Multisystem inflammatory syndrome in children (MIS-C) evolves in some pediatric patients following acute infection with SARS-CoV-2 by hitherto unknown mechanisms. Whereas acute-COVID-19 severity and outcomes were previously correlated with Notch4 expression on Tregs, here, we show that Tregs in MIS-C were destabilized through a Notch1-dependent mechanism. Genetic analysis revealed that patients with MIS-C had enrichment of rare deleterious variants affecting inflammation and autoimmunity pathways, including dominant-negative mutations in the Notch1 regulators NUMB and NUMBL leading to Notch1 upregulation. Notch1 signaling in Tregs induced CD22, leading to their destabilization in a mTORC1-dependent manner and to the promotion of systemic inflammation. These results identify a Notch1/CD22 signaling axis that disrupts Treg function in MIS-C and point to distinct immune checkpoints controlled by individual Treg Notch receptors that shape the inflammatory outcome in SARS-CoV-2 infection.

Organoids have been used to investigate the three-dimensional (3D) organization and function of their respective organs. These self-organizing 3D structures offer a distinct advantage over traditional two-dimensional (2D) culture techniques by creating a more physiologically relevant milieu to study complex biological systems. The goal of this study was to determine the feasibility of establishing organoids from various pediatric liver diseases and characterize the long-term evolution of cholangiocyte organoids (chol-orgs) under a single continuous culture condition. We established chol-orgs from 10 different liver conditions and characterized their multicellular organization into complex epithelial structures through budding, merging, and lumen formation. Immunofluorescent staining, electron microscopy, and single-nucleus RNA (snRNA-seq) sequencing confirmed the cholangiocytic nature of the chol-orgs. There were significant cell population differences in the transcript profiles of two-dimensional and organoid cultures based on snRNA-seq. Our study provides an approach for the generation and long-term maintenance of chol-orgs from various pediatric liver diseases under a single continuous culture condition.

Background: Children and adolescents with early-onset psychosis (EOP) have more rare genetic variants than individuals with adult-onset forms of the illness, implying that fewer EOP participants are needed for genetic discovery. The Schizophrenia Exome Sequencing Meta-analysis (SCHEMA) study predicted that 10 genes with ultra-rare variation were linked to adult-onset schizophrenia. We hypothesized that rare variants predicted “High” and “Moderate” by the Variant Effect Predictor Algorithm (abbreviated as VEPHMI) in these 10 genes would be enriched in our EOP cohort. Methods: We compared rare VEPHMI variants in individuals with EOP (N = 34) with race- and sex-matched controls (N = 34) using the sequence kernel association test (SKAT). Results: GRIN2A variants were significantly increased in the EOP cohort (p = 0.004), with seven individuals (20% of the EOP cohort) carrying a rare VEPHMI variant. The EOP cohort was then compared to three additional control cohorts. GRIN2A variants were significantly increased in the EOP cohort for two of the additional control sets (p = 0.02 and p = 0.02), and trending towards significance for the third (p = 0.06). Conclusion: Despite a small sample size, GRIN2A VEPHMI variant burden was increased in a cohort of individuals with EOP in comparison to controls. GRIN2A variants have been associated with a range of neuropsychiatric disorders including adult-onset psychotic spectrum disorder and childhood-onset schizophrenia. This study supports the role of GRIN2A in EOP and emphasizes its role in neuropsychiatric disorders.

Background/Objectives: Strabismus is the most common ocular disorder of childhood. Three rare, recurrent genetic duplications have been associated with both esotropia and exotropia, but the mechanisms by which they contribute to strabismus are unknown. This work aims to investigate the mechanisms of the smallest of the three, a 23 kb duplication on chromosome 4 (hg38|4:25,554,985-25,578,843). Methods: Using CRISPR and bridging oligos, we introduced the duplication into the Kolf2.1J iPSC line. We differentiated the parent line and the line with the duplication into cortical neurons using a three-dimensional differentiation protocol, and performed bulk RNASeq on neural progenitors (day 14) and differentiated neurons (day 63). Results: We successfully introduced the duplication into Kolf2.1J iPSCs by nucleofecting a bridging oligo for the newly formed junction along with cas9 ribonucleoparticles. We confirmed that the cells had a tandem duplication without inversion or deletion. The parent line and the line with the duplication both differentiated into neurons reliably. There were a total of 37 differentially expressed genes (DEGs) at day 63, 25 downregulated and 12 upregulated. There were 55 DEGs at day 14, 18 of which were also DEGs at day 63. The DEGs included a number of protocadherins, several genes involved in neuronal development, including SLITRK2, CSMD1, and VGF, and several genes of unknown function. Conclusions: A copy number variant (CNV) that confers risk for strabismus affects gene expression of several genes involved in neural development, highlighting that strabismus most likely results from abnormal neural development, and identifying several new genes and pathways for further research into the pathophysiology of strabismus.

Single-cell transcriptomics data are analyzed using two popular tools, Seurat and Scanpy. Multiple separate tools are used downstream of Seurat and Scanpy cell annotation to study cell differentiation and communication, including cell proportion difference analysis between conditions, pseudotime and trajectory analyses to study cell transition, and cell–cell communication analysis. To automate the integrative cell differentiation and communication analyses of single-cell RNA-seq data, we developed a single-cell RNA-seq downstream analysis pipeline called “scDown”. This R package includes cell proportion difference analysis, cell–cell communication analysis, pseudotime analysis, and RNA velocity analysis. Both Seurat and Scanpy annotated single-cell RNA-seq data are accepted in this pipeline. We applied scDown to a published dataset and identified a unique, previously undiscovered signature of neuronal inflammatory signaling associated with a rare genetic neurodevelopmental disorder. These findings were not identified with a simple implementation of Seurat differential gene expression analysis, illustrating the value of our pipeline in biological discovery. scDown can be broadly utilized in downstream analyses of scRNA-seq data, particularly in rare diseases.

Background/Objectives: Genomic testing has transformed rare-disease diagnostics, yet a substantial proportion of individuals remain without a molecular diagnosis even after short-read exome sequencing (SR-ES) or short-read genome sequencing (SR-GS) and repeated conventional analysis. Methods: To address this persistent gap, we evaluated a coordinated multimodal reanalysis framework for deeply investigated families with suspected monogenic disease. Six families (20 individuals; 8 affected individuals) that had remained unsolved after prior comprehensive testing were reviewed prospectively in weekly interdisciplinary case conferences over one year. Available data included SR-ES, SR-GS, long-read genome sequencing (LR-GS), RNA-seq, optical genome mapping, mobile-element analysis, and mitochondrial genome analysis. The goal was not to test a single modality in isolation, but to assess whether systematic escalation across complementary assays plus continued reinterpretation could improve case resolution. Results: Three families (50%) achieved a reportable molecular diagnosis, two (33%) yielded strong candidate findings requiring additional evidence, and one (17%) remained without a definitive new molecular diagnosis, although reinterpretation of a previously identified NOTCH3 variant provided a possible partial explanation. Resolved cases included compound-heterozygous variants in KLHL40, a 119 kb multi-exon deletion in TTN, and a recurrent insertion in RNU4-2. Candidate findings included biallelic NARS2 variants and a 1.3 kb intragenic deletion involving ZEB2. Functional transcriptomic analyses supported the KLHL40 and TTN diagnoses but did not demonstrate a splicing consequence for the candidate NARS2 intronic variant in cardiac tissue. Conclusions: This small pilot cohort is not intended to estimate general diagnostic yield, but it demonstrates that a coordinated multimodal framework can reveal different sources of added value, including structural variant discovery, orthogonal functional support, and reinterpretation of existing short-read data as knowledge evolves. These findings underscore that archived short-read exome and genome data can retain substantial diagnostic value years after initial testing, particularly when reanalyzed with updated pipelines, expanded disease gene knowledge, and orthogonal multimodal evidence. Adoption of iterative, team-based multimodal strategies may help resolve the most complex unsolved rare-disease cases.