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Longitudinal deep multi-omics profiling in a CLN3Δex7/8 minipig model identifies biomarker signatures of disease
Mitchell J Rechtzigel1, Brittany Lee2, Christine Neville3
1Pediatrics and Rare Diseases Group, Sanford Research, Sioux Falls, SD, USA.
Background:
Development of therapies for CLN3 disease, a rare pediatric lysosomal storage disorder, has been hindered by the lack of etiological insights and translatable biomarkers to clinics.
Methods:
We used a deep multi-omics approach to discover blood-based 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 2634 proteins, collectively the most exhaustive multi-omics profile conducted on serum from a porcine model. This was previously impossible due to lack of efficient deep serum proteome profiling technologies compatible with model organisms.
Results:
Here we show that the presymptomatic disease state is characterized by elevations in glycerophosphodiester species and lysosomal proteases, while later timepoints are enriched with species involved in immune cell activation and sphingolipid metabolism. Cathepsin S (CTSS), Cathepsin B (CTSB), 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.
Conclusions:
This study's findings demonstrate the potential of deep multi-omics profiling for uncovering disease-specific biomarkers, providing valuable insights for understanding disease and facilitating the identification of potential drug targets, thus offering valuable insights for therapeutic interventions.
Insights
Researchers identified novel blood biomarkers for CLN3 disease using multi-omics analysis in a porcine model. Key findings include elevated glycerophosphodiester species and lysosomal proteases, offering potential for early diagnosis and therapeutic targets.
Area of Science:
- Biochemistry
- Genetics
- Biomarker Discovery
Background:
- CLN3 disease, a rare pediatric lysosomal storage disorder, lacks clear etiological understanding and clinically translatable biomarkers.
- Therapeutic development for CLN3 disease is significantly challenged by these knowledge gaps.
Purpose of the Study:
- To discover blood-based biomarkers for CLN3 disease using a deep multi-omics approach.
- To identify potential diagnostic and therapeutic targets for CLN3 disease.
Main Methods:
- Utilized longitudinal serum samples from a porcine model of CLN3 disease.
- Employed comprehensive metabolomics and nanoparticle-based LC-MS proteomic profiling (TMTpro 18-plex).
- Generated quantitative data for 769 metabolites and 2634 proteins, representing an exhaustive serum multi-omics profile in a porcine model.
Main Results:
- Identified distinct molecular signatures at different disease stages: elevated glycerophosphodiester species and lysosomal proteases presymptomatically.
- Observed enrichment of immune cell activation and sphingolipid metabolism markers at later disease stages.
- Cathepsin S (CTSS), Cathepsin B (CTSB), glycerophosphoinositol, and glycerophosphoethanolamine significantly correlated with genotype variation, suggesting potential for a diagnostic index score.
Conclusions:
- Deep multi-omics profiling is a powerful strategy for uncovering disease-specific biomarkers.
- The identified biomarkers offer valuable insights into CLN3 disease mechanisms and progression.
- These findings facilitate the identification of potential drug targets and inform therapeutic interventions for CLN3 disease.
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