Contribution of hierarchical clustering techniques to the modeling of the geographic distribution of genetic polymorphisms associated with chronic inflammatory diseases in the Québec population
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2007
- handle: 10670/1.k926ch
- Madore Anne-Marie, Houde Louis, Vézina Hélène, Vohl M.-C., Pérusse L., Mior N., Connelly P.W., Laberge C., Gaudet D. et Laprise Catherine. (2007). Contribution of hierarchical clustering techniques to the modeling of the geographic distribution of genetic polymorphisms associated with chronic inflammatory diseases in the Québec population. Public Health Genomics, 10, (4), p. 218-226.
- doi: 10.1159/000106560
Ce document est lié à :
https://constellation.uqac.ca/id/eprint/8303/
Ce document est lié à :
https://dx.doi.org/doi:10.1159/000106560
Ce document est lié à :
doi:10.1159/000106560
Mots-clés
Histoire Démographie Génétique asthma cardiovascular diseases French Canadian population genetic risk factors génétique Québec maladies inflammatoires chroniquesSujets proches
Health services Hygiene, Social Social hygiene Public hygiene Sanitary affairs Public health services Hygiene, Public Community healthCiter ce document
Anne-Marie Madore et al., « Contribution of hierarchical clustering techniques to the modeling of the geographic distribution of genetic polymorphisms associated with chronic inflammatory diseases in the Québec population », Constellation - Université du Québec à Chicoutimi, ID : 10.1159/000106560
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Résumé
Objectives: The purpose of this project was to evaluate the potential of the downward hierarchical clustering analysis (DHCA) for studying genetic heterogeneity, i.e. differences in allele frequency in subpopulations, such as the 15 public health regions of the province of Québec (Canada). Methods: The study relied on an anonymized sample of 1,680 individuals who had participated in the Québec Heart Health Survey in 1990-1991. The genotyping of 11 variants in 8 candidate genes known to be involved in chronic inflammatory diseases, namely asthma and cardiovascular diseases, was performed using the amplification refractory mutation system and restriction fragment length polymorphism techniques. Only variants showing an allelic frequency >2% in the Québec Heart Health Survey (n = 8) were selected. DHCA techniques were then applied to model the geographical distribution of these 8 genetic variants in 15 Québec public health regions and to study genetic heterogeneity. Results: The DHCA allowed to group public health regions and gene variants on the basis of genetic variability. For both asthma and cardiovascular diseases, 3 significant clusters of public health regions and 1 cluster of gene variants were identified. Discussion: This study suggests that DHCA might be useful in studying genetic heterogeneity at the population level and for public health activities.