Publication

Baseline host determinants of robust human HIV-1 vaccine-induced immune responses: A meta-analysis of 26 vaccine regimens

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Last modified
  • 06/25/2025
Type of Material
Authors
    Yunda Huang, Fred Hutchinson Cancer CenterYuanyuan Zhang, Fred Hutchinson Cancer CenterKelly E Seaton, Duke UniversityStwphen De Rosa, Fred Hutchinson Cancer CenterJack Heptinstall, Duke UniversityLindsay N Carpp, Fred Hutchinson Cancer CenterApril Kaur Randhawa, Fred Hutchinson Cancer CenterLyle R McKinnon, University of ManitobaPaul McLaren, University of ManitobaEdna Viegas, Inst Nacl SaudeGlenda E Gray, University of WitwatersrandGavin Churchyard, Aurum Institute, JohannesburgSusan P Buchbinder, San Francisco Department of Public HealthSrilatha Edupuganti, Emory UniversityLinda-Gail Bekker, University of Cape TownMichael C Keefer, University of RochesterMina C Hosseinipour, University of North Carolina ProjectPaul A Goepfert, University of Alabama BirminghamKristen W Cohen, Fred Hutchinson Cancer CenterBrian D Williamson, Fred Hutchinson Cancer CenterJuliana M McElrath, Fred Hutchinson Cancer CenterGeorgia D Tomaras, Duke UniversityJuilee Thakar, University of RochesterJames J Kobie, University of Alabama Birmingham
Language
  • English
Date
  • 2022-10-01
Publisher
  • ELSEVIER
Publication Version
Copyright Statement
  • © 2022 The Author(s)
License
Final Published Version (URL)
Title of Journal or Parent Work
Volume
  • 84
Start Page
  • 104271
End Page
  • 104271
Supplemental Material (URL)
Abstract
  • Background: The identification of baseline host determinants that associate with robust HIV-1 vaccine-induced immune responses could aid HIV-1 vaccine development. We aimed to assess both the collective and relative performance of baseline characteristics in classifying individual participants in nine different Phase 1-2 HIV-1 vaccine clinical trials (26 vaccine regimens, conducted in Africa and in the Americas) as High HIV-1 vaccine responders. Methods: This was a meta-analysis of individual participant data, with studies chosen based on participant-level (vs. study-level summary) data availability within the HIV-1 Vaccine Trials Network. We assessed the performance of 25 baseline characteristics (demographics, safety haematological measurements, vital signs, assay background measurements) and estimated the relative importance of each characteristic in classifying 831 participants as High (defined as within the top 25th percentile among positive responders or above the assay upper limit of quantification) versus Non-High responders. Immune response outcomes included HIV-1-specific serum IgG binding antibodies and Env-specific CD4+ T-cell responses assessed two weeks post-last dose, all measured at central HVTN laboratories. Three variable importance approaches based on SuperLearner ensemble machine learning were considered. Findings: Overall, 30.1%, 50.5%, 36.2%, and 13.9% of participants were categorized as High responders for gp120 IgG, gp140 IgG, gp41 IgG, and Env-specific CD4+ T-cell vaccine-induced responses, respectively. When including all baseline characteristics, moderate performance was achieved for the classification of High responder status for the binding antibody responses, with cross-validated areas under the ROC curve (CV-AUC) of 0.72 (95% CI: 0.68, 0.76) for gp120 IgG, 0.73 (0.69, 0.76) for gp140 IgG, and 0.67 (95% CI: 0.63, 0.72) for gp41 IgG. In contrast, the collection of all baseline characteristics yielded little improvement over chance for predicting High Env-specific CD4+ T-cell responses [CV-AUC: 0.53 (0.48, 0.58)]. While estimated variable importance patterns differed across the three approaches, female sex assigned at birth, lower height, and higher total white blood cell count emerged as significant predictors of High responder status across multiple immune response outcomes using Approach 1. Of these three baseline variables, total white blood cell count ranked highly across all three approaches for predicting vaccine-induced gp41 and gp140 High responder status. Interpretation: The identified features should be studied further in pursuit of intervention strategies to improve vaccine responses and may be adjusted for in analyses of immune response data to enhance statistical power. Funding: National Institute of Allergy and Infectious Diseases (UM1AI068635 to YH, UM1AI068614 to GDT, UM1AI068618 to MJM, and UM1 AI069511 to MCK), the Duke CFAR P30 AI064518 to GDT, and National Institute of Dental and Craniofacial Research (R01DE027245 to JJK). This work was also supported by the Bill and Melinda Gates Foundation. The content is solely the responsibility of the authors and does not necessarily represent the official views of any of the funding sources.
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Keywords
Research Categories
  • Health Sciences, Immunology
  • Health Sciences, Medicine and Surgery

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