Search

BackgroundMajor depressive disorder (MDD) is associated with deficits in cognitive function, thought to be related to underlying decreased hedonic experiences. Further research is needed to fully elucidate the role of functional brain activity in this relationship. In this study, we investigated the neurofunctional correlate of the interplay between cognitive function and hedonic experiences in medication-free MDD using functional near-infrared spectroscopy (fNIRS).MethodsWe examine differences of brain activation corresponding to the verbal fluency test (VFT) between MDD patients and healthy controls (HCs). Fifty-six MDD patients and 35 HCs underwent fMRI scanning while performing the VFT. In exploratory analyses, cognitive performance, as assessed by the Cambridge Neuropsychological Test Automated Battery (CANTAB), four dimensions of hedonic processing (desire, motivation, effort, and consummatory pleasure) measured by the Dimensional Anhedonia Rating Scale (DARS), and relative changes in oxygenated hemoglobin concentration during the VFT were compared across groups.ResultsPatients with MDD demonstrated impairments in sustained attention and working memory, accompanied by lower total and subscale scores on the DARS. Compared to healthy controls, MDD patients exhibited reduced activation in the prefrontal cortex (PFC) during the VFT task (t = 2.32 to 4.77, p < 0.001 to 0.02, FDR corrected). DARS motivation, desire, and total scores as well as sustained attention, were positively correlated with activation in the dorsolateral PFC and Broca’s area (p < 0.05, FDR corrected).ConclusionsThese findings indicate that changes in prefrontal lobe oxygenated hemoglobin levels, a region implicated in hedonic motivation and cognitive function, may serve as potential biomarkers for interventions targeting individuals with MDD. Our results corroborate the clinical consensus that the prefrontal cortex is a primary target for non-invasive neuromodulatory treatments for depression.

BackgroundAnti-inflammatory agents have emerged as a potential new therapy for major depressive disorder (MDD). In this meta-analysis, our aim was to evaluate the antidepressant effect of anti-inflammatory agents and compare their efficacy.MethodsWe conducted a comprehensive search across multiple databases, including PubMed, Embase, Web of Science, Cochrane Review, Cochrane Trial, and ClinicalTrials.gov, to identify eligible randomized clinical trials. The primary outcome measures of our meta-analysis were efficacy and acceptability, while the secondary outcome measures focused on remission rate and dropout rate due to adverse events. We used odds ratio (OR) and 95% confidence interval (95% CI) to present our results.ResultsA total of 48 studies were included in our analysis. In terms of efficacy, anti-inflammatory agents demonstrated a significant antidepressant effect compared to placebo (OR = 2.04, 95% CI: 1.41–2.97, p = 0.0002). Subgroup analyses revealed that anti-inflammatory agents also exhibited significant antidepressant effects in the adjunctive therapy subgroup (OR = 2.17, 95% CI: 1.39–3.37, p = 0.0006) and in MDD patients without treatment-resistant depression subgroup (OR = 2.33, 95% CI: 1.53–3.54, p < 0.0001). Based on the surface under the cumulative ranking curve (SUCRA) value of network meta-analysis, nonsteroidal anti-inflammatory drugs (NSAIDs) (SUCRA value = 81.6) demonstrated the highest acceptability among the included anti-inflammatory agents.ConclusionIn summary, our meta-analysis demonstrates that anti-inflammatory agents have significant antidepressant effects and are well-accepted. Furthermore, adjunctive therapy with anti-inflammatory agents proved effective in treating MDD. Among the evaluated anti-inflammatory agents, NSAIDs exhibited the highest acceptability, although its efficacy is comparable to placebo.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=422004), identifier CRD42023422004.

IntroductionPrevious studies on transcriptional profiles suggested dysregulation of multiple RNA species in major depressive disorder (MDD). However, the interaction between different types of RNA was neglected. Therefore, integration of different RNA species in transcriptome analysis would be helpful for interpreting the functional readout of the transcriptome in MDD.MethodsA whole transcriptome sequencing were performed on the peripheral blood of 15 patients with MDD and 15 matched healthy controls (HCs). The differential expression of miRNAs, lncRNAs, circRNAs, and mRNAs was examined between MDD and HCs using empirical analysis of digital gene expression data in R (edgeR). Weighted correlation network analysis (WGCNA) was used to identify RNA co-expression modules associated with MDD. A ceRNA network was constructed for interpretation of interactions between different RNA species. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to explore potential biological mechanisms associated with MDD.ResultsMultiple RNAs and co-expression modules were identified to be significantly dysregulated in MDD compared to HCs. Based on the differential RNAs, a ceRNA network that were dysregulated in MDD were constructed. The pathway networks that related to oxidative phosphorylation and the chemokine signaling were found to be associated with MDD.ConclusionOur results suggested that the processes of energy metabolism and inflammation may be involved in the pathophysiology of MDD.

Background: Major depressive disorder (MDD) is a common disease which is complicated by metabolic disorder. Although MDD has been studied relatively intensively, its metabolism is yet to be elucidated.Methods: To profile the global pathophysiological processes of MDD patients, we used metabolomics to identify differential metabolites and applied a new database Metabolite set enrichment analysis (MSEA) to discover dysfunctions of metabolic pathways of this disease. Hydrophilic metabolomics were applied to identify metabolites by profiling the plasma from 55 MDD patients and 100 sex-, gender-, BMI-matched healthy controls. The metabolites were then analyzed in MSEA in an attempt to discover different metabolic pathways. To investigate dysregulated pathways, we further divided MDD patients into two cohorts: (1) MDD patients with anxiety symptoms and (2) MDD patients without anxiety symptoms.Results: Metabolites which were hit in those pathways correlated with depressive and anxiety symptoms. Altogether, 17 metabolic pathways were enriched in MDD patients, and 23 metabolites were hit in those pathways. Three metabolic pathways were enriched in MDD patients without anxiety, including glycine and serine metabolism, arginine and proline metabolism, and phenylalanine and tyrosine metabolism. In addition, L-glutamic acid was positively correlated with the severity of depression and retardation if hit in MDD patients without anxiety symptoms.Conclusions: Different kinds of metabolic pathophysiological processes were found in MDD patients. Disorder of glycine and serine metabolism was observed in both MDD patients with anxiety and those without.