Objective: To develop early sensitive and specific predictors of heart disease in Friedreich’s Ataxia (FA).

Background: FA is often accompanied by cardiomyopathy that is a leading cause of mortality. Conventional clinical tools capture late consequences of disease rather than upstream molecular drivers. To address this, we initiated an integrated translational program combining detailed clinical phenotyping with multi-omics profiling to identify novel markers to predict early cardiac disease in FA.

Method: We are conducting descriptive and integrative analysis of a deeply phenotyped cohort of FA patients and heterozygous carriers. Clinical status is assessed using FA questionnaires (FARS, SARA, and FADL), the Kansas City Cardiomyopathy Questionnaire-12, advanced cardiac imaging, clinical plasma biomarkers, and GAA repeat length. Research plasma profiling was performed using multiplex Luminex cytokine assays, targeted lipidomics by LC-MS/MS, and mass spec–based proteomics. Single-cell immune profiling using CITE-seq and genomic analyses are ongoing. Multivariate modeling approaches, including principal component analysis and elastic net–based regression, are applied to identify candidate predictive molecular features associated with FA cardiac involvement.

Results: Cytokine analyses demonstrated alterations in circulating inflammatory and remodeling markers; however, predictive modeling indicated that these alone had limited discriminatory performance. Model accuracy improved when variables were integrated with clinical and imaging metrics, suggesting a subset of circulating proteins contributes to disease pathways. Lipidomic profiling revealed distinct remodeling of inflammatory lipid mediator pathways, with clear separation between FA and control driven by coordinated pathway-level changes. Mass spec proteomics and early single-cell immune profiling further identified trends consistent with mitochondrial stress, immune activation, and fibro-inflammatory signaling.

Conclusion: These preliminary findings support integrating clinical phenotyping with genomic, proteomic, lipidomic, and immune datasets with an aim to refine molecular signatures associated with cardiac disease risk, progression, and therapeutic response. This work provides a translational framework for developing blood-based biomarker panels to improve early detection and monitoring of cardiomyopathy in Friedreich’s ataxia.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/multi-omics-biomarker-discovery-in-friedreichs-ataxia-cardiomyopathy/