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The Angelman Syndrome (AS) is an extreme neurodevelopmental disorder without effective treatments. While most patients with this disease can be diagnosed by genetic testing, there are still a handful of patients have an unrecognized genetic cause for their illness. Thus, novel approaches to clinical diagnosis and treatment are urgently needed. The aim of this study was to identify and characterize differentially expressed genes involved in AS and built potential diagnostic panel for AS by NGS sequencing. A multi-cohort analysis framework was used to analyze stem cell-derived neurons from AS patients in GSE160747 dataset. We identified three differentially expressed genes (ACTN1, ADAMTS2, SLC30A8) differentiates AS patients from controls. Moreover, we validated the expression patterns of these genes in GSE146640, GSE120225. Receiver operating characteristic (ROC) curves analysis demonstrated that these genes could function as potential diagnostic biomarkers [AUC = 1 (95% CI 1–1)]. This study may provide new approach for diagnosing patients with AS and helping to develop novel therapies in treating AS patients.

Introduction: Pediatric Crohn’s disease is a chronic inflammatory condition that affects the digestive system in children and adolescents. It is characterized by symptoms such as abdominal pain, diarrhea, weight loss, and malnutrition, and can also cause complications like growth delays and delayed puberty. However, diagnosing pediatric Crohn’s disease can be difficult, especially when it comes to non-invasive methods.Methods: In this study, we developed a diagnostic model using RNA-seq to analyze gene expression in ileal biopsy samples from children with Crohn’s disease and non-pediatric Crohn’s controls.Results: Our results showed that pediatric Crohn’s disease is associated with altered expression of genes involved in immune response, inflammation, and tissue repair. We validated our findings using two independent datasets from the Gene Expression Omnibus (GEO) database, as well as through one prospective independent dataset, and found that our model had a high accuracy rate.Discussion: These findings suggest the possibility of non-invasive diagnosis for pediatric Crohn’s disease and may inform the development of targeted therapies for this condition.