Citations

Abstract Despite the tremendous success of the classical “isolate, inactivate, and inject” approach to vaccine development, new breakthroughs in vaccine research are increasingly reliant on novel approaches that incorporate cutting edge technology and advances in innate and adaptive immunology, microbiology, virology, pathogen biology, genetics, bioinformatics, and many other disciplines in order to: (1) deepen our understanding of the key biological processes that lead to protective immunity, (2) observe vaccine responses on a global, systems level, and (3) directly apply the new knowledge gained to the development of next-generation vaccines with improved safety profiles, enhanced efficacy, and even targeted utility in select populations. Here we highlight five key components foundational to vaccinomics efforts: applied immunogenomics, next generation sequencing and other cutting-edge “omics” technologies, advanced bioinformatics and analysis techniques, and finally, systems biology applied to immune profiling and vaccine responses. We believe these “game changers” will play a critical role in moving us toward the rational and directed development of new vaccines in the 21st century.

Abstract In this article we define vaccinomics as the integration of immunogenetics and immunogenomics with systems biology and immune profiling. Vaccinomics is based on the use of cutting edge, high-dimensional (so called “omics”) assays and novel bioinformatics approaches to the development of next-generation vaccines and the expansion of our capabilities in individualized medicine. Vaccinomics will allow us to move beyond the empiric “isolate, inactivate, and inject” approach characterizing past vaccine development efforts, and toward a more detailed molecular and systemic understanding of the carefully choreographed series of biological processes involved in developing viral vaccine-induced “immunity.” This enhanced understanding will then be applied to overcome the obstacles to the creation of effective vaccines to protect against pathogens, particularly hypervariable viruses, with the greatest current impact on public health. Here we provide an overview of how vaccinomics will inform vaccine science, the development of new vaccines and/or clinically relevant biomarkers or surrogates of protection, vaccine response heterogeneity, and our understanding of immunosenescence.

Despite improvements in clinician education, symptom awareness, and respiratory precautions, influenza vaccination rates for health care workers have remained unacceptably low for more than three decades, adversely affecting patient safety. When public health is jeopardized, and a safe, low-cost, and effective method to achieve patient safety exists, health care organizations and public health authorities have a responsibility to take action and change the status quo. Mandatory influenza vaccination for health care workers is supported not only by scientific data but also by ethical principles and legal precedent. The recent influenza pandemic provides an opportunity for policymakers to reconsider the benefits of mandating influenza vaccination for health care workers, including building public trust, enhancing patient safety, and strengthening the health care workforce.

Abstract Aberrant glycosylation is a well-described hallmark of cancer. In a previous ovarian cancer case control study that examined polymorphisms in 26 glycosylation-associated genes, we found strong statistical evidence (P = 0.00017) that women who inherited two copies of a single-nucleotide polymorphism in the UDP-N-acetylgalactosamine:polypeptide N-acetylgalactosaminyltransferase, GALNT1, had decreased ovarian cancer risk. The current study attempted to replicate this observation. The GALNT1 single-nucleotide polymorphism rs17647532 was genotyped in 6,965 cases and 8,377 controls from 14 studies forming the Ovarian Cancer Association Consortium. The fixed effects estimate per rs17647532 allele was null (odds ratio, 0.99; 95% confidence interval, 0.92-1.07). When a recessive model was fit, the results were unchanged. Test for hetero geneity of the odds ratios revealed consistency across the 14 replication sites but significant differences compared with the original study population (P = 0.03). This study underscores the need for replication of putative findings in genetic association studies. Cancer Epidemiol Biomarkers Prev; 19(2); 600–4