Abstract：
Recognizing Mendelian causes is crucial in molecular diagnostics and counseling for patients with autism spectrum disorder (ASD). We explored facial dysmorphism and facial asymmetry in relation to genetic causes in ASD patients and studied the potential of objective facial phenotyping in discriminating between Mendelian and multifactorial ASD. In a cohort of 152 ASD patients, 3D facial images were used to calculate three metrics: a computational dysmorphism score, a computational asymmetry score, and an expert dysmorphism score. High scores for each of the three metrics were associated with Mendelian causes of ASD. The computational dysmorphism score showed a significant correlation with the average expert dysmorphism score. However, in some patients, different dysmorphism aspects were captured making the metrics potentially complementary. The computational dysmorphism and asymmetry scores both enhanced the individual expert dysmorphism scores in differentiating Mendelian from non-Mendelian cases. Furthermore, the computational asymmetry score enhanced the average expert opinion in predicting a Mendelian cause. By design, our study does not allow to draw conclusions on the actual point-of-care use of 3D facial analysis. Nevertheless, 3D morphometric analysis is promising for developing clinical dysmorphology applications in diagnostics and training.
摘要：
认识到孟德尔原因对于自闭症谱系障碍（ASD）患者的分子诊断和咨询至关重要。我们探索了ASD患者的面部畸形和面部不对称与遗传原因的关系，并研究了客观面部表型在区分孟德尔和多因素ASD中的潜力。在152名ASD患者的队列中，3D面部图像用于计算三个指标：计算畸形得分，计算不对称分数，和专家的畸形得分。三个指标中的每个指标的高分与ASD的孟德尔病因相关。计算畸形得分与平均专家畸形得分显着相关。然而,在一些患者中，捕获了不同的异形方面，使指标具有潜在的互补性。在区分孟德尔与非孟德尔病例方面，计算异形性和不对称性得分均增强了个别专家的异形性得分。此外，计算不对称分数提高了预测孟德尔病因的平均专家意见。根据设计，我们的研究不允许就3D面部分析的实际护理使用得出结论.然而，3D形态学分析有望在诊断和培训中开发临床形态学应用。
