A multi-omics systems vaccinology resource to develop and test computational models of immunity

• DOI: 10.1016/j.crmeth.2024.100731
• Publication Date: 2024-03-14T14:38:40Z
• Authors: Pramod Shinde; Ferran Soldevila; Joaquin Reyna; Minori Aoki; Mikkel Rasmussen; Lisa Willemsen; Mari Kojima; Brendan Ha; Jason A. Greenbaum; James A. Overton; Hector Guzman-Orozco; Somayeh Nili; Shelby Orfield; Jeremy P. Gygi; Ricardo da Silva ...; Alessandro Sette; Barry Grant; Lars Rønn Olsen; Anna Konstorum; Leying Guan; Ferhat Ay; Steven H. Kleinstein; Bjoern Peters
• Keywords: CONTEST; Predictive modelling

Systems vaccinology studies have identified factors affecting individual vaccine responses, but comparing these findings is challenging due to varying study designs. To address this lack of reproducibility, we established a community resource for Bordetella pertussis booster responses and host annual contests predicting patients' vaccination outcomes. We report here on our experiences with the "dry-run" prediction contest. found that, among 20+ models adopted from literature, most successful model outcome was based age alone. This confirms concerns about reproducibility conclusions between different studies. Further, newly trained models, handling baseline information target variables crucial. Overall, multiple co-inertia analysis gave best results tested modeling approaches. Our goal engage in challenges by making data available opening public contest August 2024.