Immunosenescence-Related Transcriptomic and Immunologic Changes in Older Individuals Following Influenza Vaccination

Abstract

The goal of annual influenza vaccination is to reduce mortality and morbidity associated with this disease through the generation of protective immune responses. The objective of the current study was to examine markers of immunosenescence and identify immunosenescence-related differences in gene expression, gene regulation, cytokine secretion, and immunologic changes in an older study population receiving seasonal influenza A/H1N1 vaccination. Surprisingly, prior studies in this cohort revealed weak correlations between immunosenescence markers and humoral immune response to vaccination. In this report, we further examined the relationship of each immunosenescence marker (age, T cell receptor excision circle frequency, telomerase expression, percentage of CD28− CD4+ T cells, percentage of CD28− CD8+ T cells, and the CD4/CD8 T cell ratio) with additional markers of immune response (serum cytokine and chemokine expression) and measures of gene expression and/or regulation. Many of the immunosenescence markers indeed correlated with distinct sets of individual DNA methylation sites, miRNA expression levels, mRNA expression levels, serum cytokines, and leukocyte subsets. However, when the individual immunosenescence markers were grouped by pathways or functional terms, several shared biological functions were identified: antigen processing and presentation pathways, MAPK, mTOR, TCR, BCR, and calcium signaling pathways, as well as key cellular metabolic, proliferation and survival activities. Furthermore, the percent of CD4+ and/or CD8+ T cells lacking CD28 expression also correlated with miRNAs regulating clusters of genes known to be involved in viral infection. Integrated (DNA methylation, mRNA, miRNA, and protein levels) network biology analysis of immunosenescence-related pathways and genesets identified both known pathways (e.g., chemokine signaling, CTL, and NK cell activity), as well as a gene expression module not previously annotated with a known function. These results may improve our ability to predict immune responses to influenza and aid in new vaccine development, and highlight the need for additional studies to better define and characterize immunosenescence.

A pilot study on primary cultures of human respiratory tract epithelial cells to predict patients’ responses to H7N9 infection

“…These observations may be attributable to "immunosenescence," i.e. an age-related decline in immune function accompanied by the dysfunction of chemokine signaling pathways [45]. In contrast, younger subjects are more likely to survive after H7N9 infection [2,[10][11][12][13][14].…”

Higher mortality in men from COVID19 infection-understanding the factors that drive the differences between the biological sexes

“…In addition we must collect disaggregated gender-relevant data that defines the various dimensions of this global epidemic. Moreover, aging studies in both sexes indicate diminished innate immune responses, and further analysis utilizing co-morbidities may provide the predilection for clinical worsening seen with this infection 13,32 . Taken together, registry data capturing socio-economic and co-morbidity characteristics and clinical protocols targeting the various components of the innate immune system should be explored to address the sex-specific differences in COVID infection.…”

“…Although several studies have shown an estimated R0 of 2.2 for COVID19, there is a broad range of values for the CFR given the inability to estimate during the early phase of this outbreak realiably. The risk for mortality shows an increase in the elderly population 13 and in those with certain pre-existing conditions related to decreased or marginal cardiac, pulmonary, renal functions, and immunosuppressive states. Another area that is gaining attention is the biological sex differences in the incidence of infection and CFR*.…”

Integration of Immune Cell Populations, mRNA-Seq, and CpG Methylation to Better Predict Humoral Immunity to Influenza Vaccination: Dependence of mRNA-Seq/CpG Methylation on Immune Cell Populations

“…Age and biologic sex were included as candidate features in all models that leveraged flow cytometry data; however, the ML model did not select age or sex in cross-validated models, likely due to their known correlations with genetic features (4, 53–55). Flow levels were critical in all expression-based models, either through their direct inclusion or through the interpretation of gene expression features.…”