Friedreich Ataxia Global Clinical Consortium UNIFIED Natural History Study

The UNIFAI Study: Friedreich Ataxia Global Clinical Consortium UNIFIED Natural History Study is a global research study designed to provide a deep and evolving understanding of the natural history of this rare and debilitating genetic disorder as well as inform clinical trial design and implementation. Friedreich's Ataxia is a rare, inherited, multi-system condition characterized by progressive neurological and cardiac symptoms. It is caused by mutations in the FXN (frataxin) gene. The UNIFAI study is a multicenter, prospective, longitudinal, observational study, which means that all data about the natural disease course will be captured at study visits conducted annually according to a single protocol for all sites. This study will recruit participants with FA worldwide, to be assessed annually for up to 25 years. Study participation involves yearly study visits with data collected from medical records and history along with clinical outcome assessments including, neurological exams, timed walking tests, upper limb function measures, and patient-reported quality of life assessments, with the option for sites to collect additional ancillary measures related to speech, vision, fatigue, balance and cognition. This global study is a harmonization of two well-established, long-standing natural history studies in FA that have provided a framework for further investigation of clinical measures that can quantitatively assess FA: FACOMS (US, Canada, Australia, New Zealand, and India) and EFACTS (European countries). These studies have been conducted in parallel with many similarities in study conduct. Uniting these two existing studies and groups of researchers gives greater power to data previously collected as well as future data. It also continues efforts to expand the network of clinical research centers specializing in FA called the FA-Global Clinical Consortium. Due to advances in understanding the genetic and cellular dysfunction of FA that lead to symptoms observed in affected individuals, there has been significant growth in the discovery and development of therapeutic approaches, many currently being evaluated in clinical trials and a first approved treatment in the United States in 2023. The UNIFAI study aims to build upon this momentum by focusing on several key objectives. UNIFAI will assess the natural history of FA by collecting data from diagnosed individuals of all ages and stages of disease progression. The data collected includes demographics, medical history, medications, neurological and functional assessments, cardiac examinations, laboratory studies, and health questionnaires. The study will assess and evaluate clinical outcomes in individuals with FA, such as disease progression, symptom severity, and overall quality of life, by various factors that might influence such outcomes such as genetic mutation, demographics (age, geography), co-existing conditions, medications, or treatments. By tracking outcomes over time, researchers aim to discern patterns, trends, and potential variations in subgroups or in the effectiveness of therapies or interventions across a diverse group of participants. The UNIFAI study aims to play a pivotal role in identifying clinical milestones and changes in natural history over time as new treatments emerge. The study will monitor how these interventions alter the trajectory of the disease, potentially leading to the identification of crucial tipping points, disease landmarks, or stages where interventions can be most impactful. This study has the potential to significantly improve our understanding of FA and lead to more effective treatments and improved outcomes for those living with FA. The study aims to inform clinical trial design and the development and validation of novel clinical outcome assessments and biomarkers that can be used in clinical trials. The UNIFAI study aims to capture data from a wide and diverse cohort of individuals with FA so that this dataset can be used to inform the selection of inclusion and exclusion criteria and power calculations for trial designs with specific clinical outcome measures.