Quantitative magnetic resonance spectroscopy of depression: The value of short-term metabolite changes in predicting treatment response.

Background: Although various prediction models of the antidepressant response have been established, the results have not been effectively applied to heterogeneous depression populations, which has seriously limited their clinical value. This study tried to build a more specific and stable model to predict treatment response in depression based on short-term changes in hippocampal metabolites. Materials and methods: Seventy-four major depressive disorder (MDD) patients and 20 healthy controls in the test set were prospectively collected and retrospectively analyzed. Subjects underwent magnetic resonance spectroscopy (MRS) once a week during 6 weeks of treatment. Hippocampal regions of interest (ROIs) were extracted by using a voxel iteration scheme combined with standard brain templates. The short-term differences in hippocampal metabolites between and within groups were screened. Then, the association between hippocampal metabolite changes and clinical response was analyzed, and a prediction model based on logistic regression was constructed. In addition, a validation set (n = 60) was collected from another medical center to validate the predictive abilities. Results: After 2-3 weeks of antidepressant treatment, the differences in indicators (tCho wee0-2, tCho wee0-3 and NAA week0-3) were successfully screened. Then, the predictive abilities of these three indicators were revealed in the logistic regression model, and the optimal prediction effect was found in d(tCho) week0-3-d(NAA) week0-3 (AUC = 0.841, 95%CI = 0.736-0.946). In addition, their predictive abilities were further confirmed with the validation set. Limitations: The small sample size and the need for multiple follow-ups limited the statistical ability to detect other findings. Conclusion: The predictive model in this study presented accurate prediction and strong verification effects, which may provide early guidance for adjusting the treatment regimens of depression and serve as a checkpoint at which the eventual treatment outcome can be predicted.

Interleukin-6-white matter network differences explained the susceptibility to depression after stressful life events.

BACKGROUND: Stressful life events (SLEs) are well-established proximal predictors of the onset of depression. However, the fundamental causes of interindividual differences in depression outcomes are poorly understood. This study addressed this depression susceptibility mechanism using a well-powered sample of adults living in China. METHODS: Healthy participants with SLEs (n = 185; mean = 47.51 years, 49.73% female), drawn from a longitudinal study on the development of depression, underwent diffusion tensor imaging, interleukin-6 (IL-6) level measurement, and trimonthly standardized clinical and scale evaluations within a two-year period. RESULTS: Receiver operating characteristic analyses indicated that reduced feeder connection and HIP.R nodal efficiency improved the predictive accuracy of post-SLEs depression (ORfeeder = 0.623, AUC = 0.869, P < 0.001; ORHIP = 0.459, AUC = 0.855, P < 0.001). The successfully established path analysis model confirmed the significant partial effect of SLEs-IL-6-white matter (WM) network differences-depression (onset and severity) (x2/8 = 1.453, goodness-of-fit [GFI] = 0.935, standard root-mean-square error of approximation [SRMR] = 0.024). Females, individuals with lower exercise frequency (EF) or annual household income (AHI) were more likely to have higher IL-6 level after SLEs (ßint-female⁎SLEs = -0.420, P < 0.001; ßint-exercise⁎SLEs = -0.412, P < 0.001; ßint-income⁎SLEs = -0.302, P = 0.005). LIMITATIONS: The sample size was restricted due to the limited incidence rate and prospective follow-up design. CONCLUSIONS: Our results suggested that among healthy adults after SLEs, those who exhibited abnormal IL-6-WM differences were susceptible to developing depression. Females, lower AHI or EF might account for an increased risk of developing these abnormal IL-6-WM differences.

Neuron secrete exosomes containing miR-9-5p to promote polarization of M1 microglia in depression.

BACKGROUND: Neuroinflammation is an important component mechanism in the development of depression. Exosomal transfer of MDD-associated microRNAs (miRNAs) from neurons to microglia might exacerbate neuronal cell inflammatory injury. RESULTS: By sequence identification, we found significantly higher miR-9-5p expression levels in serum exosomes from MDD patients than healthy control (HC) subjects. Then, in cultured cell model, we observed that BV2 microglial cells internalized PC12 neuron cell-derived exosomes while successfully transferring miR-9-5p. MiR-9-5p promoted M1 polarization in microglia and led to over releasing of proinflammatory cytokines, such as interleukin-1ß (IL-1ß), interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α), which exacerbated neurological damage. Furthermore, we identified suppressor of cytokine signaling 2 (SOCS2) as a direct target of miR-9-5p. Overexpression of miR-9-5p suppressed SOCS2 expression and reactivated SOCS2-repressed Janus kinase (JAK)/signal transducer and activator of transcription 3 (STAT3) pathways. Consistently, we confirmed that adeno-associated virus (AAV)-mediated overexpression of miR-9-5p polarized microglia toward the M1 phenotype and exacerbated depressive symptoms in chronic unpredictable mild stress (CUMS) mouse mode. CONCLUSION: MiR-9-5p was transferred from neurons to microglia in an exosomal way, leading to M1 polarization of microglia and further neuronal injury. The expression and secretion of miR-9-5p might be novel therapeutic targets for MDD.