Session Time: 1:45pm-3:15pm
Location: Hall 3FG
Objective: To provide a clinical diagnostic algorithm for pediatric Early Onset Ataxia (EOA) that can contribute to an increased diagnostic yield.
Background: In children, EOA comprises a large group of unique, rare and heterogeneous disorders, mostly of autosomal recessive inheritance, manifesting before the 25th year of life. The large variety in phenotypes and genotypes has made the diagnostic workup a challenging and costly task. The Childhood Ataxia and Cerebellar Group of the EPNS (CACG-EPNS) has developed a clinical diagnostic algorithm that guides the clinician through the broad differential diagnosis of pediatric EOA.
Methods: After an extensive literature search (until July 2017), we characterized eight crucial steps for the differential diagnosis of pediatric EOA, including: 1. clinical features, 2. assessment of additional features, 3. family history and spot diagnosis of distinct phenotypes, 4. magnetic resonance imaging, 5. biochemical testing, 6. genetic testing by Array investigation, 7. Next Generation Sequencing (NGS), including an EOA gene panel and 8. the “optional” final step to include the obtained data in the European EOA database (to enable further genetic testing (if no diagnosis is obtained) and/or longitudinal follow-up from pediatric to adult life). We retrospectively determined the algorithm’s diagnostic yield in a thoroughly phenotyped historic cohort of 35 EOA patients with “core-ataxic” (n=18), and “mixed-ataxic” (n=17) phenotypes (assessed by 7 observers).(1)
Results: The diagnostic yield was 86% (core-ataxia 83% vs mixed-ataxia 88%; ns). The algorithm did not identify 2 patients with a mitochondrial disorder (core ataxia) and 3 patients remain without a diagnosis (core and mixed ataxia).
Conclusions: In the well-phenotyped historic cohort of EOA children, the yield of the diagnostic algorithm including NGS/EOA gene panel testing, was higher than previous published results (30-40%).(2) In addition to the diagnostic gain by the presented algorithm, this could also be attributed to the meticulous phenotypic assessment of the historic cohort. Future international prospective studies may hopefully reveal the clinical gain of the current algorithm into further extent.
References: 1. Lawerman et al. Reliability of phenotypic early-onset ataxia assessment: a pilot study. DMCN 2016;58(1):70-6. 2. van de Warrenburg et al. Clinical exome sequencing for cerebellar ataxia and spastic paraplegia uncovers novel gene-disease associations and unanticipated rare disorders. Eur J Hum Genet 2016 Oct;24(10):1460-1466.
To cite this abstract in AMA style:R. Brandsma, C. Verschuuren, H. Kremer, T. de Koning, M. de Koning-Tijssen, D. Sival. A Diagnostic Algorithm for Pediatric Early Onset Ataxia [abstract]. Mov Disord. 2018; 33 (suppl 2). https://www.mdsabstracts.org/abstract/a-diagnostic-algorithm-for-pediatric-early-onset-ataxia/. Accessed December 1, 2023.
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