Risk factors and outcomes for the Q151M and T69 insertion HIV-1 resistance mutations in historic UK data

Abstract

Background: The prevalence of HIV-1 resistance to antiretroviral therapies (ART) has declined in high-income countries over recent years, but drug resistance remains a substantial concern in many low and middle-income countries. The Q151M and T69 insertion (T69i) resistance mutations in the viral reverse transcriptase gene can reduce susceptibility to all nucleoside/tide analogue reverse transcriptase inhibitors, motivating the present study to investigate the risk factors and outcomes associated with these mutations.

Methods: We considered all data in the UK HIV Drug Resistance Database for blood samples obtained in the period 1997-2014. Where available, treatment history and patient outcomes were obtained through linkage to the UK Collaborative HIV Cohort study. A matched case-control approach was used to assess risk factors associated with the appearance of each of the mutations in ART-experienced patients, and survival analysis was used to investigate factors associated with viral suppression. A further analysis using matched controls was performed to investigate the impact of each mutation on survival.

Results: A total of 180 patients with Q151M mutation and 85 with T69i mutation were identified, almost entirely from before 2006. Occurrence of both the Q151M and T69i mutations was strongly associated with cumulative period of virological failure while on ART, and for Q151M there was a particular positive association with use of stavudine and negative association with use of boosted-protease inhibitors. Subsequent viral suppression was negatively associated with viral load at sequencing for both mutations, and for Q151M we found a negative association with didanosine use but a positive association with boosted-protease inhibitor use. The results obtained in these analyses were also consistent with potentially large associations with other drugs. Analyses were inconclusive regarding associations between the mutations and mortality, but mortality was high for patients with low CD4 at detection.

Conclusions: The Q151M and T69i resistance mutations are now very rare in the UK. Our results suggest that good outcomes are possible for people with these mutations. However, in this historic sample, viral load and CD4 at detection were important factors in determining prognosis.

Keywords: 151 complex; 69 insertion complex; HIV; Multi-NRTI resistance; Multidrug resistance; NRTI.

Fig. 1

Prevalence of (a) the Q151M mutation and (b) the T69i mutation per patient by calendar year of sequencing (patients can be included in multiple calendar years, but are only counted once per year), according to whether the patient was ART experienced (black circle) or naïve (orange circle) at the time of blood sample. The denominator in each year is the total number of patients with at least one reverse transcriptase sequence recorded in that year. Binomial 95% CIs are shown

Fig. 2

Posterior mean values and 95% credibility intervals for (a) log-odds ratios in the matched case–control analysis investigating factors associated with the occurrence of the Q151M mutation and (b) log-hazard ratios in the Cox regression for confirmed viral suppression following treatment change after detection of Q151M mutation. Continuous variables were standardised (stand.), by subtracting the mean and dividing by SD, for these analyses. The results presented are from multivariable models in each case

Fig. 3

Modelled probability of viral suppression in ART-experienced patients in terms of time since treatment switch following detection of the Q151M mutation for patients with a baseline viral load of (a) 2000 copies/mL (≈ 10th centile), (b) 40,000 copies/mL (≈ 50th centile) or (c) 500,000 copies/mL (≈ 90th centile). Response is modelled according to presence or absence of a ritonavir-boosted protease inhibitor in the ART regimen at time zero, but patients were not censored at change to drug regimen in this analysis. The expected probability (solid line) and 95% credibility interval (dashed lines) from Bayesian fitting of sequential Weibull models for viral suppression and rebound are shown. DDI use was adjusted for in this analysis, but results are shown for patients not on DDI

Fig. 4

Posterior mean values and 95% credibility intervals for (a) log-odds ratios in the matched case–control analysis investigating factors associated with the occurrence of the T69 insertion mutation and (b) log-hazard ratios in the Cox regression for confirmed viral suppression following treatment change after detection of T69 insertion mutation. Continuous variables were standardised (stand.), by subtracting the mean and dividing by SD, for these analyses. The results presented are from multivariable models in each case

Fig. 5

Modelled probability of viral suppression in ART-experienced patients in terms of time since treatment switch following detection of the T69i mutation for patients with a baseline viral load of (a) 2000 copies/mL (≈ 10^th centile), (b) 10,000 copies/mL (≈ 50th centile) or (c) 225,000 copies/mL (≈ 90th centile). The expected probability (solid line) and 95% credibility interval (dashed lines) from Bayesian fitting of sequential Weibull models for viral suppression and rebound are shown. D4T use was adjusted for in this analysis, but results are shown for patients not on D4T