In-Silico Profiling of Mirnas Against Type 2 Diabetes Mellitus and Myocardial Infarction Associated Genes
In-silico profiling of miRNAs against type 2 diabetes mellitus and myocardial infarction associated genes Khadam Hussain, Muhammad Yousaf, Iram Murtaza Signal Transduction Laboratory, Department of Biochemistry, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad 45320, Pakistan Abstr...
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description | In-silico profiling of miRNAs against type 2 diabetes mellitus and myocardial infarction associated genes Khadam Hussain, Muhammad Yousaf, Iram Murtaza Signal Transduction Laboratory, Department of Biochemistry, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad 45320, Pakistan Abstract Type 2 diabetes mellitus (T2DM) and myocardial infarction (MI) are among top ten leading cause of death, worldwide. miRNA based therapeutic approach may prove an icebreaker to overcome the life-threatening complications of MI and T2DM. Mature miRNAs are endogenous single stranded, non-coding, comprised 20 to 22 nucleotides long sequence which involved in gene silencing at post transcriptional level. It has reported that T2DM affected individuals have more chance to develop MI. Therefore, a single therapeutic approach is required to regulate the common underlying molecular pathways. For this, we found T2DM and MI associated genes by using genetic testing registry (GTR) of national center of biotechnology information (NCBI). To further validate the genes data, we did gene enrichment analysis via ShinyGO database. In order to predict targeted miRNAs (8-mer and species conserved) we used TargetScan, miRWalk and miRBase tools. Data analysis shows that T2DM and MI linked genes have some common targeted miRNAs like miR-128-3p /27-3p/ 181-5p/ 132-3p/ 212-3p/ 30-5p/ 101-3p.1/ 101-3p.2/ 9-5p/ 142-3p.1/ 15-5p/ 16-5p/ 195-5p/ 424-5p/ 497-5p/ 155-5p/ 124-3p.1/ 124-3p.2/ 506-3p that may play a putative role to design a most effective therapeutic strategy. Another set of miRNAs like miR-1-3p/ 206/ 27-3p/ 181-5p/ 7-5p and miR-144-3p/ 135-5p/ 142-3p.2 have selected for T2DM and MI respectively that can target more than one gene in each pathological condition. Taken together, our findings suggest most appropriate miRNAs selection for designing better therapeutic strategy against T2DM linked MI. To check the potential of each miRNA against T2DM and MI, more investigation is needed. |
doi_str_mv | 10.1016/j.ahj.2022.10.035 |
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Mature miRNAs are endogenous single stranded, non-coding, comprised 20 to 22 nucleotides long sequence which involved in gene silencing at post transcriptional level. It has reported that T2DM affected individuals have more chance to develop MI. Therefore, a single therapeutic approach is required to regulate the common underlying molecular pathways. For this, we found T2DM and MI associated genes by using genetic testing registry (GTR) of national center of biotechnology information (NCBI). To further validate the genes data, we did gene enrichment analysis via ShinyGO database. In order to predict targeted miRNAs (8-mer and species conserved) we used TargetScan, miRWalk and miRBase tools. Data analysis shows that T2DM and MI linked genes have some common targeted miRNAs like miR-128-3p /27-3p/ 181-5p/ 132-3p/ 212-3p/ 30-5p/ 101-3p.1/ 101-3p.2/ 9-5p/ 142-3p.1/ 15-5p/ 16-5p/ 195-5p/ 424-5p/ 497-5p/ 155-5p/ 124-3p.1/ 124-3p.2/ 506-3p that may play a putative role to design a most effective therapeutic strategy. Another set of miRNAs like miR-1-3p/ 206/ 27-3p/ 181-5p/ 7-5p and miR-144-3p/ 135-5p/ 142-3p.2 have selected for T2DM and MI respectively that can target more than one gene in each pathological condition. Taken together, our findings suggest most appropriate miRNAs selection for designing better therapeutic strategy against T2DM linked MI. To check the potential of each miRNA against T2DM and MI, more investigation is needed.</description><identifier>ISSN: 0002-8703</identifier><identifier>EISSN: 1097-6744</identifier><identifier>DOI: 10.1016/j.ahj.2022.10.035</identifier><language>eng</language><publisher>Philadelphia: Elsevier Inc</publisher><subject>Biotechnology ; Complications ; Data analysis ; Diabetes ; Diabetes mellitus ; Diabetes mellitus (non-insulin dependent) ; Gene silencing ; Genes ; Genetic screening ; Heart attacks ; Icebreakers ; miRNA ; Myocardial infarction ; Nucleotide sequence ; Nucleotides ; Signal transduction</subject><ispartof>The American heart journal, 2022-12, Vol.254, p.244-245</ispartof><rights>2022</rights><rights>Copyright Elsevier Limited Dec 2022</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2746998318?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995,64385,64389,72469</link.rule.ids></links><search><creatorcontrib>Hussain, Khadam</creatorcontrib><creatorcontrib>Yousaf, Muhammad</creatorcontrib><creatorcontrib>Murtaza, Iram</creatorcontrib><title>In-Silico Profiling of Mirnas Against Type 2 Diabetes Mellitus and Myocardial Infarction Associated Genes</title><title>The American heart journal</title><description>In-silico profiling of miRNAs against type 2 diabetes mellitus and myocardial infarction associated genes Khadam Hussain, Muhammad Yousaf, Iram Murtaza Signal Transduction Laboratory, Department of Biochemistry, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad 45320, Pakistan Abstract Type 2 diabetes mellitus (T2DM) and myocardial infarction (MI) are among top ten leading cause of death, worldwide. miRNA based therapeutic approach may prove an icebreaker to overcome the life-threatening complications of MI and T2DM. Mature miRNAs are endogenous single stranded, non-coding, comprised 20 to 22 nucleotides long sequence which involved in gene silencing at post transcriptional level. It has reported that T2DM affected individuals have more chance to develop MI. Therefore, a single therapeutic approach is required to regulate the common underlying molecular pathways. For this, we found T2DM and MI associated genes by using genetic testing registry (GTR) of national center of biotechnology information (NCBI). To further validate the genes data, we did gene enrichment analysis via ShinyGO database. In order to predict targeted miRNAs (8-mer and species conserved) we used TargetScan, miRWalk and miRBase tools. Data analysis shows that T2DM and MI linked genes have some common targeted miRNAs like miR-128-3p /27-3p/ 181-5p/ 132-3p/ 212-3p/ 30-5p/ 101-3p.1/ 101-3p.2/ 9-5p/ 142-3p.1/ 15-5p/ 16-5p/ 195-5p/ 424-5p/ 497-5p/ 155-5p/ 124-3p.1/ 124-3p.2/ 506-3p that may play a putative role to design a most effective therapeutic strategy. Another set of miRNAs like miR-1-3p/ 206/ 27-3p/ 181-5p/ 7-5p and miR-144-3p/ 135-5p/ 142-3p.2 have selected for T2DM and MI respectively that can target more than one gene in each pathological condition. Taken together, our findings suggest most appropriate miRNAs selection for designing better therapeutic strategy against T2DM linked MI. To check the potential of each miRNA against T2DM and MI, more investigation is needed.</description><subject>Biotechnology</subject><subject>Complications</subject><subject>Data analysis</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>Diabetes mellitus (non-insulin dependent)</subject><subject>Gene silencing</subject><subject>Genes</subject><subject>Genetic screening</subject><subject>Heart attacks</subject><subject>Icebreakers</subject><subject>miRNA</subject><subject>Myocardial infarction</subject><subject>Nucleotide sequence</subject><subject>Nucleotides</subject><subject>Signal transduction</subject><issn>0002-8703</issn><issn>1097-6744</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9kE9LAzEQxYMoWKsfwFvA865J9l-Cp1K1FloUrOeQTWZrljWpyVbotzelnj3NvOG9YeaH0C0lOSW0vu9z9dnnjDCWdE6K6gxNKBFNVjdleY4mhBCW8YYUl-gqxj7JmvF6guzSZe92sNrjt-C71Lkt9h1e2-BUxLOtsi6OeHPYAWb40aoWRoh4DcNgx33Eyhm8PnitgrFqwEvXqaBH6x2exei1VSMYvAAH8RpddGqIcPNXp-jj-Wkzf8lWr4vlfLbKNGWMZ6IpBWlJDaArokkrCHSUl0ypkrG25UYZ4HVDDdWCg1aN4B3VhaFQVqJuqmKK7k57d8F_7yGOsvf79MwQJWvKWgheUJ5c9OTSwccYoJO7YL9UOEhK5JGo7GUiKo9Ej6NENGUeThlI5_9YCDJqC06DsQH0KI23_6R_AXyzfdw</recordid><startdate>202212</startdate><enddate>202212</enddate><creator>Hussain, Khadam</creator><creator>Yousaf, Muhammad</creator><creator>Murtaza, Iram</creator><general>Elsevier Inc</general><general>Elsevier Limited</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QO</scope><scope>7RV</scope><scope>7TS</scope><scope>7X7</scope><scope>7XB</scope><scope>88C</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AN0</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>M2O</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope></search><sort><creationdate>202212</creationdate><title>In-Silico Profiling of Mirnas Against Type 2 Diabetes Mellitus and Myocardial Infarction Associated Genes</title><author>Hussain, Khadam ; 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Mature miRNAs are endogenous single stranded, non-coding, comprised 20 to 22 nucleotides long sequence which involved in gene silencing at post transcriptional level. It has reported that T2DM affected individuals have more chance to develop MI. Therefore, a single therapeutic approach is required to regulate the common underlying molecular pathways. For this, we found T2DM and MI associated genes by using genetic testing registry (GTR) of national center of biotechnology information (NCBI). To further validate the genes data, we did gene enrichment analysis via ShinyGO database. In order to predict targeted miRNAs (8-mer and species conserved) we used TargetScan, miRWalk and miRBase tools. Data analysis shows that T2DM and MI linked genes have some common targeted miRNAs like miR-128-3p /27-3p/ 181-5p/ 132-3p/ 212-3p/ 30-5p/ 101-3p.1/ 101-3p.2/ 9-5p/ 142-3p.1/ 15-5p/ 16-5p/ 195-5p/ 424-5p/ 497-5p/ 155-5p/ 124-3p.1/ 124-3p.2/ 506-3p that may play a putative role to design a most effective therapeutic strategy. Another set of miRNAs like miR-1-3p/ 206/ 27-3p/ 181-5p/ 7-5p and miR-144-3p/ 135-5p/ 142-3p.2 have selected for T2DM and MI respectively that can target more than one gene in each pathological condition. Taken together, our findings suggest most appropriate miRNAs selection for designing better therapeutic strategy against T2DM linked MI. To check the potential of each miRNA against T2DM and MI, more investigation is needed.</abstract><cop>Philadelphia</cop><pub>Elsevier Inc</pub><doi>10.1016/j.ahj.2022.10.035</doi><tpages>2</tpages></addata></record> |
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subjects | Biotechnology Complications Data analysis Diabetes Diabetes mellitus Diabetes mellitus (non-insulin dependent) Gene silencing Genes Genetic screening Heart attacks Icebreakers miRNA Myocardial infarction Nucleotide sequence Nucleotides Signal transduction |
title | In-Silico Profiling of Mirnas Against Type 2 Diabetes Mellitus and Myocardial Infarction Associated Genes |
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