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Introduction
Genetic leukodystrophies (gLD), encompassing inherited disorders affecting cerebral white matter, are a heterogeneous group of diseases.1 While they classically first manifest in childhood, adolescent and adult-onset forms are increasingly recognised.2 3 Different pathological mechanisms produce white matter abnormalities (WMAs) depending on the affected gene.1 Hypomyelinating gLD (H-gLD) share the common histological feature of decreased myelin formation in the brain, in contrast to demyelinating gLD (loss of previously formed myelin), dysmyelinating gLD (deposition of structurally abnormal myelin) and myelinolytic disorders (vacuolisations disrupting myelin integrity).1
MRI characteristics help discriminate hypomyelination from other WMAs. In H-gLD, WMAs are widespread, mildly hyperintense on T2/fluid attenuation inversion recovery and associated with diffuse T1 hyperintense, isointense or mildly hypointense signal relative to the grey matter.4 In other gLD, WMAs can be focal or confluent, often with regional predominance, and prominent T2 hyperintensity with marked T1 hypointensity.2 4 H-gLD typically present in the neonatal period with axial hypotonia, followed by spastic paraparesis and delayed motor development in early childhood.2 4 Nystagmus, cerebellar ataxia, extrapyramidal syndrome and cognitive impairment can later develop.3 4 Depending on the gene defect, extraneurological signs have been described.4 Adolescent/adult-onset H-gLD are exceptionally reported.2 We report findings in three unrelated patients with late-onset neurological symptoms and hypomyelinating features on brain MRI.
Case reports
Brain MRI of our patients are shown in figure 1, all showing diffuse WMAs suggestive of isolated hypomyelination. Candidate variants detected by next-generation sequencing (NGS), clinical and electrophysiological features are summarised in online supplementary table 1. The genes included in the panels are listed in online supplementary table 2. Genetic methodology, molecular characteristics and bioinformatics prediction tools of …
Footnotes
Contributors GM and YN contributed equally in the conception of the manuscript, the acquisition of the data and drafting of a significant portion of the manuscript, tables and figures. JAC contributed in drafting and editing a significant portion of the manuscript. SS contributed in the analysis of the data and drafting a significant portion of the manuscript and tables. All authors approved the final manuscript.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests GM received fellowship funding from the National Multiple Sclerosis Society Institutional Clinician Training Award ICT 0002 and Biogen Fellowship Grant 6873-P-FEL. SS has nothing to disclose. JAC received personal fees for consulting for Adamas, Alkermes, Convelo, EMD Serono, Novartis and Pendopharm; speaking for Mylan and Synthon; and serving as a Co-Editor of Multiple Sclerosis Journal—Experimental, Translational and Clinical. YN received speech honoraria from Actelion and Orphan Europe, and received travel funding from Actelion, Shire and Genzyme.
Patient consent Obtained.
Provenance and peer review Not commissioned; externally peer reviewed.