NGS in Hereditary Ataxia: When Rare Becomes Frequent.
Daniele GalatoloGiovanna De MicheleGabriella SilvestriVincenzo LeuzziCarlo CasaliOlimpia MusumeciAntonella AntenoraGuja AstreaMelissa BarghigianiRoberta BattiniCarla BattistiCaterina CaputiEttore CioffiGiuseppe De MicheleMaria Teresa DottiTommasina FicoChiara FiorilloSerena GalosiMaria LietoAlessandro MalandriniMariarosa Anna Beatrice MeloneAndrea MignarriGemma NataleElena PegoraroAntonio PetrucciIvana RiccaVittorio RisoSalvatore RossiAnna RubegniArianna ScarlattiFrancesca TinelliRosanna TrovatoGioacchino TedeschiAlessandra TessaAlessandro FillaFilippo Maria SantorelliPublished in: International journal of molecular sciences (2021)
The term hereditary ataxia (HA) refers to a heterogeneous group of neurological disorders with multiple genetic etiologies and a wide spectrum of ataxia-dominated phenotypes. Massive gene analysis in next-generation sequencing has entered the HA scenario, broadening our genetic and clinical knowledge of these conditions. In this study, we employed a targeted resequencing panel (TRP) in a large and highly heterogeneous cohort of 377 patients with a clinical diagnosis of HA, but no molecular diagnosis on routine genetic tests. We obtained a positive result (genetic diagnosis) in 33.2% of the patients, a rate significantly higher than those reported in similar studies employing TRP (average 19.4%), and in line with those performed using exome sequencing (ES, average 34.6%). Moreover, 15.6% of the patients had an uncertain molecular diagnosis. STUB1, PRKCG, and SPG7 were the most common causative genes. A comparison with published literature data showed that our panel would have identified 97% of the positive cases reported in previous TRP-based studies and 92% of those diagnosed by ES. Proper use of multigene panels, when combined with detailed phenotypic data, seems to be even more efficient than ES in clinical practice.
Keyphrases
- genome wide
- copy number
- end stage renal disease
- clinical practice
- ejection fraction
- chronic kidney disease
- newly diagnosed
- healthcare
- prognostic factors
- randomized controlled trial
- dna methylation
- peritoneal dialysis
- systematic review
- electronic health record
- drug delivery
- patient reported outcomes
- preterm infants
- transcription factor
- big data
- single molecule
- cancer therapy
- data analysis
- single cell
- artificial intelligence
- genome wide identification
- subarachnoid hemorrhage