Identification of candidate biomarkers and signaling pathways associated with Alzheimer's disease using bioinformatics analysis of next generation sequencing data and molecular docking studies

Identification of candidate biomarkers and signaling pathways associated with Alzheimer's disease using bioinformatics analysis of next generation sequencing data and molecular docking studies | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Identification of candidate biomarkers and signaling pathways associated with Alzheimer's disease using bioinformatics analysis of next generation sequencing data and molecular docking studies Basavaraj Mallikarjunayya Vastrad, Shivaling Pattanashetti, Chanabasayya Vastrad This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7857157/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Alzheimer's disease (AD) is the most common cause of dementia, and one of the most common health problems all over the world. However, the molecular mechanisms of AD remain incompletely understood. The current investigation aimed to elucidate potential key candidate genes and signaling pathways in AD. Next generation sequencing (NGS) dataset GSE203206 was downloaded from the Gene Expression Omnibus (GEO) database, which included data from 39 AD samples and 8 normal control samples. Differentially expressed genes (DEGs) were identified using t-tests in the limma R bioconductor package. DEGs were subsequently investigated by Gene ontology (GO) and pathway enrichment analysis, and a protein-protein interaction (PPI) network and modules were constructed and analyzed. The miRNA-hub gene regulatory network, TF-hub gene regulatory network and drug-hub gene interaction network construction analysis were performed to predict key microRNAs (miRNAs), transcription factors (TFs) and small drug molecules. The receiver operating characteristic (ROC) curve analysis was performed to estimate the clinical diagnostic value of the hub genes. Conduct molecular docking with hub genes and corresponding active molecules. A total of 958 DEGs, including 479 up regulated genes and 479 down regulated genes were screened between AD and normal control samples. GO and pathway enrichment analysis results revealed that the up regulated genes were mainly enriched in response to stimulus, cytoplasm, small molecule binding and signal transduction, whereas down regulated genes were mainly enriched in multicellular organism development, cell junction, ion binding and cardiac conduction. The PPI network contained 4886 nodes and 10342 edges. HSP90AA1, FN1, KIT, YAP1, LSM2, SKP1, EIF5A2, TAF9, DDX39B and CDK7 were identified as the top hub genes. The regulatory network analysis revealed that miRNAs include hsa-mir-545-3p and hsa-miR-548f-5p, and TFs include PLAG1 and MEF2A might be involved in the development of AD. Drug molecules were predicted including Sulindac, Infliximab, Norfloxacin and Gemcitabine for treatment of AD. Molecular docking analysis revealed that Isocryptomerin and Macrophylloside D were the main active compounds with good binding activities to the HSP90AA1 and FN1. These findings provide new insights into the pathogenesis of AD. The hub genes, miRNAs and TFs have the potential to be used as diagnostic and therapeutic markers. Bioinformatics Medical Genetics Drug Discovery, Design, & Development Alzheimer's disease GEO bioinformatics biomarker protein-protein interaction molecular docking Full Text Additional Declarations The authors declare no competing interests. Supplementary Files SupplementaryTableS1.docx SupplementaryTableS2.docx SupplementaryTableS3.docx SupplementaryTableS4.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7857157","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":529380604,"identity":"c05725cd-1be0-4345-bad6-842145fa1b17","order_by":0,"name":"Basavaraj Mallikarjunayya Vastrad","email":"","orcid":"https://orcid.org/0000-0003-2202-7637","institution":"Department of Pharmaceutical Chemistry, K.L.E. 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However, the molecular mechanisms of AD remain incompletely understood. The current investigation aimed to elucidate potential key candidate genes and signaling pathways in AD. Next generation sequencing (NGS) dataset GSE203206 was downloaded from the Gene Expression Omnibus (GEO) database, which included data from 39 AD samples and 8 normal control samples. Differentially expressed genes (DEGs) were identified using t-tests in the limma R bioconductor package. DEGs were subsequently investigated by Gene ontology (GO) and pathway enrichment analysis, and a protein-protein interaction (PPI) network and modules were constructed and analyzed. The miRNA-hub gene regulatory network, TF-hub gene regulatory network and drug-hub gene interaction network construction analysis were performed to predict key microRNAs (miRNAs), transcription factors (TFs) and small drug molecules. The receiver operating characteristic (ROC) curve analysis was performed to estimate the clinical diagnostic value of the hub genes. Conduct molecular docking with hub genes and corresponding active molecules. A total of 958 DEGs, including 479 up regulated genes and 479 down regulated genes were screened between AD and normal control samples. GO and pathway enrichment analysis results revealed that the up regulated genes were mainly enriched in response to stimulus, cytoplasm, small molecule binding and signal transduction, whereas down regulated genes were mainly enriched in multicellular organism development, cell junction, ion binding and cardiac conduction. The PPI network contained 4886 nodes and 10342 edges. HSP90AA1, FN1, KIT, YAP1, LSM2, SKP1, EIF5A2, TAF9, DDX39B and CDK7 were identified as the top hub genes. The regulatory network analysis revealed that miRNAs include hsa-mir-545-3p and hsa-miR-548f-5p, and \u0026nbsp;TFs include PLAG1 and MEF2A might be involved in the development of AD. Drug molecules were predicted including Sulindac, Infliximab, Norfloxacin and Gemcitabine for treatment of AD. Molecular docking analysis revealed that Isocryptomerin and Macrophylloside D were the main active compounds with good binding activities to the HSP90AA1 and FN1. These findings provide new insights into the pathogenesis of AD. 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