Quantifying the fitness cost of HIV-1 drug resistance mutations through phylodynamics

Denise Kühnert; Roger Kouyos; George Shirreff; Jūlija Pečerska; Alexandra U Scherrer; Jürg Böni; Sabine Yerly; Thomas Klimkait; Vincent Aubert; Huldrych F Günthard; Tanja Stadler; Sebastian Bonhoeffer; Swiss HIV Cohort Study

doi:10.1371/journal.ppat.1006895

Quantifying the fitness cost of HIV-1 drug resistance mutations through phylodynamics

PLoS Pathog. 2018 Feb 20;14(2):e1006895. doi: 10.1371/journal.ppat.1006895. eCollection 2018 Feb.

Authors

Denise Kühnert^{1

2

3

4

5}, Roger Kouyos^{1

2}, George Shirreff^{3

6}, Jūlija Pečerska^{4

5}, Alexandra U Scherrer^{1

2}, Jürg Böni², Sabine Yerly⁷, Thomas Klimkait⁸, Vincent Aubert⁹, Huldrych F Günthard^{1

2}, Tanja Stadler^{4

5}, Sebastian Bonhoeffer³; Swiss HIV Cohort Study

Affiliations

¹ Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.
² Institute of Medical Virology, University of Zurich, Zurich, Switzerland.
³ Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland.
⁴ Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
⁵ Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
⁶ School of Medicine, Imperial College London, London, United Kingdom.
⁷ Laboratory of Virology, Division of Infectious Diseases, Geneva University Hospital, Geneva, Switzerland.
⁸ Department of Biomedicine, University of Basel, Basel, Switzerland.
⁹ Division of Immunology and Allergy, University Hospital Lausanne, Lausanne, Switzerland.

Abstract

Drug resistant HIV is a major threat to the long-term efficacy of antiretroviral treatment. Around 10% of ART-naïve patients in Europe are infected with drug-resistant HIV type 1. Hence it is important to understand the dynamics of transmitted drug resistance evolution. Thanks to routinely performed drug resistance tests, HIV sequence data is increasingly available and can be used to reconstruct the phylogenetic relationship among viral lineages. In this study we employ a phylodynamic approach to quantify the fitness costs of major resistance mutations in the Swiss HIV cohort. The viral phylogeny reflects the transmission tree, which we model using stochastic birth-death-sampling processes with two types: hosts infected by a sensitive or resistant strain. This allows quantification of fitness cost as the ratio between transmission rates of hosts infected by drug resistant strains and transmission rates of hosts infected by drug sensitive strains. The resistance mutations 41L, 67N, 70R, 184V, 210W, 215D, 215S and 219Q (nRTI-related) and 103N, 108I, 138A, 181C, 190A (NNRTI-related) in the reverse trancriptase and the 90M mutation in the protease gene are included in this study. Among the considered resistance mutations, only the 90M mutation in the protease gene was found to have significantly higher fitness than the drug sensitive strains. The following mutations associated with resistance to reverse transcriptase inhibitors were found to be less fit than the sensitive strains: 67N, 70R, 184V, 219Q. The highest posterior density intervals of the transmission ratios for the remaining resistance mutations included in this study all included 1, suggesting that these mutations do not have a significant effect on viral transmissibility within the Swiss HIV cohort. These patterns are consistent with alternative measures of the fitness cost of resistance mutations. Overall, we have developed and validated a novel phylodynamic approach to estimate the transmission fitness cost of drug resistance mutations.

Publication types

Multicenter Study
Observational Study
Research Support, Non-U.S. Gov't

MeSH terms

Adaptation, Biological / genetics
Anti-HIV Agents / therapeutic use*
Antiretroviral Therapy, Highly Active
Databases, Factual
Drug Resistance, Viral / genetics*
Genetic Fitness*
Genotype
HIV Infections / drug therapy*
HIV Infections / epidemiology
HIV Infections / virology
HIV-1 / genetics*
Humans
Mutation
Mutation Rate*
Phylogeny
Reverse Transcriptase Inhibitors / therapeutic use
Switzerland / epidemiology

Substances

Anti-HIV Agents
Reverse Transcriptase Inhibitors

Grants and funding

DK gratefully acknowledges support from the ETH Zurich Postdoctoral Fellowship Program and the Marie Curie Actions for People COFUND, and the Swiss National Science Foundation (SNSF) for generously funding her research with a Marie Heim- Vögtlin fellowship. RK also acknowledges support from the SNSF (grant BSSGI0_155851). SB, GS and DK gratefully acknowledge support from the ERC (PBDR 268540). GS was also funded by the World Health Organisation (grant number 2013/363982) and the Medical Research Council Centre for Outbreak Analysis and Modelling. JP was funded through a SystemsX grant from the SNSF (TbX). TS is supported in part by the European Research Council under the Seventh Framework Programme of the European Commission (PhyPD grant 335529). This study has been financed in the framework of the Swiss HIV Cohort Study, supported by the Swiss National Science Foundation (SNSF grant 33CS30- 134277), the SHCS Projects 470, 528, 569, 683, 724, the SHCS Research Foundation, the Swiss National Science Foundation grant 159868 (to HFG), by the Yvonne-Jacob foundation, an unrestricted research grant from Gilead, Switzerland, to the SHCS research foundation, and by the University of Zurich’s Clinical research Priority Program (CRPP) Viral infectious diseases: Zurich Primary HIV Infection Study (to HFG). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.