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Quantifying the HIV reservoir with dilution assays and deep viral sequencing.
Lotspeich, Sarah C; Richardson, Brian D; Baldoni, Pedro L; Enders, Kimberly P; Hudgens, Michael G.
Afiliación
  • Lotspeich SC; Department of Statistical Sciences, Wake Forest University, Winston-Salem, NC 27109, United States.
  • Richardson BD; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States.
  • Baldoni PL; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States.
  • Enders KP; Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, 3052, Australia.
  • Hudgens MG; Department of Medical Biology, The University of Melbourne, Parkville, Victoria, 3052, Australia.
Biometrics ; 80(1)2024 Jan 29.
Article en En | MEDLINE | ID: mdl-38364812
ABSTRACT
People living with HIV on antiretroviral therapy often have undetectable virus levels by standard assays, but "latent" HIV still persists in viral reservoirs. Eliminating these reservoirs is the goal of HIV cure research. The quantitative viral outgrowth assay (QVOA) is commonly used to estimate the reservoir size, that is, the infectious units per million (IUPM) of HIV-persistent resting CD4+ T cells. A new variation of the QVOA, the ultra deep sequencing assay of the outgrowth virus (UDSA), was recently developed that further quantifies the number of viral lineages within a subset of infected wells. Performing the UDSA on a subset of wells provides additional information that can improve IUPM estimation. This paper considers statistical inference about the IUPM from combined dilution assay (QVOA) and deep viral sequencing (UDSA) data, even when some deep sequencing data are missing. Methods are proposed to accommodate assays with wells sequenced at multiple dilution levels and with imperfect sensitivity and specificity, and a novel bias-corrected estimator is included for small samples. The proposed methods are evaluated in a simulation study, applied to data from the University of North Carolina HIV Cure Center, and implemented in the open-source R package SLDeepAssay.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Infecciones por VIH / VIH-1 Límite: Humans Idioma: En Revista: Biometrics Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Infecciones por VIH / VIH-1 Límite: Humans Idioma: En Revista: Biometrics Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos