ObjectiveOur previous studies found that disturbances in gut microbiota might have a causative role in the onset of major depressive disorder (MDD). The aim of this study was to investigate whether there were sex differences in gut microbiota in patients with MDD.Patients and methodsFirst-episode drug-naïve MDD patients and healthy controls were included. 16S rRNA gene sequences extracted from the fecal samples of the included subjects were analyzed. Principal-coordinate analysis and partial least squares-discriminant analysis were used to assess whether there were sex-specific gut microbiota. A random forest algorithm was used to identify the differential operational taxonomic units. Linear discriminant-analysis effect size was further used to identify the dominant sex-specific phylotypes responsible for the differences between MDD patients and healthy controls.ResultsIn total, 57 and 74 differential operational taxonomic units responsible for separating female and male MDD patients from their healthy counterparts were identified. Compared with their healthy counterparts, increased Actinobacteria and decreased Bacteroidetes levels were found in female and male MDD patients, respectively. The most differentially abundant bacterial taxa in female and male MDD patients belonged to phyla Actinobacteria and Bacteroidia, respectively. Meanwhile, female and male MDD patients had different dominant phylotypes.ConclusionThese results demonstrated that there were sex differences in gut microbiota in patients with MDD. The suitability of Actinobacteria and Bacteroidia as the sex-specific biomarkers for diagnosing MDD should be further explored.
Major depressive disorder (MDD) is a highly prevalent and debilitating mental illness, which is associated with disorder of gut microbiota. However, few studies focusing on detection of the signatures of bacteria in feces of MDD patients using proteomics approach have been carried out. Here, a comparative metaproteomics analysis on the basis of an isobaric tag for relative and absolute quantification coupled with tandem mass spectrometry was carried out to explore the signature of gut microbiota in patients with MDD. Ten patients (age: 18-56 years, five women) who had MDD and a score over 20 on the Hamilton's Depression Scale and 10 healthy controls (age: 24-65 years, five women) group matched for sex, age, and BMI were enrolled. As a result, 279 significantly differentiated bacterial proteins (P<0.05) were detected and used for further bioinformatic analysis. According to phylogenetic analysis, statistically significant differences were observed for four phyla: Bacteroidetes, Proteobacteria, Firmicutes, Actinobacteria (P<0.05, for each). Abundances of 16 bacterial families were significantly different between the MDD and healthy controls (P<0.05). Furthermore, Cluster of Orthologous Groups analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that disordered metabolic pathways of bacterial proteins were mainly involved in glucose metabolism and amino acid metabolism. In conclusion, fecal microbiota signatures were altered significantly in MDD patients. Our findings provide a novel insight into the potential connection between gut microbiota and depression.
Major depressive disorder (MDD) is a serious mental illness, characterized by high morbidity, which has increased in recent decades. However, the molecular mechanisms underlying MDD remain unclear. Previous studies have identified altered metabolic profiles in peripheral tissues associated with MDD. Using curated metabolic characterization data from a large sample of MDD patients, we meta-analyzed the results of metabolites in peripheral blood. Pathway and network analyses were then performed to elucidate the biological themes within these altered metabolites. We identified 23 differentially expressed metabolites between MDD patients and controls from 46 studies. MDD patients were characterized by higher levels of asymmetric dimethylarginine, tyramine, 2-hydroxybutyric acid, phosphatidylcholine (32:1), and taurochenodesoxycholic acid and lower levels of L-acetylcarnitine, creatinine, L-asparagine, L-glutamine, linoleic acid, pyruvic acid, palmitoleic acid, L-serine, oleic acid, myo-inositol, dodecanoic acid, L-methionine, hypoxanthine, palmitic acid, L-tryptophan, kynurenic acid, taurine, and 25-hydroxyvitamin D compared with controls. L-tryptophan and kynurenic acid were consistently downregulated in MDD patients, regardless of antidepressant exposure. Depression rating scores were negatively associated with decreased levels of L-tryptophan. Pathway and network analyses revealed altered amino acid metabolism and lipid metabolism, especially for the tryptophan-kynurenine pathway and fatty acid metabolism, in the peripheral system of MDD patients. Taken together, our integrated results revealed that metabolic changes in the peripheral blood were associated with MDD, particularly decreased L-tryptophan and kynurenic acid levels, and alterations in the tryptophan-kynurenine and fatty acid metabolism pathways. Our findings may facilitate biomarker development and the elucidation of the molecular mechanisms that underly MDD.
Neutrophil count adds prognostic information to MACEs in ACS. Monocyte count and lymphocyte count are predictive of severity of coronary atherosclerosis.
Background In China, the shortage of doctors leads to stressful clinical work and increasing turnover. Medical students undergoing postgraduate specialty training will be the country’s medical workforce in the coming decades, but are also subject to high workloads and academic pressure. This may have significant implications for burnout and career choice regret. Despite the importance of burnout and career choice regret, the status and relationship of these aspects in Chinese neurology postgraduates are largely unexplored, and associated factors remain unknown. Methods This study investigated the prevalence of and factors influencing burnout and career choice regret among neurology postgraduates in China. We conducted a national cross-sectional study of Chinese neurology postgraduates. Data were collected using a self-administered questionnaire that covered demographic information, the Maslach Burnout Inventory, and additional item to assess career choice regret. Results Of 4902 neurology postgraduates, 2008 returned completed questionnaires (response rate 41%). After excluding incomplete questionnaires, data for 1814 participants were analyzed. In total, 83.6% of participants had experienced symptoms of burnout, and 46.6% reported career choice regret. Binary logistic regression analysis showed postgraduate entrance examination scores, marital status, and having children were associated with burnout (all P < 0.05). Career choice regret was the strongest risk factor for burnout (odds ratio [OR] = 3.17, 95% confidence interval [CI] 2.33–4.32). Multiple logistic regression showed postgraduates with shorter work or study hours per week (OR = 0.64, 95% CI 0.47–0.88) had a low risk for career choice regret, whereas married participants (OR = 1.54, 95% CI 1.07–2.20) had a high risk for career choice regret. No symptoms of burnout (OR = 0.33, 95% CI 0.24–0.45) was also associated with a low risk for career choice regret. Conclusions Burnout symptoms and career choice regret are prevalent among neurology postgraduates in China. Career choice regret is an important predictor of burnout. Further research on reducing burnout and career choice regret among neurology postgraduates is needed. Electronic supplementary material The online version of this article (10.1186/s12909-019-1601-3) contains supplementary material, which is available to authorized users.
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