Exome Sequencing Identifies Genetic Variants Associated with Extreme Manifestations of the Cardiovascular Phenotype in Marfan Syndrome

Genes (Basel). 2022 Jun 8;13(6):1027. doi: 10.3390/genes13061027.

Abstract

Marfan Syndrome (MFS) is an autosomal dominant condition caused by variants in the fibrillin-1 (FBN1) gene. Cardinal features of MFS include ectopia lentis (EL), musculoskeletal features and aortic root aneurysm and dissection. Although dissection of the ascending aorta is the main cause of mortality in MFS, the clinical course differs considerably in age of onset and severity, even among individuals who share the same causative variant, suggesting the existence of additional genetic variants that modify the severity of the cardiovascular phenotype in MFS. We recruited MFS patients and classified them into severe (n = 8) or mild aortic phenotype (n = 14) according to age of presentation of the first aorta-related incident. We used Exome Sequencing to identify the genetic variants associated with the severity of aortic manifestations and we performed linkage analysis where suitable. We found five genes associated with severe aortic phenotype and three genes that could be protective for this phenotype in MFS. These genes regulate components of the extracellular matrix, TGFβ pathway and other signaling pathways that are involved in the maintenance of the ECM or angiogenesis. Further studies will be required to understand the functional effect of these variants and explore novel, personalized risk management and, potentially, therapies for these patients.

Keywords: Marfan syndrome; aortic aneurysm; exome sequencing; genetic modifiers.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Exome / genetics
  • Fibrillin-1 / genetics
  • Humans
  • Marfan Syndrome* / genetics
  • Mutation
  • Phenotype

Substances

  • Fibrillin-1

Grants and funding

This research was funded by ANID Fondecyt Grant 11170353 (Y.J. and J.F.C.), ANID Fondecyt Grant 1171014 and 1211411 (G.M.R.), ANID Grant EQM190110 (J.F.C.) and ANID ACT Grant 210012 (J.F.C.). Computational analyses were done in Cluster SOFIA-UDD funded by Grant EQM150093.