Literature DB >> 23524009

Genetic analysis of candidate SNPs for metabolic syndrome in obstructive sleep apnea (OSA).

Antonio Grilo1, Elena S Ruiz-Granados, Concha Moreno-Rey, Jose M Rivera, Agustin Ruiz, Luis M Real, Maria E Sáez.   

Abstract

Obstructive sleep apnea (OSA) is a common disorder characterized by the reduction or complete cessation in airflow resulting from an obstruction of the upper airway. Several studies have observed an increased risk for cardiovascular morbidity and mortality among OSA patients. Metabolic syndrome (MetS), a cluster of cardiovascular risk factors characterized by the presence of insulin resistance, is often found in patients with OSA, but the complex interplay between these two syndromes is not well understood. In this study, we present the results of a genetic association analysis of 373 candidate SNPs for MetS selected in a previous genome wide association analysis (GWAS). The 384 selected SNPs were genotyped using the Illumina VeraCode Technology in 387 subjects retrospectively assessed at the Internal Medicine Unit of the "Virgen de Valme" University Hospital (Seville, Spain). In order to increase the power of this study and to validate our findings in an independent population, we used data from the Framingham Sleep Study which comprises 368 individuals. Only the rs11211631 polymorphism was associated with OSA in both populations, with an estimated OR=0.57 (0.42-0.79) in the joint analysis (p=7.21×10(-4)). This SNP was selected in the previous GWAS for MetS components using a digenic approach, but was not significant in the monogenic study. We have also identified two SNPs (rs2687855 and rs4299396) with a protective effect from OSA only in the subpopulation with abdominal obesity. As a whole, our study does not support the idea that OSA and MetS share major genetic determinants, although both syndromes share common epidemiological and clinical features.
Copyright © 2013 Elsevier B.V. All rights reserved.

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Year:  2013        PMID: 23524009      PMCID: PMC4039742          DOI: 10.1016/j.gene.2013.03.024

Source DB:  PubMed          Journal:  Gene        ISSN: 0378-1119            Impact factor:   3.688


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