Association of a variant in the CHRNA5-A3-B4 gene cluster region to heavy smoking in the Italian population

Abstract

Large-scale population studies have established that genetic factors contribute to individual differences in smoking behavior. Linkage and genome-wide association studies have shown many chromosomal regions and genes associated with different smoking behaviors. One study was the association of single-nucleotide polymorphisms (SNPs) in the CHRNA5-A3-B4 gene cluster to nicotine addiction. Here, we report a replication of this association in the Italian population represented by three genetically isolated populations. One, the Val Borbera, is a genetic isolate from NorthWestern Italy; the Cilento population, is located in SouthWestern Italy; and the Carlantino village is located in SouthEastern Italy. Owing to their position and their isolation, the three populations have a different environment, different history and genetic structure. The variant A of the rs1051730 SNP was significantly associated with smoking quantity in two populations, Val Borbera and Cilento, no association was found in Carlantino population probably because difference in LD pattern in the variant region.

Association Between CHRNA3 and CHRNA5 Nicotine Receptor Subunit Gene Variants and Nicotine Dependence in an Isolated Populationof Kashubians in Poland

“…As in another study, CPD >10 was used as a cut-off value for low-dose smoking and high-dose smoking [ 21 ]. However, in other reports different definitions of light and heavy smokers were used, with CPD >20 as the most frequently used cut-off value [ 20 ].…”

Inheritance and quantitative trait locus analysis of low-light tolerance in cucumber (Cucumis sativus L.)

“…This result is similar to that of a prior report on traits of low-light tolerance in cucumber (Li et al, 2010). Gene cluster regions have been reported in many studies (Moynihan et al, 2009;Sorice et al, 2011). QTLs gathered in an identical region but controlled different traits, which may indicate close linkage, and pleiotropism or physiological associations.…”

Joint Data Analysis in Nutritional Epidemiology: Identification of Observational Studies and Minimal Requirements

“…One Italian study (43) collected information on dietary intake by using all 3 instruments in a subset of participants (Table 2). Two studies used a self-completed questionnaire to collect data on food preferences (34,37). Eleven studies had subjective data on physical activity, of which 4 also used accelerometers.…”