Neurology. Genetics · 2026
Plasma isomiRs as Candidate Biomarkers for Amyotrophic Lateral Sclerosis.
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Magee Rogan G, Van Deerlin Vivianna M, McMillan Corey T, Lee Edward B, Elman Lauren B, Irwin David John, Mourelatos Zissimos
Аннотация
BACKGROUND AND OBJECTIVES: There are no FDA-approved diagnostic biomarkers for amyotrophic lateral sclerosis (ALS). TDP-43 is a known cofactor in the cleavage of long premature microRNAs (miRNAs) into their short, mature products. isomiRs are miRNA variants that differ in their 5' and 3' end points and regulate distinct mRNA targets. In this study, we tested the hypotheses that circulating isomiR profiles differ in the context of TAR DNA-binding Protein pathology and that isomiRs are superior to miRNAs for classification of ALS.
METHODS: We obtained RNA from plasma samples of 14 patients with ALS and 14 age-matched and sex-matched controls for sequencing on a NextSeq 2000. Data were processed using Unique Molecular Identifier tools and a custom pipeline designed to match miRNA variant sequences without mismatches. Differential expression (DE) was identified using DEseq2 at FDR ≤ 0.1. XGBoost classifiers were built using a subset of (Model 1) isomiRs or (Model 2) miRNAs that were present above a median threshold in all sequencing batches. Parameters were tuned using grid search and 10-fold cross-validation while training to distinguish ALS samples from controls among a single large public data set. Models were then validated on in-house samples and 1 publicly available holdout data set.
RESULTS: Fourteen (0.2%), 355 (2.7%), and 14 (0.7%) isomiRs were differentially expressed in in-house plasma, public ALS plasma, and public ALS serum, respectively. One (0.1%), 94 (5.5%), and 13 (2.4%) miRNAs were differentially expressed, respectively. Model 1 accurately classified in-house ALS plasma and public ALS serum (area under the curve [AUC] = 0.87) and did not distinguish 40 of 41 Alzheimer disease samples from control plasma (GSE215789; AUC = 0.47) or 60 of 77 Parkinson disease samples from control whole blood (GSE180193; AUC = 0.55). In comparison, Model 2 using miRNAs performed worse on in-house plasma (AUC = 0.49).
DISCUSSION: Analyzing individual isomiRs may improve the performance of circulating noncoding RNAs as diagnostic biomarkers of ALS.
METHODS: We obtained RNA from plasma samples of 14 patients with ALS and 14 age-matched and sex-matched controls for sequencing on a NextSeq 2000. Data were processed using Unique Molecular Identifier tools and a custom pipeline designed to match miRNA variant sequences without mismatches. Differential expression (DE) was identified using DEseq2 at FDR ≤ 0.1. XGBoost classifiers were built using a subset of (Model 1) isomiRs or (Model 2) miRNAs that were present above a median threshold in all sequencing batches. Parameters were tuned using grid search and 10-fold cross-validation while training to distinguish ALS samples from controls among a single large public data set. Models were then validated on in-house samples and 1 publicly available holdout data set.
RESULTS: Fourteen (0.2%), 355 (2.7%), and 14 (0.7%) isomiRs were differentially expressed in in-house plasma, public ALS plasma, and public ALS serum, respectively. One (0.1%), 94 (5.5%), and 13 (2.4%) miRNAs were differentially expressed, respectively. Model 1 accurately classified in-house ALS plasma and public ALS serum (area under the curve [AUC] = 0.87) and did not distinguish 40 of 41 Alzheimer disease samples from control plasma (GSE215789; AUC = 0.47) or 60 of 77 Parkinson disease samples from control whole blood (GSE180193; AUC = 0.55). In comparison, Model 2 using miRNAs performed worse on in-house plasma (AUC = 0.49).
DISCUSSION: Analyzing individual isomiRs may improve the performance of circulating noncoding RNAs as diagnostic biomarkers of ALS.