NNRTI polymorphisms and response to
NNRTI-based ART
Lucy Garvey, Linda Harrison, Peter Tilston, Andrew Phillips,
Caroline Sabin, Anna Maria Geretti, David Dunn, Nicola
Mackie
Background
Polymorphisms occur at codons within regions 90-108, 179-190 and
225-348 in ARV-naive individuals
Although some confer low-level resistance to NNRTIs in vitro, their
impact on virological response remains unclear
Aims
1. To determine the prevalence of polymorphisms at the following
codons* in ARV-naive subjects:
90
98
100
101
103
106
108
138
179
181
188
190
225
227
230
234
236
238
318
2. To assess their impact on early virological response to NNRTI-based
therapy
* IAS Dec 2008 and Stanford database http://hivdb.stanford.edu accessed 07 Jan 2010
348
Population
ARV-naive patients starting NNRTI-based Rx with WT or polymorphisms
only on baseline genotype (any major RT mutation excluded)
Analysis
Assess early virological response at week 4 (approx timing wk 2-6):
WT versus any polymorphism
WT versus individual codon (irrespective of amino acid mutation)
Results to date
2235 eligible subjects
1221 (55%) at least one polymorphism
Most frequently seen at codons 135 (39%), 179 (10%), 98 (8%)
Average 2.4 log10 drop by wk 4
Polymorphism
Difference in reduction in viral load at week 4
238
n=35
179
n=217
138
n=79
135
n=877
106
n=51
103
n=35
101
n=39
98 n=176
90 n=71
-.5
-.25
0
.25
Average effect on reduction in viral load at week 4
.5
Proposed Further Analysis
Details on demographics including: calendar year, first-line ARV details
(EFV or NVP), HIV subtype
Assess time to VL<50 copies/mL:
WT versus any polymorphism
WT versus individual codon
Look at number of polymorphisms per patient
Prevalence of PI mutations in
HIV-infected UK adults treated with
ritonavir-boosted lopinavir as their first PI
Tristan Barber, David Dunn, Linda Harrison,
Loveleen Bansi, Ian Williams, Deenan Pillay
Background
• Little is known about the clinical significance of PI
mutations for successful sequencing of PIs
• The Quest laboratory database reported a novel LPV
resistance pathway with L76V1
• Looked at data from the UK HIV Drug Resistance
Database linked to the UK CHIC study for:
– patients failing LPV/r containing ART with demonstrable
resistance
– the prevalence of L76V
– other novel resistance mutations
1Nijhuis,
et al. Failure of treatment with first line lopinavir boosted with ritonavir can be explained by novel resistance
pathways with protease mutation 76V. JID 2009; 200: 698-709.
Methods
Population
– PI naïve adults, starting LPV/r as their first PI
Virological failure
– viral load >400 c/ml after previously being <400
– OR viral load >400 c/ml for the first 6 months of LPV/r
– Patients were censored if they stopped LPV/r or started
another PI
Resistance
– For those failing, we looked for resistance tests
– Resistance was defined as ≥1 major PI mutation on the
IAS list (Dec 2008)
Results
• N = 3056
Time to rebound
1.00
Probability of not rebounding
• Previous ART:
1580 (52%) naïve
569 (19%) NNRTI HAART
907 (30%) other
• 811 (27%) rebounded:
370 (23%) naïve
139 (24%) NNRTI HAART
302 (33%) other
0.75
0.50
0.25
0.00
0
3
6
9
12 15 18 21 24
Analysis Time (months)
27
Previous ART
naive
other
NNRTI HAART
30
33
36
Resistance
• Of 811 rebounding:
291 (36%) had
resistance tests
• Of 291 with tests:
32 (11%) had PI
resistance
• 3 had L76V
V82A
5
Q58E
3
M46L
M46L
L90M
I84V
V82A
L33F
V32I
L33F
M46L
V32I
M46I
M46I
M46I
M46I
M46L
L33F
M46I
M46I/L
M46L
I47V
L76V
V82T
I84V
M46L
M46I
M46L
V82T
M46I
L76V
V82A
L76V
I84V
T74P
2
2
2
V82A
I47A/V
V82A
I84V
I47A
I84V
V82S
I84V
V82A
L90M
L90M
L90M
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Outcomes of 2nd line ART: 1st
line NNRTI to 2nd line PI/r
Laura Waters, David Asboe, Anton Pozniak, Loveleen
Bansi, Chloe Orkin, Erasmus Smit, Esther Fearnhill
& Andrew Phillips.
UK Resistance Database and UK CHIC Study
Background
• A combination of 2 NRTI + 1 NNRTI is the most
common first line regimen worldwide
• Treatment failures continue to occur
• Second line regimens are usually PI/r based and
should include at least 2 active agents1
• Unclear how many active NRTI are necessary with
2nd line PI/r based therapy
1) 2008 BHIVA Guidelines
Objectives
• To identify factors associated with failing 2nd line,
ritonavir boosted PI-based ART
• To investigate the importance of the number of new
or fully active NRTI started at 2nd line
Methods 1
• Eligibility
Patients failing first line NNRTI-ART (VL >200
copies/ml after 4 months) and starting PI/r for the first
time
• Exclusions
• VL<200 copies/ml at start of 2nd line
• <4 months follow up
• failed new NRTI between first and second-line
therapy
Methods 2
• Virological failure of 2nd line ART was defined as
VL>200 copies/ml despite 4 months continuous use
• NRTI GSS calculated for 2nd line regimens using
Stanford
• Statistical Analyses:
•Kaplan-Meier: time to failing 2nd line HAART
•Logistic regression: identify factors associated
with having a resistance test
•Cox regression: identify factors associated with
failing 2nd line HAART
Patients starting
new drugs 2nd line
(n = 1103)
Started non-PI/r
regimen 2nd line
(n = 502)
Started PI/r
Regimen 2nd line
(n = 601)
Excluded
HIV-RNA <200 at 2nd line
<4 months follow-up
Failed new NRTI between
1st and 2nd line
Eligible for Study
(n = 403)
100
56
42
Unboosted PI
New NNRTI
New NRTI only
Other
45
138
318
1
Time to failing 2nd line HAART
222/403 (55.1%) experienced virological failure of 2nd line
1
0.8
0.6
0.4
0.2
0
0
12
24
36
48
60
72
84
Months since starting 2nd line HAART
96
Independent factors associated with failure of 2nd
line HAART (N=403)
HR (95% CI)
P-value
Age at start of 2nd line (years)
Per 10 years older
1.08 (0.86, 1.34)
0.52
Time from failing 1st line to
starting 2nd line
Per 1 month increase
1.01 (1.00, 1.03)
0.07
Number of new nucleosides
started at 2nd line1
0
1
>2
0.83 (0.51, 1.33)
1.11 (0.79, 1.56)
1
0.44
0.56
-
Ethnicity
White
Black
Other
1
0.95 (0.60, 1.51)
0.52 (0.24, 1.12)
0.95
0.52
Sex/Exposure
MSM
Hetero male
Hetero female
Other
1
1.93 (1.17, 3.20)
2.33 (1.26, 4.02)
1.59 (0.62, 2.80)
0.01
0.002
0. 11
0.94 (0.86, 1.02)
0.15
VL<200 after failing 1st line and before starting 2nd line
0.76 (0.47, 1.24)
0.28
CD4 at 2nd line (cells/mm3)
VL at 2nd line (copies/ml)
0.89 (0.83, 0.94) <0.0001
1.23 (1.06, 1.42)
0.01
Year of starting 2nd line
1 HR=1.00
Per 1 year increase
Per 50 cells higher
Per 1 log increase
(0.82, 1.21), p=0.99 if fitted as a continuous variable
GSS amongst those who had a resistance test
performed (N=211)
Patients not receiving any NRTIs (N=5) excluded
Failed 2nd line HAART
GSS
All
No
Yes
121
90
<1
33 (15.6)
20 (60.6)
13 (39.4)
1.25-1.75
71 (33.6)
42 (59.2)
29 (40.9)
>2
107 (50.7)
59 (55.1)
48 (44.9)
1 Chi-squared
test
P-value
0.801
Independent factors associated with failure of 2nd
line HAART (N=211)
HR (95% CI)
NRTI GSS1
P-value
<1
1.25-1.75
>2
Per 1 month increase
0.73 (0.37, 1.41)
0.70 (0.42, 1.15)
1
1.01 (0.99, 1.02)
0.34
0.16
Age at start of 2nd line (years)
Per 10 years older
1.29 (0.94, 1.79)
0.12
Ethnicity
White
Black
Other
MSM
Hetero male
Hetero female
Other
Per 1 year increase
1
0.61 (0.30, 1.23)
0.61 (0.23, 1.59)
1
2.53 (1.14, 5.63)
2.79 (1.28, 6.08)
1.32 (0.60, 2.90)
0.97 (0.86, 1.10)
0.17
0.31
0.02
0.01
0.50
0.67
VL<200 after failing 1st line and before starting 2nd line
0.63 (0.31, 1.27)
0.19
CD4 at 2nd line (cells/mm3)
VL at 2nd line (copies/ml)
0.85 (0.77, 0.95)
1.26 (0.99, 1.59)
0.004
0.06
Time from failing 1st line to
starting 2nd line
Sex/Exposure
Year of starting 2nd line
1 HR=1.14
Per 50 cells higher
Per 1 log increase
(0.76, 1.72), p=0.51 if fitted as a continuous variable
0.44
Summary
• Of 403 patients who started 2nd line PI/r, 216 (54%)
patients had a resistance test performed after failing
1st line HAART
• NRTI GSS was >2 for 50% of patients with
resistance tests performed
• Neither NRTI GSS nor the number of new NRTI
started at 2nd line were associated with virological
failure of 2nd line HAART
Conclusions
• Among patients who have failed an NNRTI 1st line
then started a PI/r 2nd line there was extensive
variability in the number of new NRTI started, hence
in the predicted activity of the NRTI backbone
• We found little evidence that:
• number of new NRTI started
•predicted NRTI activity within the regimen,
were associated with risk of virologic failure of the
2nd line regimen
Conclusions
• These findings may reflect:
• the strong potency of the PI/r component and/or
• a negative impact of initiating more new agents
in terms of tolerability and/or adherence
• However, further analyses are required to more
extensively explore this lack of association before
drawing firm conclusions
Prevalence and patterns of Raltegravir resistance
in treated patients in Europe- CORONET Study.
•CORONET
-European collaborative study in area of integrase resistance
- repository of integrase sequences from 9 European centres and 2 multicentre repositories (UK Drug Resistance database/ EuResist database).
•AIM
- To survey patients experiencing virological failure on Raltegravir (RAL)
based regimen within CORONET, and to assess the influence of HIV-1
subtype on patterns of RAL genotypic resistance that emerge.
•Study Group
Integrase sequences available for: 255 patients- viraemic on RAL- based
therapy plus 591 patients- prior to starting RAL- based therapy.
- Analysis included major INI resistance-associated mutations (T66I, E92Q,
F121Y, G140A/S, Y143R/C,S147G, Q148H/R/K and N155H) other nonclassic mutations at the same codons and mutations implicated in INI
resistance in vivo or in vitro (codons 51, 54, 68, 74, 95, 97, 114, 125, 128,
138, 145, 146, 151, 153, 154, 157, 160, 163, 203, 230, 263).
Distribution of HIV-1 subtypes among INI experienced
and naïve patients.
Treatment experienced
Treatment naive
Prevalence and patterns of major Raltegravir Associated
Mutations (RAMs) in INI-experienced patients (n=255).
RAM
Number
(%)
Subtype
T66I
E92Q
F121Y
G140A
of RAMs
0
9
0
4
(0.0)
(3.5)
(0.0)
(1.6)
G140S
Y143R
34
9
(13.3)
(3.5)
Total
114
(44.7)
RAM
Number
(%)
Subtype
B, G
Y143C
S147G
Q148H
Q148R
of RAMs
4
1
28
16
(1.6)
(0.4)
(11.0)
(6.3)
B
B
B
B, C, G
B
B, C,F
Q148K
N155H
1
57
(0.4)
(22.4)
B
A,B, C, D, F, G,
CRF02
B, C, G
Table 1: Prevalence of major integrase inhibitor RAMs in INI experienced patients.
RAM
Number
pattern
E92Q
E92Q + N155H
G140S
G140A/S + Q148 H/R/K
of RAMs
1
8
1
36
(%)
RAM
Number
(%)
(0.4)
(3.1)
(0.4)
(14.1)
pattern
Y143R +N155H
S147G + Q148H
Q148H/R/K
Q148H + N155H
of RAMs
1
1
6
1
(0.4)
(0.4)
(2.4)
(0.4)
G140S + Q148H + N155H
1
(0.4)
N155H
46
Y143R/C
12
(4.7)
Total
114
Table 2: Patterns of major integrase inhibitor RAMs in INI experienced patients.
(18.0)
(44.7)
Non-classic mutations at major INI resistance codons detected in
INI-experienced patients (n=255).
RAM
Number
(%)
Subtype
RAM
Number (%)
Subtype
Y143H/A/S
S147I
Q148
N155D/Q
of
RAMs
5
1
0
2
B, D
B
B
of RAMs
T66
E92A/P
F121
G140
0
2
0
0
(0.0)
(0.8)
(0.0)
(0.0)
B
-
(2.0)
(0.4)
(0.0)
(0.8)
Prevalence of other mutations implicated in INI- resistance
among INI experienced patients n=255.
Mutation
Number
(%)
Major INI Mutation
RAMs
Number
(%)
Major INI RAMs
H51Y
V54I
L68I/V
L74I/M
Q95K
1
1
1
22
2
(0.4)
(0.4)
(0.4)
(8.6)
(0.8)
13/22
2/2
Q146P
V151I*
M154I/L
E157Q
K160Q/T
1
25
28
6
8
(0.4)
(9.8)
(11.0)
(2.4)
(3.1)
1/1
19/25
14/28
4/6
5/8
T97A*
T125A/V
20
114
(7.9)
(44.7)
16/20
48/114
G163E/R
I203M
17
13
(6.7)
(5.5)
11/17
9/9
E138D/K*
12
(4.7)
11/12
S230N
17
(7.2)
9/9
P145L
1
(0.4)
1/1
*P value< 0.0001 vs. INI- naive patients. (Fisher’s exact test)
Novel mutations associated with INI experience.
Mutation
INI- experienced
INI- naive
n (%)
n (%)
P value
K159Q/R
I161L/M/N/T/V
4 (1.6)
6 (2.4)
0 (0.0)
1 (0.2)
0.008
0.004
E170A/G
4 (1.6)
0 (0.0)
0.008
*P values by Fisher’s exact test
Conclusions.
• 55.3% of viraemic patients on RAL lacked major INI resistanceassociated mutations- overall, 114/255 (44.7%) RAL experienced
patients had ≥1 major INI RAMs.
•
Of 3 major recognised pathways of genotypic resistance to RAL :
N155H and Y143R/C occurred in both B and non- B HIV1 subtypes.
Q148H/R/K- significantly more prevalent in subtype B.
• Q148 was highly conserved among INI naive patients infected with
either subtype B or non-B virus in contrast with INI experienced
counterpart.
• T97A, E138D/K and V151I significantly more common in RAL
experienced patients.
Conclusions.
• Identified 3 novel mutations that were more prevalent in RAL
experienced patients in comparison with RAL drug naive: K159Q/R,
I161L/M/N/T/V and E170AG.
• K159Q/R observed in subtype B only- in 1 patient with major INI
RAMs and in 3 other patients with other INI associated mutations.
• I161L/M/N/T/V seen in subtype B and CRFO2- in 1 patient with
major INI RAMs and in 5 patients with other mutations implicated in
INI resistance.
• E170AG seen in subtype B viruses in 2 patients alongside 2 major
INI RAMs and in all patients with other INI associated resistance
mutations.
• Require further clarification of their impact across subtype on drug
susceptibility to 1st and 2nd generation INIs.
Comparison of subtypes B and C
accessory mutations observed in high
level NRTI resistance
B, aa K
C, aa K
B, aa other
C, aa other
B, aa I
C, aa I
100
100
80
80
Proportion
Codon 43
60
40
60
20
0
0
1
2
3
B, aa other
C, aa other
Codon 118
40
20
0
B, aa V
C, aa V
4
0
1
2
3
Statistically significant differences (p<0.001) between subtype B and C
in detection of mutants at codons 43 and 118 with accumulation of TAMS.
Impact of 43, 44, and 118 on resistance and fitness in subtype B and C
backgrounds now being analysed in phenotypic assays (Tamyo Mbisa).
4
PLATO II Project of COHERE: Analysis of predictors of
triple class virologic failure (TCVF) and outcomes for
patients with TCVF.
Results so far relating to resistance (EACS Cologne,
manuscript drafted)
722 patients who developed TCVF and for whom at least one resistance
test was available at some point up to time of TCVF (1514 tests).
444 / 618 (72%) patients with a resistance test while on an NRTI after
NRTI failure had an NRTI mutation.
372 / 427 (87%) patients with a resistance test while still on an NNRTI
after NNRTI failure had an NNRTI mutation.
65 / 240 (27%) patients with a resistance test while on a PI after failing a
PI/r had a PI mutation.
Risk factors for PI resistance: longer time on a PI/r regimen since PI/r
failure, being treated with an NNRTI-containing regimen, and for having
previously used a greater number of PIs.
In the second round of the project (in progress) we will
expand the scope of the resistance data pooled to include
all resistance tests performed in people with TCF, including
those tests performed beyond the time of TCF.
The specific aims in the second round will be in people with TCVF:
1. To assess the proportion of people with TCVF for whom
resistance mutations to the three original classes, and to
the newer drug classes, are documented, either up to the
time of TCVF or beyond.
2. To document calendar time trends in the GSS for people
on ART. The GSS at any calendar time point will be
based on cumulative resistance tests up to that point
(and so could be calculated for those with VL < 50 as
well as for those with higher VL).
3. In people on ART, to assess the extent to which the
documented increasing trend over calendar time in
proportion of people with VL < 50 is explained statistically
by the current GSS (i.e. the extent to which the rate ratio
for the effect of calendar time on VL < 50 moves to 1
after adjustment for the current GSS).