An Explorative Biomarker Study for Vaccine Responsiveness after a Primary Meningococcal Vaccination in Middle-Aged Adults.

In the older adult, the benefits of vaccination to prevent infectious disease are limited, mainly because of the adaptive immune system's inability to generate protective immunity. The age-dependent decrease in immunological competence, often referred to as 'immunosenescence', results from the progressive deterioration of innate and adaptive immune responses. Most insights into mechanisms of immunological aging have been derived from studies of mouse models. In this Review, we explore how well such models are applicable to understanding the aging process throughout the 80-100 years of human life and discuss recent advances in identifying and characterizing the mechanisms that underlie age-associated defective adaptive immunity in humans.

To review findings from major epidemiologic studies regarding risk factors for and consequences of elevated markers of inflammation in older adults. Most large, current epidemiologic studies of older adults have measured serum interleukin-6 (IL-6), C-reactive protein (CRP) and tumor necrosis factor alpha (TNF-alpha) and some studies also include more extensive batteries of measures including soluble receptors. There are few defined risk factors for the modest elevations in inflammatory markers seen with aging. These include visceral adiposity, lower sex steroid hormones, smoking, depression and periodontal disease. Of the markers assessed, IL-6 is most robustly associated with incident disease, disability and mortality. Though correlated with age, the etiology of elevated inflammatory markers remains incompletely defined. Inflammation, especially IL-6 may be a common cause of multiple age-related diseases or a final common pathway by which disease leads to disability and adverse outcomes in older adults. Future research targeting inflammation should examine these pathways. Copyright © 2011. Published by Elsevier B.V.

A major goal of systems biology is the development of models that accurately predict responses to perturbation. Constructing such models requires the collection of dense measurements of system states, yet transformation of data into predictive constructs remains a challenge. To begin to model human immunity, we analyzed immune parameters in depth both at baseline and in response to influenza vaccination. Peripheral blood mononuclear cell transcriptomes, serum titers, cell subpopulation frequencies, and B cell responses were assessed in 63 individuals before and after vaccination and were used to develop a systematic framework to dissect inter- and intra-individual variation and build predictive models of postvaccination antibody responses. Strikingly, independent of age and pre-existing antibody titers, accurate models could be constructed using pre-perturbation cell populations alone, which were validated using independent baseline time points. Most of the parameters contributing to prediction delineated temporally stable baseline differences across individuals, raising the prospect of immune monitoring before intervention.