Impact of CCR5delta32 host genetic background and disease progression on HIV-1 intrahost evolutionary processes: efficient hypothesis testing through hierarchical phylogenetic models

Abstract

The interplay between C-C chemokine receptor type 5 (CCR5) host genetic background, disease progression, and intrahost HIV-1 evolutionary dynamics remains unclear because differences in viral evolution between hosts limit the ability to draw conclusions across hosts stratified into clinically relevant populations. Similar inference problems are proliferating across many measurably evolving pathogens for which intrahost sequence samples are readily available. To this end, we propose novel hierarchical phylogenetic models (HPMs) that incorporate fixed effects to test for differences in dynamics across host populations in a formal statistical framework employing stochastic search variable selection and model averaging. To clarify the role of CCR5 host genetic background and disease progression on viral evolutionary patterns, we obtain gp120 envelope sequences from clonal HIV-1 variants isolated at multiple time points in the course of infection from populations of HIV-1-infected individuals who only harbored CCR5-using HIV-1 variants at all time points. Presence or absence of a CCR5 wt/Δ32 genotype and progressive or long-term nonprogressive course of infection stratify the clinical populations in a two-way design. As compared with the standard approach of analyzing sequences from each patient independently, the HPM provides more efficient estimation of evolutionary parameters such as nucleotide substitution rates and d(N)/d(S) rate ratios, as shown by significant shrinkage of the estimator variance. The fixed effects also correct for nonindependence of data between populations and results in even further shrinkage of individual patient estimates. Model selection suggests an association between nucleotide substitution rate and disease progression, but a role for CCR5 genotype remains elusive. Given the absence of clear d(N)/d(S) differences between patient groups, delayed onset of AIDS symptoms appears to be solely associated with lower viral replication rates rather than with differences in selection on amino acid fixation.

FIG. 1

CD4⁺ T-cell numbers, viral loads, and antiretroviral treatments of 18 participants from the Amsterdam Cohort Studies who were selected for this study. Time points of clinical AIDS diagnosis are indicated with open downward triangles. Arrows indicate time points of clonal virus isolation. The length and type of antiretroviral therapy are indicated in the top part of the panels.

FIG. 2

Evolutionary rate estimates using an HPM applied separately to four patient groups (progressors, LTNP, WT, and Δ32). Evolutionary rate estimated under strict clock model (A). Mean evolutionary rate estimated under relaxed-clock model (B). LTNP (Long-term non-progressors); WT (CCR5 wt/wt); Δ32 (CCR5 wt/Δ32).

FIG. 3

Improved statistical efficiency (shrinkage effect) of the HPM. Strict clock (A). Relaxed clock (B). Posterior variance of estimated evolutionary rate from the independent analyses of each patient (white); evolutionary rate variance from the hierarchical analysis of LTNPs and progressors (black); evolutionary rate variance from the hierarchical analysis of LTNPs and progressors incorporating fixed effects (gray).

FIG. 4

Marginal posterior rate distributions for LTNP patients with different numbers of sampling time points. Least informative patients (lowest number of time points or sequences per time point): P10, P16, and P17. Most informative patients: P9, P11, and P13. (A and B) Assuming a uniform (0,0.004) rate prior. (C and D) Lognormal (−7.5,1) rate prior. (E and F) HPM with unknown mean and variance and diffuse priors.