hiv-1 dual infection and correlates of neutralization

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AIDS CLINICAL ROUNDS

HIV-1 Dual Infection and Correlates of Neutralization

Gabriel A. Wagner Postdoctoral Research Fellow

University of California San Diego Friday, July 12, 2013

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?

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

Global Distribution of HIV-1 M Subtypes

Hemelaar J. Trends Mol Med 2012

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

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

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

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

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

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

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


design?

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)

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

Study Cohort Baseline Characteristics

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

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%)

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


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%).


design?

Pacold et al., AIDS 2012, 26:157–165

Methods: Case Control

• Cohort Subset: – 4 coinfected – 7 superinfected – 19 monoinfected

• Applied linear mixed-effects models to longitudinal viral load and CD4 data

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

Log

Vira

l Loa

d

Months since Initial Infection

Pacold et al., AIDS 2012, 26:157–165

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

Squa

re R

oot C

D4

Months since Initial Infection

Pacold et al., AIDS 2012, 26:157–165

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

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

Wagner et al. JID 2013;208:271–4

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

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


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)


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



design?

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

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

What is the effect of viral genetic diversity on NAb potency and

breadth?

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

NAb Score vs. env MDI

Carter, Wagner et al., Poster 351, CROI 2013, Atlanta, GA

Future NAb score vs. Baseline env MDI

Carter, Wagner et al., Poster 351, CROI 2013, Atlanta, GA

What are protective correlates of NAb response during intrasubtype

HIV-1 superinfection?

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

3 Months after EDI: Heterologous NAb breadth and potency

Wagner et al., Oral Abstract C-129, CROI 2013, Atlanta, GA

3 Months after EDI: Heterologous NAb to tier 1 clade B virus


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

6 Months after EDI: Heterologous NAb breadth and potency


6 Months after EDI: Heterologous NAb to tier 1 clade B virus


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

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


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


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

What are the viral dynamics of HIV-1 superinfection?

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

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

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.

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

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

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

hiv-1 dual infection and correlates of neutralization

Health & Medicine

incidence of hiv

incidence of primary

frequency of hiv

types of hiv

rates of hiv

primary incidence

year of infection divergence

dual infection di strain