Gene Enrichment Analysis Research Articles

Systems genetics identifies methionine as a high risk factor for Alzheimer's disease.

As a dietary strategy, methionine restriction has been reported to promote longevity and regulate metabolic disorders. However, the role and possible regulatory mechanisms underlying methionine in neurodegenerative diseases such as Alzheimer's disease (AD), remain unexplored. This study utilized the data from BXD recombinant inbred (RI) mice to establish a correlation between the AD phenotype in mice and methionine level. Gene enrichment analysis indicated that the genes associated with the concentration of methionine in the midbrain are involved in the dopaminergic synaptic signaling pathway. Protein interaction network analysis revealed that glycogen synthase kinase 3 beta (GSK-3β) was a key regulator of the dopaminergic synaptic pathway and its expression level was significantly correlated with the AD phenotype. Finally, in vitro experiments demonstrated that methionine deprivation could reduce the expression of Aβ and phosphorylated Tau, suggesting that lowering methionine levels in humans may be a preventive or therapeutic strategy for AD. In conclusion, our findings support that methionine is a high risk factor for AD. These findings predict potential regulatory network, theoretically supporting methionine restriction to prevent AD.

An integrated bioinformatics analysis to identify the shared biomarkers in patients with obstructive sleep apnea syndrome and nonalcoholic fatty liver disease.

Obstructive sleep apnea (OSA) syndrome and nonalcoholic fatty liver disease (NAFLD) have been shown to have a close association in previous studies, but their pathogeneses are unclear. This study explores the molecular mechanisms associated with the pathogenesis of OSA and NAFLD and identifies key predictive genes. Using the Gene Expression Omnibus (GEO) database, we obtained gene expression profiles GSE38792 for OSA and GSE89632 for NAFLD and related clinical characteristics. Mitochondrial unfolded protein response-related genes (UPRmtRGs) were acquired by collating and collecting UPRmtRGs from the GeneCards database and relevant literature from PubMed. The differentially expressed genes (DEGs) associated with OSA and NAFLD were identified using differential expression analysis. Gene Set Enrichment Analysis (GSEA) was conducted for signaling pathway enrichment analysis of related disease genes. Based on the STRING database, protein-protein interaction (PPI) analysis was performed on differentially co-expressed genes (Co-DEGs), and the Cytoscape software (version 3.9.1) was used to visualize the PPI network model. In addition, the GeneMANIA website was used to predict and construct the functional similar genes of the selected Co-DEGs. Key predictor genes were analyzed using the receiver operating characteristic (ROC) curve. The intersection of differentially expressed genes shared between OSA and NAFLD-related gene expression profiles with UPRmtRGs yielded four Co-DEGs: ASS1, HDAC2, SIRT3, and VEGFA. GSEA obtained the relevant enrichment signaling pathways for OSA and NAFLD. PPI network results showed that all four Co-DEGs interacted (except for ASS1 and HDAC2). Ultimately, key predictor genes were selected in the ROC curve, including HDAC2 (OSA: AUC = 0.812; NAFLD: AUC = 0.729), SIRT3 (OSA: AUC = 0.775; NAFLD: AUC = 0.750), and VEGFA (OSA: AUC = 0.812; NAFLD: AUC = 0.861) (they have a high degree of accuracy in predicting whether a subject will develop two diseases). In this study, four co-expression differential genes for OSA and NAFLD were obtained, and they can predict the occurrence of both diseases. Transcriptional mechanisms involved in OSA and NAFLD interactions may be better understood by exploring these key genes. Simultaneously, this study provides potential diagnostic and therapeutic markers for patients with OSA and NAFLD.

Overexpression of REC8 induces aberrant gamete meiotic division and contributes to AML pathogenesis - a multiplexed microarray analysis and mendelian randomization study.

Acute myeloid leukemia (AML) is a notably lethal disease, characterized by malignant clonal proliferation of hematopoietic stem cells in the bone marrow. This study seeks to unveil potential therapeutic targets for AML, using a combined approach of microarray analysis and Mendelian randomization (MR). We collected data samples from the Gene Expression Omnibus (GEO) database and extracted pQTL data from genome-wide association studies (GWAS) to identify overlapping genes between the DEGs and GWAS data. Gene enrichment and pathway annotation analyses were performed on these genes. Furthermore, we validated gene expression levels and assessed their clinical relevance. By taking the intersection of these gene sets, we obtained a list of co-expressed genes, including four upregulated genes (REC8, TPM2, ZMIZ1, CD82) and two downregulated genes (IFNAR1, TMCO3). MR analysis demonstrated that genetically predicted protein levels of CD82, REC8, ZMIZ1, and TPM2 were significantly associated with increased odds of AML, while IFNAR1 and TMCO3 showed a protective effect. Gene ontology and KEGG pathway analyses revealed significant enrichment in functions related to female gamete generation, meiosis, p53 signaling pathway, and cardiac muscle contraction. Differences in immune cell profiles were observed between AML survivors and those with poor prognosis, including lower levels of neutrophils and higher levels of follicular helper T cells in the latter group. This study identifies a causal relationship between gene expression and AML and highlights the potential role of REC8 in leukemogenesis, possibly through its impact on gametocyte meiotic abnormalities. The findings provide new insights into the prevention and treatment of leukemia.

Analysis of the Skin and Brain Transcriptome of Normally Pigmented and Pseudo-Albino Southern Flounder (Paralichthys lethostigma) Juveniles to Study the Molecular Mechanisms of Hypopigmentation and Its Implications for Species Survival in the Natural Environment.

Southern flounder skin pigmentation is a critical phenotypic characteristic for this species' survival in the natural environment. Normal pigmentation allows rapid changes of color for concealment to capture prey and UV light protection. In contrast, highly visible hypopigmented pseudo-albinos exhibit a compromised immune system and are vulnerable to predation, sensitive to UV exposure, and likely have poor survival in the wild. Skin and brain tissue samples from normally pigmented and hypopigmented individuals were analyzed with next-generation RNA sequencing. A total of 1,589,613 transcripts were used to identify 952,825 genes to assemble a de novo transcriptome, with 99.43% of genes mapped to the assembly. Differential gene expression and gene enrichment analysis of contrasting tissues and phenotypes revealed that pseudo-albino individuals appeared more susceptible to environmental stress, UV light exposure, hypoxia, and osmotic stress. The pseudo-albinos' restricted immune response showed upregulated genes linked to cancer development, signaling and response, skin tissue formation, regeneration, and healing. The data indicate that a modified skin collagen structure likely affects melanocyte differentiation and distribution, generating the pseudo-albino phenotype. In addition, the comparison of the brain transcriptome revealed changes in myelination and melanocyte stem cell activity, which may indicate modified brain function, reduced melanocyte migration, and impaired vision.

Genetic parameters, genome-wide association study, and selection perspective on gestation length in 16 French cattle breeds

Lifetime productivity is a trait of great importance to dairy cattle populations as it combines information from production and longevity variables. Therefore, we investigated the genetic background of lifetime productivity in high-producing dairy cattle by integrating genomics and transcriptomics data sets. A total of 3,365,612 test-day milk yield records from 134,029 Chinese Holstein cows were used to define 6 lifetime productivity traits, including lifetime milk yield covering full lifespan and 5 cumulative milk yield traits covering partial lifespan. Genetic parameters were estimated based on univariate and bivariate linear animal models and the Restricted Maximum Likelihood (REML) method. Genome-wide association studies (GWAS) and weighted gene co-expression network analyses (WGCNA) were performed to identify candidate genes associated with lifetime productivity based on genomic data from 3,424 cows and peripheral blood RNA-seq data from 23 cows, respectively. Lifetime milk yield averaged 24,800.8 ± 14,396.6 kg (mean ± SD) across an average of 2.4 parities in Chinese Holstein population. The heritability estimates for lifetime productivity traits ranged from 0.05 (±0.01 for SE) to 0.10 (±0.02 for SE). The estimate of genetic correlation between lifetime milk yield and productive life is 0.88 (±0.3 for SE) while the genetic correlation with 305d milk yield in the first lactation was 0.49 (±0.08 for SE). Absolute values for most genetic correlation estimates between lifetime productivity and type traits were lower than 0.30. Moderate genetic correlations were found between udder related traits and lifetime productivity, such as with udder depth (0.33), rear udder attachment height (0.33), and udder system (0.34). Some single nucleotide polymorphisms and gene co-expression modules significantly associated with lifetime milk yield were identified based on GWAS and WGCNA analyses, respectively. Functional enrichment analyses of the candidate genes identified revealed important pathways related to immune system, longevity, energy utilization and metabolism, and FoxO signaling. The genes NTMT1, FNBP1, and S1PR1 were considered to be the most important candidate genes influencing lifetime productivity in Holstein cows. Overall, our findings indicate that lifetime productivity is heritable in Chinese Holstein cattle and important candidate genes were identified by integrating genomic and transcriptomic data sets.

Transcriptome-Wide Association Study Reveals New Molecular Interactions Associated with Melanoma Pathogenesis.

A transcriptome-wide association study (TWAS) was conducted on genome-wide association study (GWAS) summary statistics of malignant melanoma of skin (UK Biobank dataset) and The Cancer Genome Atlas-Skin Cutaneous Melanoma (TCGA-SKCM) gene expression weights to identify melanoma susceptibility genes. The GWAS included 2465 cases and 449,799 controls, while the gene expression testing was conducted on 103 cases. Afterward, a gene enrichment analysis was applied to identify significant TWAS associations. The melanoma's gene-microRNA (miRNA) regulatory network was constructed from the TWAS genes and their corresponding miRNAs. At last, a disease enrichment analysis was conducted on the corresponding miRNAs. The TWAS detected 27 genes associated with melanoma with p-values less than 0.05 (the top three genes are LOC389458 (RBAK), C16orf73 (MEIOB), and EIF3CL). After the joint/conditional test, one gene (AMIGO1) was dropped, resulting in 26 significant genes. The Gene Ontology (GO) biological process associated the extended gene set (76 genes) with protein K11-linked ubiquitination and regulation of cell cycle phase transition. K11-linked ubiquitin chains regulate cell division. Interestingly, the extended gene set was related to different skin cancer subtypes. Moreover, the enriched pathways were nsp1 from SARS-CoV-2 that inhibit translation initiation in the host cell, cell cycle, translation factors, and DNA repair pathways full network. The gene-miRNA regulatory network identified 10 hotspot genes with the top three: TP53, BRCA1, and MDM2; and four hotspot miRNAs: mir-16, mir-15a, mir-125b, and mir-146a. Melanoma was among the top ten diseases associated with the corresponding (106) miRNAs. Our results shed light on melanoma pathogenesis and biologically significant molecular interactions.

Exploring the Role of Neutrophil-Related Genes in Osteosarcoma via an Integrative Analysis of Single-Cell and Bulk Transcriptome.

The involvement of neutrophil-related genes (NRGs) in patients with osteosarcoma (OS) has not been adequately explored. In this study, we aimed to examine the association between NRGs and the prognosis as well as the tumor microenvironment of OS. The OS data were obtained from the TARGET-OS and GEO database. Initially, we extracted NRGs by intersecting 538 NRGs from single-cell RNA sequencing (scRNA-seq) data between aneuploid and diploid groups, as well as 161 up-regulated differentially expressed genes (DEGs) from the TARGET-OS datasets. Subsequently, we conducted Least Absolute Shrinkage and Selection Operator (Lasso) analyses to identify the hub genes for constructing the NRG-score and NRG-signature. To assess the prognostic value of the NRG signatures in OS, we performed Kaplan-Meier analysis and generated time-dependent receiver operating characteristic (ROC) curves. Gene enrichment analysis (GSEA) and gene set variation analysis (GSVA) were utilized to ascertain the presence of tumor immune microenvironments (TIMEs) and immunomodulators (IMs). Additionally, the KEGG neutrophil signaling pathway was evaluated using ssGSEA. Subsequently, PCR and IHC were conducted to validate the expression of hub genes and transcription factors (TFs) in K7M2-induced OS mice. FCER1G and C3AR1 have been identified as prognostic biomarkers for overall survival. The findings indicate a significantly improved prognosis for OS patients. The effectiveness and precision of the NRG signature in prognosticating OS patients were validated through survival ROC curves and an external validation dataset. The results clearly demonstrate that patients with elevated NRG scores exhibit decreased levels of immunomodulators, stromal score, immune score, ESTIMATE score, and infiltrating immune cell populations. Furthermore, our findings substantiate the potential role of SPI1 as a transcription factor in the regulation of the two central genes involved in osteosarcoma development. Moreover, our analysis unveiled a significant correlation and activation of the KEGG neutrophil signaling pathway with FCER1G and C3AR1. Notably, PCR and IHC demonstrated a significantly higher expression of C3AR1, FCER1G, and SPI1 in Balb/c mice induced with K7M2. Our research emphasizes the significant contribution of neutrophils within the TIME of osteosarcoma. The newly developed NRG signature could serve as a good instrument for evaluating the prognosis and therapeutic approach for OS.

Comprehensive analyses show the enhancement effect of exogenous melatonin on fluroxypyr-meptyl multiple phase metabolisms in Oryza sativa for reducing environmental risks

The role of melatonin (MT), an essential phytohormone controlling the physiological and biochemical reactions of plants to biotic and abiotic stress, in alleviating pesticide phytotoxicity remains unclear. This study explores the effects of MT (0 and 200 mg/L) and six doses of fluroxypyr-meptyl (FLUME) (0–0.14 mg/L) on the physiological response of rice (Oryza sativa). FLUME exposure inhibited the growth of rice seedlings, with MT treatment ameliorating this effect. To determine the biochemical processes and catalytic events involved in FLUME breakdown in rice, six rice root and shoot libraries exposed to either FLUME or FLUME–MT were generated and then subjected to RNA-Seq–LC-Q-TOF-HRMS/MS analyses. The results showed that 1510 root genes and 139 shoot genes exhibited higher upregulation in plants treated with an ecologically realistic FLUME concentration and MT than in those treated with FLUME alone. Gene enrichment analysis revealed numerous FLUME-degradative enzymes operating in xenobiotic tolerance to environmental stress and molecular metabolism. Regarding the FLUME degradation process, certain differentially expressed genes were responsible for producing important enzymes, such as cytochrome P450, glycosyltransferases, and acetyltransferases. Four metabolites and ten conjugates in the pathways involving hydrolysis, malonylation, reduction, glycosylation, or acetylation were characterized using LC-Q-TOF-HRMS/MS to support FLUME-degradative metabolism. Overall, external application of MT can increase rice tolerance to FLUME-induced oxidative stress by reducing phytotoxicity and FLUME accumulation. This study provides insights into MT's role in facilitating FLUME degradation, with potential implications for engineering genotypes supporting FLUME degradation in paddy crops.

Bioinformatics analysis of key genes, immune infiltration, and risk assessment in low bone mineral density among perimenopausal women: An observational study.

This study aimed to identify hub genes and elucidate the molecular mechanisms underlying low bone mineral density (BMD) in perimenopausal women. R software was used to normalize the dataset and screen the gene set associated with BMD in perimenopausal women from the Gene Expression Omnibus database. Cytoscape software was used to identify 7 critical genes. Gene enrichment analysis and protein interaction was employed to further analyze the core genes, and the CIBERSORT deconvolution algorithm was used to perform immune infiltration analysis of 22 immune genes in the samples. Furthermore, an analysis of the immune correlations of 7 crucial genes was conducted. Subsequently, a receiver operating characteristic curve was constructed to assess the diagnostic efficacy of these essential genes. A total of 171 differentially expressed genes were identified that were primarily implicated in the signaling pathways associated with apoptosis. Seven crucial genes (CAMP, MMP8, HMOX1, CTNNB1, ELANE, AKT1, and CEACAM8) were effectively filtered. The predominant functions of these genes were enriched in specific granules. The pivotal genes displayed robust associations with activated dendritic cells. The developed risk model showed a remarkable level of precision, as evidenced by an area under the curve of 0.8407 and C-index of 0.854. The present study successfully identified 7 crucial genes that are significantly associated with low BMD in perimenopausal women. Consequently, this research offers a solid theoretical foundation for clinical risk prediction, drug sensitivity analysis, and the development of targeted drugs specifically tailored for addressing low BMD in perimenopausal women.

Integrated analysis of miRNAome and transcriptome reveals that microgravity induces the alterations of critical functional gene modules via the regulation of miRNAs in short-term space-flown C. elegans

Microgravity, as a unique hazardous factor encountered in space, can induce a series of harmful effects on living organisms. The impact of microgravity on the pivotal functional gene modules stemming from gene enrichment analysis via the regulation of miRNAs is not fully illustrated. To explore the microgravity-induced alterations in critical functional gene modules via the regulation of miRNAs, in the present study, we proposed a novel bioinformatics algorithm for the integrated analysis of miRNAome and transcriptome from short-term space-flown C. elegans. The samples of C. elegans were exposed to two space conditions, namely spaceflight (SF) and spaceflight control (SC) onboard the International Space Station for 4 days. Additionally, the samples of ground control (GC) were included for comparative analysis. Using the present algorithm, we constructed regulatory networks of functional gene modules annotated from differentially expressed genes (DEGs) and their associated regulatory differentially expressed miRNAs (DEmiRNAs). The results showed that functional gene modules of molting cycle, defense response, fatty acid metabolism, lysosome, and longevity regulating pathway were facilitated by 25 down-regulated DEmiRNAs (e.g., cel-miR-792, cel-miR-65, cel-miR-70, cel-lsy-6, cel-miR-796, etc.) in the SC vs. GC groups, whereas these modules were inhibited by 13 up-regulated DEmiRNAs (e.g., cel-miR-74, cel-miR-229, cel-miR-70, cel-miR-249, cel-miR-85, etc.) in the SF vs. GC groups. These findings indicated that microgravity could significantly alter gene expression patterns and their associated functional gene modules in short-term space-flown C. elegans. Additionally, we identified 34 miRNAs as post-transcriptional regulators that modulated these functional gene modules under microgravity conditions. Through the experimental verification, our results demonstrated that microgravity could induce the down-regulation of five critical functional gene modules (i.e., molting cycle, defense response, fatty acid metabolism, lysosome, and longevity regulating pathways) via the regulation of miRNAs in short-term space-flown C. elegans.

Pathophysiology of hypereosinophilia-associated heart disease.

Cardiac complications in patients with hypereosinophilia cause significant morbidity and mortality. However, mechanisms of how eosinophilic inflammation causes heart damage are poorly understood. We developed a model of hypereosinophilia-associated heart disease by challenging hypereosinophilic mice with peptide from the cardiac myosin heavy chain. Disease outcomes were measured by histology, immunohistochemistry, flow cytometry, and measurement of cells and biomarkers in peripheral blood. Eosinophil dependence was determined by using eosinophil-deficient mice (ΔdblGATA). Single cells from heart were subjected to single cell RNA sequencing to assess cell composition, subtypes and expression profiles. Mice challenged with myocarditic and control peptide had peripheral blood leukocytosis, but only those challenged with myocarditic peptide had heart inflammation. Heart tissue was infiltrated by eosinophil-rich inflammatory infiltrates associated with cardiomyocyte damage. Disease penetrance and severity were dependent on the presence of eosinophils. Single cell RNA sequencing showed enrichment of myeloid cells, T-cells and granulocytes (neutrophils and eosinophils) in the myocarditic mice. Macrophages were M2 skewed, and eosinophils had an activated phenotype. Gene enrichment analysis identified several pathways potentially involved in pathophysiology of disease. Eosinophils are required for heart damage in hypereosinophilia-associated heart disease. Additionally, myeloid cells, granulocytes and T-cell cooperatively or independently participate in the pathogenesis of hypereosinophilia-associated heart disease.

Genes associated with cortical thickness alterations in behavioral addiction.

Behavioral addiction (BA) is a conceptually new addictive phenotype characterized by compulsive reward-seeking behaviors despite adverse consequences. Currently, its underlying neurogenetic mechanism remains unclear. Here, this study aimed to investigate the association between cortical thickness (CTh) and genetic phenotypes in BA. We conducted a systematic search in five databases and extracted gene expression data from the Allen Human Brain Atlas. Meta-analysis of 10 studies (343 addicted individuals and 355 controls) revealed that the BA group showed thinner CTh in the precuneus, postcentral gyrus, orbital-frontal cortex, and dorsolateral prefrontal cortex (P < 0.005). Meta-regression showed that the CTh in the precuneus and postcentral gyrus were negatively associated with the addiction severity (P < 0.0005). More importantly, the CTh phenotype of BA was spatially correlated with the expression of 12 genes (false discovery rate [FDR] < 0.05), and the dopamine D2 receptor had the highest correlation (rho = 0.55). Gene enrichment analysis further revealed that the 12 genes were involved in the biological processes of behavior regulation and response to stimulus (FDR < 0.05). In conclusion, our findings demonstrated the thinner CTh in cognitive control-related brain areas in BA, which could be associated with the expression of genes involving dopamine metabolism and behavior regulation.

Integrative Analysis Identified rs907091 at the miRNA Binding Region of the IKZF3 Gene as a Potential Functional Variant for Rheumatoid Arthritis

Objective: Previous studies have identified a large number of associations between genetic variants and rheumatoid arthritis (RA), but the functional mechanisms underlying the associations are largely unknown. Methods: Based on publicly available datasets and results, we explored the functional mechanisms underlying the associations between regulatory polymorphisms in miRNA target sites (poly-miRTSs) and RA by combining integrative analyses (expression quantitative trait locus analysis, eQTL, and gene enrichment analysis) with in-house molecular experiments (allelic expression imbalance experiment, AEI, and dual-luciferase reporter gene assay). Results: By integrating the results from the MirSNP and eQTL databases, a total of 114 pairs between poly-miRTSs and target genes were identified, which correspond to 70 unique poly-miRTSs and 28 genes. Most of the 28 genes were located in the HLA region, and they tended to be enriched in multiple immune-related GO terms or pathways, e.g., “antigen processing and presentation” and “immune response”. Among these poly-miRTSs, rs907091 in the 3’UTR of IKZF3 (non-HLA region) was highlighted. Further AEI experiments showed that the C allele had a higher expression of ~18% than the T allele, suggesting an obvious allelic expression imbalance. Dual-luciferase reporter gene assays showed that miR-326 and miR-330-5p could regulate IKZF3 expression (P&lt;0.05) mediated by rs907091 in the 3’UTR binding site. Conclusion: Our study explored some functional mechanisms underlying the associations between poly-miRTSs and target genes and highlighted rs907091 at the miRNA binding region of the IKZF3 gene as a potential functional variant for rheumatoid arthritis.

Decoding Retinoblastoma: Unveiling Gene Networks and Potential Targets through In Silico Analysis

Background Retinoblastoma is an aggressive cancer whose majority of patients are infants and children below the age of five. Approximately 80% of the total patients of retinoblastoma reside in low-to-middle-income countries like India. Lack of public and medical awareness and the absence of significant and regular clinical trials to test and authenticate new potential treatments impede the process of treating retinoblastoma. Attempts have been made to establish an effective way to diagnose retinoblastoma early so that it can be controlled in time, but so far, no significant success has been documented on that front. Moreover, recent strategies include computational and informatics solutions to identify potential targets at a genetic level to alter the expression of defective proteins in human subjects. Aim The main aim of the current study is to unravel the potential targets of Retinoblastoma, an aggressive pediatric cancer, utilizing an in silico network biology approach. Methods In the present study, we have utilized the gene network analysis approach to identify hub genes that affect the expression in the human system. We developed the Protein – Protein Interaction network utilizing 158 genes extracted from the NCBI OMIM database and identified 15 key genes, which were then subjected to metascape analysis to identify pathways and processes that affect and prioritize genes based on their significance scores. We were able to identify the following target genes: RBBP4, TFDP1, and RBBP7. Result RBBP4, TFDP1, and RBBP7 were identified as the most novel target genes against retinoblastoma after gene network and enrichment analysis. Conclusion Our in-silico network analysis unveiled the intricate mechanisms behind the progression of retinoblastoma by dissecting 158 associated genes in humans. Thus, this work not only illuminates the underlying dynamics of the disease but also offers a promising avenue for intervention.

P-159 Single-cell high-throughput methylation and transcriptomic analysis indicates variations in sensitivity to Folate-mediated one-carbon metabolism in mouse preimplantation embryos

Abstract Study question Do Folate-mediated one-carbon metabolism (FOCM) supplements impose methylating conditions that influence methylation and transcriptomic profiles during preimplantation period of mouse embryos? Summary answer Subtle differences in embryo methylation profiles were induced by FOCM supplements, despite transcriptomic signatures remained stable and selective genes related to metabolism were activated. What is known already Previous human studies of populations affected by seasonal variations in diet including folate availability have shown methylation changes in specific loci known as metastable epialleles (MEs). MEs exhibit stability across tissues, indicating these could be potential biosensors for heightened sensitivity to external methylating influences in early embryonic stages. Despite significant progress in IVF embryo culture conditions, the sensitivity to the outer metabolic environment during the extensive genomic transformation of embryo reprogramming remains inadequately understood. Study design, size, duration This is a prospective experimental study conducted from January 2023 to December 2023. A total of 111 fresh mouse zygotes (F1 hybrid (B6/CBA)) were subjected embryo culture conditions with different FOCM supplies of 5-MTHF and betaine up to expanded blastocyst stage (105 hours). At different timepoints, individual embryos were collected and disaggregated in individual cells for downstream single-cell analysis. Participants/materials, setting, methods Mouse zygotes were collected from the oviduct, washed and culture in KSOM supplemented with 5-MTHF and betaine at respectively concentrations of 50μM and 50μg/mL (THF/bet(50)), 10μM and 10μg/mL (THF/bet(10)) and no supplement till blastocyst stage at 37 °C, 6%CO2 and 5%O2. Individual embryos were collected at 2 cells, 4 cells, 8 cells, Morula and Blastocyst stage and disaggregated into single cells for subsequent single-cell RNAseq (SmartSeq2) and single-cell methylome analysis through Splinted Ligation Adapter Tagging (scSPLAT). Main results and the role of chance The methylation analysis conducted though scSPLAT revealed a comprehensive reduction in global methylation levels throughout developmental stages. Notably, zygotes exhibited a maximal proportion of methylated cytosines at CpG sites, while blastocysts displayed minimal methylation levels, with sporadic increases in isolated cells. Quantitative profiling indicated lower methylation intensities in treated embryos from zygote to 4 cells, followed by a reversal trend from 8 cells to blastocyst, suggestive of an enhanced assimilation of one-carbon metabolism (FOCM) supplements. Transcriptomic profiles obtained through scRNAseq exhibited correlation with developmental trajectories from zygote to blastocyst. However, no discernible variations were attributed to the combined exposure of Betaine and 5-MTHF. Gene enrichment analysis of differentially expressed genes at various timepoints highlighted specific metabolic responses, including mitochondrial oxidative stress and variations in glutathione metabolism. This suggests that the folate forms utilized in this study may possess a protective role as antioxidants, contributing to the observed effects on gene expression during embryonic development. Limitations, reasons for caution The methylation analysis shown in this study was a pilot carried out with low coverage of sequencing deepness, further analysis are ongoing to increase reads coverage. Wider implications of the findings Exposure of mouse embryos to FOCM enhanced global methylation during cell division from 8 cells to blastocyst, indicating heightened assimilation during DNA synthesis. While the transcriptomic signature remained stable, increased expression of genes linked to mitochondrial oxidative stress and glutathione metabolism suggests FOCM’s potential antioxidant role. Trial registration number not applicable

Identification of immune-associated biomarkers of diabetes nephropathy tubulointerstitial injury based on machine learning: a bioinformatics multi-chip integrated analysis

BackgroundDiabetic nephropathy (DN) is a major microvascular complication of diabetes and has become the leading cause of end-stage renal disease worldwide. A considerable number of DN patients have experienced irreversible end-stage renal disease progression due to the inability to diagnose the disease early. Therefore, reliable biomarkers that are helpful for early diagnosis and treatment are identified. The migration of immune cells to the kidney is considered to be a key step in the progression of DN-related vascular injury. Therefore, finding markers in this process may be more helpful for the early diagnosis and progression prediction of DN.MethodsThe gene chip data were retrieved from the GEO database using the search term ' diabetic nephropathy ‘. The ' limma ' software package was used to identify differentially expressed genes (DEGs) between DN and control samples. Gene set enrichment analysis (GSEA) was performed on genes obtained from the molecular characteristic database (MSigDB. The R package ‘WGCNA’ was used to identify gene modules associated with tubulointerstitial injury in DN, and it was crossed with immune-related DEGs to identify target genes. Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on differentially expressed genes using the ‘ClusterProfiler’ software package in R. Three methods, least absolute shrinkage and selection operator (LASSO), support vector machine recursive feature elimination (SVM-RFE) and random forest (RF), were used to select immune-related biomarkers for diagnosis. We retrieved the tubulointerstitial dataset from the Nephroseq database to construct an external validation dataset. Unsupervised clustering analysis of the expression levels of immune-related biomarkers was performed using the ‘ConsensusClusterPlus ‘R software package. The urine of patients who visited Dongzhimen Hospital of Beijing University of Chinese Medicine from September 2021 to March 2023 was collected, and Elisa was used to detect the mRNA expression level of immune-related biomarkers in urine. Pearson correlation analysis was used to detect the effect of immune-related biomarker expression on renal function in DN patients.ResultsFour microarray datasets from the GEO database are included in the analysis : GSE30122, GSE47185, GSE99340 and GSE104954. These datasets included 63 DN patients and 55 healthy controls. A total of 9415 genes were detected in the data set. We found 153 differentially expressed immune-related genes, of which 112 genes were up-regulated, 41 genes were down-regulated, and 119 overlapping genes were identified. GO analysis showed that they were involved in various biological processes including leukocyte-mediated immunity. KEGG analysis showed that these target genes were mainly involved in the formation of phagosomes in Staphylococcus aureus infection. Among these 119 overlapping genes, machine learning results identified AGR2, CCR2, CEBPD, CISH, CX3CR1, DEFB1 and FSTL1 as potential tubulointerstitial immune-related biomarkers. External validation suggested that the above markers showed diagnostic efficacy in distinguishing DN patients from healthy controls. Clinical studies have shown that the expression of AGR2, CX3CR1 and FSTL1 in urine samples of DN patients is negatively correlated with GFR, the expression of CX3CR1 and FSTL1 in urine samples of DN is positively correlated with serum creatinine, while the expression of DEFB1 in urine samples of DN is negatively correlated with serum creatinine. In addition, the expression of CX3CR1 in DN urine samples was positively correlated with proteinuria, while the expression of DEFB1 in DN urine samples was negatively correlated with proteinuria. Finally, according to the level of proteinuria, DN patients were divided into nephrotic proteinuria group (n = 24) and subrenal proteinuria group. There were significant differences in urinary AGR2, CCR2 and DEFB1 between the two groups by unpaired t test (P < 0.05).ConclusionsOur study provides new insights into the role of immune-related biomarkers in DN tubulointerstitial injury and provides potential targets for early diagnosis and treatment of DN patients. Seven different genes ( AGR2, CCR2, CEBPD, CISH, CX3CR1, DEFB1, FSTL1 ), as promising sensitive biomarkers, may affect the progression of DN by regulating immune inflammatory response. However, further comprehensive studies are needed to fully understand their exact molecular mechanisms and functional pathways in DN.

Bioinformatics analysis of potential pathogenesis and risk genes of neuroinflammation-promoted brain injury in intracerebral hemorrhage

IntroductionSpontaneous (non-traumatic) intracerebral hemorrhage (ICH) is one of the major causes of global death. The purpose of our bioinformatics analysis was to detect viable pathophysiological targets and small-molecule drug candidates and to identify the precise secondary mechanisms of brain injury in ICH. Material and methodsThe GSE24265 dataset, consisting of data from four perihematomal brain tissues and seven contralateral brain tissues, was downloaded from the Gene Expression Omnibus (GEO) database and screened for differentially expressed genes (DEGs) in ICH. Online analysis tool GEO2R and Drug Susceptibility Assessment Module within the ACBI Bioinformation tool was used for data differential expression analysis. TargetScan, miRDB, and RNA22 were used to investigate the miRNAs regulating the DEGs. The functional annotation of DEGs was performed using Gene Ontology (GO) resources, and the cell signaling pathway analysis of DEGs was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG). DAVID is used to perform GO function enrichment analysis and KEGG pathway analysis of candidate target genes. Enrichment analysis was performed for delving the molecular mechanism of DEGs, and protein–protein interaction (PPI) networks and microRNA (miRNA)-messenger RNA (mRNA) networks were used to reveal the hub nodes and the related interaction relationships. Hub genes and miRNA-mRNA interaction of PPI network were identified by STRING version 12.0 online software and Cytoscape. Next, the DEGs were analyzed using the L1000CDS2 database to identify small-molecule compounds with potential therapeutic effects. ResultsA total of 325 upregulated genes and 103 downregulated genes associated with ICH were identified. The biological functions of DEGs associated with ICH are mainly involved in the inflammatory response, chemokine activity, and immune response. The KEGG analysis identified several pathways significantly associated with ICH, including but not limited to cytokine-cytokine receptor interaction and MAPK signaling pathway. A PPI network consisting of 188 nodes and 563 edges was constructed using STRING, and 27 hub genes were identified with Cytoscape software. The miRNA-mRNA network with high connectivity contained key 27 mRNAs (from C-C motif chemokine ligand 5 (CCL5), C-C motif chemokine ligand 8 (CCL8), …., to dishevelled-associated activator of morphogenesis 1 (DAAM1), and FRAT regulator of WNT signaling pathway 1 (FRAT1)) and 135 candidate miRNAs. These genes and miRNAs are closely related to secondary brain injury induced by ICH. In addition, a L1000CDS2 analysis of six small-molecule compounds revealed their therapeutic potential. ConclusionsOur study explores the pathogenesis of brain tissue injury promoted by neuroinflammation in ICH and extends the clinical utility of its key genes. At the same time, we constructed a miRNA-mRNA network which may play crucial roles in the pathogenesis of ICH. In addition, we obtained six small molecule compounds that will have anti-inflammatory effects on ICH, including Geldanamycin, Dasatinib, BMS-345541, Saracatinib, and Afatinib.

Microarray-based Detection of Critical Overexpressed Genes in the Progression of Hepatic Fibrosis in Non-alcoholic Fatty Liver Disease: A Protein-protein Interaction Network Analysis.

Non-alcoholic fatty liver disease (NAFLD) is a prevalent cause of chronic liver disease and encompasses a broad spectrum of disorders, including simple steatosis, steatohepatitis, fibrosis, cirrhosis, and liver cancer. However, due to the global epidemic of NAFLD, where invasive liver biopsy is the gold standard for diagnosis, it is necessary to identify a more practical method for early NAFLD diagnosis with useful therapeutic targets; as such, molecular biomarkers could most readily serve these aims. To this end, we explored the hub genes and biological pathways in fibrosis progression in NAFLD patients. Raw data from microarray chips with GEO accession GSE49541 were downloaded from the Gene Expression Omnibus database, and the R package (Affy and Limma) was applied to investigate differentially expressed genes (DEGs) involved in the progress of low- (mild 0-1 fibrosis score) to high- (severe 3-4 fibrosis score) fibrosis stage NAFLD patients. Subsequently, significant DEGs with pathway enrichment were analyzed, including gene ontology (GO), KEGG and Wikipathway. In order to then explore critical genes, the protein-protein interaction network (PPI) was established and visualized using the STRING database, with further analysis undertaken using Cytoscape and Gephi software. Survival analysis was undertaken to determine the overall survival of the hub genes in the progression of NAFLD to hepatocellular carcinoma. A total of 311 significant genes were identified, with an expression of 278 being upregulated and 33 downregulated in the high vs. low group. Gene functional enrichment analysis of these significant genes demonstrated major involvement in extracellular matrix (ECM)-receptor interaction, protein digestion and absorption, and the AGE-RAGE signaling pathway. The PPI network was constructed with 196 nodes and 572 edges with PPI enrichment using a p-value < 1.0 e-16. Based on this cut-off, we identified 12 genes with the highest score in four centralities: Degree, Betweenness, Closeness, and Eigenvector. Those twelve hub genes were CD34, THY1, CFTR, COL3A1, COL1A1, COL1A2, SPP1, THBS1, THBS2, LUM, VCAN, and VWF. Four of these hub genes, namely CD34, VWF, SPP1, and VCAN, showed significant association with the development of hepatocellular carcinoma. This PPI network analysis of DEGs identified critical hub genes involved in the progression of fibrosis and the biological pathways through which they exert their effects in NAFLD patients. Those 12 genes offer an excellent opportunity for further focused research to determine potential targets for therapeutic applications.

Integrated approach of network pharmacology, molecular docking, and clinical observations in evaluating the efficacy and safety of Bufei Huoxue capsules for pulmonary hypertension associated with chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a persistent and progressive disorder characterized by airway or alveolar abnormalities, commonly leading to pulmonary hypertension (PH). This clinical observational study investigates the therapeutic mechanisms of Bufei Huoxue capsules (BHC) in treating PH in patients with COPD-linked PH (COPD-PH) using network pharmacology and molecular docking methods, and assesses the therapeutic efficacy and safety of BHCs. The active compounds and their target proteins in BHCs were sourced from the Traditional Chinese Medicine Systems Pharmacology database, with additional target proteins derived from the GeneCards and OMIM databases. An active network was constructed using Cytoscape 3.7.1, and interaction networks were established. Intersecting targets underwent Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using the Metascape database. Network pharmacology and molecular docking studies demonstrated favorable binding affinities of BHC active ingredients, such as quercetin, bavachalcone, and isobavachin, for key targets including PTGS1, ESR1, and PTGS2. Gene Ontology enrichment analysis highlighted the involvement of these targets in processes such as the positive regulation of locomotion, the transmembrane receptor protein tyrosine kinase signaling pathway, and peptidyl-tyrosine phosphorylation. KEGG pathway analysis indicated their roles in pathways related to cancer, AGE-RAGE signaling in diabetic complications, and prostate cancer. BHCs exhibit therapeutic effects on COPD-PH through multi-component, multi-target, and multi-pathway interactions. This clinical observational study confirms the efficacy and safety of BHCs in improving cardiac and pulmonary functions, enhancing exercise tolerance, and elevating the quality of life in patients with COPD-PH.

A novel m6A/m5C/m1A/m7G-related classification and risk signature predicts prognosis and reveals immunotherapy inclination in gastric cancer.

Gastric cancer (GC) is characterized by high morbidity and mortality rates, and the prognosis is not optimistic. Therefore, the search for new biomarkers is crucial. Methylation modifications in RNA modifications play a crucial role in tumors. However, the role of methylation modification of integrated m6A/m5C/m1A/m7G, in GC and its related analysis have not been reported. It still needs to be studied in depth. Our study aims to deepen our understanding of m6A/m5C/m1A/m7G methylation and potentially provide new strategies for GC treatment. We used TCGA-STAD (The Cancer Genome Atlas-Stomach Adenocarcinoma) as a training set and GSE84433 as a validation set to analyze and determine potential associations between m6A/m5C/m1A/m7G-related genes and clinical risk of GC. In addition, we explored the prognostic value and potential biological mechanisms of m6A/m5C/m1A/m7G-related genes in GC through consistent clustering, differential expression gene identification, enrichment analysis, and immune infiltration analysis. Finally, we constructed m6A/m5C/m1A/m7G-related risk signature (MRRS) to evaluate the correlation between risk grade and survival prognosis, drug sensitivity, and immune infiltration, and validated the validity by immunohistochemical staining. We identified subgroups of C1, C2, and C3 patients by consensus clustering using data from 45 m6A/m5C/m1A/m7G-related genes. The three groups showed significant differences in survival, immune scores, and immune cell infiltration. We then constructed MRRS using least absolute shrinkage and selection operator (LASSO) regression analysis, including SLC5A6, FKBP10, GPC3, and GGH, which could accurately differentiate between high-/low-risk populations. Its accuracy was further validated in the validation set and immunohistochemical staining. These results suggest that m6A/m5C/m1A/m7G are closely related to the GC tumor immune microenvironment, and MRRS has good performance in predicting the survival of GC patients. In this study, we highlighted the association of m6A/m5C/m1A/m7G subtypes with changes in the GC immunotumor microenvironment. We constructed and validated MRRS, which is valuable in predicting survival, immune infiltration and drug sensitivity in GC patients. This helps to deepen our understanding of m6A/m5C/m1A/m7G methylation and potentially provides new strategies for GC treatment.