Persistence of transmitted HIV-1 drug resistance mutations associated with fitness costs and viral genetic backgrounds

Abstract

Transmission of drug-resistant pathogens presents an almost-universal challenge for fighting infectious diseases. Transmitted drug resistance mutations (TDRM) can persist in the absence of drugs for considerable time. It is generally believed that differential TDRM-persistence is caused, at least partially, by variations in TDRM-fitness-costs. However, in vivo epidemiological evidence for the impact of fitness costs on TDRM-persistence is rare. Here, we studied the persistence of TDRM in HIV-1 using longitudinally-sampled nucleotide sequences from the Swiss-HIV-Cohort-Study (SHCS). All treatment-naïve individuals with TDRM at baseline were included. Persistence of TDRM was quantified via reversion rates (RR) determined with interval-censored survival models. Fitness costs of TDRM were estimated in the genetic background in which they occurred using a previously published and validated machine-learning algorithm (based on in vitro replicative capacities) and were included in the survival models as explanatory variables. In 857 sequential samples from 168 treatment-naïve patients, 17 TDRM were analyzed. RR varied substantially and ranged from 174.0/100-person-years;CI=[51.4, 588.8] (for 184V) to 2.7/100-person-years;[0.7, 10.9] (for 215D). RR increased significantly with fitness cost (increase by 1.6[1.3,2.0] per standard deviation of fitness costs). When subdividing fitness costs into the average fitness cost of a given mutation and the deviation from the average fitness cost of a mutation in a given genetic background, we found that both components were significantly associated with reversion-rates. Our results show that the substantial variations of TDRM persistence in the absence of drugs are associated with fitness-cost differences both among mutations and among different genetic backgrounds for the same mutation.

Fig 1. Reversion rate of individual TDRM.

Reversion rate was quantified via an interval-censored survival model using an exponential distribution. The table below showed the number of reversion and total number observed at baseline for each TDRM. NRTI resistance mutations showed the largest variability that included both the fastest (184V) and the slowest (215D) reverting TDRM.

Fig 2. Impact of fitness cost on reversion rates.

In unadjusted survival analysis (“fitness cost”), in survival analysis adjusted for type of mutation (“fitness cost adj.”). Impact of mean fitness cost and residual fitness cost in univariable analysis (“uvar.”) and in multivariable analysis including both mean and residual fitness cost (“mvar.”).