Development and validation of a non-invasive method for quantifying amino acids in human saliva

Area of Science:

• Analytical Chemistry
• Biochemistry
• Clinical Diagnostics

Background:

• Saliva offers advantages over blood and urine for sample collection due to its non-invasive nature and ease of collection.
• Quantifying salivary amino acids can aid in early disease detection, particularly for various malignancies.
• Liquid chromatography-tandem mass spectrometry (LC-MS/MS) provides high sensitivity and selectivity for complex biological samples.

Purpose of the Study:

• To develop and validate a method for quantifying 13 salivary-free amino acid (SFAA) profiles in human saliva.
• To support the early clinical diagnosis of diseases, including cancer, by analyzing SFAA patterns.
• To establish the utility of LC-MS/MS for sensitive and selective amino acid analysis in saliva.

Main Methods:

• Saliva samples were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) with an Intrada Amino Acid column.
• A binary gradient elution and electrospray ionization in positive ion mode were employed for chromatographic separation and detection.
• Amino acids were extracted using acetonitrile, and quantification was performed using multiple reaction monitoring (MRM) modes.

Main Results:

• The method demonstrated high sensitivity with limit of detection (LOD) and limit of quantification (LOQ) values in the micromolar range for most amino acids.
• Matrix-matched calibration curves showed excellent linearity (r² ≥ 0.998), and recovery experiments confirmed accuracy (85-110%).
• Intra- and inter-day precision were generally low (0.02-7.28%), indicating a reliable method for SFAA quantification.

Conclusions:

• The developed LC-MS/MS method is suitable for accurate and sensitive quantification of SFFA profiles in saliva.
• Salivary amino acid patterns show potential as biomarkers for early cancer detection and monitoring.
• This approach can advance research into new cancer treatments and the identification of biomarkers for various diseases.