With increasing attention paid to the concept of the microbiota–gut–brain axis, mounting evidence reveals that the gut microbiota is involved in a variety of neurological and psychiatric diseases. However, gut microbiota changes in major depressive disorder (MDD) patients and their association with disease mechanisms remain undefined. Fifty MDD patients and sixty healthy controls were recruited from the Shanghai Healthy Mental Center, China. Fecal samples were collected, and the compositional characteristics of the intestinal flora were determined in MDD patients by MiSeq sequencing. Venous blood was collected for the detection of plasma indoleamine-2,3-dioxygenase (Ido), kynurenine (Kyn) and tryptophan (Trp) levels. Stool samples of bacterial 16S sequencing was carried out. A total of 2,705,809 optimized sequences were obtained, with an average of 54,116 per sample. More unique OTUs were observed at the family, genus and species levels in the control group compared with the MDD cases. Further analysis showed significant changes in the α- and β-diversities and relative abundance levels of gut microbial entities in MDD patients, as well as elevated amounts of Ido and Kyn indicating Kyn pathway activation, KEGG bacterial 16S function prediction analysis shows a variety of amino acids and metabolic (including Ido, Trp and Kyn) changes in the body of patients with MDD. These may result in increased neurotoxic metabolites and reduced generation of serotonin in the disease process. These changed factors may potentially be utilized as biomarkers for MDD in the future, playing more important roles in the disease course.

Major depressive disorder (MDD) is related to human’s immune status, and immunological indicators such as mitogen stimulated cell proliferation and cytokines may become candidate biomarkers for disease diagnosis. One hundred diagnosed major depressive disorder subjects and 100 health controls were enrolled in this study. Phytohaemagglutinin and lipopolysaccharide stimulated cell proliferations and cytokine concentrations were detected in peripheral blood mononuclear cells from both groups. The corresponding stimulated responses were conducted and confirmed in chronic unpredictable mild stress (CUMS) mice. Compared to the people in control group, there were lower cell proliferations and lower TNF-α produced in lipopolysaccharide stimulated peripheral blood mononuclear cells in depression patients, lower IL-2 and IL-10 produced in phytohaemagglutinin stimulated peripheral blood mononuclear cells in depression patients, higher IL-6, IL-10 and lower IL-2 secretions were detected in peripheral plasma in depression patients. In CUMS mice we found lower splenocyte proliferations, lower IL-1α productions and higher IL-6 secretions in lipopolysaccharide stimulated splenocytes. It seems lipopolysaccharide stimulated cell proliferation activities were inhibited in depressive states. Lower lipopolysaccharide stimulated cell proliferation and phytohaemagglutinin stimulated or plasma cytokine IL-2 decreases should be potential monitoring indices in the depressive state assessment for major depressive disorder patients.

Alzheimer’s disease (AD) is a multifactorial brain disorder and infectious diseases are considered as one of the predisposing factors for AD. Toxoplasma gondii, an obligate intracellular parasitic protozoan, is suspected of being associated with AD. Serum samples were collected from 109 AD patients and 114 age-matched healthy controls. ELISA was performed using recombinant T. gondii cyst wall protein 1 (CST1) to detect T. gondii antibodies. A parallel experiment was performed with Toxoplasma gondii tachyzoites lysate protein. To analyze whether factors associated with the onset of AD included chronic T. gondii infection, a multivariate logistic regression model was applied, further validating the correlation between chronic T. gondii infection and AD. AD patients exhibited significantly higher levels of Toxoplasma-specific antibodies in their serum compared to the control group, with statistically significant differences (p < 0.05). Multivariate logistic regression analysis revealed that Toxoplasma infection is a risk factor for AD (p < 0.01), and the CST1 antigen can significantly improve the model’s performance in predicting the occurrence of AD. The results indicate that chronic infection with Toxoplasma gondii could be one of the risk factors for the development of AD, potentially predisposing individuals with underlying health conditions to the disease. This further validates the correlation between Toxoplasma gondii and AD.

Based on its objective characteristics, laboratory markers have always been the research direction of clinical diagnosis and assessment of mental disorders including Alzheimer's disease. MTT Colorimetric Assay, ELISA, and quantitative PCR were used to investigate the responsiveness of peripheral blood mononuclear cells (PBMCs) to mitogen Lipopolysaccharides (LPS) and Phytohemagglutinin (PHA), PBMCs genomic methylation and hydroxymethylation levels, nuclear DNA and mitochondrial DNA damage, respiratory chain enzyme activities, and circulating cell-free mitochondrial DNA levels were detected in 90 patients with Alzheimer's disease. In the Alzheimer's disease group, LPS stimulated PBMCs viability, TNF-α secretion, PHA stimulated IL-10 secretion, genomic DNA methylation levels, circulating cell-free mitochondrial DNA copies, citrate synthase activity were reduced compared to the control; while the LPS stimulated PBMCs IL-1α secretion, PHA stimulated IL-1α and IFN-γ secretion, plasma IL-6 and TNF-α, mitochondrial DNA damages were increased compared to the control. The reactivity of peripheral blood mononuclear cells to mitogens, mitochondrial DNA integrity characteristics, and cell-free mitochondrial DNA copies may be used as candidate laboratory biomarkers to help clinical management of Alzheimer's disease.

Background: Schizophrenia is frequently underdiagnosed or diagnosed late due to the lack of objective diagnostic markers. This study aimed to develop and validate a machine learning model using routine hematological parameters for the auxiliary diagnosis of schizophrenia. Methods: A total of 150 first-episode drug-naïve schizophrenia patients and 150 healthy controls were enrolled. Study parameters included routine hematological parameters and its derived inflammatory markers. Feature selection was performed using Elastic Net regression, followed by the construction of an L2-regularized logistic regression model. Model discriminative performance, calibration, and clinical utility were assessed through internal validation, area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis. An independent cohort of 50 schizophrenia patients and 50 patients with major depressive disorder (MDD) was used for exploratory differential diagnostic evaluation. Results: The final model incorporated 12 features: neutrophil count (NEUT), eosinophil count (EO), mean platelet volume (MPV), hematocrit (HCT), hemoglobin (HGB), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), neutrophil-to-platelet ratio (NPR), along with age and sex. The model achieved an AUC of 0.859 (95% CI: 0.780–0.937) on the test set, with an accuracy of 0.767, sensitivity of 0.711, and specificity of 0.822. Calibration curves confirmed good calibration, and decision curve analysis further verified its clinical utility. In the exploratory differential diagnostic analysis, the model showed limited performance in distinguishing schizophrenia from MDD. Conclusions: The model based on routine hematological parameters and L2-regularized logistic regression can effectively differentiate first-episode drug-naïve schizophrenia patients from healthy controls, providing a low-cost and easily accessible auxiliary diagnostic tool for clinical practice.