Elucidating the clinical and genetic spectrum of inositol polyphosphate phosphatase INPP4A-related neurodevelopmental disorder.

Purpose: Biallelic INPP4A variants have recently been associated with severe neurodevelopmental disease in single-case reports. Here, we expand and elucidate the clinical-genetic spectrum and provide a pathomechanistic explanation for genotype-phenotype correlations.

Methods: Clinical and genomic investigations of 30 individuals were undertaken alongside molecular and in silico modelling and translation reinitiation studies.

Clustering of predicted loss-of-function variants in genes linked with monogenic disease can explain incomplete penetrance.

Background: Genetic variants that severely alter protein products (e.g. nonsense, frameshift) are often associated with disease.

Development of a leakage impact assessment for patients with a stoma, who may be impacted by leakage.

For people living with a stoma leakage is unpredictable. Despite advances in stoma products, leakage can lead to soiling and this, along with worrying about leakage, can significantly affect patients' everyday lives and impact their quality of life. It is also associated with excessive product use and increased healthcare resources.

TECPR2-related hereditary sensory and autonomic neuropathy in two siblings from Palestine.

Due to the majority of currently available genome data deriving from individuals of European ancestry, the clinical interpretation of genomic variants in individuals from diverse ethnic backgrounds remains a major diagnostic challenge. Here, we investigated the genetic cause of a complex neurodevelopmental phenotype in two Palestinian siblings. Whole exome sequencing identified a homozygous missense TECPR2 variant (Chr14(GRCh38):g.

Evaluating the use of paralogous protein domains to increase data availability for missense variant classification.

Background: Classification of rare missense variants remains an ongoing challenge in genomic medicine. Evidence of pathogenicity is often sparse, and decisions about how to weigh different evidence classes may be subjective. We used a Bayesian variant classification framework to investigate the performance of variant co-localisation, missense constraint, and aggregating data across paralogous protein domains ("meta-domains").