Sunday, May 18, 2025
5/18/2025
Sex-specific Influences on tear microRNAs in dry eye disease - PROJECT SUMMARY Dry eye disease (DED) affects millions of Americans, causing discomfort, vision problems, pain, and potential ocular surface damage. The prevalence of DED is higher in women than men, and there may be molecular differences among racial groups. Tear fluid, which can be collected non-invasively, holds promise for identifying DED biomarkers. Our hypothesis is that the molecular composition of tear fluid can distinguish DED subtypes and correlate with clinical signs and severity. MicroRNAs (miRNAs) in circulation have shown great stability and resistance to degradation over long-term storage. Therefore, miRNAs present in tear fluid hold significant promise for clinical biomarkers, complementing proteins. In this proposal, we aim to analyze a large sample set (n=800) to discover sex- and race-specific differences in tear miRNAs and proteins and their relationship to disease severity and subtypes. By considering diverse populations, confounding factors, and integrating multi-omics data, we will identify reliable biomarkers applicable in clinical settings. We anticipate that discovering tear biomarkers will improve DED diagnosis and enable personalized treatment based on each patient's tear composition. Personalized medicine approaches accounting for sex and race-specific factors will guide tailored treatments, improving outcomes for DED patients. Furthermore, we will explore the interplay between tear miRNAs and proteins, investigating potential connections and novel molecular mechanisms. Machine learning will be employed to deepen our understanding of the underlying molecular processes involved in DED subtypes and provide insights into therapeutic targets and interventions. Finally, we will create a reference database compiling a comprehensive profile of miRNAs and proteins detected in human tear fluid. This freely accessible database will include demographic parameters, clinical histories, and functional tools for data analysis and visualization. It will serve as a valuable resource for vision researchers studying the expression patterns of molecules of interest in human tears, facilitating further investigations and advancements in the field.
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