Developing vaccines for an aging population

Black, Steven; Gregorio, Ennio De; Rappuoli, Rino

doi:10.1126/scitranslmed.aaa0722

Cited by 21 publications

(20 citation statements)

References 31 publications

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“…There is general consensus that we need to improve in producing better vaccines and developing better vaccination strategies . So far, strategies to overcome these defects associated with immune ageing have been empirical, with some, albeit limited, success.…”

Section: Approaches To Improve Vaccination Outcome In An Older Populamentioning

confidence: 99%

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The life cycle of a T cell after vaccination – where does immune ageing strike?

Kim

Fang

Weyand

et al. 2016

Clinical and Experimental Immunology

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SummaryVaccination is the optimal intervention to prevent the increased morbidity and mortality from infection in older individuals and to maintain immune health during ageing. To optimize benefits from vaccination, strategies have to be developed that overcome the defects in an adaptive immune response that occur with immune ageing. Most current approaches are concentrated on activating the innate immune system by adjuvants to improve the induction of a T cell response. This review will focus upon T cell-intrinsic mechanisms that control how a T cell is activated, expands rapidly to differentiate into short-lived effector cells and into memory precursor cells, with short-lived effector T cells then mainly undergoing apoptosis and memory precursor cells surviving as long-lived memory T cells. Insights into each step of this longitudinal course of a T cell response that takes place over a period of several weeks is beginning to allow identifying interventions that can improve this process of T cell memory generation and specifically target defects that occur with ageing.

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Section: Approaches To Improve Vaccination Outcome In An Older Populamentioning

confidence: 99%

“…Approaches to improve vaccination outcome in an older population -empirical, based on system analysis or based on mechanistic models? strategies [11]. So far, strategies to overcome these defects associated with immune ageing have been empirical, with some, albeit limited, success.…”

Section: Introductionmentioning

confidence: 99%

The life cycle of a T cell after vaccination – where does immune ageing strike?

Kim

Fang

Weyand

et al. 2016

Clinical and Experimental Immunology

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“…Aging is associated with progressive deterioration of immune function that leads to increased susceptibility to opportunistic infections, decreased responsiveness to vaccines, and increased incidence of autoimmunity and cancer [105, 106]. How to prevent/reverse immunosenescence in aged individuals to ensure a healthy, quality life and to cut down societal health care-related cost remains a major challenge to medical research [107, 108]. …”

Section: The Prospect Of Thymus Bioengineering In Therapeuticsmentioning

confidence: 99%

Restoration of Thymus Function with Bioengineered Thymus Organoids

et al. 2016

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The thymus is the primary site for the generation of a diverse repertoire of T-cells that are essential to the efficient function of adaptive immunity. Numerous factors varying from aging, chemotherapy, radiation exposure, virus infection and inflammation contribute to thymus involution, a phenomenon manifested as loss of thymus cellularity, increased stromal fibrosis and diminished naïve T-cell output. Rejuvenating thymus function is a challenging task since it has limited regenerative capability and we still do not know how to successfully propagate thymic epithelial cells (TECs), the predominant population of the thymic stromal cells making up the thymic microenvironment. Here, we will discuss recent advances in thymus regeneration and the prospects of applying bioengineered artificial thymus organoids in regenerative medicine and solid organ transplantation.

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“…Aging causes an increased risk for diseases. Age-related diseases are becoming a public health concern due to an overall increase in the older population and the average human life span in developed countries (Rowe et al, 2016; Black et al, 2015). It is predicted that by the year 2050, the number of Americans over 85 years of age will triple from 2015 (Jaul and Barron, 2017; United Nations Department of Economic and Social Affairs, 2015).…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Analysis of Age, Sex, and Tissue Effects on Gene Expression Variability in Alzheimer’s Disease

Brooks

Mias

2018

Preprint

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2Alzheimer's disease (AD) has been categorized by the Centers for Disease Control and 3 Prevention (CDC) as the 6 th leading cause of death in the United States. AD is a significant 4 health-care burden because of its increased occurrence (specifically in the elderly population) 5 and the lack of effective treatments and preventive methods. With an increase in life expectancy, 6 the CDC expects AD cases to rise to 15 million by 2060. Aging has been previously associated 7 with susceptibility to AD, and there are ongoing efforts to effectively differentiate between normal 8 and AD age-related brain degeneration and memory loss. AD targets neuronal function and can 9 cause neuronal loss due to the buildup of amyloid-beta plaques and intracellular neurofibrillary 10 tangles. 11Our study aims to identify temporal changes within gene expression profiles of healthy controls 12 and AD subjects. We conducted a meta-analysis using publicly available microarray expression 13 data from AD and healthy cohorts. For our meta-analysis, we selected datasets that reported 14 donor age and gender, and used Affymetrix and Illumina microarray platforms (8 datasets, 2,088 15 samples). Raw microarray expression data were re-analyzed, and normalized across arrays. We 16 then performed an analysis of variance, using a linear model that incorporated age, tissue type, 17 sex, and disease state as effects, as well as study to account for batch effects, and including 18 binary interaction between factors. Our results identified 3,735 statistically significant (Bonferroni 19 adjusted p<0.05) gene expression differences between AD and healthy controls, which we 20 filtered for biological effect (10% two-tailed quantiles of mean differences between groups) to 21 obtain 352 genes. Interesting pathways identified as enriched comprised of neurodegenerative 22 diseases pathways (including AD), and also mitochondrial translation and dysfunction, synaptic 23 vesicle cycle and GABAergic synapse, and gene ontology terms enrichment in neuronal system, 24 transmission across chemical synapses and mitochondrial translation. 25 Overall our approach allowed us to effectively combine multiple available microarray datasets 26 and identify gene expression differences between AD and healthy individuals including full age 27 and tissue type considerations. Our findings provide potential gene and pathway associations 28 that can be targeted to improve AD diagnostics and potentially treatment or prevention. (US). 29

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Developing vaccines for an aging population

Cited by 21 publications

References 31 publications

The life cycle of a T cell after vaccination – where does immune ageing strike?

The life cycle of a T cell after vaccination – where does immune ageing strike?

Restoration of Thymus Function with Bioengineered Thymus Organoids

Data-Driven Analysis of Age, Sex, and Tissue Effects on Gene Expression Variability in Alzheimer’s Disease

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