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Increased HIV-1 vaccine efficacy against viruses with genetic signatures in Env V2

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Abstract

The RV144 trial demonstrated 31% vaccine efficacy at preventing human immunodeficiency virus (HIV)-1 infection1. Antibodies against the HIV-1 envelope variable loops 1 and 2 (Env V1 and V2) correlated inversely with infection risk2. We proposed that vaccine-induced immune responses against V1/V2 would have a selective effect against, or sieve, HIV-1 breakthrough viruses. A total of 936 HIV-1 genome sequences from 44 vaccine and 66 placebo recipients were examined. We show that vaccine-induced immune responses were associated with two signatures in V2 at amino acid positions 169 and 181. Vaccine efficacy against viruses matching the vaccine at position 169 was 48% (confidence interval 18% to 66%; P = 0.0036), whereas vaccine efficacy against viruses mismatching the vaccine at position 181 was 78% (confidence interval 35% to 93%; P = 0.0028). Residue 169 is in a cationic glycosylated region recognized by broadly neutralizing and RV144-derived antibodies. The predicted distance between the two signature sites (21 ± 7 Å) and their match/mismatch dichotomy indicate that multiple factors may be involved in the protection observed in RV144. Genetic signatures of RV144 vaccination in V2 complement the finding of an association between high V1/V2-binding antibodies and reduced risk of HIV-1 acquisition, and provide evidence that vaccine-induced V2 responses plausibly had a role in the partial protection conferred by the RV144 regimen.

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Figure 1: Phylogenetic tree of env-V1/V2 nucleotide sequences.
Figure 2: Bar graphs representing the mutations at positions 169 and 181 based on sequences from 44 vaccine and 66 placebo recipients.

Accession codes

Primary accessions

GenBank/EMBL/DDBJ

Data deposits

Sequences are available under GenBank accession numbers JX446645JX448316.

Change history

  • 24 September 2012

    The web PDF was replaced to correct a corrupted Ångström symbol in three places

References

  1. Rerks-Ngarm, S. et al. Vaccination with ALVAC and AIDSVAX to prevent HIV-1 infection in Thailand. N. Engl. J. Med. 361, 2209–2220 (2009)

    Article  CAS  Google Scholar 

  2. Haynes, B. F. et al. Immune-correlates analysis of an HIV-1 vaccine efficacy trial. N. Engl. J. Med. 366, 1275–1286 (2012)

    Article  CAS  Google Scholar 

  3. Plotkin, S. A. & Gilbert, P. B. Nomenclature for immune correlates of protection after vaccination. Clin. Infect. Dis. 54, 1615–1617 (2012)

    Article  Google Scholar 

  4. Rolland, M. & Gilbert, P. Evaluating immune correlates in HIV type 1 vaccine efficacy trials: what RV144 may provide. AIDS Res. Hum. Retroviruses 28, 400–404 (2012)

    Article  CAS  Google Scholar 

  5. Gilbert, P. B., Self, S. G. & Ashby, M. A. Statistical methods for assessing differential vaccine protection against human immunodeficiency virus types. Biometrics 54, 799–814 (1998)

    Article  CAS  Google Scholar 

  6. Gilbert, P., Self, S., Rao, M., Naficy, A. & Clemens, J. Sieve analysis: methods for assessing from vaccine trial data how vaccine efficacy varies with genotypic and phenotypic pathogen variation. J. Clin. Epidemiol. 54, 68–85 (2001)

    Article  CAS  Google Scholar 

  7. Rolland, M. et al. Genetic impact of vaccination on breakthrough HIV-1 sequences from the STEP trial. Nature Med. 17, 366–371 (2011)

    Article  CAS  Google Scholar 

  8. Wei, X. et al. Antibody neutralization and escape by HIV-1. Nature 422, 307–312 (2003)

    Article  CAS  ADS  Google Scholar 

  9. Moore, P. L. et al. Limited neutralizing antibody specificities drive neutralization escape in early HIV-1 subtype C infection. PLoS Pathog. 5, e1000598 (2009)

    Article  Google Scholar 

  10. Tomaras, G. D. et al. Polyclonal B cell responses to conserved neutralization epitopes in a subset of HIV-1-infected individuals. J. Virol. 85, 11502–11519 (2011)

    Article  CAS  Google Scholar 

  11. Lynch, R. M. et al. The B cell response is redundant and highly focused on V1V2 during early subtype C infection in a Zambian seroconverter. J. Virol. 85, 905–915 (2011)

    Article  CAS  Google Scholar 

  12. Robb, M. L. et al. Risk behaviour and time as covariates for efficacy of the HIV vaccine regimen ALVAC-HIV (vCP1521) and AIDSVAX B/E: a post-hoc analysis of the Thai phase 3 efficacy trial RV 144. Lancet Infect. Dis. 12, 531–537 (2012)

    Article  CAS  Google Scholar 

  13. Gilbert, P. B., Wu, C. & Jobes, D. V. Genome scanning tests for comparing amino acid sequences between groups. Biometrics 64, 198–207 (2008)

    Article  CAS  MathSciNet  Google Scholar 

  14. Edlefsen, P. T. Model-based sieve analysis. Preprint at http://arxiv.org/abs/1206.6701 (2012)

  15. Gilbert, P. B. et al. Statistical interpretation of the RV144 HIV vaccine efficacy trial in Thailand: a case study for statistical issues in efficacy trials. J. Infect. Dis. 203, 969–975 (2011)

    Article  Google Scholar 

  16. Carlson, J. M. et al. Phylogenetic dependency networks: inferring patterns of CTL escape and codon covariation in HIV-1 Gag. PLoS Comput. Biol. 4, e1000225 (2008)

    Article  MathSciNet  Google Scholar 

  17. Felsenstein, J. Phylogenies and the comparative method. Am. Nat. 125, 1–15 (1985)

    Article  Google Scholar 

  18. Pond, S. L. & Frost, S. D. Datamonkey: rapid detection of selective pressure on individual sites of codon alignments. Bioinformatics 21, 2531–2533 (2005)

    Article  CAS  Google Scholar 

  19. Derdeyn, C. A. et al. Envelope-constrained neutralization-sensitive HIV-1 after heterosexual transmission. Science 303, 2019–2022 (2004)

    Article  CAS  ADS  Google Scholar 

  20. Moore, P. L. et al. Potent and broad neutralization of HIV-1 subtype C by plasma antibodies targeting a quaternary epitope including residues in the V2 loop. J. Virol. 85, 3128–3141 (2011)

    Article  CAS  Google Scholar 

  21. Doria-Rose, N. A. et al. A short segment of the HIV-1 gp120 V1/V2 region is a major determinant of resistance to V1/V2 neutralizing antibodies. J. Virol. 86, 8319–8323 (2012)

    Article  CAS  Google Scholar 

  22. McLellan, J. S. et al. Structure of HIV-1 gp120 V1/V2 domain with broadly neutralizing antibody PG9. Nature 480, 336–343 (2011)

    Article  CAS  ADS  Google Scholar 

  23. Rubinstein, N. D. et al. Computational characterization of B-cell epitopes. Mol. Immunol. 45, 3477–3489 (2008)

    Article  CAS  Google Scholar 

  24. Gilbert, P. B., Novitsky, V. & Essex, M. Covariability of selected amino acid positions for HIV type 1 subtypes C and B. AIDS Res. Hum. Retroviruses 21, 1016–1030 (2005)

    Article  CAS  Google Scholar 

  25. Poon, A. F., Lewis, F. I., Pond, S. L. & Frost, S. D. An evolutionary-network model reveals stratified interactions in the V3 loop of the HIV-1 envelope. PLoS Comput. Biol. 3, e231 (2007)

    Article  ADS  MathSciNet  Google Scholar 

  26. Prentice, R. L. et al. The analysis of failure times in the presence of competing risks. Biometrics 34, 541–554 (1978)

    Article  CAS  Google Scholar 

  27. Lunn, M. & McNeil, D. Applying Cox regression to competing risks. Biometrics 51, 524–532 (1995)

    Article  CAS  Google Scholar 

  28. Grambsch, P. & Therneau, T. M. Proportional hazards tests and diagnostics based on weighted residuals. Biometrika 81, 515–526 (1994)

    Article  MathSciNet  Google Scholar 

  29. Gilbert, P. B. Comparison of competing risks failure time methods and time-independent methods for assessing strain variations in vaccine protection. Stat. Med. 19, 3065–3086 (2000)

    Article  CAS  Google Scholar 

  30. Storey, J. D. The positive false discovery rate: a Bayesian interpretation and the q-value. Ann. Stat. 31, 2013–2035 (2003)

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

We thank B. F. Haynes and F. A. Matsen for advice and comments, and I. A. Wilson and R. L. Stanfield for assistance. This study was supported in part by an Interagency Agreement Y1-AI-2642-12 between US Army Medical Research and Material Command (USAMRMC) and the National Institutes of Allergy and Infectious Diseases. This work was also supported by a cooperative agreement (W81XWH-07-2-0067) between the Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., and the US Department of Defense (DOD). Additional support was provided to P.B.G. through the NIH grant 2R37AI05465-10. The opinions herein are those of the authors and should not be construed as official or representing the views of the US Department of Defense or the Department of the Army.

Author information

Authors and Affiliations

Authors

Contributions

M.R. conducted the sequence analysis with contributions from B.B.L., W.D. and B.S.M.; P.T.E. and P.B.G. conducted the site-scanning sieve analyses. M.R., S.T., E.S.-B. and J.I.M. designed the sequencing experiments. B.B.L., L.C., P.K., S.N., J.N.S., K.W., H.Z., M.B., S.H., A. Bates, M.L., A.O’S., E.L., A. Bradfield, G.I. and V.A. performed viral sequencing. T.H., A.C.deC., C.A.M., H.A. and M.J. contributed statistical analyses. C.C., S.M. and W.R.S. developed the EPIMAP approach. J.S.M., I.G. and P.D.K. identified antibody contact residues and performed V2 structural analyses. J.M.C. performed phylogenetic dependency network analyses. R.J.O’C., M.S.deS., S.N., S.R.-N., M.L.R., N.L.M. and J.H.K. conducted the RV144 trial. M.R., P.T.E., P.B.G., J.I.M. and J.H.K. designed the studies, analysed data, prepared the manuscript (with contributions from J.M.C., P.D.K. and W.R.S.) and supervised the project.

Corresponding author

Correspondence to Morgane Rolland.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Information 1

This file contains Supplementary Figures 1–5, Supplementary Methods, Supplementary Tables 1–11 and Supplementary Note 1. (PDF 973 kb)

Supplementary Information 2

This Supplementary Information file contains the Code for differential VE and for the site-scanning methods. (PDF 712 kb)

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Rolland, M., Edlefsen, P., Larsen, B. et al. Increased HIV-1 vaccine efficacy against viruses with genetic signatures in Env V2. Nature 490, 417–420 (2012). https://doi.org/10.1038/nature11519

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