Genomic answers for children: Dynamic analyses of >1000 pediatric rare disease genomes.

PURPOSE: This study aimed to provide comprehensive diagnostic and candidate analyses in a pediatric rare disease cohort through the Genomic Answers for Kids program. METHODS: Extensive analyses of 960 families with suspected genetic disorders included short-read exome sequencing and short-read genome sequencing (srGS); PacBio HiFi long-read genome sequencing (HiFi-GS); variant calling for single nucleotide variants (SNV), structural variant (SV), and repeat variants; and machine-learning variant prioritization. Structured phenotypes, prioritized variants, and pedigrees were stored in PhenoTips database, with data sharing through controlled access the database of Genotypes and Phenotypes. RESULTS: Diagnostic rates ranged from 11% in patients with prior negative genetic testing to 34.5% in naive patients. Incorporating SVs from genome sequencing added up to 13% of new diagnoses in previously unsolved cases. HiFi-GS yielded increased discovery rate with >4-fold more rare coding SVs compared with srGS. Variants and genes of unknown significance remain the most common finding (58% of nondiagnostic cases). CONCLUSION: Computational prioritization is efficient for diagnostic SNVs. Thorough identification of non-SNVs remains challenging and is partly mitigated using HiFi-GS sequencing. Importantly, community research is supported by sharing real-time data to accelerate gene validation and by providing HiFi variant (SNV/SV) resources from >1000 human alleles to facilitate implementation of new sequencing platforms for rare disease diagnoses.

The NSIGHT1-randomized controlled trial: rapid whole-genome sequencing for accelerated etiologic diagnosis in critically ill infants.

Genetic disorders are a leading cause of morbidity and mortality in infants in neonatal and pediatric intensive care units (NICU/PICU). While genomic sequencing is useful for genetic disease diagnosis, results are usually reported too late to guide inpatient management. We performed an investigator-initiated, partially blinded, pragmatic, randomized, controlled trial to test the hypothesis that rapid whole-genome sequencing (rWGS) increased the proportion of NICU/PICU infants receiving a genetic diagnosis within 28 days. The participants were families with infants aged <4 months in a regional NICU and PICU, with illnesses of unknown etiology. The intervention was trio rWGS. Enrollment from October 2014 to June 2016, and follow-up until November 2016. Of all, 26 female infants, 37 male infants, and 2 infants of undetermined sex were randomized to receive rWGS plus standard genetic tests (n = 32, cases) or standard genetic tests alone (n = 33, controls). The study was terminated early due to loss of equipoise: 73% (24) controls received genomic sequencing as standard tests, and 15% (five) controls underwent compassionate cross-over to receive rWGS. Nevertheless, intention to treat analysis showed the rate of genetic diagnosis within 28 days of enrollment (the primary end-point) to be higher in cases (31%, 10 of 32) than controls (3%, 1 of 33; difference, 28% [95% CI, 10-46%]; p = 0.003). Among infants enrolled in the first 25 days of life, the rate of neonatal diagnosis was higher in cases (32%, 7 of 22) than controls (0%, 0 of 23; difference, 32% [95% CI, 11-53%];p = 0.004). Median age at diagnosis (25 days [range 14-90] in cases vs. 130 days [range 37-451] in controls) and median time to diagnosis (13 days [range 1-84] in cases, vs. 107 days [range 21-429] in controls) were significantly less in cases than controls (p = 0.04). In conclusion, rWGS increased the proportion of NICU/PICU infants who received timely diagnoses of genetic diseases.

Whole-genome sequencing for identification of Mendelian disorders in critically ill infants: a retrospective analysis of diagnostic and clinical findings.

BACKGROUND: Genetic disorders and congenital anomalies are the leading causes of infant mortality. Diagnosis of most genetic diseases in neonatal and paediatric intensive care units (NICU and PICU) is not sufficiently timely to guide acute clinical management. We used rapid whole-genome sequencing (STATseq) in a level 4 NICU and PICU to assess the rate and types of molecular diagnoses, and the prevalence, types, and effect of diagnoses that are likely to change medical management in critically ill infants. METHODS: We did a retrospective comparison of STATseq and standard genetic testing in a case series from the NICU and PICU of a large children's hospital between Nov 11, 2011, and Oct 1, 2014. The participants were families with an infant younger than 4 months with an acute illness of suspected genetic cause. The intervention was STATseq of trios (both parents and their affected infant). The main measures were the diagnostic rate, time to diagnosis, and rate of change in management after standard genetic testing and STATseq. FINDINGS: 20 (57%) of 35 infants were diagnosed with a genetic disease by use of STATseq and three (9%) of 32 by use of standard genetic testing (p=0·0002). Median time to genome analysis was 5 days (range 3-153) and median time to STATseq report was 23 days (5-912). 13 (65%) of 20 STATseq diagnoses were associated with de-novo mutations. Acute clinical usefulness was noted in 13 (65%) of 20 infants with a STATseq diagnosis, four (20%) had diagnoses with strongly favourable effects on management, and six (30%) were started on palliative care. 120-day mortality was 57% (12 of 21) in infants with a genetic diagnosis. INTERPRETATION: In selected acutely ill infants, STATseq had a high rate of diagnosis of genetic disorders. Most diagnoses altered the management of infants in the NICU or PICU. The very high infant mortality rate indicates a substantial need for rapid genomic diagnoses to be allied with a novel framework for precision medicine for infants in NICU and PICU who are diagnosed with genetic diseases to improve outcomes. FUNDING: Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Human Genome Research Institute, and National Center for Advancing Translational Sciences.