Capturing heart valve development with Gene Ontology.

Introduction: The normal development of all heart valves requires highly coordinated signaling pathways and downstream mediators. While genomic variants can be responsible for congenital valve disease, environmental factors can also play a role. Later in life valve calcification is a leading cause of aortic valve stenosis, a progressive disease that may lead to heart failure. Current research into the causes of both congenital valve diseases and valve calcification is using a variety of high-throughput methodologies, including transcriptomics, proteomics and genomics. High quality genetic data from biological knowledge bases are essential to facilitate analyses and interpretation of these high-throughput datasets. The Gene Ontology (GO, http://geneontology.org/) is a major bioinformatics resource used to interpret these datasets, as it provides structured, computable knowledge describing the role of gene products across all organisms. The UCL Functional Gene Annotation team focuses on GO annotation of human gene products. Having identified that the GO annotations included in transcriptomic, proteomic and genomic data did not provide sufficient descriptive information about heart valve development, we initiated a focused project to address this issue. Methods: This project prioritized 138 proteins for GO annotation, which led to the curation of 100 peer-reviewed articles and the creation of 400 heart valve development-relevant GO annotations. Results: While the focus of this project was heart valve development, around 600 of the 1000 annotations created described the broader cellular role of these proteins, including those describing aortic valve morphogenesis, BMP signaling and endocardial cushion development. Our functional enrichment analysis of the 28 proteins known to have a role in bicuspid aortic valve disease confirmed that this annotation project has led to an improved interpretation of a heart valve genetic dataset. Discussion: To address the needs of the heart valve research community this project has provided GO annotations to describe the specific roles of key proteins involved in heart valve development. The breadth of GO annotations created by this project will benefit many of those seeking to interpret a wide range of cardiovascular genomic, transcriptomic, proteomic and metabolomic datasets.

Digital Fellowships: Inspiring use of contemporary technologies in applied healthcare.

The adoption of digital technologies in healthcare, accelerated by the COVID-19 pandemic, requires a well-prepared workforce capable of implementing those technologies. Here, we examine the role and impact of digital fellowships in facilitating digital transformation in healthcare systems. Digital fellowships are structured educational programmes designed to equip healthcare professionals with advanced digital skills. Focusing on UK-based initiatives like the Topol Digital Fellowship and the Fellowship in Clinical AI, we explore their efforts to prepare healthcare leaders for digital and AI adoption. Each fellowship programme provides participants with hands-on experience in digital healthcare projects and fosters interdisciplinary collaboration and post-fellowship support. We discuss how these fellowships contribute to staff retention by diversifying professional experiences and opportunities. We call for increased collaborations between universities, industry, and professional bodies to integrate lessons from digital fellowships into relevant curricula, acknowledging that digital fellowships are just one piece of the puzzle in bridging the digital skills gap in the healthcare workforce.

SLC6A1 variant pathogenicity, molecular function and phenotype: a genetic and clinical analysis.

Genetic variants in the SLC6A1 gene can cause a broad phenotypic disease spectrum by altering the protein function. Thus, systematically curated clinically relevant genotype-phenotype associations are needed to understand the disease mechanism and improve therapeutic decision-making. We aggregated genetic and clinical data from 172 individuals with likely pathogenic/pathogenic (lp/p) SLC6A1 variants and functional data for 184 variants (14.1% lp/p). Clinical and functional data were available for a subset of 126 individuals. We explored the potential associations of variant positions on the GAT1 3D structure with variant pathogenicity, altered molecular function and phenotype severity using bioinformatic approaches. The GAT1 transmembrane domains 1, 6 and extracellular loop 4 (EL4) were enriched for patient over population variants. Across functionally tested missense variants (n = 156), the spatial proximity from the ligand was associated with loss-of-function in the GAT1 transporter activity. For variants with complete loss of in vitro GABA uptake, we found a 4.6-fold enrichment in patients having severe disease versus non-severe disease (P = 2.9 × 10-3, 95% confidence interval: 1.5-15.3). In summary, we delineated associations between the 3D structure and variant pathogenicity, variant function and phenotype in SLC6A1-related disorders. This knowledge supports biology-informed variant interpretation and research on GAT1 function. All our data can be interactively explored in the SLC6A1 portal (https://slc6a1-portal.broadinstitute.org/).

Personalized recurrence risk assessment following the birth of a child with a pathogenic de novo mutation.

Following the diagnosis of a paediatric disorder caused by an apparently de novo mutation, a recurrence risk of 1-2% is frequently quoted due to the possibility of parental germline mosaicism; but for any specific couple, this figure is usually incorrect. We present a systematic approach to providing individualized recurrence risk. By combining locus-specific sequencing of multiple tissues to detect occult mosaicism with long-read sequencing to determine the parent-of-origin of the mutation, we show that we can stratify the majority of couples into one of seven discrete categories associated with substantially different risks to future offspring. Among 58 families with a single affected offspring (representing 59 de novo mutations in 49 genes), the recurrence risk for 35 (59%) was decreased below 0.1%, but increased owing to parental mixed mosaicism for 5 (9%)-that could be quantified in semen for paternal cases (recurrence risks of 5.6-12.1%). Implementation of this strategy offers the prospect of driving a major transformation in the practice of genetic counselling.

Recurrent heterozygous PAX6 missense variants cause severe bilateral microphthalmia via predictable effects on DNA-protein interaction.

PURPOSE: Most classical aniridia is caused by PAX6 haploinsufficiency. PAX6 missense variants can be hypomorphic or mimic haploinsufficiency. We hypothesized that missense variants also cause previously undescribed disease by altering the affinity and/or specificity of PAX6 genomic interactions. METHODS: We screened PAX6 in 372 individuals with bilateral microphthalmia, anophthalmia, or coloboma (MAC) from the Medical Research Council Human Genetics Unit eye malformation cohort (HGUeye) and reviewed data from the Deciphering Developmental Disorders study. We performed cluster analysis on PAX6-associated ocular phenotypes by variant type and molecular modeling of the structural impact of 86 different PAX6 causative missense variants. RESULTS: Eight different PAX6 missense variants were identified in 17 individuals (15 families) with MAC, accounting for 4% (15/372) of our cohort. Seven altered the paired domain (p.[Arg26Gln]x1, p.[Gly36Val]x1, p.[Arg38Trp]x2, p.[Arg38Gln]x1, p.[Gly51Arg]x2, p.[Ser54Arg]x2, p.[Asn124Lys]x5) and one the homeodomain (p.[Asn260Tyr]x1). p.Ser54Arg and p.Asn124Lys were exclusively associated with severe bilateral microphthalmia. MAC-associated variants were predicted to alter but not ablate DNA interaction, consistent with the electrophoretic mobility shifts observed using mutant paired domains with well-characterized PAX6-binding sites. We found no strong evidence for novel PAX6-associated extraocular disease. CONCLUSION: Altering the affinity and specificity of PAX6-binding genome-wide provides a plausible mechanism for the worse-than-null effects of MAC-associated missense variants.

Exome sequencing can detect pathogenic mosaic mutations present at low allele frequencies.

The development of next generation sequencing (NGS) has radically transformed the scientific landscape, making it possible to sequence the exome of any given individual in a cost-effective way. The power of this approach has been demonstrated by a number of groups who have identified pathogenic mutations in small pedigrees that have been resistant to traditional genetic mapping. Recently it has become clear that exome sequencing has great potential with respect to sporadic disease and the identification of de novo mutations. This is highlighted by studies reporting whole-exome sequencing of patient-parental trios affected by learning disability, autism and schizophrenia. It is widely anticipated that the introduction of this technique into a clinical setting will revolutionise genetic diagnosis. However, the sensitivity of NGS exome sequencing is currently unclear. Here, we describe the exome sequencing of DNA samples from a patient with double cortex syndrome and her parents, resulting in the detection of a mosaic splicing mutation in LIS1. This variant was found at an allele frequency of just 18%, demonstrating that NGS methods have the capacity to identify pathogenic mosaic mutations present at a low level.