Pathogenic variants in TNRC6B cause a genetic disorder characterised by developmental delay/intellectual disability and a spectrum of neurobehavioural phenotypes including autism and ADHD.

BACKGROUND: Rare variants in hundreds of genes have been implicated in developmental delay (DD), intellectual disability (ID) and neurobehavioural phenotypes. TNRC6B encodes a protein important for RNA silencing. Heterozygous truncating variants have been reported in three patients from large cohorts with autism, but no full phenotypic characterisation was described. METHODS: Clinical and molecular characterisation was performed on 17 patients with TNRC6B variants. Clinical data were obtained by retrospective chart review, parent interviews, direct patient interaction with providers and formal neuropsychological evaluation. RESULTS: Clinical findings included DD/ID (17/17) (speech delay in 94% (16/17), fine motor delay in 82% (14/17) and gross motor delay in 71% (12/17) of subjects), autism or autistic traits (13/17), attention deficit and hyperactivity disorder (ADHD) (11/17), other behavioural problems (7/17) and musculoskeletal findings (12/17). Other congenital malformations or clinical findings were occasionally documented. The majority of patients exhibited some dysmorphic features but no recognisable gestalt was identified. 17 heterozygous TNRC6B variants were identified in 12 male and five female unrelated subjects by exome sequencing (14), a targeted panel (2) and a chromosomal microarray (1). The variants were nonsense (7), frameshift (5), splice site (2), intragenic deletions (2) and missense (1). CONCLUSIONS: Variants in TNRC6B cause a novel genetic disorder characterised by recurrent neurocognitive and behavioural phenotypes featuring DD/ID, autism, ADHD and other behavioural abnormalities. Our data highly suggest that haploinsufficiency is the most likely pathogenic mechanism. TNRC6B should be added to the growing list of genes of the RNA-induced silencing complex associated with ID/DD, autism and ADHD.

Evaluation and classification of severity for 176 genes on an expanded carrier screening panel.

BACKGROUND: Disease severity is important when considering genes for inclusion on reproductive expanded carrier screening (ECS) panels. We applied a validated and previously published algorithm that classifies diseases into four severity categories (mild, moderate, severe, and profound) to 176 genes screened by ECS. Disease traits defining severity categories in the algorithm were then mapped to four severity-related ECS panel design criteria cited by the American College of Obstetricians and Gynecologists (ACOG). METHODS: Eight genetic counselors (GCs) and four medical geneticists (MDs) applied the severity algorithm to subsets of 176 genes. MDs and GCs then determined by group consensus how each of these disease traits mapped to ACOG severity criteria, enabling determination of the number of ACOG severity criteria met by each gene. RESULTS: Upon consensus GC and MD application of the severity algorithm, 68 (39%) genes were classified as profound, 71 (40%) as severe, 36 (20%) as moderate, and one (1%) as mild. After mapping of disease traits to ACOG severity criteria, 170 out of 176 genes (96.6%) were found to meet at least one of the four criteria, 129 genes (73.3%) met at least two, 73 genes (41.5%) met at least three, and 17 genes (9.7%) met all four. CONCLUSION: This study classified the severity of a large set of Mendelian genes by collaborative clinical expert application of a trait-based algorithm. Further, it operationalized difficult to interpret ACOG severity criteria via mapping of disease traits, thereby promoting consistency of ACOG criteria interpretation.

Phenotype of CM-AVM2 caused by variants in EPHB4: how much overlap with hereditary hemorrhagic telangiectasia (HHT)?

PURPOSE: EPHB4 variants were recently reported to cause capillary malformation-arteriovenous malformation 2 (CM-AVM2). CM-AVM2 mimics RASA1-related CM-AVM1 and hereditary hemorrhagic telangiectasia (HHT), as clinical features include capillary malformations (CMs), telangiectasia, and arteriovenous malformations (AVMs). Epistaxis, another clinical feature that overlaps with HHT, was reported in several cases. Based on the clinical overlap of CM-AVM2 and HHT, we hypothesized that patients considered clinically suspicious for HHT with no variant detected in an HHT gene (ENG, ACVRL1, or SMAD4) may have an EPHB4 variant. METHODS: Exome sequencing or a next-generation sequencing panel including EPHB4 was performed on individuals with previously negative molecular genetic testing for the HHT genes and/or RASA1. RESULTS: An EPHB4 variant was identified in ten unrelated cases. Seven cases had a pathogenic EPHB4 variant, including one with mosaicism. Three cases had an EPHB4 variant of uncertain significance. The majority had epistaxis (6/10 cases) and telangiectasia (8/10 cases), as well as CMs. Two of ten cases had a central nervous system AVM. CONCLUSIONS: Our results emphasize the importance of considering CM-AVM2 as part of the clinical differential for HHT and other vascular malformation syndromes. Yet, these cases highlight significant differences in the cutaneous presentations of CM-AVM2 versus HHT.

Further delineation of Aymé-Gripp syndrome and use of automated facial analysis tool.

Aymé-Gripp syndrome (AGS) is an autosomal dominant multisystem disorder caused by specific heterozygous variants in MAF. The resulting aberrant protein shows impaired GSK-mediated MAF phosphorylation. AGS is characterized by congenital cataracts, sensorineural hearing loss, short stature, intellectual disability, and distinctive facial features with brachycephaly. Cardiac and joint phenotypes are present in nearly half of patients. We review information on 10 published individuals with MAF mutations and clinical AGS and describe five additional patients, including three with novel mutations. Joint problems, typically including radioulnar synostosis and joint limitations, were present in 9/15 patients. Hip replacement in young adulthood was needed in four patients. Pericarditis occurred in 6/15 individuals. An automated facial analysis of 2D photos was used to compare the facial phenotype of 13 individuals from the literature or reported here, with facial photos of a control cohort of unaffected individuals and a cohort of Down syndrome patients. A multiclass approach yielded an accuracy of 86.86% and 89.05%, respectively, in two independent experiments compared to a random chance of 37.74%. In binary comparisons of AGS and Down syndrome, the area under the curve (AUC) was 0.994 (P < .001) and 1.0 (P < .001), respectively. Binary comparisons of AGS and unaffected controls yielded AUC of 0.994 (P < .001) and 0.989 (P = .003), respectively, suggesting that the facial phenotype of AGS could clearly be distinguished from unaffected individuals and from Down syndrome patients. Automated facial analysis may be helpful in the identification and evaluation of individuals suspected to have AGS.