<HashMap><database>biostudies-arrayexpress</database><scores/><additional><submitter>Qi Wu</submitter><organism>Homo sapiens</organism><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/E-MTAB-15843</full_dataset_link><description>This study investigates the molecular mechanisms of hypertrophic cardiomyopathy (HCM), a common genetic heart disease where the link between cardiac remodeling and immune response is not fully understood. We aimed to identify novel diagnostic biomarkers and explore transcriptomic alterations in peripheral blood. To achieve this, bulk RNA-sequencing was performed on blood samples from 4 HCM patients and 3 healthy controls. The resulting data were analyzed using differential expression, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms to identify key genes involved in HCM pathogenesis, with a focus on MEIS3 as a potential immune modulator.</description><repository>biostudies-arrayexpress</repository><sample_protocol>Nucleic Acid Extraction - Total RNA was extracted from whole blood samples using TRIzol reagent. The quality and integrity of the extracted RNA were confirmed using an Agilent Bioanalyzer, ensuring a RIN value greater than 7.</sample_protocol><sample_protocol>Library Construction - Poly-A mRNA was enriched from total RNA for cDNA library construction.</sample_protocol><sample_protocol>Sample Collection - Peripheral blood samples were obtained from 4 patients with obstructive hypertrophic cardiomyopathy (HCM) and 3 healthy donors. Written informed consent was obtained from all participants, and the study protocol was approved by the institutional ethics committee. Whole blood was collected in EDTA tubes.</sample_protocol><sample_protocol>Sequencing - The prepared cDNA libraries were sequenced on an Illumina NovaSeq platform. Sequencing was performed using a 150 bp paired-end read configuration, with a target depth of approximately 50 million reads per sample.</sample_protocol><figure_sub>Organization</figure_sub><figure_sub>MINSEQE Score</figure_sub><figure_sub>Assays and Data</figure_sub><figure_sub>MAGE-TAB Files</figure_sub><omics_type>Unknown</omics_type><omics_type>Transcriptomics</omics_type><omics_type>Genomics</omics_type><omics_type>Proteomics</omics_type><instrument_platform>Not applicable</instrument_platform><instrument_platform>Agilent Bioanalyzer</instrument_platform><instrument_platform>Illumina HiSeq 1000</instrument_platform><pubmed_abstract>&lt;h4>Background&lt;/h4>Hypertrophic cardiomyopathy (HCM) is a prevalent genetic cardiac disorder characterized by myocardial hypertrophy and diastolic dysfunction. While traditionally attributed to sarcomeric mutations, recent studies have highlighted the pivotal contribution of immune dysregulation and stromal-immune interactions in its pathophysiology. However, the molecular drivers bridging structural remodeling and immune activation remain poorly defined.&lt;h4>Objective&lt;/h4>This study aimed to characterize the clinical and immunological role of the transcription factor MEIS3 in HCM through integrative transcriptomic and single-cell analyses, with a focus on its diagnostic potential and regulatory interactions within the cardiac microenvironment.&lt;h4>Methods&lt;/h4>We performed bulk RNA sequencing on peripheral blood samples from clinically diagnosed HCM patients (n = 4) and matched healthy controls (n = 3), followed by differential expression analysis and weighted gene co-expression network analysis (WGCNA). Machine learning algorithms (LASSO and Random Forest) were used to identify key diagnostic genes. Single-cell RNA sequencing (scRNA-seq) from myocardial tissues was used to localize gene expression. The immunological context was evaluated via xCell-based immune deconvolution, cytokine-immune cell correlation analysis, and ceRNA network construction centered on MEIS3.&lt;h4>Results&lt;/h4>MEIS3 was significantly upregulated in HCM samples and identified as a core hub gene in the HCM-associated blue WGCNA module. Machine learning consistently ranked MEIS3 among the top discriminatory markers (AUC > 0.90). scRNA-seq revealed MSCs as the predominant MEIS3-expressing population in HCM myocardium. Functional enrichment implicated MEIS3 in pathways related to protein synthesis, mitochondrial metabolism, and immune modulation. Immune deconvolution indicated increased M1 macrophages, NK cells, and dendritic cells in HCM. MEIS3 expression positively correlated with key immunomodulatory cytokines (CXCL12, BMP1) and altered immune landscapes. The ceRNA network identified candidate lncRNA-miRNA-MEIS3 axes potentially driving its overexpression. Cytokine-immune cell analysis revealed MEIS3-linked cytokines bridging stromal and immune compartments, reinforcing its central role in immunoregulatory remodeling.&lt;h4>Conclusion&lt;/h4>MEIS3 functions as a stromal-centric immunomodulator in HCM, shaping cytokine expression and immune infiltration in the diseased heart. Its expression shows diagnostic potential and may represent a novel target for immuno-modulatory strategies. These findings open new avenues for immuno-targeted interventions in HCM management.</pubmed_abstract><study_type>RNA-seq of coding RNA</study_type><species>Homo sapiens</species><pubmed_title>Integrative Multi-Omics Identifies MEIS3 as a Diagnostic Biomarker and Immune Modulator in Hypertrophic Cardiomyopathy</pubmed_title><pubmed_authors>Qi Wu</pubmed_authors><pubmed_authors>Jinchen He, Zehua Zhou, Dejun Kong, Heng Zhu, Chunmei Liu, Yuyuan Wang, Tianqi Wu, Jinfeng Chen, Yan Liao, Qi Wu1</pubmed_authors></additional><is_claimable>false</is_claimable><name>Transcriptome profiling of peripheral blood from patients with hypertrophic cardiomyopathy (HCM) compared to healthy controls</name><description>This study investigates the molecular mechanisms of hypertrophic cardiomyopathy (HCM), a common genetic heart disease where the link between cardiac remodeling and immune response is not fully understood. We aimed to identify novel diagnostic biomarkers and explore transcriptomic alterations in peripheral blood. To achieve this, bulk RNA-sequencing was performed on blood samples from 4 HCM patients and 3 healthy controls. The resulting data were analyzed using differential expression, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms to identify key genes involved in HCM pathogenesis, with a focus on MEIS3 as a potential immune modulator.</description><dates><release>2025-11-17T00:00:00Z</release><modification>2025-11-17T02:01:45.74Z</modification><creation>2025-10-23T17:09:25.07Z</creation></dates><accession>E-MTAB-15843</accession><cross_references><ENA>ERP182844</ENA><EFO>EFO_0002944</EFO><EFO>EFO_0004170</EFO><EFO>EFO_0005518</EFO><EFO>EFO_0003738</EFO><EFO>EFO_0004184</EFO><doi>10.3389/fimmu.2025.1675467</doi></cross_references></HashMap>