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Molecular diagnosis of neurogenetic disorders : motoneuron, peripheral nerve and muscle disorders

Authors :
Burgunder, J-M.
Schöls, L.
Baets, J.
Andersen, Peter M.
Gasser, T.
Szolnoki, Z.
Fontaine, B.
Van Broeckhoven, C.
Di Donato, S.
De Jonghe, P.
Lynch, T.
Mariotti, C.
Spinazzola, A.
Tabrizi, S.J.
Tallaksen, C.
Zeviani, M.
Harbo, H.F.
Finsterer, J.
Burgunder, J-M.
Schöls, L.
Baets, J.
Andersen, Peter M.
Gasser, T.
Szolnoki, Z.
Fontaine, B.
Van Broeckhoven, C.
Di Donato, S.
De Jonghe, P.
Lynch, T.
Mariotti, C.
Spinazzola, A.
Tabrizi, S.J.
Tallaksen, C.
Zeviani, M.
Harbo, H.F.
Finsterer, J.
Publication Year :
2012

Abstract

Objectives: The EFNS guidelines on the molecular diagnosis of motoneuron disorders, neuropathies and myopathies are designed to summarize the possibilities and limitations of molecular genetic techniques and to provide diagnostic criteria for deciding when a molecular diagnostic work-up is indicated. Search strategy: To collect data about the planning, conditions and performance of molecular diagnosis of these disorders, a literature search in various electronic databases was carried out and original papers, meta-analyses, review papers and guideline recommendations reviewed. Results: The best level of evidence for genetic testing recommendation (Level B) can be found for the disorders with specific presentations, including familial ALS, spinal and bulbar muscular atrophy, Charcot-Marie-Tooth 1A, myotonic dystrophy and Duchenne muscular dystrophy. For a number of less common disorders a precise description of the phenotype, including the use of immunological methods in the case of myopathies, is considered good clinical practice to guide molecular genetic testing. Conclusion: These guidelines are provisional and the availability of molecular-genetic epidemiological data in the future about the neurogenetic disorders under discussion in the present paper will allow improved recommendation with an increased level of evidence.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1400066958
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1002.9781444346268.ch8