Genetic variability of CYP2D6, CYP2B6, CYP2C9 and CYP2C19 genes across the Italian Peninsula. (2nd January 2018)

• Record Type: Journal Article
• Authors: Carano, Francesco; Sarno, Stefania; De Fanti, Sara; Serventi, Patrizia; Bini, Carla; Luiselli, Donata; Pelotti, Susi
• Is Part Of: Annals of human biology. Volume 45:Number 1(2018)
• Page Start: 66
• Page End: 71
• Publication Date: 2018-01-02
• Subjects: Pharmacogenetics -- cytochrome-P450 (CYP) genes -- Italian population -- genetic variation -- geographic structure; Human biology -- Periodicals; 612
• DOI: 10.1080/03014460.2017.1378368
• Languages: English
• ISSNs: 0301-4460

Abstract

Abstract: Background: Environmental conditions and past migratory events may have shaped genetic heterogeneity of clinically relevant enzymes involved in the phase I metabolism of the most common therapeutic drugs. Aim: To investigate the genetic variability of CYP2D6, CYP2B6, CYP2C19 and CYP2C9 across the Italian Peninsula, by sampling only ancestrally and geographically homogeneous individuals from northern, central and southern Italy. Subjects and methods: A total of 25 SNPs were genotyped in 174 unrelated Italian individuals by means of multiplex PCR and minisequencing reactions. CYP2D6 genotypic data were used to predict phenotypes and the phylogenetic relationships among reconstructed haplotypes were represented by means of a Median Joining Network. Results: Pairwise Fisher Exact tests revealed significant differences between northern and southern Italy in the distribution of CYP2C19 genotypes, with the CYP2C19*2 allele appearing over-represented in northern Italy. Likewise, significant differences in the distribution of CYP2D6 genotypes (*4/*3, *4/*4 and *6/*4) responsible for the poor metabolizer phenotype were observed in northern with respect to both central and southern Italy. Conclusions: The north–south structuring pattern showed by CYP2D6 and CYP2C19 underline how a deeper knowledge of the geographic distribution of alleles may improve clinical practice and help to avoid hypothetical bias in drug trials.