Novel and Recurrent Copy Number Variants in ABCA4 -Associated Retinopathy.
Zelia CorradiClaire-Marie DhaenensOlivier GrunewaldIpek Selen KocabaşIsabelle MeunierFrancesca SimonelliMarianthi KaraliFrans P M CremersRebekkah J Hitti-MalinPublished in: International journal of molecular sciences (2024)
ABCA4 is the most frequently mutated gene leading to inherited retinal disease (IRD) with over 2200 pathogenic variants reported to date. Of these, ~1% are copy number variants (CNVs) involving the deletion or duplication of genomic regions, typically >50 nucleotides in length. An in-depth assessment of the current literature based on the public database LOVD, regarding the presence of known CNVs and structural variants in ABCA4 , and additional sequencing analysis of ABCA4 using single-molecule Molecular Inversion Probes (smMIPs) for 148 probands highlighted recurrent and novel CNVs associated with ABCA4 -associated retinopathies. An analysis of the coverage depth in the sequencing data led to the identification of eleven deletions (six novel and five recurrent), three duplications (one novel and two recurrent) and one complex CNV. Of particular interest was the identification of a complex defect, i.e., a 15.3 kb duplicated segment encompassing exon 31 through intron 41 that was inserted at the junction of a downstream 2.7 kb deletion encompassing intron 44 through intron 47. In addition, we identified a 7.0 kb tandem duplication of intron 1 in three cases. The identification of CNVs in ABCA4 can provide patients and their families with a genetic diagnosis whilst expanding our understanding of the complexity of diseases caused by ABCA4 variants.
Keyphrases
- copy number
- mitochondrial dna
- single molecule
- genome wide
- dna methylation
- optical coherence tomography
- end stage renal disease
- living cells
- healthcare
- newly diagnosed
- systematic review
- ejection fraction
- chronic kidney disease
- single cell
- diabetic retinopathy
- big data
- computed tomography
- small molecule
- emergency department
- deep learning
- magnetic resonance
- peritoneal dialysis
- machine learning
- patient reported outcomes
- fluorescent probe
- adverse drug
- fluorescence imaging