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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Veröffentlicht in:The American heart journal 2022-12, Vol.254, p.244-245
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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.
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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. 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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. 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source ScienceDirect Journals (5 years ago - present); ProQuest Central UK/Ireland
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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