Translational informatics approach for identifying the functional molecular communicators linking coronary artery disease, infection and inflammation

Ankit Sharma; Madankumar Ghatge; Lakshmi Mundkur; Rajani Kanth Vangala

doi:10.3892/mmr.2016.5013

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Translational informatics approach for identifying the functional molecular communicators linking coronary artery disease, infection and inflammation

Journal article

Open access

Peer reviewed

Translational informatics approach for identifying the functional molecular communicators linking coronary artery disease, infection and inflammation

Ankit Sharma, Madankumar Ghatge, Lakshmi Mundkur and Rajani Kanth Vangala

Molecular medicine reports, Vol.13(5), pp.3904-3912

05/01/2016

DOI: 10.3892/mmr.2016.5013

PMCID: PMC4838147

PMID: 27035874

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Abstract

Translational informatics approaches are required for the integration of diverse and accumulating data to enable the administration of effective translational medicine specifically in complex diseases such as coronary artery disease (CAD). In the current study, a novel approach for elucidating the association between infection, inflammation and CAD was used. Genes for CAD were collected from the CAD‑gene database and those for infection and inflammation were collected from the UniProt database. The cytomegalovirus (CMV)‑induced genes were identified from the literature and the CAD‑associated clinical phenotypes were obtained from the Unified Medical Language System. A total of 55 gene ontologies (GO) termed functional communicator ontologies were identified in the gene sets linking clinical phenotypes in the diseasome network. The network topology analysis suggested that important functions including viral entry, cell adhesion, apoptosis, inflammatory and immune responses networked with clinical phenotypes. Microarray data was extracted from the Gene Expression Omnibus (dataset: GSE48060) for highly networked disease myocardial infarction. Further analysis of differentially expressed genes and their GO terms suggested that CMV infection may trigger a xenobiotic response, oxidative stress, inflammation and immune modulation. Notably, the current study identified γ‑glutamyl transferase (GGT)‑5 as a potential biomarker with an odds ratio of 1.947, which increased to 2.561 following the addition of CMV and CMV‑neutralizing antibody (CMV‑NA) titers. The C‑statistics increased from 0.530 for conventional risk factors (CRFs) to 0.711 for GGT in combination with the above mentioned infections and CRFs. Therefore, the translational informatics approach used in the current study identified a potential molecular mechanism for CMV infection in CAD, and a potential biomarker for risk prediction.

Biomarkers - metabolism

Coronary Artery Disease - etiology

Coronary Artery Disease - genetics

Coronary Artery Disease - metabolism

Female

Gene Ontology

Humans

Infection - complications

Infection - genetics

Infection - metabolism

Inflammation - complications

Inflammation - genetics

Inflammation - metabolism

Male

Medical Informatics Applications

Details

Title: Subtitle: Translational informatics approach for identifying the functional molecular communicators linking coronary artery disease, infection and inflammation
Creators: Ankit Sharma - Thrombosis Research Institute
Madankumar Ghatge - Thrombosis Research Institute
Lakshmi Mundkur - Thrombosis Research Institute
Rajani Kanth Vangala - Thrombosis Research Institute
Resource Type: Journal article
Publication Details: Molecular medicine reports, Vol.13(5), pp.3904-3912
DOI: 10.3892/mmr.2016.5013
PMID: 27035874
PMCID: PMC4838147
NLM abbreviation: Mol Med Rep
ISSN: 1791-2997
eISSN: 1791-3004
Language: English
Date published: 05/01/2016
Academic Unit: Internal Medicine
Record Identifier: 9984949176002771

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