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MicroRNAs (miRNAs) are non\u2010coding RNAs (ncRNAs) that modulate immune responses and play a pivotal role in the pathogenesis of MTB by altering host immune defences. Insights into the regulatory functions of these miRNAs have revealed mechanisms through which MTB evades immune surveillance and establishes persistent infections, highlighting the critical role of miRNA networks in TB pathogenesis. The purpose of this study was to analyse miRNA expression in plasma from TB patients, to predict target genes, and to construct regulatory networks to elucidate the roles of miRNAs in TB pathogenesis. Plasma samples from three patients with active TB and three healthy controls were analysed using high\u2010throughput small RNA sequencing. DEMs were identified using DESeq2, and target genes were predicted via TargetScan and miRWalk. Protein\u2013protein interaction (PPI) networks were constructed using STRING and Cytoscape. Functional enrichment analyses were performed using Gene Ontology (GO) and KEGG databases. A total of 23 DEMs were identified, including 17 upregulated and 6 downregulated miRNAs. hsa\u2010miR\u201015a\u20105p emerged as the most significantly upregulated miRNA. PPI network analysis highlighted CCND1, CDK6 and CCND2 as central genes, potentially regulated by miR\u201015a\u20105p. GO and KEGG analyses revealed enrichment in pathways related to cell cycle regulation, kinase activity and protein complex formation, suggesting their involvement in TB pathogenesis. This study identifies hsa\u2010miR\u201015a\u20105p and its target genes as key components in the regulatory landscape of TB. These findings offer new insights into the molecular mechanisms of TB and propose potential biomarkers and therapeutic targets for future research.<\/jats:p>","DOI":"10.1111\/jcmm.70567","type":"journal-article","created":{"date-parts":[[2025,5,19]],"date-time":"2025-05-19T13:39:19Z","timestamp":1747661959000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["<scp>miRNA<\/scp> Differential Expression Profile Analysis and Identification of Potential Key Genes in Active Tuberculosis"],"prefix":"10.1111","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-9904-476X","authenticated-orcid":false,"given":"Jun","family":"Yang","sequence":"first","affiliation":[{"name":"Faculty of Applied Sciences Universiti Teknologi MARA  Shah Alam Selangor Malaysia"},{"name":"Department of Laboratory Medicine Guilin Medical University Affiliated Hospital  Guilin Guangxi China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanliang","family":"Dan","sequence":"additional","affiliation":[{"name":"Faculty of Applied Sciences Universiti Teknologi MARA  Shah Alam Selangor Malaysia"},{"name":"Nanxishan Hospital of Guangxi Zhuang Autonomous Region (The Second People's Hospital of Guangxi Zhuang Autonomous Region)  Guilin Guangxi China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yeng","family":"Chen","sequence":"additional","affiliation":[{"name":"Faculty of Dentistry University of Malaiya  Kuala Lumpur Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linrong","family":"Zou","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine Guilin Medical University Affiliated Hospital  Guilin Guangxi China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shanshan","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine Guilin Medical University Affiliated Hospital  Guilin Guangxi China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine Guilin Medical University Affiliated Hospital  Guilin Guangxi China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maslinda Binti","family":"Musa","sequence":"additional","affiliation":[{"name":"Faculty of Applied Sciences Universiti Teknologi MARA  Shah Alam Selangor Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,5,19]]},"reference":[{"key":"e_1_2_12_2_1","volume-title":"WHO's Global Tuberculosis Report 2023","author":"Geneva WHO","year":"2024"},{"key":"e_1_2_12_3_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40249-020-00739-7"},{"issue":"9","key":"e_1_2_12_4_1","article-title":"Forecasting New Tuberculosis Cases in Malaysia: A Time\u2010Series Study Using the Autoregressive Integrated Moving Average (ARIMA) Model","volume":"15","author":"Ab Rashid M. 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