UNASSIGNED: Dilated cardiomyopathy (DCM) is the second leading cause of heart failure, with intricate pathophysiological underpinnings. In order to shed fresh light on the mechanistic research of DCM, we combined bulk RNA-seq and single-cell RNA-seq (scRNA-seq) data to examine significant cells and genes implicated in the disease.
UNASSIGNED: This analysis employed publicly accessible bulk RNA-seq and scRNA-seq DCM datasets. The scRNA-seq data underwent normalization, principal component, and t-distribution stochastic neighbor embedding analysis. Cell-to-cell communication networks and activity analysis were conducted using CellChat. Utilizing enrichment analysis, the marker genes\' role in the active cells was evaluated. After screening by limma software and weighted gene co-expression network analysis, the differentially expressed genes (DEGs) served as hub genes. Furthermore, these hub genes were subjected to immunological studies, transcription factor expression, and gene set enrichment. Lastly, the expression of the four hub genes and their connection to DCM were verified using the rat models.
UNASSIGNED: Fibroblasts and monocytes were chosen as hub cells from among the eight identified cell clusters; their marker genes intersected with DEGs to yield six hub genes. In addition, the six hub genes and the essential module genes intersected to yield four essential genes (ASPN, SFRP4, LUM, and FRZB) that were connected to the Wnt signaling pathway and highly expressed in fibroblast. The four hub DEGs had an expression pattern in the DCM rat model experiment results that was in line with the findings of the bioinformatics study. Additionally, there was a strong correlation between decreased cardiac function and the up-regulation of ASPN, SFRP4, LUM, and FRZB.
UNASSIGNED: Ultimately, bulk RNA-seq and scRNA-seq data identified fibroblasts and monocytes as the main cell types implicated in DCM. The highly expressed genes ASPN, FRZB, LUM, and SFRP4 in fibroblasts may aid in the mechanistic investigation of DCM.

Body weight (BW) is an important economic trait in chickens. The hypothalamus serves as a central regulator of appetite and energy balance, and extensive research has demonstrated its pivotal role in regulating BW. However, the molecular network of the hypothalamus regulating BW traits in chickens needs to be further illuminated. In the present study, 200 1-day-old male 817 broilers were reared to 50 d of age, and BW were recorded. 20 birds with the lowest BW were classified as the low body weight group (L-BWG), and 20 birds with the highest BW were classified as the high body weight group (H-BWG). 18 hypothalamic tissue samples were collected, including 5 from the L-BWG, 5 from the H-BWG, and 8 from the middle weight range, and were analyzed using RNA-seq and weighted gene co-expression network analysis (WGCNA). Among the 18 RNA-seq samples, 5 samples from the L-BWG and 5 from the H-BWG were selected for differential expression gene analysis. Compared with the L-BWG, 195 and 1,241 genes were upregulated and downregulated in the H-BWG, respectively. The WGCNA analysis classified all co-expressed genes in the hypothalamus of 817 broilers into 20 modules. Among these modules, the pink module was identified as significantly negatively (r = -0.81, P = 4×10-5) associated with BW. Furthermore, several genes, including Wnt family member 6 (WNT6), growth differentiation factor 11 (GDF11), bone morphogenetic protein 4 (BMP4), and erb-b2 receptor tyrosine kinase 4 (ERBB4), involved in \"regulation of developmental process\" and \"response to growth factor,\" were identified as hub genes that contribute to the regulation of BW. These results provide valuable information for further understanding of the gene expression and regulation affecting BW traits and will contribute to the molecular breeding of chickens in the future.

In pigs, meat quality depends markedly on the fatty acid (FA) content and composition of the intramuscular fat, which is partly determined by the gene expression in this tissue. The aim of this work was to identify the link between muscle gene expression and its FA composition. In an (Iberian × Duroc) × Duroc backcrossed pig population, we identified modules of co-expressed genes, and correlation analyses were performed for each of them versus the phenotypes, finding four relevant modules. Two of the modules were positively correlated with saturated FAs (SFAs) and monounsaturated FAs (MUFAs), while negatively correlated with polyunsaturated FAs (PUFAs) and the omega-6/omega-3 ratio. The gene-enrichment analysis showed that these modules had over-representation of pathways related with the biosynthesis of unsaturated FAs, the Peroxisome proliferator-activated receptor signalling pathway and FA elongation. The two other relevant modules were positively correlated with PUFA and the n-6/n-3 ratio, but negatively correlated with SFA and MUFA. In this case, they had an over-representation of pathways related with fatty and amino acid degradation, and with oxidative phosphorylation. Using a graphical Gaussian model, we inferred a network of connections between the genes within each module. The first module had 52 genes with 87 connections, and the most connected genes were ADIPOQ, which is related with FA oxidation, and ELOVL6 and FABP4, both involved in FA metabolism. The second module showed 196 genes connected by 263 edges, being FN1 and MAP3K11 the most connected genes. On the other hand, the third module had 161 genes connected by 251 edges and ATG13 was the top neighbouring gene, while the fourth module had 224 genes and 655 connections, and its most connected genes were related with mitochondrial pathways. Overall, this work successfully identified relevant muscle gene networks and modules linked with FA composition, providing further insights on how the physiology of the pigs influences FA composition.

Gene co-expression networks may encode hitherto inadequately recognized vulnerabilities for adult gliomas. By identifying evolutionally conserved gene co-expression modules around EGFR (EM) or PDGFRA (PM), we recently proposed an EM/PM classification scheme, which assigns IDH-wildtype glioblastomas (GBM) into the EM subtype committed in neural stem cell compartment, IDH-mutant astrocytomas and oligodendrogliomas into the PM subtype committed in early oligodendrocyte lineage. Here, we report the identification of EM/PM subtype-specific gene co-expression networks and the characterization of hub gene polypyrimidine tract-binding protein 1 (PTBP1) as a genomic alteration-independent vulnerability in IDH-wildtype GBM. Supervised by the EM/PM classification scheme, we applied weighted gene co-expression network analysis to identify subtype-specific global gene co-expression modules. These gene co-expression modules were characterized for their clinical relevance, cellular origin and conserved expression pattern during brain development. Using lentiviral vector-mediated constitutive or inducible knockdown, we characterized the effects of PTBP1 on the survival of IDH-wildtype GBM cells, which was complemented with the analysis of PTBP1-depedent splicing pattern and overexpression of splicing target neuron-specific CDC42 (CDC42-N) isoform.  Transcriptomes of adult gliomas can be robustly assigned into 4 large gene co-expression modules that are prognostically relevant and are derived from either malignant cells of the EM/PM subtypes or tumor microenvironment. The EM subtype is associated with a malignant cell-intrinsic gene module involved in pre-mRNA splicing, DNA replication and damage response, and chromosome segregation, and a microenvironment-derived gene module predominantly involved in extracellular matrix organization and infiltrating immune cells. The PM subtype is associated with two malignant cell-intrinsic gene modules predominantly involved in transcriptional regulation and mRNA translation, respectively. Expression levels of these gene modules are independent prognostic factors and malignant cell-intrinsic gene modules are conserved during brain development. Focusing on the EM subtype, we identified PTBP1 as the most significant hub for the malignant cell-intrinsic gene module. PTBP1 is not altered in most glioma genomes. PTBP1 represses the conserved splicing of CDC42-N. PTBP1 knockdown or CDC42-N overexpression disrupts actin cytoskeleton dynamics, causing accumulation of reactive oxygen species and cell apoptosis. PTBP1-mediated repression of CDC42-N splicing represents a potential genomic alteration-independent, developmentally conserved vulnerability in IDH-wildtype GBM.

The most prevalent cyanotic congenital heart disease, Tetralogy of Fallot (TOF), has an unknown etiology. Long-stranded non-coding RNAs (lncRNAs) have been linked to cardiac development and congenital heart disease, as evidenced by an increasing number of studies; nevertheless, additional research is necessary to fully understand the function that TOF-related lncRNAs play in the condition. This study constructed lncRNA-mRNA co-expression networks, performed functional enrichment analysis, and screened hub lncRNAs using Weighted Gene Co-expression Network Analysis (WGCNA) using the Gene Expression Omnibus dataset GSE36761. Ten hub lncRNAs, including IRF1-AS1, AC012360.6, HLA-F-AS1, RP1-253P7.4, NPTN-IT1, RP11-166P13.4, RP5-1183I21.2, SNHG14, CH17-98J9.1, and RP11-894P9.1, were identified by WGCNA analysis as potentially significant contributors to the development of TOF. Based on functional enrichment analysis, lncRNA mainly contributes to TOF by altering gene splicing patterns. New insights on the mechanism underlying TOF occurrence are provided by identifying hub lncRNAs associated with the disease and analyzing their regulatory networks.

UNASSIGNED: To explore the mechanism and active components of the anti-colitis effects of myrrh essential oil (MEO).
UNASSIGNED: In this study, we investigated the anti-inflammatory effects and molecular mechanisms of MEO on dextran sulfate sodium (DSS)-induced colitis with in vitro cell experiments, RNA-seq (RNA Sequencing), Weighted gene co-expression network analysis (WGCNA), combined with \"weighting coefficient\" network pharmacology, as and in vivo pharmacodynamic experiments. A 3% DSS solution was used to induce colitis in BALB/c mice and MEO was administered orally. We performed gas chromatography-mass spectrometry (GC-MS) analysis of the MEO components. The disease activity index (DAI) was evaluated by observing body weight, fecal characteristics, and blood in the stool of mice. The levels of inflammatory cytokines (TNF-α and IL-1β) in mouse serum were measured using ELISA (Enzyme-linked immunosorbent assay) kits. Additionally, the expression of MAPK-related proteins (JNK, p-JNK, ERK, and p-ERK) in mouse colonic tissues was detected by Western blotting and immunohistochemistry.
UNASSIGNED: MEO (0.0625-0.125µg/g, p.o). significantly inhibited the expression of the inflammatory mediator Nitric oxide (NO) in lipopolysaccharide (LPS)-induced RAW264.7 macrophages. After treatment, there was a significant increase in body weight and alleviation of diarrhea and bloody stools in colitis mice. It also reduced inflammatory cell infiltration. Furthermore, it decreased the serum levels of TNF-α and IL-1β, and reduced the activity of p-JNK and p-ERK in the MAPK pathway.
UNASSIGNED: MEO relieved DSS-induced colitis by modulating the MAPK pathway. The experimental results indicate that the MAPK pathway might be inhibited by the synergistic effect of gamma-Muurolene, Curzerene, beta-Elemene, and Furanoeudesma 1.3-diene in MEO, which provides a novel idea for subsequent research and development of new anti-colitis drugs.

BACKGROUND: Patients with atrial fibrillation (AF) often have coronary artery disease (CAD), but the biological link between them remains unclear. This study aims to explore the common pathogenesis of AF and CAD and identify common biomarkers.
METHODS: Gene expression profiles for AF and stable CAD were downloaded from the Gene Expression Omnibus database. Overlapping genes related to both diseases were identified using weighted gene co-expression network analysis (WGCNA), followed by functional enrichment analysis. Hub genes were then identified using the machine learning algorithm. Immune cell infiltration and correlations with hub genes were explored, followed by drug predictions. Hub gene expression in AF and CAD patients was validated by real-time qPCR.
RESULTS: We obtained 28 common overlapping genes in AF and stable CAD, mainly enriched in the PI3K-Akt, ECM-receptor interaction, and relaxin signaling pathway. Two hub genes, COL6A3 and FKBP10, were positively correlated with the abundance of MDSC, plasmacytoid dendritic cells, and regulatory T cells in AF and negatively correlated with the abundance of CD56dim natural killer cells in CAD. The AUCs of COL6A3 and FKBP10 were all above or close to 0.7. Drug prediction suggested that collagenase clostridium histolyticum and ocriplasmin, which target COL6A3, may be potential drugs for AF and stable CAD. Additionally, COL6A3 and FKBP10 were upregulated in patients with AF and CAD.
CONCLUSIONS: COL6A3 and FKBP10 may be key biomarkers for AF and CAD, providing new insights into the diagnosis and treatment of this disease.

This study aimed to explore the key efferocytosis-related genes in diabetic retinopathy (DR) and their regulatory mechanisms. Public DR-related gene expression datasets, GSE160306 (training) and GSE60436 (validation), were downloaded. Differentially expressed efferocytosis-related genes (DEERGs) were analyzed using differential expression analysis and weighted gene co-expression network analysis. Functional enrichment analysis was conducted. Moreover, efferocytosis-related signature genes were identified using machine learning analysis, and their expression levels and diagnostic value were analyzed. Furthermore, nomograms were constructed; immune cell infiltration was analyzed; and gene set enrichment analysis, transcriptional regulation analysis, and small-molecule drug (SMD) prediction of efferocytosis-related signature genes were performed. In total, 36 DEERGs were identified in DR, and were markedly enriched in multiple functions, such as visual system development. Through further machine learning analysis, two efferocytosis-related signature genes, Ferritin Light Chain (FTL) and Fc Gamma Binding Protein (FCGBP), were identified, and were found to be upregulated in DR samples and showed high diagnostic performance for DR. A nomogram constructed using FTL and FCGBP accurately predicted the risk of DR. Moreover, the level of infiltration of immature B cells was positively correlated with FTL and FCGBP expression levels. Multiple transcription factors (TFs), such as CCCTC-Binding Factor (CTCF) and KLF Transcription Factor 9 (KLF9), were found to interact with both FTL and FCGBP. In addition, FTL can be targeted by miRNAs, such as miR-22-3p, and FCGBP can be targeted by miR-7973. In addition, both FTL and FCGBP can be targeted by SMDs, such as bisphenol A. Key efferocytosis-related genes, such as FTL and FCGBP, may promote DR development. Detecting or targeting FTL and FCGBP may aid in the prevention, diagnosis, and treatment of DR.

Purpose: Age-related macular degeneration (AMD) is a chronic and progressive macular degenerative disease that culminates in a gradual deterioration of central vision. Despite its prevalence, the key biomarkers for AMD have not yet been fully elucidated. In this study, we aimed to efficiently identify biomarkers crucial for diagnosing AMD. Methods: Three datasets pertaining to retinal pigment epithelium (RPE)/choroid tissues associated with AMD were selected from the GEO database. The GSE50195 dataset was utilized to conduct weighted gene co-expression network analysis (WGCNA) for identifying module genes linked to AMD. KEGG and GO enrichment analyses were subsequently conducted on these module genes. GSE29801 and GSE135092 datasets were subjected to differential expression analysis to pinpoint the DEGs intersecting with the module genes. Subsequently, wet AMD (wAMD) and dry AMD (dAMD) mouse models were developed, from which RPE/choroid tissues were harvested to validate the hub genes via RT-qPCR and Western blot. Results: Using the WGCNA, we selected the \"antiquewhite4\" module (r = 0.91 and p = 7e-07), which contains a total of 325 genes. Through the intersection of module genes with DEGs, nine hub genes were identified. Pathways involved in complement and coagulation cascades, ECM-receptor interactions, unsaturated fatty acid biosynthesis, and fatty acid elongation play important roles in AMD. Notably, CDH18 demonstrated notable variance across all three datasets. Post validation using RT-qPCR experiments revealed a significant downregulation of CDH18 in both dAMD and wAMD. EGLN3 was expressed at low levels in wAMD. In dAMD, EYA2, LTB, and PODXL were significantly downregulated, whereas APOC1 was notably upregulated. Western blot confirmed that CDH18 was lowly expressed in dAMD and wAMD mouse models. Conclusion: CDH18 was identified as the key gene involved in the pathogenesis of AMD. An imbalance of the complement and coagulation cascades is a potential mechanism of AMD. This study provides a novel idea for diagnosing and treating AMD in the future.

UNASSIGNED: Tumor-Node-Metastasis (TNM) stage of gastric cancer (GC) is one of the main factors affecting clinical outcome. The aim of this study was to explore the targets related to TNM stage of GC, and screening natural bioactive drug.
UNASSIGNED: RNA sequencing data of the TCGA-STAD cohort were downloaded from UCSC database. Genes associated with TNM staging were identified by weighted gene co-expression network analysis (WGCNA). Univariate Cox regression, least absolute shrinkage and selection operator (LASSO), extreme gradient boosting (Xgboost), random forest (RF) and cytohubba plug-in of cytoscope were applied to screen hub genes. Natural bioactive ingredients were available from the HERB database. Molecular docking was used to evaluate the binding activity of active ingredients to the hub protein. CCK-8, flow cytometry, transwell and Western blot assays were used to analyze the effects of diosgenin on GC cells.
UNASSIGNED: 898 TNM-related genes were screened out through WGCNA. Three genes associated with GC progression/prognosis were identified, including nuclear receptor subfamily 3 group C member 2 (NR3C2), solute carrier family 1 member 5 (SLC1A5) and FAT atypical cadherin 1 (FAT1) based on the machine learning algorithms and hub co-expression network analysis. Diosgenin had good binding activity with SLC1A5. SLC1A5 was highly expressed in GC and was closely associated with tumor stage, overall survival and immune infiltration of GC patients. Diosgenin could inhibit cell viability and invasive ability, promote apoptosis and induce cell cycle arrest in G0/G1 phase. In addition, diosgenin promoted cleaved caspase 3 expression and inhibited Ki67, cyclin D1, p-S6K1, and SLC1A5 expression levels, while the mTORC1 activator (MHY1485) reversed this phenomenon.
UNASSIGNED: For the first time, this work reports diosgenin may inhibit the activation of mTORC1 signaling through targeting SLC1A5, thereby inhibiting the malignant behaviors of GC cells.