Returning Integrated Genomic Risk and Clinical Recommendations: The eMERGE Study

The potential of artificial intelligence (AI) to reduce health care disparities and inequities is recognized, but it can also exacerbate these issues if not implemented in an equitable manner. This perspective identifies potential biases in each stage of the AI life cycle, including data collection, annotation, machine learning model development, evaluation, deployment, operationalization, monitoring, and feedback integration. To mitigate these biases, we suggest involving a diverse group of stakeholders, using human-centered AI principles. Human-centered AI can help ensure that AI systems are designed and used in a way that benefits patients and society, which can reduce health disparities and inequities. By recognizing and addressing biases at each stage of the AI life cycle, AI can achieve its potential in health car

Dominant-negative variant in SLC1A4 causes an autosomal dominant epilepsy syndrome.

SLC1A4 is a trimeric neutral amino acid transporter essential for shuttling L-serine from astrocytes into neurons. Individuals with biallelic variants in SLC1A4 are known to have spastic tetraplegia, thin corpus callosum, and progressive microcephaly (SPATCCM) syndrome, but individuals with heterozygous variants are not thought to have disease. We identify an 8-year-old patient with global developmental delay, spasticity, epilepsy, and microcephaly who has a de novo heterozygous three amino acid duplication in SLC1A4 (L86_M88dup). We demonstrate that L86_M88dup causes a dominant-negative N-glycosylation defect of SLC1A4, which in turn reduces the plasma membrane localization of SLC1A4 and the transport rate of SLC1A4 for L-serine

HNRNPC haploinsufficiency affects alternative splicing of intellectual disability-associated genes and causes a neurodevelopmental disorder

Heterogeneous nuclear ribonucleoprotein C (HNRNPC) is an essential, ubiquitously abundant protein involved in mRNA processing. Genetic variants in other members of the HNRNP family have been associated with neurodevelopmental disorders. Here, we describe 13 individuals with global developmental delay, intellectual disability, behavioral abnormalities, and subtle facial dysmorphology with heterozygous HNRNPC germline variants. Five of them bear an identical in-frame deletion of nine amino acids in the extreme C terminus. To study the effect of this recurrent variant as well as HNRNPC haploinsufficiency, we used induced pluripotent stem cells (iPSCs) and fibroblasts obtained from affected individuals. While protein localization and oligomerization were unaffected by the recurrent C-terminal deletion variant, total HNRNPC levels were decreased. Previously, reduced HNRNPC levels have been associated with changes in alternative splicing. Therefore, we performed a meta-analysis on published RNA-seq datasets of three different cell lines to identify a ubiquitous HNRNPC-dependent signature of alternative spliced exons. The identified signature was not only confirmed in fibroblasts obtained from an affected individual but also showed a significant enrichment for genes associated with intellectual disability. Hence, we assessed the effect of decreased and increased levels of HNRNPC on neuronal arborization and neuronal migration and found that either condition affects neuronal function. Taken together, our data indicate that HNRNPC haploinsufficiency affects alternative splicing of multiple intellectual disability-associated genes and that the developing brain is sensitive to aberrant levels of HNRNPC. Hence, our data strongly support the inclusion of HNRNPC to the family of HNRNP-related neurodevelopmental disorders. [Display omitted] We identified genetic variants of HNRNPC in 13 individuals with intellectual disability and global developmental delay. Through a meta-analysis of multiple cell types, we found that loss of HNRNPC affects alternative splicing, in particular of intellectual disability-associated genes. In vivo assays confirmed that neurodevelopment was affected by aberrant HNRNPC levels