Description
Development of therapies for CLN3 Batten disease, a rare pediatric lysosomal storage disorder, has been hindered by a lack of etiological insights and translatable biomarkers. Here, we used deep multi-omics to discover new biomarkers using longitudinal serum samples from a porcine model of CLN3 disease, which was previously impossible due to lack of efficient serum proteome profiling technologies compatible with model organisms. Comprehensive metabolomics was combined with a nanoparticle-based LC-MS-based proteomic profiling coupled with TMTpro 18-plex to generate quantitative data on 769 metabolites and 2,634 proteins, collectively the most exhaustive multi-omics profile conducted on serum from a porcine model. The presymptomatic disease state was characterized by elevations in glycerophosphodiester species and lysosomal proteases, while later timepoints were enriched with species involved in immune cell activation and sphingolipid metabolism. Cathepsin S, Cathepsin B, glycerophosphoinositol, and glycerophosphoethanolamine captured a large portion of the genotype-correlated variation between healthy and diseased animals, suggesting that an index score based on these analytes could have great utility for tracking disease in the clinic.
[doi:10.25345/C5FQ9QG43]
[dataset license: CC0 1.0 Universal (CC0 1.0)]
Keywords: sphingolipid metabolism ; lysosomal storage ; blood serum ; lipidomics ; metabolomics
Contact
Principal Investigators:
(in alphabetical order)
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Jon J Brudvig, Sanford Research, USA
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alexcampos
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Distinct protein accessions are counted across all files submitted in the "Statistical Analysis
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