OMIC Technologies and Vaccine Development: From the Identification of Vulnerable Individuals to the Formulation of Invulnerable Vaccines

Nicola Cotugno, Alessandra Ruggiero, Veronica Santilli, Emma Concetta Manno, Salvatore Rocca, Sonia Zicari, Donato Amodio, Manuela Colucci, Paolo Rossi, Ofer Levy, Federico Martinon-Torres, Andrew J Pollard, Paolo Palma

Research output: Contribution to journalReview articlepeer-review


Routine vaccination is among the most effective clinical interventions to prevent diseases as it is estimated to save over 3 million lives every year. However, the full potential of global immunization programs is not realised because population coverage is still suboptimal. This is also due to the inadequate immune response and paucity of informative correlates of protection upon immunization of vulnerable individuals such as newborns, preterm infants, pregnant women, and elderly individuals as well as those patients affected by chronic and immune compromising medical conditions. In addition, these groups are undervaccinated for a number of reasons, including lack of awareness of vaccine-preventable diseases and uncertainty or misconceptions about the safety and efficacy of vaccination by parents and healthcare providers. The presence of these nonresponders/undervaccinated individuals represents a major health and economic burden to society, which will become particularly difficult to address in settings with limited public resources. This review describes innovative and experimental approaches that can help identify specific genomic profiles defining nonresponder individuals for whom specific interventions might be needed. We will provide examples that show how such information can be useful to identify novel biomarkers of safety and immunogenicity for future vaccine trials. Finally, we will discuss how system biology "OMICs" data can be used to design bioinformatic tools to predict the vaccination outcome providing genetic and molecular "signatures" of protective immune response. This strategy may soon enable identification of signatures highly predictive of vaccine safety, immunogenicity, and efficacy/protection thereby informing personalized vaccine interventions in vulnerable populations.

Original languageEnglish
Pages (from-to)8732191
JournalJournal of Immunology Research
Publication statusPublished - 2019


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