Establishing parameters for the characterization of rare neurometabolic and neurodegenerative diseases using mass-spectrometry based Metabolomics
by Henry Gerd Klemp
Date of Examination:2021-09-23
Date of issue:2021-10-18
Advisor:Prof. Dr. André Fischer
Referee:Prof. Dr. André Fischer
Referee:Prof. Dr. Klaus-Armin Nave
Persistent Address:
http://dx.doi.org/10.53846/goediss-8875
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Abstract
English
Rare diseases are a class of disorders where every single disease has a low prevalence, but due to their incredible variety, they affect more than 100 million people worldwide. A significant number of these disorders lead to neuropediatric, neurometabolic, and neurodegenerative disorders. The high diversity of disorders and widespread missing information hinder potentially life-saving diagnoses. While newborn screening successfully alleviated diagnostic problems for the most common rare disorders, the majority remain unstudied. Next-generation sequencing methods have led to a giant leap forward in rare disease detection, but undocumented variants of unknown significance can still hinder diagnosis. Additionally, the outbreak and severity of many of these disorders cannot be predicted from the genotype alone. As metabolism is the interphase between exogenous factors and endogenous factors, the holistic study of metabolism, metabolomics, may help characterize rare neurometabolic disorders working in concert with genomics techniques. Consequently, the main aim of this project was to establish a liquid chromatography mass spectrometry-based platform for the characterization of rare neurometabolic and neuropediatric disorders. For this, we developed an in-house untargeted metabolomics platform, as well as applied the commercial AbsoluteIDQ p180-kit from Biocrates for targeted metabolomics applications. For our untargeted platform, we selected a combination of a chromatography method for hydrophilic analytes, as well as a technique for lipids. To alleviate identification problems common to untargeted metabolomics, we decided to generate a metabolite identification library for the hydrophilic method comprising 408 human disease-relevant metabolites. Our untargeted method compared well with other methods in the field and was able to show additional validation parameters commonly not studied by other metabolomics methods. In a second part, we aimed to apply our complete metabolomics platform to several research projects in the rare disease field. Here we were able to discover new potential biomarkers for peroxisomal disorders, find potential prognostic biomarkers for developing the cerebral phenotype of X-Adrenoleukodystrophy, provide metabolic validation data to a single patient with an alteration in fatty acid elongation, as well as study the organic cation transporter 1 (OCT-1). Using these applications, we could successfully fulfill the aims of this project and show the utility of metabolomics in characterizing neurometabolic conditions. Further research is needed to study the abilities of this metabolic platform in detail. However, this metabolomics platform may significantly contribute to the diagnosis and characterization of rare disorders, especially in association with other omics disciplines.
Keywords: Rare diseases; Rare disorders; Metabolomics; LC-MS; Mass spectrometry; Zellwegers disease; Peroxisomes; ELOVL1; neurometabolic
