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Bioinformatics and System Biology Techniques to Determine Biomolecular Signatures and Pathways of Prion Disorder
Prion disorder (PD) is caused by misfolding and the formation of clumps of proteins in the brain, notably Prion proteins resulting in a steady decrease in brain function. Early detection of PD is difficult due to its unpredictable nature, and diagnosis is limited regarding specificity and sensitivit...
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Published in: | Bioinformatics and biology insights 2022-01, Vol.16, p.11779322221145373 |
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description | Prion disorder (PD) is caused by misfolding and the formation of clumps of proteins in the brain, notably Prion proteins resulting in a steady decrease in brain function. Early detection of PD is difficult due to its unpredictable nature, and diagnosis is limited regarding specificity and sensitivity. Considering the uncertainties, the current study used network-based integrative system biology approaches to reveal promising molecular biomarkers and therapeutic targets for PD. In this study, brain transcriptomics gene expression microarray datasets (GSE160208 and GSE124571) of human PD were evaluated and 35 differentially expressed genes (DEGs) were identified. By employing network-based protein–protein interaction (PPI) analysis on these DEGs, 10 central hub proteins, including SPP1, FKBP5, HPRT1, CDKN1A, BAG3, HSPB1, SYK, TNFRSF1A, PTPN6, and CD44, were identified. Employing bioinformatics approaches, a variety of transcription factors (EGR1, SSRP1, POLR2A, TARDP, and NR2F1) and miRNAs (hsa-mir-8485, hsa-mir-148b-3p, hsa-mir-4295, hsa-mir-26b-5p, and hsa-mir-16-5p) were predicted. EGR1 was found as the most imperative transcription factor (TF), and hsa-mir-16-5p and hsa-mir-148b-3p were found as the most crucial miRNAs targeted in PD. Finally, resveratrol and hypochlorous acid were predicted as possible therapeutic drugs for PD. This study could be helpful in better understanding of molecular systems and prospective pharmacological targets for developing effective PD treatments. |
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Early detection of PD is difficult due to its unpredictable nature, and diagnosis is limited regarding specificity and sensitivity. Considering the uncertainties, the current study used network-based integrative system biology approaches to reveal promising molecular biomarkers and therapeutic targets for PD. In this study, brain transcriptomics gene expression microarray datasets (GSE160208 and GSE124571) of human PD were evaluated and 35 differentially expressed genes (DEGs) were identified. By employing network-based protein–protein interaction (PPI) analysis on these DEGs, 10 central hub proteins, including SPP1, FKBP5, HPRT1, CDKN1A, BAG3, HSPB1, SYK, TNFRSF1A, PTPN6, and CD44, were identified. Employing bioinformatics approaches, a variety of transcription factors (EGR1, SSRP1, POLR2A, TARDP, and NR2F1) and miRNAs (hsa-mir-8485, hsa-mir-148b-3p, hsa-mir-4295, hsa-mir-26b-5p, and hsa-mir-16-5p) were predicted. EGR1 was found as the most imperative transcription factor (TF), and hsa-mir-16-5p and hsa-mir-148b-3p were found as the most crucial miRNAs targeted in PD. Finally, resveratrol and hypochlorous acid were predicted as possible therapeutic drugs for PD. This study could be helpful in better understanding of molecular systems and prospective pharmacological targets for developing effective PD treatments.</description><identifier>ISSN: 1177-9322</identifier><identifier>EISSN: 1177-9322</identifier><identifier>DOI: 10.1177/11779322221145373</identifier><identifier>PMID: 36582393</identifier><language>eng</language><publisher>London, England: SAGE Publications</publisher><subject>Bioinformatics ; Biology ; Biomarkers ; Brain ; CD44 antigen ; Clumps ; DNA microarrays ; Drug development ; EGR-1 protein ; Gene expression ; Hypochlorous acid ; Original ; Proteins ; Resveratrol ; Syk protein ; System effectiveness ; Therapeutic targets ; Transcription factors ; Transcriptomics</subject><ispartof>Bioinformatics and biology insights, 2022-01, Vol.16, p.11779322221145373</ispartof><rights>The Author(s) 2022</rights><rights>The Author(s) 2022.</rights><rights>The Author(s) 2022. This work is licensed under the Creative Commons Attribution – Non-Commercial License https://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2022 2022 SAGE Publications Ltd unless otherwise noted. Manuscript content on this site is licensed under Creative Commons Licenses</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c532t-ff241d60053e9288df23483e9789554598cfebb7bb231708aa96646f58b92b7a3</citedby><cites>FETCH-LOGICAL-c532t-ff241d60053e9288df23483e9789554598cfebb7bb231708aa96646f58b92b7a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9793038/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2768128335?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,21966,25753,27853,27924,27925,37012,37013,44590,44945,45333,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36582393$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Mredul, Md Bazlur Rahman</creatorcontrib><creatorcontrib>Khan, Umama</creatorcontrib><creatorcontrib>Rana, Humayan Kabir</creatorcontrib><creatorcontrib>Meem, Tahera Mahnaz</creatorcontrib><creatorcontrib>Awal, Md Abdul</creatorcontrib><creatorcontrib>Rahman, Md Habibur</creatorcontrib><creatorcontrib>Khan, Md Salauddin</creatorcontrib><title>Bioinformatics and System Biology Techniques to Determine Biomolecular Signatures and Pathways of Prion Disorder</title><title>Bioinformatics and biology insights</title><addtitle>Bioinform Biol Insights</addtitle><description>Prion disorder (PD) is caused by misfolding and the formation of clumps of proteins in the brain, notably Prion proteins resulting in a steady decrease in brain function. Early detection of PD is difficult due to its unpredictable nature, and diagnosis is limited regarding specificity and sensitivity. Considering the uncertainties, the current study used network-based integrative system biology approaches to reveal promising molecular biomarkers and therapeutic targets for PD. In this study, brain transcriptomics gene expression microarray datasets (GSE160208 and GSE124571) of human PD were evaluated and 35 differentially expressed genes (DEGs) were identified. By employing network-based protein–protein interaction (PPI) analysis on these DEGs, 10 central hub proteins, including SPP1, FKBP5, HPRT1, CDKN1A, BAG3, HSPB1, SYK, TNFRSF1A, PTPN6, and CD44, were identified. Employing bioinformatics approaches, a variety of transcription factors (EGR1, SSRP1, POLR2A, TARDP, and NR2F1) and miRNAs (hsa-mir-8485, hsa-mir-148b-3p, hsa-mir-4295, hsa-mir-26b-5p, and hsa-mir-16-5p) were predicted. EGR1 was found as the most imperative transcription factor (TF), and hsa-mir-16-5p and hsa-mir-148b-3p were found as the most crucial miRNAs targeted in PD. Finally, resveratrol and hypochlorous acid were predicted as possible therapeutic drugs for PD. This study could be helpful in better understanding of molecular systems and prospective pharmacological targets for developing effective PD treatments.</description><subject>Bioinformatics</subject><subject>Biology</subject><subject>Biomarkers</subject><subject>Brain</subject><subject>CD44 antigen</subject><subject>Clumps</subject><subject>DNA microarrays</subject><subject>Drug development</subject><subject>EGR-1 protein</subject><subject>Gene expression</subject><subject>Hypochlorous acid</subject><subject>Original</subject><subject>Proteins</subject><subject>Resveratrol</subject><subject>Syk protein</subject><subject>System effectiveness</subject><subject>Therapeutic targets</subject><subject>Transcription factors</subject><subject>Transcriptomics</subject><issn>1177-9322</issn><issn>1177-9322</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>AFRWT</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNp1kktv1DAQxyNERR_wAbggS1y4bPEjju0LEn0AlSpRqeVs2ckk61ViL3ZCtd--DimlLcIHezTzn589My6KtwQfEyLEx3lTjOZFSMmZYC-Kg9m3mp0vH9n7xWFKG4wrIkX1qthnFZeUKXZQbE9ccL4NcTCjqxMyvkHXuzTCgHKkD90O3UC99u7nBAmNAZ3BCHFwHub4EHqop95EdO06b8YpwoK4MuP61uwSCi26ii54dOZSiA3E18Vea_oEb-7Po-LHl_Ob02-ry-9fL04_X65qzui4altakqbCmDNQVMqmpayU2RZScV5yJesWrBXWUkYElsaoqiqrlkurqBWGHRUXC7cJZqO30Q0m7nQwTv92hNhpE3PJPWiwItMbWjJWl2AbY7GwJcGYMiyhYpn1aWFtJztAU4Mfo-mfQJ9GvFvrLvzSKo8HM5kBH-4BMcyNHPXgUg19bzyEKWkquFJcMFxm6ftn0k2Yos-tyqpKEioZ41lFFlUdQ0oR2ofHEKznset__kbOefe4ioeMP58hC44XQTId_L32_8Q7IavB9w</recordid><startdate>20220101</startdate><enddate>20220101</enddate><creator>Mredul, Md Bazlur Rahman</creator><creator>Khan, Umama</creator><creator>Rana, Humayan Kabir</creator><creator>Meem, Tahera Mahnaz</creator><creator>Awal, Md Abdul</creator><creator>Rahman, Md Habibur</creator><creator>Khan, Md Salauddin</creator><general>SAGE Publications</general><general>Sage Publications Ltd</general><general>SAGE Publishing</general><scope>AFRWT</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QO</scope><scope>7XB</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AYAGU</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>LK8</scope><scope>M0N</scope><scope>M7P</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20220101</creationdate><title>Bioinformatics and System Biology Techniques to Determine Biomolecular Signatures and Pathways of Prion Disorder</title><author>Mredul, Md Bazlur Rahman ; 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Early detection of PD is difficult due to its unpredictable nature, and diagnosis is limited regarding specificity and sensitivity. Considering the uncertainties, the current study used network-based integrative system biology approaches to reveal promising molecular biomarkers and therapeutic targets for PD. In this study, brain transcriptomics gene expression microarray datasets (GSE160208 and GSE124571) of human PD were evaluated and 35 differentially expressed genes (DEGs) were identified. By employing network-based protein–protein interaction (PPI) analysis on these DEGs, 10 central hub proteins, including SPP1, FKBP5, HPRT1, CDKN1A, BAG3, HSPB1, SYK, TNFRSF1A, PTPN6, and CD44, were identified. Employing bioinformatics approaches, a variety of transcription factors (EGR1, SSRP1, POLR2A, TARDP, and NR2F1) and miRNAs (hsa-mir-8485, hsa-mir-148b-3p, hsa-mir-4295, hsa-mir-26b-5p, and hsa-mir-16-5p) were predicted. EGR1 was found as the most imperative transcription factor (TF), and hsa-mir-16-5p and hsa-mir-148b-3p were found as the most crucial miRNAs targeted in PD. Finally, resveratrol and hypochlorous acid were predicted as possible therapeutic drugs for PD. This study could be helpful in better understanding of molecular systems and prospective pharmacological targets for developing effective PD treatments.</abstract><cop>London, England</cop><pub>SAGE Publications</pub><pmid>36582393</pmid><doi>10.1177/11779322221145373</doi><oa>free_for_read</oa></addata></record> |
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subjects | Bioinformatics Biology Biomarkers Brain CD44 antigen Clumps DNA microarrays Drug development EGR-1 protein Gene expression Hypochlorous acid Original Proteins Resveratrol Syk protein System effectiveness Therapeutic targets Transcription factors Transcriptomics |
title | Bioinformatics and System Biology Techniques to Determine Biomolecular Signatures and Pathways of Prion Disorder |
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