Friedreich’s ataxia transcriptomic dysregulation and identification of cell type-specific biomarkers: A systematic review and meta-analysis

Friedreich’s ataxia (FRDA) is a progressive neurodegenerative disease caused by a guanine-adenine-adenine (GAA) trinucleotide repeat expansion within the first intron of the FXN gene. The GAA expansion in FRDA induces a transcriptionally repressive state that reduces expression of the protein product Frataxin. Despite Frataxin's ubiquitous expression, the dorsal root ganglia sensory neurons (SNs) are particularly affected, causing sensory/proprioceptive loss, while lower motor neurons (LMNs) are largely spared in FA. The basis for this cell-type specific selective vulnerability remains a central unanswered question in FRDA pathophysiology. Here we generated induced pluripotent stem cell derived sensory neurons, lower motor neurons and neural crest cells from FRDA and isogenic corrected control cell lines. These were profiled using bulk RNA sequencing and used in the systematic review and meta-analysis of all human bulk RNA-seq datasets derived from FRDA and control samples. Our group performed a systematic review and meta-analysis of human bulk RNA-sequencing datasets in FRDA, reprocessing all studies through a unified analysis pipeline to enable direct cross-study comparison. We analysed 23 independent datasets comprising 94 FRDA and 99 control samples across 10 distinct cell types, spanning both disease-relevant (cardiomyocytes, sensory neurons) and unaffected cell types (fibroblasts, lymphocytes) of FRDA. This integrative approach allowed us to identify transcriptional changes that are consistently associated with FRDA across studies, while simultaneously delineating those that are cell-type specific. We have identified a panel of robust biomarkers of FRDA that would be useful readouts in in vitro drug screens, in clinical trials, as well as generating hypothesis as to how these biomarkers relate to the pathophysiological mechanisms of FRDA. All biomarkers, datasets and results can also be explored through the open-access FRDA Transcriptomic Atlas (https://marniemaddock.github.io/FRDATranscriptomicAtlas/).