Abstract
The dynamic change of human immunodeficiency virus type-1 (HIV-1) particles that cause AIDS displays considerable variation from patients to patients. It is likely that such variation in HIV-1 pathogenesis is correlated with the genetic architecture of hosts. Traditional genetic analysis of HIV-1 infection is based on various biochemical approaches, but it has been little successful because HIV-1 dynamics, as a complex trait, is under polygenic control and sensitive to environmental changes. Here, we present a novel model for integrating mathematical functions for HIV-1 dynamics that have been well constructed into a multivariate mixture model for genetic mapping. This integrative mapping model on the foundation of linkage disequilibrium (LD)-based haplotype block analysis provides unique power to precisely detect human quantitative trait loci (QTL) determining HIV-1 dynamics and facilitates positional cloning of target QTL. The model allows for a number of hypothesis tests for the effects of the dynamic QTL on the virion clearance rate, the infected cell life-span and the average viral generation timein vivo, all of which provide theoretical principles to guide the development of efficient gene therapy strategies.
Highlights
During human immunodeficiency virus type-1 (HIV-1) pathogenesis, an increased viral load is known to be closely linked with CD4 lymphocyte depletion and disease progression (Ho et al, 1989; Patterson et al, 1993), but little is clear about the genetic control of the kinetics of virus in vivo
The simulation conditions include: (i) There is a segregating quantitative trait loci (QTL) with allele A and a in the simulated population that determines HIV dynamics; (ii) The population is assumed to be at Hardy-Weinberg equilibrium, with allele frequencies of q for allele A and of 1 2 q for allele a; (iii) The residual errors among different time points follow a multivariate normal distribution MVN(0, S), where S can be fit by the AR(1) model
In the simulation example derived from the experiment of Perelson et al (1996) we found that the QTL for overall HIV-1 dynamic curves might exert significant effects on the rate of virus-producing cells and the rate for virion clearance
Summary
During HIV-1 pathogenesis, an increased viral load is known to be closely linked with CD4 lymphocyte depletion and disease progression (Ho et al, 1989; Patterson et al, 1993), but little is clear about the genetic control of the kinetics of virus in vivo. Perelson et al (1996) constructed a mathematical function to model the dynamic curves of HIV-1 for five different patients undergoing antiretroviral drug therapy. The viral data of Perelson et al (1996) can be fit by a mathematical function derived to describe the timedependent total concentration, V(t), of plasma virions (including infectious, VI(t), and non-infectious, VNI(t)) after antiviral treatment, assuming the steady state for a system. We decompose V(t) into two parts due to different virus compartments, i.e
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