Integrating genealogical and dynamical modelling to infer escape and reversion rates in HIV epitopes

Integrating genealogical and dynamical modelling to infer escape and reversion rates in HIV epitopes
Duncan Palmer, Angela McLean, Gil McVean
(Submitted on 5 Feb 2013)

The rates of escape and reversion in response to selection pressure arising from the host immune system, notably the cytotoxic T-lymphocyte (CTL) response, are key factors determining the evolution of HIV. Existing methods for estimating these parameters from cross-sectional population data using ordinary differential equations (ODE) ignore information about the genealogy of sampled HIV sequences, which has the potential to cause systematic bias and over-estimate certainty. Here, we describe an integrated approach, validated through extensive simulations, which combines genealogical inference and epidemiological modelling, to estimate rates of CTL escape and reversion in HIV epitopes. We show that there is substantial uncertainty about rates of viral escape and reversion from cross-sectional data, which arises from the inherent stochasticity in the evolutionary process. By application to empirical data, we find that point estimates of rates from a previously published ODE model and the integrated approach presented here are often similar, but can also differ several-fold depending on the structure of the genealogy. The model-based approach we apply provides a framework for the statistical analysis of escape and reversion in population data and highlights the need for longitudinal and denser cross-sectional sampling to enable accurate estimate of these key parameters.

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4 thoughts on “Integrating genealogical and dynamical modelling to infer escape and reversion rates in HIV epitopes

  1. Pingback: Thoughts on “Integrating genealogical and dynamical modelling to infer escape and reversion rates in HIV epitopes” | Haldane's Sieve

  2. The idea behind this paper makes a lot of sense to me, but I am wondering what the meaning of the rates is. My understanding is that most CTL escape mutations emerge early in infection, but not all presented epitopes escape. In other words, in a fraction of cases escape is fast while the remainder does not escape. The paper attempts to fit this dynamics with a single-rate model (convoluted with a transmission dynamics embedded on a genealogy), which could be problematic. Would the fraction of cases in which escape is rapid be a more meaningful number?

    richard

  3. Pingback: Most viewed on Haldane’s Sieve: February 2013 | Haldane's Sieve

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