Frontometaphyseal dysplasia is an X-linked trait primarily characterized by a skeletal dysplasia comprising hyperostosis of the skull and modeling anomalies of the tubular bones. Extraskeletal features include tracheobronchial, cardiac, and urological malformations. A proportion of individuals have missense mutations or small deletions in the X-linked gene, FLNA. We report here our experience with comprehensive screening of the FLNA gene in a group of 23 unrelated probands (11 familial instances, 12 simplex cases; total affected individuals 32) with FMD. We found missense mutations leading to substitutions in the actin-binding domain and within filamin repeats 9, 10, 14, 16, 22, and 23 of filamin A in 13/23 (57%) of individuals in this cohort. Some mutations present with a male phenotype that is characterized by a severe skeletal dysplasia, cardiac, and genitourinary malformations that leads to perinatal death. Although no phenotypic feature consistently discriminates between females with FMD who are heterozygous for FLNA mutations and those in whom no FLNA mutation can be identified, there is a difference in the degree of skewing of X-inactivation between these two groups. This observation suggests that locus heterogeneity may exist for this disorder.

The purpose of this study was to determine if a donor age effect exists for the frequency of aneuploidy and other chromosome abnormalities in human spermatozoa. Sperm samples were collected from 18 healthy men from the general population. Each individual belonged to one of six age groups (20-24, 25-29, 30-34, 35-39, 40-44, > or = 45 years) with three men in each group. Two multicolour fluorescence in-situ hybridizations were performed on spermatozoa from each donor using probes for chromosomes 13 and 21, and two chromosome 1-specific probes allowed for detection of duplications and deletions as well as disomy of chromosome 1. The abnormality frequencies and the Pearson correlation coefficients were calculated to determine if a relationship existed between donor age and the frequency of chromosome abnormalities in spermatozoa. A statistically significant association with donor age was detected for the frequency of acentric fragments of chromosome 1 (P < 0.05).

Purpose Deep 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. Methods We 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. Results Unrelated, 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. Conclusion Deep 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.