Epidemiología, detección de resistencias y tropismo de VIH-1puesta al día

  1. Miriam Albert Hernández 1
  2. Ángel San Miguel Hernández 2
  1. 1 Servicio de Microbiología. Complejo Asistencial de Zamora. Hospital Virgen de la Concha. Zamora. Universidad de Salamanca. Salamanca
  2. 2 Servicio de Análisis Clínicos. Hospital Universitario Río Hortega. Valladolid
Revista:
Revista de Medicina de Laboratorio

ISSN: 2660-7484 2660-7638

Año de publicación: 2020

Volumen: 1

Número: 1

Páginas: 10-20

Tipo: Artículo

DOI: 10.20960/REVMEDLAB.00014 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Revista de Medicina de Laboratorio

Objetivos de desarrollo sostenible

Resumen

HIV-1 infection accounts for 98 % of cases worldwide. It is characterized by its enormous diversification and rapid evolution, marked by a geographically defined distribution of several genetically distinct viruses. The current pandemic HIV-1 is phylogenetically divided into 4 groups: M, N, O and P. Only the M group (9 subtypes and more than 98 circulating recombinant forms –CRFs-) has spread throughout Africa and the rest of continents, the distribution of subtypes and CRFs being heterogeneous (CRF02_AG is the most prevalent in Cameroon). Within some subtypes, the high genetic variation has led to the classification of sub-subtypes, constantly updated. The most predominant subtype in Europe is B, responsible for 66 % of cases and 11 % worldwide and for which the most information is available and against which most antiretroviral drugs (ARD) are designed. The emerging genetic diversity and dynamism of HIV-1 requires constant monitoring, representing a challenge for optimal diagnosis and treatment. Different diagnostic methods are available to study resistance to ARD as well as to determine the tropism of the virus, essential to guide Maraviroc (a powerful alternative with little resistance). Genotypic methods are of choice for both purposes, although in resistances determination they have more value to detect resistance than to predict sensitivity. The most used for viral tropism detection are WebPSSM and Geno2Pheno-(G2P), being the algorithm G2P with 5 % false positive rate which could provide a reliable prediction in clinical practice.