Conclusion of diagnostic odysseys due to inversions disrupting GLI3 and FBN1 .
Alistair T PagnamentaJing YuJulie EvansPhilip Twissnull nullnull nullAmaka C OffiahMohamed WafikSarju G MehtaMohammed K JavaidSarah F SmithsonJenny C TaylorPublished in: Journal of medical genetics (2022)
Many genetic testing methodologies are biased towards picking up structural variants (SVs) that alter copy number. Copy-neutral rearrangements such as inversions are therefore likely to suffer from underascertainment. In this study, manual review prompted by a virtual multidisciplinary team meeting and subsequent bioinformatic prioritisation of data from the 100K Genomes Project was performed across 43 genes linked to well-characterised skeletal disorders. Ten individuals from three independent families were found to harbour diagnostic inversions. In two families, inverted segments of 1.2/14.8 Mb unequivocally disrupted GLI3 and segregated with skeletal features consistent with Greig cephalopolysyndactyly syndrome. For one family, phenotypic blending was due to the opposing breakpoint lying ~45 kb from HOXA13 In the third family, long suspected to have Marfan syndrome, a 2.0 Mb inversion disrupting FBN1 was identified. These findings resolved lengthy diagnostic odysseys of 9-20 years and highlight the importance of direct interaction between clinicians and data-analysts. These exemplars of a rare mutational class inform future SV prioritisation strategies within the NHS Genomic Medicine Service and similar genome sequencing initiatives. In over 30 years since these two disease-gene associations were identified, large inversions have yet to be described and so our results extend the mutational spectra linked to these conditions.
Keyphrases
- copy number
- genome wide
- mitochondrial dna
- quality improvement
- dna methylation
- patient safety
- electronic health record
- palliative care
- healthcare
- mental health
- case report
- big data
- single cell
- pulmonary embolism
- gene expression
- magnetic resonance imaging
- current status
- magnetic resonance
- genome wide identification
- functional connectivity
- computed tomography
- artificial intelligence
- long noncoding rna