Phylogenetic approach reveals that virus genotype largely determines HIV set-point viral load

Alizon, Samuel; von Wyl, Viktor; Stadler, Tanja; Kouyos, Roger D; Yerly, Sabine; Hirschel, Bernard; Böni, Jürg; Shah, Cyril; Klimkait, Thomas; Furrer, Hansjakob; Rauch, Andri; Vernazza, Pietro L; Bernasconi, Enos; Battegay, Manuel; Bürgisser, Philippe; Telenti, Amalio; Günthard, Huldrych F; Bonhoeffer, Sebastian; Swiss HIV Cohort Study, (2010). Phylogenetic approach reveals that virus genotype largely determines HIV set-point viral load. PLoS pathogens, 6(9), e1001123. San Francisco, Calif.: Public Library of Science 10.1371/journal.ppat.1001123

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HIV virulence, i.e. the time of progression to AIDS, varies greatly among patients. As for other rapidly evolving pathogens of humans, it is difficult to know if this variance is controlled by the genotype of the host or that of the virus because the transmission chain is usually unknown. We apply the phylogenetic comparative approach (PCA) to estimate the heritability of a trait from one infection to the next, which indicates the control of the virus genotype over this trait. The idea is to use viral RNA sequences obtained from patients infected by HIV-1 subtype B to build a phylogeny, which approximately reflects the transmission chain. Heritability is measured statistically as the propensity for patients close in the phylogeny to exhibit similar infection trait values. The approach reveals that up to half of the variance in set-point viral load, a trait associated with virulence, can be heritable. Our estimate is significant and robust to noise in the phylogeny. We also check for the consistency of our approach by showing that a trait related to drug resistance is almost entirely heritable. Finally, we show the importance of taking into account the transmission chain when estimating correlations between infection traits. The fact that HIV virulence is, at least partially, heritable from one infection to the next has clinical and epidemiological implications. The difference between earlier studies and ours comes from the quality of our dataset and from the power of the PCA, which can be applied to large datasets and accounts for within-host evolution. The PCA opens new perspectives for approaches linking clinical data and evolutionary biology because it can be extended to study other traits or other infectious diseases.

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