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Personalized Medicine Using Neuroimmunological Biomarkers in Depressive Disorders

Authors
Chi, SuhyukLee, Moon-Soo
Issue Date
Feb-2021
Publisher
MDPI
Keywords
cytokines; neuroimmunology; depression; machine learning
Citation
JOURNAL OF PERSONALIZED MEDICINE, v.11, no.2, pp.1 - 14
Indexed
SCIE
SCOPUS
Journal Title
JOURNAL OF PERSONALIZED MEDICINE
Volume
11
Number
2
Start Page
1
End Page
14
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/129258
DOI
10.3390/jpm11020114
ISSN
2075-4426
Abstract
Major depressive disorder (MDD) is associated with increased suicidal risk and reduced productivity at work. Neuroimmunology, the study of the immune system and nervous system, provides further insight into the pathogenesis and outcome of MDD. Cytokines are the main modulators of neuroimmunology, and their levels are somewhat entangled in depressive disorders as they affect depressive symptoms and are affected by antidepressant treatment. The use of cytokine-derived medication as a treatment option for MDD is currently a topic of interest. Although not very promising, cytokines are also considered as possible prognostic or diagnostic markers for depression. The machine learning approach is a powerful tool for pattern recognition and has been used in psychiatry for finding useful patterns in data that have translational meaning and can be incorporated in daily clinical practice. This review focuses on the current knowledge of neuroimmunology and depression and the possible use of machine learning to widen our understanding of the topic.
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