AKT1 and genetic vulnerability to bipolar disorder

Progress and Implications from Genetic Studies of Bipolar Disorder

With the advancements in gene sequencing technologies, including genome-wide association studies, polygenetic risk scores, and high-throughput sequencing, there has been a tremendous advantage in mapping a detailed blueprint for the genetic model of bipolar disorder (BD). To date, intriguing genetic clues have been identified to explain the development of BD, as well as the genetic association that might be applied for the development of susceptibility prediction and pharmacogenetic intervention. Risk genes of BD, such as CACNA1C, ANK3, TRANK1, and CLOCK, have been found to be involved in various pathophysiological processes correlated with BD. Although the specific roles of these genes have yet to be determined, genetic research on BD will help improve the prevention, therapeutics, and prognosis in clinical practice. The latest preclinical and clinical studies, and reviews of the genetics of BD, are analyzed in this review, aiming to summarize the progress in this intriguing field and to provide perspectives for individualized, precise, and effective clinical practice.

Potential pharmacological mechanisms of tanshinone IIA in the treatment of human neuroblastoma based on network pharmacological and molecular docking Technology

Tanshinone IIA (Tan-IIA) is the main bioactive component of Chinese herbal medicine salvia miltiorrhiza (Danshen). Sodium sulfonate of Tan-IIA is widely used in the treatment of cardiovascular and cerebrovascular diseases. Tan-IIA also has inhibitory effects on tumor cells such as gastric cancer, but its therapeutic effect and mechanism on human neuroblastoma have not been evaluated, so its pharmacological mechanism is systematically evaluated by the combined method of network pharmacology and molecular docking. PharmMapper and SwissTargetPrediction predicted 331 potential Tan-IIA-related targets, and 1,152 potential neuroblastoma-related targets were obtained from GeneCards, DisGeNET, DrugBank, OMIM and Therapeutic Target databases (TTD), 107 common targets for Tan-IIA and neuroblastoma. Through gene ontology (GO) functional annotation, Kyoto Encyclopedia of Genes and Genomesa (KEGG) pathway enrichment, protein-protein interaction (PPI) network and cytoHubba plug-in, 10 related signal pathways (Pathways in cancer, PI3K-Akt signaling pathway, Prostate cancer, etc.) and 10 hub genes were identified. The results of molecular docking showed that Tan-IIA could interact with 10 targets: GRB2, SRC, EGFR, PTPN1, ESR1, IGF1, MAPK1, PIK3R1, AKT1 and IGF1R. This study analyzed the related pathways and targets of Tan-IIA in the treatment of human neuroblastoma, as well as the potential anticancer and anti-tumor targets and related signaling pathways of Tan-IIA, which provides a reference for us to find and explore effective drugs for the treatment of human neuroblastoma.

T-cell exhaustion prediction algorithm in tumor microenvironment for evaluating prognostic stratification and immunotherapy effect of esophageal cancer

Esophageal cancer (EC) is a common digestive malignancy that ranks sixth in cancer deaths, with a 5-year survival rate of 15%-25%. As a result, reliable prognostic biomarkers are required to accurately predict the prognosis of EC. T-cell exhaustion (TEX) is associated with poorer prognosis and immune infiltration in EC. In this study, nine risk genes were finally screened to constitute the prognostic model using least absolute shrinkage and selection operator analysis. Patients were divided into two groups based on the expression of the TEX-related genes: high-risk group and low-risk group. The expression of TEX-related genes differed significantly between the two groups. The findings revealed that the risk model developed was highly related to the clinical prognosis and amount of immune cell infiltration in EC patients. It was also significantly correlated with the therapeutic sensitivity of multiple chemotherapeutic agents in EC patients. Subsequently, we successfully constructed drug-resistant cell lines KYSE480/CDDP-R and KYSE180/CDDP-R to verify the correlation between PD-1 and drug resistance in EC. Then, we examined the mRNA and protein expression levels of PD-1 in parental and drug-resistant cells using qPCR and WB. It was found that the expression level of PD-1 was significantly increased in the plasma red of drug-resistant cells. Next, we knocked down PD-1 in drug-resistant cells and found that the resistance of EC cells to CDDP was significantly reduced. And the proportion of apoptotic cells in cells treated with 6 μM CDDP for 24 h was significantly in increase. The TEX-based risk model achieved good prediction results for prognosis prediction in EC patients. And it was also significantly associated with the level of immune cell infiltration and drug therapy sensitivity of EC patients. Additionally, the downregulation of PD-1 may be associated with increased drug sensitivity in EC and enhanced T-cell infiltration. The high-risk group had lower TIDE scores, indicating that the high-risk group benefits more after receiving immunotherapy. Thus, the TEX-based risk model can be used as a novel tumor prognostic biomarker.

Ginsenoside Rg1 can reverse fatigue behavior in CFS rats by regulating EGFR and affecting Taurine and Mannose 6-phosphate metabolism

Background: Chronic fatigue syndrome (CFS) is characterized by significant and persistent fatigue. Ginseng is a traditional anti-fatigue Chinese medicine with a long history in Asia, as demonstrated by clinical and experimental studies. Ginsenoside Rg1 is mainly derived from ginseng, and its anti-fatigue metabolic mechanism has not been thoroughly explored. Methods: We performed non-targeted metabolomics of rat serum using LC-MS and multivariate data analysis to identify potential biomarkers and metabolic pathways. In addition, we implemented network pharmacological analysis to reveal the potential target of ginsenoside Rg1 in CFS rats. The expression levels of target proteins were measured by PCR and Western blotting. Results: Metabolomics analysis confirmed metabolic disorders in the serum of CFS rats. Ginsenoside Rg1 can regulate metabolic pathways to reverse metabolic biases in CFS rats. We found a total of 34 biomarkers, including key markers Taurine and Mannose 6-phosphate. AKT1, VEGFA and EGFR were identified as anti-fatigue targets of ginsenoside Rg1 using network pharmacological analysis. Finally, biological analysis showed that ginsenoside Rg1 was able to down-regulate the expression of EGFR. Conclusion: Our results suggest ginsenoside Rg1 has an anti-fatigue effect, impacting the metabolism of Taurine and Mannose 6-phosphate through EGFR regulation. This demonstrates ginsenoside Rg1 is a promising alternative treatment for patients presenting with chronic fatigue syndrome.

Systematic review of Kaixinsan in treating depression: Efficacy and pharmacological mechanisms

Introduction

Kaixinsan (KXS) has been in use as an effective classic formulation of traditional Chinese medicine for depression. However, its active components and action mechanism against depression remain elusive. The purpose of this study was to summarize and evaluate the efficacy and potential pharmacological mechanisms of KXS in antidepressant treatment.

Materials and methods

Reports on the use of KXS in the treatment of depression were systematically collected from PubMed, Web of Science, Embase, China National Knowledge Infrastructure, Chongqing VIP, and Wanfang Data from the establishment to July 2022, including those on mood disorders in neurological diseases such as Alzheimer's disease. Meta-analysis was conducted with the Review Manager 5.3 software. Online datasets, traditional Chinese medicine system pharmacological analysis platform, GeneCards, online Mendelian inheritance in man, and DisGeNET were used to investigate the depression-related genes. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments were performed to construct the 'component-target-pathways' network using Metascape online analyses.

Result

Ten studies were included in the analysis. Meta-analysis showed that both low-dose KXS (SMD = 19.66, Z = 7.96, and I ² = 42%) and high-dose KXS (SMD = 23.84, Z = 8.46, and I ² = 13%) could increase the sucrose preference in depression models. In addition, 5-hydroxytryptamine (5-HT) (SMD = 10.91, Z = 2.95, and I ² = 50%) returned to normal level after the treatment at low dose KXS. In network pharmacology, 50 active components and 376 gene targets were screened out. AKT1, GAPDH, ALB, TNF, and TP53 were the core target proteins. GO analysis showed that KXS mainly treats depression in biological processes such as response to drugs, cellular calcium ion homeostasis, and regulation of chemical synaptic signal transmission. KEGG results show that the mechanism of action of KXS in treating depression is through neural activity ligand-receptor interaction, the calcium signaling and CAMP signaling pathways.

Discussion

The study reveals the active components and potential molecular mechanism of KXS in the treatment of depression and provides evidence for future basic research.

Discovery of Biomarkers and Potential Mechanisms of Agarwood Incense Smoke Intervention by Untargeted Metabolomics and Network Pharmacology

Background

Agarwood, as a traditional Chinese medicine, has great potential value for the treatment of tranquilization. However, its potential mechanisms and biomarkers are still unclear.

Methods

In this study, ultra-high performance liquid chromatography-quadrupole-Exactive Orbitrap mass spectrometry (UHPLC-Q-Exactive Orbitrap-MS)-based metabonomics was adopted to discover the potential biomarkers in mice after agarwood incense smoke (AIS) intervention. Furthermore, the chemical components in agarwood were identified based on UHPLC-Q-Exactive Orbitrap-MS. The global view of potential compound-target-pathway (C-T-B) network was constructed through network pharmacology to understand the potentially material basis of biomarkers.

Results

Metabolic profiling indicated that the metabolic changed significantly in mice serum after AIS intervention. A total of 18 potential biomarkers closely related to insomnia and emotional disease were identified, mainly involving in tryptophan metabolism, arginine and proline metabolism, cysteine and methionine metabolism and steroid hormone biosynthesis pathways. A total of 138 components in agarwood were identified based on UHPLC-Q-Exactive Orbitrap-MS. The results showed that mainly compounds such as flidersia type 2-(2-phenylethyl) chromones (FTPECs) and sesquiterpenes exerted good docking abilities with key target proteins, which were involved in multiple diseases including depression and hypnosis.

Conclusion

In conclusion, this study enhanced current understanding of the change of metabolic markers after AIS intervention. Meanwhile, it also confirmed the feasibility of combining metabolomics and network pharmacology to identify active components and elucidate the material basis of biomarkers and mechanisms.