FABP1 gene variant associated with risk of metabolic syndrome

Author:

Zare-Feyzabadi Reza1,Mozaffari Majid1,Ghayour-Mobarhan Majid2,Valizadeh Mohsen2

Affiliation:

1. Department of Chemistry, Shahrood Branch, Islamic Azad University, Shahrood, Iran

2. Metabolic Syndrome Research Center, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran

Abstract

Background: Metabolic Syndrome (MetS) is defined by a clustering of metabolic abnormalities associated with an increased risk of cardiovascular disease and type 2 diabetes mellitus. There has been an increasing interest in the associations of genetic variants involved in diabetes and obesity in the FABP1 pathway. The relationship between the rs2241883 polymorphism of FABP1 and risk of MetS remains unclear. Objective: We aimed to examine the association between this genetic polymorphism and the presence of MetS and its constituent factors. Methods: A total of 942 participants were recruited as part of the Mashhad Stroke and Heart Atherosclerosis Disorders (MASHAD study) Cohort. Patients with MetS were identified using the International Diabetes Federation (IDF) criteria (n=406) and those without MetS (n=536) were also recruited. DNA was extracted from peripheral blood samples and used for genotyping of the FABP1 rs2241883T/C polymorphism using Tetra-Amplification Refractory Mutation System Polymerase Chain Reaction (Tetra-ARMS PCR). Genetic analysis was confirmed by gel electrophoresis and DNA sequencing. Results: Using both univariate and multivariate analyses after adjusting for age, sex and physical activity, carriers of C allele (CT/CC genotypes) in FABP1 variant were related to an increased risk of MetS, compared to non-carriers (OR: 1.38, 95%CI: 1.04,1.82, p=0.026). Conclusion: The present study shows that C allele in the FABP1 variant can be associated with an increased risk of MetS. The evaluation of these factors in a larger population may help further confirm these findings.

Publisher

Bentham Science Publishers Ltd.

Subject

Organic Chemistry,Computer Science Applications,Drug Discovery,General Medicine

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