Abstract

In the field of neurodegeneration, it is important to identify biomarkers that enable early disease prediction, since these disorders start decades before clinical symptoms manifest. Cerebrospinal fluid (CSF) is considered an excellent source for biomarker discovery since it is in direct contact with the extracellular space of the brain and directly reflects disease-specific changes.While the liquor drainage is no major risk factor for patients, it is still not as easy and popular as simple blood sampling and less liquid can be collected. Especially when a variety of experiments for one cohort is planned, the volume of CSF can be a limiting factor. Therefore, it is essential that extraction and analytical methods are adapted to low amounts of liquor. If in follow-up studies, additional replicates to increase statistical significance or different extraction approaches are planned, the required amounts have to be minimized.With this extraction method, a combined proteomics and metabolomics approach is possible. This opportunity implies a variety of advantages. First, a classification matrix based on the comprehensive data set has a potentially higher accuracy even without a deeper understanding of the biological meaning of the different omics changes. If the proteome and metabolome differences can be linked to each other, this approach can conceivably open so far unknown doors regarding the cause or progression of different diseases like Alzheimer's or Parkinson's disease.

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