JIMD Reports (Sep 2022)

A cross‐sectional natural history study of aspartylglucosaminuria

  • Kimberly Goodspeed,
  • Daniel Horton,
  • Andrea Lowden,
  • Peter V. Sguigna,
  • Timothy Booth,
  • Zhiyue J. Wang,
  • Veronica Bordes Edgar

DOI
https://doi.org/10.1002/jmd2.12294
Journal volume & issue
Vol. 63, no. 5
pp. 425 – 433

Abstract

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Abstract Aspartylglucosaminuria (AGU) is a rare lysosomal storage disorder that causes stagnation of development in adolescence and neurodegeneration in early adulthood. Precision therapies, including gene transfer therapy, are in development with a goal of taking advantage of the slow clinical course. Understanding of disease natural history and identification of disease‐relevant biomarkers are important steps in clinical trial readiness. We describe the clinical features of a diverse population of patients with AGU, including potential imaging and electrophysiological biomarkers. This is a single‐center, cross‐sectional study of the clinical, neuropsychological, electrophysiological, and imaging characteristics of AGU. A comprehensive assessment of eight participants (5 Non‐Finnish) revealed a mean non‐verbal IQ (NVIQ) of 70.25 ± 10.33 which decreased with age (rs = −0.85, p = 0.008). All participants demonstrated deficits in communication and gross/fine motor dysfunction. Auditory and visual evoked potentials demonstrated abnormalities in one or both modalities in 7 of 8 subjects, suggesting sensory pathway dysfunction. Brain imaging demonstrated T2 FLAIR hypointensity in the pulvinar nuclei and cerebral atrophy, as previously shown in the Finnish AGU population. Magnetic resonance spectroscopy (MRS) showed a 5.1 ppm peak corresponding to the toxic substrate (GlcNAc‐Asn), which accumulates in AGU. Our results showed there was no significant difference between Finnish and Non‐Finnish patients, and performance on standardized cognitive and motor testing was similar to prior studies. Age‐related changes on functional assessments and disease‐relevant abnormalities on surrogate biomarkers, such as MRS, could be used as outcome measures in a clinical trial.

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