A Novel Network Pharmacology Strategy to Decode Metabolic Biomarkers and Targets Interactions for Depression

Study on plasma metabolomics profiling of depression in Chinese community-dwelling older adults based on untargeted LC/GC‒MS

Depression is a serious psychiatric illness that causes great inconvenience to the lives of elderly individuals. However, the diagnosis of depression is somewhat subjective. Nontargeted gas chromatography (GC)/liquid chromatography (LC)-mass spectrometry (MS) was used to study the plasma metabolic profile and identify objective markers for depression and metabolic pathway variation. We recruited 379 Chinese community-dwelling individuals aged ≥ 65. Plasma samples were collected and detected by GC/LC‒MS. Orthogonal partial least squares discriminant analysis and a heatmap were utilized to distinguish the metabolites. Receiver operating characteristic curves were constructed to evaluate the diagnostic value of these differential metabolites. Additionally, metabolic pathway enrichment was performed to reveal metabolic pathway variation. According to our standard, 49 people were included in the depression cohort (DC), and 49 people age- and sex-matched individuals were included in the non-depression cohort (NDC). 64 metabolites identified via GC‒MS and 73 metabolites identified via LC‒MS had significant contributions to the differentiation between the DC and NDC, with VIP values > 1 and p values < 0.05. Three substances were detected by both methods: hypoxanthine, phytosphingosine, and xanthine. Furthermore, 1-(sn-glycero-3-phospho)-1D-myo-inositol had the largest area under the curve (AUC) value (AUC = 0.842). The purine metabolic pathway is the most important change in metabolic pathways. These findings show that there were differences in plasma metabolites between the depression cohort and the non-depression cohort. These identified differential metabolites may be markers of depression and can be used to study the changes in depression metabolic pathways.

Network pharmacology: a bright guiding light on the way to explore the personalized precise medication of traditional Chinese medicine

Network pharmacology can ascertain the therapeutic mechanism of drugs for treating diseases at the level of biological targets and pathways. The effective mechanism study of traditional Chinese medicine (TCM) characterized by multi-component, multi-targeted, and integrative efficacy, perfectly corresponds to the application of network pharmacology. Currently, network pharmacology has been widely utilized to clarify the mechanism of the physiological activity of TCM. In this review, we comprehensively summarize the application of network pharmacology in TCM to reveal its potential of verifying the phenotype and underlying causes of diseases, realizing the personalized and accurate application of TCM. We searched the literature using "TCM network pharmacology" and "network pharmacology" as keywords from Web of Science, PubMed, Google Scholar, as well as Chinese National Knowledge Infrastructure in the last decade. The origins, development, and application of network pharmacology are closely correlated with the study of TCM which has been applied in China for thousands of years. Network pharmacology and TCM have the same core idea and promote each other. A well-defined research strategy for network pharmacology has been utilized in several aspects of TCM research, including the elucidation of the biological basis of diseases and syndromes, the prediction of TCM targets, the screening of TCM active compounds, and the decipherment of mechanisms of TCM in treating diseases. However, several factors limit its application, such as the selection of databases and algorithms, the unstable quality of the research results, and the lack of standardization. This review aims to provide references and ideas for the research of TCM and to encourage the personalized and precise use of Chinese medicine.

Downregulation of FTO in the hippocampus is associated with mental disorders induced by fear stress during pregnancy

Mental disorders (MD), such as anxiety, depression, and cognitive impairment, are very common during pregnancy and predispose to adverse pregnancy outcomes; however, the underlying mechanisms are still under intense investigation. Although the most common RNA modification in epigenetics, N6-methyladenosine (m6A) has been widely studied, its role in MD has not been investigated. Here, we observed that fat mass and obesity-associated protein (FTO) are downregulated in the hippocampus of pregnant rats with MD induced by fear stress and demonstrated that FTO participates in and regulates MD induced by fear stress. In addition, we identified four genes with anomalous modifications and expression (double aberrant genes) that were directly regulated by FTO, namely Angpt2, Fgf10, Rpl21, and Adcy7. Furthermore, we found that these genes might induce MD by regulating the PI3K/Akt and Rap1 signaling pathways. It appears that FTO-mediated m6A modification is a key regulatory mechanism in MD caused by fear stress during pregnancy.

Comprehensive Analysis of lncRNA-mRNA Expression Profiles in Depression-like Responses of Mice Related to Polystyrene Nanoparticle Exposure

Plastics in the environment can break down into nanoplastics (NPs), which pose a potential threat to public health. Studies have shown that the nervous system constitutes a significant target for nanoplastics. However, the potential mechanism behind nanoplastics' neurotoxicity remains unknown. This study aimed to investigate the role of lncRNA in the depressive-like responses induced by exposure to 25 nm polystyrene nanoplastics (PS NPs). Forty mice were divided into four groups administered doses of 0, 10, 25, and 50 mg/kg via gavage for 6 months. After conducting behavioral tests, RNA sequencing was used to detect changes in mRNAs, miRNAs, and lncRNAs in the prefrontal cortex of the mice in the 0 and 50 mg/kg PS NPs groups. The results revealed that mice exposed to chronic PS NPs developed depressive-like responses in a dose-dependent manner. It was demonstrated that 987 mRNAs, 29 miRNAs, and 116 lncRNAs were significantly different between the two groups. Then, a competing endogenous RNA (ceRNA) network containing 6 lncRNAs, 18 miRNAs, and 750 mRNAs was constructed. Enrichment results suggested that PS NPs may contribute to the onset of depression-like responses through the activation of axon guidance, neurotrophin-signaling pathways, and dopaminergic synapses. This study provided evidence of the molecular relationship between PS NPs and depression-like responses.

The 2210408F21Rik/miR-1968-5p/Hras axis regulates synapse-related proteins in a mouse model of depressive-like behaviors through a ceRNA mechanism

Abnormal expression of long non-coding RNAs (lncRNAs) has been correlated with depressive disorders, but limited data are available on the lncRNA-microRNA (miRNA/miR)-messenger RNA (mRNA) competitive endogenous RNA (ceRNA) mechanism in depression. Herein, we address this issue based on transcriptome sequencing and in vitro experiments. Mouse hippocampus tissues were obtained from chronic unpredictable mild stress (CUMS)-induced mice to screen out differentially expressed mRNAs and lncRNAs based on the transcriptome sequencing. Next, the depression-related differentially expressed genes (DEGs) were obtained, followed by Gene Ontology (GO) and Kyoto Encylopedia of Genes and Genomes (KEGG) enrichment analysis. A total of 1018 differentially expressed mRNAs, 239 differentially expressed lncRNAs, and 58 DEGs related to depression were acquired. The miRNAs targeting Harvey rat sarcoma virus oncogene (Hras) and miRNAs sponged by Hras-related lncRNA were intersected to identify the ceRNA regulatory network. In addition, the synapse-related genes related to depression were acquired by bioinformatics analysis. Hras was identified as the core gene related to depression, mainly related to neuronal excitation. We also found that 2210408F21Rik competitively bound to miR-1968-5p that targeted Hras. The effects of 2210408F21Rik/miR-1968-5p/Hras axis on neuronal excitation were verified in primary hippocampal neurons. The experimental data indicated that the downregulation of 2210408F21Rik increased the level of miR-1968-5p to diminish Hras expression, thereby affecting neuronal excitation in CUMS mice. In conclusion, the 2210408F21Rik/miR-1968-5p/Hras ceRNA network can potentially affect the expression of synapsia-related proteins and is a promising target for preventing and treating depression.

A Data-Driven Approach to Construct a Molecular Map of Trypanosoma cruzi to Identify Drugs and Vaccine Targets

Chagas disease (CD) is endemic in large parts of Central and South America, as well as in Texas and the southern regions of the United States. Successful parasites, such as the causative agent of CD, Trypanosoma cruzi have adapted to specific hosts during their phylogenesis. In this work, we have assembled an interactive network of the complex relations that occur between molecules within T. cruzi. An expert curation strategy was combined with a text-mining approach to screen 10,234 full-length research articles and over 200,000 abstracts relevant to T. cruzi. We obtained a scale-free network consisting of 1055 nodes and 874 edges, and composed of 838 proteins, 43 genes, 20 complexes, 9 RNAs, 36 simple molecules, 81 phenotypes, and 37 known pharmaceuticals. Further, we deployed an automated docking pipeline to conduct large-scale docking studies involving several thousand drugs and potential targets to identify network-based binding propensities. These experiments have revealed that the existing FDA-approved drugs benznidazole (Bz) and nifurtimox (Nf) show comparatively high binding energies to the T. cruzi network proteins (e.g., PIF1 helicase-like protein, trans-sialidase), when compared with control datasets consisting of proteins from other pathogens. We envisage this work to be of value to those interested in finding new vaccines for CD, as well as drugs against the T. cruzi parasite.

Comparative analysis of gut microbiota and fecal metabolome features among multiple depressive animal models

BACKGROUNDS

Emerging studies reported that gut microbiota and fecal metabolites take part in major depressive disorder (MDD) pathogenesis. However, the conclusions based on a single depressive animal model seem inconsistent or even controversial.

METHODS

Multiple depression rat models, including chronic unpredictable mild stress, chronic restraint stress, social defeat, and learned helplessness, were used. Then, the 16S ribosomal RNA gene sequencing and liquid chromatography-mass spectrometry analysis determined the alteration of gut microbiota and fecal metabolites.

RESULTS

The results of sucrose preference test and forced swimming test suggested that each model successfully established depression-like behavior. A total of 179 discriminative amplicon sequence variants (ASVs) were identified among four models. The overall discriminative ASVs mainly belonged to the family Lachnospiraceae, Muribaculaceae, and Oscillospiraceae. Moreover, the fecal metabolomic analysis identified 468 differential expressed metabolites. Among all the differential metabolites, 11 specific pathways significantly altered, which were mainly belonged to lipid and amino acid metabolism. Finally, co-occurrence network analysis suggested that target differential metabolites were associated with discriminative ASVs mainly assigned to family taxon Lachnospiraceae, Muribaculaceae, and Oscillospiraceae.

LIMITATIONS

The heterogeneity of MDD in humans cannot be totally imitated by animal models.

CONCLUSIONS

In multiple depression models, the alterations of family Lachnospiraceae, Muribaculaceae, and Oscillospiraceae with the dysbiosis of lipid and amino acid metabolism were gut microbiota and fecal metabolome features. The findings of our research may help us to have a comprehensive understanding of gut microbiota and fecal metabolome in depression.

Integrative resource for network-based investigation of COVID-19 combinatorial drug repositioning and mechanism of action

An effective monotherapy to target the complex and multifactorial pathology of SARS-CoV-2 infection poses a challenge to drug repositioning, which can be improved by combination therapy. We developed an online network pharmacology-based drug repositioning platform, COVID-CDR (http://vafaeelab.com/COVID19repositioning.html), that enables a visual and quantitative investigation of the interplay between the primary drug targets and the SARS-CoV-2-host interactome in the human protein-protein interaction network. COVID-CDR prioritizes drug combinations with potential to act synergistically through different, yet potentially complementary, pathways. It provides the options for understanding multi-evidence drug-pair similarity scores along with several other relevant information on individual drugs or drug pairs. Overall, COVID-CDR is a first-of-its-kind online platform that provides a systematic approach for pre-clinical in silico investigation of combination therapies for treating COVID-19 at the fingertips of the clinicians and researchers.

Diagnostic Biomarker Hsa_circ_0126218 and Functioning Prediction in Peripheral Blood Monocular Cells of Female Patients With Major Depressive Disorder

Introduction

Although major depressive diroder (MDD) has brought huge burden and challenges to society globally, effective and accurate diagnoses and treatments remain inadequate. The pathogenesis that for women are more likely to suffer from depression than men needs to be excavated as well. The function of circRNAs in pathological process of depression has not been widely investigated. This study aims to explore potential diagnostic biomarker circRNA of female patients with MDD and to investigate its role in pathogenesis.

Methods

First, an expression profile of circRNAs in the peripheral blood monocular cells of MDD patients and healthy peripherals were established based on high-throughput sequencing analysis. In addition, the top 10 differentially expressed circRNAs were quantified by quantitative real-time PCR to explore diagnostic biomarkers. To further investigate the function of biomarkers in the pathogenesis of MDD, bioinformatics analysis on downstream target genes of the biomarkers was carried out.

Results

There is a mass of dysregulated circRNAs in PBMCs between female MDD patients and healthy controls. Among the top 10 differentially expressed circRNAs, hsa_circ_0126218 is more feasible as a diagnostic biomarker. The expression level of hsa_circ_0126218 displayed upregulation in patients with MDD and the area under the operating characteristic curve of hsa_circ_0126218 was 0.801 (95% CI 0.7226–0.8791, p < 0.0001). To explain the competing endogenous RNA role of hsa_circ_0126218 in the pathogenesis of female MDD, a hsa_circ_0126218-miRNA-mRNA network was established. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses stated that some of the enriched pathways downstream of hsa_circ_0126218 are closely related to MDD. Moreover, we established a protein-protein network to further screen out the hub genes (PIK3CA, PTEN, MAPK1, CDC42, Lyn, YES1, EPHB2, SMAD2, STAT1, and ILK). The function of hsa_circ_0126218 was refined by constructing a verified circRNA-predicted miRNA-hub gene subnetwork.

Conclusion

hsa_circ_0126218 can be considered as a new female MDD biomarker, and the pathogenesis of female MDD by the downstream regulation of hsa_circ_0126218 has been predicted. These findings may help further improve the early detection, effective diagnosis, convenient monitoring of complications, precise treatment, and timely recurrence prevention of depression.

Comprehensive Analysis Strategy of Nervous-Endocrine-Immune-Related Metabolites to Evaluate Arachidonic Acid as a Novel Diagnostic Biomarker in Depression

Depression is one of the most complex multifactorial diseases affected by genetic and environmental factors. The molecular mechanism underlying depression remains largely unclear. To address this issue, a novel nervous-endocrine-immune (NEI) network module was used to find the metabolites and evaluate the diagnostic ability of patients with depression. During this process, metabolites were acquired from a professional depression metabolism database. Over-representation analysis was performed using IMPaLA. Then, the metabolite-metabolite interaction (MMI) network of the NEI system was used to select key metabolites. Finally, the receiver operating characteristic curve analysis was evaluated for the diagnostic ability of arachidonic acid. The results show that the numbers of the nervous system, endocrine system, and immune system pathways are 10, 19, and 12 and the numbers of metabolites are 38, 52, and 13, respectively. The selected shared metabolite-enriched pathways can be 97.56% of the NEI-related pathways. Arachidonic acid was extracted from the NEI system network by using an optimization formula and validated by in vivo experiments. It was indicated that the proposed model was good at screening arachidonic acid for the diagnosis of depression. This method provides reliable evidences and references for the diagnosis and mechanism research of other related diseases.

The noncanonical chronicles: Emerging roles of sphingolipid structural variants

Sphingolipids (SPs) are structurally diverse and represent one of the most quantitatively abundant classes of lipids in mammalian cells. In addition to their structural roles, many SP species are known to be bioactive mediators of essential cellular processes. Historically, studies have focused on SP species that contain the canonical 18‑carbon, mono-unsaturated sphingoid backbone. However, increasingly sensitive analytical technologies, driven by advances in mass spectrometry, have facilitated the identification of previously under-appreciated, molecularly distinct SP species. Many of these less abundant species contain noncanonical backbones. Interestingly, a growing number of studies have identified clinical associations between these noncanonical SPs and disease, suggesting that there is functional significance to the alteration of SP backbone structure. For example, associations have been found between SP chain length and cardiovascular disease, pain, diabetes, and dementia. This review will provide an overview of the processes that are known to regulate noncanonical SP accumulation, describe the clinical correlations reported for these molecules, and review the experimental evidence for the potential functional implications of their dysregulation. It is likely that further scrutiny of noncanonical SPs may provide new insight into pathophysiological processes, serve as useful biomarkers for disease, and lead to the design of novel therapeutic strategies.