DPA-714 and FDG PET/MRI in Depression

Depression, a common psychological disorder, is characterized by persistent low mood, loss of interest, and anhedonia, leading to significant dysfunctions and a high suicide risk. Its pathogenesis remains challenging, with recent focus on neuroinflammation-a chronic immune response in the central nervous system-as a potential contributor. PET imaging, using tracers like 18F-FDG and \[18F\]DPA-714, can visualize metabolic and neuroinflammatory changes. Combining these two tracers can explore the correlation between neuroinflammation and glucose metabolism in depression, further elucidating its possible mechanisms. We hypothesize that microglial activation in depression, especially in major gray matter regions of interest (prefrontal cortex, anterior cingulate cortex, and insula) and 12 additional regions and subregions, will show higher TSPO levels and increased glucose metabolism compared to the control group.

Depression is a common psychological disorder caused by various factors, characterized by significant and persistent low mood, loss of interest, and anhedonia as core symptoms, leading to physical, psychological, and social dysfunctions, with a high risk of suicide. The pathogenesis of depression remains a challenging topic in the medical field. Imaging studies are crucial for exploring the pathogenesis of depression. Recently, neuroinflammation has gained significant attention regarding the pathophysiological mechanisms of depression. Neuroinflammation, a chronic inflammatory response of the immune system in the central nervous system, may be related to the onset and progression of depression. PET is an imaging method that uses radioactive tracers to visualize physiological activities and metabolic processes in the body. 18F-FDG-PET can reflect neuronal degeneration and the reduction in the number and function of protrusions in vitro, directly indicating lesion sites and involvement. Therefore, PET/MRI brain metabolism imaging can uncover possible pathogenesis and explore unique brain network characteristics from a molecular imaging perspective. PET studies can depict local functional metabolism and neurochemical changes in the brain through radionuclide labeling. \[18F\]DPA-714, a PET tracer, is a high-affinity ligand for the translocator protein (TSPO), a mitochondrial outer membrane protein expressed in activated microglia and macrophages in the brain, serving as a marker of neuroinflammation. As a TSPO radioligand, DPA-714 can explore in vivo changes in neuroinflammation. Combining these two tracers can explore the correlation between neuroinflammation and glucose metabolism in depression, further elucidating its possible mechanisms. This study will collect data from patients diagnosed with recurrent depression and first-episode depression in the Psychosomatic Sleep Department and Neurology Department of the First Affiliated Hospital of Dalian Medical University. Healthy individuals who underwent "DPA-714 or FDG imaging PET/MRI" physical examinations in the PET/CT room of our hospital will also be included. According to the inclusion and exclusion criteria, the groups will consist of 25 cases of recurrent depression, 25 cases of first-episode depression, and 20 healthy controls. Additionally, all three groups will undergo neuropsychological assessments, including Hamilton Anxiety Scale, Hamilton Depression Scale, Mini-mental State Examination, Montreal Cognitive Assessment, Pittsburgh Sleep Quality Index Scale, and other related cognitive, sleep, and emotional scales. We used DPA-714 imaging agent PET/MRI to scan the whole brain, selecting major gray matter regions of interest (prefrontal cortex, anterior cingulate cortex, and insula) and 12 additional regions and subregions to measure TSPO values. The patients with recurrent depression and first episode depression were compared with the normal control group to explore their characteristics. Moreover, through the relationship between TSPO values and neuropsychological scores, the correlation between TSPO values and depression severity was explored. The statistical method we use is that SPSS26.0 statistical software (IBM, New York, United States) was used to conduct statistical analysis on the basic demographic data of each group. Normal test and homogeneity test of variance were performed on the data. Continuous variables conforming to normal distribution were expressed in the form of mean ± standard deviation (±s). Samples that do not conform to a normal distribution and variables represented as graded data are described by the median (interquartile range). The Chi-square test was used to compare categorical data groups. For normally distributed data, a two independent sample T-test was employed. Non-normally distributed data were analyzed using the Mann-Whitney U test. Pearson or Spearman correlation coefficients were used for correlation analysis, depending on the data distribution.