Abstract

Understanding the determinants of broadly neutralizing antibody (bNAb) evolution is crucial for the development of bNAb-based HIV vaccines1. Despite emerging information on cofactors that promote bNAb evolution in natural HIV-1 infections, in which the induction of bNAbs is genuinely rare2, information on the impact of the infecting virus strain on determining the breadth and specificity of the antibody responses to HIV-1 is lacking. Here we analyse the influence of viral antigens in shaping antibody responses in humans. We call the ability of a virus strain to induce similar antibody responses across different hosts its antibody-imprinting capacity, which from an evolutionary biology perspective corresponds to the viral heritability of the antibody responses. Analysis of 53 measured parameters of HIV-1-binding and neutralizing antibody responses in a cohort of 303 HIV-1 transmission pairs (individuals who harboured highly related HIV-1 strains and were putative direct transmission partners or members of an HIV-1 transmission chain) revealed that the effect of the infecting virus on the outcome of the bNAb response is moderate in magnitude but highly significant. We introduce the concept of bNAb-imprinting viruses and provide evidence for the existence of such viruses in a systematic screening of our cohort. The bNAb-imprinting capacity can be substantial, as indicated by a transmission pair with highly similar HIV-1 antibody responses and strong bNAb activity. Identification of viruses that have bNAb-imprinting capacities and their characterization may thus provide the potential to develop lead immunogens.

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Data availability

The antibody response and patient data reported in this paper are completely tabulated in Supplementary Data 1, 2. Sequence data of T282–R282 Env consensus and Env clones reported in Fig. 2c are deposited in GenBank. Accession codes are listed in Extended Data Fig. 6b. The raw sequencing files of the Illumina full HIV sequencing data of patients T282 and R282 referred to in Fig. 2c and Extended Data Fig. 6 have been uploaded to https://zenodo.org/ (https://doi.org/10.5281/zenodo.1324259). pol sequence data of the 606 studied cases are available from the corresponding authors and/or the SHCS scientific board (http://www.shcs.ch/contact) upon request.

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Acknowledgements

Financial support for this study has been provided by the Swiss National Science Foundation (SNF; 314730_152663 and 314730_172790 to A.T.; 324730B_179571 to H.F.G.; PZ00P3-142411 and BSSGI0_155851 to R.D.K.), the Clinical Priority Research Program of the University of Zurich (Viral infectious diseases: Zurich Primary HIV Infection Study to H.F.G. and A.T.), the Yvonne-Jacob Foundation (to H.F.G.), the Swiss Vaccine Research Institute (to A.T., H.F.G. and R.D.K.) and the SystemsX.ch grant AntibodyX (to A.T.). This study has been cofinanced within the framework of the Swiss HIV Cohort Study, supported by the SNF (33CS30_148522 to H.F.G.), by the small nested SHCS project 744 (to A.T.) and by the SHCS research foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The SHCS data are collected by the five Swiss University Hospitals, two Cantonal Hospitals, 15 affiliated hospitals and 36 private physicians (listed in http://www.shcs.ch/180-health-care-providers). We thank the patients participating in the ZPHI and the SHCS and their physicians and study nurses for patient care and D. Perraudin and M. Minichiello for administrative assistance.

Reviewer information

Nature thanks P. Lemey, J. Overbaugh and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Author notes

    • Thomas Liechti

    Present address: ImmunoTechnology Section, Vaccine Research Center, NIAID, National Institutes of Health, Bethesda, MD, USA

  1. A list of participants and their affiliations appears at the end of the paper

  2. These authors contributed equally: Roger D. Kouyos, Peter Rusert, Claus Kadelka

  3. These authors jointly supervised this work: Roger D. Kouyos, Huldrych F. Günthard, Alexandra Trkola

Affiliations

  1. Institute of Medical Virology, University of Zurich, Zurich, Switzerland

    • Roger D. Kouyos
    • , Peter Rusert
    • , Claus Kadelka
    • , Michael Huber
    • , Alex Marzel
    • , Hanna Ebner
    • , Merle Schanz
    • , Thomas Liechti
    • , Nikolas Friedrich
    • , Dominique L. Braun
    • , Alexandra U. Scherrer
    • , Jacqueline Weber
    • , Therese Uhr
    • , Nicolas S. Baumann
    • , Christine Leemann
    • , Herbert Kuster
    • , Jürg Böni
    • , Karin J. Metzner
    • , Huldrych F. Günthard
    • , Alexandra Trkola
    • , Jürg Böni
    • , Michael Huber
    • , Alexandra U. Scherrer
    •  & Alexandra Trkola
  2. Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland

    • Roger D. Kouyos
    • , Claus Kadelka
    • , Alex Marzel
    • , Dominique L. Braun
    • , Alexandra U. Scherrer
    • , Christine Leemann
    • , Herbert Kuster
    • , Karin J. Metzner
    • , Huldrych F. Günthard
    • , Alexia Anagnostopoulos
    • , Dominique L. Braun
    • , Jan Fehr
    • , Huldrych F. Günthard
    • , Barbara Hasse
    • , Roger D. Kouyos
    • , Helen Kovari
    • , Bruno Ledergerber
    • , Karin J. Metzner
    • , Nicolas Müller
    • , Alexandra U. Scherrer
    • , Roberto Speck
    •  & Rainer Weber
  3. Clinique de La Source, Lausanne, Switzerland

    • Jean-Philippe Chave
  4. Division of Infectious Diseases, University Hospital Lausanne, University of Lausanne, Lausanne, Switzerland

    • Matthias Cavassini
    •  & Matthias Cavassini
  5. Division of Infectious Diseases, Regional Hospital Lugano, Lugano, Switzerland

    • Enos Bernasconi
    •  & Enos Bernasconi
  6. Division of Infectious Diseases, Cantonal Hospital St. Gallen, St. Gallen, Switzerland

    • Matthias Hoffmann
    • , Matthias Hoffmann
    • , Christian Kahlert
    • , Dunja Nicca
    • , Patrick Schmid
    •  & Pietro Vernazza
  7. Division of Infectious Diseases, University Hospital Geneva, University of Geneva, Geneva, Switzerland

    • Alexandra Calmy
    •  & Alexandra Calmy
  8. Division of Infectious Diseases, University Hospital Basel, University of Basel, Basel, Switzerland

    • Manuel Battegay
    • , Manuel Battegay
    • , Luigia Elzi
    • , Hans H. Hirsch
    • , Catia Marzolini
    •  & Marcel Stöckle
  9. Department of Infectious Diseases, University Hospital Bern, University of Bern, Bern, Switzerland

    • Andri Rauch
    • , Andri Rauch
    •  & Gilles Wandeler
  10. Laboratory of Virology, Division of Infectious Diseases, University Hospital Geneva, University of Geneva, Geneva, Switzerland

    • Sabine Yerly
    • , Hansjakob Furrer
    • , Laurent Kaiser
    •  & Sabine Yerly
  11. Division of Immunology and Allergy, University Hospital Lausanne, University of Lausanne, Lausanne, Switzerland

    • Vincent Aubert
    • , Guiseppe Pantaleo
    •  & Matthieu Perreau
  12. Division of Infection Diagnostics, Department of Biomedicine-Petersplatz, University of Basel, Basel, Switzerland

    • Thomas Klimkait
    • , Hans H. Hirsch
    •  & Thomas Klimkait
  13. Basel Institute for Clinical Epidemiology and Biostatistics, University Hospital Basel, University of Basel, Basel, Switzerland

    • Heiner C. Bucher
  14. Institute of Microbiology, University Hospital Lausanne, University of Lausanne, Lausanne, Switzerland

    • Angela Ciuffi
  15. Centre for Laboratory Medicine, Canton St. Gallen, St. Gallen, Switzerland

    • Günter Dollenmaier
  16. Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland

    • Matthias Egger
  17. Global Health Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    • Jacques Fellay
  18. Clinic for Infectious Diseases and Hospital Hygiene, Kantonsspital Aarau, Aarau, Switzerland

    • Christoph A. Fux
  19. Positive Council, Zurich, Switzerland

    • David Haerry
  20. Clinic for Obstetrics, University Hospital Basel, University of Basel, Basel, Switzerland

    • Irene Hösli
  21. Children’s Hospital of Eastern Switzerland, St. Gallen, Switzerland

    • Christian Kahlert
  22. Institute of Global Health, University of Geneva, Geneva, Switzerland

    • Olivia Keiser
  23. Cantonal Institute of Microbiology, Bellinzona, Bellinzona, Switzerland

    • Gladys Martinetti
  24. Department of Obstetrics and Gynecology, University Hospital Geneva, University of Geneva, Geneva, Switzerland

    • Begona Martinez de Tejada
  25. University Children’s Hospital, University of Zurich, Zurich, Switzerland

    • Paolo Paioni
  26. University Children’s Hospital, University of Basel, Basel, Switzerland

    • Christoph Rudin
  27. Kantonsspital Baselland, University of Basel, Basel, Switzerland

    • Philip Tarr

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Consortia

  1. The Swiss HIV Cohort Study

Contributions

R.D.K., P.R., C.K., H.F.G. and A.T. conceived and designed the study and analysed data. M.Hu., A.M., H.E., M.S., T.L., N.F., J.W., T.U., N.S.B., C.L., H.K., J.B. and K.J.M. conducted experiments and analysed data. D.L.B., A.U.S., J.-P.C., M.C., E.B., M.Ho., A.C., M.B., A.R., S.Y., V.A., T.K., H.F.G. and the members of the Swiss HIV Cohort Study conceived and managed the SHCS and ZPHI cohorts, collected and contributed patient samples and clinical data. R.D.K., C.K., M.S., H.F.G. and A.T. wrote the manuscript, on which all co-authors commented.

Competing interests

The University of Zurich filed a European patent application (EP18184854.0) that includes the full envelope sequences of patients T282 and R282 or components thereof for use as bNAb-inducing immunogens with R.D.K., P.R., H.F.G. and A.T. listed as inventors. All other authors declare no competing interests.

Corresponding authors

Correspondence to Roger D. Kouyos or Huldrych F. Günthard or Alexandra Trkola.

Extended data figures and tables

  1. Extended Data Fig. 1 Selection and characterization of the HIV-1 transmission cohort used to investigate the antibody imprinting capacity of HIV-1.

    a, b, Principal aims of the study. a, Defining the binding and neutralizing antibody imprinting capacity of HIV-1 strains/immunogens (that is, determining the heritability of these responses). The schematic depicts the possible outcomes of a transmission. The recipient may either have the same or a different type of antibody response as the transmitter. b, Creating means to identify bNAb-imprinting HIV-1 strains. The schematic depicts the possible outcomes of a transmission if the transmitter has a bNAb response. The recipient may also develop a bNAb response or not. c, Workflow of the study. d, The search for transmission pairs started with a cohort of 4,281 patients, who were included in the Swiss 4.5K Screen4 and for which HIV-1 antibody-binding data are available5. e, Histogram of the genetic (pol) distance of the 303 identified transmission pairs. f, Genetic (pol) distance to the transmission partner stratified by duration of untreated infection for the n = 606 patients in the transmission pair cohort. As in the Swiss 4.5K Screen, patients are grouped by infection length into categories of 1–3 years (n = 138), 3–5 years (n = 252) and more than 5 years (n = 216). Medians are shown (centre line), each box spans the IQR and each whisker extends to the most extreme value no more than 1.5× IQR from the box. More extreme values are shown as points.

  2. Extended Data Fig. 2 Neutralization score analyses and strategies to determine the antibody-imprinting capacity of HIV-1.

    a, Neutralization activity against a multi-clade 14-virus panel of all 606 transmitter and recipient plasma samples. Dashed horizontal lines at 20%, 50% and 80% and brackets display the thresholds used for the assignment of scores. On the basis of these data, each plasma–virus combination received a score of 0–3. The neutralization score of a plasma sample is the sum of the 14 individual scores against the panel viruses (0–42). Individual data points are shown as jittered circles. b, c, Distribution of neutralization breadth (b; P = 0.69) and neutralization scores (c; P = 0.40) in n = 303 transmitters and recipients (P values: two-tailed Wilcoxon signed-rank test). Medians are shown (centre line), each box spans the IQR and the whiskers extend to the 10% and 90% percentile. Individual data points are shown as jittered circles. d, Scatter plot of the neutralization score of recipients and transmitters for all 303 transmission pairs (Spearman; ρ = 0.139, P = 0.015). The number of pairs with the indicated values is depicted by dot size. e, Strategies to determine the antibody-imprinting capacity of HIV-1. For each of the 14 neutralization and 39 binding reactivities, the similarity in reactivity (Spearman correlation) was compared between transmitters and recipients to test whether transmission partners shared similar antibody responses.

  3. Extended Data Fig. 3 Antibody similarity measurements are insensitive to the assignment of transmitter and recipient status, to choice of confounders and outliers.

    a, Distribution of Spearman correlations (as in Fig. 1a) of neutralization–antibody-binding responses in pairs, in which the role of transmitter and recipient was randomly assigned within each of the n = 303 pairs (1,000 reassignments). Each violin plot is smoothed using a normal kernel, and its width represents the likelihood of a certain Spearman correlation. Grey daggers correspond to the similarities retrieved for the actual assignment of transmitter and recipient used in this study. For all investigated parameters, there was no statistically significant difference between the actual assignment and the shuffled assignment of transmitters and recipients (two-sided PSpearman > 0.05). b, Proportion of variability in responses explained by the infecting virus, determined using mixed-effect Tobit regression models (black circles) and linear mixed-effect models (horizontal bars). Standard errors of the linear mixed-effect models (black error bar; obtained by leave-one-out analyses) are shown. In each row, the models were adjusted for the indicated set of cofactors and only transmission pairs with complete information were included (number of pairs shown per row). c, Proportion of variability in responses explained by the infecting virus, determined using mixed-effect Tobit regression models on the full 303 pairs for which missing cofactors were imputed based on the other cofactors. Each violin plot is the result of 100 independent imputations, smoothed using a normal kernel, and its width represents the likelihood of a certain variability. Medians are shown (lines).

  4. Extended Data Fig. 4 Similarity of neutralization and antibody-binding responses in subtype-B-infected transmission pairs.

    ad, To exclude influences of the subtype of the infecting virus, as a sensitivity analysis to Fig. 1a, b, the similarity of neutralization (a, b) and antibody-binding (c, d) responses was tested for the subset of subtype-B-infected transmission pairs (n = 254). a, c, Spearman correlation of the neutralization–antibody-binding response to each pseudovirus or antigen. Significant correlations (two-sided PSpearman < 0.05) are coloured. b, d, Average Spearman correlation of antibody responses in observed transmission pairs (n = 303) compared to two alternative scenarios: (1) completely random reassignment of recipients to transmitters and (2) random reassignment of recipients to transmitters with same demographics (subtype, ethnicity and untreated infection length). One-sided P values were derived from comparison with 1,000 reassignments. Each violin plot is smoothed using a normal kernel, and its width represents the likelihood of a certain average correlation in the respective alternative scenario. The medians are shown (white dots), each box spans the IQR and each whisker extends to the most extreme value no more than 1.5× IQR from the box.

  5. Extended Data Fig. 5 Within-pair similarity of neutralization and binding responses remains significant for transmission pairs with lower genetic distance.

    ac, As a sensitivity analysis for Fig. 1b, the average similarity of neutralization and antibody-binding responses was determined for those transmission pairs with a genetic distance <0.03 (a, n = 280), <0.02 (b, n = 243) or <0.01 (c, n = 148), and compared to two alternative scenarios: (1) completely random reassignment of recipients to transmitters and (2) random reassignment of recipients to transmitters with same demographics (subtype, ethnicity and untreated infection length). One-sided P values were derived from comparison with 1,000 reassignments. Each violin plot is smoothed using a normal kernel, and its width represents the likelihood of a certain average correlation in the respective alternative scenario. The medians are shown (white dots), each box spans the IQR and each whisker extends to the most extreme value no more than 1.5× IQR from the box. d, e, As a sensitivity analysis for Fig. 1c, the proportion of variability in responses explained by the infecting virus, determined using unadjusted (d) and fully adjusted (e) (adjusted for duration of infection, subtype, ethnicity, log viral load and diversity) mixed-effect Tobit regression models is shown when restricting the analysis to closely related pairs (threshold on the x axis).

  6. Extended Data Fig. 6 Full-genome comparison of T282 and R282 consensus sequences.

    a, Multiple sequence alignment of the full genome consensus sequences of T282 and R282 with HXB2. Nucleotide variations from HXB2 are depicted by colour: A (red), T (green), C (blue), G (yellow); deletions by a horizontal bar. b, Overview and accession codes of env sequences derived from three bNAb-imprinting transmission pairs depicted in Fig. 2c. Indicated transmission time estimate is based on estimated time of infection of recipient.

  7. Extended Data Fig. 7 Mutant virus neutralization mapping and distribution of transmission pair characteristics among pairs with and without transferability of antibody response.

    a, Changes in neutralization activity of wild-type and mutant viruses were compared for six bNAbs (four targeting the CD4 binding site, two targeting the V3 glycan) and for the plasma of the elite-neutralizing pair. Increases in mutant half-maximum inhibitory concentration (IC50) values >tenfold and decreases in mutant half-maximum neutralization titre (NT50) values >two fold appear coloured. b, c, Association of transmission pair characteristics and transferability of antibody response in n = 303 transmission pairs. Transferability of antibody responses was determined according to relatively liberal (strength threshold = 4 and similarity threshold = 0.4) and strict criteria (strength threshold = 5 and similarity threshold = 0.5). b, Influence of continuous variables (mean log10 HIV-1 RNA in the transmission pair, the difference of these log10 RNA values, and the genetic distance in the pair) tested by univariable logistic regression. c, Influence of categorical variables (acute infection, long virus evolution, infecting subtype, ethnicity and transmission mode) tested by two-tailed Fisher’s exact test. The area of a rectangle corresponds to the number of pairs with the respective characteristic. MSM, men who have sex with men; HET, heterosexual transmission; IDU, intravenous drug users.

  8. Extended Data Fig. 8 Systematic strategy to trace HIV-1 strains with bNAb-imprinting capacity.

    HIV-1 strains that have the capacity to induce bNAb activity can be identified by measuring the similarity and the strength of the antibody response in each pair. A stepwise description of the approach is shown. See Methods ‘Systematic strategy to trace HIV-1 strains with bNAb-imprinting capacity’ for details.

  9. Extended Data Table 1 Patient demographics of the study population and entire population in the Swiss 4.5K screen
  10. Extended Data Table 2 Proportion of variability of neutralization and binding responses explained by the infecting virus strain using variously adjusted mixed-effect Tobit models

Supplementary Information

  1. Supplementary Methods

    This file contains a Supplementary Methods, providing extended methods descriptions.

  2. Reporting Summary

  3. Supplementary Data

    This file contains Supplementary Dataset 1: Patient characteristics, neutralisation and binding responses of the 606 patients in the transmission pair cohort.

  4. Supplementary Data

    This file contains Supplementary Dataset 2: Neutralization data of bnAbs and the elite-neutralizing transmission pair.

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https://doi.org/10.1038/s41586-018-0517-0

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