Genome-wide gene expression in a pharmacological hormonal transition model and its relation to depressive symptoms

Potential Pleiotropic Genes and Shared Biological Pathways in Epilepsy and Depression Based on GWAS Summary Statistics

Current epidemiological and experimental studies have indicated the overlapping genetic foundation of epilepsy and depression. However, the detailed pleiotropic genetic etiology and neurobiological pathways have not been well understood, and there are many variants with underestimated effect on the comorbidity of the two diseases. Utilizing genome-wide association study (GWAS) summary statistics of epilepsy (15,212 cases and 29,677 controls) and depression (170,756 cases and 329,443 controls) from large consortia, we assessed the integrated gene-based association with both diseases by Multimarker Analysis of Genomic Annotation (MAGMA) and Fisher's meta-analysis. On the one hand, shared genes with significantly altered transcripts in Gene Expression Omnibus (GEO) data sets were considered as possible pleiotropic genes. On the other hand, the pathway enrichment analysis was conducted based on the gene lists with nominal significance in the gene-based association test of each disease. We identified a total of two pleiotropic genes (CD3G and SLCO3A1) with gene expression analysis validated and interpreted twenty-five common biological process supported with literature mining. This study indicates the potentially shared genes associated with both epilepsy and depression based on gene expression, meta-data analysis, and pathway enrichment strategy along with traditional GWAS and provides insights into the possible intersecting pathways that were not previously reported.

Therapeutic Targets and Mechanism of Xingpi Jieyu Decoction in Depression: A Network Pharmacology Study

Background

Depression is a common mental disease that lacks effective therapeutic drugs with good curative effects and few adverse reactions. Traditional Chinese medicine (TCM) has the advantages of multiple components, multiple channels, and fewer adverse reactions in the treatment of depression. Although Xingpi Jieyu Decoction (XPJYD) demonstrates a good therapeutic effect on depression, the pharmacological mechanism underlying its antidepressant effect is still unclear.

Methods

We used a network pharmacology strategy, including the construction and analysis of a complex drug-disease network, to explore the complex mechanism of XPJYD treatment of depression. In addition, molecular docking technology was used to preliminarily study the binding ability of the potential active components and core therapeutic targets of XPJYD.

Results

The network pharmacology results showed 42 targets of XPJYD that are involved in depression. PPI network analysis demonstrated that the top 10 core targets were AKT1, VEGFA, MAPK8, FOS, ESR1, NR3C1, IL6, HIF1A, NOS3, and AR. The molecular docking results showed that the binding energies of beta sitosterol with AR, FOS, AKT1, VEGFA, NR3C1, and NOS3 were less than −7.0 kcal·mol⁻¹, indicating a good docking effect. The GO enrichment analysis results showed that the XPJYD antidepression mechanism mainly involves the following biological processes such as apoptotic signaling pathway, cellular response to lipid, inflammatory response, and others. The KEGG analysis results indicated that XPJYD may regulate 13 pathways such as PI3K-Akt signaling pathway and estrogen signaling pathway in the treatment of depression.

Conclusions

This study reflects the characteristics of the mechanism of action by which XPJYD treats depression, which includes multiple components, multiple targets, and multiple pathways, and provides a biological basis for further verification and a novel perspective for drug discovery in depression.

Genome-wide gene expression changes in postpartum depression point towards an altered immune landscape

Maternal postpartum depression (PPD) is a significant public health concern due to the severe negative impact on maternal and child health and well-being. In this study, we aimed to identify genes associated with PPD. To do this, we investigated genome-wide gene expression profiles of pregnant women during their third trimester of pregnancy and tested the association of gene expression with perinatal depressive symptoms. A total of 137 women from a cohort from the University of North Carolina, USA were assessed. The main phenotypes analysed were Edinburgh Postnatal Depression Scale (EPDS) scores at 2 months postpartum and PPD (binary yes/no) based on an EPDS cutoff of 10. Illumina NextSeq500/550 transcriptomic sequencing from whole blood was analysed using the edgeR package. We identified 71 genes significantly associated with postpartum depression scores at 2 months, after correction for multiple testing at 5% FDR. These included several interesting candidates including TNFRSF17, previously reported to be significantly upregulated in women with PPD and MMP8, a matrix metalloproteinase gene, associated with depression in a genome-wide association study. Functional annotation of differentially expressed genes revealed an enrichment of immune response-related biological processes. Additional analysis of genes associated with changes in depressive symptoms from recruitment to 2 months postpartum identified 66 genes significant at an FDR of 5%. Of these genes, 33 genes were also associated with depressive symptoms at 2 months postpartum. Comparing the results with previous studies, we observed that 15.4% of genes associated with PPD in this study overlapped with 700 core maternal genes that showed significant gene expression changes across multiple brain regions (P = 7.9e-05) and 29-53% of the genes were also associated with estradiol changes in a pharmacological model of depression (P values range = 1.2e-4-2.1e-14). In conclusion, we identified novel genes and validated genes previously associated with oestrogen sensitivity in PPD. These results point towards the role of an altered immune transcriptomic landscape as a vulnerability factor for PPD.

Rapid action of mechanism investigation of Yixin Ningshen tablet in treating depression by combinatorial use of systems biology and bioinformatics tools

ETHNOPHARMACOLOGICAL RELEVANCE

Yixin Ningshen tablet is a CFDA-approved TCM formula for treating depression clinically. However, little is known about its active compounds and related potential target proteins, so far, no researches have been performed to investigate its mechanism of action for the treatment of depression.

AIM OF THE STUDY

Here we develop an original bioinformatics pipeline composed of text mining tools, database querying and systems biology combinatorial analysis, which is applied to rapidly explore the mechanism of action of Yixin Ningshen tablet in treating depression.

MATERIALS AND METHODS

Text mining and database query were applied to identify active compounds in Yixin Ningshen tablet for the treatment of depression. Then SwissTargetPrediction was used to predict their potential target proteins. PubMed was retrieved to summarize known depression related systems biology results. Ingenuity Pathway Analysis (IPA) tools and STRING were applied to construct a compound-target protein-gene protein-differential protein-differential metabolite network with the integration of compound-target interaction and systems biology results, as well as enrich the target proteins related pathways. ChEMBL and CDOCKER were used to validate the compound-target interactions.

RESULTS

62 active compounds and their 286 potential target proteins were identified in Yixin Ningshen tablet for the treatment of depression. The construction of compound-target protein-gene protein-differential protein-differential metabolite network shrinked the number of potential target proteins from 286 to 133. Pathway enrichment analysis of target proteins indicated that Neuroactive ligand-receptor interaction, Calcium signaling pathway, Serotonergic synapse, cAMP signaling pathway and Gap junction were the common primary pathways regulated by both Yixin Ningshen Tablet and anti-depressant drugs, and MAPK, Relaxin, AGE-RAGE, Estrogen, HIF-1, Jak-STAT signaling pathway, Endocrine resistance, Arachidonic acid metabolism and Regulation of actin cytoskeleton were the specifically main pathways regulated by Yixin Ningshen tablet for the treatment of depression. Further validations based on references and molecular docking results demonstrated that Yixin Ningshen tablet could primarily target MAPT, CHRM1 and DRD1, thus regulating serotonergic neurons, cholinergic transmission, norepinephrine and dopamine reuptake for the treatment of depression.

CONCLUSIONS

This study displays the power of extensive mining of public data and bioinformatical repositories to provide answers for a specific pharmacological question. It furthermore demonstrates how the usage of such a combinatorial approach is advantageous for the biologist in terms of experimentation time and costs.