Multi-variate statistical and machine learning reveals the interplay between sex and age in antibody responses to de novo SARS-CoV-2 infection and vaccination

Prevention of negative COVID19 infection outcomes and infection/vaccine-acquired immunity is associated with the quality of antibody responses, whose variance by age and sex are poorly understood. Integrated, network approaches, identified sex and age effects in antibody responses and neutralization...

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Bibliographic Details
Published in:bioRxiv 2023-12
Main Authors: Cuperlovic-Culf, Miroslava, Bennett, Steffany, Galipeau, Yannick, Mccluskie, Pauline S, Arnold, Corey, Bagheri, Salman, Cooper, Curtis L, Langlois, Marc-Andre, Fritz, Jorg, Piccirillo, Ciriaco A, Crawley, Angela M
Format: Article
Language:English
Subjects:
Age
Antibodies
Correlation analysis
COVID-19
Females
Immunoglobulin A
Infections
Learning algorithms
Machine learning
Severe acute respiratory syndrome coronavirus 2
Sex differences
Stochasticity
Vaccines
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Summary:Prevention of negative COVID19 infection outcomes and infection/vaccine-acquired immunity is associated with the quality of antibody responses, whose variance by age and sex are poorly understood. Integrated, network approaches, identified sex and age effects in antibody responses and neutralization potential of de novo infection and vaccination throughout the Covid-19 pandemic. Cluster analysis found neutralization values followed SARS-CoV-2 specific receptor binding RIgG, spike SIgG and S and RIgA levels based on COVID19 status. Stochastic behavior tests and other analytical methods revealed sex differences only in persons 60 y.o. females. Complex correlation analyses found vaccination induced less antibody isotype switching and neutralization in older persons, especially in females. Sex dependent antibody & neutralization behavior decayed fastest in older males and with vaccination. Such sex and age characterization by machine learning can direct studies integrating cell mediated responses to define yet elusive correlates of protection and inform age and sex precision-focused vaccine design.Competing Interest StatementThe authors have declared no competing interest.
DOI:10.1101/2023.12.05.569965