Untargeted Investigation of Non-Alcoholic Fatty Liver Disease Using Effective Mutiplatform GC-MS Instrumentation

Significance of the Study

Non-alcoholic fatty liver disease (NAFLD) affects a growing population in developed countries and mirrors the rise in obesity and metabolic syndrome. Early detection of biochemical changes can inform prevention and treatment strategies.

Objectives and Study Overview

This investigation aimed to deploy a multi-platform gas chromatography mass spectrometry workflow to discover and confirm untargeted biomarkers of NAFLD. Using a rodent model with dietary copper and fructose variations, investigators collected liver and plasma samples for comprehensive metabolomic profiling.

Methodology and Instrumentation

• Sample Preparation and Derivatization: Extraction with water/methanol, drying, two-step derivatization using methoxyamine hydrochloride and MTBSTFA to stabilize sugars, acids, amino acids, and lipids.
• Gas Chromatography Systems:
  • Agilent 7890 with LECO L-Pal3 autosampler
  • Rxi-5 Sil and Rxi-17 Sil columns for GCxGC
• Mass Spectrometry Platforms:
  • LECO Pegasus BT GC-TOFMS (EI, m/z 45–600, 10 spectra/s) for high throughput
  • LECO Pegasus HRT GCxGC‐HRT (EI and CI, m/z 30–1500, 200 spectra/s) for high resolution and multidimensional separations
• Data Processing: Untargeted peak detection, deconvolution with ChromaTOF, accurate mass formula determination, and spectral library matching using both main and replib databases.

Main Results and Discussion

• Robust detection of metabolites such as aconitic acid, L-lysine, and stearic acid with library similarities above 900/1000.
• Identification of upregulated liver metabolites (eg, fumaric acid, histidine, pantothenic acid) contrasted with plasma profiles showing elevated citric acid.
• GCxGC-HRT contour plots and extracted ion chromatograms demonstrated clear group clustering and removal of background interferences for confident biomarker assignment.
• High-resolution MS provided accurate mass (PPM errors <0.3) for molecular and adduct ions, enhancing identification confidence.

Benefits and Practical Applications

• Accelerated throughput of complex biological samples via GC-TOFMS supports large-scale studies and routine lab workflows.
• Enhanced chromatographic and spectral resolution enables comprehensive metabolome coverage and reliable biomarker discovery.
• Methodology is transferable to QA/QC, clinical research, and pharmaceutical development requiring robust metabolite profiling.

Future Trends and Applications

• Integration with machine learning and cloud-based analytics for automated feature annotation and pattern recognition.
• Application expansion to human cohorts and other disease models for translational metabolomics.
• Further automation and miniaturization of sampling and derivatization for high-throughput clinical screening.

Conclusion

The combined use of GC-TOFMS and GCxGC-HRT demonstrated a powerful platform for untargeted metabolomics in NAFLD research. By balancing throughput and resolution, this approach provides a reliable workflow for biomarker discovery in complex biological matrices.

Reference

• Alonso DE, Zhang X, Richards T, Binkley J. Untargeted Investigation of Non-Alcoholic Fatty Liver Disease Using Effective Multiplatform GC-MS Instrumentation. LECO Corporation and University of Louisville, 2024.