Identification of the minimal combination of clinical features in probands for efficient mutation detection in the FBN1 gene

Abstract

Mutations identified in the fibrillin-1 (FBN1) gene have been associated with Marfan syndrome (MFS). Molecular analysis of the gene is classically performed in probands with MFS to offer diagnosis for at-risk relatives and in children highly suspected of MFS. However, FBN1 gene mutations are found in an ill-defined group of diseases termed 'type I fibrillinopathies', which are associated with an increased risk of aortic dilatation and dissection. Thus, there is growing awareness of the need to identify these non-MFS probands, for which FBN1 gene screening should be performed. To answer this need we compiled the molecular data obtained from the screening of the FBN1 gene in 586 probands, which had been addressed to our laboratory for molecular diagnosis. In this group, the efficacy of FBN1 gene screening was high in classical MFS probands (72.5%,), low (58%) in those referred for incomplete MFS and only slight (14.3%) for patients referred as possible MFS. Using recursive partitioning, we found that the best predictor of the identification of a mutation in the FBN1 gene was the presence of features in at least three organ systems, combining one major, and various minor criteria. We also show that our original recommendation of two systems involved with at least one with major criterion represents the minimal criteria because in probands not meeting these criteria, the yield of mutation identification drastically falls. This recommendation should help clinicians and biologists in identifying probands with a high probability of carrying a FBN1 gene mutation, and thus optimize biological resources.

Figure 1

Regression tree for incomplete MFS probands.