Cannabinoid Signaling in Auditory Function and Development

Potential uses of auditory nerve stimulation to modulate immune responses in the inner ear and auditory brainstem

Bioelectronic medicine uses electrical stimulation of the nervous system to improve health outcomes throughout the body primarily by regulating immune responses. This concept, however, has yet to be applied systematically to the auditory system. There is growing interest in how cochlear damage and associated neuroinflammation may contribute to hearing loss. In conjunction with recent findings, we propose here a new perspective, which could be applied alongside advancing technologies, to use auditory nerve (AN) stimulation to modulate immune responses in hearing health disorders and following surgeries for auditory implants. In this article we will: (1) review the mechanisms of inflammation in the auditory system in relation to various forms of hearing loss, (2) explore nerve stimulation to reduce inflammation throughout the body and how similar neural-immune circuits likely exist in the auditory system (3) summarize current methods for stimulating the auditory system, particularly the AN, and (4) propose future directions to use bioelectronic medicine to ameliorate harmful immune responses in the inner ear and auditory brainstem to treat refractory conditions. We will illustrate how current knowledge from bioelectronic medicine can be applied to AN stimulation to resolve inflammation associated with implantation and disease. Further, we suggest the necessary steps to get discoveries in this emerging field from bench to bedside. Our vision is a future for AN stimulation that includes additional protocols as well as advances in devices to target and engage neural-immune circuitry for therapeutic benefits.

A Systematic Review on Metabolomics Analysis in Hearing Impairment: Is It a Possible Tool in Understanding Auditory Pathologies?

With more than 466 million people affected, hearing loss represents the most common sensory pathology worldwide. Despite its widespread occurrence, much remains to be explored, particularly concerning the intricate pathogenic mechanisms underlying its diverse phenotypes. In this context, metabolomics emerges as a promising approach. Indeed, lying downstream from molecular biology's central dogma, the metabolome reflects both genetic traits and environmental influences. Furthermore, its dynamic nature facilitates well-defined changes during disease states, making metabolomic analysis a unique lens into the mechanisms underpinning various hearing impairment forms. Hence, these investigations may pave the way for improved diagnostic strategies, personalized interventions and targeted treatments, ultimately enhancing the clinical management of affected individuals. In this comprehensive review, we discuss findings from 20 original articles, including human and animal studies. Existing literature highlights specific metabolic changes associated with hearing loss and ototoxicity of certain compounds. Nevertheless, numerous critical issues have emerged from the study of the current state of the art, with the lack of standardization of methods, significant heterogeneity in the studies and often small sample sizes being the main limiting factors for the reliability of these findings. Therefore, these results should serve as a stepping stone for future research aimed at addressing the aforementioned challenges.

Cannabidiol regulates apoptosis and autophagy in inflammation and cancer: A review

Cannabidiol (CBD) is a terpenoid naturally found in plants. The purified compound is used in the treatment of mental disorders because of its antidepressive, anxiolytic, and antiepileptic effects. CBD can affect the regulation of several pathophysiologic processes, including autophagy, cytokine secretion, apoptosis, and innate and adaptive immune responses. However, several authors have reported contradictory findings concerning the magnitude and direction of CBD-mediated effects. For example, CBD treatment can increase, decrease, or have no significant effect on autophagy and apoptosis. These variable results can be attributed to the differences in the biological models, cell types, and CBD concentration used in these studies. This review focuses on the mechanism of regulation of autophagy and apoptosis in inflammatory response and cancer by CBD. Further, we broadly elaborated on the prospects of using CBD as an anti-inflammatory agent and in cancer therapy in the future.

Genome-wide DNA methylation analysis of middle-aged and elderly monozygotic twins with age-related hearing loss in Qingdao, China

OBJECTIVE

To explore the differences in DNA methylation associated with age-related hearing loss in a study of 57 twin pairs from China.

DESIGN

Monozygotic twins were identified through the Qingdao Twin Registration system. The median age of participants was >50 years. Their hearing thresholds were measured using a multilevel pure-tone audiometry assessment. The pure-tone audiometry was calculated at low frequencies (0.5, 1.0, and 2.0 kHz), speech frequencies (0.5, 1.0, 2.0, and 4.0kHz), and high frequencies (4.0 and 8 kHz). The CpG sites were tested using a linear mixed-effects model, and the function of the cis-regulatory regions and ontological enrichments were predicted using the online Genomic Regions Enrichment of Annotations Tool. The differentially methylated regions were identified using a comb-p python library approach.

RESULTS

In each of the PTA categories (low-, speech-, high-frequency), age-related hearing loss was detected in 25.9%, 19.3%, and 52.8% of participants. In the low-, speech- and high-frequency categories we identified 18, 42, and 12 individual CpG sites and 6, 11, and 6 differentially methylated regions. The CpG site located near DUSP4 had the strongest association with low- and speech-frequency, while the strongest association with high-frequency was near C21orf58. We identified associations of ALG10 with high-frequency hearing, C3 and LCK with low- and speech-frequency hearing, and GBX2 with low-frequency hearing. Top pathways that may be related to hearing, such as the Notch signaling pathway, were also identified.

CONCLUSION

Our study is the first of its kind to identify these genes and their associated with DNA methylation may play essential roles in the hearing process. The results of our epigenome-wide association study on twins clarify the complex mechanisms underlying age-related hearing loss.

Tobacco, but Neither Cannabis Smoking Nor Co-Drug Use, Is Associated With Hearing Loss in the National Health and Nutrition Examination Survey, 2011 to 2012 and 2015 to 2016

INTRODUCTION

A relationship between tobacco smoking and hearing loss has been reported; associations with cannabis smoking are unknown. In this cross-sectional population-based study, we examined relationships between hearing loss and smoking (tobacco, cannabis, or co-drug use).

METHODS

We explored the relationship between hearing loss and smoking among 2705 participants [mean age = 39.41 (SE: 0.36) years] in the National Health and Nutrition Examination Survey (2011 to 12; 2015 to 16). Smoking status was obtained via questionnaire; four mutually exclusive groups were defined: nonsmokers, current regular cannabis smokers, current regular tobacco smokers, and co-drug users. Hearing sensitivity (0.5 to 8 kHz) was assessed, and two puretone averages (PTAs) computed: low- (PTA 0.5,1,2 ) and high-frequency (PTA 3,4,6,8 ). We defined hearing loss as threshold >15 dB HL. Multivariable logistic regression was used to examine sex-specific associations between smoking and hearing loss in the poorer ear (selected based on PTA 0.5,1,2 ) adjusting for age, sex, race/ethnicity, hypertension, diabetes, education, and noise exposure with sample weights applied.

RESULTS

In the age-sex adjusted model, tobacco smokers had increased odds of low- and high-frequency hearing loss compared with non-smokers [odds ratio (OR) = 1.58, 95% confidence ratio (CI): 1.05 to 2.37 and OR = 1.97, 95% CI: 1.58 to 2.45, respectively]. Co-drug users also had greater odds of low- and high-frequency hearing loss [OR = 2.07, 95% CI: 1.10 to 3.91 and OR = 2.24, 95% CI: 1.27 to 3.96, respectively]. In the fully adjusted multivariable model, compared with non-smokers, tobacco smokers had greater odds of high-frequency hearing loss [multivariable adjusted odds ratio = 1.64, 95% CI: 1.28-2.09]. However, in the fully adjusted model, there were no statistically significant relationships between hearing loss (PTA 0.5,1,2 or PTA 3,4,6,8 ) and cannabis smoking or co-drug use.

DISCUSSION

Cannabis smoking without concomitant tobacco consumption is not associated with hearing loss. However, sole use of cannabis was relatively rare and the prevalence of hearing loss in this population was low, limiting generalizability of the results. This study suggests that tobacco smoking may be a risk factor for hearing loss but does not support an association between hearing loss and cannabis smoking. More definitive evidence could be derived using physiological measures of auditory function in smokers and from longitudinal studies.

Plasma metabolomics analyses highlight the multifaceted effects of noise exposure and the diagnostic power of dysregulated metabolites for noise-induced hearing loss in steel workers

Noise exposure can lead to various kinds of disorders. Noise-induced hearing loss (NIHL) is one of the leading disorders confusing the noise-exposed workers. It is essential to identify NIHL markers for its early diagnosis and new therapeutic targets for its treatment. In this study, a total of 90 plasma samples from 60 noise-exposed steel factory male workers (the noise group) with (NIHL group, n = 30) and without NIHL (non-NIHL group, n = 30) and 30 male controls without noise exposure (control group) were collected. Untargeted human plasma metabolomic profiles were determined with HPLC-MS/MS. The levels of the metabolites in the samples were normalized to total peak intensity, and the processed data were subjected to multivariate data analysis. The Wilcoxon test and orthogonal partial least square-discriminant analysis (OPLS-DA) were performed. With the threshold of p < 0.05 and the variable importance of projection (VIP) value >1, 469 differential plasma metabolites associated with noise exposure (DMs-NE) were identified, and their associated 58 KEGG pathways were indicated. In total, 33 differential metabolites associated with NIHL (DMs-NIHL) and their associated 12 KEGG pathways were identified. There were six common pathways associated with both noise exposure and NIHL. Through multiple comparisons, seven metabolites were shown to be dysregulated in the NIHL group compared with the other two groups. Through LASSO regression analysis, two risk models were constructed for NIHL status predication which could discriminate NIHL from non-NIHL workers with the area under the curve (AUC) values of 0.840 and 0.872, respectively, indicating their efficiency in NIHL diagnosis. To validate the results of the metabolomics, cochlear gene expression comparisons between susceptible and resistant mice in the GSE8342 dataset from Gene Expression Omnibus (GEO) were performed. The immune response and cell death-related processes were highlighted for their close relations with noise exposure, indicating their critical roles in noise-induced disorders. We concluded that there was a significant difference between the metabolite’s profiles between NIHL cases and non-NIHL individuals. Noise exposure could lead to dysregulations of a variety of biological pathways, especially immune response and cell death-related processes. Our results might provide new clues for noise exposure studies and NIHL diagnosis.