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Longitudinal Deep Multi-Omics Profiling in a CLN3 Minipig Model Reveals Novel Biomarker Signatures for Batten Disease

ABSTRACT: 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.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Sus Scrofa (ncbitaxon:9823)

SUBMITTER: Jon J Brudvig

PROVIDER: MSV000092536 | MassIVE | Thu Jul 27 09:54:00 BST 2023

SECONDARY ACCESSION(S): PXD044146

REPOSITORIES: MassIVE

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Longitudinal Deep Multi-Omics Profiling in aCLN3Δex7/8Minipig Model Reveals Novel Biomarker Signatures for Batten Disease

Project description:Development of therapies for CLN3 Batten disease, a rare pediatric lysosomal storage disorder, has been hindered by the lack of etiological insights and translatable biomarkers to clinics. Here, we used a deep multi-omics approach to discover new biomarkers using longitudinal serum samples from a porcine model of CLN3 disease. 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, which was previously impossible due a to lack of efficient deep serum proteome profiling technologies compatible with model organisms. 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 in the clinic.

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