Pilot Project Awardees
Gopal Jadhav
Centers for Disease Control and Prevention (CDC) states noise induced hearing loss (NIHL) as one of the prevalent health issues in the U.S. Currently, there are no FDA approved treatments for NIHL. Therefore, search to identify novel druggable targets for NIHL is required. Recently, role of inflammation proved to be attractive targets for novel drug discovery against NIHL and associated ototoxicity. TREM1 is a main culprit responsible for exaggerating various inflammatory disorders by manipulating human immune system. Its pharmacological inhibition by LR12 in the subversion of various disease models, project that it might thus be used as a template to design TREM1 inhibitory agents, provided derivatives devoid mainly of proteolytic degradation and mutagenicity, could be discovered. Our preliminary data showed that TREM1 inhibition by LR12 protects against NIHL. To address LR12 low half-life issue, we identified two GJMs small molecules as potential TREM1 inhibitors using molecular docking. GJMs directly bind TREM1 and possibly with good PK/PD. Data together develops central hypothesis that "TREM1 inhibition as novel treatment against NIHL and associated ototoxicity". To achieve this, AIm (1) dual approach where GJMs/LR12/Vehicle will be administered trans-tympanically 1-day after (Therapeutic) or 1-week before (Prophylactic) exposure to PTS-noise levels. Hearing functions via ABRs and DPOAEs, and HCs, SGNs and macrophages abundance will be examined. We anticipate TREM1 inhibitors to attenuate NIHL. Aim (2) precise PK/PD of GJMs will be performed. We anticipate GJMs to be more stable, non-hepatotoxic and non-mutagenic than LR12. The data will allow us to determine the most efficacious and potent TREM1 inhibitor against NIHL and ototoxicity. Impact: Pilot studies will unwrap the critical role of TREM1 in NIHL and ototoxicity and display it as novel inflammatory target. TREM1 inhibition may preserve cochlear sensory cells. The data will reveal efficacy, potency, therapeutic window of protection against NIHL and PK/PD properties of GJMs. Such information will form the basis to prioritize lead TREM1 inhibitors (LR12/GJMs) for optimization of target selectivity and therapeutic ADMET properties to provide novel therapeutics for NIHL.
Steven Fernandes
Hearing loss affects more than 1.5 billion people globally, comprising approximately 20% of the global population. Of these, 430 million people have disabling hearing loss, a number expected to rise to 700 million by 2050. Children with hearing loss often do not receive the same level of schooling as their peers, and adults with hearing loss are more likely to face higher unemployment rates or occupy lower-level jobs. Therefore, according to the WHO, unaddressed hearing loss incurs an annual global cost of US$ 980 billion, including the costs of hearing devices, educational support, productivity losses, and societal impacts. When hair cells are lost, sound is not readily converted into neural activity in the cochlea. To mitigate this issue, we intend to develop a deep learning-based method for detecting auditory hair cells (HCs) along the entire length of the cochlea. We propose to use two main algorithms in our deep learning model to analyze microscopy images of cochlear HCs: iFS-RCNN for HC detection and EM-net for HC segmentation. Unlike traditional Faster R-CNN, which requires a large volume of labeled data, iFS-RCNN is designed to learn new classes using just a few labeled examples. iFS-RCNN incorporates memory-augmented components for efficient feature storage, making it more memory-efficient than traditional Faster R-CNN methods. For HC segmentation, we will use EM-net to analyze the fluorescent signal in HCs along the cochlea's length. We will also optimize the spatial embeddings of cells for instance segmentation. Pixels that belong to a cell are projected from their spatial locations through predicted embedding vectors, forming clusters around centroid object instances. To identify clusters of pixels and predict segmentation masks for missing cells, we will employ Deep Embedded Subspace Clustering, known for its robustness against noise and scalability.
Yusi Fu
Drug-induced ototoxicity is a leading cause of acquired hearing loss. Intravenous administration of aminoglycoside antibiotics is used to treat individuals with cystic fibrosis (CF) hospitalized with respiratory infections, which can lead to sensorineural hearing loss (SNHL) in a dose-dependent manner. Yet, there is substantial variability in the degree of hearing loss among individuals of similar age and cumulative aminoglycoside dosing, suggestive of genomic influences that contribute to susceptibility to Aminoglycoside-Induced Hearing Loss (AIHL). To uncover susceptibility-related genes, other researchers are conducting genome-wide association studies (GWAS) by genotyping ~700 patients with CF using microarrays and their corresponding audiograms by audiologists. GWAS focus on statistical associations to identify associated loci instead of the functional gene. Thus, a major challenge posed by GWAS is the exploration of the functional consequences of nearby variants of identified loci. Although the array-based imputation strategy enables us to investigate more than 90% of the common loci (minor allele frequency, MAF ≥ 0.5%), it cannot be applied to rare variants (MAF < 0.5%) that make up the vast majority of human genetic variations. Whole genome sequencing (WGS) can determine almost the entire DNA sequence of a single individual at a single base resolution and is efficient for evaluating rare genetic variants. WGS enables the profiling of exon regions and regulatory non-coding sequences (e.g., promoters and enhancers), which can also contribute to altering the transcription and expression of genes. With the reduced cost of sequencing, WGS has become more popular when determining the risk variants associated with traits and diseases, as it guarantees that real functional variants are sequenced. WGS can identify rare genetic variants and better understand complex traits. WGS can identify rare variants with high confidence, with a substitution error rate of 10-5 to 10-4/bp. Based on sequencing results from 1000 genome projects, WGS can detect 4-5 million rare variants in each individual. Studies have shown that, both analytically and numerically, extreme phenotype sampling (EPS) increases the presence of rare causal variants in various settings. For this study, we will utilize WGS of extreme phenotypes to potentially identify rare variants that modulate susceptibility to AIHL. The results can be used to curate a list of candidate genes for testing in a future study with a larger sample size. Impact - This study can potentially identify candidate causal genes for AIHL susceptibility and provide a list of variants for test in future studies. The results will help identify patients with CF at risk for AIHL and improve the quality of life of patients treated with aminoglycosides.
Sarath Vijayakumar
Cystic fibrosis (CF) is an autosomal recessive genetic disorder with a prevalence of over 40,000 children and adults in the U.S. and an estimated 105,000 people worldwide. It is the most common fatal genetic disease in the United States. The reduced or null function of the cystic fibrosis transmembrane conductance regulator (CFTR) protein predisposes patients to frequent pulmonary bacterial infections, pancreatic exocrine insufficiency, and gastrointestinal complications. Although the arsenal of antibiotics has expanded, aminoglycosides, especially tobramycin—selected for its anti-P. aeruginosa activity—remain pivotal for managing acute pulmonary exacerbations in patients with CF. Notably, while many aminoglycosides manifest ototoxic effects predominantly either in the cochlea or the vestibular system, tobramycin impacts both systems. In the inner ear, CFTR expression has been observed in the basolateral membrane of the cochlear outer hair cells and it has been shown to interact directly with prestin, the cochlear outer hair cell electromotility protein. Furthermore, pendrin and CFTR mRNA transcripts co-localize in the mitochondria-rich cells of the mouse endolymphatic sac. While CFTR's role in vestibular physiology has been implied, its exact expression pattern within the vestibular organs remains elusive. In this proposed study, we postulate: 1) the higher incidence of vestibular impairment in patients with CF is due to CFTR mutation affecting the ionic homeostasis and normal function of the vestibular organs 2) CFTR channel dysfunction sensitizes the vestibular organs to aminoglycoside ototoxicity. Our investigative approach will involve 1) mapping the cellular distribution of the CFTR channel across both vestibular and auditory organs, and 2) detailing the vestibular and auditory effects of tobramycin-induced ototoxicity using a CF mouse model harboring the prevalent CFTR ΔF508 mutation. This investigation aims to enrich our comprehension of the CFTR channel's physiological role in vestibular and auditory organs. From a public health perspective, this research would elucidate molecular underpinnings and associated risks of irreversible ototoxicity in CF patients undergoing tobramycin therapy.
