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CONTRIBUTI SCIENTIFICI – Scientific Papers

Volume:

Biochimica Clinica 2020; 44(3) 249-254

Pubblicato on-line:

July 8, 2020

DOI:

10.19186/BC_2020.031

Scarica in PDF:
Autenticazione richiesta

Pharmacogenetic markers able to predict lipid-related parameters in a cohort of ritonavir treated patients

AUTORI

Jessica Cusato1, Andrea Calcagno1, Miriam Antonucci1, Letizia Marinaro1, Valeria Avataneo1, Amedeo De Nicolò1,
Alice Palermiti1, Stefano Bonora1, Giovanni Di Perri1, Antonio D’Avolio1,2
1Department of Medical Sciences, University of Turin, Amedeo di Savoia Hospital, Turin, Italy.
2Interdepartmental Center for Clinical and Experimental Pharmacology (CIFACS), University of Turin

ABSTRACT

Introduction: Ritonavir (RTV) could cause lipodistrofy and body fat redistribution. Pharmacogenetics could explain part of variability in RTV treatment outcome, but few data are present in literature concerning its influence on lipid-associated parameters. For these reasons, aim of this study is to describe the role of single nucleotide polymorphisms (SNPs) in genes involved in lipids and RTV transport and metabolism in affecting lipid-related biomarkers in a cohort of HIV-infected patients.
Methods: adult HIV-affected patients, being on RTV-containing antiretroviral treatment for at least 6 months, were enrolled at the “Amedeo di Savoia” hospital in Turin (Italy). Genotypes were assessed through real-time PCR.
Results: 99 patients were recruited for the study. The following associations were suggested: ABCB13435 TT on total cholesterol and triglycerydes, ABCB12677 on viral load, ABCC2-1249 AA on glucose,ABCC2 -24 GA/AA on total cholesterol, low density lipoproteins cholesterol and triglycerides, ABCG21194+928 CC on pancreatic amylase, HNF4 975 CG/GG on total cholesterol, low density lipoproteins cholesterol, VEGF-1154 AA on lactate dehydrogenase.
Discussion: This work was the first analyzing genetic polymorphisms affecting lipid-related markers in a cohort of RTV-treated patients. Further analyses are warranted to confirm these data and evaluate their influence on cardiovascular risk.

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