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Proteomic Analysis in Diabetic Cardiomyopathy using Bioinformatics Approach
Diabetic cardiomyopathy is a distinct clinical entity that produces asymptomatic heart failure in diabetic patients without evidence of coronary artery disease and hypertension. Abnormalities in diabetic cardiomyopathy include: myocardial hypertrophy, impairment of contractile proteins, accumulation...
Autores principales: | , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Libertas Academica
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2735956/ https://www.ncbi.nlm.nih.gov/pubmed/19812762 |
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author | Rao, Allam Appa Thota, Hanuman Adapala, Ramamurthy Changalasetty, Suresh Babu Gumpeny, Ramachandra Sridhar Akula, Annapurna Thota, Lalitha Saroja Challa, Siva Reddy Rao, M.R. Narasinga Das, Undurti N. |
author_facet | Rao, Allam Appa Thota, Hanuman Adapala, Ramamurthy Changalasetty, Suresh Babu Gumpeny, Ramachandra Sridhar Akula, Annapurna Thota, Lalitha Saroja Challa, Siva Reddy Rao, M.R. Narasinga Das, Undurti N. |
author_sort | Rao, Allam Appa |
collection | PubMed |
description | Diabetic cardiomyopathy is a distinct clinical entity that produces asymptomatic heart failure in diabetic patients without evidence of coronary artery disease and hypertension. Abnormalities in diabetic cardiomyopathy include: myocardial hypertrophy, impairment of contractile proteins, accumulation of extracellular matrix proteins, formation of advanced glycation end products, and decreased left ventricular compliance. These abnormalities lead to the most common clinical presentation of diabetic cardiomyopathy in the form of diastolic dysfunction. We evaluated the role of various proteins that are likely to be involved in diabetic cardiomyopathy by employing multiple sequence alignment using ClustalW tool and constructed a Phylogenetic tree using functional protein sequences extracted from NCBI. Phylogenetic tree was constructed using Neighbour—Joining Algorithm in bioinformatics approach. These results suggest a causal relationship between altered calcium homeostasis and diabetic cardiomyopathy that implies that efforts directed to normalize calcium homeostasis could form a novel therapeutic approach. |
format | Text |
id | pubmed-2735956 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Libertas Academica |
record_format | MEDLINE/PubMed |
spelling | pubmed-27359562009-09-14 Proteomic Analysis in Diabetic Cardiomyopathy using Bioinformatics Approach Rao, Allam Appa Thota, Hanuman Adapala, Ramamurthy Changalasetty, Suresh Babu Gumpeny, Ramachandra Sridhar Akula, Annapurna Thota, Lalitha Saroja Challa, Siva Reddy Rao, M.R. Narasinga Das, Undurti N. Bioinform Biol Insights Original Research Diabetic cardiomyopathy is a distinct clinical entity that produces asymptomatic heart failure in diabetic patients without evidence of coronary artery disease and hypertension. Abnormalities in diabetic cardiomyopathy include: myocardial hypertrophy, impairment of contractile proteins, accumulation of extracellular matrix proteins, formation of advanced glycation end products, and decreased left ventricular compliance. These abnormalities lead to the most common clinical presentation of diabetic cardiomyopathy in the form of diastolic dysfunction. We evaluated the role of various proteins that are likely to be involved in diabetic cardiomyopathy by employing multiple sequence alignment using ClustalW tool and constructed a Phylogenetic tree using functional protein sequences extracted from NCBI. Phylogenetic tree was constructed using Neighbour—Joining Algorithm in bioinformatics approach. These results suggest a causal relationship between altered calcium homeostasis and diabetic cardiomyopathy that implies that efforts directed to normalize calcium homeostasis could form a novel therapeutic approach. Libertas Academica 2008-01-21 /pmc/articles/PMC2735956/ /pubmed/19812762 Text en Copyright © 2008 The authors. http://creativecommons.org/licenses/by/3.0 This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Original Research Rao, Allam Appa Thota, Hanuman Adapala, Ramamurthy Changalasetty, Suresh Babu Gumpeny, Ramachandra Sridhar Akula, Annapurna Thota, Lalitha Saroja Challa, Siva Reddy Rao, M.R. Narasinga Das, Undurti N. Proteomic Analysis in Diabetic Cardiomyopathy using Bioinformatics Approach |
title | Proteomic Analysis in Diabetic Cardiomyopathy using Bioinformatics Approach |
title_full | Proteomic Analysis in Diabetic Cardiomyopathy using Bioinformatics Approach |
title_fullStr | Proteomic Analysis in Diabetic Cardiomyopathy using Bioinformatics Approach |
title_full_unstemmed | Proteomic Analysis in Diabetic Cardiomyopathy using Bioinformatics Approach |
title_short | Proteomic Analysis in Diabetic Cardiomyopathy using Bioinformatics Approach |
title_sort | proteomic analysis in diabetic cardiomyopathy using bioinformatics approach |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2735956/ https://www.ncbi.nlm.nih.gov/pubmed/19812762 |
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