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Prioritizing Candidate Genes for Type 2 Diabetes Mellitus using Integrated Network and Pathway Analysis
BACKGROUND: Type 2 Diabetes Mellitus (T2DM) has emerged as a major threat to global health that fosters life-threatening clinical complications, taking a huge toll on our society. More than 65 million Indians suffer from T2DM, making it one of the leading causes of death. T2DM and associated complic...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Avicenna Research Institute
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9376990/ https://www.ncbi.nlm.nih.gov/pubmed/36061131 http://dx.doi.org/10.18502/ajmb.v14i3.9831 |
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author | Prakash, Tejaswini Ramachandra, Nallur B |
author_facet | Prakash, Tejaswini Ramachandra, Nallur B |
author_sort | Prakash, Tejaswini |
collection | PubMed |
description | BACKGROUND: Type 2 Diabetes Mellitus (T2DM) has emerged as a major threat to global health that fosters life-threatening clinical complications, taking a huge toll on our society. More than 65 million Indians suffer from T2DM, making it one of the leading causes of death. T2DM and associated complications have to be constantly monitored and managed which reduces the overall quality of life and increases socioeconomic burden. Therefore, it is crucial to develop specific treatment and management strategies. In order to achieve this, it is essential to understand the underlying genetic causes and molecular mechanisms. METHODS: Integrated gene network and ontology analyses facilitate prioritization of plausible candidate genes for T2DM and also aid in understanding their mechanistic pathways. In this study, T2DM-associated genes were subjected to sequential interaction network and gene set enrichment analysis. High ranking network clusters were derived and their interrelation with pathways was assessed. RESULTS: About 23 significant candidate genes were prioritized from 615 T2DM-associated genes which were overrepresented in pathways related to insulin resistance, type 2 diabetes, signaling cascades such as insulin receptor signaling pathway, PI3K signaling, IGFR signaling pathway, ERBB signaling pathway, MAPK signaling pathway and their regulatory mechanisms. CONCLUSION: Of these, two tyrosine kinase receptor genes-EGFR and IGF1R were identified as common nodes and can be considered to be significant candidate genes in T2DM. |
format | Online Article Text |
id | pubmed-9376990 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Avicenna Research Institute |
record_format | MEDLINE/PubMed |
spelling | pubmed-93769902022-09-01 Prioritizing Candidate Genes for Type 2 Diabetes Mellitus using Integrated Network and Pathway Analysis Prakash, Tejaswini Ramachandra, Nallur B Avicenna J Med Biotechnol Original Article BACKGROUND: Type 2 Diabetes Mellitus (T2DM) has emerged as a major threat to global health that fosters life-threatening clinical complications, taking a huge toll on our society. More than 65 million Indians suffer from T2DM, making it one of the leading causes of death. T2DM and associated complications have to be constantly monitored and managed which reduces the overall quality of life and increases socioeconomic burden. Therefore, it is crucial to develop specific treatment and management strategies. In order to achieve this, it is essential to understand the underlying genetic causes and molecular mechanisms. METHODS: Integrated gene network and ontology analyses facilitate prioritization of plausible candidate genes for T2DM and also aid in understanding their mechanistic pathways. In this study, T2DM-associated genes were subjected to sequential interaction network and gene set enrichment analysis. High ranking network clusters were derived and their interrelation with pathways was assessed. RESULTS: About 23 significant candidate genes were prioritized from 615 T2DM-associated genes which were overrepresented in pathways related to insulin resistance, type 2 diabetes, signaling cascades such as insulin receptor signaling pathway, PI3K signaling, IGFR signaling pathway, ERBB signaling pathway, MAPK signaling pathway and their regulatory mechanisms. CONCLUSION: Of these, two tyrosine kinase receptor genes-EGFR and IGF1R were identified as common nodes and can be considered to be significant candidate genes in T2DM. Avicenna Research Institute 2022 /pmc/articles/PMC9376990/ /pubmed/36061131 http://dx.doi.org/10.18502/ajmb.v14i3.9831 Text en Copyright© 2022 Avicenna Research Institute https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) |
spellingShingle | Original Article Prakash, Tejaswini Ramachandra, Nallur B Prioritizing Candidate Genes for Type 2 Diabetes Mellitus using Integrated Network and Pathway Analysis |
title | Prioritizing Candidate Genes for Type 2 Diabetes Mellitus using Integrated Network and Pathway Analysis |
title_full | Prioritizing Candidate Genes for Type 2 Diabetes Mellitus using Integrated Network and Pathway Analysis |
title_fullStr | Prioritizing Candidate Genes for Type 2 Diabetes Mellitus using Integrated Network and Pathway Analysis |
title_full_unstemmed | Prioritizing Candidate Genes for Type 2 Diabetes Mellitus using Integrated Network and Pathway Analysis |
title_short | Prioritizing Candidate Genes for Type 2 Diabetes Mellitus using Integrated Network and Pathway Analysis |
title_sort | prioritizing candidate genes for type 2 diabetes mellitus using integrated network and pathway analysis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9376990/ https://www.ncbi.nlm.nih.gov/pubmed/36061131 http://dx.doi.org/10.18502/ajmb.v14i3.9831 |
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