Detecting Cochlear Synaptopathy Through Curvature Quantification of the Auditory Brainstem Response

Research trends and hotspot analysis of age-related hearing loss: A bibliometric analysis from 2019 to 2023

BACKGROUND

Age-related hearing loss (ARHL) - also termed presbycusis - is prevalent among older adults, leading to a range of issues. Although considerable progress in the understanding of ARHL over the decades, available reports lack data from recent years and do not comprehensively reflect the latest advancements and trends. Therefore, our study sought to assess research hotspots and trends in ARHL over the past 5 years to provide the basis for future research.

MATERIALS AND METHODS

The Web of Science Core Collection database was searched and screened from January 1, 2019 to October 21, 2023, according to the inclusion criteria. CiteSpace (5.8.R3), VOSviewer (1.6.19), and Microsoft Excel 2019 were employed for bibliometric analysis and visualization.

RESULTS

3084 articles from 92 countries led by the United States and China were included. There has been a steady upward trend in the number of publications from 2019 to 2023. The most productive institutions, authors, and journals are Johns Hopkins University (n = 113), Lin FR (n = 66), and Ear and Hearing (n = 135), respectively. Trend topic analyses revealed that "cochlear synaptopathy" and "dementia" were the predominant foci. Keywords, including "individuals" and "national health", began to appear.

CONCLUSION

Over the past 5 years, the annual number of publications has increased significantly and will continue to do so. Research on the mechanism of ARHL, represented by "oxidative stress", is a continuing focus. Emerging topics such as "individual differences" and "national health" may be potential future hotspots in this field.

The curvature quantification of wave I in auditory brainstem responses detects cochlear synaptopathy in human beings

PURPOSE

Patients with age-related hearing loss complain often about reduced speech perception in adverse listening environment. Studies on animals have suggested that cochlear synaptopathy may be one of the primary mechanisms responsible for this phenomenon. A decreased wave I amplitude in supra-threshold auditory brainstem response (ABR) can diagnose this pathology non-invasively. However, the interpretation of the wave I amplitude in humans remains controversial. Recent studies in mice have established a robust and reliable mathematic algorithm, i.e., curve curvature quantification, for detecting cochlear synaptopathy. This study aimed to determine whether the curve curvature has sufficient test-retest reliability to detect cochlear synaptopathy in aging humans.

METHODS

Healthy participants were recruited into this prospective study. All subjects underwent an audiogram examination with standard and extended high frequencies ranging from 0.125 to 16 kHz and an ABR with a stimulus of 80 dB nHL click. The peak amplitude, peak latency, curvature at the peak, and the area under the curve of wave I were calculated and analyzed.

RESULTS

A total of 80 individuals with normal hearing, aged 18 to 61 years, participated in this study, with a mean age of 26.4 years. Pearson correlation analysis showed a significant negative correlation between curvature and age, as well as between curvature and extended high frequency (EHF) threshold (10-16 kHz). Additionally, the same correlation was observed between age and area as well as age and EHF threshold. The model comparison demonstrated that the curvature at the peak of wave I is the best metric to correlate with EHF threshold.

CONCLUSION

The curvature at the peak of wave I is the most sensitive metric for detecting cochlear synaptopathy in humans  and may be applied in routine diagnostics to detect early degenerations of the auditory nerve.

The relationship and interdependence of auditory thresholds, proposed behavioural measures of hidden hearing loss, and physiological measures of auditory function

OBJECTIVES

Standard diagnostic measures focus on threshold elevation but hearing concerns may occur independently of threshold elevation - referred to as "hidden hearing loss" (HHL). A deeper understanding of HHL requires measurements that locate dysfunction along the auditory pathway. This study aimed to describe the relationship and interdependence between certain behavioural and physiological measures of auditory function that are thought to be indicative of HHL.

DESIGN

Data were collected on a battery of behavioural and physiological measures of hearing. Threshold-dependent variance was removed from each measure prior to generating a multiple regression model of the behavioural measures using the physiological measures.

STUDY SAMPLE

224 adults in the United States with audiometric thresholds ≤65 dB HL.

RESULTS

Thresholds accounted for between 21 and 60% of the variance in our behavioural measures and 5-51% in our physiological measures of hearing. There was no evidence that the behavioural measures of hearing could be predicted by the selected physiological measures.

CONCLUSIONS

Several proposed behavioural measures for HHL: thresholds-in-noise, frequency-modulation detection, and speech recognition in difficult listening conditions, are influenced by hearing sensitivity and are not predicted by outer hair cell or auditory nerve physiology. Therefore, these measures may not be able to assess threshold-independent hearing disorders.

Diabetes mellitus, hearing loss, and therapeutic interventions: A systematic review of insights from preclinical animal models

OBJECTIVES

The aim of this systematic review article is to evaluate the relationship between diabetes mellitus (DM) and sensorineural hearing loss (SNHL) utilizing preclinical animal models. The review focused on studies assessing SNHL in diabetic animal models, elucidating the mechanisms of DM-associated SNHL, and exploring the response of diabetic animal models to noise overexposure. We also discussed studies investigating the efficacy of potential therapeutic strategies for amelioration of DM-associated SNHL in the animal models.

METHODS

A protocol of this systematic review was designed a priori and was registered in the PROSPERO database (registration number: CRD42023439961). We conducted a comprehensive search on PubMed, Science Direct, Web of Science, Scopus, and EMBASE databases. A minimum of three reviewers independently screened, selected, and extracted data. The risk of bias assessment of eligible studies was conducted using the Systematic Review Center for Laboratory Animal Experimentation (SYRCLE) tool.

RESULTS

Following the screening of 238 studies, twelve original articles were included in this systematic review. The studies revealed that hyperglycemia significantly affects auditory function, with various pathological mechanisms contributing to DM-induced hearing impairment, including cochlear synaptopathy, microangiopathy, neuropathy, oxidative stress, mitochondrial abnormalities, and apoptosis-mediated cell death. Emerging interventions, such as Asiaticoside, Trigonelline, Chlorogenic acid, and Huotanquyu granules, demonstrated efficacy in providing otoprotection for preserving cochlear hair cells and hearing function.

CONCLUSIONS

Our systematic review delves into the intricate relationship between DM and hearing impairment in animal models. Future research should focus on targeted therapies to enhance cochlear mitochondrial function, alleviate oxidative stress, and regulate apoptosis. The association between SNHL and social isolation as well as cognitive decline underscores the necessity for innovative therapeutic modalities addressing yet undiscovered mechanisms. Translating findings from animal models to human studies will validate these findings, offering a synergistic approach to effectively manage DM-associated co-morbidities such as hearing impairment.

An Open-Source Deep Learning-Based GUI Toolbox For Automated Auditory Brainstem Response Analyses (ABRA)

In this paper, we introduce a new, open-source software developed in Python for analyzing Auditory Brainstem Response (ABR) waveforms. ABRs are a far-field recording of synchronous neural activity generated by the auditory fibers in the ear in response to sound, and used to study acoustic neural information traveling along the ascending auditory pathway. Common ABR data analysis practices are subject to human interpretation and are labor-intensive, requiring manual annotations and visual estimation of hearing thresholds. The proposed new Auditory Brainstem Response Analyzer (ABRA) software is designed to facilitate the analysis of ABRs by supporting batch data import/export, waveform visualization, and statistical analysis. Techniques implemented in this software include algorithmic peak finding, threshold estimation, latency estimation, time warping for curve alignment, and 3D plotting of ABR waveforms over stimulus frequencies and decibels. The excellent performance on a large dataset of ABR collected from three labs in the field of hearing research that use different experimental recording settings illustrates the efficacy, flexibility, and wide utility of ABRA.

Minimum Detectable Differences in Electrocochleography Measurements: Bayesian-Based Predictions

Physiology of the cochlea and auditory nerve can be assessed with electrocochleography (ECochG), a technique that involves measuring auditory evoked potentials from an electrode placed near or within the cochlea. Research, clinical, and operating room applications of ECochG have in part centered on measuring the auditory nerve compound action potential (AP) amplitude, the summating potential (SP) amplitude, and the ratio of the two (SP/AP). Despite the common use of ECochG, the variability of repeated amplitude measurements for individuals and groups is not well understood. We analyzed ECochG measurements made with a tympanic membrane electrode in a group of younger normal-hearing participants to characterize the within-participant and group-level variability for the AP amplitude, SP amplitude, and SP/AP amplitude ratio. Results show that the measurements have substantial variability and that, especially with smaller sample sizes, significant reduction in variability can be obtained by averaging measurements across repeated electrode placements within subjects. Using a Bayesian-based model of the data, we generated simulated data to predict minimum detectable differences in AP and SP amplitudes for experiments with a given number of participants and repeated measurements. Our findings provide evidence-based recommendations for the design and sample size determination of future experiments using ECochG amplitude measurements, and the evaluation of previous publications in terms of sensitivity to detecting experimental effects on ECochG amplitude measurements. Accounting for the variability of ECochG measurements should result in more consistent results in the clinical and basic assessments of hearing and hearing loss, either hidden or overt.

Optimizing non-invasive functional markers for cochlear deafferentation based on electrocochleography and auditory brainstem responses

Accumulating evidence suggests that cochlear deafferentation may contribute to suprathreshold deficits observed with or without elevated hearing thresholds, and can lead to accelerated age-related hearing loss. Currently there are no clinical diagnostic tools to detect human cochlear deafferentation in vivo. Preclinical studies using a combination of electrophysiological and post-mortem histological methods clearly demonstrate cochlear deafferentation including myelination loss, mitochondrial damages in spiral ganglion neurons (SGNs), and synaptic loss between inner hair cells and SGNs. Since clinical diagnosis of human cochlear deafferentation cannot include post-mortem histological quantification, various attempts based on functional measurements have been made to detect cochlear deafferentation. So far, those efforts have led to inconclusive results. Two major obstacles to the development of in vivo clinical diagnostics include a lack of standardized methods to validate new approaches and characterize the normative range of repeated measurements. In this overview, we examine strategies from previous studies to detect cochlear deafferentation from electrocochleography and auditory brainstem responses. We then summarize possible approaches to improve these non-invasive functional methods for detecting cochlear deafferentation with a focus on cochlear synaptopathy. We identify conceptual approaches that should be tested to associate unique electrophysiological features with cochlear deafferentation.