Sampling volatile biomarkers (odors) from clinical samples is a noninvasive, inexpensive, and effective method for disease detection. Although odor profiles have been utilized for the detection of cancer, acidosis, diabetes, and specific genetic disorders, their role in detecting progressive diseases is unknown. Therefore, the development of effective diagnostic tools using malodors requires technique validation during all stages of disease progression rather than end stage disease. One such progressive disease associated with overall systemic health is periodontal disease. As the 6<sup>th</sup> most common chronic disease worldwide, the presence of active end stage periodontitis has been associated with autoimmune disorders, cancer, lung infections, and heart disease. Thus, early detection of this progressive disease is the key to maintaining systemic health. The aim of this study was to develop a procedure for optimal extraction and analysis of volatile organic compounds (VOCs) in the various clinical stages of periodontal disease using solid-phase microextraction gas chromatography-mass spectrometry (SPME-GC-MS). A SPME method was developed for optimal compound equilibration, extraction, and desorption times. Then, saliva samples were collected and analyzed from the following periods of disease development: healthy (no active disease present), gingivitis (early disease), and periodontitis (end stage disease). Statistical analyses for extracted VOCs were performed using principal component analysis (PCA). This study reveals critical methodology optimization for analyzing odors in progressive disorders in hopes for better diagnostic tools.

Extraction and analysis of volatile biomarkers in oral disease using solid-phase microextraction (SPME)

2019 Spring National Meeting

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