Nanopore long-read sequencing facilitates accurate diagnosis of KMT2B-related dystonia

Abstract

Diagnosis of KMT2B-related dystonia remains challenging due to the high prevalence of variants of uncertain significance and technological constraint of short-read pipelines. To overcome these limitations, we integrated nanopore-based long-read sequencing with a validated KMT2B-episignature classifier to perform simultaneous genetic and epigenetic profiling for three cases with prior uncertain KMT2B-related findings. Our workflow detected characteristic deviations in the KMT2B-episignature score in two cases with previously unresolved or missed KMT2B variants, while refuting an ambiguous indel call. Combining genomic-variant detection with DNA-methylation analysis eliminated the need for sequential testing and enhanced accurate diagnosis of KMT2B-related dystonia, offering a basis for streamlined epigenetics-guided diagnostics.