美国斯坦福大学Bali Pulendran团队对人类对多种疫苗抗体反应持久性的，预测因子和机制进行了系统疫苗学分析。相关论文于2025年1月2日发表于国际顶尖学术期刊《自然—免疫学》杂志上。

研究小组进行了系统疫苗学分析，以调查人类对H5N1流感疫苗（包含和不含AS03佐剂）的免疫反应，以确定影响抗体反应强度和持久性的因素。他们的发现揭示了第7天血小板和粘附相关的血液转录特征，预测了抗体反应的持续时间，这表明血小板在调节抗体反应的持久性方面具有潜在的作用。

由于血小板起源于巨核细胞，研究团队探索了血小板生成素（TPO）介导的巨核细胞活化对抗体反应寿命的影响。小组发现TPO可以增强疫苗诱导的抗体反应的持久性。TPO激活的巨核细胞还通过整合素β1/β2介导的细胞间相互作用，以及存活因子APRIL和MIF-CD74轴，促进人骨髓浆细胞的存活。

利用机器学习，研究团队开发了一个基于血小板相关特征的分类器，该分类器预测了来自七项独立试验的六种疫苗的抗体反应寿命，强调了疫苗耐久性的保守机制。

附：英文原文

Title: System vaccinology analysis of predictors and mechanisms of antibody response durability to multiple vaccines in humans

Author: Cortese, Mario, Hagan, Thomas, Rouphael, Nadine, Wu, Sheng-Yang, Xie, Xia, Kazmin, Dmitri, Wimmers, Florian, Gupta, Shakti, van der Most, Robbert, Coccia, Margherita, Aranuchalam, Prabhu S., Nakaya, Helder I., Wang, Yating, Coyle, Elizabeth, Horiuchi, Shu, Wu, Hanchih, Bower, Mary, Mehta, Aneesh, Gunthel, Clifford, Bosinger, Steve E., Kotliarov, Yuri, Cheung, Foo, Schwartzberg, Pamela L., Germain, Ronald N., Tsang, John, Li, Shuzhao, Albrecht, Randy, Ueno, Hideki, Subramaniam, Shankar, Mulligan, Mark J., Khurana, Surender, Golding, Hana, Pulendran, Bali

Issue&Volume: 2025-01-02

Abstract: We performed a systems vaccinology analysis to investigate immune responses in humans to an H5N1 influenza vaccine, with and without the AS03 adjuvant, to identify factors influencing antibody response magnitude and durability. Our findings revealed a platelet and adhesion-related blood transcriptional signature on day 7 that predicted the longevity of the antibody response, suggesting a potential role for platelets in modulating antibody response durability. As platelets originate from megakaryocytes, we explored the effect of thrombopoietin (TPO)-mediated megakaryocyte activation on antibody response longevity. We found that TPO administration enhanced the durability of vaccine-induced antibody responses. TPO-activated megakaryocytes also promoted survival of human bone-marrow plasma cells through integrin β1/β2-mediated cell–cell interactions, along with survival factors APRIL and the MIF–CD74 axis. Using machine learning, we developed a classifier based on this platelet-associated signature, which predicted antibody response longevity across six vaccines from seven independent trials, highlighting a conserved mechanism for vaccine durability.

DOI: 10.1038/s41590-024-02036-z

Source: https://www.nature.com/articles/s41590-024-02036-z