Abstract
A large fraction of monogenic disorders causes craniofacial abnormalities with characteristic facial morphology. These disorders can be diagnosed more efficiently with the support of computer-aided next-generation phenotyping tools, such as DeepGestalt. These tools have learned to associate facial phenotypes with the underlying syndrome through training on thousands of patient photographs. However, this “supervised” approach means that diagnoses are only possible if the disorder was part of the training set. To improve recognition of ultra-rare disorders, we created GestaltMatcher, which uses a deep convolutional neural network based on the DeepGestalt framework. We used photographs of 17,560 patients with 1,115 rare disorders to define a “Clinical Face Phenotype Space”. Distance between cases in the phenotype space defines syndromic similarity, allowing test patients to be matched to a molecular diagnosis even when the disorder was not included in the training set. Similarities among patients with previously unknown disease genes can also be detected. Therefore, in concert with mutation data, GestaltMatcher could accelerate the clinical diagnosis of patients with ultra-rare disorders and facial dysmorphism, as well as enable the delineation of novel phenotypes.
Competing Interest Statement
The authors have declared no competing interest.
Funding Statement
This work was funded by the Deutsche Forschungsgemeinschaft.
Author Declarations
I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.
Yes
The details of the IRB/oversight body that provided approval or exemption for the research described are given below:
This study is governed by the following Institutional Review Board (IRB) approval: Charité Universitätsmedizin Berlin, Germany (EA2/190/16); UKB Universitätsklinikum Bonn, Germany (Lfd.Nr.386/17). The authors have obtained written informed consent given by the patients or their guardians, including permission to publish photographs.
All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.
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Data Availability
This work can be accessed by the gestaltmatcher.org.