Phenotypic spectrum and genomics of undiagnosed arthrogryposis multiplex congenita

Annie Laquerriere, Dana Jaber, Emanuela Abiusi, Jérome Maluenda, Dan Mejlachowicz, Alexandre Vivanti, Klaus Dieterich, Radka Stoeva, Loic Quevarec, Flora Nolent, Valerie Biancalana, Philippe Latour (+79 others)
2021 Journal of Medical Genetics  
BackgroundArthrogryposis multiplex congenita (AMC) is characterised by congenital joint contractures in two or more body areas. AMC exhibits wide phenotypic and genetic heterogeneity. Our goals were to improve the genetic diagnosis rates of AMC, to evaluate the added value of whole exome sequencing (WES) compared with targeted exome sequencing (TES) and to identify new genes in 315 unrelated undiagnosed AMC families.MethodsSeveral genomic approaches were used including genetic mapping of
more » ... c mapping of disease loci in multiplex or consanguineous families, TES then WES. Sanger sequencing was performed to identify or validate variants.ResultsWe achieved disease gene identification in 52.7% of AMC index patients including nine recently identified genes (CNTNAP1, MAGEL2, ADGRG6, ADCY6, GLDN, LGI4, LMOD3, UNC50 and SCN1A). Moreover, we identified pathogenic variants in ASXL3 and STAC3 expanding the phenotypes associated with these genes. The most frequent cause of AMC was a primary involvement of skeletal muscle (40%) followed by brain (22%). The most frequent mode of inheritance is autosomal recessive (66.3% of patients). In sporadic patients born to non-consanguineous parents (n=60), de novo dominant autosomal or X linked variants were observed in 30 of them (50%).ConclusionNew genes recently identified in AMC represent 21% of causing genes in our cohort. A high proportion of de novo variants were observed indicating that this mechanism plays a prominent part in this developmental disease. Our data showed the added value of WES when compared with TES due to the larger clinical spectrum of some disease genes than initially described and the identification of novel genes.
doi:10.1136/jmedgenet-2020-107595 pmid:33820833 fatcat:yprvlrekbbfjpmopj2db7o6ef4