Ward Daniel, Pattarapreeyakul Lapasrada, Pitaksalee Rujiraporn, Thawong Naphatcha, Sawaengdee Waritta, Tuntigumthon Suthida, Patterson Catriona, Tetteh Kevin, Campino Susana, Dhepakson Panadda, Mahasirimongkol Surakameth, Clark Taane G
Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine (LSHTM), Keppel Street, London, WC1E 7HT, UK.
Department of Medical Sciences, Medical Life Sciences Institute, Ministry of Public Health, 88/7 Tiwanon Road, Nonthaburi, 11000, Thailand.
Sci Rep. 2025 Jan 9;15(1):1519. doi: 10.1038/s41598-024-84392-2.
During the COVID-19 pandemic, heterologous vaccination strategies were employed to alleviate the strain on vaccine supplies. The Thailand Ministry of Health adopted these strategies using vector, inactivated, and mRNA vaccines. However, this approach has introduced challenges for SARS-CoV-2 sero-epidemiology studies. Our study analysed 647 samples from healthcare workers who received CoronaVac, ChAdOx1 nCoV-19, and BNT162b2 vaccines. The serological profile encompassed responses to various SARS-CoV-2 variants and vectors, measuring IgG, IgM, and IgA isotypes, alongside IgG avidity assays. The results demonstrated that heterologous CoronaVac/ChAdOx1 nCoV-19 schedules elicited significantly stronger antibody responses compared to homologous schedules (IgG: 1.2-fold, IgM: 10.9-fold, IgA: 3.1-fold increase). Additionally, a heterologous BNT162b2 boost at 4-weeks post-initial vaccination showed greater antibody levels than a ChAdOx1 nCoV-19 boost (IgG: 1.1-fold, IgM: slight decrease, IgA: 1.5-fold increase). Using a combination of three analytes, IgG against wild-type Spike trimer, nucleoprotein and Omicron receptor binding domains, enabled the clustering of responses within a statistical Gaussian mixture model that successfully discriminates between breakthrough infections and vaccination types (F-score = 0.82). The development of statistical models to predict breakthrough infections can improve serological surveillance. Overall, our study underscores the necessity for vaccine (re-)development and the creation of serological tools to monitor vaccine performance.
在新冠疫情期间，采用了异源疫苗接种策略以缓解疫苗供应压力。泰国卫生部采用了这些策略，使用了载体疫苗、灭活疫苗和信使核糖核酸疫苗。然而，这种方法给新冠病毒血清流行病学研究带来了挑战。我们的研究分析了647名接种了科兴新冠疫苗、牛津大学/阿斯利康新冠疫苗（ChAdOx1 nCoV-19）和辉瑞/BioNTech新冠疫苗（BNT162b2）的医护人员的样本。血清学分析包括对各种新冠病毒变体和载体的反应，检测免疫球蛋白G（IgG）、免疫球蛋白M（IgM）和免疫球蛋白A（IgA）亚型，同时进行IgG亲和力检测。结果表明，与同源接种方案相比，异源的科兴新冠疫苗/牛津大学/阿斯利康新冠疫苗接种方案引发的抗体反应明显更强（IgG：增加1.2倍，IgM：增加10.9倍，IgA：增加3.1倍）。此外，在初次接种后4周进行异源的辉瑞/BioNTech新冠疫苗加强接种，其抗体水平高于牛津大学/阿斯利康新冠疫苗加强接种（IgG：增加1.1倍，IgM：略有下降，IgA：增加1.5倍）。使用针对野生型刺突三聚体、核蛋白和奥密克戎受体结合域的三种分析物IgG的组合，能够在统计高斯混合模型中对反应进行聚类，该模型成功区分了突破性感染和疫苗接种类型（F分数=0.82）。开发预测突破性感染的统计模型可以改善血清学监测。总体而言，我们的研究强调了疫苗（重新）开发以及创建监测疫苗性能的血清学工具的必要性。
