A Comprehensive Microarray Analysis of Downregulation of Three Immune-Specific Core Genes and Regulatory Pathways in Children and Adults with Friedreich's Ataxia

Friedreich's Ataxia (FRDA) is a hereditary illness for which there is no treatment. As a result, new biomarkers and essential mechanisms connected to FRDA advancement must be discovered as soon as possible. Friedreich's Ataxia (FRDA) is a genetic spinal cord and cerebellar condition caused mostly by homozygous repetitive amplification of the Guanine-Adenine-Adenine (GAA) triplet in the frataxin gene. The expression level of functional Frataxin decreases as a result of repeat amplification and mutation. Frataxin deficiency can cause mitochondrial dysregulation by promoting the activation of oxidative stress and ferroptosis. Initial symptoms in children frequently include a loss of balance and increasing ataxia. Patients may develop dysarthria and loss of tendon reflex as the condition progresses, and in many cases, this is followed by myocardial infarction and diabetes. There is currently no effective therapy for preventing FRDA progression, with the majority of treatments being symptomatic. As a result, a greater understanding of the underlying pathophysiology and the development of more effective treatment techniques is critical. Some serum biomarkers have recently been identified as possible essential signatures in the aetiology of FRDA. The levels of neurofilament light and heavy chains, for example, are markedly elevated in Friedreich's ataxia patients and decline with age. Furthermore, serum hsTnT, NTproBNP, and miRNAs have been linked to the advancement of cardiomyopathy in adult FRDA patients. However, the clinical use of these biomarkers has yet to be proven in prospective cohorts, and the clinical association between them is poorly understood. Furthermore, these biomarkers have yet to be employed in FRDA clinical diagnosis. As a result, identifying additional biomarkers could provide crucial information on FRDA diagnosis and treatment. Bioinformatics analysis is currently being used to find critical biomarkers closely connected to disease prognosis in a range of disorders, including cancer, cardiac disease, and neurodegenerative disease. Furthermore, competitive endogenous RNA (ceRNA) networks will aid in the understanding of the novel mechanism of transcriptional regulatory networks in disease progression.