Hongfen Wang, Bo Sun, Shiya Wang, Jing Pan, Rongrong Du, Xinyuan Pang, Jiongming Bai, Jinming Han, Jinli Feng
The findings support further evaluation of m6A-related signatures for ALS discrimination and molecular characterization, while larger independent cohorts and additional calibration are required before clinical application.
Background Amyotrophic lateral sclerosis (ALS) lacks reliable and minimally invasive biomarkers for early diagnosis. m6A-associated single-nucleotide polymorphisms (m6A-SNPs) may influence RNA methylation and gene expression, offering opportunities to identify clinically relevant diagnostic markers. Methods We integrated eQTLGen cis-eQTL data, RMVar m6A-SNP annotations, and ALS transcriptomic datasets to identify m6A-SNP–related genes. Random Forest and LASSO regression were combined to screen robust diagnostic markers. A nomogram was constructed and validated using independent cohorts. Immune infiltration, predicted m6A modification sites, and potential RBP–SNP interactions were assessed. Peripheral blood samples from ALS patients were used for exploratory validation of gene expression and global m6A levels. Results We identified 109 ALS-associated m6A-SNP-related genes with cis-eQTL signals and narrowed these to seven candidate diagnostic markers (TMED5, OXR1, BRI3, FEM1C, SUZ12, EIF2AK4, and TJAP1). The seven-gene model outperformed the individual markers in the training cohort and retained moderate discrimination in the independent validation cohort. ALS samples showed differences in inferred immune-cell composition, including monocytes, neutrophils, and T-cell subsets. The selected SNP loci were located near predicted m6A sites and annotated RBP-binding regions. Exploratory clinical validation showed significant upregulation of FEM1C and SUZ12 at both mRNA and protein levels, accompanied by reduced global m6A modification. Conclusions Through multi-omics integration and exploratory clinical validation, this study identifies m6A-SNP-related candidate markers associated with ALS. The findings support further evaluation of m6A-related signatures for ALS discrimination and molecular characterization, while larger independent cohorts and additional calibration are required before clinical application.