Investigating potential biomarkers associated with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis using Mendelian randomization and transcriptomic analysis.

ABSTRACT: Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is an autoimmune disorder characterized by multi-organ involvement. Early identification and accurate diagnosis of AAV is crucial for improving prognosis. However, research on biomarkers associated with AAV is limited. This study aimed to explore novel biomarkers for AAV through transcriptomic data analysis and Mendelian randomization (MR). AAV-related datasets (GSE104948 and GSE108109) were analyzed. Differentially expressed genes (DEGs) between AAV and normal groups were identified in the GSE104948 dataset. MR analysis was then used to investigate the causal relationship between DEGs and AAV. Genes with a significant causal relationship were selected as candidate genes for further analysis. Machine learning algorithms

SUBMITTER: Wang Y 

PROVIDER: S-EPMC12366041 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature