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Background: Acromesomelic chondrodysplasias are a rare subgroup of the clinically and genetically heterogeneous osteochondrodysplasias that are characterised by abnormalities in the limb development and short stature. Here, we report a 2‐year‐old boy, offspring of consanguineous parents, with acromesomelic dysplasia and postaxial polydactyly in which exome sequencing identified a novel homozygous missense variant in BMPR1B. The patient showed skeletal malformation of both hands and feet that included complex brachydactyly with the thumbs most severely affected, postaxial polydactyly of both hands, shortened toes as well as a bilateral hypoplasia of the fibula. Methods: Whole trio exome sequencing was conducted to identify potential genetic variants in the patient. Results: The analysis identified the biallelic variant NM_001203.3:c.821A > G;p.(Gln274Arg) in BMPR1B, a gene encoding bone morphogenetic protein receptor 1B. Conclusion: The skeletal phenotype can be brought in line with the phenotypes of previously reported cases of BMPR1B‐associated chondrodysplasias. However, the postaxial polydactyly described here is a novel clinical finding in a BMPR1B‐related case; notably, it has previously been reported in other acromesomelic dysplasia cases caused by homozygous pathogenic variants in GDF5—a gene which encodes for growth differentiation factor 5, a high‐affinity ligand to BMPR1B. [ABSTRACT FROM AUTHOR]

The most important factor that complicates the work of dysmorphologists is the significant phenotypic variability of the human face. Next-Generation Phenotyping (NGP) tools that assist clinicians with recognizing characteristic syndromic patterns are particularly challenged when confronted with patients from populations different from their training data. To that end, we systematically analyzed the impact of genetic ancestry on facial dysmorphism. For that purpose, we established the GestaltMatcher Database (GMDB) as a reference dataset for medical images of patients with rare genetic disorders from around the world. We collected 10,980 frontal facial images - more than a quarter previously unpublished - from 8,346 patients, representing 581 rare disorders. Although the predominant ancestry is still European (67%), data from underrepresented populations have been increased considerably via global collaborations (19% Asian and 7% African). This includes previously unpublished reports for more than 40% of the African patients. The NGP analysis on this diverse dataset revealed characteristic performance differences depending on the composition of training and test sets corresponding to genetic relatedness. For clinical use of NGP, incorporating non-European patients resulted in a profound enhancement of GestaltMatcher performance. The top-5 accuracy rate increased by +11.29%. Importantly, this improvement in delineating the correct disorder from a facial portrait was achieved without decreasing the performance on European patients. By design, GMDB complies with the FAIR principles by rendering the curated medical data findable, accessible, interoperable, and reusable. This means GMDB can also serve as data for training and benchmarking. In summary, our study on facial dysmorphism on a global sample revealed a considerable cross ancestral phenotypic variability confounding NGP that should be counteracted by international efforts for increasing data diversity. GMDB will serve as a vital reference database for clinicians and a transparent training set for advancing NGP technology.