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Quantitative Analysis of -Hydroxybutyrate in Hair Using Target Analyte Finding Processing of Comprehensive GC-HRT Data

Applications | 2016 | LECOInstrumentation
GC/MSD, GC/HRMS, GC/TOF
Industries
Forensics
Manufacturer
Agilent Technologies, LECO

Summary

Significance of the topic


Hair analysis offers a unique window into long-term exposure to drugs and endogenous compounds that are rapidly cleared from blood and urine. Gamma-hydroxybutyrate (GHB) poses analytical challenges due to its short biological half-life yet remains incorporated into hair. A robust, sensitive and high-resolution workflow is essential to detect and quantify GHB in hair and to leverage comprehensive mass spectral data for simultaneous identification of other metabolites.

Aims and study overview


The study aimed to compare two sample preparation techniques for extracting GHB from hair and to demonstrate a rapid quantitative approach using Target Analyte Finding (TAF) in high-resolution time-of-flight GC-MS data. It also explored the capability of non-targeted screening through High Resolution Deconvolution (HRD) to identify a broad range of endogenous and exogenous compounds in a single acquisition.

Methodology


Hair strands from two volunteers were washed with water and dichloromethane, dried, and split into two sets. One set was homogenized by bead disruption, the other was cut into small segments. Each 20 mg aliquot was spiked with deuterated GHB internal standard, extracted overnight in methanol, dried under nitrogen, and derivatized with BSTFA. The samples were analyzed by GC-HRT with comprehensive full-scan acquisition.

Used instrumention


  • Gas chromatograph with autosampler operating in pulsed splitless mode at 250 °C
  • Rxi-5MS capillary column (30 m × 0.25 mm × 0.25 µm) with constant helium flow
  • LECO Pegasus GC-HRT time-of-flight mass spectrometer at 25 000 resolution (FWHM), EI 70 eV, m/z 45–510, 10 spectra/s

Results and discussion


The TAF algorithm in ChromaTOF-HRT software provided fast quantitation by matching accurate-mass ions and retention time windows. Calibration for GHB (quantifier ion m/z 233.1024, qualifier 239.1400) exhibited linearity (r2 > 0.997) across 0.15–5.0 ng/mg. Bead-ruptor preparation consistently yielded higher GHB concentrations (0.41–0.61 ng/mg for volunteer A; 1.21–1.34 ng/mg for B) than the cut method. Volunteer B showed greater incorporation of GHB. HRD processing of the full-scan data identified a diverse array of compounds—acids, amino acids, fatty acids, esters and more—with mass accuracy below 1 ppm, facilitating both targeted and non-targeted analyses from the same dataset.

Benefits and practical applications


  • The bead disruption method enhances extraction efficiency for polar analytes in hair
  • High-resolution TOFMS with TAF enables precise, interference-free quantitation of GHB at trace levels
  • Comprehensive HRD screening supports retrospective discovery of additional biomarkers without repeat analyses
  • Streamlined workflow suits high-throughput laboratories focused on forensic, clinical or sports anti-doping testing

Future trends and applications


Advances in spectral databases and automated HRD algorithms will expand non-targeted screening capabilities. Integration of machine learning for pattern recognition in hair metabolomics may reveal novel exposure markers. Further miniaturization and coupling with micro-extraction techniques could streamline sample preparation. High-throughput multiplex assays may combine hair analysis with other biological matrices for comprehensive exposure profiling.

Conclusion


A single high-resolution GC-TOF measurement using targeted and non-targeted processing delivers robust quantitation of GHB in hair while uncovering a broad metabolite profile. The bead-ruptor extraction method proves superior for recovering GHB, and the combination of TAF and HRD maximizes the value of each data file for forensic and clinical investigations.

Reference


LECO Corporation Quantitative Analysis of γ-Hydroxybutyrate in Hair Using Comprehensive GC-HRT Data Form No 203-821-504 2016

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