MSACL 2024 Abstract

Let Me Talk Your Ears Off: Determination of Chemical Markers of Ménière's Disease in Earwax Allix M. Coon (1), Gavin Setzen (2), Rabi A. Musah (1) (1) Department of Chemistry, University at Albany, State University of New York, Albany, NY, (2) Albany ENT & Allergy Services, Albany, NY Allix Coon, PhD (Presenter) University at Albany, SUNY >> POSTER (PDF)

Presenter Bio: Allix Coon is a post-doctoral researcher at the University at Albany, State University of New York who works under the direction of Professor Rabi Ann Musah. Her research focuses on the application of mass spectrometry towards the development of novel disease detection systems using mass spectrometry and non-traditional biological matrices that can be acquired non-invasively. Among the mass spectrometric approaches she has explored for this purpose are direct analysis in real time – mass spectrometry (DART-MS), GC-MS, two-dimensional GC-MS and MALDI-MS.

Introduction:
An increasing trend in the field of medical diagnostics is to utilize non-traditional biological matrices that can be collected in a minimally invasive manner as reporters of disease. These can include tears, sweat, fingernails and cerumen, otherwise known as earwax. Earwax is a highly lipid-rich matrix that can potentially provide information on diseases associated with lipid dysregulation. One disorder that is being investigated is Ménière’s disease. It is a disease of the inner ear that results in extreme vertigo and eventual hearing loss. The current approach to disease detection involves eliminating other potential disorders though “diagnosis by exclusion”. As a result, its presence is extremely time consuming to determine, and thus a rapid and accurate method of diagnosis would be of high benefit.

Methods:
Earwax was collected at a clinic from confirmed Ménière's disease and non-Ménière's disease donors. The individual plugs were suspended in ethyl acetate and the mass spectrometric technique, direct analysis in real time – high-resolution mass spectrometry (DART-HRMS) was used to acquire their chemical profiles. The acquired mass spectra were then subjected to multivariate statistical analysis to ascertain the chemical differences between the two groups.

Results:
Earwax is reported to contain hundreds of compounds and thus the DART-MS-derived data were screened against a compiled list of the known earwax constituents contained in the literature. A heatmap rendering of the mass spectral data for the subset of masses that matched those of earwax constituents reported in the literature was created, and analysis of variance was performed to reveal which masses were within a 95% confidence limit. A total of 100 masses were found to be important for differentiating the Ménière's disease and non-Ménière's disease samples. When inspecting the bar graph renderings of these masses, it was concluded that a subset of fifteen were presence/absence markers that were only found in one of the two groups including cholesteryl stearate and a cholesterol derivative with the formula C28H48O that we detected in previous studies. A partial least squares (PLS) classification model built on the basis of these markers exhibited an 83.08% leave-one-out cross validation, and an external validation prediction accuracy of 85% when screening the cerumen of unknowns.

Conclusion:
The results revealed 15 potential compounds that could serve as reporters for Ménière's disease. This work demonstrates that: (1) earwax can serve as a viable and readily accessible matrix that can be analyzed to reveal a disease state; and (2) a rapid and accurate Ménière’s disease diagnosis approach could be developed through interrogation of earwax using ambient ionization mass spectrometry.