Development of machine-learning-driven signatures for diagnosing and monitoring therapeutic response in major depressive disorder using integrated immune cell profiles and plasma cytokines
Year: 2024
Type: article
Abstract: Our diagnostic model derived from CyTOF and cytokines demonstrates high diagnostic value. However, relying solely on immune cells may not provide optimal predictions for antidepressant treatment response. In contrast, leveraging cytokines has proven valuable, leading to the construction of a seven-factor treatment response prediction model. Importantly, we observed that several significantly altered cytokines in MDD can normalize following antidepressant treatment, indicating their potential as therapeutic targets.
Source: Theranostics
DOI: 10.7150/thno.102602
Authors: Shen He, Faming Zhao, Guangqiang Sun, Yue Shi, Tianlun Xu, Yu Zhang, Siyuan Li, Linna Zhang, Xingkun Chu, Chen Du, Dabing Yang, Jing Zhang, Changrong Ge, Jingjing Huang, Zuoquan Xie, Huafang Li
Institutions: Shanghai Jiao Tong University, Shanghai Mental Health Center, Huazhong University of Science and Technology, Chinese Academy of Sciences, Shanghai Institute of Materia Medica, State Key Laboratory of Drug Research, Henan Psychiatric Hospital, Henan Medical University, Tongji University, Shanghai Key Laboratory of Psychotic Disorders
Language: English
Subfield: Pharmacology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,671
OpenAlex ID: W4403987398