GO Functional Enrichment Analysis Research Articles

Genome-wide investigation of lncRNAs revealed their tight association with gastric cancer

BackgroundGastric cancer (GC) is a significant health issue globally, ranking as the fifth most common cancer with over 10,000 new cases reported annually. Long non-coding RNA (lncRNA) has emerged as a critical player in cellular functions, influencing GC's development, growth, metastasis, and prognosis. However, our understanding of lncRNA's role in the pathogenesis of GC remains limited. Therefore, it is particularly important to explore the relationship between lncRNA and gastric cancer.Methodswe conducted a comprehensive analysis of RNA sequencing data from the GEO database and stomach adenocarcinoma (STAD) data from the TCGA database to identify lncRNAs that exhibit altered expression levels in GC and the mechanisms underlying lncRNA-mediated transcription and post-transcriptional regulation were explored.ResultsThis study uncovered 94 lncRNAs with differential expression and, through co-expression analysis, linked these to 1508 differentially expressed genes (DEGs). GO functional enrichment analysis highlighted that these DEGs are involved in critical pathways, such as cell adhesion and the positive regulation of cell migration. By establishing a lncRNA-miRNA-mRNA regulatory network, we found that the ceRNA mechanism, particularly involving RP11-357H14.17 and CTD-2377D24.4, could play a role in GC progression. Experimental validation of selected differentially expressed lncRNAs and mRNAs (including RP11-357H14.17-CLDN1, BBOX1, TRPM2-AS, CLDN1, PLAU, HOXB7) confirmed the RNA-seq results.ConclusionsOverall, our findings highlight the critical role of the lncRNA-mRNA regulatory network in the development and progression of GC, offering potential biomarkers for diagnosis and targets for innovative treatment strategies.

Label free quantitative proteomic profiling of serum samples of intellectually disabled young patients revealed dysregulation of complement coagulation and cholesterol cascade systems.

Intellectual disability is a heterogeneous disorder, diagnosed using intelligence quotient (IQ) score criteria. Currently, no specific clinical test is available to diagnose the disease and its subgroups due to inadequate understanding of the pathophysiology. Therefore, current study was designed to explore the molecular mechanisms involved in disease perturbation, and to identify potential biomarkers for disease diagnosis and prognosis. A total of 250 participants were enrolled in this study, including 200 intellectually disabled (ID) subjects from the subgroups (mild, moderate, and severe) with age and gender matched healthy controls (n = 50). Initially, IQ testing score and biochemical profile of each subject was generated, followed by label-free quantitative proteomics of subgroups of IQ and healthy control group through nano-LC/MS- mass spectrometry. A total of 310 proteins were identified, among them198 proteins were common among all groups. Statistical analysis (ANOVA) of the subgroups of ID showed 142 differentially expressed proteins, in comparison to healthy control group. From these, 120 proteins were found to be common among all subgroups. The remaining 22 proteins were categorized as exclusive proteins found only in disease subgroups. Furthermore, the hierarchical cluster analysis (HCL) of common significant proteins was also performed, followed by PANTHER protein classification and GO functional enrichment analysis. Results provides that the datasets of differentially expressed proteins, belong to the categories of immune / defense proteins, transfer carrier proteins, apolipoproteins, complement proteins, protease inhibitors, hemoglobin proteins etc., they are known to involvein immune system, and complement and coagulation pathway cascade and cholesterol metabolism pathway. Exclusively expressed 22 proteins were found to be disease stage specific and strong PPI network specifically those that have significant role in platelets activation and degranulation, such as Filamin A (FLNA). Furthermore, to validate the mass spectrometric findings, four highly significant proteins (APOA4, SAP, FLNA, and SERPING) were quantified by ELISA in all the study subjects. AUROC analysis showed a significant association of APOA4 (0.830), FLNA (0.958), SAP (0.754) and SERPING (0.600) with the disease. Apolipoprotein A4 (APOA4) has a significant role in cholesterol transport, and in modulation of glucose and lipid metabolism in the CNS. Similarly, FLNA has a crucial role in the nervous system, especially in the functioning of synaptic network. Therefore, both APOA4, and FLNA proteins represent good potential for candidate biomarkers for the diagnosis and prognosis of the intellectual disability. Overall, serum proteome of ID patients provides valuable information of proteins/pathways that are altered during ID progression.

Auxiliary diagnosis and prognosis evaluation of KIF4A, RAD51AP1 and CDKN3 in esophageal cancer

To investigate the expression of mRNA in esophageal cancer (ESCA) tissues and its potential and diagnostic and prognostic value by high-throughput sequencing data. Using the Cancer Genome Atlas Program (TCGA) database in USA by integrative bioinformatics analysis methods, the gene expression profiles and clinical data of 173 patients with ECSA were collected. The mRNA expression levels in ESCA tissue and para-cancerous tissue samples were analyzed using DESeq2, edgeR and limma to screen the differentially expressed genes (DEGs). DEGs-related protein network diagrams were drawn. GO and KEGG function enrichment analysis were performed and the hub genes were screened and the survival analysis of hub genes was analyzed. Genes related to the prognosis of ESCA were selected and their prognostic value in ESCA was analyzed. Finally, the receiver operating characteristic curve was drawn to evaluate its diagnostic value. The results showed that using TCGA cancer data, a total of 620 up-regulated DEGs and 668 down-regulated DEGs with significant differential expression between ESCA and para-cancerous tissues were screened. DEGs were mainly involved in receptor complexes, ubiquitin ligase complexes, etc., playing GTPase activity, phospholipid binding, and other molecular functions, and participating in the regulation of intracellular substance transport, small molecule metabolism, and other biological processes. Protein functional enrichment analysis showed that these proteins were mainly enriched in the IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, Epstein-Barr virus infection, neutrophil extracellular trap formation, and other pathways involved in the formation and development process of ESCA. Survival analysis showed that the overall survival rate of ESCA patients with high expression of KIF4A, RAD51AP1, and CDKN3 was significantly shortened, and the difference was statistically significant (P<0.05). Furthermore, the areas under the curve (AUC) of KIF4A, RAD51AP1, and CDKN3 for diagnosing esophageal cancer were 0.956, 0.951 and 0.979, respectively, with sensitivities and specificities both exceeding 80%. Additionally, ROC results of the combined diagnostic model of these three genes showed an AUC of 0.979, with sensitivities and specificities of 0.914 and 1, respectively. This indicates that KIF4A, RAD51AP1 and CDKN3 have individual or combined auxiliary diagnostic value for ESCA. In conclusion, KIF4A, RAD51AP1 and CDKN3 have high diagnostic efficiency for ESCA, and their increased expression is closely related to the prognosis, suggesting that these three genes could be used as auxiliary diagnostic and prognostic factors for ESCA.

Mechanism of Si Ni San Combined with Astragalus in Treating Hepatic Fibrosis: A Network Pharmacology and Molecular Docking Study.

Si Ni San combined with Astragalus (SNSQ) has demonstrated significant efficacy in the treatment of hepatic fibrosis (HF), as confirmed by clinical practice. However, its pharmacological mechanism remains unclear. This study employs network pharmacology to identify key targets and proteins for molecular docking. Additionally, animal experiments were conducted to validate the network pharmacology results, providing further insights into the mechanism of SNSQ in treating HF. Effective compounds of SNSQ were screened from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) and Encyclopedia of Traditional Chinese Medicine (ETCM) databases. Molecular formula structures of these effective compounds were obtained from the PubChem database. Partial target proteins with a probability greater than 0.6 were sourced from the SWISS database. Uniprot IDs corresponding to these target proteins were retrieved from the SUPERPRED database. The remaining target proteins of the compounds were obtained from the Uniprot database based on the Uniprot IDs. The drug target proteins were then summarized. Target points related to HF were selected from the GeneCards and OMIM databases. Common target points were identified in the Venn diagram and imported into Cytoscape 3.9.1 software to construct the "SNSQ-effective compound-target pathway-HF" network. AutoDock software was used for molecular docking of compounds and target proteins with high-degree values. The common target points underwent GO function enrichment and KEGG pathway enrichment analysis using the DAVID database. An HF rat model was established, and serum AST and ALT activities were measured. The Hyp assay kit was utilized to detect the Hyp content in liver tissue. To the transcription levels of pro-inflammatory factors (IL-1β, TNF-α, IL-6) and anti-inflammatory factors (IL-10, TGF-β1, IL-4) in rat serum and liver.IL-1β, TNF-α, IL-10, and TGF-β1 were chosen for validation through ELISA. Western blotting and qRT-PCR were used to assess the expression of related proteins, namely NFKB1, NF-κBp65, NF-κBp50, α-SMA, and Col-1 in liver tissue. qRT-PCR was also employed to study the expression of ECM synthesis and proliferation-related genes, including Cyclin D1, TIMP1, COL1A1 in HSC-T6 cells and rat liver tissue, as well as the inhibition of the ECM-related gene MMP13 in HSC-T6 cells and rat liver tissue. A total of 16 valid compounds were predicted, with kaempferol, sitosterol, and isorhamnetin exhibiting high-degree values. KEGG enrichment analysis revealed that the target genes of SNSQ were enriched in multiple pathological pathways, with the NF-Kappa B signaling pathway being predominant. Molecular docking simulations indicated strong affinities between SNSQ's primary components-kaempferol, sitosterol, isorhamnetin-and NFKB1. Experimental results demonstrated significant reductions in AST, ALT, and Hyp levels in the SNSQ group. Pro-inflammatory factors (IL-1β, TNF-ɑ) were markedly reduced, while anti-inflammatory factors (IL-10, TGF-β1) were substantially increased. The protein expression and transcription levels of α-SMA and Col-1 were significantly decreased, whereas those of NFKB1, NF-κBp65, and NF-κBp50 were notably elevated. mRNA expression levels of Cyclin D1, TIMP1, COL1A1 in HSC-T6 cells and rat liver tissue were significantly decreased, whereas MMP13 mRNA expression level was significantly increased. Treatment of HF with SNSQ involves multiple targets and pathways, with a close association with the overexpression of NFKB1 and activation of the NF-Kappa B signaling pathway. Its mechanism is closely linked to the activation of inflammatory responses, HSC activation, and proliferation.

Huangqin-Huanglian Decoction Protects Liver against Non-alcoholic Fatty Liver Disease in High Fat-diet Mice.

Traditional Chinese medicine (TCM) has the advantage of low toxicity of natural ingredients, multiple targets and effects, and low medication costs. It has unique advantages for metabolic and chronic diseases. Huangqin-Huanglian decoction (HQHLD) is composed of Scutellariae Radix, Coptidis Rhizoma, Rehmanniae Radix, and Gentianae Radix Et Rhozima; it has great potential for the treatment of NAFLD with the modern pharmacological research and TCM theory, but there is still a relative lack of research on the potential targets and pharmacological effects of HQHLD. In this work, we have used network pharmacology to predict the targets and signaling pathways of HQHLD, and validated NAFLD-related targets using the HFD model in order to explore more therapeutic drugs and methods for NAFLD. We collected the HQHLD ingredients and NAFLD targets through TCMSP, ETCM, DisGeNET, HGMD, MalaCards, OMIM, and TTD, built ingredients-target networks by Cytoscape, and screened key ingredients in HQHLD. DAVID and Metascape databases were used for GO functional enrichment analysis and KEGG pathway enrichment analysis, respectively. Molecular docking of the key ingredients and key targets was performed by AutoDock. We verified the effect of HQHLD on high-fat diet (HFD) mice by measuring the weight, liver weight index, and the level of TG, TC, LDL-C, and HDLC. HE staining and oil-red staining were performed to detect the damage and fat accumulation in the liver. The changes in INSR, PPAR-α, PPAR-γ, TNF-α, and caspase3 were experimented with WB. With the network pharmacology analysis, we found quercetin, baicalein, sitosterol, wogonin, oroxylin-A, glycyrrhizin, hydroberberine, berberine, sesamin, and carotene to be the main ingredients in HQHLD. According to KEGG pathway analysis, INSR, AKT, JNK1, PPAR-α, PPAR-γ, and the other 16 targets are the main targets of HQHLD in the treatment of NAFLD. We took HFD mice as the in vivo model of NAFLD. Our results showed that HQHLD could reduce liver weight, and TG and LDL-C levels, and increase HDL-C level in serum. By HE and oil red staining, we found that HQHLD could protect the morphology of hepatocytes and reduce fat in the liver. We also found HQHLD to protect the liver by increasing the expression of INSR and PPAR-α, and reducing the expression of PPAR-γ, TNF-α, and caspase3 in the liver. In conclusion, our study has firstly studied the main ingredients and key targets of HQHDL in treating NAFLD by network pharmacology analysis, and preliminarily confirmed that HQHLD could alleviate NAFLD in a multi-target way by lowering fatty acids, and decreasing insulin resistance, inflammation, and apoptosis in the liver.

Exploring the impact of PDGFD in osteosarcoma metastasis through single-cell sequencing analysis.

The overall survival rate for metastatic osteosarcoma hovers around 20%. Responses to second-line chemotherapy, targeted therapies, and immunotherapies have demonstrated limited efficacy in metastatic osteosarcoma. Our objective is to validate differentially expressed genes and signaling pathways between non-metastatic and metastatic osteosarcoma, employing single-cell RNA sequencing (scRNA-seq) and additional functional investigations. We aim to enhance comprehension of metastatic mechanisms and potentially unveil a therapeutic target. scRNA-seq was performed on two primary osteosarcoma lesions (1 non-metastatic and 1 metastatic). Seurat package facilitated dimensionality reduction and cluster identification. Copy number variation (CNV) was predicted using InferCNV. CellChat characterized ligand-receptor-based intercellular communication networks. Differentially expressed genes underwent GO function enrichment analysis and GSEA. Validation was achieved through the GSE152048 dataset, which identified PDGFD-PDGFRB as a common ligand-receptor pair with significant contribution. Immunohistochemistry assessed PDGFD and PDGFRB expression, while multicolor immunofluorescence and flow cytometry provided insight into spatial relationships and the tumor immune microenvironment. Kaplan-Meier survival analysis compared metastasis-free survival and overall survival between high and low levels of PDGFD and PDGFRB. Manipulation of PDGFD expression in primary osteosarcoma cells examined invasion abilities and related markers. Ten clusters encompassing osteoblasts, osteoclasts, osteocytes, fibroblasts, pericytes, endothelial cells, myeloid cells, T cells, B cells, and proliferating cells were identified. Osteoblasts, osteoclasts, and osteocytes exhibited heightened CNV levels. Ligand-receptor-based communication networks exposed significant fibroblast crosstalk with other cell types, and the PDGF signaling pathway was activated in non-metastatic osteosarcoma primary lesion. These results were corroborated by the GSE152048 dataset, confirming the prominence of PDGFD-PDGFRB as a common ligand-receptor pair. Immunohistochemistry demonstrated considerably greater PDGFD expression in non-metastatic osteosarcoma tissues and organoids, correlating with extended metastasis-free and overall survival. PDGFRB expression showed no significant variation between non-metastatic and metastatic osteosarcoma, nor strong correlations with survival times. Multicolor immunofluorescence suggested co-localization of PDGFD with PDGFRB. Flow cytometry unveiled a highly immunosuppressive microenvironment in metastatic osteosarcoma. Manipulating PDGFD expression demonstrated altered invasive abilities and marker expressions in primary osteosarcoma cells from both non-metastatic and metastatic lesions. scRNA-seq illuminated the activation of the PDGF signaling pathway in primary lesion of non-metastatic osteosarcoma. PDGFD displayed an inhibitory effect on osteosarcoma metastasis, likely through the suppression of the EMT signaling pathway.

Interspecific grafting promotes poplar growth and drought resistance via regulating phytohormone signaling and secondary metabolic pathways

Populus cathayana (C) grafted onto P. deltoides (D) (C/D) can promote growth better than self-grafting (C/C and D/D). However, the mechanisms underlying growth and resistance to drought stress are not clear. In this study, we performed physiological and RNA-seq analysis on the different grafted combinations. It was found that C/D plants exhibited higher growth, net photosynthetic rate, IAA content and intrinsic water use efficiency (WUEi) than C/C and D/D plants under both well-watered and drought-stressed conditions. However, most growth, photosynthetic indices, and IAA content were decreased less in C/D, whereas ABA content, WUEi and root characteristics (e.g., root length, volume, surface area and vitality) were increased more in C/D than in other grafting combinations under drought-stressed conditions. Transcriptomic analysis revealed that the number of differentially expressed genes (DEGs) in leaves of C/D vs C/C (control, 181; drought, 121) was much lower than that in the roots of C/D vs D/D (control, 1639; drought, 1706), indicating that the rootstocks were more responsive to drought resistance. KEGG and GO functional enrichment analysis showed that the enhanced growth and drought resistance of C/D were mainly related to DEGs involved in the pathways of ABA and IAA signaling, and secondary metabolite biosynthesis, especially the pathways for lignin and dopamine synthesis and metabolism. Therefore, our results further demonstrated the dominant role of rootstock in drought resistance, and enriched our knowledge on the mechanism of how interspecific grafting enhanced the growth and drought resistance in poplar.

The m6A methyltransferase METTL5 promotes neutrophil extracellular trap network release to regulate hepatocellular carcinoma progression.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide, it has a poor prognosis due to its highly invasive and metastatic nature. Consequently, identifying effective prognostic markers and potential therapeutic targets has been extensively investigated. METTL5, an 18S rRNA methyltransferase, is abnormally high in HCC. But its biological function and prognostic significance in HCC remain largely unelucidated. This study aimed to investigate the role of METTL5 in HCC progression, and elucidate its possible molecular mechanisms in HCC via transcriptome sequencing, providing new insights for identifying new HCC prognostic markers and therapeutic targets. The METTL5 expression in HCC and paracancerous tissues was analyzed using HCC immunohistochemical microarrays and bioinformatic retrieval methods to correlate METTL5 with clinicopathological features and survival prognosis. We constructed a METTL5 knockdown hepatocellular carcinoma cell line model and an animal model to determine the effect of METTL5 on hepatocellular carcinoma progression. Subsequently, RNA sequencing was performed to analyze the molecular mechanism of METTL5 in HCC based on the sequencing results, and relevant experiments were performed to verify it. We found that METTL5 expression was elevated in hepatocellular carcinoma tissues and correlated with poor patient prognosis, and in the analysis of clinicopathological features showed a correlation with TNM staging. In hepatocellular carcinoma cell lines with knockdown of METTL5, the malignant biological behavior was significantly reduced both invitro and invivo. Based on the sequencing results as well as the results of GO functional enrichment analysis and KEGG pathway enrichment analysis, we found that METTL5 could promote the generation and release of neutrophil extracellular capture network (NETs) and might further accelerate the progression of HCC. The m6A methyltransferase METTL5 is overexpressed in hepatocellular carcinoma (HCC) and correlates with poor prognosis. METTL5 accelerates malignant progression of HCC by promoting generation and release of the neutrophil extracellular traps (NETs) network, providing new insights for clinical biomarkers and immunotherapeutic targets in HCC prognosis.

Effect of stability of PTEN on hepatocellular carcinoma.

As an antioncogene gene, phosphataseandtensinhomolog (PTEN) is closely related to tumorigenesis. However, after mutation, PTEN will lose its function and no longer exert a tumor suppression effect. Through this research, we explored the impact of PTEN mutation on hepatic carcinoma (HCC) and the mechanism of PTEN for regulating HCC. First, bioinformatics was used to analyze the prognosis of PTEN in HCC. PTEN-related genes were then further analyzed by the LinkedOmics database, and GO and KEGG functional enrichment analysis were performed. Next, databases were utilized to predict the mutation and mutation frequency of PTEN. Eventually, CRISPR-Cas12a was applied to detect the R130Q mutation on PTEN in clinical samples of HCC. Finally, the fact that miR-92a-3p targets PTEN was identified by dual luciferase reporter gene assays, RT-qPCR, western blot, and rescue experiments. Bioinformatics analysis indicated the high mutation frequency of R130Q/G/L* site on the PTEN gene. Through CRISPR-Cas12a, R130Q mutation was detected on PTEN in 26 out of 40 clinical samples of HCC. On the one hand, our study revealed that CRISPR-Cas12a might play an important role in the screening and prognosis of HCC as a new clinical method to detect PTEN mutation.

Quantitative Proteomic Analysis Identifying and Evaluating TRAF6 and IL-8 as Potential Diagnostic Biomarkers in Neonatal Patients with Necrotizing Enterocolitis.

Necrotizing enterocolitis (NEC) is a common gastrointestinal complication in premature infants, resulting in high morbidity and mortality, and its early detection is crucial for accurate treatment and outcome prediction. Extensive research has demonstrated a clear correlation between NEC and extremely low birth weight, degree of preterm, formula feeding, infection, hypoxic/ischemic damage, and intestinal dysbiosis. The development of noninvasive biomarkers of NEC from stool, urine, and serum has attracted a great deal of interest because to these clinical connections and the quest for a deeper knowledge of disease pathophysiology. Therefore, this study aims to identify protein expression patterns in NEC and discover innovative diagnostic biomarkers. In this study, we recruited five patients diagnosed with NEC and paired necrotic segments of intestinal tissue with adjacent normal segments of intestine to form experimental and control groups. Quantitative proteomics tandem mass tagging (TMT) labeling technique was used to detect and quantify the proteins, and the expression levels of the candidate biomarkers in the intestinal tissues were further determined by quantitative polymerase chain reaction (RT-qPCR), Western blot analysis, Immunofluorescence methods and enzyme-linked immunosorbent assay (ELISA). A total of 6880 proteins were identified and quantified in patients with NEC. A significant disparity in protein expression was observed between necrotic and normal segments of intestinal tissue in NEC patients. A total of 55 proteins were found to be upregulated, and 40 proteins were found to be downregulated in NEC patients when using a p-value of < 0.05, and an absolute fold change of > 1.2 for analysis. GO function enrichment analysis showed the positive regulation of significant biological processes such as mitochondrial organization, vasoconstriction, rRNA catabolism, fluid shear stress response, and glycerol ether biosynthesis processes. Enrichment analysis also revealed essential functions such as ligand-gated ion channel activity, potassium channel activity, ligand-gated cation channel activity, ligand-gated ion channel activity, and ligand-gated channel activity, including molecular functions such as ligand-gated ion channel activity and mitotic events in this comparative group. Significant changes were found in endomembrane protein complex, membrane fraction, mitochondrial membrane fraction, membrane components, membrane intrinsic components, and other localized proteins. Additional validation of intestinal tissue and serum revealed a substantial increase in TRAF6 (tumor necrosis factor receptor-associated factor 6) and IL-8(Interleukin-8, CXCL8). The quantitative proteomic TMT method can effectively detect proteins with differential expression in the intestinal tissues of NEC patients. Proteins TRAF6 and CXCL8/IL-8 are significantly upregulated in the intestinal tissues and serum samples of patients and may serve as valuable predictor factors for NEC's early diagnosis.

Mining Heat-Resistant Key Genes of Peony Based on Weighted Gene Co-Expression Network Analysis.

The RNA-Seq and gene expression data of mature leaves under high temperature stress of Paeonia suffruticosa 'Hu Hong' were used to explore the key genes of heat tolerance of peony. The weighted gene co-expression network analysis (WGCNA) method was used to construct the network, and the main modules and core genes of co-expression were screened according to the results of gene expression and module function enrichment analysis. According to the correlation of gene expression, the network was divided into 19 modules. By analyzing the expression patterns of each module gene, Blue, Salmon and Yellow were identified as the key modules of peony heat response related functions. GO and KEGG functional enrichment analysis was performed on the genes in the three modules and a network diagram was constructed. Based on this, two key genes PsWRKY53 (TRINITY_DN60998_c1_g2, TRINITY_DN71537_c0_g1) and PsHsfB2b (TRINITY_DN56794_c0_g1) were excavated, which may play a key role in the heat shock response of peony. The three co-expression modules and two key genes were helpful to further elucidate the heat resistance mechanism of P. suffruticosa 'Hu Hong'.

The brain-heart axis: Integrative analysis of the shared genetic etiology between neuropsychiatric disorders and cardiovascular disease

BackgroundMultiple observational studies have reported substantial comorbidity between neuropsychiatric disorders and cardiovascular disease (CVD), but the underlying mechanisms remain largely unknown. MethodsUsing GWAS summary datasets of 8 neuropsychiatric disorders and 6 cardiovascular diseases, an integrative analysis incorporating linkage-disequilibrium-score-regression (LDSC), Mendelian randomization (MR), functional mapping and annotation (FUMA), and functional enrichment analysis, was conducted to investigate shared genetic etiology of the brain-heart axis from the whole genome level, single-nucleotide polymorphism (SNP) level, gene level, and biological pathway level. ResultsIn LDSC analysis, 18 pairwise traits between neuropsychiatric disorders and CVD were identified with significant genetic overlaps, revealing extensive genome-wide genetic correlations. In bidirectional MR analysis, 19 pairwise traits were identified with significant causal relationships. Genetic liabilities to neuropsychiatric disorders, particularly attention-deficit hyperactivity disorder and major depressive disorder, conferred extensive significant causal effects on the risk of CVD, while hypertension seemed to be a risk factor for multiple neuropsychiatric disorders, with no significant heterogeneity or pleiotropy. In FUMA analysis, 13 shared independent significant SNPs and 887 overlapping protein-coding genes were detected between neuropsychiatric disorders and CVD. With GO and KEEG functional enrichment analysis, biological pathways of the brain-heart axis were highly concentrated in neurotransmitter synaptic transmission, lipid metabolism, aldosterone synthesis and secretion, glutathione metabolism, and MAPK signaling pathway. ConclusionExtensive genetic correlations and genetic overlaps between neuropsychiatric disorders and CVD were identified in this study, which might provide some new insights into the brain-heart axis and the therapeutic targets in clinical practice.

Integrating network pharmacology with molecular docking to rationalize the ethnomedicinal use of Alchornea laxiflora (Benth.) Pax & K. Hoffm. for efficient treatment of depression.

Background: Alchornea laxiflora (Benth.) Pax & K. Hoffm. (A. laxiflora) has been indicated in traditional medicine to treat depression. However, scientific rationalization is still lacking. Hence, this study aimed to investigate the antidepressant potential of A. laxiflora using network pharmacology and molecular docking analysis. Materials and methods: The active compounds and potential targets of A. laxiflora and depression-related targets were retrieved from public databases, such as PubMed, PubChem, DisGeNET, GeneCards, OMIM, SwissTargetprediction, BindingDB, STRING, and DAVID. Essential bioactive compounds, potential targets, and signaling pathways were predicted using in silico analysis, including BA-TAR, PPI, BA-TAR-PATH network construction, and GO and KEGG pathway enrichment analysis. Later on, with molecular docking analysis, the interaction of essential bioactive compounds of A. laxiflora and predicted core targets of depression were verified. Results: The network pharmacology approach identified 15 active compounds, a total of 219 compound-related targets, and 14,574 depression-related targets with 200 intersecting targets between them. SRC, EGFR, PIK3R1, AKT1, and MAPK1 were the core targets, whereas 3-acetyloleanolic acid and 3-acetylursolic acid were the most active compounds of A. laxiflora with anti-depressant potential. GO functional enrichment analysis revealed 129 GO terms, including 82 biological processes, 14 cellular components, and 34 molecular function terms. KEGG pathway enrichment analysis yielded significantly enriched 108 signaling pathways. Out of them, PI3K-Akt and MAPK signaling pathways might have a key role in treating depression. Molecular docking analysis results exhibited that core targets of depression, such as SRC, EGFR, PIK3R1, AKT1, and MAPK1, bind stably with the analyzed bioactive compounds of A. laxiflora. Conclusion: The present study elucidates the bioactive compounds, potential targets, and pertinent mechanism of action of A. laxiflora in treating depression. A. laxiflora might exert an antidepressant effect by regulating PI3K-Akt and MAPK signaling pathways. However, further investigations are required to validate.

Neurodevelopmental toxicity and molecular mechanism of environmental concentration of tetrabromobisphenol A bis (2- hydroxyethyl) ether exposure to sexually developing male SD rats

Tetrabromobisphenol A bis (2- hydroxyethyl) ether (TBBPA-DHEE), as one of the main derivatives of Tetrabromobisphenol A, been attracted attention for its health risks. In this study, the neurotoxicity, mechanism, and susceptivity of TBBPA-DHEE exposure to sexually developing male rats were systematically studied. Neurobehavioral research showed that TBBPA-DHEE exposure could significantly affect the behavior, learning,and memory abilities of male-developing rats, and aggravate their depression. TBBPA-DHEE exposure could inhibit the secretion of neurotransmitters. Transcriptomics studies show that TBBPA-DHEE can significantly affect gene expression, and a total of 334 differentially expressed genes are enriched. GO function enrichment analysis shows that TBBPA-DHEE exposure can significantly affect the expression of genes related to synapses and cell components. KEGG function enrichment analysis shows that TBBPA-DHEE exposure can significantly affect the expression of signal pathways related to nerves, nerve development, and signal transduction. Susceptibility analysis showed that female rats were more susceptible to TBBPA-DHEE exposure than male rats. Therefore, TBBPA-DHEE exposure has neurodevelopmental toxicity to male developmental rats, and female developmental rats are more susceptible than male developmental rats. Its possible molecular mechanism is that TBBPA-DHEE may inhibit the secretion of neurotransmitters and affect signal pathways related to neurodevelopment and signal transduction.

Bioinformatics analysis and experimental validation of key genes associated with lumbar disc degeneration and biomechanics

BackgroundLumbar disc degeneration (LDD) is an important pathological basis for the development of degenerative diseases of the lumbar spine. Most clinical patients have low back pain as their main symptom. The deterioration of the biomechanical environment is an important cause of LDD. Although there is a large amount of basic research on LDD, there are fewer reports that correlate biomechanical mechanisms with basic research. Our research aims to identify 304 key genes involved in LDD due to biomechanical deterioration, using a bioinformatics approach. We focus on SMAD3, CAV1, SMAD7, TGFB1 as hub genes, and screen for 30 potential target drugs, offering novel insights into LDD pathology and treatment options. MethodsThe Gene Cards, GenCLip3, OMIM and Drugbank databases were explored to obtain genes associated with biomechanics and LDD, followed by making veen plots to obtain both co-expressed genes. GO enrichment analysis and KEGG pathway analysis of the co-expressed genes were obtained using the DAVID online platform and visualised via a free online website. Protein interaction networks (PPI) were obtained through the STRING platform and visualised through Cytoscape 3.9.0. These genes were predicted for downstream interaction networks using the STITCH platform. Then, the GSE56081 dataset was used to validate the key genes. RT-PCR was used to detect mRNA expression of core genes in the degenerated nucleus pulposus (NP) samples and western bolt was used for protein expression. Lastly, the obtained hub genes were searched in the drug database (DGIdb) to find relevant drug candidates. ResultsFrom the perspective of biomechanics-induced LDD, we obtained a total of 304 genes, the GO functional enrichment and KEGG pathway enrichment analysis showed that the functions of these genes are mostly related to inflammation and apoptosis. The PPI network was constructed and four Hub genes were obtained through the plug-in of Cytoscape software, namely SMAD3, CAV1, SMAD7 and TGFB1. The analysis of key genes revealed that biomechanical involvement in LDD may be related to the TGF-β signaling pathway. Validation of the GSE56081 dataset revealed that SMAD3 and TGFB1 were highly expressed in degenerating NP samples. RT-PCR results showed that the mRNA expression of SMAD3 and TGFB1 was significantly increased in the severe degeneration group; Western blot results also showed that the protein expression of TGFB1 and P-SMAD3 was significantly increased. In addition, we identified 30 potential drugs. ConclusionThis study presented a new approach to investigate the correlation between biomechanical mechanisms and LDD. The deterioration of the biomechanical environment may cause LDD through the TGF-β signaling pathway. TGFB1 and SMAD3 are important core targets. The important genes, pathways and drugs obtained in this study provided a new basis and direction for the study, diagnosis and treatment of LDD.

Functional enrichment analysis reveals the involvement of DARS2 in multiple biological pathways and its potential as a therapeutic target in esophageal carcinoma.

The enzyme Aspartyl tRNA synthetase 2 (DARS2) is a crucial enzyme in the mitochondrial tRNA synthesis pathway, playing a critical role in maintaining normal mitochondrial function and protein synthesis. However, the role of DARS2 in ESCA is unclear. Transcriptional data of pan-cancer and ESCA were downloaded from UCSC XENA, TCGA, and GEO databases to analyze the differential expression of DARS2 between tumor samples and normal samples, and its correlation with clinicopathological features of ESCA patients. R was used for GO, KEGG, and GSEA functional enrichment analysis of DARS2 co-expression and to analyze the connection of DARS2 with glycolysis and m6A-related genes. In vitro experiments were performed to assess the effects of interfering with DARS2 expression on ESCA cells. TarBase v.8, mirDIP, miRTarBase, ENCORI, and miRNet databases were used to analyze and construct a ceRNA network containing DARS2. DARS2 was overexpressed in various types of tumors. In vitro experiments confirmed that interfering with DARS2 expression significantly affected the proliferation, migration, apoptosis, cell cycle, and glycolysis of ESCA cells. DARS2 may be involved in multiple biological pathways related to tumor development. Furthermore, correlation and differential analysis revealed that DARS2 may regulate ESCA m6A modification through its interaction with METTL3 and YTHDF1. A ceRNA network containing DARS2, DLEU2/has-miR-30a-5p/DARS2, was successfully predicted and constructed. Our findings reveal the upregulation of DARS2 in ESCA and its association with clinical features, glycolysis pathway, m6A modification, and ceRNA network. These discoveries provide valuable insights into the molecular mechanisms underlying ESCA.

High expression of TBRG4 in relation to unfavorable outcome and cell ferroptosis in hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) is the most common type of malignant liver tumor with poor prognosis. In this study, we investigated the expression of transforming growth factor beta regulator 4 (TBRG4) in HCC and its effects on the proliferation, invasion, and metastasis of HCC cells, and analyzed the possible molecular mechanisms.MethodDownloading the expression and clinical information of HCC samples in the TCGA database, analyzing the expression differences of TBRG4 by bioinformatics methods, analyzing the clinical relevance and prognostic significance. Performing GO, KEGG and GSEA enrichment analysis on the TBRG4-related gene set in patient HCC tissues. Applying cell counting, scratch test and Transwell experiment to study the biological function of TBRG4 in HCC. Mitochondrial membrane potential, apoptosis and ROS levels were evaluated to assess cell iron death. Western blot, RT-PCR, laser confocal microscopy and co-immunoprecipitation were used to detect and analyze the downstream signaling pathways and interacting molecules of TBRG4.ResultsBioinformatics analysis revealed that TBRG4 was abnormally highly expressed in HCC tumor tissues and was associated with poor prognosis and metastasis in HCC patients. GO and KEGG functional enrichment analysis showed that TBRG4 was related to oxidative stress and NADH dehydrogenase (ubiquinone) activity. GSEA enrichment analysis showed that TBRG4 was associated with Beta catenin independent wnt signaling and B cell receptor. Functional experiments confirmed that knocking down TBRG4 could inhibit the proliferation, migration, and invasion of HCC cells. Mechanistically, TBRG4 inhibited the function of HCC cells through the DDX56/p-AKT/GSK3β signaling pathway. In addition, interference with TBRG4 expression could reduce the mitochondrial membrane potential and accumulate ROS in HCC cells, leading to increased ferroptosis. Co-IP analysis showed that TBRG4 specifically bound to Beclin1.ConclusionTBRG4 is highly expressed in HCC tumor tissues and is associated with poor prognosis. It may regulate the proliferation, invasion, and metastasis of HCC cells through the DDX56/p-AKT/GSK3β signaling pathway. TBRG4 may interact with Beclin1 to regulate the ferroptosis of HCC cells.

Mechanism of Houpu Wenzhong Decoction in the Treatment of Chronic Gastritis and Depression Based on Network Pharmacology and Molecular Docking

Objective: The study aimed to discuss the possible mechanisms of Houpu Wenzhong Decoction in the treatment of chronic gastritis and depression based on network pharmacology and molecular docking. Methods: The chemical components and corresponding targets of seven crude drugs in Houpu Wenzhong Decoction were retrieved from the database TCMSP. The targets for treating chronic gastritis and depression were obtained from the database GeneCards. STRING 11.5 was used to establish the protein-protein interaction network of common targets among “chemical components- chronic gastritis-depression”, and then Cytoscape was employed for visual analysis. The targets with the top ten degrees were selected as key targets, which were then imported to BioGPS to obtain the distribution in organs and tissues. The common targets were analyzed via Go and KEGG pathway enrichment analyses using Metascape. The top ten degrees of active components were verified by molecular docking of key targets. Results: Under the conditions of OB ≥ 30% and DL ≥ 0.18, a total of 144 chemical components and related 251 targets of Houpu Wenzhong Decoction were retrieved. 1192 and 12902 targets were retrieved for chronic gastritis and depression from the GeneCards database, respectively. 104 common targets were obtained by intersection among the two diseases and drug targets. The key common targets have been found to be mainly distributed in organs and tissues, such as the adrenal cortex, amygdala, appendix, adrenal gland, colorectal, liver, and prostates, as observed through BioGPS analysis. 5141 biological processes, 354 cell components, and 615 molecular functions were obtained by GO functional enrichment analysis, and 302 signal pathways were obtained by KEGG enrichment analysis. Among these, IL-17, TNF, PI3K-Akt, and toll-like receptor signaling pathway have been found to be involved. Molecular docking results showed the key active components, naringenin and hesperidin, to have good binding activities with targets STAT3 and Jun. Conclusion: 104 common targets between chronic gastritis and depression have been obtained as the basis for Houpu Wenzhong Decoction to treat the two diseases. The ten key active ingredients have been found to act on 15 key signal pathways through 104 common key targets to treat the two diseases.

Genetic Analysis of Partially Resistant and Susceptible Chickpea Cultivars in Response to Ascochyta rabiei Infection.

The molecular mechanism involved in chickpea (Cicer arietinum L.) resistance to the necrotrophic fungal pathogen Ascochyta rabiei is not well documented. A. rabiei infection can cause severe damage in chickpea, resulting in significant economic losses. Understanding the resistance mechanism against ascochyta blight can help to define strategies to develop resistant cultivars. In this study, differentially expressed genes from two partially resistant cultivars (CDC Corinne and CDC Luna) and a susceptible cultivar (ICCV 96029) to ascochyta blight were identified in the early stages (24, 48 and 72 h) of A. rabiei infection using RNA-seq. Altogether, 3073 genes were differentially expressed in response to A. rabiei infection across different time points and cultivars. A larger number of differentially expressed genes (DEGs) were found in CDC Corinne and CDC Luna than in ICCV 96029. Various transcription factors including ERF, WRKY, bHLH and MYB were differentially expressed in response to A. rabiei infection. Genes involved in pathogen detection and immune signalings such as receptor-like kinases (RLKs), Leucine-Rich Repeat (LRR)-RLKs, and genes associated with the post-infection defence response were differentially expressed among the cultivars. GO functional enrichment and pathway analysis of the DEGs suggested that the biological processes such as metabolic process, response to stimulus and catalytic activity were overrepresented in both resistant and susceptible chickpea cultivars. The expression patterns of eight randomly selected genes revealed by RNA-seq were confirmed by quantitative PCR (qPCR) analysis. The results provide insights into the complex molecular mechanism of the chickpea defence in response to the A. rabiei infection.

Construction of LncRNA-Related ceRNA Networks in Longissimus Dorsi Muscle of Jinfen White Pigs at Different Developmental Stages.

The development of skeletal muscle in pigs might determine the quality of pork. In recent years, long non-coding RNAs (lncRNAs) have been found to play an important role in skeletal muscle growth and development. In this study, we investigated the whole transcriptome of the longissimus dorsi muscle (LDM) of Jinfen White pigs at three developmental stages (1, 90, and 180 days) and performed a comprehensive analysis of lncRNAs, mRNAs, and micro-RNAs (miRNAs), aiming to find the key regulators and interaction networks in Jinfen White pigs. A total of 2638 differentially expressed mRNAs (DE mRNAs) and 982 differentially expressed lncRNAs (DE lncRNAs) were identified. Compared with JFW_1d, there were 497 up-regulated and 698 down-regulated DE mRNAs and 212 up-regulated and 286 down-regulated DE lncRNAs in JFW_90d, respectively. In JFW_180d, there were 613 up-regulated and 895 down-regulated DE mRNAs and 184 up-regulated and 131 down-regulated DE lncRNAs compared with JFW_1d. There were 615 up-regulated and 477 down-regulated DE mRNAs and 254 up-regulated and 355 down-regulated DE lncRNAs in JFW_180d compared with JFW_90d. Compared with mRNA, lncRNA has fewer exons, fewer ORFs, and a shorter length. We performed GO and KEGG pathway functional enrichment analysis for DE mRNAs and the potential target genes of DE lncRNAs. As a result, several pathways are involved in muscle growth and development, such as the PI3K-Akt, MAPK, hedgehog, and hippo signaling pathways. These are among the pathways through which mRNA and lncRNAs function. As part of this study, bioinformatic screening was used to identify miRNAs and DE lncRNAs that could act as ceRNAs. Finally, we constructed an lncRNA-miRNA-mRNA regulation network containing 26 mRNAs, 7 miRNAs, and 17 lncRNAs; qRT-PCR was used to verify the key genes in these networks. Among these, XLOC_022984/miR-127/ENAH and XLOC_016847/miR-486/NRF1 may function as key ceRNA networks. In this study, we obtained transcriptomic profiles from the LDM of Jinfen White pigs at three developmental stages and screened out lncRNA-miRNA-mRNA regulatory networks that may provide crucial information for the further exploration of the molecular mechanisms during skeletal muscle development.