Personalized Medicine Using Neuroimmunological Biomarkers in Depressive Disorders

• Published in: Journal of personalized medicine Vol. 11; no. 2; p. 114
• Main Authors: Chi, Suhyuk, Lee, Moon-Soo
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 10-02-2021; MDPI
• Subjects: Artificial intelligence; Biomarkers; Bipolar disorder; Brain research; Cytokines; Dopamine; Enzymes; Immune system; Inflammation; Learning algorithms; Machine learning; Mental depression; Mental disorders; Nervous system; Neuroimmunology; Neuromodulation; Pattern recognition; Precision medicine; Review; Schizophrenia; Serotonin; Social research; Suicides & suicide attempts; Tumor necrosis factor-TNF; neuroimmunology; cytokines; depression; machine learning
• ISSN: 2075-4426; 2075-4426
• DOI: 10.3390/jpm11020114

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.