The combined effects of myocardial infarction risk factors: Simulation of the combined effects of gene variants, age, and smoking and an analysis of their interaction

G. J. Osmak, D. Lvovs, B. V. Titov, N. A. Matveeva, O. O. Favorova, Sasha Favorov

Research output: Contribution to journalArticlepeer-review

Abstract

Regression analysis has been used to model the combined influence of adverse factors, namely, specific variants of the CRP (rs1130864), IFNG (rs2430561), TGFB1 (rs1982073), FGB (rs1800788), and PTGS1 (rs3842787) genes; age; and smoking on the risk of myocardial infarction in men, as well as the possible interactions between these factors. The individual effects of each considered genetic factor were comparable in strength to the influence of smoking on the risk of myocardial infarction, and the presence of a combination of two or more genetic variants in nonsmokers resulted in a higher risk of myocardial infarction than in noncarrier smokers. A significant interaction between the presence of the FGB allele rs1800788*T and age was discovered; the protective effect of this allele decreased with age and gradually transformed into a predisposing effect. The study demonstrated that the association of FGB rs1800788*T with the risk of myocardial infarction should be considered only in the context of interaction with age.

Original languageEnglish (US)
Pages (from-to)123-128
Number of pages6
JournalBiophysics (Russian Federation)
Volume62
Issue number1
DOIs
StatePublished - Jan 1 2017

Keywords

  • interaction
  • modeling of combined effects
  • myocardial infarction
  • regression analysis
  • risk factors

ASJC Scopus subject areas

  • Biophysics

Fingerprint

Dive into the research topics of 'The combined effects of myocardial infarction risk factors: Simulation of the combined effects of gene variants, age, and smoking and an analysis of their interaction'. Together they form a unique fingerprint.

Cite this