Platelets as immune sensors: monitoring immune dynamics and diagnosing disease states across multiple disorders.

Abstract

Beyond their classical roles in haemostasis and thrombosis, platelets have been recognised as active regulators of immune responses. However, whether platelets can function as immune sensors capable of monitoring immune status remains largely unexplored. We first analysed platelet transcriptomes from patients at different stages following haematopoietic stem cell transplantation (HSCT) to assess their ability to capture immune reconstitution dynamics. We then employed immune cell-platelet co-incubation experiments to elucidate the mechanistic role of RNA transfer in reshaping platelet immune molecular profiles. Subsequently, platelet transcriptomes were examined in immune-related conditions, including HSCT-associated acute graft-versus-host disease (aGVHD), cytomegalovirus (CMV) DNAemia, and immune-inflammatory diseases such as systemic lupus erythematosus (SLE) and ulcerative colitis (UC), to evaluate their capacity to identify disease-specific immune dysregulation. Finally, machine learning models were developed based on platelet immune gene signatures to assess diagnostic performance. Platelet transcriptomes accurately reflected the dynamics of immune reconstitution following HSCT. Mechanistically, immune cells directly reprogrammed platelet immune-related molecular features through RNA transfer. Moreover, platelets sensitively detected immune alterations associated with transplant complications, including aGVHD and CMV DNAemia, and effectively monitored immune activity and inflammatory states in SLE and UC. Machine learning models based on platelet immune gene profiles further improved diagnostic accuracy across disease settings. This study establishes platelets as precise, readily accessible, and noninvasive immune sensors, extending their functional repertoire from immune regulation to immune surveillance and diagnosis in immune-related diseases. National Natural Science Foundation of China; CAMS Innovation Fund for Medical Sciences; Science and Technology Projects of Xizang Autonomous Region, China; National Key Research and Development Program of China; Tianjin Municipal Science and Technology Commission Grant; and Natural Science Foundation of Tianjin.