Gabriel A. Wagner, MD, of UC San Diego Owen Clinic, presents "HIV-1 Dual Infection and Correlates of Neutralization"

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AIDS CLINICAL ROUNDS

2. HIV-1 Dual Infection and
Correlates of Neutralization
Gabriel A. Wagner
Postdoctoral Research Fellow
University of California San Diego
Friday, July 12, 2013

3. Outline
• What is HIV-1 dual infection?
• What does it mean to the global epidemic?
• How common is it?
• What are the individual consequences?
• What does it portend for rational vaccine
design?

4. Types of HIV-1 Dual Infection (DI)
Strain 1 + Strain 2
Coinfection
(CI)
Time
Strain 1 Strain 2
Superinfection
(SI)
Time
Intrasubtype
(same subtype)
or
Intersubtype
(different
subtypes)
M.Pacold

6. Global Distribution of HIV-1 M Subtypes
Hemelaar J. Trends Mol Med 2012

7. Artenstein et al. JID 1995;171:805-10

8. Previous Investigative Methods
• Single genome sequencing (SGS): obtain the sequences
of 20-30 individual HIV genomes
• Lacks sensitivity required to discern low minority
populations (<5%)
• Cannot be used in large cohorts

9. Ultradeep Sequencing (UDS)
• Shorter reads, but many more of them
• High coverage depth suitable for detecting
minority variants (<1%) [Archer et al., PLOS One 2012; 7(11)]
[Modified from Bushman et al., AIDS 2008]
400
100
50
960 000
250 000 000
519 000 000
http://www.genomeweb.com/sequencing/survey-illumina-solid-and-454-gain-ground-research-labs-most-users-mull-addition

10. Clinical cohorts
• San Diego Primary Infection Cohort
– Longitudinal (including acute and early infection)
– Predominantly MSM, White
– Subtype B
– ART-naive
• IAVI Protocol C Cohort
– Longitudinal
– Heterosexual discordant, MSM, SW (varies by clinical site)
– Subtypes C, A, D (varies by clinical site)
– ART-naive

11. Methods: UDS
• Blood → HIV-1 RNA → cDNA → PCR 3 regions
• Pooled 3 PCR products per sample
• Sequenced 16 samples concurrently on a 454 GS
FLX Titanium plate
• Processed reads and generated phylogenies
• DI: nucleotide divergence> 2.5% (RT, gag) and >
5% (env), confirmed by phylogenetic bootstrap
env: C2-V3-C3
(416 bp)
pol: RT
(534 bp)
gag: p24
(253 bp)
Pacold et al., AIDS 2012, 26:157–165

12. Phylogenies: Dual vs. Monoinfection
P265 env, 3rd year of infection
Divergence: 16%
D381 env, 6th year of infection
Divergence: 14%
High
bootstrap
support for
dual
infection

13. Time Point Sampling
• Last time point per participant sampled with
UDS
– (N=118)
• If DI, baseline sample was deep sequenced
• If DI at baseline: coinfection (CI)
• If MI at baseline: superinfection (SI), and
timing of SI was determined

14. Outline
• What is HIV-1 dual infection?
• What does it mean to the global epidemic?
• How common is it?
• What are the individual consequences?
• What does it portend for rational vaccine
design?

15. Redd et al. JID 2012;206:267–74
• Heterosexual open, rural cohort
• 7 out of 149 identified with inter- or intra-subtype superinfection
• Rate of HIV superinfection: 1.44 per 100 PYs
• Unadjusted primary HIV incidence rate: 1.15 per 100 PYs
• Adjusted primary incidence 3.28 per 100 PYs (borderline statistical significance)

16. Piantadosi et al. PLoS Pathog 2007;3(11)
• High-risk Kenyan women cohort
• 7 out of 36 individuals intrasubtype A
• Frequency of HIV-1 superinfection: 3.7% per year
• Incidence of primary infection in this cohort, 8% per year

17. Study Cohort Baseline Characteristics
Wagner et al., Poster 510, CROI 2013, Atlanta, GA

18. Rates of HIV-1 Dual Infection in SD
• Of 118 cohort participants:
– 7 baseline co-infected (5.9% prevalence, 95% CI
2.4%−11.8%) at a median time from EDI of 2.8 months
(IQR 2.3−3.2 months)
– 10 superinfections identified over 201.6 person-years,
resulting in an overall incidence of superinfection of
4.96 per 100 person-years (95% CI 2.67–9.22)
• 7 superinfections occurred in the first year (6.3% first-year
incidence, 95% CI 2.6%−12.6%), and 3 in the second year
(2.9% second-year incidence, 95% CI 0.6%−8.2%)

19. Wagner et al., Poster 510, CROI 2013, Atlanta, GA

20. Incidence of Primary HIV
in MSM in San Diego
• Primary HIV incidence in the cohort was
calculated for repeat testers who were initially
negative and subsequently tested positive:
– 4.37 per 100 person-years (95% CI 3.56–5.36)
• Incidence of HIV-1 superinfection comparable
to incidence of primary infection

21. Wagner et al., Poster 510, CROI 2013, Atlanta, GA
Cumulative Prevalence of HIV-1 Dual Infection
Throughout 215 person-years of follow-up, the cumulative prevalence of HIV-
1 dual infection (co-infections and superinfections) was 14.4% (95% CI
8.6%−22.1%).

22. Outline
• What is HIV-1 dual infection?
• What does it mean to the global epidemic?
• How common is it?
• What are the individual consequences?
• What does it portend for rational vaccine
design?

24. Pacold et al., AIDS 2012, 26:157–165

25. Methods: Case Control
• Cohort Subset:
– 4 coinfected
– 7 superinfected
– 19 monoinfected
• Applied linear mixed-effects models to
longitudinal viral load and CD4 data

26. Comparison of VL Progressions
• Compared to MI,
SI had a
significantly
faster viral load
increase (p<0.05).
• The difference
between MI and
CI was not
significant
(p=0.06).
N CI 4 3 2 1 1 1
per SI 7 6 3 2 2 1
time MI 19 18 12 8 9 6
point
LogViralLoad
Months since Initial Infection
Pacold et al., AIDS 2012, 26:157–165

27. Comparison of CD4 Progressions
• MI, CI, SI CD4
progressions
are not
significantly
different from
each other
(p>0.05)
N CI 4 3 2 1 1 1
per SI 7 6 3 2 2 1
time MI 18 18 11 8 9 6
point
SquareRootCD4
Months since Initial Infection
Pacold et al., AIDS 2012, 26:157–165

28. Subject HLA-A HLA-B C2-V3 RT pol
1 (K6) 23, 29 44, 44 In=Out In>Out In>Out
2 (K9) 03, 29 44, 57 Out>In In=Out In>Out
3 (D2) 03, 32 35, 47 Out>In Out>In NA
4 (P2) 01, 68 35, 57 In=Out NA NA
5 (P8) 24, 31 35, 41 In=Out In=Out NA
6 (S1) 24, 66 35, 41 In=Out In=Out NA
7 (U7) 01, 03 08, 35 In=Out In=Out NA
Evidence of CTL Escape by SI Virus
• Amino acid differences between Initial versus Superinfecting viruses are compared inside
vs. outside epitopes. Bold: p<0.05.
• Unique characteristics of K6 and K9 among SI participants:
• Complete replacement of initial by SI virus
• Evidence of CTL escape
Pacold et al., AIDS 2012, 26:157–165

29. DI and coreceptor usage
• Both DI and infection with CXCR4 (X4)-using
virus have been associated with accelerated
disease progression
• Coreceptor usage can be determined
phenotypically or predicted from genotype
• UDS increases sensitivity of coreceptor usage
prediction

30. Wagner et al. JID 2013;208:271–4

31. Methods: Case Control
• Cohort Subset:
– N=102
• Co‐receptor usage predicted
– geno2pheno 454 [Thielen et al. Intervirology 2012;
55:113‐7]
– Samples classified as X4‐capable when >1% of the
viral population predicted as X4-using variants
[Daumer et al. BMC Med Inform Decis Mak 2011; 11:30]
• Nonparametric and correlation analyses
performed to examine associations between
X4-usage and dual infection

32. Prevalence of X4 coreceptor usage
• At baseline, X4 usage
was high (23 of 102
subjects harbored X4
variants)
• X4 usage was not
associated with
infection duration or DI
Wagner et al. JID 2013;208:271–4

33. HIV-1 superinfection and coreceptor usage
• Longitudinal analysis of 47 participants:
– 41 MI
– 5 SI
– 1 CI
• Coreceptor usage changed in 12 of 47
participants
– X4 usage emerged in 4 of 41 monoinfections vs 2
of 5 superinfections (P = 0.12)
Wagner et al. JID 2013;208:271–4

34. HIV-1 superinfection and coreceptor usage
• In case G59, an increase in the proportion of X4 usage (black solid diamonds)
coincided with the detection of a superinfecting strain (pie charts), and X4
variants disappeared when this strain was no longer detected
Wagner et al. JID 2013;208:271–4

35. Outline
• What is HIV-1 dual infection?
• What does it mean to the global epidemic?
• How common is it?
• What are the individual consequences?
• What does it portend for rational vaccine
design?

36. Vaccines and HIV-1 Superinfection
• Neutralizing antibodies (NAbs): best correlate of
protection from re-infection with most viruses and of
protection mediated by viral vaccines1
• Recent studies underscore need for better
understanding of natural development of NAbs for
vaccine design2,3
• HIV-1 Superinfection
– an effective vaccine must contain immunogens broad and
potent enough to protect from very diverse viral challenges.
– unique opportunity to study correlates of protection
1Plotkin SA. C R Acad Sci III 1999,322:943-951
2Klein et al., Nature 2012; 492:118-122
3Walker et al., Nature 2011; 477:466-470

37. Assessing neutralization breadth and potency
• Monogram Biosciences: high-throughput neutralization assay against
autologous and heterologous pseudoviruses
– cross-clade heterologous panel used for the selection of best Protocol G donors and highly
predictive of neutralization breadth on a larger panel1,2
NL43 (highly neutralization-susceptible clade B) = positive control
aMLV (irrelevant mouse retrovirus) = negative control
94UG103 (clade A)
92BR020 (clade B)
JRCSF (clade B)
SF162 (clade B)
IAVIC22 (clade C)
93IN905 (clade C)
92TH021 (CRF AE)
Neutralization data analysis:
Infectivity inhibition  IC50 titer  neutralization score (breadth and
potency)
Landais E., NAC Retreat 2012
1Richman et al., PNAS 2003; 100,7:4144-4149
2Simek et al., J.Virol. 2009; 83(14):7337

38. What is the effect of viral genetic
diversity on NAb potency and
breadth?

39. Methods: Diversity vs. neutralization
• Cohort subset (N=34)
• UDS maximal sequence divergence
– estimate of diversity
• Neutralization assays against heterologous
pseudoviruses (Monogram Biosciences)
• Correlation analysis between genetic maximal
divergence (MDI) in each coding region vs. NAb

40. NAb Score vs. env MDI
Carter, Wagner et al., Poster 351, CROI 2013, Atlanta, GA

41. Future NAb score vs. Baseline env MDI
Carter, Wagner et al., Poster 351, CROI 2013, Atlanta, GA

42. What are protective correlates of
NAb response during intrasubtype
HIV-1 superinfection?

43. Comparing NAb development in
superinfection vs. monoinfection
• NAb activity against autologous and heterologous
viruses before and after superinfection (SI)
–Compared to monoinfected (MI) controls matched to
duration of infection within 3 months
• 10 SI
• 19 MI
• Nonparametric test performed at 3, 12, 24, and
36 months after EDI

44. 3 Months after EDI:
Heterologous NAb breadth and potency
Wagner et al., Oral Abstract C-129, CROI 2013, Atlanta, GA

45. 3 Months after EDI:
Heterologous NAb to tier 1 clade B virus
Wagner et al., Oral Abstract C-129, CROI 2013, Atlanta, GA
At 3 months, those who would acquire SI (8) had significantly weaker NAb
response against susceptible clade B viruses than MI (17), p = 0.011.
p < 0.05

46. 6 Months after EDI:
Heterologous NAb breadth and potency
Wagner et al., Oral Abstract C-129, CROI 2013, Atlanta, GA

47. 6 Months after EDI:
Heterologous NAb to tier 1 clade B virus
Wagner et al., Oral Abstract C-129, CROI 2013, Atlanta, GA
At 6 months, those who became superinfected (3) had significantly weaker NAb
response against susceptible clade B heterologous viruses than MI (19).
p < 0.05

48. 12 months after EDI:
Autologous NAb to 3M virus
At 12 months, those who became SI (7) had significantly weaker NAb response
against 3-month autologous virus than MI group (15).
p < 0.05
Wagner et al., Oral Abstract C-129, CROI 2013, Atlanta, GA

49. 12 months after EDI:
Autologous NAb to 6M virus
At 12 months, those who became SI had weaker NAb response against 6-month
autologous virus, with a trend towards statistical significance.
*p = 0.051
Wagner et al., Oral Abstract C-129, CROI 2013, Atlanta, GA

50. 24 and 36 Months after EDI:
Heterologous and Autologous NAb
• No significant difference in NAb response
against heterologous viruses
• No significant difference in NAb response
against 3-month or 12-month autologous
viruses

51. What are the viral dynamics of
HIV-1 superinfection?

52. Viral dynamics in SI and NAb response
• Deep-sequencing and single-genome data for 7 SI
– phylogenetic trees generated using BEAST
– Screened for recombination
– Viral dynamics evaluated using nucleotide entropy as
a marker of diversity
• NAb responses to autologous viruses (ANAb)
were evaluated before and after superinfection
and compared against viral diversity

53. Chaillon, Wagner et al., Poster 177LB, CROI 2013. Manuscript submitted.

54. Chaillon, Wagner et al., Poster 177LB, CROI 2013. Manuscript submitted.
• A strong NAb response was observed to autologous virus
at time of superinfection for G5
• G5 also displayed high viral diversity within env at the two
latest time points available (respective mean entropy of
0.117 and 0.08) where recombination events were also
observed
Mean ANAb titers to contemporaneous viruses at the time of and shortly following
superinfection.

55. Limitations
• Molecular evidence of HIV-1 dual infection
– Limited to coding regions sequenced
– Limited to compartment sampled
– Recombination can homogenize viral populations and
may make DI detection more difficult
• Methodology bias
– UDS platform
– Bioinformatic analysis
• Follow up
– ART initiation in the cohort

56. Overall Conclusions
• High rates of intrasubtype B HIV-1 dual infection in
high-risk cohort
– Most cases occur in first year
• Superinfection associated with higher VL, potential CTL
escape and X4 coreceptor usage
• env diversity likely driven by NAb selective pressure
and not vice versa
• ‘Window of susceptibility’ in the first year of primary
infection where individuals with weaker heterologous
and slower autologous NAb development are at risk of
SI
• Viral dynamics after superinfection fall into discrete
patterns

57. Acknowledgments
Univ of California San Diego
Davey Smith
Doug Richman
Caroline Ignacio
Melissa Laird
Antoine Chaillon
Sara Gianella
Demetrius Dela Cruz
Funding
U.S. Department of Veterans Affairs
National Institutes of Health
International AIDS Vaccine Initiative
National Science Foundation
James B. Pendleton Charitable Trust
Monogram Biosciences
Terri Wrin
Pham Phung
All Participants in the San Diego
Primary Infection Cohort and IAVI
Protocol C Cohort
The Scripps Research Institute
Pascal Poignard
Elise Landais