Uncovering latent factors underlying weak and robust responses to influenza vaccine in healthy and obese older adults
Uncovering latent factors underlying weak and robust responses to influenza vaccine in healthy and obese older adults
批准号:
10665055
负责人:
John F Alcorn
金额:
$77.6万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-07-13 至 2027-06-30
关键词:
AddressAdultAffectAgeAntibodiesAntibody ResponseB-LymphocytesBlood specimenBody mass indexCell CompartmentationCellsCellular ImmunityChromatinComputer AnalysisCoupledData SetDevelopmentDimensionsDisciplineEffectivenessElderlyEpigenetic ProcessFlow CytometryGenerationsGeneticGenetic TranscriptionGenomicsImmuneImmune responseImmunityImmunologyImpairmentIndividualInfectionInflammation MediatorsInfluenzaInfluenza preventionInfluenza vaccinationKnowledgeMachine LearningMeasuresMemoryMemory B-LymphocyteMolecularMolecular ProfilingObesityOutcomeParticipantPathway interactionsPatternPeripheral Blood Mononuclear CellPhenotypePlasma CellsPlasmablastProteinsRaceStructure of germinal center of lymph nodeSystemSystems BiologyTestingVaccinationVaccine DesignVaccinesVariantVitamin DVulnerable Populationsagedcohortcytokineexceptional respondersexperimental analysisfrailtygene regulatory networkhealthy weighthigh dimensionalityimmunogenicityinfluenza virus vaccineinsightmachine learning frameworkmachine learning methodmachine learning predictionmiddle agemolecular markermultiple omicsnovelobese personprogramsresponsescreeningseasonal influenzasextranscriptomicsvaccine formulationvaccine immunogenicityvaccine responsevaccinology
中文摘要
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英文摘要
Summary/Abstract
Although vaccination is the most effective measure for influenza prevention, there is considerable
variation in the responses to influenza vaccines that is influenced by factors such as age, sex,
and obesity level. Major advances in predicting and analyzing the cellular and molecular basis of
vaccine responses are being made possible by the application of high-dimensional experimental
and computational approaches that comprise Systems Vaccinology. This framework is yielding
predictive molecular signatures for influenza vaccine immunogenicity and protection. However,
there remains a considerable knowledge gap in delineation of cellular and molecular pathways
that affect the responses to advanced-generation influenza vaccines in older or obese individuals.
To gain new insights into the cellular and molecular states that underlie variation of influenza
vaccine responses in older, healthy weight or obese individuals we propose to perform deep
molecular and genomic profiling of immune cell states after screening for extreme responders.
Our approach, focused on extremes of individual vaccine responses, draws upon successful prior
use of such a framework in analyzing genetic basis of extreme phenotypic variability. We propose
in Aim 1 to elucidate latent factors and B cell genomic states underlying weak or robust
immunogenicity of the advanced-generation seasonal influenza vaccine within healthy weight
older individuals using deep molecular profiling and interpretable machine learning as well as
computational genomics. Aim 2 will delineate latent factors and infer molecular mechanisms by
which obesity distinctively affects influenza vaccine immunogenicity based on high-dimensional
and multi-scale profiling of the immune responses as in Aim 1. Uncovering new molecular markers
and pathways will spur tailored vaccine design that addresses specific impairments in vulnerable
individuals. Our team brings together strong expertise in three complementary and essential
disciplines that comprise vaccinology, immunology and systems biology.
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