AI Article Synopsis

  • Researchers aimed to understand why oral vaccines, like the oral poliovirus vaccine (OPV), are less effective in low-income countries by analyzing immune responses in 292 infants from India.
  • Despite measuring various immune factors, no specific immune profile was linked to the effectiveness of OPV, though higher stool viral pathogen presence was noted in infants who didn't respond to the vaccine.
  • By using machine learning, they demonstrated that it's possible to predict vaccine response based on immune markers and infection status, achieving an accuracy of around 58%, but emphasized that better results may come from studying mucosal tissue more closely.

Article Abstract

Identification of the causes of poor oral vaccine immunogenicity in low-income countries might lead to more effective vaccines. We measured mucosal and systemic immune parameters at the time of vaccination with oral poliovirus vaccine (OPV) in 292 Indian infants aged 6-11 months, including plasma cytokines, leukocyte counts, fecal biomarkers of environmental enteropathy and peripheral blood T-cell phenotype, focused on gut-homing regulatory CD4+ populations. We did not find a distinct immune phenotype associated with OPV immunogenicity, although viral pathogens were more prevalent in stool at the time of immunization among infants who failed to seroconvert (63.9% vs. 45.6%,  = 0.002). Using a machine-learning approach, we could predict seroconversion a priori using immune parameters and infection status with a median 58% accuracy (cross-validation IQR: 50-69%) compared with 50% expected by chance. Better identification of immune predictors of OPV immunogenicity is likely to require sampling of mucosal tissue and improved oral poliovirus infection models.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7089977PMC
http://dx.doi.org/10.1038/s41541-020-0178-5DOI Listing

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