Rationale and Uses For a Public HIV Drug Resistance Database

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Rationale and Uses For a Public HIV DrugRationale and Uses For a Public HIV Drug
Resistance DatabaseResistance Database
Bob Shafer, MDBob Shafer, MD
Professor of Medicine and by Courtesy PathologyProfessor of Medicine and by Courtesy Pathology
(Infectious Diseases)(Infectious Diseases)

2
OutlineOutline
• HIV drug therapy essentials
• HIVDB
• Examples of public health applications
• Surveillance of transmitted drug resistance
• Genetic mechanisms of acquired drug resistance

HIV Replication and Targets of Therapy

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AAntintirretroetrovviral Inhibitors (ARVs)iral Inhibitors (ARVs)
AZT
1990 1995 2000 2005
ddI
d4TddC
3TC
SQV
RTV
IDV
NVP
TDFABC
NFV
APV
DLV
EFV
LPV ATV
T20
TPV DRV RAL
MVC
FTC ETR
Nucleoside
RT Inhibitor
Nonnucleoside
RT inhibitor
Protease
Inhibitor
Fusion
Inhibitor
CCR5
Inhibitor
Integrase
Inhibitor

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HIV Genetic VariationHIV Genetic Variation
• Generation of variation
• High mutation rate
• Recombination
• Proviral DNA “archive”
• Selective evolutionary pressures
• Immunological
• Antiretroviral drugs (ARVs)

Tebit DM, Arts EJ. Tracking a century of global expansion and evolution of HIV. Lancet Infect Dis 2011

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HIV-1 RT: Active Site, Template, Primer, and dNTP
Incoming nucleotide
Active site

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NNRTI Resistance Mutations
Etravirine
NNRTI resistance mutations
Active site

HIV-1 Protease Drug Resistance Mutations
Active site & substrate cleft
Lopinavir Major resistance mutations
Minor resistance mutations

Models Relating HIV Drug Resistance to Treatment
Response

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10 Million Patients on Antiretroviral Therapy
2013 Global AIDS Response Progress Reporting (WHO/UNICEF/UNAIDS)

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OutlineOutline
• HIVDB
• Surveillance for transmitted drug resistance

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Database RationaleDatabase Rationale
• Drug resistance knowledge important for

Interpreting genotypic resistance tests

Designing surveillance studies and public health decisions

Assisting drug development.

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How we know what we know about HIVHow we know what we know about HIV
drug resistance mutationsdrug resistance mutations
• Genotype-treatment correlations – 1998
• Genotype-phenotype correlations – 2002
• Genotype-outcome correlations – 2005

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Database RationaleDatabase Rationale
• Large amounts of drug resistance data are important for
generating drug-resistance knowledge.
• Uniform representation of 3 main data correlations
facilitates meta-analyses.

Genotype-Rx
Genotype-Phenotype
Genotype-Outcome
Clinical management
Epidemiologic studies
Drug development
http://hivdb.stanford.edu

Genotypic HIV Resistance Testing
CCTCAGATCACTCTTTGGCAACGACCCATAGTCACAATAAAGATAGCGGGACAACTAAAGGAAGCTCTATTAGATACAGGAGCAGATGATACAGT
ATTAGAAGAAATGAATTTGCCAGGAAAATGGAAACCAAAAATAATAGTGGGAATTGGAGGGTTTACCAAAGTAAGACAGTATGATCATGTACAAAT
AGAAATCTGTGGACATAAAGTTATAGGTGCAGTATTAATAGGACCTACACCTGCCAATATAATTGGAAGAAATCTGTTGACTCAGCTTGGCTGTAC
TTTAAATTTT
PQITLWQRPIVTIKIAGQLKEALLDTGADDTVLEEMNLPGKWKPKIIVGIGGFTKVRQYDHVQIEICGHKVIGAVLIGPTPANIIGR
NLLTQLGCTLNF
Differences from Consensus B:
L10I, G17R, K20I, E35D, N37S, M46I, I62V, L63P, A71I, G73S, I84V, L90M, I93L

HIV-1 Genotypic Resistance Testing: Online Interpretation
Meaningful Results
(1) Quality control
(2) Sequence Interpretation
(3) Literature references
(4) Clinical education / advice
Shafer RW et al. HIV-1 RT and Protease Search Engine for Queries. Nat Med 2000

HIVdb: Genotypic Resistance Interpretation
http://hivdb.stanford.edu

HIVdb: Genotypic Resistance Interpretation

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Surveillance for Transmitted Drug
Resistance

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OutlineOutline
• HIVDB

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Rationale for Surveillance for Drug ResistanceRationale for Surveillance for Drug Resistance
in ARV-Naive Populationsin ARV-Naive Populations
• Assess extent of transmitted drug resistance (TDR).
• Monitor the expected efficacy of first-line therapies.

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Challenges to ARV-Resistance SurveillanceChallenges to ARV-Resistance Surveillance
• There is no perfect definition of genotypic resistance.
• There are many different drug-resistance mutations (DRMs).
• Drug resistance mutations occasionally occur in the absence
of selective drug pressure. Therefore, not all drug-resistance
mutations are evidence for transmitted drug resistance
(TDR).

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Challenges to ARV-Resistance SurveillanceChallenges to ARV-Resistance Surveillance
• More than 300 studies of genotypic resistance in ARV-
naïve patients have been published.
• Findings differ by region, time, study population, and
potentially study methods.

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Surveillance Drug Resistance Mutations (SDRMs)Surveillance Drug Resistance Mutations (SDRMs)
• Drug-resistance mutations with a high sensitivity and specificity
for detecting selective ARV pressure.
• Nonpolymorphic.
• Applicable to all HIV-1 subtypes.
Shafer RW, et al. HIV drug resistance mutations for
drug resistance surveillance. AIDS 2007

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HIV-1 Resistance in ARV-Naïve Populations:HIV-1 Resistance in ARV-Naïve Populations:
Analysis of Published RT and PR SequencesAnalysis of Published RT and PR Sequences
• Well-characterized representative population of ARV-
naïve persons.
• Country and year of virus isolation known.
• HIV-1 RT ± PR sequence is publicly available.

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Calibrated Population Resistance Analysis ToolCalibrated Population Resistance Analysis Tool
Gifford, RJ et al. The calibrated population resistance tool: standardized
genotypic estimation of transmitted HIV-1 drug resistance. AIDS 2008
• Standardized approach
to handling missing data
and poor sequence
quality.
• Applies SDRM list to a
set of sequences
• Backward-compatibility

Prevalence by RegionPrevalence by Region
Region No.
Studies
No.
Persons
% Resistance
Median
% Resistance
IQR
North America 24 11,038 11.4 8.8 – 14.0
Europe 44 11,419 9.3 6.0 – 15.1
Latin America 39 5,802 7.6 4.0 – 10.1
High-income Asia 11 3,190 5.5 3.5 – 9.0
Former Soviet Union 11 1,124 3.4 0.0 – 6.4
South/Southeast Asia 49 4,181 3.3 2.0 – 5.3
Sub-Saharan Africa 86 9,904 2.8 1.1 – 5.7
264 46,660

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887 1529
<=1
1538
<=3
1343
4
1803
<=6
1200
7
1449
<=14
Years Since AR
0
4
8
Overall
0
4
8
NRTI
0
4
8
NNRTI
%Resistance
0
4
8
PI
Sub-Saharan Africa
Sub-Saharan AfricaSub-Saharan Africa
http://hivdb.stanford.edu/surveillance/map/

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South/Southeast Asia
495 512
<=2
858
3
556
4
877
<=6
811
<=9
Years Since AR
0
4
8
Overall
0
4
8
NRTI
0
4
8
NNRTI
%Resistance
0
4
8
PI
South / Southeast AsiaSouth / Southeast Asia
http://hivdb.stanford.edu/surveillance/map/

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Most Common SDRMs by Region and ARV ClassMost Common SDRMs by Region and ARV Class

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• Significant differences in prevalence of resistance in ARV-
naïve patients by region and year.
• Transmitted NNRTI resistance is increasing in Sub-
Saharan Africa and South/Southeast Asia.
• Analysis of data from many studies is required to obtain
meaningful estimates of transmitted drug resistance.
ConclusionsConclusions

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OutlineOutline
• HIVDB

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RationaleRationale
• In resource-limited regions, ~25% of patients receiving
first-line ART develop virological failure within 1 year.
• Drug-resistance mutations are detected in 50% to 90%
of patients with virological failure.
• Regimens used in resource-limited countries differ from
those used in well-resourced countries.
• Patients in resource-limited countries are monitored
infrequently and second-line therapy is chosen without
genotypic resistance testing.

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Genetic Mechanisms of Resistance in PatientsGenetic Mechanisms of Resistance in Patients
with Virological Failurewith Virological Failure
• Choosing second-line therapy.
• Developing point-of-care (POC) diagnostic tests.

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WHO-Recommended First-Line ARV RegimensWHO-Recommended First-Line ARV Regimens
WHO-Recommended Regimens, 2016 to 2013
NRTI NRTI NNRTI / PI
d4T (being phased out) 3TC (or FTC) EFV
AZT NVP
TDF LPV (PI, 2nd
line)
ABC (children)

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Number of Patients by Regimen and SubtypeNumber of Patients by Regimen and Subtype
A B C AE AG D G Misc Total
d4T/3TC/NVP 50 55 121 430 123 27 122 40 1121
AZT/3TC/NVP 45 99 394 45 50 42 46 21 469
d4T/3TC/EFV 13 92 188 16 9 2 3 11 540
AZT/3TC/EFV 25 244 274 45 20 17 26 11 576
133 490 977 536 202 88 197 83 2706
Data summary from mid 2012

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Sources of Patient Data and SequencesSources of Patient Data and Sequences
Number Studies Number Patients %
10 largest 1,409 51%
20 largest 1,981 72%
50 largest 2,640 98%
Data summary from mid 2012

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Question From WHO: Which NRTI should beQuestion From WHO: Which NRTI should be
substituted in patients stopping d4T?substituted in patients stopping d4T?
• Patients with virological failure on d4T can develop resistance by
two mutually exclusive mutational pathways:
• Thymidine analog mutations: cross-resistance to AZT
• Non-thymidine analog mutations particularly K65R: cross-resistance to
TDF and increased susceptibility to AZT
• In vitro studies have shown that viruses belonging to subtype C
are at increased risk for developing K65R.

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Impact of NNRTI, Subtype, and Years on NRTI-Impact of NNRTI, Subtype, and Years on NRTI-
Resistance Mutations in 1,840 Patients Receiving d4TResistance Mutations in 1,840 Patients Receiving d4T

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Impact of Subtype on AZT and TDF Cross-Resistance inImpact of Subtype on AZT and TDF Cross-Resistance in
1,840 Patients Receiving d4T1,840 Patients Receiving d4T

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Rationale for Point-Of-Care (POC) Resistance TestingRationale for Point-Of-Care (POC) Resistance Testing
in Low/Middle-Income Countries?in Low/Middle-Income Countries?
• POC test for detecting virological failure have been
developed.
• A POC resistance test for a limited number of the most
important mutations could be used:
• To confirm virological failure
• To suggest among second-line therapy options
• Be used prior to therapy in regions with elevated TDR or in
patients with uncertain treatment history.

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Sensitivity for Detecting Resistance after 1st-LineSensitivity for Detecting Resistance after 1st-Line
Failure: 4 NNRTI and 6 NRTI-Resistance MutationsFailure: 4 NNRTI and 6 NRTI-Resistance Mutations

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Sensitivity for Detecting Resistance in UntreatedSensitivity for Detecting Resistance in Untreated
Patients: 4 NNRTI and 6 NRTI-Resistance MutationsPatients: 4 NNRTI and 6 NRTI-Resistance Mutations

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ConclusionsConclusions
• Drug resistance knowledge is important for interpreting genotypic
resistance tests, designing surveillance studies, and drug
development.
• Large amounts of drug resistance data are important for
generating drug-resistance knowledge.
• Drug-resistance data consists mostly of correlations between
genotype-treatment, genotype-phenotype, and genotype-
virological outcome.

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Acknowledgements
Funding
NIAID – Division of AIDS
Bill and Melinda Gates Foundation
Database / Data analysis
Soo-Yon Rhee, M.S.
Tommy Liu, B.S.
Michele Tang, M.D.
Vici Varghese, Ph.D.

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5.0
6.0
4.0
3.0
2.0
1.0
-4 0 4 8 12 16 20 24 28 32 36 40 44
PlasmaHIV-1RNAlogcopies/ml
Ibalizumab Infusions
Accompanying antiretrovirals: etravirine + enfuvirtide
1997 2009
97 98 99 00 01 02 03 04 05 06 07 08 09
April 2010June 2009
Below the level of quantification Below the level of quantification
HIV-1 levels prior to TMB-202 HIV-1 levels during and following TMB-202
EFV
ENF
DRV + RAL
A B
HIV-1 Evolution and Drug Resistance:
An Example
Fessel WJ, et al. The efficacy of an anti-CD4 monoclonal
antibody for HIV-1 treatment. Antivir Res 2011

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