Wenhao An ¹ Jiajun Zhou ¹ Zhiqiang Qiu ¹ Peishen Wang ² Xinye Han ² Yanwen Cheng ² Zi He ² Yihua An ^1* Shouwei Li ^1*

• ¹ Sanbo Brain Hospital, Capital Medical University, Beijing, China
• ² Department of Research and Development, Beijing Yihua Biotechnology Co., Ltd, Beijing, China

The continuous extension of human life expectancy poses challenges in the form of age-related diseases, notably Alzheimer's disease and atherosclerosis. While their etiology remains incompletely understood, mounting evidence suggests a close association between these two diseases. Genetic factors, immune system dysregulation, chronic inflammatory responses, as well as vascular aging and endothelial dysfunction have prompted a reevaluation of this association. This study aims to unveil potential connections between these diseases through gene expression analysis. We focused on shared differentially expressed genes to explore the biological functionalities relevant to both conditions. Leveraging machine learning algorithms, we identified optimal diagnostic and hub genes. Immunocyte infiltration analysis and confirmation of correlation networks deepened our understanding of these diseases. Consensus clustering for disease subtyping further highlighted the close relationship between AD and AS. Overall, we hope this research provides new insights for future investigations into these two diseases.