ProMENDA: an updated resource for proteomic and metabolomic characterization in depression.

Depression is a prevalent mental disorder with a complex biological mechanism. Following the rapid development of systems biology technology, a growing number of studies have applied proteomics and metabolomics to explore the molecular profiles of depression. However, a standardized resource facilitating the identification and annotation of the available knowledge from these scattered studies associated with depression is currently lacking. This study presents ProMENDA, an upgraded resource that provides a platform for manual annotation of candidate proteins and metabolites linked to depression. Following the establishment of the protein dataset and the update of the metabolite dataset, the ProMENDA database was developed as a major extension of its initial release. A multi-faceted annotation scheme was employed to provide comprehensive knowledge of the molecules and studies. A new web interface was also developed to improve the user experience. The ProMENDA database now contains 43,366 molecular entries, comprising 20,847 protein entries and 22,519 metabolite entries, which were manually curated from 1370 human, rat, mouse, and non-human primate studies. This represents a significant increase (more than 7-fold) in molecular entries compared to the initial release. To demonstrate the usage of ProMENDA, a case study identifying consistently reported proteins and metabolites in the brains of animal models of depression was presented. Overall, ProMENDA is a comprehensive resource that offers a panoramic view of proteomic and metabolomic knowledge in depression. ProMENDA is freely available at https://menda.cqmu.edu.cn .

Identification of Potential Biomarkers for Major Depressive Disorder: Based on Integrated Bioinformatics and Clinical Validation.

Major depressive disorder (MDD) is a severe mental illness characterized by a lack of objective biomarkers. Mounting evidence suggests there are extensive transcriptional molecular changes in the prefrontal cortex (PFC) of individuals with MDD. However, it remains unclear whether there are specific genes that are consistently altered and possess diagnostic power. In this study, we conducted a systematic search of PFC datasets of MDD patients from the Gene Expression Omnibus database. We calculated the differential expression of genes (DEGs) and identified robust DEGs using the RRA and MetaDE methods. Furthermore, we validated the consistently altered genes and assessed their diagnostic power through enzyme-linked immunosorbent assay experiments in our clinical blood cohort. Additionally, we evaluated the diagnostic power of hub DEGs in independent public blood datasets. We obtained eight PFC datasets, comprising 158 MDD patients and 263 healthy controls, and identified a total of 1468 unique DEGs. Through integrated analysis, we identified 290 robustly altered DEGs. Among these, seven hub DEGs (SLC1A3, PON2, AQP1, EFEMP1, GJA1, CENPD, HSD11B1) were significantly down-regulated at the protein level in our clinical blood cohort. Moreover, these hub DEGs exhibited a negative correlation with the Hamilton Depression Scale score (P < 0.05). Furthermore, these hub DEGs formed a panel with promising diagnostic power in three independent public blood datasets (average AUCs of 0.85) and our clinical blood cohort (AUC of 0.92). The biomarker panel composed of these genes demonstrated promising diagnostic efficacy for MDD and serves as a useful tool for its diagnosis.

Integrated analysis of transcriptional changes in major depressive disorder: Insights from blood and anterior cingulate cortex.

Background: Major depressive disorder (MDD) was involved in widely transcriptional changes in central and peripheral tissues. While, previous studies focused on single tissues, making it difficult to represent systemic molecular changes throughout the body. Thus, there is an urgent need to explore the central and peripheral biomarkers with intrinsic correlation. Methods: We systematically retrieved gene expression profiles of blood and anterior cingulate cortex (ACC). 3 blood datatsets (84 MDD and 88 controls) and 6 ACC datasets (100 MDD and 100 controls) were obtained. Differential expression analysis, RobustRankAggreg (RRA) analysis, functional enrichment analysis, immune associated analysis and protein-protein interaction networks (PPI) were integrated. Furthermore, the key genes were validated in an independent ACC dataset (12 MDD and 15 controls) and a cohort with 120 MDD and 117 controls. Results: Differential expression analysis identified 2211 and 2021 differential expressed genes (DEGs) in blood and ACC, respectively. RRA identified 45 and 25 robust DEGs in blood and ACC based on DEGs, and all of them were closely associated with immune cells. Functional enrichment results showed both the robust DEGs in blood and ACC were enriched in humoral immune response. Furthermore, PPI identified 8 hub DEGs (CD79A, CD79B, CD19, MS4A1, PLP1, CLDN11, MOG, MAG) in blood and ACC. Independent ACC dataset showed the area under the curve (AUC) based on these hub DEGs was 0.77. Meanwhile, these hub DEGs were validated in the serum of MDD patients, and also showed a promising diagnostic power. Conclusions: The biomarker panel based on hub DEGs yield a promising diagnostic efficacy, and all of these hub DEGs were strongly correlated with immunity. Humoral immune response may be the key link between the brain and blood in MDD, and our results may provide further understanding for MDD.

Wernicke encephalopathy induced by glucose infusion: A case report and literature review.

Introduction: Wernicke encephalopathy (WE) is a potentially fatal condition caused by thiamine (vitamin B1) deficiency. Chronic alcoholism is the most common cause of WE; however, other conditions responsible for thiamine deficiency should also be considered. Case Report: We report the case of a 64-year-old woman with a history of diabetes who presented with confusion and apathy. Magnetic resonance imaging of the brain showed T2 hyperintensities involving dorsolateral medulla oblongata, tegmentum of the pons, vermis of the cerebellum, periaqueductal region, and the bilateral mammillary bodies. She had a history of intravenous glucose administration before her mental symptoms developed. On suspicion of WE, she was treated with a high dose of thiamine empirically. Her clinical condition improved rapidly in 2 weeks. Conclusion: Endogenous thiamine stores can be rapidly depleted in the case of enhanced glucose oxidation. Patients who receive glucose should also be prescribed thiamine to avoid inducing or exacerbating WE.

Multi-Omics Analysis Reveals Age-Related Microbial and Metabolite Alterations in Non-Human Primates.

Aging is a systemic physiological degenerative process, with alterations in gut microbiota and host metabolism. However, due to the interference of multiple confounding factors, aging-associated molecular characteristics have not been elucidated completely. Therefore, based on 16S ribosomal RNA (rRNA) gene sequencing and non-targeted metabolomic detection, our study systematically analyzed the composition and function of the gut microbiome, serum, and fecal metabolome of 36 male rhesus monkeys spanning from 3 to 26 years old, which completely covers juvenile, adult, and old stages. We observed significant correlations between 41 gut genera and age. Moreover, 86 fecal and 49 serum metabolites exhibited significant age-related correlations, primarily categorized into lipids and lipid-like molecules, organic oxygen compounds, organic acids and derivatives, and organoheterocyclic compounds. Further results suggested that aging is associated with significant downregulation of various amino acids constituting proteins, elevation of lipids, particularly saturated fatty acids, and steroids. Additionally, age-dependent changes were observed in multiple immune-regulatory molecules, antioxidant stress metabolites, and neurotransmitters. Notably, multiple age-dependent genera showed strong correlations in these changes. Together, our results provided new evidence for changing characteristics of gut microbes and host metabolism during aging. However, more research is needed in the future to verify our findings.

Sex difference in cerebral atherosclerotic stenosis in Chinese asymptomatic subjects.

Background and purpose: Sex difference in cerebral atherosclerosis has been noted in previous studies, but the precise characteristics remain incompletely elucidated. This study aims to identify the sex difference in patients with asymptomatic cerebrovascular stenosis. Materials and methods: The image and clinical data of 1305 consecutive patients who had head and neck computed tomography angiography (CTA) were collected. Fifty hundred and seventy-three patients (287 males) with asymptomatic atherosclerotic stenosis in cerebral arteries were finally included. The stenosis number, distribution, severity and their changes with age were analyzed and compared between males and females. Simple linear regression was used to assess the change in lesions with age. Results: A total of 2097 stenoses were identified in 573 patients, males had more stenoses than females (3 [2, 5] vs 3 [2, 4], p=0.015). The number of stenoses in extracranial arteries was much higher in males (p = 0.001). Females had higher percentage of stenosis in anterior (89.6% vs 85.9%, p = 0.012) and intracranial arteries (63.3% vs 57.1%, p = 0.004) than males. Males had higher percentage of moderate-severe stenosis (5.1% vs 3.2%, p = 0.026). Age (OR = 1.67; 95% CI 1.24-2.25; p < 0.001) and hypertension (OR = 2.53; 95% CI 1.24-5.15; p = 0.01) were associated with moderate-severe stenosis. In patients over 50 years old, the number of stenoses increased by 1.03 per 10 years (p < 0.001), with 0.72 more stenoses in males (p = 0.003). Conclusions: Cerebral atherosclerotic stenosis was different between sexes regarding the distribution, severity and the change pattern with age, which underline the sex specific management in patients with cerebral atherosclerosis.