Although blood and tissue are primary materials used in disease diagnosis, their cumbersome and invasive collection has spurred increasing interest in developing alternative approaches that utilize non-traditional matrices. Earwax is an underutilized matrix that is receiving more attention due to its ease of accessibility. As a lipid-rich material, it has the potential to reflect lipid profile changes correlated to disease. However, its chemical complexity can impede its analysis using traditional techniques. Furthermore, to be useful, the profile of “normal” earwax must be established. We utilized two-dimensional gas chromatography-mass spectrometry (GC×GC-MS) and direct analysis in real-time – high-resolution mass spectrometry (DART-HRMS) to establish the chemical profile of earwax. From GC×GC-MS analysis of ethyl acetate extracts made from samples acquired from healthy donors, 44 compounds, which is the greatest number ever detected or observed in un-saponified earwax samples, were identified. Represented classes included alkanes, alkenes, fatty acids, esters, triglycerides and cholesterol esters. Of the 44 compounds detected, 42 were identified for the first time in un-saponified earwax. The observed compound classes were also detected by DART-HRMS. Earwax from patients diagnosed with Ménière’s disease, a disorder of the inner ear, was then analyzed using both techniques. Visual comparison of the GC×GC-MS contour plots revealed recognizable patterns representing either earwax from healthy donors or that from individuals with Ménière’s disease. Major distinctions between the two included differences in triglyceride profiles, and levels of fatty acids. Results from multivariate statistical analysis of the DART-HRMS spectra showed that the two classes of samples could be separated and identified with 100% accuracy. The results demonstrate earwax to be a viable and readily accessible matrix that can be analyzed to show the presence of disease states. The observations pave the way for the use of this biological matrix in medical diagnostics.

Mass spectrometric analysis of earwax: Progress towards diagnosing Ménière’s disease

ACS Spring Meeting 2021

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