Characterizing the Access of Cholinergic Antagonists to Efferent Synapses in the Inner Ear

Stimulation of cholinergic efferent neurons innervating the inner ear has profound, well-characterized effects on vestibular and auditory physiology, after activating distinct ACh receptors (AChRs) on afferents and hair cells in peripheral endorgans. Efferent-mediated fast and slow excitation of vestibular afferents are mediated by α4β2*-containing nicotinic AChRs (nAChRs) and muscarinic AChRs (mAChRs), respectively. On the auditory side, efferent-mediated suppression of distortion product otoacoustic emissions (DPOAEs) is mediated by α9α10nAChRs. Previous characterization of these synaptic mechanisms utilized cholinergic drugs, that when systemically administered, also reach the CNS, which may limit their utility in probing efferent function without also considering central effects. Use of peripherally-acting cholinergic drugs with local application strategies may be useful, but this approach has remained relatively unexplored. Using multiple administration routes, we performed a combination of vestibular afferent and DPOAE recordings during efferent stimulation in mouse and turtle to determine whether charged mAChR or α9α10nAChR antagonists, with little CNS entry, can still engage efferent synaptic targets in the inner ear. The charged mAChR antagonists glycopyrrolate and methscopolamine blocked efferent-mediated slow excitation of mouse vestibular afferents following intraperitoneal, middle ear, or direct perilymphatic administration. Both mAChR antagonists were effective when delivered to the middle ear, contralateral to the side of afferent recordings, suggesting they gain vascular access after first entering the perilymphatic compartment. In contrast, charged α9α10nAChR antagonists blocked efferent-mediated suppression of DPOAEs only upon direct perilymphatic application, but failed to reach efferent synapses when systemically administered. These data show that efferent mechanisms are viable targets for further characterizing drug access in the inner ear.

Gpr125 Marks Distinct Cochlear Cell Types and Is Dispensable for Cochlear Development and Hearing

The G protein-coupled receptor (GPR) family critically regulates development and homeostasis of multiple organs. As a member of the GPR adhesion family, Gpr125 (Adgra3) modulates Wnt/PCP signaling and convergent extension in developing zebrafish, but whether it is essential for cochlear development in mammals is unknown. Here, we examined the Gpr125lacZ/+ knock-in mice and show that Gpr125 is dynamically expressed in the developing and mature cochleae. From embryonic day (E) 15.5 to postnatal day (P) 30, Gpr125-β-Gal is consistently expressed in the lesser epithelial ridge and its presumed progenies, the supporting cell subtypes Claudius cells and Hensen’s cells. In contrast, Gpr125-β-Gal is expressed transiently in outer hair cells, epithelial cells in the lateral cochlear wall, interdental cells, and spiral ganglion neurons in the late embryonic and early postnatal cochlea. In situ hybridization for Gpr125 mRNA confirmed Gpr125 expression and validated loss of expression in Gpr125lacZ/lacZ cochleae. Lastly, Gpr125lacZ/+ and Gpr125lacZ/lacZ cochleae displayed no detectable loss or disorganization of either sensory or non-sensory cells in the embryonic and postnatal ages and exhibited normal auditory physiology. Together, our study reveals that Gpr125 is dynamically expressed in multiple cell types in the developing and mature cochlea and is dispensable for cochlear development and hearing.

Subclinical Auditory Dysfunction: Relationship Between Distortion Product Otoacoustic Emissions and the Audiogram

Purpose Distortion product otoacoustic emissions (DPOAEs) and audiometric thresholds have been used to account for the impacts of subclinical outer hair cell (OHC) dysfunction on auditory perception and measures of auditory physiology. However, the relationship between DPOAEs and the audiogram is unclear. This study investigated this relationship by determining how well DPOAE levels can predict the audiogram among individuals with clinically normal hearing. Additionally, the impacts of age, noise exposure, and the perception of tinnitus on the ability of DPOAE levels to predict the audiogram were evaluated. Method Suprathreshold DPOAE levels from 1 to 10 kHz and pure-tone thresholds from 0.25 to 16 kHz were measured in 366 ears from 194 young adults (19–35 years old) with clinically normal audiograms and middle ear function. The measured DPOAE levels at all frequencies were used to predict pure-tone thresholds at each frequency. Participants were grouped by age, self-reported noise exposure/Veteran status, and self-report of tinnitus. Results Including DPOAE levels in the pure-tone threshold prediction model improved threshold predictions at all frequencies from 0.25 to 16 kHz compared with a model based only on sample mean pure-tone thresholds, but these improvements were modest. DPOAE levels for f 2 frequencies of 4 and 5 kHz were particularly influential in predicting pure-tone thresholds above 4 kHz. However, prediction accuracy varied based on participant characteristics. On average, predicted pure-tone thresholds were better than measured thresholds among Veterans, individuals with tinnitus, and the oldest age group. Conclusions These results indicate a complex relationship between DPOAE levels and the audiogram. Underestimation of pure-tone thresholds for some groups suggests that additional factors other than OHC damage may impact thresholds among individuals within these categories. These findings suggest that DPOAE levels and pure-tone thresholds may differ in terms of how well they reflect subclinical OHC dysfunction. Supplemental Material https://doi.org/10.23641/asha.13564745

Towards Personalized Auditory Models: Predicting Individual Sensorineural Hearing-Loss Profiles From Recorded Human Auditory Physiology

Over the past decades, different types of auditory models have been developed to study the functioning of normal and impaired auditory processing. Several models can simulate frequency-dependent sensorineural hearing loss (SNHL) and can in this way be used to develop personalized audio-signal processing for hearing aids. However, to determine individualized SNHL profiles, we rely on indirect and noninvasive markers of cochlear and auditory-nerve (AN) damage. Our progressive knowledge of the functional aspects of different SNHL subtypes stresses the importance of incorporating them into the simulated SNHL profile, but has at the same time complicated the task of accomplishing this on the basis of noninvasive markers. In particular, different auditory-evoked potential (AEP) types can show a different sensitivity to outer-hair-cell (OHC), inner-hair-cell (IHC), or AN damage, but it is not clear which AEP-derived metric is best suited to develop personalized auditory models. This study investigates how simulated and recorded AEPs can be used to derive individual AN- or OHC-damage patterns and personalize auditory processing models. First, we individualized the cochlear model parameters using common methods of frequency-specific OHC-damage quantification, after which we simulated AEPs for different degrees of AN damage. Using a classification technique, we determined the recorded AEP metric that best predicted the simulated individualized cochlear synaptopathy profiles. We cross-validated our method using the data set at hand, but also applied the trained classifier to recorded AEPs from a new cohort to illustrate the generalizability of the method.

Predicting synapse counts in living humans by combining computational models with auditory physiology

Aging, noise exposure, and ototoxic medications lead to cochlear synapse loss in animal models. As cochlear function is highly conserved across mammalian species, synaptopathy likely occurs in humans as well. Indeed, temporal bone studies demonstrate loss of synapses with advancing age in humans. Synaptopathy is predicted to result in perceptual deficits including tinnitus, hyperacusis, and difficulty understanding speech-in-noise. However, there is currently no method for diagnosing synaptopathy in living humans. This prevents us from determining if noise-induced synaptopathy occurs in humans, identifying the perceptual consequences of synaptopathy, or testing potential drug treatments. Several physiological measures are sensitive to synaptopathy in animal models, including auditory brainstem response (ABR) wave I amplitude. However, it is unclear how to translate these measures to synaptopathy diagnosis in humans. In this study, a human computational model of the auditory periphery that can predict ABR waveforms and distortion product otoacoustic emissions (DPOAEs) was fit using Bayesian regression analysis to predict synapse counts in individual human participants based on their measured DPOAE levels and ABR wave I amplitudes. Lower predicted synapse numbers were associated with higher noise exposure history, increased likelihood of tinnitus, and poorer speech-in-noise perception. These findings illustrate the utility of this modeling approach in predicting synapse counts from physiological data.

Towards personalized auditory models: predicting individual sensorineural-hearing-loss profiles from recorded human auditory physiology

Over the past decades, different types of auditory models have been developed to study the functioning of normal and impaired auditory processing. Several models can simulate frequency-dependent sensorineural hearing loss (SNHL), and can in this way be used to develop personalized audio-signal processing for hearing aids. However, to determine individualized SNHL profiles, we rely on indirect and non-invasive markers of cochlear and auditory-nerve (AN) damage. Our progressive knowledge of the functional aspects of different SNHL subtypes stresses the importance of incorporating them into the simulated SNHL profile, but has at the same time complicated the task of accomplishing this on the basis of non-invasive markers. In particular, different auditory evoked potential (AEP) types can show a different sensitivity to outer-hair-cell (OHC), inner-hair-cell (IHC) or AN damage, but it is not clear which AEP-derived metric is best suited to develop personalized auditory models. This study investigates how simulated and recorded AEPs can be used to derive individual AN- or OHC-damage patterns and personalize auditory processing models. First, we individualized the cochlear-model parameters using common methods of frequency-specific OHC-damage quantification, after which we simulated AEPs for different degrees of AN-damage. Using a classification technique, we determined the recorded AEP metric that best predicted the simulated individualized CS profiles. We cross-validated our method using the dataset at hand, but also applied the trained classifier to recorded AEPs from a new cohort to illustrate the generalisability of the method.