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Related Experiment Video

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Lipidomics and Transcriptomics in Neurological Diseases
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CLAW-MRM: Comprehensive Lipidomics Automation Workflow for Multiple Reaction Monitoring Using Large Language Models.

Connor Beveridge1, Sanjay Iyer1, Caitlin E Randolph1

  • 1Department of Chemistry, Purdue University, 560 Oval Drive, West Lafayette, Indiana 47907, United States.

Analytical Chemistry
|September 2, 2025
PubMed
Summary

This study introduces CLAW-MRM, an automated workflow for lipidomics analysis. It simplifies lipid identification and statistical analysis, offering insights into Alzheimer's disease lipid metabolism.

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Area of Science:

  • Biochemistry
  • Bioinformatics
  • Neuroscience

Background:

  • Lipidomic profiling generates complex data, hindering manual annotation and interpretation.
  • Existing tools lack automated workflows and integration with statistical/bioinformatics analyses.
  • Lipid structural and chemical diversity complicates lipidome analysis.

Purpose of the Study:

  • Introduce the Comprehensive Lipidomics Automated Workflow for Multiple Reaction Monitoring (CLAW-MRM).
  • Automate lipid annotation, statistical analysis, and data parsing for high-throughput lipidomics.
  • Enhance biological relevance by linking lipid expression with gene patterns and enabling AI-driven interaction.

Main Methods:

  • Utilized custom multiple reaction monitoring (MRM) precursor product ion transitions for lipid analysis.
  • Employed trimmed mean of m-value (TMM) normalization for robust cross-sample comparisons.
  • Integrated LIGER (Lipidome Gene Enrichment Reactions) for linking lipidomics with gene expression and utilized a natural language interface powered by large language models.

Main Results:

  • Analyzed lipid profiles in Alzheimer's disease (AD) mouse liver tissues and brain lipid droplets.
  • Assessed the impact of normalization strategies on TMM-normalized lipidomic outcomes.
  • Identified metabolic pathways enriched in differentially expressed lipids in AD using CLAW-MRM-based LIGER.

Conclusions:

  • CLAW-MRM streamlines end-to-end lipidomics data acquisition to interpretation.
  • The platform automates lipid structural identification and integrates AI-assisted bioinformatics.
  • CLAW-MRM provides valuable insights into altered lipid metabolism in Alzheimer's disease.