Neuropediatrics 2016; 47 - FV04-04
DOI: 10.1055/s-0036-1583731

A Combined Metabolic–Genetic Approach to Early-Onset Epileptic Encephalopathies: Results from a Swiss Study Cohort

L. Abela 1, 2, K. Steindl 2, 3, L. Simmons 1, 2, P. Joset 3, M. Papuc 3, D. Mathis 4, B. Schmitt 5, G. Wohlrab 5, A. Klein 1, R. Asadollahi 3, L. Crowther 1, 2, O. Sass 4, M. Hersberger 4, A. Rauch 2, 3, B. Plecko 1, 2
  • 1Division of Child Neurology, University Children’s Hospital Zurich
  • 2Radiz–Rare Disease Initiative Zurich, Clinical Research Priority Program for Rare Diseases
  • 3Institute of Medical Genetics, University of Zurich, Schlieren
  • 4Division of Clinical Chemistry and Biochemistry, University Children Hospital Zurich
  • 5Division of Epilepsy and Neurophysiology, University Children’s Hospital Zurich

Background: Early onset epileptic encephalopathies (EE) represent a heterogeneous group of rare disorders that constitute a major diagnostic and therapeutic challenge. Here, we applied a combined “omics” approach to unravel the etiologic background of early-onset EE in a cohort of 63 patients.

Methods: From April 2013 until December 2014, we included 63 patients with early-onset EE of unclear etiology. Neurometabolic analysis comprised plasma amino acids, α-aminoadipic semialdehyde, pipecolic acid, plasma vitamin B6 compounds, a lymphoblast culture, and an untargeted metabolomics approach. Genetic workup included a high-resolution chromosomal microarray and a whole exome sequencing (WES) in index patients and their parents.

Results: Clinical and EEG record data were collected from all patients. Targeted biochemical analysis was normal in all patients. Untargeted metabolomic analysis in 36 patients identified two novel potential plasma biomarkers for Snyder Robinson Syndrome and infantile cerebellar retinal degeneration. In 8% (5/63), microarray analysis identified pathogenic deletions (del 1p36, del 22q11.23, del CDKL5/GPM6A, del UBE3A, del MBD5). In 38% (19/49), WES revealed mutations in known EE/ID genes (ARX, CDKL5, FKTN, SCN1A, SCN2A, SCN8A, KCNQ2, SMS, ACO2, KDM5C, STXBP1, GABRB2, MIB1), while in 51% (25/49) novel candidate genes are under investigation.

Conclusion: WES is a powerful technique to unravel mutations in known but also novel candidate genes that are associated with EE. Untargeted metabolome analysis has the potential to support the pathogenicity of novel missense mutations affecting metabolic pathways and to identify novel biomarkers that may facilitate diagnosis and future treatment monitoring.