# A Novel Sample Preparation Method for GC-MS Analysis of Volatile Organic Compounds in Whole Blood for Veterinary Use

## TL;DR

This paper introduces a new method for preparing blood samples to detect volatile organic compounds in veterinary diagnostics, improving accuracy and efficiency.

## Contribution

A standardized sample preparation method using urea and NaCl for enhanced VOC detection in whole blood for veterinary use.

## Key findings

- Urea with NaCl improved VOC detection sensitivity by up to 151.3%.
- Matrix effect variation was reduced by -35.5% to 25% compared to water-only controls.
- The method simplifies procedures while maintaining accuracy for veterinary diagnostics.

## Abstract

Volatile organic compounds (VOCs) in biological samples originate both from exogenous and endogenous sources. Recent studies have highlighted their potential as cancer biomarkers, emphasizing the need for accurate detection methods in clinical settings. However, analysis of VOCs in whole blood (WB) samples remains challenging due to the complex matrix effects caused by the protein−VOC binding phenomenon and lack of standardized sample preparation protocols. Therefore, this study suggests a standardized method for advanced VOC analysis in WB samples specifically for veterinary applications. We compared 12 combinations of reagents composed of protein denaturing reagents and salts, particularly urea mixtures, to enhance VOC decoupling from proteins and improve matrix effect uniformity in gas chromatography−mass spectrometry (GC-MS) analysis. Among all combinations, urea with NaCl showed an optimal performance, demonstrating an advancement in the detection sensitivity of up to 151.3% and a significantly reduced matrix effect variation (−35.5% to 25%) compared with the water-only control. This novel approach eliminates complex procedures while maintaining accuracy, making it particularly suitable for veterinary uses. The method’s standardization and improved performance characteristics offer a practical solution for efficient VOC detection in veterinary diagnostics, potentially advancing tumor biomarker research.