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access icon openaccess Network-based computational approach to identify genetic links between cardiomyopathy and its risk factors

  • Author(s): Md. Nasim Haidar 1 ; M. Babul Islam 1 ; Utpala Nanda Chowdhury 2 ; Md. Rezanur Rahman 3 ; Fazlul Huq 4 ; Julian M.W. Quinn 5 ; Mohammad Ali Moni 4, 5
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  • Source: Volume 14, Issue 2, April 2020, p. 75 – 84
    DOI:  10.1049/iet-syb.2019.0074 , Print ISSN 1751-8849, Online ISSN 1751-8857
This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Received 11/07/2019, Accepted 21/10/2019, Revised 23/09/2019, Published 31/10/2019

Cardiomyopathy (CMP) is a group of myocardial diseases that progressively impair cardiac function. The mechanisms underlying CMP development are poorly understood, but lifestyle factors are clearly implicated as risk factors. This study aimed to identify molecular biomarkers involved in inflammatory CMP development and progression using a systems biology approach. The authors analysed microarray gene expression datasets from CMP and tissues affected by risk factors including smoking, ageing factors, high body fat, clinical depression status, insulin resistance, high dietary red meat intake, chronic alcohol consumption, obesity, high-calorie diet and high-fat diet. The authors identified differentially expressed genes (DEGs) from each dataset and compared those from CMP and risk factor datasets to identify common DEGs. Gene set enrichment analyses identified metabolic and signalling pathways, including MAPK, RAS signalling and cardiomyopathy pathways. Protein–protein interaction (PPI) network analysis identified protein subnetworks and ten hub proteins (CDK2, ATM, CDT1, NCOR2, HIST1H4A, HIST1H4B, HIST1H4C, HIST1H4D, HIST1H4E and HIST1H4L). Five transcription factors (FOXC1, GATA2, FOXL1, YY1, CREB1) and five miRNAs were also identified in CMP. Thus the authors’ approach reveals candidate biomarkers that may enhance understanding of mechanisms underlying CMP and their link to risk factors. Such biomarkers may also be useful to develop new therapeutics for CMP.

Inspec keywords: diseases; cellular biophysics; medical disorders; molecular biophysics; RNA; biology computing; genetics; genomics; biochemistry; proteins; neurophysiology; bioinformatics; data analysis

Other keywords: high-calorie diet; HIST1H4C; managing CMP; risk factor datasets; risk factors including smoking; FOXC1; clinical depression status; differentially expressed genes; network-based computational approach; cardiomyopathy; HIST1H4D; important risk factors; authors; transcription factors; high-fat diet; inflammatory CMP development; FOXL1; systems biology approach; high dietary red meat intake; YY1; microarray gene expression datasets; protein–protein interaction network analysis identified protein subnetworks; CREB1; CDT1; ageing factors; lifestyle factors

Subjects: Knowledge engineering techniques; Physics of subcellular structures; Data handling techniques; Biology and medical computing; Patient diagnostic methods and instrumentation; Biomedical engineering; Physical chemistry of biomolecular solutions and condensed states; Probability theory, stochastic processes, and statistics; Other topics in statistics

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