miRNA profiling as a complementary diagnostic tool for amyotrophic lateral sclerosis

Abstract

Amyotrophic lateral sclerosis (ALS), the most prevalent motor neuron disease characterized by its complex genetic structure, lacks a single diagnostic test capable of providing a conclusive diagnosis. In order to demonstrate the potential for genetic diagnosis and shed light on the pathogenic role of miRNAs in ALS, we developed an ALS diagnostic rule by training the model using 80% of a miRNA profiling dataset consisting of 253 ALS samples and 103 control samples. Subsequently, we validated the diagnostic rule using the remaining 20% of unseen samples. The diagnostic rule we developed includes miR-205-5p, miR-206, miR-376a-5p, miR-412-5p, miR-3927-3p, miR-4701-3p, miR-6763-5p, and miR-6801-3p. Remarkably, the rule achieved an 82% true positive rate and a 73% true negative rate when predicting the unseen samples. Furthermore, the identified miRNAs target 21 genes in the PI3K-Akt pathway and 27 genes in the ALS pathway, including notable genes such as BCL2, NEFH, and OPTN. We propose that miRNA profiling may serve as a complementary diagnostic tool to supplement the clinical presentation and aid in the early recognition of ALS.