Label-free proteomics differences in the dorsolateral prefrontal cortex between bipolar disorder patients with and without psychosis

Deciphering the omicron variant: integrated omics analysis reveals critical biomarkers and pathophysiological pathways

BACKGROUND

The rapid emergence and global dissemination of the Omicron variant of SARS-CoV-2 have posed formidable challenges in public health. This scenario underscores the urgent need for an enhanced understanding of Omicron's pathophysiological mechanisms to guide clinical management and shape public health strategies. Our study is aimed at deciphering the intricate molecular mechanisms underlying Omicron infections, particularly focusing on the identification of specific biomarkers.

METHODS

This investigation employed a robust and systematic approach, initially encompassing 15 Omicron-infected patients and an equal number of healthy controls, followed by a validation cohort of 20 individuals per group. The study's methodological framework included a comprehensive multi-omics analysis that integrated proteomics and metabolomics, augmented by extensive bioinformatics. Proteomic exploration was conducted via an advanced Ultra-High-Performance Liquid Chromatography (UHPLC) system linked with mass spectrometry. Concurrently, metabolomic profiling was executed using an Ultra-Performance Liquid Chromatography (UPLC) system. The bioinformatics component, fundamental to this research, entailed an exhaustive analysis of protein-protein interactions, pathway enrichment, and metabolic network dynamics, utilizing state-of-the-art tools such as the STRING database and Cytoscape software, ensuring a holistic interpretation of the data.

RESULTS

Our proteomic inquiry identified eight notably dysregulated proteins (THBS1, ACTN1, ACTC1, POTEF, ACTB, TPM4, VCL, ICAM1) in individuals infected with the Omicron variant. These proteins play critical roles in essential physiological processes, especially within the coagulation cascade and hemostatic mechanisms, suggesting their significant involvement in the pathogenesis of Omicron infection. Complementing these proteomic insights, metabolomic analysis discerned 146 differentially expressed metabolites, intricately associated with pivotal metabolic pathways such as tryptophan metabolism, retinol metabolism, and steroid hormone biosynthesis. This comprehensive metabolic profiling sheds light on the systemic implications of Omicron infection, underscoring profound alterations in metabolic equilibrium.

CONCLUSIONS

This study substantially enriches our comprehension of the physiological ramifications induced by the Omicron variant, with a particular emphasis on the pivotal roles of coagulation and platelet pathways in disease pathogenesis. The discovery of these specific biomarkers illuminates their potential as critical targets for diagnostic and therapeutic strategies, providing invaluable insights for the development of tailored treatments and enhancing patient care in the dynamic context of the ongoing pandemic.

Proteomics analysis of the gut-brain axis in a gut microbiota-dysbiosis model of depression

Major depressive disorder (MDD) is a serious mental illness. Increasing evidence from both animal and human studies suggested that the gut microbiota might be involved in the onset of depression via the gut-brain axis. However, the mechanism in depression remains unclear. To explore the protein changes of the gut-brain axis modulated by gut microbiota, germ-free mice were transplanted with gut microbiota from MDD patients to induce depression-like behaviors. Behavioral tests were performed following fecal microbiota transplantation. A quantitative proteomics approach was used to examine changes in protein expression in the prefrontal cortex (PFC), liver, cecum, and serum. Then differential protein analysis and weighted gene coexpression network analysis were used to identify microbiota-related protein modules. Our results suggested that gut microbiota induced the alteration of protein expression levels in multiple tissues of the gut-brain axis in mice with depression-like phenotype, and these changes of the PFC and liver were model specific compared to chronic stress models. Gene ontology enrichment analysis revealed that the protein changes of the gut-brain axis were involved in a variety of biological functions, including metabolic process and inflammatory response, in which energy metabolism is the core change of the protein network. Our data provide clues for future studies in the gut-brain axis on protein level and deepen the understanding of how gut microbiota cause depression-like behaviors.

Altered spatiotemporal consistency in pediatric bipolar disorder patients with and without psychotic symptoms

OBJECTIVE

Psychotic symptoms are quite common in patients with pediatric bipolar disorder (PBD) and may affect the symptom severity and prognosis of PBD. However, the potential mechanisms are less well elucidated until now. Thus, the purpose of this study was to investigate the brain functional differences between PBD patients with and without psychotic symptoms.

METHOD

A total of 71 individuals including: 27 psychotic PBD (P-PBD), 25 nonpsychotic PBD (NP-PBD), and 19 healthy controls were recruited in the present study. Each subject underwent 3.0 Tesla functional magnetic resonance imaging scan. Four-dimensional (spatiotemporal) Consistency of local neural Activities (FOCA) was employed to detect the local brain activity changes. Analyses of variance (ANOVA) were used to reveal brain regions with significant differences among three groups groups of individuals, and inter-group comparisons were assessed using post hoc tests.

RESULTS

The ANOVA obtained significant among-group FOCA differences in the left triangular inferior frontal gyrus, left supplementary motor area, left precentral gyrus, right postcentral gyrus, right superior occipital gyrus, and right superior frontal gyrus. Compared with the control group, the P-PBD group showed decreased FOCA in the left supplementary motor area and bilateral superior frontal gyrus and showed increased FOCA in the left triangular inferior frontal gyrus. In contrast, the NP-PBD group exhibited decreased FOCA in the right superior occipital gyrus and right postcentral gyrus and showed increased FOCA in the left orbital inferior frontal gyrus. Compared to the NP-PBD group, the P-PBD group showed decreased FOCA in the right superior frontal gyrus.

CONCLUSION

The present findings demonstrated that the two groups of PBD patients exhibited segregated brain functional patterns, providing empirical evidence for the biological basis of different clinical outcomes between PBD patients with and without psychotic symptoms.

Classifiers for Predicting Coronary Artery Disease Based on Gene Expression Profiles in Peripheral Blood Mononuclear Cells

Objective

Coronary artery disease (CAD) is a serious global health concern. Current diagnostic methods for CAD involve risk to the patient and are costly, so better diagnostic tools are needed. We defined four classifiers based on gene expression profiles in peripheral blood mononuclear cells and determined their potential for CAD detection.

Methods

We downloaded a CAD-related data set (GSE113079) from the Gene Expression Omnibus (GEO) database. We identified differentially expressed genes (DEGs) in peripheral blood mononuclear cells between CAD samples and healthy controls. DEGs were analyzed for functional enrichment. To create a robust CAD classifier, DEGs were identified by feature selection using the principal component analysis. Then, least absolute shrinkage and selection operator (LASSO) logistic regression, random forest, and support vector machine (SVM) models were created. Gene set variation analysis (GSVA) score and gene set enrichment analysis (GSEA) were also conducted. The performance of the models was evaluated in terms of the area under receiver operating characteristic curves (AUC).

Results

In the training set, we found 135 up-regulated genes and 104 down-regulated genes in CAD patients compared with controls. The DEGs were involved in some pathways associated with CAD, such as pathways involving calcium and interleukin-17 signaling. Twenty genes were identified as optimal features and used to generate the logistic classifier based on LASSO. The AUC for the classifier was 1.00 in the training set and 0.997 in the test set. Using the 20 DEGs, SVM and random forest classifiers were also generated and showed high diagnostic efficacy, with respective AUCs of 0.997 and 1.00 against the training set. A GSVA score was also established using the top 20 significant DEGs, which showed an AUC of 0.971 in the training set and 0.989 in the test set. Furthermore, GSEA showed autophagy and the proteasome to be major pathways involving the DEGs.

Conclusion

We identified a set of genes specific for CAD whose expression can be measured non-invasively. Using these genes, we defined four diagnostic classifiers using multiple methods.

Oxidative Stress Impact on the Transcriptome of Differentiating Neuroblastoma Cells: Implication for Psychiatric Disorders

Prenatal environmental exposures that have been shown to induce oxidative stress (OS) during pregnancy, such as smoking and alcohol consumption, are risk factors for the onset of schizophrenia and other neurodevelopmental disorders (NDDs). While the OS role in the etiology of neurodegenerative diseases is well known, its contribution to the genomic dysregulation associated with psychiatric disorders is less well defined. In this study we used the SH-SY5Y cell line and applied RNA-sequencing to explore transcriptomic changes in response to OS before or during neural differentiation. We observed differential expression of many genes, most of which localised to the synapse and were involved in neuronal differentiation. These genes were enriched in schizophrenia-associated signalling pathways, including PI3K/Akt, axon guidance, and signalling by retinoic acid. Interestingly, circulatory system development was affected by both treatments, which is concordant with observations of increased prevalence of cardiovascular disease in patients with NDDs. We also observed a very significant increase in the expression of immunity-related genes, supporting current hypotheses of immune system involvement in psychiatric disorders. While further investigation of this influence in other cell and animal models is warranted, our data suggest that early life exposure to OS has a disruptive influence on neuronal gene expression that may perturb normal differentiation and neurodevelopment, thereby contributing towards overall risk for developing psychiatric diseases.