Causal role of immune cells in major depressive disorder and bipolar disorder: Mendelian randomization (MR) study.

BACKGROUND: Major depressive disorder (MDD) and bipolar disorder (BD) are prevalent psychiatric conditions linked to inflammatory processes. However, it is unclear whether associations of immune cells with these disorders are likely to be causal. METHODS: We used two-sample Mendelian randomization (MR) approach to investigate the relationship between 731 immune cells and the risk of MDD and BD. Rigorous sensitivity analyses are conducted to assess the reliability, heterogeneity, and horizontal pleiotropy of the findings. RESULTS: Genetically-predicted CD27 on IgD+ CD38- unswitched memory B cell (inverse variance weighting (IVW): odds ratio (OR) [95 %]: 1.017 [1.007 to 1.027], p = 0.001), CD27 on IgD+ CD24+ B cell (IVW: OR [95 %]: 1.021 [1.011 to 1.031], p = 4.821E-05) and other 12 immune cells were associated with increased risk of MDD in MR, while HLA DR++ monocyte %leukocyte (IVW: OR [95 %]: 0.973 [0.948 to 0.998], p = 0.038), CD4 on Central Memory CD4+ T cell (IVW: OR [95 %]: 0.979 [0.963 to 0.995], p = 0.011) and other 13 immune cells were associated with decreased risk of MDD in MR. Additionally, CD33+ HLA DR+ Absolute Count (IVW: OR [95 %]: 1.022[1.007 to 1.036], p = 0.007), CD28+ CD45RA- CD8+ T cell %T cell (IVW: OR [95 %]: 1.024 [1.008 to 1.041], p = 0.004) and other 18 immune cells were associated with increased risk of BD in MR, while CD62L on CD62L+ myeloid Dendritic Cell (IVW: OR [95 %]: 0.926 [0.871 to 0.985], p = 0.014), IgD- CD27- B cell %lymphocyte (IVW: OR [95 %]: 0.918 [0.880 to 0.956], p = 4.654E-05) and other 13 immune cells were associated with decreased risk of BD in MR. CONCLUSIONS: This MR study provides robust evidence supporting a causal relationship between immune cells and the susceptibility to MDD and BD, offering valuable insights for future clinical investigations. Experimental studies are also required to further examine causality, mechanisms, and treatment potential for these immune cells for MDD and BD.

Artificial intelligence in psychiatry research, diagnosis, and therapy.

Psychiatric disorders are now responsible for the largest proportion of the global burden of disease, and even more challenges have been seen during the COVID-19 pandemic. Artificial intelligence (AI) is commonly used to facilitate the early detection of disease, understand disease progression, and discover new treatments in the fields of both physical and mental health. The present review provides a broad overview of AI methodology and its applications in data acquisition and processing, feature extraction and characterization, psychiatric disorder classification, potential biomarker detection, real-time monitoring, and interventions in psychiatric disorders. We also comprehensively summarize AI applications with regard to the early warning, diagnosis, prognosis, and treatment of specific psychiatric disorders, including depression, schizophrenia, autism spectrum disorder, attention-deficit/hyperactivity disorder, addiction, sleep disorders, and Alzheimer's disease. The advantages and disadvantages of AI in psychiatry are clarified. We foresee a new wave of research opportunities to facilitate and improve AI technology and its long-term implications in psychiatry during and after the COVID-19 era.