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Original research
Refining nosology by modelling variation among facial phenotypes: the RASopathies

Abstract

Background In clinical genetics, establishing an accurate nosology requires analysis of variations in both aetiology and the resulting phenotypes. At the phenotypic level, recognising typical facial gestalts has long supported clinical and molecular diagnosis; however, the objective analysis of facial phenotypic variation remains underdeveloped. In this work, we propose exploratory strategies for assessing facial phenotypic variation within and among clinical and molecular disease entities and deploy these techniques on cross-sectional samples of four RASopathies: Costello syndrome (CS), Noonan syndrome (NS), cardiofaciocutaneous syndrome (CFC) and neurofibromatosis type 1 (NF1).

Methods From three-dimensional dense surface scans, we model the typical phenotypes of the four RASopathies as average ‘facial signatures’ and assess individual variation in terms of direction (what parts of the face are affected and in what ways) and severity of the facial effects. We also derive a metric of phenotypic agreement between the syndromes and a metric of differences in severity along similar phenotypes.

Results CFC shows a relatively consistent facial phenotype in terms of both direction and severity that is similar to CS and NS, consistent with the known difficulty in discriminating CFC from NS based on the face. CS shows a consistent directional phenotype that varies in severity. Although NF1 is highly variable, on average, it shows a similar phenotype to CS.

Conclusions We established an approach that can be used in the future to quantify variations in facial phenotypes between and within clinical and molecular diagnoses to objectively define and support clinical nosologies.

  • Phenotype
  • Methods
  • Diagnosis

Data availability statement

Data are available in a public, open access repository. The data from the FaceBase repository (https://doi.org/10.25550/1WWC) are available to researchers pending an approved data access request. Data from other sources were collected without approval for broad data sharing and are not publicly available.

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