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

BackgroundPolymorphisms 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

Aims1. To determine the prevalence of polymorphisms at the following

codons* in ARV-naive subjects:

2. To assess their impact on early virological response to NNRTI-based therapy

90 98 100 101 103 106 108 138 179 181 188 190 225 227 230 234 236 238 318 348

* IAS Dec 2008 and Stanford database http://hivdb.stanford.edu accessed 07 Jan 2010

PopulationARV-naive patients starting NNRTI-based Rx with WT or polymorphisms only on baseline genotype (any major RT mutation excluded)

AnalysisAssess early virological response at week 4 (approx timing wk 2-6):

WT versus any polymorphismWT versus individual codon (irrespective of amino acid mutation)

Results to date2235 eligible subjects1221 (55%) at least one polymorphismMost frequently seen at codons 135 (39%), 179 (10%), 98 (8%)Average 2.4 log10

drop by wk 4

Difference in reduction in viral load at week 4

n=71

n=176

n=39

n=35

n=51

n=877

n=79

n=217

n=35

90

98

101

103

106

135

138

179

238P

olym

orph

ism

-.5 -.25 0 .25 .5Average effect on reduction in viral load at week 4

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 polymorphismWT 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

• 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

Background

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

0.00

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0.50

0.75

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Pro

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ndin

g

0 3 6 9 12 15 18 21 24 27 30 33 36Analysis Time (months)

naive NNRTI HAARTother

Previous ART

Time to rebound• N = 3056

• Previous ART:1580 (52%) naïve 569 (19%) NNRTI HAART 907 (30%) other

• 811 (27%) rebounded:370 (23%) naïve139 (24%) NNRTI HAART302 (33%) other

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 I84V 2M46L V82A 2L90M 2

L33F M46L V82A I84V L90M 1V32I M46I I47A/V V82A 1L33F M46L V82A L90M 1M46L V82T I84V L90M 1V32I M46I I47A 1M46I L76V I84V 1M46I V82A V82S 1M46I L76V 1M46I I84V 1M46L T74P 1L33F 1M46I 1M46I/L 1M46L 1I47V 1L76V 1V82T 1I84V 1

Outcomes of 2nd line ART: 1st line NNRTI to 2nd line PI/r

Laura Waters, Laura Waters, David AsboeDavid Asboe, Anton Pozniak, Loveleen , Anton Pozniak, Loveleen Bansi, Bansi, Chloe Orkin, Erasmus Smit, Esther FearnhillChloe Orkin, Erasmus Smit, Esther Fearnhill

& Andrew Phillips.& Andrew Phillips.

UK Resistance Database and UK CHIC StudyUK Resistance Database and UK CHIC Study

• A combination of 2 NRTI + 1 NNRTI is the most A combination of 2 NRTI + 1 NNRTI is the most common first line regimen worldwidecommon first line regimen worldwide

• Treatment failures continue to occur Treatment failures continue to occur

• Second line regimens are usually PI/r based and Second line regimens are usually PI/r based and should include at least 2 active agentsshould include at least 2 active agents11

• Unclear how many active NRTI are necessary with Unclear how many active NRTI are necessary with 2nd line PI/r based therapy 2nd line PI/r based therapy

BackgroundBackground

1) 2008 BHIVA Guidelines

• To identify factors associated with failing 2To identify factors associated with failing 2ndnd line, line, ritonavir boosted PI-based ARTritonavir boosted PI-based ART

• To investigate the importance of the number of new To investigate the importance of the number of new or fully active NRTI started at 2or fully active NRTI started at 2ndnd line line

ObjectivesObjectives

• EligibilityEligibility

Patients failing first line NNRTI-ART (VL >200 Patients failing first line NNRTI-ART (VL >200 copies/ml after 4 months) and starting PI/r for the first copies/ml after 4 months) and starting PI/r for the first time time

• ExclusionsExclusions

• VL<200 copies/ml at start of 2VL<200 copies/ml at start of 2ndnd line line

• <4 months follow up <4 months follow up

• failed new NRTI between first and second-line failed new NRTI between first and second-line therapytherapy

Methods 1Methods 1

• Virological failure of 2Virological failure of 2ndnd line ART was defined as line ART was defined as VL>200 copies/ml despite 4 months continuous use VL>200 copies/ml despite 4 months continuous use

• NRTI GSS calculated for 2NRTI GSS calculated for 2ndnd line regimens using line regimens using StanfordStanford

• Statistical Analyses:Statistical Analyses:

•Kaplan-Meier: time to failing 2Kaplan-Meier: time to failing 2ndnd line HAART line HAART

•Logistic regression: identify factors associated Logistic regression: identify factors associated with having a resistance test with having a resistance test

•Cox regression: identify factors associated with Cox regression: identify factors associated with failing 2failing 2ndnd line HAART line HAART

Methods 2Methods 2

Patients starting new drugs 2nd line

(n = 1103)

Started PI/r Regimen 2nd line

(n = 601)

Started non-PI/rregimen 2nd line

(n = 502)

Unboosted PI 45New NNRTI 138New NRTI only 318Other 1

ExcludedHIV-RNA <200 at 2nd line 100<4 months follow-up 56Failed new NRTI between1st and 2nd line 42

Eligible for Study(n = 403)

Time to failing 2Time to failing 2ndnd line HAART line HAART

0

0.2

0.4

0.6

0.8

1

0 12 24 36 48 60 72 84 96

Months since starting 2nd line HAART

222/403 (55.1%) experienced virological failure of 2nd line

Independent factors associated with failure of 2Independent factors associated with failure of 2ndnd line HAART (N=403)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 0 0.83 (0.51, 1.33) 0.44started at 2nd line1 1 1.11 (0.79, 1.56) 0.56

>2 1 -

Ethnicity White 1 -Black 0.95 (0.60, 1.51) 0.95

Other 0.52 (0.24, 1.12) 0.52

Sex/Exposure MSM 1 -Hetero male 1.93 (1.17, 3.20) 0.01

Hetero female 2.33 (1.26, 4.02) 0.002

Other 1.59 (0.62, 2.80) 0. 11

Year of starting 2nd line Per 1 year increase 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) Per 50 cells higher 0.89 (0.83, 0.94) <0.0001VL at 2nd line (copies/ml) Per 1 log increase 1.23 (1.06, 1.42) 0.01

1 HR=1.00 (0.82, 1.21), p=0.99 if fitted as a continuous variable

Failed 2nd line HAART

GSS All No Yes P-value

121 90

<1 33 (15.6) 20 (60.6) 13 (39.4) 0.801

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

Patients not receiving any NRTIs (N=5) excluded

GSS amongst those who had a resistance test GSS amongst those who had a resistance test performed (N=211)performed (N=211)

Independent factors associated with failure of 2Independent factors associated with failure of 2ndnd line HAART (N=211)line HAART (N=211)

HR (95% CI) P-value

NRTI GSS1 <1 0.73 (0.37, 1.41) 0.341.25-1.75 0.70 (0.42, 1.15) 0.16

>2 1

Time from failing 1st line to starting 2nd line

Per 1 month increase 1.01 (0.99, 1.02) 0.44

Age at start of 2nd line (years) Per 10 years older 1.29 (0.94, 1.79) 0.12

Ethnicity White 1 -Black 0.61 (0.30, 1.23) 0.17

Other 0.61 (0.23, 1.59) 0.31

Sex/Exposure MSM 1 -Hetero male 2.53 (1.14, 5.63) 0.02

Hetero female 2.79 (1.28, 6.08) 0.01

Other 1.32 (0.60, 2.90) 0.50

Year of starting 2nd line Per 1 year increase 0.97 (0.86, 1.10) 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) Per 50 cells higher 0.85 (0.77, 0.95) 0.004VL at 2nd line (copies/ml) Per 1 log increase 1.26 (0.99, 1.59) 0.06

1 HR=1.14 (0.76, 1.72), p=0.51 if fitted as a continuous variable

• Of 403 patients who started 2Of 403 patients who started 2ndnd line PI/r, 216 (54%) line PI/r, 216 (54%) patients had a resistance test performed after failing patients had a resistance test performed after failing 11stst line HAART line HAART

• NRTI GSS was NRTI GSS was >>2 for 50% of patients with 2 for 50% of patients with resistance tests performedresistance tests performed

• Neither NRTI GSS nor the number of new NRTI Neither NRTI GSS nor the number of new NRTI started at 2started at 2ndnd line were associated with virological line were associated with virological failure of 2failure of 2ndnd line HAART line HAART

SummarySummary

• Among patients who have failed an NNRTI 1st line Among patients who have failed an NNRTI 1st line then started a PI/r 2nd line there was extensive then started a PI/r 2nd line there was extensive variability in the number of new NRTI started, hence variability in the number of new NRTI started, hence in the predicted activity of the NRTI backbonein the predicted activity of the NRTI backbone

• We found little evidence that:We found little evidence that:

• number of new NRTI startednumber of new NRTI started

•predicted NRTI activity within the regimen, predicted NRTI activity within the regimen,

were associated with risk of virologic failure of the were associated with risk of virologic failure of the 2nd line regimen2nd line regimen

ConclusionsConclusions

• These findings may reflect:These findings may reflect:

• the strong potency of the PI/r component and/or the strong potency of the PI/r component and/or

• a negative impact of initiating more new agents a negative impact of initiating more new agents in terms of tolerability and/or adherencein terms of tolerability and/or adherence

• However, further analyses are required to more However, further analyses are required to more extensively explore this lack of association before extensively explore this lack of association before drawing firm conclusionsdrawing firm conclusions

ConclusionsConclusions

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 multi-centre 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 GroupIntegrase 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 non-classic 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

of RAMs

(%) Subtype RAM Number

of RAMs

(%) Subtype

T66I 0 (0.0) Y143C 4 (1.6) BE92Q 9 (3.5) B, C, G S147G 1 (0.4) BF121Y 0 (0.0) Q148H 28 (11.0) BG140A 4 (1.6) B, G Q148R 16 (6.3) B, C, G

G140S 34 (13.3) B Q148K 1 (0.4) BY143R 9 (3.5) B, C,F N155H 57 (22.4) A,B, C, D, F, G,

CRF02Total 114 (44.7)

Table 1: Prevalence of major integrase inhibitor RAMs in INI experienced patients.

RAM

pattern

Number

of RAMs

(%) RAM

pattern

Number

of RAMs

(%)

E92Q 1 (0.4) Y143R +N155H 1 (0.4)E92Q + N155H 8 (3.1) S147G + Q148H 1 (0.4)G140S 1 (0.4) Q148H/R/K 6 (2.4)G140A/S + Q148 H/R/K 36 (14.1) Q148H + N155H 1 (0.4)

G140S + Q148H + N155H 1 (0.4) N155H 46 (18.0)Y143R/C 12 (4.7) Total 114 (44.7)

Table 2: Patterns of major integrase inhibitor RAMs in INI experienced patients.

Non-classic mutations at major INI resistance codons detected in INI-experienced patients (n=255).

RAM Number

of RAMs

(%) Subtype RAM Number

of RAMs

(%) Subtype

T66 0 (0.0) - Y143H/A/S 5 (2.0) B, DE92A/P 2 (0.8) B S147I 1 (0.4) BF121 0 (0.0) - Q148 0 (0.0) -G140 0 (0.0) - N155D/Q 2 (0.8) B

Prevalence of other mutations implicated in INI- resistance among INI experienced patients n=255.

Mutation Number (%) Major INI RAMs

Mutation Number (%) Major INI RAMs

H51Y 1 (0.4) - Q146P 1 (0.4) 1/1

V54I 1 (0.4) - V151I* 25 (9.8) 19/25

L68I/V 1 (0.4) - M154I/L 28 (11.0) 14/28

L74I/M 22 (8.6) 13/22 E157Q 6 (2.4) 4/6

Q95K 2 (0.8) 2/2 K160Q/T 8 (3.1) 5/8

T97A* 20 (7.9) 16/20 G163E/R 17 (6.7) 11/17

T125A/V 114 (44.7) 48/114 I203M 13 (5.5) 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

n (%)

INI- naive

n (%)

P value

K159Q/R 4 (1.6) 0 (0.0) 0.008I161L/M/N/T/V 6 (2.4) 1 (0.2) 0.004

E170A/G 4 (1.6) 0 (0.0) 0.008*P values by Fisher’s exact test

• 55.3% of viraemic patients on RAL lacked major INI resistance-associated 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.

Conclusions.

Comparison of subtypes B and C accessory mutations observed in high

level NRTI resistance

0

20

40

60

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B, aa K B, aa otherC, aa K C, aa other

Pro

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B, aa I B, aa V B, aa otherC, aa I C, aa V C, aa other

Pro

port

ionCodon 43 Codon 118

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).

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).