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Udgivet

Recognition of alpha-mannosidosis in paediatric and adult patients: Presentation of a diagnostic algorithm from an international working group

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Alpha-mannosidosis is an ultra-rare progressive lysosomal storage disorder caused by deficiency of alpha-mannosidase. Timely diagnosis of the disease has the potential to influence patient outcomes as preventive therapies can be initiated at an early stage. However, no internationally-recognised algorithm is currently available for the diagnosis of the disease. With the aim of developing a diagnostic algorithm for alpha-mannosidosis an international panel of experts met to reach a consensus by applying the nominal group technique. Two proposals were developed for diagnostic algorithms of alpha-mannosidosis, one for patients ≤10 years of age and one for those >10 years of age. In younger patients, hearing impairment and/or speech delay are the cardinal symptoms that should prompt the clinician to look for additional symptoms that may provide further diagnostic clues. Older patients have different clinical presentations, and the presence of mental retardation and motor impairment progression and/or psychiatric manifestations should prompt the clinician to assess for other symptoms. In both younger and older patients, either additional metabolic monitoring or referral for testing is warranted upon suspicion of disease. Oligosaccharides in urine (historically performed) or serum were considered as an initial screening procedure, while enzymatic activity may also be considered as first choice in some centres. Molecular testing should be performed as a final confirmatory step. The developed algorithms can easily be applied in a variety of settings, and may help to favour early diagnosis of alpha mannosidosis and treatment.

OriginalsprogEngelsk
TidsskriftMolecular Genetics and Metabolism
Vol/bind126
Udgave nummer4
Sider (fra-til)470-474
Antal sider5
ISSN1096-7192
DOI
StatusUdgivet - 2019

Bibliografisk note

Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.

ID: 58995033