Matthews Harold, Vanneste Michiel, Katsura Kaitlin, Aponte David, Patton Michael, Hammond Peter, Baynam Gareth, Spritz Richard, Klein Ophir D, Hallgrimsson Benedikt, Peeters Hilde, Claes Peter
Department of Human Genetics, KU Leuven, Leuven, Flemish Brabant, Belgium.
Medical Imaging Research Center, UZ Leuven, Leuven, Flemish Brabant, Belgium.
J Med Genet. 2022 Jul 20. doi: 10.1136/jmedgenet-2021-108366.
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).
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.
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.
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.
在临床遗传学中，建立准确的疾病分类学需要分析病因和由此产生的表型变异。在表型水平上，识别典型的面部形态长期以来一直有助于临床和分子诊断；然而，对面部表型变异的客观分析仍不完善。在这项研究中，我们提出了探索性策略，用于评估临床和分子疾病实体内部和之间的面部表型变异，并将这些技术应用于四种RAS病的横断面样本：科斯特洛综合征（CS）、努南综合征（NS）、心脏颜面皮肤综合征（CFC）和1型神经纤维瘤病（NF1）。
通过三维密集表面扫描，我们将四种RAS病的典型表型建模为平均“面部特征”，并从方向（面部哪些部位受到影响以及如何受影响）和面部影响的严重程度方面评估个体变异。我们还得出了综合征之间表型一致性的指标以及沿相似表型严重程度差异的指标。
就方向和严重程度而言，CFC表现出相对一致的面部表型，与CS和NS相似，这与基于面部区分CFC和NS的已知困难相一致。CS表现出一致的方向性表型，严重程度有所不同。虽然NF1高度可变，但平均而言，它表现出与CS相似的表型。
我们建立了一种方法，未来可用于量化临床和分子诊断之间以及内部面部表型的变异，以客观地定义和支持临床疾病分类学。
