Genes to Diseases (G2D) Computational Method to Identify Asthma Candidate Genes

Asthma is a complex trait for which different strategies have been used to identify its environmental and genetic predisposing factors. Here, we describe a novel methodological approach to select candidate genes for asthma genetic association studies. In this regard, the Genes to Diseases (G2D) computational tool has been used in combination with a genome-wide scan performed in a sub-sample of the Saguenay−Lac-St-Jean (SLSJ) asthmatic familial collection (n = 609) to identify candidate genes located in two suggestive loci shown to be linked with asthma (6q26) and atopy (10q26.3), and presenting differential parent-of-origin effects. This approach combined gene selection based on the G2D data mining analysis of the bibliographic and protein public databases, or according to the genes already known to be associated with the same or a similar phenotype. Ten genes (LPA, NOX3, SNX9, VIL2, VIP, ADAM8, DOCK1, FANK1, GPR123 and PTPRE) were selected for a subsequent association study performed in a large SLSJ sample (n = 1167) of individuals tested for asthma and atopy related phenotypes. Single nucleotide polymorphisms (n = 91) within the candidate genes were genotyped and analysed using a family-based association test. The results suggest a protective association to allergic asthma for PTPRE rs7081735 in the SLSJ sample (p = 0.000463; corrected p = 0.0478). This association has not been replicated in the Childhood Asthma Management Program (CAMP) cohort. Sequencing of the regions around rs7081735 revealed additional polymorphisms, but additional genotyping did not yield new associations. These results demonstrate that the G2D tool can be useful in the selection of candidate genes located in chromosomal regions linked to a complex trait

Avoiding uncertainty in Hofstede and GLOBE

This paper compares the Uncertainty Avoidance (UA) dimension of national culture across the Hofstede and GLOBE models, looking at relationships in both data and analysis. Rather than mutual support, we detail major differences and anomalies across the studies. We show how these anomalies are resulting in contradictory explanations in research on national differences across a range of individual-, firm- and country-level phenomena. We clarify the UA measurement in both Hofstede and GLOBE, and find that the two models are measuring different components of the UA construct. We propose a two-component model of UA, namely, UA-stress and UA-rule orientation, and confirm its validity with national culture data from the Hofstede and GLOBE studies, and economic data from the World Bank. We also explain the negative GLOBE UA practices-values relationship using motivational theories. A way forward in future UA-related research is suggested. The Hofstede UA index, the GLOBE UA practices scores and the GLOBE UA values scores should be used within the specific domains that they represent: that is, stress, rule orientation practices and rule orientation aspirations, respectively. Resolving the contradictions in UA between and within Hofstede and GLOBE will help cross-cultural researchers develop more robust theories and more practical recommendations for international business management