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Unveiling the genetic basis of the low pH response in the acidophilic yeast Maudiozyma bulderi as a potential host for biorefinery.

Nonconventional yeasts represent a great genetic and phenotypic diversity with potential for industrial strain development in the bio-production of green chemicals. In recent years, mass genome sequencing of nonconventional yeasts has opened avenues to improved understanding of transcriptional networks and phenotypic plasticity and gene function, including the discovery of novel genes. Here, we investigated the expressional and morphological changes at low-pH in three strains of the acidophilic yeast Maudiozyma bulderi (previously Kazachstania bulderi and Saccharomyces bulderi): CBS 8638, CBS 8639, and NRRL Y-27205. The comparison of the transcriptome of cells growing in a bioreactor at pH = 5.5 vs pH = 2.5, primarily showed dysregulation of genes involved in cell wall integrity, with NRRL Y-27205 the least acidophilic strain, showing the largest transcriptional response when compared to the other strains. We identified four uncharacterized genes, unique to M. bulderi, and predicted function as transporters, upregulated at low pH. Microscopy studies showed that M. bulderi cell wall is not damaged in acidic environment, and the membrane lipid composition remains stable at low pH, unlike Saccharomyces cerevisiae. Overall, our data on transcriptional variability in M. bulderi highlights genes and cellular pathways involved in the acidophilic adaptation of this species and can aid further strain development.

Hydrogen-Ion Concentration↗

Genome-wide epigenomic atlas and multi-omics responses of Eriocheir sinensis to natural extreme heat.

BACKGROUND: Global climate warming has led to increasingly frequent and prolonged extreme summer heat events, posing severe environmental challenges to aquaculture systems. Extreme summer heat can disrupt the performance of pond-cultured ectotherms. The Chinese mitten crab (Eriocheir sinensis) is an economically important freshwater crustacean, but coordinated molecular differences following contrasting natural summers remain incompletely characterized. RESULTS: We performed a comprehensive multi-omics analysis integrating meteorological monitoring, mRNA/lncRNA transcriptomics, small-RNA profiling of miRNAs, DNA methylomics, and LC-MS metabolomics in E. sinensis populations collected from Yancheng, China, between 2020 and 2024. Across the ten farms, survival was significantly lower in 2024, whereas yield and the proportion of large individuals showed nonsignificant downward trends. Gene-set analyses showed negative enrichment of cellular heat-response, protein-folding, oxidative-phosphorylation, and mitochondrial ATP-production terms in the 2024 cohort at the time of sampling. The integrated transcript annotation contained 72,240 lncRNAs and 63,833 mRNAs, and CpG was the predominant methylation context. Differential methylation analysis identified 73 regions and 185 cytosines, with hypomethylated events predominating within the significant subset. Metabolomic profiles differed between annual cohorts and mapped to carbohydrate, lipid, and amino-acid pathways. Cross-omics integration prioritized eight candidate genes-ADCY9, UNC79, UBN1, IFT52, ACO2, LOC126986070, LOC127001126, and LOC126997895-and qPCR reproduced the reported directions of expression for selected RNAs. CONCLUSION: This study provides the first integrative multi-omics framework for understanding chronic heat adaptation in E. sinensis. By linking transcriptomic, epigenomic, and metabolic remodeling, we elucidate the molecular mechanisms underlying energy imbalance, epigenetic reprogramming, and immune dysregulation during prolonged thermal stress. These findings offer valuable insights and genomic resources for breeding heat-tolerant crab strains and improving aquaculture resilience under ongoing climate change.

DNA methylation↗

Profiling at mRNA, protein, and metabolite levels reveals alterations in renal amino acid handling and glutathione metabolism in kidney tissue of Pept2-/- mice.

PEPT2 is an integral membrane protein in the apical membrane of renal epithelial cells that operates as a rheogenic transporter for di- and tripeptides and structurally related drugs. Its prime role is thought to be the reabsorption of filtered di- and tripeptides contributing to amino acid homeostasis. To elucidate the role of PEPT2 in renal amino acid metabolism we submitted kidney tissues of wild-type and a Pept2(-/-) mouse line to a comprehensive transcriptome, proteome and metabolome profiling and analyzed urinary amino acids and dipeptides. cDNA microarray analysis identified 147 differentially expressed transcripts in transporter-deficient animals, and proteome analysis by 2D-PAGE and MALDI-TOF-MS identified 37 differentially expressed proteins. Metabolite profiling by GC-MS revealed predominantly altered concentrations of amino acids and derivatives. Urinary excretion of amino acids demonstrated increased glycine and cysteine/cystine concentrations and dipeptides in urine were assessed by amino acid analysis of urine samples before and after in vitro dipeptidase digestion. Dipeptides constituted a noticeable fraction of urinary amino acids in Pept2(-/-) animals, only, and dipeptide-bound glycine and cystine were selectively increased in Pept2(-/-) urine samples. These findings were confirmed by a drastically increased excretion of cysteinyl-glycine (cys-gly). Urinary loss of cys-gly together with lower concentrations of cysteine, glycine, and oxoproline in kidney tissue and altered expression of mRNA and proteins involved in glutathione (GSH) metabolism suggests that PEPT2 is predominantly a system for reabsorption of cys-gly originating from GSH break-down, thus contributing to resynthesis of GSH.

Amino Acids↗

Cardiovascular Complications Are Increased in Inflammatory Bowel Disease: A Path Toward Achievement of a Personalized Risk Estimation.

Background/Objectives: The global burden of inflammatory bowel diseases (IBDs) continues to rise, with up to 50% of patients experiencing extraintestinal manifestations. Cardiovascular diseases (CVDs) are of particular concern, ranking as the second leading cause of mortality in this population. Despite a comparatively lower prevalence of traditional cardiovascular (CV) risk factors, the persistent inflammatory milieu and immune dysregulation inherent to IBD may contribute to heightened CVD risk. In this study, following a review of the current literature, an ongoing prospective trial designed to clarify CV risk profiles in IBD patients is detailed. Methods: A cohort of patients with IBD is being enrolled for comprehensive baseline evaluation of CV risk factors, lifestyle metrics, and disease characteristics. The incidence of major adverse cardiovascular events (MACEs) will be tracked and contrasted with a gender- and age-matched non-IBD cohort over a 2-year follow-up period. In cases of MACE occurrence, a multi-omics analysis-including genomic, proteomic, transcriptomic, and microbiome profiling-will be performed, along with a parallel evaluation in matched IBD controls without MACE. An artificial intelligence (AI) framework will support the analysis of this complex dataset. Results: To date, over 150 patients with IBD have been enrolled, and detailed phenotypic data and biological samples have been collected. Conclusions: We aim to introduce an IBD-specific correction factor for existing CV risk scores upon study completion. This is particularly relevant for individuals under 40 years of age, who are often inadequately assessed by current risk stratification models.

Crohn’s disease↗

Serial analysis of gene expression (SAGE): advances, analysis and applications to pigment cell research.

As cells progress from normal to diseased states, they may undergo a series of gene expression changes. Advances in molecular biology allow us to examine a host of these changes at once, in a high throughput fashion. Serial analysis of gene expression (SAGE) allows for the expression profiling of the complete transcriptome of a given cell, and has the potential for identifying novel genes as well as those in low abundance. In this review, we will outline the technique, how one analyzes the massive amounts of data generated, and describe pigment cell libraries currently in the making.

Gene Expression Profiling↗

Airway microbiome diversity, intramucosal bacteria, and spatial immunity in asthmatic adults and controls.

RATIONALE: Asthma is characterized by disruption of the thoracic airway mucosae and loss of microbial diversity. Spatial profiling of the mucosal transcriptome may systematically discover mechanisms for microbial influences on immunity. OBJECTIVES: We investigated relationships between clinical measures, microbial communities, and the host mucosal transcriptome within different strata of bronchial biopsies in subjects with and without asthma. METHODS: We performed bronchoscopy in 65 asthmatic adults and 44 healthy controls, quantifying bacterial operational taxonomic units (OTUs) in bronchial brushings by 16S ribosomal RNA (rRNA) gene amplicon sequences. Biopsy histologic features were scored blind to diagnosis. Following 16S rRNA in situ hybridization of 44 biopsies, bacterial foci were scored in epithelium, basement membrane, and stroma. Global human gene expression was quantified in epithelial and stromal compartments using digital spatial profiling. MEASUREMENTS AND MAIN RESULTS: Clinical asthma was independently predicted by basement membrane abnormalities (BaseMA), endobronchial bacterial diversity, and circulating eosinophil counts, but not by specific OTU abundances. 16S rRNA staining revealed bacteria within epithelium and mucosa of all biopsies. Intramucosal bacteria counts correlated negatively with spatially organized coexpression networks encoding antigen-specific immunity, neutrophil functions, and matrix activation, whereas BaseMA correlated positively with the adaptive immunity module. Eosinophil counts correlated with epithelial bacterial counts and senescence pathways. Clinical asthma was accompanied by upregulation of a regulatory T-cell network. CONCLUSIONS: Asthma and its related phenotypes are accompanied by complex mucosal events that extend beyond eosinophilic pathways. Components of diverse airway microbiota may modify immunity by beneficial interactions within the mucosa.

Humans↗

Ability to differentiate between cp and ncp BVDV by microarrays: towards an application in clinical veterinary medicine?

Microarray expression profiling provides a comprehensive portrait of the transcriptional world enabling us to view the organism as a 'system' that is more than the sum of its parts. The vigilance of cells to environmental change, the alacrity of the transcriptional response, the short half-life of cellular mRNA and the genome-scale nature of the investigation collectively explain the power of this method. These same features pose the most significant experimental design and execution issues which, unless surmounted, predictably generate a distorted image of the transcriptome. Conversely, the expression profile of a properly conceived and conducted microarray experiment can be used for hypothesis testing: disclosure of the metabolic and biosynthetic pathways that underlie adaptation of the organism to infectious processes; the identification of co-ordinately regulated genes; the regulatory circuits and signal transduction systems that mediate the adaptive response; and temporal features of developmental programmes. The study of viral pathogenesis by microarray expression profiling poses special challenges and opportunities. Although the technical hurdles are many, obtaining expression profiles of an organism growing in tissue will probably reveal strategies for growth and survival of the virus in the host's cells. Here, we show data obtained using a tailored microarray system based on synthetic polynucleotides derived from human sequences (SIRS-Lab GmbH, Jena, Germany) to study the effect of cytopathogenic (cpe) and non-cytopathogenic (ncp) bovine viral diarrhoea virus (BVDV) infection of bovine macrophages, focusing on intracellular signalling molecules. Of the 575 genes present on the array, more than 70% showed a reaction with the oligonuleotides spotted on the array, and 26 genes were differentially expressed comparing cDNA derived from cpe and ncp infected cells. These data will help to further understand our knowledge regarding BVDV infection, and will especially help to understand differences in cellular responses to cpe and ncp biotypes.

Animals↗

Large-scale analysis of the human and mouse transcriptomes.

High-throughput gene expression profiling has become an important tool for investigating transcriptional activity in a variety of biological samples. To date, the vast majority of these experiments have focused on specific biological processes and perturbations. Here, we have generated and analyzed gene expression from a set of samples spanning a broad range of biological conditions. Specifically, we profiled gene expression from 91 human and mouse samples across a diverse array of tissues, organs, and cell lines. Because these samples predominantly come from the normal physiological state in the human and mouse, this dataset represents a preliminary, but substantial, description of the normal mammalian transcriptome. We have used this dataset to illustrate methods of mining these data, and to reveal insights into molecular and physiological gene function, mechanisms of transcriptional regulation, disease etiology, and comparative genomics. Finally, to allow the scientific community to use this resource, we have built a free and publicly accessible website (http://expression.gnf.org) that integrates data visualization and curation of current gene annotations.

Animals↗

Blood from septic patients with necrotising soft tissue infection treated with hyperbaric oxygen reveal different gene expression patterns compared to standard treatment.

BACKGROUND: Sepsis and shock are common complications of necrotising soft tissue infections (NSTI). Sepsis encompasses different endotypes that are associated with specific immune responses. Hyperbaric oxygen (HBO2) treatment activates the cells oxygen sensing mechanisms that are interlinked with inflammatory pathways. We aimed to identify gene expression patterns associated with effects of HBO2 treatment in patients with sepsis caused by NSTI, and to explore sepsis-NSTI profiles that are more receptive to HBO2 treatment. METHODS: An observational cohort study examining 83 NSTI patients treated with HBO2 in the acute phase of NSTI, fourteen of whom had received two sessions of HBO2 (HBOx2 group), and another ten patients (non-HBO group) who had not been exposed to HBO2. Whole blood RNA sequencing and clinical data were collected at baseline and after the intervention, and at equivalent time points in the non-HBO group. Gene expression profiles were analysed using machine learning techniques to identify sepsis endotypes, treatment response endotypes and clinically relevant transcriptomic signatures of response to treatment. RESULTS: We identified differences in gene expression profiles at follow-up between HBO2-treated patients and patients not treated with HBO2. Moreover, we identified two patient endotypes before and after treatment that represented an immuno-suppressive and an immune-adaptive endotype respectively, and we characterized the genetic profile of the patients that transition from the immuno-suppressive to the immune-adaptive endotype after treatment. We discovered one gene MTCO2P12 that distinguished individuals who altered their endotype in response to treatment from non-responders. CONCLUSION: The global gene expression pattern in blood changed in response to HBO2 treatment in a direction associated with clinical biochemistry improvement, and the study provides potential novel biomarkers and pathways for monitoring HBO2 treatment effects and predicting an HBO2 responsive NSTI-sepsis profile. TRIAL REGISTRATION: Biological material was collected during the INFECT study, registered at ClinicalTrials.gov (NCT01790698) 04/02/2013.

Humans↗

Gene expression variation between mouse inbred strains.

BACKGROUND: In this study, we investigated the effect of genetic background on expression profiles. We analysed the transcriptome of mouse hindlimb muscle of five frequently used mouse inbred strains using spotted oligonucleotide microarrays. RESULTS: Through ANOVA analysis with a false discovery rate of 10%, we show that 1.4% of the analysed genes is significantly differentially expressed between these mouse strains. Differential expression of several of these genes has been confirmed by quantitative RT-PCR. The number of genes affected by genetic background is approximately ten-fold lower than the number of differentially expressed genes caused by a dystrophic genetic defect. CONCLUSIONS: We conclude that evaluation of the effect of background on gene expression profiles in the tissue under study is an effective and sensible approach when comparing expression patterns in animal models with heterogeneous genetic backgrounds. Genes affected by the genetic background can be excluded in subsequent analyses of the disease-related changes in expression profiles. This is often a more effective strategy than backcrossing and inbreeding to obtain isogenic backgrounds.

Animals↗

Impact of commensal microbiota on murine gastrointestinal tract gene ontologies.

The gastrointestinal tract (GIT) of eukaryotes is colonized by a vast number of bacteria, where the commensal microbiota play an important role in defining the healthy gut. To investigate the influence of commensal bacteria on multiple regions of the host GIT transcriptome, the gene expression profiles of the corpus, jejunum, descending colon, and rectum of conventional (n = 3) and germ-free mice (n = 3) were examined using the Affymetrix Mu74Av2 GeneChip. Differentially regulated genes were identified using the global error assessment model, and a novel method of Gene Ontology (GO) clustering was used to identify significantly modulated biological functions. The microbiota modify the greatest number of genes in the jejunum (267 genes with an alpha < 0.001) and the fewest in the rectum (137 genes with an alpha < 0.001). Clustering genes by GO biological process and molecular function annotations revealed that, despite the large number of differentially regulated genes, the residential microbiota most significantly modified genes involved in such biological processes as immune function and water transport all along the length of the mouse GIT. Additionally, region-specific communication between the host and microbiota were identified in the corpus and jejunum, where tissue kallikrein and apoptosis regulator activities were modulated, respectively. These findings identify important interactions between the microbiota and the mouse gut tissue transcriptome and, furthermore, suggest that interactions between the microbial population and host GIT are implicated in the coordination of region-specific functions.

Animals↗

Spatial Omics in High-Grade Gliomas: Mapping Immune-Tumor Niches for Precision Therapy.

High-grade gliomas (HGGs), particularly glioblastoma (GBM), remain among the most lethal human cancers despite decades of molecular profiling and therapeutic innovation. A primary reason for treatment failure is that HGG biology is spatial: malignant cell states, immune suppression, metabolic stress, and therapeutic resistance are organized into distinct anatomical and functional niches. Spatial omics technologies now enable high-dimensional mapping of gene expression, protein signaling, immune architecture, and metabolic activity within intact tumor tissue. These approaches reveal how proneural and mesenchymal transcriptional states coexist yet localize to distinct regions, alongside hypoxic, invasive, and stem-enriched niches. Spatial analyses show that key clinical determinants, including O6-methylguanine-DNA methyltransferase (MGMT)-associated temozolomide resistance, radiotherapy tolerance in hypoxic regions, and immunotherapy failure driven by myeloid-dominated immune exclusion, are influenced not only by molecular programs but also by cellular location. Beyond biological insight, spatial omics is reshaping clinical paradigms by enabling region-specific patient stratification, early assessment of treatment response, and identification of therapy-resistant reservoirs that seed recurrence. Prior bulk and single-cell studies defined HGG cell states and pathways but often treated resistance as tumor-wide. This review presents a spatially explicit framework that synthesizes spatial transcriptomic and immune-profiling studies to identify tumor-immune niches and spatial bottlenecks that drive therapeutic failure and recurrence.

Humans↗

Evolutionary and resistance dynamics in oligometastatic and oligoprogressive cancer treated with stereotactic radiotherapy and systemic therapies: A systematic review and focused meta-analysis.

BACKGROUND: Oligometastatic and oligoprogressive disease treated with stereotactic ablative radiotherapy (SABR) represents a clinically heterogeneous entity. Increasing evidence suggests that anatomical definitions alone may not adequately capture underlying biological diversity. This systematic review aimed to synthesize translational evidence exploring evolutionary dynamics, resistance mechanisms, and biomarker-driven stratification in patients treated with SABR. METHODS: A systematic literature review was performed including prospective and retrospective studies evaluating translational biomarkers in oligometastatic or oligoprogressive settings treated with SABR. Studies assessing genomic, transcriptomic, circulating or immune-related biomarkers were included. Data were summarized qualitatively according to predefined translational domains: (i) evolutionary dynamics under systemic therapy pressure, (ii) baseline biological stratification, (iii) longitudinal circulating biomarkers, and (iv) systemic immune remodeling. Exploratory quantitative visual syntheses were performed using reported hazard ratios when conceptually comparable endpoints were available. RESULTS: 19 studies comprising 1527 patients were included. Across tumor types and treatment contexts, translational analyses consistently indicated that anatomically defined oligometastatic states encompass biologically distinct subgroups with different risks of systemic progression. Studies evaluating oligoprogression under ongoing systemic therapy suggested a distinction between spatially constrained resistance and systemic molecular escape, supported by circulating tumor DNA and tissue- or plasma-based molecular profiling (including genomic and transcriptomic analyses). Baseline biological features, including adverse genomic signatures and circulating biomarkers, were associated with inferior progression outcomes despite metastasis-directed therapy. Longitudinal biomarkers provided early signals of treatment response and systemic control. Immune remodeling after SABR showed context-dependent effects, both systemic immune activation and treatment-related immunosuppression reported across studies.

Humans↗

HUMESS: integrating quantitative transcriptomic analysis and metabolic modeling to unveil condition-specific gene signatures.

SUMMARY: Transcriptomic analysis is a key tool for exploring gene expression, but the complexity of biological systems often limits its insights. In particular, the lack of intermodal or multi-layered analysis hinders the ability to fully capture key cellular functions such as metabolism from transcriptomic data alone. Here, we introduce a novel approach that informs transcriptomic data analysis with metabolic network modeling to address this. Unlike traditional methods, HUman MEtabolism Specific Signature (HUMESS) uses genome-scale metabolic modeling and flux analysis to highlight reactions and involved genes based on their metabolic significance, offering a deeper understanding of transcriptomic data. Our computational pipeline, supported by a user-friendly Rshiny application, enhances gene expression analysis by uncovering metabolic phenotypic signatures. AVAILABILITY AND IMPLEMENTATION: HUMESS is open source and available under GitLab https://gitlab.univ-nantes.fr/bird_pipeline_registry/humess with the complete documentation available at https://gitlab.univ-nantes.fr/bird_pipeline_registry/humess/-/wikis/Home. A zenodo archive is also available at the following DOI: https://doi.org/10.5281/zenodo.15487717. An RShiny application has been developed to facilitate the exploration and analysis of HUMESS's results. The app is available online at the following address: https://shiny-bird.univ-nantes.fr/app/shinymess but can also be installed locally, available under GitLab https://gitlab.univ-nantes.fr/pare-l/shinymess.

Humans↗

Identifying key palmitoylation-associated genes in endometriosis through genomic data analysis.

BACKGROUND: Palmitoylation, a post-translational lipid modification, has garnered increasing attention for its role in inflammatory processes and tumorigenesis. Emerging evidence suggests a potential association between palmitoylation and inflammatory responses in the pathogenesis of endometriosis. However, the precise mechanistic interplay remains elusive, necessitating further investigation. METHODS: This study integrated transcriptomic analysis and Mendelian randomization (MR) to identify a causal gene set implicated in endometriosis. Differentially expressed genes (DEGs) were first identified in the training dataset using the limma package in R. Weighted gene co-expression network analysis (WGCNA) was subsequently performed, leveraging Single Sample Gene Set Enrichment Analysis (ssGSEA)-derived scores of palmitoylation-related genes (PRGs) as phenotypic traits to identify key modular genes. The intersection of these key modular genes with DEGs yielded a refined gene set. Machine learning algorithms were then applied to further optimize gene selection, followed by external validation, immune infiltration analysis, RNA network construction, and exploration of potential targeted drug candidates. RESULTS: Through a rigorous screening process, VRK1, GALNT12, and RMI1 emerged as key genes associated with palmitoylation, exhibiting significant downregulation in endometriosis samples (P <&#x2009;0.05), indicative of a potential protective role. Immune infiltration analysis further revealed strong correlations between these genes and M2 macrophages as well as resting Natural Killer (NK) cells. Additionally, investigations into the targeted RNA network and drug association profiling provided novel insights, laying the groundwork for future high-quality validation studies. CONCLUSIONS: This study employed a comprehensive analytical framework to identify palmitoylation-associated key genes in endometriosis. The integration of immunoinfiltration analysis, RNA network construction, and drug association profiling offers valuable insights for advancing clinical diagnostics, disease monitoring, and therapeutic development in endometriosis.

Humans↗

The human transcriptome map reveals extremes in gene density, intron length, GC content, and repeat pattern for domains of highly and weakly expressed genes.

The chromosomal gene expression profiles established by the Human Transcriptome Map (HTM) revealed a clustering of highly expressed genes in about 30 domains, called ridges. To physically characterize ridges, we constructed a new HTM based on the draft human genome sequence (HTMseq). Expression of 25,003 genes can be analyzed online in a multitude of tissues (http://bioinfo.amc.uva.nl/HTMseq). Ridges are found to be very gene-dense domains with a high GC content, a high SINE repeat density, and a low LINE repeat density. Genes in ridges have significantly shorter introns than genes outside of ridges. The HTMseq also identifies a significant clustering of weakly expressed genes in domains with fully opposite characteristics (antiridges). Both types of domains are open to tissue-specific expression regulation, but the maximal expression levels in ridges are considerably higher than in antiridges. Ridges are therefore an integral part of a higher order structure in the genome related to transcriptional regulation.

Base Composition↗

Disease-associated expression profiles in peripheral blood mononuclear cells from patients with advanced renal cell carcinoma.

Expression profiling has demonstrated that transcriptomes of primary malignancies differ from those in normal tissue. It is unknown, however, whether there exist "surrogate" transcriptional markers in peripheral blood mononuclear cells (PBMCs) of patients with solid tumors. We identified transcripts expressed differentially between PBMCs from renal cell carcinoma patients and normal subjects, some of which appear to reflect specific immune responses of circulating cells. We also identified small sets of predictor genes distinguishing PBMCs from renal cell carcinoma patients and normal volunteers with high accuracy. The present findings have important implications for diagnosis and future clinical pharmacogenomic studies of antitumor therapies.

Adult↗

Transcriptome sequencing reveals regulatory genes associated with neurogenic hearing loss.

Hearing loss is a prevalent condition with a significant impact on individuals' quality of life. However, comprehensive studies investigating the differential gene expression and regulatory mechanisms associated with hearing loss are lacking, particularly in the context of diverse patient samples. In this study, we integrated data from 10 patients across different regions, age groups, and genders, with their data retrieved from a public transcriptome database, to explore the molecular basis of hearing loss. These samples are mainly from fibroblasts and keratinocytes. Through differential gene expression analysis, we identified key genes, including ICAM1, SLC1A1, and CD24, which have already been shown to play important roles in neurogenic hearing loss. Furthermore, we predicted potential transcriptional regulatory factors that may modulate the expression of these genes. Enrichment analysis revealed biological processes and pathways associated with hearing loss, highlighting the involvement of circadian rhythm disruption and other neuro-related disorders. Although our study is limited by the sample size and the absence of larger-scale investigations, the identified genes and regulatory factors provide valuable insights into the molecular mechanisms underlying hearing loss. Further molecular and cellular experiments are necessary to validate these findings and elucidate the precise regulatory mechanisms involved. In conclusion, our study contributes to the understanding of hearing loss pathogenesis and offers potential targets for molecular diagnostics and gene-based therapies. This provides a foundation for further research into personalized approaches to diagnosing and treating hearing loss.

Humans↗