He, Y.; Xing, J.; Wang, S.; Jiang, H.; Lun, Y.; Han, Y.; Erhart, P.; Boeckler, D.; Zhang, J.

Objective: Despite surgical advance, effective targeted drugs for non-surgical treatment of abdominal aortic aneurysm (AAA) are lacking because of the unclear pathogenesis of AAA. N6-methyladenosine (m6A) methylation, acknowledged for its pivotal influence on RNA metabolism, including aspects such as stability, transport, translation, and splicing, is largely implied for its role in AAA mechanism. This study aims to elucidate the involvement of m6A methylation in the progression of AAA through an integrative multi-omics and machine learning approach. Methods and Results: We utilized methylated RNA immunoprecipitation sequencing (MeRIP-seq) to map the m6A methylation landscape in AAA tissues and combined this with RNA sequencing (RNA-seq) from the GEO database, to explore the interplay between m6A methylation and gene expression. A machine learning-based AAA m6A-related mRNA signature (AMRMS) was developed to predict the risk of AAA dilation. The AMRMS showed robust predictive power in distinguishing between patients with large and small AAAs. Notably, FKBP11 was identified as a key gene significantly influencing the predictive model, and up-regulated in large AAA compared to its in small AAA. Further single-cell RNA sequencing (scRNA-seq) and histological analysis highlighted the critical role of FKBP11 in mediating the endoplasmic reticulum stress of plasma cells within the AAA walls and its correlation with m6A methylation. Conclusions: The m6A modification regulatory network plays a vital role in the progression of AAA, and the AMRMS offers promising potential in assessing the risk of AAA dilation. Our findings suggest that elevated FKBP11, by activating endoplasmic reticulum stress in plasma cells, may significantly contribute to AAA expansion.