Pathogenic variants in multiple genes on the X chromosome have been implicated in syndromic and non-syndromic intellectual disability disorders. ZFX on Xp22.11 encodes a transcription factor that has been linked to diverse processes including oncogenesis and development, but germline variants have not been characterized in association with disease. Here, we present clinical and molecular characterization of 18 individuals with germline ZFX variants. Exome or genome sequencing revealed 11 variants in 18 subjects (14 males and 4 females) from 16 unrelated families. Four missense variants were identified in 11 subjects, with seven truncation variants in the remaining individuals. Clinical findings included developmental delay/intellectual disability, behavioral abnormalities, hypotonia, and congenital anomalies. Overlapping and recurrent facial features were identified in all subjects, including thickening and medial broadening of eyebrows, variations in the shape of the face, external eye abnormalities, smooth and/or long philtrum, and ear abnormalities. Hyperparathyroidism was found in four families with missense variants, and enrichment of different tumor types was observed. In molecular studies, DNA-binding domain variants elicited differential expression of a small set of target genes relative to wild-type ZFX in cultured cells, suggesting a gain or loss of transcriptional activity. Additionally, a zebrafish model of ZFX loss displayed an altered behavioral phenotype, providing additional evidence for the functional significance of ZFX. Our clinical and experimental data support that variants in ZFX are associated with an X-linked intellectual disability syndrome characterized by a recurrent facial gestalt, neurocognitive and behavioral abnormalities, and an increased risk for congenital anomalies and hyperparathyroidism.
Cornelia de Lange Syndrome (CdLS) is a rare, dominantly inherited multisystem developmental disorder characterized by highly variable manifestations of growth and developmental delays, upper limb involvement, hypertrichosis, cardiac, gastrointestinal, craniofacial, and other systemic features. Pathogenic variants in genes encoding cohesin complex structural subunits and regulatory proteins (NIPBL, SMC1A, SMC3, HDAC8, and RAD21) are the major pathogenic contributors to CdLS. Heterozygous or hemizygous variants in the genes encoding these five proteins have been found to be contributory to CdLS, with variants in NIPBL accounting for the majority (>60%) of cases, and the only gene identified to date that results in the severe or classic form of CdLS when mutated. Pathogenic variants in cohesin genes other than NIPBL tend to result in a less severe phenotype. Causative variants in additional genes, such as ANKRD11, EP300, AFF4, TAF1, and BRD4, can cause a CdLS-like phenotype. The common role that these genes, and others, play as critical regulators of developmental transcriptional control has led to the conditions they cause being referred to as disorders of transcriptional regulation (or "DTRs"). Here, we report the results of a comprehensive molecular analysis in a cohort of 716 probands with typical and atypical CdLS in order to delineate the genetic contribution of causative variants in cohesin complex genes as well as novel candidate genes, genotype-phenotype correlations, and the utility of genome sequencing in understanding the mutational landscape in this population.
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.
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.