Impact of pretreatment low-abundance HIV-1 drug-resistant variants on virological failure among HIV-1/TB-co-infected individuals

Abstract

Objectives:
To determine the impact of pretreatment low-abundance HIV-1 drug-resistant variants (LA-DRVs) on virological failure (VF) among HIV-1/TB-co-infected individuals treated with NNRTI first-line ART.

Methods:
We conducted a case-control study of 170 adults with HIV-1/TB co-infection. Cases had at least one viral load (VL) ≥1000 RNA copies/mL after ≥6 months on NNRTI-based ART, and controls had sustained VLs <1000 copies/mL. We sequenced plasma viruses by Sanger and MiSeq next-generation sequencing (NGS). We assessed drug resistance mutations (DRMs) using the Stanford drug resistance database, and analysed NGS data for DRMs at ≥20%, 10%, 5% and 2% thresholds. We assessed the effect of pretreatment drug resistance (PDR) on VF.

Results:
We analysed sequences from 45 cases and 125 controls. Overall prevalence of PDR detected at a ≥20% threshold was 4.7% (8/170) and was higher in cases than in controls (8.9% versus 3.2%), P = 0.210. Participants with PDR at ≥20% had almost 4-fold higher odds of VF (adjusted OR 3.7, 95% CI 0.8-18.3) compared with those without, P = 0.104. PDR prevalence increased to 18.2% (31/170) when LA-DRVs at ≥2% were included. Participants with pretreatment LA-DRVs only had 1.6-fold higher odds of VF (adjusted OR 1.6, 95% CI 0.6-4.3) compared with those without, P = 0.398.

Conclusions:
Pretreatment DRMs and LA-DRVs increased the odds of developing VF on NNRTI-based ART, although without statistical significance. NGS increased detection of DRMs but provided no additional benefit in identifying participants at risk of VF at lower thresholds. More studies assessing mutation thresholds predictive of VF are required to inform use of NGS in treatment decisions.

Full text

ZurichOpenRepositoryandArchiveUniversityofZurichMainLibraryStrickhofstrasse39CH-8057Zurichwww.zora.uzh.chYear:2020Impactofpretreatmentlow-abundanceHIV-1drug-resistantvariantsonvirologicalfailureamongHIV-1/TB-co-infectedindividualsChimukangara,Benjamin;Giandhari,Jennifer;Lessells,Richard;Yende-Zuma,Nonhlanhla;Sartorius,Benn;Samuel,Reshmi;Khanyile,KhulekaniS;Stray-Pedersen,Babill;Moodley,Pravi;Metzner,KarinJ;Padayatchi,Nesri;Naidoo,Kogieleum;DeOliveira,TulioAbstract:OBJECTIVES:Todeterminetheimpactofpretreatmentlow-abundanceHIV-1drug-resistantvariants(LA-DRVs)onvirologicalfailure(VF)amongHIV-1/TB-co-infectedindividualstreatedwithNNRTIrst-lineART.METHODS:Weconductedacase-controlstudyof170adultswithHIV-1/TBco-infection.Caseshadatleastoneviralload(VL)฀1000RNAcopies/mLafter฀6monthsonNNRTI-basedART,andcontrolshadsustainedVLs<1000copies/mL.WesequencedplasmavirusesbySangerandMiSeqnext-generationsequencing(NGS).Weassesseddrugresistancemutations(DRMs)usingtheStanforddrugresistancedatabase,andanalysedNGSdataforDRMsat฀20%,10%,5%and2%thresholds.Weassessedtheeectofpretreatmentdrugresistance(PDR)onVF.RESULTS:Weanalysedsequencesfrom45casesand125controls.OverallprevalenceofPDRdetectedata฀20%thresholdwas4.7%(8/170)andwashigherincasesthanincontrols(8.9%versus3.2%),P=0.210.ParticipantswithPDRat฀20%hadalmost4-foldhigheroddsofVF(adjustedOR3.7,95%CI0.8-18.3)comparedwiththosewithout,P=0.104.PDRprevalenceincreasedto18.2%(31/170)whenLA-DRVsat฀2%wereincluded.ParticipantswithpretreatmentLA-DRVsonlyhad1.6-foldhigheroddsofVF(adjustedOR1.6,95%CI0.6-4.3)comparedwiththosewithout,P=0.398.CONCLUSIONS:PretreatmentDRMsandLA-DRVsincreasedtheoddsofdevelopingVFonNNRTI-basedART,althoughwithoutstatisticalsignicance.NGSincreaseddetectionofDRMsbutprovidednoadditionalbenetinidentifyingparticipantsatriskofVFatlowerthresholds.MorestudiesassessingmutationthresholdspredictiveofVFarerequiredtoinformuseofNGSintreatmentdecisions.DOI:https://doi.org/10.1093/jac/dkaa343PostedattheZurichOpenRepositoryandArchive,UniversityofZurichZORAURL:https://doi.org/10.5167/uzh-191118JournalArticlePublishedVersion
ThefollowingworkislicensedunderaCreativeCommons:Attribution-NonCommercial4.0International(CCBY-NC4.0)License.Originallypublishedat:Chimukangara,Benjamin;Giandhari,Jennifer;Lessells,Richard;Yende-Zuma,Nonhlanhla;Sartorius,Benn;Samuel,Reshmi;Khanyile,KhulekaniS;Stray-Pedersen,Babill;Moodley,Pravi;Metzner,KarinJ;

Padayatchi,Nesri;Naidoo,Kogieleum;DeOliveira,Tulio(2020).Impactofpretreatmentlow-abundanceHIV-1drug-resistantvariantsonvirologicalfailureamongHIV-1/TB-co-infectedindividuals.JournalofAntimicrobialChemotherapy,75(11):3319-3326.DOI:https://doi.org/10.1093/jac/dkaa3432

Impact of pretreatment low-abundance HIV-1 drug-resistant variants
on virological failure among HIV-1/TB-co-infected individuals
Benjamin Chimukangara
1,2,3
*, Jennifer Giandhari
1
, Richard Lessells
1
, Nonhlanhla Yende-Zuma
2,4
,
Benn Sartorius
5,6
, Reshmi Samuel
3
, Khulekani S. Khanyile
1
, Babill Stray-Pedersen
7
†, Pravi Moodley
3
,
Karin J. Metzner
8,9
, Nesri Padayatchi
2,4
, Kogieleum Naidoo
2,4
and Tulio De Oliveira
1,2
1
KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), College of Health Sciences, University of KwaZulu-Natal, Doris
Duke Medical Research Institute, Durban, South Africa;
2
Centre for the AIDS Programme of Research in South Africa (CAPRISA),
University of KwaZulu-Natal, Durban, South Africa;
3
Department of Virology, National Health Laboratory Service, University of
KwaZulu-Natal, Durban, South Africa;
4
South African Medical Research Council (SAMRC), CAPRISA HIV-TB Pathogenesis and Treatment
Research Unit, Durban, South Africa;
5
Public Health Medicine, School of Nursing and Public Health, University of KwaZulu-Natal,
Durban, South Africa;
6
Health Metrics Sciences, University of Washington, Seattle, USA;
7
Institute of Clinical Medicine, University of
Oslo, Oslo University Hospital, Oslo, Norway;
8
Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich,
University of Zurich, Zurich, Switzerland;
9
Institute of Medical Virology, University of Zurich, Zurich, Switzerland
*Corresponding author: E-mail: benjiechim@gmail.com
†Deceased.
Received 17 April 2020; accepted 3 July 2020
Objectives: To determine the impact of pretreatment low-abundance HIV-1 drug-resistant variants (LA-DRVs)
on virological failure (VF) among HIV-1/TB-co-infected individuals treated with NNRTI first-line ART.
Methods: We conducted a case–control study of 170 adults with HIV-1/TB co-infection. Cases had at least one
viral load (VL) 1000 RNA copies/mL after 6months on NNRTI-based ART, and controls had sustained VLs
<1000 copies/mL. We sequenced plasma viruses by Sanger and MiSeq next-generation sequencing (NGS). We
assessed drug resistance mutations (DRMs) using the Stanford drug resistance database, andanalysed NGS data
for DRMs at 20%, 10%, 5% and 2% thresholds. We assessed the effect of pretreatment drug resistance (PDR)
on VF.
Results: We analysed sequences from 45 cases and 125 controls. Overall prevalence of PDR detected at a 20%
threshold was 4.7% (8/170) and was higher in cases than in controls (8.9% versus 3.2%), P= 0.210. Participants
with PDR at 20% had almost 4-fold higher odds of VF (adjusted OR 3.7, 95% CI 0.8–18.3) compared with those
without, P= 0.104. PDR prevalence increased to 18.2% (31/170) when LA-DRVs at 2% were included.
Participants with pretreatment LA-DRVs only had 1.6-fold higher odds of VF (adjusted OR 1.6, 95% CI 0.6–4.3)
compared with those without, P= 0.398.
Conclusions: Pretreatment DRMs and LA-DRVs increased the odds of developing VF on NNRTI-based ART, al-
though without statistical significance. NGS increased detection of DRMs but provided no additional benefit in
identifying participants at risk of VF at lower thresholds. More studies assessing mutation thresholds predictive of
VF are required to inform use of NGS in treatment decisions.
Introduction
The success of scaling-up ART is greatly threatened by the emer-
gence and transmission of HIV drug resistance (HIVDR). HIVDR
that occurs in individuals who have not yet initiated ART, or who
have prior ART use and are re-initiating first-line treatment, is
known as pretreatment drug resistance (PDR).
1,2
PDR is associated
with poor ART outcomes,
3,4
and there is strong evidence suggest-
ing a substantial increase in levels of PDR in southern Africa,
the region with the greatest HIV epidemic.
2,5,6
With evidence of
increasing PDR, the WHO now recommends modifying the stand-
ard first-line ART regimen or introducing pretreatment HIVDR test-
ing when NNRTI-PDR levels reach 10%.
1
V
CThe Author(s) 2020. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecom
mons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original
work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
3319
J Antimicrob Chemother 2020; 75: 3319–3326
doi:10.1093/jac/dkaa343 Advance Access publication 8 August 2020

Changing the standard first-line ART regimen offers a more
feasible alternative option to pretreatment HIVDR testing. The
WHO recommends use of dolutegravir, an integrase strand trans-
fer inhibitor (INSTI), that is cheaper and better tolerated compared
with current NNRTIs.
7–9
Despite this recommendation, concerns
over use of dolutegravir among specific subpopulations remain.
This includes women of child-bearing age, due to potential for
neural tube birth defects occurring when dolutegravir is used at
the time of conception.
10–12
In addition, concerns also exist
regarding co-administration of dolutegravir and TB treatment
among HIV-1/TB-co-infected people, specifically from drug–drug
interactions with rifampicin,
9
and in patients who do not tolerate
dolutegravir.
13
This highlights potential for the continued use of
NNRTIs, and the relevance of assessing the impact of NNRTI resist-
ance mutations on ART.
Sanger sequencing has been the conventional method used for
detecting HIV drug resistance mutations (DRMs). Sanger sequenc-
ing is relatively expensive, and does not reliably detect mutations
that are not well represented, i.e. occurring at <20% of the viral
population.
14,15
With advances in technology, next-generation
sequencing (NGS) is becoming more popular and likely to replace
Sanger sequencing in routine laboratory workflows.
14
NGS allows
for multiplexing of samples, thereby reducing the cost of HIVDR
testing. Furthermore, NGS has the ability to detect low-abundance
drug-resistant variants (LA-DRVs), i.e. mutations occurring in <20%
of the viral population.
14
There is evidence suggesting that NNRTI-PDR detected by
Sanger sequencing results in poor ART outcomes,
16–18
but there
remains limited knowledge around the impact of LA-DRVs on
treatment outcomes, and at different mutation frequencies.
We sought to determine the impact of pretreatment LA-DRVs on
virological failure (VF) among HIV-1/TB individuals treated with
NNRTI-based first-line ART.
Patients and methods
Ethics
This research study was approved by the Biomedical Research Ethics
Committee of the University of KwaZulu-Natal (reference number: BF340/
17). Ethics approvals were also obtained from the Biomedical Research
Ethics Committee of the University of KwaZulu-Natal (reference numbers:
E107/05and BF051/09; Clinicaltrials.gov number NCT 01539005) for studies
from which samples were obtained, and participants gave informed con-
sent for sample storage andre-use.
Study design and study population
This was a nested case–control study aimed at determining the impact of
pretreatment LA-DRVs on NNRTI-based ART outcomes. We defined VF as
having at least one viral load (VL) 1000 HIV-1 RNA copies/mL in plasma
after 6months on NNRTI-based ART. De-identified remnant plasma sam-
ples from HIV-1/TB-co-infected adults (18years) were obtained from the
Starting Antiretroviral therapy at three Points in Tuberculosis (SAPiT) trial,
and from a subsequent study known as the TB Recurrence upon Treatment
with HAART(TRuTH).
The SAPiT trial was an open-label, randomized, controlled trial
conducted by the Centre for AIDS Programme Research in Africa (CAPRISA)
between June 2005 and July 2008, at the eThekwini Clinical Research Site
(ECRS) in Durban, South Africa. The study investigated the effect of ART
started during TB treatment (in two integrated-therapy groups) or after
completion of TB treatment (in one sequential-therapy group) on mortality.
The majority of participants received a once-daily regimen of efavirenz,
lamivudine and didanosine (EFV/3TC/ddI) at ART initiation, but drug
switcheswere allowed during the study. VLs were measured at the time of
screening, at randomization and every 6 months thereafter. SAPiT study
participants wereenrolled into the TRuTH study, a prospective cohort study
conducted between 2009 and 2013. The study aimed to assess TB recur-
rence among participants who were either cured or had successfully com-
pleted their TB treatment after 24months follow-up in SAPiT. Details of the
SAPiT and TRuTH studies have been published previously.
19–21
In this analysis, we defined cases as participants with at least one VL
1000 copies/mL after 6months of initiating an NNRTI-based ART. We
defined controls as participants who had sustained virological suppression
(VL <1000 copies/mL) after at least 6 months on ART (SAPiT ± TRuTH),
and maintained viral suppression throughout the study follow-up period
(5–6years). Pre-ART samples from cases and controls were included in a
1:2 case:control ratio. A simple random sampling strategy was used to se-
lect unmatched controls. If plasma samples were not available for cases at
their first high VL, we accessed a subsequent sample based on availability
of remnant plasma. We excluded participants who had switched from an
NNRTI-based regimen at the time of ART failure.
Laboratory methods
We retrieved plasma samples with VLs 1000 copies/mL from a #80Cbio-
repository and thawed them to roomtemperature prior to viral RNAextrac-
tion. For each sample, we centrifuged 500 lLofplasmaat23000gfor 1 h
at 4C to pellet the virus. We extracted viral RNA from 200lL of pelleted
plasma using a NucliSens EasyMAG HIV-1 (bioMe´rieux, Craponne, France)
extraction system, and amplified the protease and reverse transcriptase
genes using Southern African Treatment Resistance Network custom pri-
mers, as described previously.
22
We purified successfully amplified PCR
products using a QIAquick PCR purification kit (Qiagen, Hilden, Germany),
according to the manufacturer’s instructions. To limit sample variability in
the final sequencing product, we aliquotted purified PCR products of each
sample forSanger sequencing and NGS.
Sanger sequencing
In preparation for capillary electrophoresis, we performedsequencing reac-
tions using a BigDye Terminatorv3.1 kit (Applied Biosystems,Foster City, CA,
USA), and sequencing reaction purifications using a BigDye XTerminator
v3.1 purification kit (Applied Biosystems), according to the manufacturer’s
instructions. We performed capillary electrophoresison an ABI 3730 genet-
ic analyser and assessed the quality of sequences using Geneious software
v8.1.9 (Biomatters Ltd, New Zealand).
23
We excluded sequences with in-
complete reverse transcriptase (codons 1–254) genes, and detected DRMs
using the Stanford UniversityHIV drug resistancedatabase (version 8.6).
24
Next-generation sequencing
For NGS, we determinedPCR product concentrations using a Qubit 3.0 fluor-
imeter (Life Technologies, Malaysia), diluted amplicons to 0.2 ng/lLand
performed library preparation using the Nextera-XT DNA Library
Preparation kit and Nextera Index kit (Illumina, SanDiego, CA, USA), accord-
ing to the manufacturer’s instructions. In summary, library preparation
involved kit-based enzymatic fragmentation of DNA, dual indexing of frag-
mented DNA and bead-based purification of amplicons using AMPure
beads (Beckman Coulter, Brea, CA, USA). We performed quality control
steps using the LabChip GX Touch (PerkinElmer, Hopkinton, MA, USA) to
determine the amplicon size, and used the Qubit 3.0 fluorometer (Life
Technologies, Malaysia) to determine library concentrations. We normal-
ized each sample library to 4 nM concentration, pooled the normalized
libraries and diluted them to a final concentration of 10 pM. We spiked the
Chimukangara et al.
3320

10 pM library with 5% PhiX control, and sequenced it on an Illumina MiSeq
platformusing the MiSeq Nano Reagent Kit v2 (500 cycles).
For paired-end sequencing analysis, we used Genome Detective, a web-
based tool for analysis of molecular sequence data (https://www.genome
detective.com).
25
In summary, the software used Trimmomatic for quality
control in filtering sequences, for adaptor trimming and for checking for
external contamination. It generated gene coverage plots and mapped
them to a default HIV-1 subtype C reference sequence in Genome
Detective. We excluded sequences with <100%depth of coverage or having
incomplete reverse transcriptase (codons 1–254) genes. We aligned the
sequences to an annotated HIV-1C reference sequence, and analysed for
LA-DRVs in Geneious software v8.1.9(Biomatters Ltd, NewZealand).
23
Drug resistance analysis
We determined both Sanger sequencing and NGS DRMs based on the
Stanford University HIV drug resistance database (version 8.6).
24
We esti-
mated HIVDR prevalence at 20%, 10%, 5% and 2% thresholds, and
defined drug resistance as having an NRTI resistance mutation or an NNRTI
resistance mutation. We excluded individuals who did not have both an
NGS and Sanger sequence either at the pre-ART timepoint or at VF. We
excluded PI resistance mutations from our analysis, as none of the partici-
pants selected had initiated PI-based ARTregimen.
Data analysis
We used STATA v13 (StataCorp, College Station, TX, USA) for statistical
analysis. We used the Fisher’s exact test and Wilcoxon rank-sum test (for
categorical and continuous variables, respectively) to compare baseline
demographics (i.e. sex and age) and clinical characteristics (CD4 count, VL,
months on ART and SAPiT randomization arm) betweencases and controls.
We analysed the effect of PDR majority mutations on ART. To determine
the impact of pretreatment LA-DRVs on VF, we excluded PDR majority
mutations (i.e. mutations at 20% threshold) from the analysis. We further
excluded thymidine analogue mutations (TAMs) D67NGE and K219NE, that
do not confer any resistance to didanosine. We used univariable and multi-
variable logistic regression to assess the association between pretreatment
LA-DRVs and VF. The model was adjusted for age,gender, CD4 count at ART
initiation, VL at ART initiation, and randomization. We did not adjust for
time on ART and TB medications, as controls were only sampled prior to
treatment initiation, and TB medications were only taken for 6months at
SAPiT enrolment.
Results
Participant characteristics
We identified 99/642 cases with at least one VL 1000 copies/mL
after receiving ART for at least 6 months, with approximately 50%
(50/99) of the cases having two consecutive VLs 1000
copies/mL. From a total of 543 participants with sustained viro-
logical suppression, we selected 198 controls, giving a total of 297
participants (i.e. 99 cases and 198 controls). Of the 297 partici-
pants, 207 (69 cases and 138 controls) had appropriate samples
available for testing. The median duration on ART for the 69 cases
was 5 years (IQR 4.5–5.6) and the median duration on ART for the
138 controls was 6 years (IQR 5.0–6.3) (Figure S1, available as
Supplementary data at JAC Online). We obtained complete NGS
and Sanger sequence pairs for 170 participants (45 cases and 125
controls) (Figure 1,TableS1). Thirty-two of the 45 (71%) cases
achieved viral suppression at subsequent points including those
who switched ART.
All except two participants (168/170) received EFV/3TC/ddI at
ART initiation. Of the two participants (i.e. controls), one received
efavirenz with zidovudine and lamivudine, and the other received
nevirapine with lamivudine and didanosine at ART initiation.
Table 1summarizes the demographic and clinical characteristics
of the participants included in the final analysis. We did not
observe any significant differences in demographic and clinical
characteristics when comparing cases and controls.
HIV-1 drug resistance data before ART initiation
Overall, of170 pre-ART sequences, all were subtype C. Eight (4.7%)
had at least one DRM detected by Sanger sequencing and by NGS
at a 20% threshold (four cases and four controls). NGS at a
20% threshold (i.e. majority drug resistance) was completely
concordant with Sanger sequencing, so from this point onwards
we only refer to NGS data. Seven of the eight sequences revealed
single class resistance (two NRTI and five NNRTI), the other case
Participants in SAPiT trial
n= 642
Participants selected
n= 297
Participants with samples processed
n= 207
Participants with unsuccessful HIV
genotype
n=37
(Cases, n= 24; Controls, n= 13)
Participants with samples not processed
n=90
(Cases, n= 30; Controls, n= 60)
Failed amplification (22)
Incomplete sequences (15)
Samples unavailable in biorepository (83)
Participants switched to non-NNRTI regimen (7)
Cases (99) a
Controls (198) b
Cases (69)
Controls (138)
Participants included in final analysis
n= 170
Cases (45)
Controls (125)
Figure 1. Summary flow chart of participants from selection to analysis.
a
Cases included all participants enrolled in the SAPiT trial that had viral
loads 1000 copies/mL after 6 months on ART.
b
Controls were ran-
domly selected from SAPiT trial participants to match cases at a 1:2
ratio.
Impact of pretreatment HIV-1 drug resistance on virological failure JAC
3321

harboured both NRTI and NNRTI resistance. The most common
mutations (K103N and V108I) were detected in 3/8 pre-ART
sequences (Table S2). Table 2summarizes the pre-ART drug class
mutations observed by NGS at different mutation thresholds.
Figure 2shows the prevalence of majority DRMs and LA-DRVs at
pre-ART, in cases and controls, respectively.
Impact of pretreatment majority DRMs and LA-DRVs
on VF
The overall prevalence of pretreatment majority DRMs was higher
in cases than in controls (8.9% versus 3.2%), P=0.210.Overallme-
dian time to VF among cases was 15.5 months (IQR 9.2–29.2).
Cases with PDR at a 20% threshold had a shorter median time to
VF (9.4 months, IQR 8.4–14.7) compared with cases without PDR
mutations (16.3 months, IQR 9.2–30.4), P= 0.151. Participants
with pretreatment majority DRMs (i.e. at a 20% threshold) had
almost 4-fold higher odds of VF [adjusted OR (aOR) 3.7, 95% CI
0.8–18.3] compared with those without (P= 0.104). PDR preva-
lence increased to 18.2% (31/170) when LA-DRVs at 2% were
included (24.4% among cases and 16.0% among controls),
P= 0.260. Of the 170 pre-ART sequences, 23 (13.5%, 7 cases and
16 controls) had LA-DRVs only (i.e. mutations at 2% to <20%),
2 with dual class resistance and 21 withsingle class resistance, i.e.
NRTI (15) and NNRTI (6) resistance. Participants with pretreatment
LA-DRVs had 1.6-fold higher odds of VF (aOR 1.6, 95% CI 0.6–4.3)
compared with those without (P= 0.398). The pre-ART LA-DRVs
were as follows: 10.0% (17/170) for NRTIs (6 cases and 11 con-
trols) and 4.7% (8/170) for NNRTIs (2 cases and 6 controls). The
most common pre-ART DRM was K65R, occurring in 6 of 170
(3.5%) sequences (Figure2a). The median frequency of K65R at
pre-ART was 2.8% (IQR 2.2–3.1), and it occurred as the only muta-
tion in five of the six sequences.
Twenty-eight of 31 (90%) participants harboured pretreatment
NRTI- and/or NNRTI-LA-DRVs that are associated with resistance
to the ART regimen the participants were taking. Of those, only
Table 1. Baseline characteristics of participants included in the final analysis
Characteristic
Total
(n= 170)
Cases
(n= 45)
Controls
(n= 125) Pvalue
Female, n(%) 99 (58.2) 29 (64.4) 70 (56.0) 0.326
Age in years, median (IQR) 34 (29–40) 35 (27–39) 34 (29–41) 0.420
Viral load (log
10
copies/mL), median (IQR)
a
5.3 (4.8–5.7) 5.2 (4.8–5.7) 5.3 (4.8–5.7) 0.496
CD4 count (cells/mm
3
), median (IQR) 141 (58–224) 107 (42–219) 150 (83–225) 0.148
Treatment arms
b
early integrated, n(%) 50 (29.4) 12 (26.7) 38 (30.4)
late integrated, n(%) 65 (38.2) 17 (37.8) 48 (38.4)
sequential, n(%) 55 (32.4) 16 (35.6) 39 (31.2)
Baseline refers to time of enrolment in the SAPiT trial.
a
One case and two controls with missing viral loads prior to ART initiation.
b
Early integrated arm, ART initiated within a month of starting TB treatment; late integrated arm, ART initiated within a month of completing inten-
sive phase of TB treatment; sequential arm, ART initiated within a month of completing the continuation phase of TB treatment.
Table 2. Proportion of pre-ART NRTI and NNRTI resistance by NGS mutation thresholds
Detection threshold
Characteristics 2% 5% 10% 20%
Overall resistance (n=170)
Any resistance, n(%) 31 (18.2) 13 (7.7) 11 (6.5) 8 (4.7)
Any NRTI resistance, n(%) 19 (11.2) 6 (3.5) 5 (2.9) 2 (1.2)
Any NNRTI resistance, n(%) 15 (8.8) 8 (4.7) 7 (4.1) 7 (4.1)
Cases (n=45)
Any resistance, n(%) 11 (24.4) 7 (15.6) 7 (15.6) 4 (8.9)
Any NRTI resistance, n(%) 7 (15.6) 2 (4.4) 1 (2.2) 1 (2.2)
Any NNRTI resistance, n(%) 6 (13.3) 5 (11.1) 4 (8.9) 4 (8.9)
Controls (n=125)
Any resistance, n(%) 20 (16.0) 6 (4.8) 4 (3.2) 4 (3.2)
Any NRTI resistance, n(%) 12 (9.6) 4 (3.2) 4 (3.2) 1 (0.8)
Any NNRTI resistance, n(%) 9 (7.2) 3 (2.4) 3 (2.4) 3 (2.4)
NGS, next-generation sequencing.
Chimukangara et al.
3322

three cases showed selection of LA-DRVs to majority DRMs at VF.
The LA-DRVs selected for were K65R, L74I and V106AI mutations.
The NNRTI mutation V106AI became a majority V106M mutation
at VF in two cases, whilst the NRTI mutation L74I became a
majority L74V mutation in one case, and the NRTI mutation K65R
became a majority DRM in one case (Table S3). Despite K65R occur-
ring as the most common DRM at pre-ART, the mutation was only
selected for in one of the three cases.
Drug resistance data at virological failure
At VF, 80.0% (36/45) had majority DRMs (i.e. a 20% threshold),
and the proportion increased to 84.4% (38/45) when LA-DRVs at
2% were included. Of the 36 with majority DRMs, 27 had dual class
resistance and 9 had single class NNRTI resistance. The most
common majority NNRTI mutation at VF was V106MI, occurring in
48.9% (22/45) of sequences, whilst M184VI was the most com-
mon NRTI mutation, occurring in 46.7% (21/45) of sequences.
None of the baseline characteristics (i.e. sex, age, CD4 counts, VLs
and study arm) was associated with VF (Table S4).
Discussion
In this analysis, we observed an increase in odds ofVF among indi-
viduals with either pre-ART majority DRMs or LA-DRVs compared
with those without, although without statistical significance. We
observed that lowering the mutation detection threshold
increased the detection of DRMs but had no additional benefit
in identifying participants at risk of VF. We also observed that
early versus delayed ART with rifampicin-based TB treatment did
not enhance VF or the acquisition of DRMs (Table S4). However, our
7.0
6.0
5.0
4.0
Drug resistance mutation prevalence (%)
3.0
2.0
1.0
0.0
V106AIM
V108I
G190EV
K103N
K101E
V179D
F227L
K238T
K65R
K70R
T215AI
L74I
F77L
K219EN
D67EGN
K103N
V179D
A98G
V108I
H221Y
K65R
M184V
L74I
T215A
NNRTI mutations NRTI mutations
Mutations detected in cases at pre-ART
(a
)
(b)
Mutations detected in controls at pre-ART
Major mutations
Minor variants
Major mutations
Minor variants
NNRTI mutations NRTI mutations
7.0
6.0
5.0
4.0
Drug resistance mutation prevalence (%)
3.0
2.0
1.0
0.0
Figure 2. (a) Drug resistance mutations detected in cases with pre-ART resistance. (b) Drug resistance mutations detected in controls with pre-ART
resistance. Major mutations represent mutations detected at frequencies of 20% threshold, and minor variants represents mutations detected at
frequencies of between 2% and <20%.
Impact of pretreatment HIV-1 drug resistance on virological failure JAC
3323

definition of VF as having at least one VL 1000 copies/mL after
6 months on ART means that the proportions of DRMs reported
are likely not to be reflective of those observed in people with pro-
longed viraemia on ART. This is considering that some participants
might have suppressed their VL following intervention and there-
fore would not be ordinarily classified as VFs. Also, the lack of ART
adherence data in this analysis means that we could not rule out
poor ART adherence as a cause of VF amongst the cases.
A recent systematic review by the WHO HIVResNet working
group showed that the majority of published studies (14 of 25)
have reported no significant association between LA-DRVs and VF,
among individuals exposed to first-line NNRTI-based regimens.
18
However, 11 of the 25 studies showed a higher risk of VF when indi-
viduals harbour NNRTI LA-DRVs prior to treatment initiation,
18
sug-
gesting that LA-DRVs still play an important role in treatment
response. The ANRS 12249 trial showed that having dual class
resistance (NRTI and NNRTI) at 5% increased the time to viral
suppression by almost 12 months (IQR 2.76–16.39) compared
with not having PDR (median 3.48 months; IQR 2.79–5.78),
26
an
outcome we could not determine in our study due to only three
participants having dual class pretreatment LA-DRVs. However,
despite the increased risk of VF with LA-DRVs at 5%, the ANRS
12249 trial further suggested that a combination of potent NRTI
drugs with an NNRTI, coupled with good ART adherence, could re-
sult in short-term virological suppression even in the presence of
pretreatment NNRTI DRMs.
26
Controversy remains around the effect of pretreatment
LA-DRVs on ART, as shown previously in the OCTANE trials. The
OCTANE/A5208 trial 1,
27
done among women that had prior
exposure to single dose nevirapine (sdNVP), suggested that pre-
treatment LA-DRVs have a significant impact on ART outcomes,
whilst the follow-up OCTANE trial 2 showed no such impact among
women without prior exposure to sdNVP.
28
The contradiction sug-
gested that prior exposure to NNRTIs before ART initiation
increases the mutant population size that can be selected for on
NNRTI-based ART. This is supported by PDR data from a Kenyan
cohort study showing that the number of pretreatment NNRTI
mutationsand their frequency (in a sample isolate) determine the
risk of treatment failure, with a greater risk among individuals on
nevirapine-based ART compared with efavirenz-based ART.
29
Given that any history of previous prevention of mother-to-child
transmission (PMTCT) of HIV was not available, and noting the
demographic distribution of participants included, it is likely that
some women included in our analyses had undisclosed prior ART
exposure for PMTCT.
The differences observed in the impact of pretreatment
LA-DRVs on ART outcomes can be attributed to several factors. The
WHO HIVResNet working group identified factors such as: the
method of detecting HIVDR mutations; the analyses of mutations
affecting one or more drug classes; the inclusion in some cases of
majority DRMs; different mutation cut-off thresholds; variability in
the stage of PDR detection; and differences in the number of
individuals included in each study.
18
Therefore, lower frequency
thresholds of mutations should be interpreted with caution.
A multicountry nested case–control study showed a reduction in
specificity from 98% (95% CI 95%–99%) at a 20% threshold, to
92% (95% CI 88%–95%) at a 1% threshold,
30
suggesting that the
accuracy of resistance as a predictor of VF decreases with a
reduction in the detection threshold. Such reductions in specificity
could result in unnecessary modification of ART regimens, war-
ranting the need for careful consideration of the benefits and
shortcomings of detecting LA-DRVs for public health purposes.
The most common NNRTI mutations at VF occurred at positions
where mutations are known to be highly selected for by efavirenz
(i.e. positions 103, 106, 188 and 190),
24
suggesting adequate drug
pressure for the selection of NNRTI DRMs. However, of greater rele-
vance to the current ART programmes are NRTI resistance muta-
tions. As more countries (including South Africa) roll out
dolutegravir in combination with tenofovir and lamivudine (also
known as TLD), ensuring the potency of the NRTI drugs is impera-
tive to the success of the new ART regimen. The K65R mutation
which causes high levels of resistance to tenofovir and intermedi-
ate resistance to lamivudine
24
is of greater concern in the TLD
regimen. We detected the K65R mutation at a frequency of only
2%–5% pre-ART, evolving to a majority DRM in only one out of the
three participants, and therefore we could not assess its impact on
VF, with didanosine treatment. However, continued monitoring
of NRTI resistance is warranted in order to avoid potential dolute-
gravir functional monotherapy due to pre-existing NRTI DRMs.
Moreover, despite dolutegravir replacing NNRTIs in first-line ART,
monitoring NNRTI resistance remains important in specific subpo-
pulations, such as women of child-bearing age, HIV-1/TB-treated
individuals and those who do not tolerate dolutegravir.
The findings from this study should be interpreted with consid-
eration of the following limitations. Basing VF on only one VLresult
is not conventional. However, 84% (38/45) of the cases in this
study already had majority DRMs, with over half of them having
dual class NRTI and NNRTI resistance at VF, suggesting the need
to consider early VL monitoring and switching of ART regimens be-
fore the accumulation of DRMs.
31
Secondly, about 43% (127/297)
of the selected participants ended up being excluded from the
analysis (Figure 1) due to the unavailability of stored samples and
unsuccessful genotyping. However, there was no significant differ-
ence between the participants included and those excluded
among the cases (Table S1). Lastly, most participants in this study
initiated ART on didanosine, a drug that is not commonly used in
current regimens.
In conclusion, in a population of individuals treated for HIV-1/TB
initiated on NNRTI-based ART, we found that pretreatment
LA-DRVs increased the odds of VF, although without statistical
significance. Despite the ability of NGS to detect lower frequency
mutations, LA-DRVs must be interpreted with caution to avoid mis-
classification of people as being at risk of VF and hence unneces-
sary modification of ART regimens. More studies investigating the
impact of LA-DRVs on ART are required, including individuals with
different clinical characteristics, and considering variables such
as the time to VF due to outgrowth of LA-DRVs, the role of viral
mutational loads and specific mutation cut-off thresholds that can
inform use of NGS in guiding HIV treatment decisions at a public
health level.
Acknowledgements
We thank participants of the SAPiT and TRuTH studies at the eThekwini
Clinic. We acknowledge support from the South Africa Medical Research
Council (SAMRC), Poliomyelitis Research Foundation (PRF), Letten
Chimukangara et al.
3324

Foundation (Norway), Stanford–SPARK program (Stanford University
Medical), the Technology Innovation Agency (TIA) and the National
Health Laboratory Services, Department of Virology, at the University of
KwaZulu-Natal.
This manuscript is dedicated to Babill Stray-Pedersen (1943–2019).
Funding
This work was supported by a flagship grant from the South African
Medical Research Council (MRC-RFA-UFSP-01-2013/UKZN HIVEPI), and
the Centre for AIDS Programme Research in South Africa (CAPRISA). The
TRuTH study was funded by the Howard Hughes Medical Institute, grant
55007065, and the Centers for Disease Control and Prevention (CDC)
cooperative agreement UY2G/PS001350-02. Patient care was supported
by the KwaZulu-Natal Department of Health and the US President’s
Emergency Plan for AIDS Relief (PEPFAR).
Transparency declarations
None to declare.
Supplementary data
Figure S1 and Tables S1 to S4 are available as Supplementary data at
JAC Online.
References
1World Health Organization 2017. Guidelines on the public health response
to pretreatment HIV drug resistance. https://apps.who.int/iris/bitstream/han
dle/10665/255880/9789241550055-eng.pdf?sequence=1.
2Gupta RK, Gregson J, Parkin N et al. HIV-1 drug resistance before initiation
or re-initiation of first-line antiretroviral therapy in low-income and middle-
income countries: a systematic review and meta-regression analysis. Lancet
Infect Dis 2018; 18: 346–55.
3Wittkop L, Gu¨ nthard HF, de Wolf F et al. Effect of transmitted drug resist-
ance on virological and immunological response to initial combination anti-
retroviral therapy for HIV (EuroCoord-CHAIN joint project): a European
multicohort study. Lancet Infect Dis 2017; 11: 363–71.
4Hamers RL, Schuurman R, Sigaloff KCE et al. Effect of pretreatment
HIV-1 drug resistance on immunological, virological, and drug-
resistance outcomes of first-line antiretroviral treatment in sub-
Saharan Africa: a multicentre cohort study. Lancet Infect Dis 2012; 12:
307–17.
5Rhee S-Y, Blanco JL, Jordan MR et al. Geographic and temporal trends in
the molecular epidemiology and genetic mechanisms of transmitted HIV-1
drug resistance: an individual-patient and sequence-level meta-analysis.
PLoS Med 2015; 12: e1001810.
6Chimukangara B, Lessells R, Rhee S-Y et al. Trends in pretreatment
HIV-1 drug resistance in antiretroviral therapy-naive adults in South
Africa, 2000–2016: a pooled sequence analysis. EClinicalMedicine 2019;
9: 26–34.
7Venter WDF, Clayden P, Serenata C. The ADVANCE study: a groundbreaking
trial to evaluate a candidate universal antiretroviral regimen. Curr Opin HIV
AIDS 2017; 12: 351–4.
8Clinton Health Access Initiative 2017. ARV market report: The state of the
antiretroviral drug market in low- and middle-income countries, 2016–2021.
https://clintonhealthaccess.org/wp-content/uploads/2017/09/2017-ARV-
Market-Report_Final-2.pdf.
9World Health Organization 2019. Policy brief: Update of recommendations
on first- and second-line antiretroviral regimens. https://apps.who.int/iris/bit
stream/handle/10665/325892/WHO-CDS-HIV-19.15-eng.pdf?ua=1.
10 Zash R, Makhema J, Shapiro R. Neural-tube defects with dolutegravir
treatment from the time of conception. NEnglJMed2018; 379: 979–81.
11 WorldHealthOrganization2018.Policy brief: Updated recommendations
on first-line and second-line antiretroviral regimens and post-exposure
prophylaxis and recommendations on early infant diagnosis of HIV. http://
apps.who.int/iris/bitstream/handle/10665/273632/WHO-CDS-HIV-18.18-
eng.pdf?ua=1.
12 Dorward J, Lessells R, Drain P et al. Dolutegravir for first-line antiretroviral
therapy in low-income and middle-income countries: uncertainties and
opportunities for implementation and research. Lancet HIV 2018; 5: e400–4.
13 de Boer MGJ, van den Berk GEL, van Holten N et al. Intolerance of
dolutegravir-containing combination antiretroviral therapy regimens in real-
life clinical practice. Aids 2016; 30: 2831–4.
14 Chimukangara B, Samuel R, Naidoo K et al. Primary HIV-1 drug-resistant
minority variants. AIDS Rev 2017; 19: 89–96.
15 Tang MW, Shafer RW. HIV-1 antiretroviral resistance: scientific principles
and clinical applications. Drugs 2012; 72: e1–25.
16 Kantor R, Smeaton L, Vardhanabhuti S et al. Pretreatment HIV drug re-
sistance and HIV-1 subtype C are independently associated with virologic fail-
ure: results from the multinational PEARLS (ACTG A5175) clinical trial. Clin
Infect Dis 2015; 60: 1541–9.
17 A
´vila-Rı´o s S, G ar cı´a-Morales C, Matı´as -Flor en ti no M et al. Pretreatment
HIV-drug resistance in Mexico and its impact on the effectiveness of first-line
antiretroviral therapy: a nationally representative 2015 WHO survey. Lancet
HIV 2016; 3: e579–e591.
18 Mbunkah HA, Bertagnolio S, Hamers RL et al. Low-abundance drug-
resistant HIV-1 variants in antiretroviral drug-naive individuals: a systematic
review of detection methods, prevalence, and clinical impact. JInfectDis
2019; 221: 1584–97.
19 Abdool Karim SS, Naidoo K, Grobler A et al. Timing of initiation of antiretro-
viral drugs during tuberculosis therapy. NEnglJMed2 010; 362: 697–706.
20 Padayatchi N, Abdool Karim SS, Naidoo K et al. Improved survival in
multi-drug resistant tuberculosis patients receiving integrated TB and ART in
the SAPiT Trial. Int J Tuberc Lung Dis 2014; 18: 147–54.
21 Sivro A, McKinnon LR, Yende-Zuma N et al. Plasma cytokine predictors of
tuberculosis recurrence in antiretroviral-treated human immunodeficiency
virus-infected individuals from Durban, South Africa. Clin Infect Dis 2017; 65:
819–26.
22 Manasa J, Danaviah S, Pillay S et al. An affordable HIV-1 drug resistance
monitoring method for resource limited settings. JVisExp2014; 51242.
23 Kearse M, Moir R, Wilson A et al. Geneious basic: an integrated and ex-
tendable desktop software platform for the organization and analysis of se-
quence data. Bioinformatics 2012; 28: 1647–9.
24 Liu TF, Shafer RW. Web resources for HIV type 1 genotypic-resistance test
interpretation. Clin Infect Dis 2006; 42: 1608–18.
25 Vilsker M, Moosa Y, Nooij S et al. Genome detective: an automated sys-
tem for virus identification from high-throughput sequencing data.
Bioinformatics 2018; 35: 871–3.
26 Derache A, Iwuji C, Baisley K et al. Impact of next generation
sequencing defined HIV pre-treatment drug resistance on virological
outcomes in the ANRS 12249 treatment as prevention trial. Clin Infect
Dis 2018; 69: 207–14.
27 Boltz VF, Zheng Y, Lockman S et al. Role of low-frequency HIV-1 var-
iants in failure of nevirapine-containing antiviral therapy in women pre-
viously exposed to single-dose nevirapine. Proc Natl Acad Sci USA 2011;
108: 9202–7.
Impact of pretreatment HIV-1 drug resistance on virological failure JAC
3325

28 Boltz VF, Bao Y, Lockman S et al. Low-frequency nevirapine (NVP)-resist-
ant HIV-1 variants are not associated with failure of antiretroviral therapy in
women without prior exposure to single-dose NVP. JInfectDis2014; 209:
703–10.
29 Beck IA, Levine M, McGrath CJ et al. Pre-treatment HIV-drug resistance
associated with virologic outcome of first-line NNRTI-antiretroviral therapy: a
cohort study in Kenya. EClinicalMedicine 2020; 18: 100239.
30 Inzaule SC, Hamers RL, Noguera-Julian M et al. Clinically relevant thresh-
olds for ultrasensitive HIV drug resistance testing: a multi-country nested
case–control study. Lancet HIV 2018; 5: e638–46.
31 Shroufi A, Van Cutsem G, Cambiano V et al. Simplifyingswitchtosecond-
line antiretroviral therapy in sub Saharan Africa: predicted effect of using a
single viral load to define efavirenz-based first-line failure. Aids 2019; 33:
1635–44.
Chimukangara et al.
3326