4.6 Article

Proteomic Signatures of the Serological Response to Influenza Vaccination in a Large Human Cohort Study

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VIRUSES-BASEL
卷 14, 期 11, 页码 -

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MDPI
DOI: 10.3390/v14112479

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influenza vaccination; serological response; serum proteomics; cohort analyses; seroconversion

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  1. National Institutes of Health (USA)

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This study analyzed serum samples from 138 influenza vaccine recipients, finding a positive correlation between cholesterol transport proteins and seroconversion, a significant association between actin cytoskeleton dynamics proteins and high adjusted seroconversion, and complex interactions of complement system proteins in different age groups.
The serological response to the influenza virus vaccine is highly heterogeneous for reasons that are not entirely clear. While the impact of demographic factors such as age, body mass index (BMI), sex, prior vaccination and titer levels are known to impact seroconversion, they only explain a fraction of the response. To identify signatures of the vaccine response, we analyzed 273 protein levels from 138 serum samples of influenza vaccine recipients (2019-2020 season). We found that levels of proteins functioning in cholesterol transport were positively associated with seroconversion, likely linking to the known impact of BMI. When adjusting seroconversion for the demographic factors, we identified additional, unexpected signatures: proteins regulating actin cytoskeleton dynamics were significantly elevated in participants with high adjusted seroconversion. Viral strain specific analysis showed that this trend was largely driven by the H3N2 strain. Further, we identified complex associations between adjusted seroconversion and other factors: levels of proteins of the complement system associated positively with adjusted seroconversion in younger participants, while they were associated negatively in the older population. We observed the opposite trends for proteins of high density lipoprotein remodeling, transcription, and hemostasis. In sum, careful integrative modeling can extract new signatures of seroconversion from highly variable data that suggest links between the humoral response as well as immune cell communication and migration.

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