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Record W4308305340 · doi:10.1101/2022.11.03.22281912

Antibody response durability following three-dose COVID-19 vaccination in people with HIV receiving suppressive ART

2022· preprint· en· W4308305340 on OpenAlexafffund
Hope R. Lapointe, Francis Mwimanzi, Peter K. Cheung, Yurou Sang, Fatima Yaseen, Sarah Speckmaier, Evan Barad, Nadia Moran-Garcia, Sneha Datwani, Maggie C. Duncan, Rebecca Kalikawe, Siobhan Ennis, Landon Young, Bruce Ganase, F. Harrison Omondi, Gisele Umviligihozo, Winnie Dong, Junine Toy, Paul Sereda, Laura Burns, Cecilia T. Costiniuk, Curtis Cooper, Aslam H. Anis, Victor C. M. Leung, Daniel T. Holmes, Mari L. DeMarco, Janet Simons, Malcolm Hedgcock, Natalie Prystajecky, Christopher F. Lowe, Marc G. Romney, Rolando Barrios, Silvia Guillemi, Chanson J. Brumme, Julio Montaner, Mark Hull, Marianne Harris, Masahiro Niikura, Mark A. Brockman, Zabrina L. Brumme

Bibliographic record

VenuemedRxiv · 2022
Typepreprint
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsBC Centre for Disease ControlUniversity of British ColumbiaUniversity of OttawaOttawa HospitalSimon Fraser UniversityProvidence Health CareMcGill University Health CentreHIV Legal NetworkSt. Paul's HospitalCentre for Advancing Health OutcomesAIDS Vancouver
FundersCanadian Institutes of Health ResearchAmerican Heart AssociationMinistry of Health, British ColumbiaBritish Columbia Centre for Disease ControlGenome British ColumbiaMichael Smith Health Research BCSimon Fraser UniversityPublic Health Agency of CanadaWellcome TrustProvidence Health CareBCCDC Foundation for Public HealthPublic Health Agency
KeywordsAntibodyMedicineVaccinationNeutralizationCoronavirus disease 2019 (COVID-19)CohortHuman immunodeficiency virus (HIV)ImmunologyVirologyInternal medicine

Abstract

fetched live from OpenAlex

ABSTRACT Background Limited data exist regarding longer-term antibody responses following three-dose COVID-19 vaccination, and the impact of a first SARS-CoV-2 infection during this time, in people living with HIV (PLWH) receiving suppressive antiretroviral therapy (ART). We quantified wild-type-(WT), Omicron BA.1- and Omicron BA.5-specific responses up to six months post-third dose in 64 PLWH and 117 controls who remained COVID-19-naive or experienced their first SARS-CoV-2 infection during this time. Design Longitudinal observational cohort. Methods We quantified WT- and Omicron-specific Anti-Spike receptor-binding domain IgG concentrations, ACE2 displacement activities and live virus neutralization at one, three and six months post-third vaccine dose. Results Third doses boosted all antibody measures above two-dose levels, but BA.1-specific responses remained significantly lower than WT-specific ones, with BA.5-specific responses lower still. Serum IgG concentrations declined at similar rates in COVID-19-naive PLWH and controls post-third dose (median WT- and BA.1-specific half-lives were between 66-74 days for both groups). Antibody function also declined significantly yet comparably between groups: six months post-third dose, BA.1-specific neutralization was undetectable in >80% of COVID-19 naive PLWH and >90% of controls. Breakthrough SARS-CoV-2 infection boosted antibody concentrations and function significantly above vaccine-induced levels in both PLWH and controls, though BA.5-specific neutralization remained significantly poorer than BA.1 even post-breakthrough. Conclusions Following three-dose COVID-19 vaccination, antibody response durability in PLWH receiving ART is comparable to controls. PLWH also mounted strong responses to breakthrough infection. Due to temporal response declines however, COVID-19-naive individuals, regardless of HIV status, would benefit from a fourth dose within 6 months of their third.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.374
Teacher spread0.337 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2022
Admission routes2
Has abstractyes

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