Repurposing Azilsartan medoxomil attenuates periodontitis by targeting SERPINB9 to promote apoptosis of IL1B+ macrophages

Periodontitis (PD) is a common chronic inflammatory disease characterized by progressive destruction of periodontal tissues and is associated with systemic disorders such as diabetes and Cardiovascular Disease. Despite its high global burden, current diagnostic and therapeutic strategies remain limited, highlighting the urgent need for reliable biomarkers and novel therapeutic targets. Macrophages are central to the pathogenesis of PD. Recent single-cell transcriptomic studies have identified IL1B⁺ macrophages as a pro-inflammatory subset closely linked to tissue destruction. However, the molecular mechanisms governing their survival remain poorly understood. In this study, we integrated multiple single-cell RNA Sequencing datasets from the GEO database and applied five machine-learning algorithms to systematically identify critical regulators among differentially expressed genes in macrophages. SERPINB9 (PI9 in humans, Spi6 in mice) emerged as a key candidate, showing elevated expression in IL1B⁺ macrophages. Functional validation in vitro and in vivo confirmed that SERPINB9 promotes macrophage survival and sustains inflammatory responses. Furthermore, an in silico drug-repurposing screen based on FDA-approved compounds identified Azilsartan medoxomil as a potential inhibitor of SERPINB9. Pharmacological inhibition of SERPINB9 attenuated inflammatory macrophage responses and alleviated alveolar bone loss in experimental periodontitis, supporting its therapeutic potential. Collectively, these findings reveal a novel programmed cell death-related regulatory mechanism in macrophages, identifying SERPINB9 as a promising biomarker, and suggest that targeting SERPINB9 may offer a clinically translatable therapeutic strategy for periodontitis.

Drug repurposing; IL1B(+) macrophages; Machine learning; Periodontitis; SERPINB9.