PREMATURE CORONARY ARTERY DISEASE

INTERPLAY OF IMMUNE-INFLAMMATORY GENOMICS IN THE PATHOGENESIS OF PCAD

Abstract

Introduction: Integrative genomics may help in the identification of novel
biological pathways in the pathogenesis of CAD. Objectives: To find out the association of 5
Cytokine SNPs and 13 CAD SNPs gene risk scores with serum cytokine levels in Premature
Coronary Artery Disease (PCAD). To identify the direct and indirect protein interactions of the 13
CAD risk genes and the 5 cytokine genes in PCAD. Study Design: Case-control study. Setting:
Army Medical College, in association with University College London (UCL), London, United
Kingdom (UK). Materials and Methods: 340 PCAD patients and 310 age and sex matched
controls were recruited. Serum IL18, TNFA, IL6 and IL10 levels were measured using ELISA
(Invitrogen). The SNPs were genotyped using TAQMAN and KASPar assays. Data analysis was
done using standard SPSS software version-21 (SPSS Inc, Chicago, Illinois, USA). The proteinprotein
interaction (PPI) network was generated using STRING version 9.0, Genemania and
I-Tessar web. Results: The patients of PCAD had mean ± SD age of 42 ± 3.80 years consisting
of 329 males and 11 females. The 5 SNP cytokine gene risk score correlated significantly with
the serum IL-18, IL-6, TNF-alpha, IL-18: IL-10 and TNF-alpha: IL-10 ratios (p<0.01). The 13 CAD
SNP gene risk score also correlated significantly with the serum IL-18, TNF-alpha, IL-18: IL-10
and TNF-alpha: IL-10 ratios but not with serum IL-6 levels. IL-6 works in close interaction with
IL-6R, STAT3 and NFKB1. While MRAS, MIA3 and SORT1 interact with each other CXCL-12
mediates its actions by interacting with IL-18, JAK-2 and CCR4. LPA interacts closely with APOB
and LPL acts via interaction with APOA4 and APOA5. Conclusion: The correlation between
gene risk scores and serum cytokine levels can aid in the analysis of complex networks to
understand the pathogenesis of PCAD.