Vaccination History, Body Mass Index, Age, and Baseline Gene Expression Predict Influenza Vaccination Outcomes.
Vaccination History, Body Mass Index, Age, and Baseline Gene Expression Predict Influenza Vaccination Outcomes.
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DOI：
10.3390/v14112446
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发表时间：
2022-11-04
期刊：
影响因子：
--
通讯作者：
Gresham D
中科院分区：
文献类型：
--
作者：
Forst CV;Chung M;Hockman M;Lashua L;Adney E;Hickey A;Carlock M;Ross T;Ghedin E;Gresham D
季节性流感是美国和全球的主要公共卫生负担。年度疫苗接种计划是根据流行的流感病毒株设计的。然而，季节性流感疫苗的有效性在不同季节和不同个体之间差异很大。已知有许多因素影响疫苗接种效果，包括年龄、性别和合并症。在这里，我们试图确定疫苗接种前的全血基因表达谱是否能提供有关先前存在的免疫状态和对疫苗的免疫应答的信息。我们对参加年度流感疫苗试验的275名参与者在接种前获得的全血样本进行了RNA测序(RNAseq)，进行了完整的转录组分析。用血凝抑制试验(HAI)评估接种前和接种后28天的血清学状态，以确定基线免疫状态和对接种的反应。我们发现有证据表明，具有免疫功能的基因在先前存在的免疫力较高的个体以及对疫苗接种有较大反应的个体中的表达增加。使用随机森林模型，我们发现这组基因可以用来预测疫苗反应，其性能类似于仅结合生理和先前接种状态的模型。同时使用基因表达和生理因素的模型具有最大的预测能力，表明了分子图谱在增强疫苗应答预测方面的潜在用途。此外，与增强的疫苗接种反应相关的基因的表达可能指向有助于建立对季节性流感疫苗的强大免疫反应的其他生物途径。
Seasonal influenza is a primary public health burden in the USA and globally. Annual vaccination programs are designed on the basis of circulating influenza viral strains. However, the effectiveness of the seasonal influenza vaccine is highly variable between seasons and among individuals. A number of factors are known to influence vaccination effectiveness including age, sex, and comorbidities. Here, we sought to determine whether whole blood gene expression profiling prior to vaccination is informative about pre-existing immunological status and the immunological response to vaccine. We performed whole transcriptome analysis using RNA sequencing (RNAseq) of whole blood samples obtained prior to vaccination from 275 participants enrolled in an annual influenza vaccine trial. Serological status prior to vaccination and 28 days following vaccination was assessed using the hemagglutination inhibition assay (HAI) to define baseline immune status and the response to vaccination. We find evidence that genes with immunological functions are increased in expression in individuals with higher pre-existing immunity and in those individuals who mount a greater response to vaccination. Using a random forest model, we find that this set of genes can be used to predict vaccine response with a performance similar to a model that incorporates physiological and prior vaccination status alone. A model using both gene expression and physiological factors has the greatest predictive power demonstrating the potential utility of molecular profiling for enhancing prediction of vaccine response. Moreover, expression of genes that are associated with enhanced vaccination response may point to additional biological pathways that contribute to mounting a robust immunological response to the seasonal influenza vaccine.
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DOI：
10.1109/tvcg.2014.2346248
发表时间：
2014-12
影响因子：
5.2
作者：
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DOI：
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发表时间：
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影响因子：
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作者：
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