Noise-induced hearing loss (NIHL) is caused by prolonged exposure to loud sounds from different occupational and environmental sources. Patients may not exhibit a significantly reduced hearing threshold, which makes early detection of NIHL difficult, with diagnosis relying on audiometric testing. This study aims to investigate the proteomics of perilymph, cerebrospinal fluid (CSF), and blood from guinea pig, to identify potential biomarkers for NIHL.
Perilymph and CSF were collected from the cochlear apex in a guinea pig after opening the bulla, while blood was obtained from the same animal and processed using a Volumetric Absorptive Micro-sampling (VAMS) device. All samples were trypsin-digested and prepared for mass spectrometry analysis using two different quantitative shotgun proteomic approaches: Data-Independent Acquisition (DIA) and Data-Dependent Acquisition (DDA).
Initial findings demonstrated that DIA identified 1306, 1326, and 1770 proteins in perilymph, CSF, and blood, approximately twice the number of proteins identified by DDA. A total of 794 proteins were found in all three samples, while 61, 60, and 787 proteins were exclusively identified in perilymph, CSF, and blood, respectively. Notably, proteins such as Complement factors, Glutathione peroxidase, Superoxide dismutase, and HSP70 were detected in both local and systemic samples. These proteins are associated with inflammation and oxidative stress, which have been reported in NIHL in previous studies. This correlation suggests the potential utility of these biomarkers for studying noise trauma and its effects on the immune system, which can contribute to noise-induced deafness. Furthermore, it suggests the potential of using readily accessible systemic samples, such as blood, for studying noise trauma, which may be used as an effective diagnostic tool without inner ear samples from invasive surgeries.
Future studies will employ a NIHL model to assess proteomic changes following sound exposure. This research highlights the previously untapped potential of using fluid-based biomarkers for diagnosing inner ear disorders.