Abstract
PurposeDeep phenotyping is an emerging trend in precision medicine for genetic disease. The shape of the face is affected in 30–40% of known genetic syndromes. Here, we determine whether syndromes can be diagnosed from 3D images of human faces. MethodsWe analyzed variation in three-dimensional (3D) facial images of 7057 subjects: 3327 with 396 different syndromes, 727 of their relatives, and 3003 unrelated, unaffected subjects. We developed and tested machine learning and parametric approaches to automated syndrome diagnosis using 3D facial images. ResultsUnrelated, unaffected subjects were correctly classified with 96% accuracy. Considering both syndromic and unrelated, unaffected subjects together, balanced accuracy was 73% and mean sensitivity 49%. Excluding unrelated, unaffected subjects substantially improved both balanced accuracy (78.1%) and sensitivity (56.9%) of syndrome diagnosis. The best predictors of classification accuracy were phenotypic severity and facial distinctiveness of syndromes. Surprisingly, unaffected relatives of syndromic subjects were frequently classified as syndromic, often to the syndrome of their affected relative. ConclusionDeep phenotyping by quantitative 3D facial imaging has considerable potential to facilitate syndrome diagnosis. Furthermore, 3D facial imaging of “unaffected” relatives may identify unrecognized cases or may reveal novel examples of semidominant inheritance.
Highlights
Of >7000 rare syndromes in humans, 30–40% involve dysmorphic craniofacial features[1] and such features often contribute to initial clinical diagnoses
The analysis is based on a data freeze of 3327 subjects with 396 syndromes (File S1), 727 of their apparently unaffected relatives, and 3003 unrelated, unaffected individuals, including 2851 from the facial shape genome-wide association study (GWAS) cohort of Shaffer et al.[14] plus 152 enrolled through this project
When only the syndromic individuals were analyzed, syndrome diagnosis accounted for 14–15% of the total variation in facial shape, regardless of whether asymmetric facial variation was considered, and nearly 19% of the total variance when unrelated unaffected subjects were included (Table S4) (MANOVA, p < 0.001)
Summary
Of >7000 rare syndromes in humans, 30–40% involve dysmorphic craniofacial features[1] and such features often contribute to initial clinical diagnoses. Diagnoses enable affected individuals and their families to access resources, prognoses, and available treatments. Access to medical genetics remains limited, especially outside of the developed world. Expert systems have been deployed to assist syndrome diagnosis, including computer databases[2] and analytic software,[3] as well as human expert[4] and online services.[5] In parallel, diagnosis has been greatly facilitated by improvements to molecular diagnostic testing and sequencing.[6] testing is expensive and access remains limited outside high-income countries.[7] Even with sequencing, nearly 50% of all patients remain undiagnosed.[8]
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