A common variant in RAB27A gene is associated with fractional exhaled nitric oxide levels in adults.

BACKGROUND: Exhaled nitric oxide (FeNO) is a biomarker for eosinophilic inflammation in the airways and for responsiveness to corticosteroids in asthmatics. OBJECTIVE: We sought to identify in adults the genetic determinants of fractional exhaled nitric oxide (FeNO) levels and to assess whether environmental and disease-related factors influence these associations. METHODS: We performed a genome-wide association study of FeNO through meta-analysis of two independent discovery samples of European ancestry: the outbred EGEA study (French Epidemiological study on the Genetics and Environment of Asthma, N = 610 adults) and the Hutterites (N = 601 adults), a founder population living on communal farms. Replication of main findings was assessed in adults from an isolated village in Sardinia (Talana study, N = 450). We then investigated the influence of asthma, atopy and tobacco smoke exposure on these genetic associations, and whether they were also associated with FeNO values in children of the EAGLE (EArly Genetics & Lifecourse Epidemiology, N = 8858) consortium. RESULTS: We detected a common variant in RAB27A (rs2444043) associated with FeNO that reached the genome-wide significant level (P = 1.6 × 10(-7) ) in the combined discovery and replication adult data sets. This SNP belongs to member of RAS oncogene family (RAB27A) and was associated with an expression quantitative trait locus for RAB27A in lymphoblastoid cell lines from asthmatics. A second suggestive locus (rs2194437, P = 8.9 × 10(-7) ) located nearby the sodium/calcium exchanger 1 (SLC8A1) was mainly detected in atopic subjects and influenced by inhaled corticosteroid use. These two loci were not associated with childhood FeNO values. CONCLUSIONS AND CLINICAL RELEVANCE: This study identified a common variant located in RAB27A gene influencing FeNO levels specifically in adults and with a biological relevance to the regulation of FeNO levels. This study provides new insight into the biological mechanisms underlying FeNO levels in adults.

Probing the factor structure of metabolic syndrome in Sardinian genetic isolates.

BACKGROUND AND AIMS: Owing to the multiplicity of the key components of metabolic syndrome (MetS), its diagnosis is very complex. The lack of a unique definition is responsible for the prevalence variability observed among studies; therefore, a definition based on continuous variables was recommended. The aim of this study was to compare competing models of the MetS factor structure for selecting the one that explains the best clustering pattern and to propose an algorithm for computing MetS as a continuous variable. METHODS AND RESULTS: Data were from isolated Sardinian populations (n = 8102). Confirmatory factor analysis (CFA) and two-group CFA by gender were performed to evaluate the sex-specific factor structure of MetS. After selecting the best model, an algorithm was obtained using factor loadings/residual variances. The quality of the MetS score was evaluated by the receiver operating characteristics curve and the area under the curve. Cross-validation was performed to validate the score and to determine the best cut point. The best fit model was a bifactor one with a general factor (MetS) and three specific factors (f1: obesity/adiposity trait; f2: hypertension/blood pressure trait; and f3: lipid trait). Gender-specific algorithms were implemented to obtain MetS scores showing a good diagnostic performance (0.80 specificity and 0.80 sensitivity for the cut point). Furthermore, cross-validation confirmed these results. CONCLUSION: These analyses suggested that the bifactor model was the most representative one. In addition, they provided a score and a cut point that are both clinically accessible and interpretable measures for MetS diagnosis and likely useful for evaluating the association with adverse cardiovascular disease and diabetes and for investigating the MetS genetic component.