Metabolomics/lipidomics in rare neurologic diseases

Rare disorders (Orphan Diseases) are defined with an incidence below 1:2000 and 50% have their onset in childhood. Orphan diseases of the central nervous system (CNS) may manifest with a variety of symptoms as early onset epilepsies, childhood onset movement disorders, primary intellectual disability or else. Due to the rarity of the single disease entity, diagnosis is hampered by lack of recognizable phenotypes and limited clinical knowledge. This often causes a diagnostic odyssey and prevents causal treatment. Biomarkers are defined as anything that indicates a diseased/altered phenotype and are of utmost importance as they can guide further diagnostic work-up. To date, in neurological disorders of childhood selective screening of biomarkers in plasma and cerebrospinal fluid (CSF) is performed by applying different sequential biochemical methods, which is time consuming and often needs large sample volumes. The metabolome represents the global spectrum of low molecular-weight metabolites in a distinct biological sample, and provides temporal information about its biochemical environment. Similarly, lipidomic profiling, a subset of metabolomics devoted to the qualitative and quantitative analysis of lipids, has emerged as a promising new tool for identifying alterations in lipid classes. Metabolomic profiles differ in normal and pathological conditions and thereby offer insight into disease-associated metabolic dysregulation. Comparative analysis of the metabolome (control vs. study groups) should allow the identification of disease specific metabolomic phenotypes and the discovery of novel biomarkers. During the course of this project, mass spectrometric analysis of CSF and plasma samples, collected in the context of routine diagnostic work-up, will be employed to interrogate for biochemical variations between affected subjects versus control groups. Its advantage is the broad view on metabolomic perturbations by applying one single method. To date, blood plasma is the most common choice for clinical diagnostic analysis due to minimally invasive collection and its rich composition of metabolites. CSF on the other hand is more taxing to collect, but due to its proximity to the brain and CNS, CSF may provide a more accurate and unique reflection of the neurochemical condition. The metabolomic composition of plasma is well studied, with over 4500 compounds reported, and new constituents appearing in the literature infrequently. In contrast, a deta iled CSF metabolome database (CMD) was only first published in 2007 by David S. Wishart. It now contains at least 468 small molecules, including 42 phosphatidylcholines, 14 sphingolipids and 33 metal ions. The CMD along with other freely available online databases (e.g. KEGG, Human Metabolome Database, PubChem) are powerful and essential informatics tools, and will be used extensively in this study for the identification of putative neurological biomarkers.