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Diagnosis of genetic diseases in seriously ill children by rapid whole-genome sequencing and automated phenotyping and interpretation.

ABSTRACT: By informing timely targeted treatments, rapid whole-genome sequencing can improve the outcomes of seriously ill children with genetic diseases, particularly infants in neonatal and pediatric intensive care units (ICUs). The need for highly qualified professionals to decipher results, however, precludes widespread implementation. We describe a platform for population-scale, provisional diagnosis of genetic diseases with automated phenotyping and interpretation. Genome sequencing was expedited by bead-based genome library preparation directly from blood samples and sequencing of paired 100-nt reads in 15.5 hours. Clinical natural language processing (CNLP) automatically extracted children's deep phenomes from electronic health records with 80% precision and 93% recall. In 101 children with 105 genetic diseases, a mean of 4.3 CNLP-extracted phenotypic features matched the expected phenotypic features of those diseases, compared with a match of 0.9 phenotypic features used in manual interpretation. We automated provisional diagnosis by combining the ranking of the similarity of a patient's CNLP phenome with respect to the expected phenotypic features of all genetic diseases, together with the ranking of the pathogenicity of all of the patient's genomic variants. Automated, retrospective diagnoses concurred well with expert manual interpretation (97% recall and 99% precision in 95 children with 97 genetic diseases). Prospectively, our platform correctly diagnosed three of seven seriously ill ICU infants (100% precision and recall) with a mean time saving of 22:19 hours. In each case, the diagnosis affected treatment. Genome sequencing with automated phenotyping and interpretation in a median of 20:10 hours may increase adoption in ICUs and, thereby, timely implementation of precise treatments.

SUBMITTER: Clark MM

PROVIDER: S-EPMC9512059 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Diagnosis of genetic diseases in seriously ill children by rapid whole-genome sequencing and automated phenotyping and interpretation.

Clark Michelle M MM Hildreth Amber A Batalov Sergey S Ding Yan Y Chowdhury Shimul S Watkins Kelly K Ellsworth Katarzyna K Camp Brandon B Kint Cyrielle I CI Yacoubian Calum C Farnaes Lauge L Bainbridge Matthew N MN Beebe Curtis C Braun Joshua J A JJA Bray Margaret M Carroll Jeanne J Cakici Julie A JA Caylor Sara A SA Clarke Christina C Creed Mitchell P MP Friedman Jennifer J Frith Alison A Gain Richard R Gaughran Mary M George Shauna S Gilmer Sheldon S Gleeson Joseph J Gore Jeremy J Grunenwald Haiying H Hovey Raymond L RL Janes Marie L ML Lin Kejia K McDonagh Paul D PD McBride Kyle K Mulrooney Patrick P Nahas Shareef S Oh Daeheon D Oriol Albert A Oriol Albert A Puckett Laura L Rady Zia Z Reese Martin G MG Ryu Julie J Salz Lisa L Sanford Erica E Stewart Lawrence L Sweeney Nathaly N Tokita Mari M Van Der Kraan Luca L White Sarah S Wigby Kristen K Williams Brett B Williams Brett B Wong Terence T Wright Meredith S MS Yamada Catherine C Schols Peter P Reynders John J Hall Kevin K Dimmock David D Veeraraghavan Narayanan N Defay Thomas T Kingsmore Stephen F SF Kingsmore Stephen F SF

Science translational medicine 20190401 489

By informing timely targeted treatments, rapid whole-genome sequencing can improve the outcomes of seriously ill children with genetic diseases, particularly infants in neonatal and pediatric intensive care units (ICUs). The need for highly qualified professionals to decipher results, however, precludes widespread implementation. We describe a platform for population-scale, provisional diagnosis of genetic diseases with automated phenotyping and interpretation. Genome sequencing was expedited by ...[more]

PMID: 31019026

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Project description: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.

Project description:BackgroundSepsis is characterized by highly heterogeneous immune responses associated with a spectrum of disease severity. Methods that rapidly and sensitively profile these immune responses can potentially personalize immune-adjuvant therapies for sepsis. We hypothesized that the ELLA microfluidic approach to measure cytokine production from the whole blood of septic and critically ill patients would deliver faster, more precise results than the existing optic-driven ELISpot quantification. We tested our hypothesis by measuring ex vivo-stimulated production of TNF and IFNγ in critically ill and septic patients (n = 22), critically ill and non-septic patients (n = 10), and healthy volunteers (n = 10) through both ELLA and ELISpot immunoassays. Blood samples were subjected to one of three stimulants for 4 h or 18 h durations during days 1, 7-10, and 14 of critical illness. Stimulants for lymphocytes included anti-CD3/anti-CD28 and phorbol 12-myristate 13-acetate (PMA), whereas LPS was used for monocytes. Stimulated TNF and IFNγ concentrations were then associated with 30-day mortality.ResultsBoth ELISpot and ELLA immunoassays showed substantial agreement in TNF concentrations post 4 h and 18 h LPS stimulation, with concordance correlation coefficients at 0.62 and 0.60, respectively. ELLA had a broad dynamic measurement range and provided accurate TNF and IFNγ readings at both minimal and elevated cytokine concentrations (with mean coefficients of variation between triplicate readings at 2.1 ± 1.4% and 4.9 ± 7.2%, respectively). However, there was no association between the ELLA-determined cytokine concentrations on the first day of critical illness and 30-day mortality rate. In contrast, using the ELISpot for cytokine quantification revealed that non-survivors had reduced baseline TNF levels at 18 h, decreased LPS-induced TNF levels at 18 h, and diminished TNF levels post 4 h/18 h anti-CD3/28 stimulation.ConclusionsOur study affirms the feasibility of obtaining dependable immune phenotyping data within 6 h of blood collection from critically ill patients, both septic and non-septic, using the ELLA immunoassay. Both ELLA and ELISpot can offer valuable insights into prognosis, therapeutic strategies, and the underlying mechanisms of sepsis development.

Dataset Information

Diagnosis of genetic diseases in seriously ill children by rapid whole-genome sequencing and automated phenotyping and interpretation.

Publications

Diagnosis of genetic diseases in seriously ill children by rapid whole-genome sequencing and automated phenotyping and interpretation.

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