Association of modifiers and other genetic factors explain Marfan syndrome clinical variability View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-12

AUTHORS

Melodie Aubart, Steven Gazal, Pauline Arnaud, Louise Benarroch, Marie-Sylvie Gross, Julien Buratti, Anne Boland, Vincent Meyer, Habib Zouali, Nadine Hanna, Olivier Milleron, Chantal Stheneur, Thomas Bourgeron, Isabelle Desguerre, Marie-Paule Jacob, Laurent Gouya, Emmanuelle Génin, Jean-François Deleuze, Guillaume Jondeau, Catherine Boileau

ABSTRACT

Marfan syndrome (MFS) is a rare autosomal dominant connective tissue disorder related to variants in the FBN1 gene. Prognosis is related to aortic risk of dissection following aneurysm. MFS clinical variability is notable, for age of onset as well as severity and number of clinical manifestations. To identify genetic modifiers, we combined genome-wide approaches in 1070 clinically well-characterized FBN1 disease-causing variant carriers: (1) an FBN1 eQTL analysis in 80 fibroblasts of FBN1 stop variant carriers, (2) a linkage analysis, (3) a kinship matrix association study in 14 clinically concordant and discordant sib-pairs, (4) a genome-wide association study and (5) a whole exome sequencing in 98 extreme phenotype samples.Three genetic mechanisms of variability were found. A new genotype/phenotype correlation with an excess of loss-of-cysteine variants (P = 0.004) in severely affected subjects. A second pathogenic event in another thoracic aortic aneurysm gene or the COL4A1 gene (known to be involved in cerebral aneurysm) was found in nine individuals. A polygenic model involving at least nine modifier loci (named gMod-M1-9) was observed through cross-mapping of results. Notably, gMod-M2 which co-localizes with PRKG1, in which activating variants have already been described in thoracic aortic aneurysm, and gMod-M3 co-localized with a metalloprotease (proteins of extra-cellular matrix regulation) cluster. Our results represent a major advance in understanding the complex genetic architecture of MFS and provide the first steps toward prediction of clinical evolution. More... »

PAGES

1759-1772

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41431-018-0164-9

DOI

http://dx.doi.org/10.1038/s41431-018-0164-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1106021440

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30087447


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