules can partially reflect central epigenetic states.
“Evidence indicates that peripheral blood mononuclear cells (PBMCs) and other circulating molecules can partially reflect central epigenetic states, supporting patient stratification, severity assessment, treatment prediction, and personalized care (Milic et al., 2025; Roy et al., 2017).”
From Histone modifications and depression: epigenetic mechanisms, therapeutic targets, and translational outlook (2026) · cites this paper as Milic et al., 2025
The Discussion says peripheral biomarkers can reflect depression pathophysiology, and §4.10 describes potential uses of epigenetic markers for treatment prediction and personalized care. But the cited passages do not establish that PBMCs or other circulating molecules reflect central epigenetic states. Section 4.15 instead cautions that inferring central changes from peripheral biomarkers is a major limitation; page numbers were not available in our copy. (LLM, conf=0.84)
Experimental — accuracy not yet measuredInflammatory markers such as CRP and IL-6, as well as neurotrophins including BDNF, NGF, and VEGF, are closely associated with depression.
“Inflammatory markers such as CRP and IL-6, as well as neurotrophins including BDNF, NGF, and VEGF, are closely associated with depression (Milic et al., 2025).”
From Histone modifications and depression: epigenetic mechanisms, therapeutic targets, and translational outlook (2026) · cites this paper as Milic et al., 2025
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Jha, M. K., & Trivedi, M. H. (2023) · Psychiatric Clinics of North America · doi:10.1016/s0193-953x(23)00042-4 · Cited by 7 · see citing works
Maes, M. H. J., Rachayon, M., Jirakran, K., et al. (2023) · medRxiv · doi:10.1101/2023.06.01.23290858 · Cited by 5 · see citing works
DHEA and response to antidepressant treatment: A Mendelian Randomization analysis
Souza‐Teodoro, L. H., Davies, N. M., Warren, H. R., Andrade, L. H., & de Carvalho, L. A. (2024) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2024.02.049 · Cited by 5 · see citing works
Eating Disorder and Quality of Life
Milić, J., Stankic, D., & Stefanovic, D. (2023) · Springer eBooks · doi:10.1007/978-3-031-16691-4_21 · Cited by 3 · see citing works
Examining Potential Biomarkers for Depression Diagnosis: A Literature Review
Dhillon, G. K., & Gangaram, S. C. (2024) · Undergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal · doi:10.26685/urncst.621 · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [14]Singhal N. Stigma, Prejudice and Discrimination Against People with Mental Illness: A Physician Review; American Psychiatric Association Portal of Patients and Families. March 2024 Available online: https://www.psychiatry.org/patients-families/stigma-and-discrimination (accessed on 15 July 2024)
Cited by
Sorted by citations
Lv, L.-Z., Wang, Z.-D., Ren, J.-J., Li, L.-H., Liu, X.-B., Li, J.-L., Zhu, H., Jiang, B., Han, Y.-P., Zhou, X.-M., et al. (2026) · Frontiers in Genetics · doi:10.3389/fgene.2025.1722453 · Cited by 7 · see citing works
Chehadi, A. C., Pereira de Lima, E., Detregiachi, C. R. P., Santos de Argollo Haber, R., Catharin, V. M. C. S., Fornari Laurindo, L., Engracia Valenti, V., Machado Galhardi, C., Tanaka, M., & Maria Barbalho, S. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27010465 · Cited by 8 · see citing works
- Authors
- Milic, J., Jovic, S., & Sapic, R.
- Affiliations
- Institute of Public Health of Serbia “Dr Milan Jovanovic Batut”, Dr. Subotica Starijeg 6, 11000 Belgrade, Serbia
- Faculty of Security Studies, University of Belgrade, Gospodara Vucica 40, 11000 Belgrade, Serbia
- Faculty of Health Studies, University of Bijeljina, 76300 Bijeljina, Republika Srpska, Bosnia and Herzegovina
- Venue
- Genes
- Publisher
- MDPI AG
- Published
- 2025-04-25
- Volume
- 16
- Issue
- 5
- Pages
- 487
- ISSN
- 2073-4425 (ISSN-L)
- PMC
- PMC12111755
- OpenAlex
- W4409806570
- Cited by
- 19
- References
- 94
- Citations by year
- 2026: 14 · 2025: 5
- FWCI
- 2.56
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Genes (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Neuroscience › Biological Psychiatry › Tryptophan and brain disorders
- Keywords
- depression, genetic biomarkers, epigenetic biomarkers, biomarker classification, personalized treatment, treatment response prediction, symptom severity, neuroendocrine pathways, neurobiological pathways, metabolic pathways, inflammatory signaling, diagnostic accuracy
- MeSH terms
- Depression, Depressive Disorder, Humans, Inflammation, Neurosecretory Systems, Biomarkers, Epigenesis, Genetic, Epigenomics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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