Energy Metabolism Dysregulation in Myocardial Infarction: An Integrative Analysis of Ischemic Cardiomyopathy.

BACKGROUND: Myocardial metabolism is closely related to functional changes after myocardial infarction (MI). OBJECTIVE: This study aimed to present an integrative examination of human ischemic cardiomyopathy. METHODS: We used both GSE121893 single-cell suspension sequencing and GSE19303 transcription microarray data sets from the GEO database, along with a murine MI model for full-spectrum metabolite detection. Through a systematic investigation that involved differential metabolite identification and functional enrichment analysis, we shed light on the pivotal role of energy metabolism dysregulation in the progression of MI. RESULTS: Our findings revealed an association between the core regulatory genes CDKN1A, FOS, ITGB4, and MAP2K1 and the underlying pathophysiology of the disease. These genes are identified as critical elements in the complex landscape of myocardial ischemic disorder, highlighting novel insights into therapeutic targets and the intricate biological mechanisms involved. CONCLUSION: This analysis provides a framework for future research on the metabolic alterations associated with MI.

Gene signatures of copper metabolism related genes may predict prognosis and immunity status in Ewing's sarcoma.

Background: Cuproptosis is copper-induced cell death. Copper metabolism related genes (CMRGs) were demonstrated that used to assess the prognosis out of tumors. In the study, CMRGs were tested for their effect on TME cell infiltration in Ewing's sarcoma (ES). Methods: The GEO and ICGC databases provided the mRNA expression profiles and clinical features for downloading. In the GSE17674 dataset, 22prognostic-related copper metabolism related genes (PR-CMRGs) was identified by using univariate regression analysis. Subsequently, in order to compare the survival rates of groups with high and low expression of these PR-CMRGs,Kaplan-Meier analysis was implemented. Additionally, correlations among them were examined. The study employed functional enrichment analysis to investigate probable underlying pathways, while GSVA was applied to evaluate enriched pathways in the ES (Expression Set). Through an unsupervised clustering algorithm, samples were classified into two clusters, revealing significant differences in survival rates and levels of immune infiltration. Results: Using Lasso and step regression methods, five genes (TFRC, SORD, SLC11A2, FKBP4, and AANAT) were selected as risk signatures. According to the Kaplan-Meier survival analysis, the high-risk group had considerably lower survival rates than the low-risk group(p=6.013e-09). The area under the curve (AUC) values for the receiver operating characteristic (ROC) curve were 0.876, 0.883, and 0.979 for 1, 3, and 5 years, respectively. The risk model was further validated in additional datasets, namely GSE63155, GSE63156, and the ICGC datasets. To aid in outcome prediction, a nomogram was developed that incorporated risk levels and clinical features. This nomogram's performance was effectively validated through calibration curves.Additionally, the study evaluated the variations in immune infiltration across different risk groups, as well as high-expression and low-expression groups. Importantly, several drugs were identified that displayed sensitivity, offering potential therapeutic options for ES. Conclusion: The findings above strongly indicate that CMRGs play crucial roles in predicting prognosis and immune status in ES.

Identification of Differentially Expressed Genes and Protein-Protein Interaction in Patients With COVID-19 and Diabetes Peripheral Neuropathy: A Bioinformatics and System Biology Approach.

The coronavirus disease 2019 (COVID-19) pandemic has had a significant impact globally, resulting in a higher death toll and persistent health issues for survivors, particularly those with pre-existing medical conditions. Numerous studies have demonstrated a strong correlation between catastrophic COVID-19 results and diabetes. To gain deeper insights, we analysed the transcriptome dataset from COVID-19 and diabetic peripheral neuropathic patients. Using the R programming language, differentially expressed genes (DEGs) were identified and classified based on up and down regulations. The overlaps of DEGs were then explored between these groups. Functional annotation of those common DEGs was performed using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Bio-Planet, Reactome, and Wiki pathways. A protein-protein interaction (PPI) network was created with bioinformatics tools to understand molecular interactions. Through topological analysis of the PPI network, we determined hub gene modules and explored gene regulatory networks (GRN). Furthermore, the study extended to suggesting potential drug molecules for the identified mutual DEG based on the comprehensive analysis. These approaches may contribute to understanding the molecular intricacies of COVID-19 in diabetic peripheral neuropathy patients through insights into potential therapeutic interventions.

Decoding genetic and pathophysiological mechanisms in amyotrophic lateral sclerosis and primary lateral sclerosis: A comparative study of differentially expressed genes and implicated pathways in motor neuron disorders.

Motor Neuron Disorders (MNDs), characterized by the degradation and loss of function of motor neurons, are recognized as fatal conditions with limited treatment options and no known cure. The present study aimed to identify the pathophysiological functions and affected genes in patients with MNDs, specifically Amyotrophic Lateral Sclerosis (ALS) and Primary Lateral Sclerosis (PLS). The GSE56808 dataset comprised three sample groups: six patients diagnosed with ALS (GSM1369650, GSM1369652, GSM1369654, GSM1369656, GSM1369657, GSM1369658), five patients diagnosed with PLS (GSM1369648, GSM1369649, GSM1369653, GSM1369655, GSM1369659), and six normal controls (GSM1369642, GSM1369643, GSM1369644, GSM1369645, GSM1369646, and GSM1369647). The application of computational analysis of microarray gene expression profiles enabled us to identify 346 significantly differentially expressed genes (DEGs), 169 genes for the ALS sample study, and 177 genes for the PLS sample study. Enrichment was carried out using MCODE, a Cytoscape plugin. Functional annotation of DEGs was carried out via ClueGO/CluePedia (v2.5.9) and further validated via the DAVID database. NRP2, SEMA3D, ROBO3 and, CACNB1, CACNG2 genes were identified as the gene of interest for ALS and PLS sample groups, respectively. Axonal guidance (GO:0007411) and calcium ion transmembrane transport (GO:0070588) were identified to be some of the significantly dysregulated gene ontology (GO) terms, with arrhythmogenic right ventricular cardiomyopathy (KEGG:05412) to be the top relevant KEGG pathway which is affected in MND patients. ROBO3 gene was observed to have distinctive roles in ALS and PLS-affected patients, hinting towards the differential progression of ALS from PLS. The insights derived from our comprehensive analysis accentuate the distinct variances in the underlying molecular pathogenesis of ALS and PLS. Further research should investigate the mechanistic roles of the identified DEGs and molecular pathways, leading to potential targeted therapies for ALS and PLS.

Direction-aware functional class scoring enrichment analysis of infinium DNA methylation data.

Infinium Methylation BeadChip arrays remain one of the most popular platforms for epigenome-wide association studies, but tools for downstream pathway analysis have their limitations. Functional class scoring (FCS) is a group of pathway enrichment techniques that involve the ranking of genes and evaluation of their collective regulation in biological systems, but the implementations described for Infinium methylation array data do not retain direction information, which is important for mechanistic understanding of genomic regulation. Here, we evaluate several candidate FCS methods that retain directional information. According to simulation results, the best-performing method involves the mean aggregation of probe limma t-statistics by gene followed by a rank-ANOVA enrichment test using the mitch package. This method, which we call 'LAM,' outperformed an existing over-representation analysis method in simulations, and showed higher sensitivity and robustness in an analysis of real lung tumour-normal paired datasets. Using matched RNA-seq data, we examine the relationship of methylation differences at promoters and gene bodies with RNA expression at the level of pathways in lung cancer. To demonstrate the utility of our approach, we apply it to three other contexts where public data were available. First, we examine the differential pathway methylation associated with chronological age. Second, we investigate pathway methylation differences in infants conceived with in vitro fertilization. Lastly, we analyse differential pathway methylation in 19 disease states, identifying hundreds of novel associations. These results show LAM is a powerful method for the detection of differential pathway methylation complementing existing methods. A reproducible vignette is provided to illustrate how to implement this method.

Integration analysis of miRNA-mRNA pairs between two contrasting genotypes reveals the molecular mechanism of jujube (Ziziphus jujuba Mill.) response to high-temperature stress.

With global warming, high temperature (HT) has become one of the most common abiotic stresses resulting in significant crop yield losses, especially for jujube (Ziziphus jujuba Mill.), an important temperate economic crop cultivated worldwide. This study aims to explore the coping mechanism of jujube to HT stress at the transcriptional and post-transcriptional levels, including identifying differentially expressed miRNAs and mRNAs as well as elucidating the critical pathways involved. High-throughput sequencing analyses of miRNA and mRNA were performed on jujube leaves, which were collected from "Fucumi" (heat-tolerant) and "Junzao" (heat-sensitive) cultivars subjected to HT stress (42 °C) for 0, 1, 3, 5, and 7 days, respectively. The results showed that 45 known miRNAs, 482 novel miRNAs, and 13,884 differentially expressed mRNAs (DEMs) were identified. Among them, integrated analysis of miRNA target genes prediction and mRNA-seq obtained 1306 differentially expressed miRNAs-mRNAs pairs, including 484, 769, and 865 DEMIs-DEMs pairs discovered in "Fucuimi", "Junzao" and two genotypes comparative groups, respectively. Furthermore, functional enrichment analysis of 1306 DEMs revealed that plant-pathogen interaction, starch and sucrose metabolism, spliceosome, and plant hormone signal transduction were crucial pathways in jujube leaves response to HT stress. The constructed miRNA-mRNA network, composed of 20 DEMIs and 33 DEMs, displayed significant differently expressions between these two genotypes. This study further proved the regulatory role of miRNAs in the response to HT stress in plants and will provide a theoretical foundation for the innovation and cultivation of heat-tolerant varieties.

Single-cell transcriptomics reveals stage- and side-specificity of gene modules in colorectal cancer.

BACKGROUND: An understanding of mechanisms underlying colorectal cancer (CRC) development and progression is yet to be fully elucidated. This study aims to employ network theoretic approaches to analyse single cell transcriptomic data from CRC to better characterize its progression and sided-ness. METHODS: We utilized a recently published single-cell RNA sequencing data (GEO-GSE178341) and parsed the cell X gene data by stage and side (right and left colon). Using Weighted Gene Co-expression Network Analysis (WGCNA), we identified gene modules with varying preservation levels (weak or strong) of network topology between early (pT1) and late stages (pT234), and between right and left colons. Spearman's rank correlation (ρ) was used to assess the similarity or dissimilarity in gene connectivity. RESULTS: Equalizing cell counts across different stages, we detected 13 modules for the early stage, two of which were non-preserved in late stages. Both non-preserved modules displayed distinct gene connectivity patterns between the early and late stages, characterized by low ρ values. One module predominately dealt with myeloid cells, with genes mostly enriched for cytokine-cytokine receptor interaction potentiallystimulating myeloid cells to participate in angiogenesis. The second module, representing a subset of epithelial cells, was mainly enriched for carbohydrate digestion and absorption, influencing the gut microenvironment through the breakdown of carbohydrates. In the comparison of left vs. right colons, two of 12 modules identified in the right colon were non-preserved in the left colon. One captured a small fraction of epithelial cells and was enriched for transcriptional misregulation in cancer, potentially impacting communication between epithelial cells and the tumor microenvironment. The other predominantly contained B cells with a crucial role in maintaining human gastrointestinal health and was enriched for B-cell receptor signalling pathway. CONCLUSIONS: We identified modules with topological and functional differences specific to cell types between the early and late stages, and between the right and left colons. This study enhances the understanding of roles played by different cell types at different stages and sides, providing valuable insights for future studies focused on the diagnosis and treatment of CRC.

Upregulation of sperm-associated antigen 5 expression in endometrial carcinoma was associated with poor prognosis and immune dysregulation, and promoted cell migration and invasion.

Sperm-associated antigen 5 (SPAG5) regulates cancer cell invasion and is involved in the progression of many cancers. However, the role of SPAG5 in endometrial carcinoma (EC) is still unknown. The purpose of this study was to explore the role of SPAG5 in EC and its potential molecular mechanism. The UALCAN tool and cBioPortal were used to analyze the expression and alterations of SPAG5 in EC, respectively. OncoLnc was used for survival analysis. We analyzed the effects of SPAG5 on immune cell infiltration and the expression levels of immune checkpoints. We also overexpressed and knocked down SPAG5 in EC cells to explore the effect of SPAG5 regulation on migration, invasion, apoptosis, and the cell cycle of EC cells. We found that SPAG5 was overexpressed and the SPAG5 gene was often mutated in EC. High SPAG5 expression was significantly associated with poor overall survival in patients with EC. SPAG5 also affected the level of immune cell infiltration in the TIME and the expression of immune checkpoints lymphocyte activating 3 (LAG3) and T cell immunoreceptor with Ig and ITIM domains (TIGIT) in patients with EC. It may also be involved in the immunotherapy response in these patients. In vitro experiments showed that SPAG5 promotes cancer cell migration and invasion. In conclusion, this study lays the foundation for further understanding the molecular mechanisms of EC involving SPAG5 and contributes to diagnosing and managing this disease.

Identification of miRNA expression profile in middle ear cholesteatoma using small RNA-sequencing.

BACKGROUND: The present study aims to identify the differential miRNA expression profile in middle ear cholesteatoma and explore their potential roles in its pathogenesis. METHODS: Cholesteatoma and matched normal retroauricular skin tissue samples were collected from patients diagnosed with acquired middle ear cholesteatoma. The miRNA expression profiling was performed using small RNA sequencing, which further validated by quantitative real-time PCR (qRT-PCR). Target genes of differentially expressed miRNAs in cholesteatoma were predicted. The interaction network of 5 most significantly differentially expressed miRNAs was visualized using Cytoscape. Further Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analyses were processed to investigate the biological functions of miRNAs in cholesteatoma. RESULTS: The miRNA expression profile revealed 121 significantly differentially expressed miRNAs in cholesteatoma compared to normal skin tissues, with 56 upregulated and 65 downregulated. GO and KEGG pathway enrichment analyses suggested their significant roles in the pathogenesis of cholesteatoma. The interaction network of the the 2 most upregulated (hsa-miR-21-5p and hsa-miR-142-5p) and 3 most downregulated (hsa-miR-508-3p, hsa-miR-509-3p and hsa-miR-211-5p) miRNAs identified TGFBR2, MBNL1, and NFAT5 as potential key target genes in middle ear cholesteatoma. CONCLUSIONS: This study provides a comprehensive miRNA expression profile in middle ear cholesteatoma, which may aid in identifying therapeutic targets for its management.

TES and SLC40A1 as Potential Biomarkers for Predicting Survival in T-Cell Acute Lymphoblastic Leukemia.

INTRODUCTION: Identifying patients with high-risk T-cell acute lymphoblastic leukemia (T-ALL) is crucial for personalized therapy; however, the lack of robust biomarkers hinders prognosis assessment. To address this issue, our study aimed to screen and validate genes whose expression may serve as predictive indicators of outcomes in T-ALL patients while also investigating the underlying molecular mechanisms. METHODS: Differentially expressed genes (DEGs) between T-ALL patients and healthy controls were identified by integrating data from three independent public datasets. Functional annotation of these DEGs and protein-protein interactions were also conducted. Further, we enrolled a prospective cohort of T-ALL patients (n = 20) at our center, conducting RNA-seq analysis on their bone marrow samples. Survival-based univariate Cox analysis was employed to identify gene expressions related to survival, and an intersection algorithm was sequentially applied. Furthermore, we validated the identified genes using cases from the Therapeutically Applicable Research to Generate Effective Treatments database, plotting Kaplan-Meier curves for secondary validation. RESULTS: Through the integration of survival-related genes with DEGs identified in T-ALL, our analysis revealed six T-ALL-specific genes, the expression levels of which were linked to prognostic value. Notably, the independent prognostic value of SLC40A1 and TES expression levels was confirmed in both an external cohort and a prospective cohort at our center. CONCLUSION: In summary, our preliminary study indicates that the expression levels of TES and SLC40A1 genes show promise as potential indicators for predicting survival outcomes in T-ALL patients.

Genome-wide DNA methylation and transcriptomic analysis of liver tissues subjected to early ischemia/reperfusion injury upon human liver transplantation.

INTRODUCTION AND OBJECTIVES: Epigenetic changes represent a mechanism connecting external stresses with long-term modifications of gene expression programs. In solid organ transplantation, ischemia-reperfusion injury (IRI) appears to induce epigenomic changes in the graft, although the currently available data are extremely limited. The present study aimed to characterize variations in DNA methylation and their effects on the transcriptome in liver transplantation from brain-dead donors. PATIENTS AND METHODS: 12 liver grafts were evaluated through serial biopsies at different timings in the procurement-transplantation process: T0 (warm procurement, in donor), T1 (bench surgery), and T2 (after reperfusion, in recipient). DNA methylation (DNAm) and transcriptome profiles of biopsies were analyzed using microarrays and RNAseq. RESULTS: Significant variations in DNAm were identified, particularly between T2 and T0. Functional enrichment of the best 1000 ranked differentially methylated promoters demonstrated that 387 hypermethylated and 613 hypomethylated promoters were involved in spliceosomal assembly and response to biotic stimuli, and inflammatory immune responses, respectively. At the transcriptome level, T2 vs. T0 showed an upregulation of 337 and downregulation of 61 genes, collectively involved in TNF-α, NFKB, and interleukin signaling. Cell enrichment analysis individuates macrophages, monocytes, and neutrophils as the most significant tissue-cell type in the response. CONCLUSIONS: In the process of liver graft procurement-transplantation, IRI induces significant epigenetic changes that primarily act on the signaling pathways of inflammatory responses dependent on TNF-α, NFKB, and interleukins. Our DNAm datasets are the early IRI methylome literature and will serve as a launch point for studying the impact of epigenetic modification in IRI.

A whole-exome sequencing study of patent foramen ovale: investigating genetic variants and their association with cardiovascular disorders.

Background: Patent foramen ovale (PFO) has a genetic predisposition and is closely associated with cryptogenic stroke (CS), migraine, decompression sickness, and hypoxemia. Identifying PFO-related mutant genes through whole-exome sequencing (WES) can help in the early recognition of cardiovascular genetic risk factors, guide timely clinical intervention, and reduce the occurrence of cardiovascular events. Methods: We analyzed mutant genes from ClinVar and OMIM databases. WES was performed on 25 PFO patients from Zhejiang Provincial Hospital of Chinese Medicine. Pathogenicity of variants was evaluated using American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology. (AMP) guidelines. Results: In ClinVar (4 Feb 2023), 113 coding gene mutations were found, including 83 associated with PFO. From OMIM (18 Apr 2023), 184 gene mutations were analyzed, with 110 mutant coding genes. WES identified pathogenic mutations in two of 25 PFO patients (8%). LDLR, SDHC, and NKX2-5 genes were linked to PFO and primarily involved in myocardial tissue function. NKX2-5 may play a crucial role in PFO development, interacting with NOTCH1, GATA4, MYH6, SCN5A signaling pathways regulating cardiomyocyte characteristics. Conclusion: We identified pathogenic mutations in LDLR, SDHC, and NKX2-5 genes, implying their role in PFO development. Functional enrichment analysis revealed NKX2-5's interaction with signaling pathways regulating cardiomyocyte function. These findings enhance our understanding of PFO's genetic basis, suggesting potential therapeutic targets for future research.

of Potential Noncoding RNAs Related to Spinal Cord Injury Based on Competing Endogenous RNAs.

This study aims to elucidate the key regulatory molecules, specifically messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and microRNAs (miRNAs) and their roles in the development and progression of spinal cord injury (SCI). Expression profiles (GSE45006, GSE19890, and GSE125630) for SCI were sourced from the Gene Expression Omnibus (GEO) database. By comparing rats with SCI at various time points against those without SCI, we identified differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs), and miRNAs (DEmiRNAs). The GSE45006 dataset facilitated the production of DEmRNAs, which were then clustered using Mfuzz. Subsequently, we constructed a protein-protein interaction (PPI) network and anticipated interaction pairs between miRNA-mRNA and lncRNA-mRNA. These pairs were instrumental in forming a regulatory network involving lncRNA-miRNA-mRNA interactions. Additionally, we conducted functional enrichment studies on the DEmRNAs within these gene networks. A total of 2313 DEmRNAs were identified using the GSE45006 dataset, alongside 111 DEmiRNAs from GSE19890. From GSE125630, we extracted 154 DElncRNAs and 2322 DEmRNAs. Our analysis revealed 294 up-regulated DEmRNAs, grouped into the up-cluster, and 407 down-regulated DEmRNAs, forming the down-cluster. Key hub genes in the PPI network, such as Rhof, Vav1, Lyz2, Rab3a, Lyn, Cyfip1, Gns, and Nckap1l, were identified. Additionally, the study successfully constructed a competing endogenous RNA (ceRNA) network, revealing 55 unique lncRNA-miRNA-mRNA link pairs. Our research established a ceRNA network associated with SCI, identifying several critical lncRNA-miRNA-mRNA connection pairs integral to the disease's onset and progression. Notably, significant associations, including the AABR07041411.1-miR-125a-5p-Slc4a7 and the Smg1-rno-miR-331-3p-Tlr4 pairs, were observed to exert a significant influence within this biological context.

Comparative Genomics Unveils Functional Diversity, Pangenome Openness, and Underlying Biological Drivers among Bacillus subtilis Group.

The Bacillus subtilis group (Bs group), with Bacillus subtilis as its core species, holds significant research and economic value in various fields, including science, industrial production, food, and pharmaceuticals. However, most studies have been confined to comparative genomics analyses and exploration within individual genomes at the level of species, with few conducted within groups across different species. This study focused on Bacillus subtilis, the model of Gram-positive bacteria, and 14 other species with significant research value, employing comparative pangenomics as well as population enrichment analysis to ascertain the functional enrichment and diversity. Through the quantification of pangenome openness, this work revealed the underlying biological drivers and significant correlation between pangenome openness and various factors, including the distribution of toxin-antitoxin- and integrase-related genes, as well as the number of endonucleases, recombinases, repair system-related genes, prophages, integrases, and transfer mobile elements. Furthermore, the functional enrichment results indicated the potential for secondary metabolite, probiotic, and antibiotic exploration in Bacillus licheniformis, Bacillus paralicheniformis, and Bacillus spizizenii, respectively. In general, this work systematically exposed the quantification of pangenome openness, biological drivers, the pivotal role of genomic instability factors, and mobile elements, providing targeted exploration guidance for the Bs group.

Effect of Calebin-A on Critical Genes Related to NAFLD: A Protein-Protein Interaction Network and Molecular Docking Study.

Background: Calebin-A is a minor phytoconstituent of turmeric known for its activity against inflammation, oxidative stress, cancerous, and metabolic disorders like Non-alcoholic fatty liver disease(NAFLD). Based on bioinformatic tools. Subsequently, the details of the interaction of critical proteins with Calebin-A were investigated using the molecular docking technique. Methods: We first probed the intersection of genes/ proteins between NAFLD and Calebin-A through online databases. Besides, we performed an enrichment analysis using the ClueGO plugin to investigate signaling pathways and gene ontology. Next, we evaluate the possible interaction of Calebin-A with significant hub proteins involved in NAFLD through a molecular docking study. Results: We identified 87 intersection genes Calebin-A targets associated with NAFLD. PPI network analysis introduced 10 hub genes (TP53, TNF, STAT3, HSP90AA1, PTGS2, HDAC6, ABCB1, CCT2, NR1I2, and GUSB). In KEGG enrichment, most were associated with Sphingolipid, vascular endothelial growth factor A (VEGFA), C-type lectin receptor, and mitogen-activated protein kinase (MAPK) signaling pathways. The biological processes described in 87 intersection genes are mostly concerned with regulating the apoptotic process, cytokine production, and intracellular signal transduction. Molecular docking results also directed that Calebin-A had a high affinity to bind hub proteins linked to NAFLD. Conclusion: Here, we showed that Calebin-A, through its effect on several critical genes/ proteins and pathways, might repress the progression of NAFLD.

Integrated transcriptomics and histopathology approach identifies a subset of rejected donor livers with potential suitability for transplantation.

BACKGROUND: Liver transplantation is an effective treatment for liver failure. There is a large unmet demand, even as not all donated livers are transplanted. The clinical selection criteria for donor livers based on histopathological evaluation and liver function tests are variable. We integrated transcriptomics and histopathology to characterize donor liver biopsies obtained at the time of organ recovery. We performed RNA sequencing as well as manual and artificial intelligence-based histopathology (10 accepted and 21 rejected for transplantation). RESULTS: We identified two transcriptomically distinct rejected subsets (termed rejected-1 and rejected-2), where rejected-2 exhibited a near-complete transcriptomic overlap with the accepted livers, suggesting acceptability from a molecular standpoint. Liver metabolic functional genes were similarly upregulated, and extracellular matrix genes were similarly downregulated in the accepted and rejected-2 groups compared to rejected-1. The transcriptomic pattern of the rejected-2 subset was enriched for a gene expression signature of graft success post-transplantation. Serum AST, ALT, and total bilirubin levels showed similar overlapping patterns. Additional histopathological filtering identified cases with borderline scores and extensive molecular overlap with accepted donor livers. CONCLUSIONS: Our integrated approach identified a subset of rejected donor livers that are likely suitable for transplantation, demonstrating the potential to expand the pool of transplantable livers.

MHIF-MSEA: a novel model of miRNA set enrichment analysis based on multi-source heterogeneous information fusion.

Introduction: MicroRNAs (miRNAs) are a class of non-coding RNA molecules that play a crucial role in the regulation of diverse biological processes across various organisms. Despite not encoding proteins, miRNAs have been found to have significant implications in the onset and progression of complex human diseases. Methods: Conventional methods for miRNA functional enrichment analysis have certain limitations, and we proposed a novel method called MiRNA Set Enrichment Analysis based on Multi-source Heterogeneous Information Fusion (MHIF-MSEA). Three miRNA similarity networks (miRSN-DA, miRSN-GOA, and miRSN-PPI) were constructed in MHIF-MSEA. These networks were built based on miRNA-disease association, gene ontology (GO) annotation of target genes, and protein-protein interaction of target genes, respectively. These miRNA similarity networks were fused into a single similarity network with the averaging method. This fused network served as the input for the random walk with restart algorithm, which expanded the original miRNA list. Finally, MHIF-MSEA performed enrichment analysis on the expanded list. Results and Discussion: To determine the optimal network fusion approach, three case studies were introduced: colon cancer, breast cancer, and hepatocellular carcinoma. The experimental results revealed that the miRNA-miRNA association network constructed using miRSN-DA and miRSN-GOA exhibited superior performance as the input network. Furthermore, the MHIF-MSEA model performed enrichment analysis on differentially expressed miRNAs in breast cancer and hepatocellular carcinoma. The achieved p-values were 2.17e(-75) and 1.50e(-77), and the hit rates improved by 39.01% and 44.68% compared to traditional enrichment analysis methods, respectively. These results confirm that the MHIF-MSEA method enhances the identification of enriched miRNA sets by leveraging multiple sources of heterogeneous information, leading to improved insights into the functional implications of miRNAs in complex diseases.

Identification of key mRNAs and signaling pathways in obsessive compulsive disorder based on weighted gene co-expression network analysis and cytoHubba plugin.

PURPOSE: Obsessive-compulsive disorder (OCD) is a complex psychiatric disorder. Genetic and broad environmental factors are common risk factors for OCD. The purpose of this study is to explore the molecular mechanism of OCD and to find new molecular targets for the diagnosis and management of OCD. METHODS: All data were downloaded from public dataset. Key modules and candidate key mRNAs were identified based on weighted gene co-expression network analysis (WGCNA). The "limma" R package was used for differential expression analysis of mRNAs. Subsequently, functional enrichment analysis of differentially expressed mRNAs (DEmRNAs) was also carried out. In addition, a diagnostic model was constructed. Finally, the infiltration level of immune cells in OCD and its correlation with multicentric key DEmRNAs were analyzed. RESULTS: Green and red modules were selected as the hub modules. A total of 447 mRNAs were considered candidate key mRNAs according to GS > 0.2 and MM > 0.3. A total of 26 DEmRNAs in the same direction were identified in the GSE60190 and GSE78104 datasets. A total of 26 DEmRNAs were intersected with candidate key mRNAs in WGCNA to obtain 10 intersection DEmRNAs (HSPB1, ITPK1, CBX7, PPP1R10, TAOK1, PISD, MKNK2, RWDD1, PPA1, and RELN). However, only four DEmRNAs (HSPB1, TAOK1, MKNK2, and PPA1) predicted related drugs. Subsequently, receiver operating characteristic analysis shows that the diagnostic model has high diagnostic value. Moreover, six multicentric key DEmRNAs (SNRPF, SNRNP70, PRPF8, NOP56, EPRS, and CCT2) were screened by UpSet package. Finally, six multicentric key DEmRNAs were found to be associated with immune cells. CONCLUSION: The key molecules obtained in this study lay a foundation for further research on the molecular mechanism of OCD.

A System Biology Approach Reveals New Targets for Human Thyroid Gland Toxicity in Embryos and Adult Individuals.

Compounds of natural or synthetic origin present in personal care products, food additives, and packaging may interfere with hormonal regulation and are called endocrine-disrupting chemicals (EDCs). The thyroid gland is an important target of these compounds. The objective of this study was to analyze public data on the human thyroid transcriptome and investigate potential new targets of EDCs in the embryonic and adult thyroid glands. We compared the public transcriptome data of adult and embryonic human thyroid glands and selected 100 up- or downregulated genes that were subsequently subjected to functional enrichment analysis. In the embryonic thyroid, the most highly expressed gene was PRMT6, which methylates arginine-4 of histone H2A (86.21%), and the downregulated clusters included plasma lipoprotein particles (39.24%) and endopeptidase inhibitory activity (24.05%). For the adult thyroid gland, the most highly expressed genes were related to the following categories: metallothionein-binding metals (56.67%), steroid hormone biosynthetic process (16.67%), and cellular response to vascular endothelial growth factor stimulus (6.67%). Several compounds ranging from antihypertensive drugs to enzyme inhibitors were identified as potentially harmful to thyroid gland development and adult function.

Critical gene signature and immunological characterization in peripheral vascular atherosclerosis: novel insights from mendelian randomization and transcriptomics.

Introduction: Peripheral vascular atherosclerosis (PVA) is a chronic inflammatory disease characterized by lipid accumulation in blood vessel walls, leading to vessel narrowing and inadequate blood supply. However, the molecular mechanisms underlying PVA remain poorly understood. In this study, we employed a combination of Mendelian randomization (MR) analysis and integrated transcriptomics to identify the critical gene signature associated with PVA. Methods: This study utilized three public datasets (GSE43292, GSE100927 and GSE28829) related to peripheral vascular atherosclerosis obtained from the Gene Expression Omnibus database. Instrumental variables (IVs) were identified through expression quantitative trait loci (eQTL) analysis, and two-sample MR analysis was performed using publicly available summary statistics. Disease critical genes were identified based on odds ratios and intersected with differentially expressed genes in the disease dataset. GSE28829 dataset was used to validate the screened disease critical genes. Functional enrichment analysis, GSEA analysis, and immune cell infiltration analysis were performed to further characterize the role of these genes in peripheral vascular atherosclerosis. Results: A total of 26,152 gene-related SNPs were identified as IVs, and 242 disease-associated genes were identified through MR analysis. Ten disease critical genes (ARHGAP25, HCLS1, HVCN1, RBM47, LILRB1, PLAU, IFI44L, IL1B, IFI6, and CFL2) were significantly associated with peripheral vascular atherosclerosis. Functional enrichment analysis using KEGG pathways revealed enrichment in the NF-kappa B signaling pathway and osteoclast differentiation. Gene set enrichment analysis further demonstrated functional enrichment of these genes in processes related to vascular functions and immune system activation. Additionally, immune cell infiltration analysis showed differential ratios of B cells and mast cells between the disease and control groups. The correlations analysis highlights the intricate interplay between disease critical genes and immune cells associated with PVA. Conclusion: In conclusion, this study provides new insights into the molecular mechanisms underlying PVA by identifying ten disease critical genes associated with the disease. These findings, supported by differential expression, functional enrichment, and immune system involvement, emphasize the role of these genes in vascular function and immune cell interactions in the context of PVA. These findings contribute to a better understanding of PVA pathogenesis and offer potential targets for further mechanistic exploration and therapeutic interventions.