In vitro screening model for compound interactions with human and dairy animal BCRP orthologs.

Orthologs of breast cancer resistance protein (BCRP/ABCG2), an ATP-binding cassette (ABC) efflux transmembrane transporter, are present in several species. The list of compounds known to interact with BCRP is growing, and many questions remain concerning species-specific variations in substrate specificity and affinity and the potency of inhibitors. As the most abundant efflux transporter known to be present in the blood-milk barrier, BCRP can increase the elimination of certain xenobiotics to milk, posing a risk for suckling offspring and dairy product consumers. Here we developed a model that can be employed to investigate species-specific differences between BCRP substrates and inhibitors. Membrane vesicles were isolated from transiently transduced human embryonic kidney (HEK) 293 cells, overexpressing BCRP, with human, bovine, caprine, and ovine cDNA sequences. To confirm BCRP transport activity in the transduced cells, D-luciferin efflux was measured and to confirm transport activity in the membrane vesicles, [3H] estrone-3-sulfate ([3H]E1S) influx was measured. We also determined the Michaelis-Menten constant (Km) and Vmax of [3H]E1S for each species. We have developed an in vitro transport model to study differences in compound interactions with BCRP orthologs from milk-producing animal species and humans. BCRP transport activity was demonstrated in the species-specific transduced cells by a reduced accumulation of D-luciferin compared with the control cells, indicating BCRP-mediated efflux of D-luciferin. Functionality of the membrane vesicle model was demonstrated by confirming ATP-dependent transport and by quantifying the kinetic parameters, Km and Vmax for the model substrate [3H]E1S. The values were not significantly different between species for the model substrates tested. This model can be insightful for appropriate inter-species extrapolations and risk assessments of xenobiotics in lactating woman and dairy animals.

PhenoScore quantifies phenotypic variation for rare genetic diseases by combining facial analysis with other clinical features using a machine-learning framework.

Several molecular and phenotypic algorithms exist that establish genotype-phenotype correlations, including facial recognition tools. However, no unified framework that investigates both facial data and other phenotypic data directly from individuals exists. We developed PhenoScore: an open-source, artificial intelligence-based phenomics framework, combining facial recognition technology with Human Phenotype Ontology data analysis to quantify phenotypic similarity. Here we show PhenoScore's ability to recognize distinct phenotypic entities by establishing recognizable phenotypes for 37 of 40 investigated syndromes against clinical features observed in individuals with other neurodevelopmental disorders and show it is an improvement on existing approaches. PhenoScore provides predictions for individuals with variants of unknown significance and enables sophisticated genotype-phenotype studies by testing hypotheses on possible phenotypic (sub)groups. PhenoScore confirmed previously known phenotypic subgroups caused by variants in the same gene for SATB1, SETBP1 and DEAF1 and provides objective clinical evidence for two distinct ADNP-related phenotypes, already established functionally.

Human disease genes website series: An international, open and dynamic library for up-to-date clinical information.

Since the introduction of next-generation sequencing, an increasing number of disorders have been discovered to have genetic etiology. To address diverse clinical questions and coordinate research activities that arise with the identification of these rare disorders, we developed the Human Disease Genes website series (HDG website series): an international digital library that records detailed information on the clinical phenotype of novel genetic variants in the human genome (https://humandiseasegenes.info/). Each gene website is moderated by a dedicated team of clinicians and researchers, focused on specific genes, and provides up-to-date-including unpublished-clinical information. The HDG website series is expanding rapidly with 424 genes currently adopted by 325 moderators from across the globe. On average, a gene website has detailed phenotypic information of 14.4 patients. There are multiple examples of added value, one being the ARID1B gene website, which was recently utilized in research to collect clinical information of 81 new patients. Additionally, several gene websites have more data available than currently published in the literature. In conclusion, the HDG website series provides an easily accessible, open and up-to-date clinical data resource for patients with pathogenic variants of individual genes. This is a valuable resource not only for clinicians dealing with rare genetic disorders such as developmental delay and autism, but other professionals working in diagnostics and basic research. Since the HDG website series is a dynamic platform, its data also include the phenotype of yet unpublished patients curated by professionals providing higher quality clinical detail to improve management of these rare disorders.