Multi-phasic gene profiling using candidate gene approach predict the capacity of specific antibody production and maintenance following COVID-19 vaccination in Japanese population

利用候选基因方法进行多阶段基因谱分析,预测日本人群接种新冠疫苗后特异性抗体的产生和维持能力

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Abstract

BACKGROUND: Vaccination against severe acute respiratory syndrome coronavirus type 2 is highly effective in preventing infection and reducing the severity of coronavirus disease (COVID-19). However, acquired humoral immunity wanes within six months. Focusing on the different tempo of acquisition and attenuation of specific antibody titers in individuals, we investigated the impact of genetic polymorphisms on antibody production after COVID-19 vaccination. METHODS: In total 236 healthcare workers from a Japanese municipal hospital, who received two doses of the vaccine were recruited. We employed a candidate gene approach to identify the target genetic polymorphisms affecting antibody production after vaccination. DNA samples from the study populations were genotyped for 33 polymorphisms in 15 distinct candidate genes encoding proteins involved in antigen-presenting cell activation, T cell activation, T-B interaction, and B cell survival. We measured total anti-SARS-Cov2 spike IgG antibody titers and analyzed the association with genetic polymorphisms at several time points after vaccination using an unbiased statistical method, and stepwise logistic regression following multivariate regression. RESULTS: Significant associations were observed between seven SNPs in NLRP3, OAS1, IL12B, CTLA4, and IL4, and antibody titers at 3 weeks after the first vaccination as an initial response. Six SNPs in NLRP3, TNF, OAS1, IL12B, and CTLA4 were associated with high responders with serum antibody titer > 4000 BAU/ml as boosting effect at 3 weeks after the second vaccination. Analysis of long-term maintenance showed the significance of the three SNPs in IL12B, IL7R, and MIF for the maintenance of antibody titers and that in BAFF for attenuation of neutralizing antibodies. Finally, we proposed a predictive model composed of gene profiles to identify the individuals with rapid antibody attenuation by receiver operating characteristic (ROC) analysis (area under the curve (AUC)= 0.76, sensitivity = 82.5%, specificity=67.8%). CONCLUSIONS: The candidate gene approach successfully showed shifting responsible gene profiles and initial and boosting effect mainly related to the priming phase into antibody maintenance including B cell survival, which traces the phase of immune reactions. These gene profiles provide valuable information for further investigation of humoral immunity against COVID-19 and for building a strategy for personalized vaccine schedules.

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