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ISSN 1527-3172 (Electronic)

2019, Number 2-3

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MEDICC Review 2019; 21 (2-3)

Pharmacogenetic markers: A path toward individualized HIV therapy

García-Blanco D, Gravier-Hernández R, Rabeiro-Martínez CL, Gil VL, Pérez-Ávila J

Language: English
References: 77
Page: 59-68
PDF size: 186.25 Kb.


ABSTRACT

INTRODUCTION Approximately 73% of persons with HIV who receive antiretroviral therapy in Cuba are in viral suppression. The non-response of the remaining 27% could be due to several factors including adverse drug reactions and HIV resistance to antiretroviral drugs, as well as social factors and idiosyncratic characteristics of each patient. Genetic information explains from 20% to 95% of a drug’s effects and variations in response. Considering optimization of therapeutic efficacy in our country, genetic factors of the host should be identified.
OBJECTIVE Identify polymorphisms affecting genetic variability of responses to antiretroviral drugs.
EVIDENCE ACQUISITION A literature review was conducted (of original articles, published theses, clinical reports and bibliographic review studies, from 2000 to 2018, in Spanish and English listed in MEDLINE/PubMed, SciELO, LILACS, PharmGKB and Google Scholar) with the following key words: pharmacogenetics, human immunodeficiency virus, anti-retroviral agents, genetic polymorphism, genetic techniques, pharmacogenomic variants.
DEVELOPMENT The review identified 77 relevant publications meeting specific quality criteria. A summary table was built with data collected on antiretroviral drugs, genes and proteins involved in polymorphic variations, their associated effects and relevant scientific references. Information was included on polymorphisms related to 12 antiretroviral drugs used in HIV therapy. Polymorphisms determine variations in proteins involved in drug transport and metabolism and in elements of immunity. Relevant pharmacogenetic biomarkers recognized by drug regulatory agencies were identified.
CONCLUSIONS The study identified genetic variations (single-nucleotide polymorphisms) associated with 12 antiretroviral drugs. In most cases, no statistically significant causal association was found. Identifying polymorphic variations is a medium- and long-term objective that requires statistical support and adoption of strategies to optimize antiretroviral therapy. An approach combining plasma-level monitoring and pharmacogenetic analysis is recommended to optimize therapy for HIV patients.


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