TGDS pathogenic variants cause Catel-Manzke syndrome without hyperphalangy

Catel-Manzke syndrome, also known as micrognathia-digital-syndrome, is a rare autosomal recessive disorder characterized by the combination of the two cardinal features Pierre-Robin sequence and bilateral hyperphalangy leading to ulnar clinodactyly (ulnar curvature of the phalanges) and radial deviation (radial angulation at the metacarpophalangeal joint) of the index finge

PEDIA: prioritization of exome data by image analysis.

PURPOSE: Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists. METHODS: Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds. RESULTS: The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20-89% and the top 10 accuracy rate by more than 5-99% for the disease-causing gene. CONCLUSION: Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis

Effective diagnosis of genetic disease by computational phenotype analysis of the disease-associated genome

Less than half of patients with suspected genetic disease receive a molecular diagnosis. We have therefore integrated next-generation sequencing (NGS), bioinformatics, and clinical data into an effective diagnostic work-flow. We used variants in the 2741 established Mendelian disease genes [the disease-associated genome (DAG)] to develop a targeted enrichment DAG panel (7.1 Mb), which achieves a coverage of 20-fold or better for 98% of bases. Furthermore, we established a computational method [Phenotypic Interpretation of eXomes (PhenIX)] that evaluated and ranked variants based on pathogenicity and semantic similarity of patients' phenotype described by Human Phenotype Ontology (HPO) terms to those of 3991 Mendelian diseases. In computer simulations, ranking genes based on the variant score put the true gene in first place less than 5% of the time; PhenIX placed the correct gene in first place more than 86% of the time. In a retrospective test of PhenIX on 52 patients with previously identified mutations and known diagnoses, the correct gene achieved a mean rank of 2.1. In a prospective study on 40 individuals without a diagnosis, PhenIX analysis enabled a diagnosis in 11 cases (28%, at a mean rank of 2.4). Thus, the NGS of the DAG followed by phenotype-driven bioinformatic analysis allows quick and effective differential diagnostics in medical genetics

Variants in the SK2 channel gene (KCNN2) lead to dominant neurodevelopmental movement disorders

KCNN2 encodes the small conductance calcium-activated potassium channel 2 (SK2). Rodent models with spontaneous Kcnn2 mutations show abnormal gait and locomotor activity, tremor and memory deficits, but human disorders related to KCNN2 variants are largely unknown. Using exome sequencing, we identified a de novo KCNN2 frameshift deletion in a patient with learning disabilities, cerebellar ataxia and white matter abnormalities on brain MRI. This discovery prompted us to collect data from nine additional patients with de novo KCNN2 variants (one nonsense, one splice site, six missense variants and one in-frame deletion) and one family with a missense variant inherited from the affected mother. We investigated the functional impact of six selected variants on SK2 channel function using the patch-clamp technique. All variants tested but one, which was reclassified to uncertain significance, led to a loss-of-function of SK2 channels. Patients with KCNN2 variants had motor and language developmental delay, intellectual disability often associated with early-onset movement disorders comprising cerebellar ataxia and/or extrapyramidal symptoms. Altogether, our findings provide evidence that heterozygous variants, likely causing a haploinsufficiency of the KCNN2 gene, lead to novel autosomal dominant neurodevelopmental movement disorders mirroring phenotypes previously described in rodents

Regulatory variants of FOXG1 in the context of its topological domain organisation

FOXG1 syndrome is caused by FOXG1 intragenic point mutations, or by long-range position effects (LRPE) of intergenic structural variants. However, the size of the FOXG1 regulatory landscape is uncertain, because the associated topologically associating domain (TAD) in fibroblasts is split into two domains in embryonic stem cells (hESC). Indeed, it has been suggested that the pathogenetic mechanism of deletions that remove the stem-cell-specific TAD boundary may be enhancer adoption due to ectopic activity of enhancer(s) located in the distal hESC-TAD. Herein we map three de novo translocation breakpoints to the proximal regulatory domain of FOXG1. The classical FOXG1 syndrome in these and in other translocation patients, and in a patient with an intergenic deletion that removes the hESC-specific TAD boundary, do not support the hypothesised enhancer adoption as a main contributor to the FOXG1 syndrome. Also, virtual 4 C and HiC-interaction data suggest that the hESC-specific TAD boundary may not be critical for FOXG1 regulation in a majority of human cells and tissues, including brain tissues and a neuronal progenitor cell line. Our data support the importance of a critical regulatory region (SRO) proximal to the hESC-specific TAD boundary. We further narrow this critical region by a deletion distal to the hESC-specific boundary, associated with a milder clinical phenotype. The distance from FOXG1 to the SRO ( > 500 kb) highlight a limitation of ENCODE DNase hypersensitivity data for functional prediction of LRPE. Moreover, the SRO has little overlap with a cluster of frequently associating regions (FIREs) located in the proximal hESC-TAD