Elucidation of the complex metabolic profile of cerebrospinal fluid using an untargeted biochemical profiling assay

- Untargeted metabolomics is a semi-quantitative screening approach used to identify small molecules in cerebrospinal fluid.
- CSF has a complex biochemical profile
- Urine and/or plasma may be sufficient surrogates for CSF for diagnosis of a subset of inborn errors of metabolism.
- Untargeted metabolomics provides a broad-based screening method but requires targeted follow-up testing for confirmation.
- Specific IEM validation will show the power of metabolomics to identify disease signatures, monitor progression, and assess treatment biomarkers.

We sought to determine the molecular composition of human cerebrospinal fluid (CSF) and identify the biochemical pathways represented in CSF to understand the potential for untargeted screening of inborn errors of metabolism (IEMs). Biochemical profiles for each sample were obtained using an integrated metabolomics workflow comprised of four chromatographic techniques followed by mass spectrometry. Secondarily, we wanted to compare the biochemical profile of CSF with those of plasma and urine within the integrated mass spectrometric-based metabolomic workflow. Three sample types, CSF (N = 30), urine (N = 40) and EDTA plasma (N = 31), were analyzed from retrospectively collected pediatric cohorts of equivalent age and gender characteristics. We identified 435 biochemicals in CSF representing numerous biological and chemical/structural families. Sixty-three percent (273 of 435) of the biochemicals detected in CSF also were detected in urine and plasma, another 32% (140 of 435) were detected in either plasma or urine, and 5% (22 of 435) were detected only in CSF. Analyses of several metabolites showed agreement between clinically useful assays and the metabolomics approach. An additional set of CSF and plasma samples collected from the same patient revealed correlation between several biochemicals detected in paired samples. Finally, analysis of CSF from a pediatric case with dihydropteridine reductase (DHPR) deficiency demonstrated the utility of untargeted global metabolic phenotyping as a broad assessment to screen samples from patients with undifferentiated phenotypes. The results indicate a single CSF sample processed with an integrated metabolomics workflow can be used to identify a large breadth of biochemicals that could be useful for identifying disrupted metabolic patterns associated with IEMs.