Longitudinal Deep Multi-Omics Profiling in a CLN3Δex7/8 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 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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