Background Exome/genome sequencing (ES/GS) have been recently used in neonatal and pediatric/cardiac intensive care units (NICU and PICU/CICU) to diagnose and care for acutely ill infants, but the effectiveness of targeted gene panels for these purposes remains unknown. Methods RapSeq, a newly developed panel targeting 4,503 disease‐causing genes, was employed on selected patients in our NICU/PICU/CICU. Twenty trios were sequenced from October 2015 to March 2017. We assessed diagnostic yield, turnaround times, and clinical consequences. Results A diagnosis was made in 10/20 neonates (50%); eight had de novo variants ( ASXL1 , CHD , FBN1 , KMT2D , FANCB , FLNA , PAX3 ), one was a compound heterozygote for CHAT , and one had a maternally inherited GNAS variant. Preliminary reports were generated by 9.6 days (mean); final reports after Sanger sequencing at 16.3 days (mean). In all positive infants, the diagnosis changed management. In a case with congenital myasthenia, diagnosis and treatment occurred at 17 days versus 7 months in a historical control. Conclusions This study shows that a gene panel that includes the majority of known disease‐causing genes can rapidly identify a diagnosis in a large number of tested infants. Due to simpler deployment and interpretation and lower costs, this approach might represent an alternative to ES/GS in the NICU/PICU/CICU.

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Congenital myasthenic syndrome (CMS) is a group of 32 disorders involving genetic dysfunction at the neuromuscular junction resulting in skeletal muscle weakness that worsens with physical activity. Precise diagnosis and molecular subtype identification are critical for treatment as medication for one subtype may exacerbate disease in another (Finsterer 2019; Prior et al. 2021; Engel et al. 2015). The SNAP25-related CMS subtype (congenital myasthenic syndrome 18, CMS18; MIM #616330) is a rare disorder characterized by muscle fatigability, delayed psychomotor development and ataxia. Herein, we performed rapid whole genome sequencing (rWGS) on a critically ill newborn leading to the discovery of an unreported pathogenic de novo SNAP25 c.529C>T; p.Gln177Ter variant. In this report, we present a novel case of CMS18 related to a variant affecting both SNAP25A and SNAP25B isoforms with complex neonatal consequence. This discovery offers unique insight into the extent of phenotypic severity in CMS18, expands the reported SNAP25 variant phenotype and paves a foundation for personalized management for CMS18.

Background Rapidly and efficiently identifying critically ill infants for whole genome sequencing (WGS) is a costly and challenging task currently performed by scarce, highly trained experts and is a major bottleneck for application of WGS in the NICU. There is a dire need for automated means to prioritize patients for WGS. Methods Institutional databases of electronic health records (EHRs) are logical starting points for identifying patients with undiagnosed Mendelian diseases. We have developed automated means to prioritize patients for rapid and whole genome sequencing (rWGS and WGS) directly from clinical notes. Our approach combines a clinical natural language processing (CNLP) workflow with a machine learning-based prioritization tool named Mendelian Phenotype Search Engine (MPSE). Results MPSE accurately and robustly identified NICU patients selected for WGS by clinical experts from Rady Children’s Hospital in San Diego (AUC 0.86) and the University of Utah (AUC 0.85). In addition to effectively identifying patients for WGS, MPSE scores also strongly prioritize diagnostic cases over non-diagnostic cases, with projected diagnostic yields exceeding 50% throughout the first and second quartiles of score-ranked patients. Conclusions Our results indicate that an automated pipeline for selecting acutely ill infants in neonatal intensive care units (NICU) for WGS can meet or exceed diagnostic yields obtained through current selection procedures, which require time-consuming manual review of clinical notes and histories by specialized personnel.

Background: Genetic disorders contribute to significant morbidity and mortality in critically ill newborns. Despite advances in genome sequencing technologies, a majority of neonatal cases remain unsolved. Complex structural variants (SVs) often elude conventional genome sequencing variant calling pipelines and will explain a portion of these unsolved cases. Methods:As part of the Utah NeoSeq project, we used a research-based, rapid whole-genome sequencing (WGS) protocol to investigate the genomic etiology for a newborn with a left-sided congenital diaphragmatic hernia (CDH) and cardiac malformations, whose mother also had a history of CDH and atrial septal defect.