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Developmental Biology - Genetic Diagnostics
Diagnosing Rare Genetic Diseases Fast!
Genome sequencing in a first-line diagnostic test for babies with genetic diseases...
Researchers at Rady Children's Institute for Genomic Medicine (RCIGM) in San Diego, California, use a machine-learning process and clinical natural language processing (CNLP) to diagnose rare genetic diseases in record time. This new method is speeding answers to physicians caring for infants in intensive care and opening the door to increased use of genome sequencing as a first-line diagnostic test for babies with cryptic conditions.
"Some people call this artificial intelligence, we call it 'augmented intelligence'. Patient care will always begin and end with the doctor. By harnessing the power of technology, we can quickly and accurately determine the root cause of genetic diseases. We rapidly provide this critical information to intensive care physicians so they can focus on personalizing care for babies who are struggling to survive."
Stephen Kingsmore MD DSc, President and Chief Executive Officer (CEO), RCIGM.
A new study documenting the process is published in the journal Science Translational Medicine. The workflow and research were led by the RCIGM team in collaboration with leading technology and data-science developers - Alexion, Clinithink, Diploid, Fabric Genomics and Illumina.
Dr. Kingsmore's team has pioneered a rapid Whole Genome Sequencing process to deliver genetic test results to neonatal and pediatric intensive care (NICU/PICU) physicians to guide medical intervention. RCIGM is the research arm of Rady Children's Hospital-San Diego. By reducing the need for labor-intensive manual analysis of genomic data, the supervised automated pipeline provided significant time-savings.
In February 2018, the same team achieved the Guinness World Record for fastest diagnosis through whole genome sequencing. Of automated runs, the fastest times, average 19 hours, were achieved using augmented intelligence.
"This is truly pioneering work by the RCIGM team--saving the lives of very sick newborn babies by using AI to rapidly and accurately analyze their whole genome sequence" says Eric Topol, MD, Professor of Molecular Medicine at Scripps Research and author of a new book Deep Medicine. RCIGM has optimized and integrated several time-saving technologies into a rapid Whole Genome Sequencing (rWGS) process to screen a child's entire genetic makeup for thousands of genetic anomalies from a blood sample.
Key components in the rWGS pipeline come from Illumina, the global leader in DNA sequencing, including Nextera DNA Flex library preparation, whole genome sequencing via the NovaSeq 6000 and the S1 flow cell format. Speed and accuracy are enhanced by Illumina's DRAGEN (Dynamic Read Analysis for GENomics) Bio-IT Platform. Other pipeline elements include the following:
Clinithink's clinical natural language processing platform, CliX ENRICH, quickly combs through a patient's electronic medical record to automatically extract crucial phenotype information.
Another core element of machine learning is MOON by Diploid. This platform automates genome interpretation using AI to automatically filter and rank likely pathogenic variants. Deep phenotype integration, based in natural language processing of the medical literature, is a key feature driving automated interpretation. MOON takes five minutes to suggest the causal mutation out of the 4.5 million variants in a whole genome.
In addition, Alexion's rare disease and data science expertise enabled the translation of clinical information into a computer format for guided interpretation. As part of this study, the genetic sequencing data was fed into automated computational platforms under the supervision of researchers. For comparison and verification, clinical medical geneticists on the team used Fabric Genomics' AI-based algorithms VAAST and Phevor integrated into the clinical decision support software, OPAL (now called Fabric Enterprise) to confirm the output of the automated pipeline. Fabric software is part of RCIGM's standard analysis and interpretation workflow.
The study: "Diagnosis of genetic diseases in seriously ill children by rapid whole-genome sequencing and automated phenotyping and interpretation," found automated, retrospective diagnoses agreed with expert manual interpretation (97 percent recall, 99 percent precision in 95 children with 97 genetic diseases).
Researchers concluded that genome sequencing with automated phenotyping and interpretation, in a median 20:10 hours, may spur use in intensive care units, thereby enabling timely and precise medical care.
"Using machine-learning platforms doesn't replace human experts. Instead it augments their capabilities," sys Michelle Clark, PhD, statistical scientist at RCIGM and the first author of the study. "By informing timely targeted treatments, rapid genome sequencing can improve the outcomes of seriously ill children with genetic diseases."
An estimated four percent of newborns in North America are affected by genetic diseases, which are the leading cause of death in infants. Rare genetic diseases also account for approximately 15 percent of admissions to children's hospitals.
The RCIGM workflow is engineered to speed and scale up genomic data interpretation to reduce the time and cost of whole genome sequencing. The team's goal is to make rWGS accessible and available to any child who needs it. Increased automation of the process removes a barrier to scaling up clinical use of WGS by reducing the need for time-consuming manual analysis and interpretation of the data by scarce certified clinical medical geneticists.
There were fewer than 1,600 of these experts nationwide in 2017, according to the American Board of Medical Genetics and Genomics. Rady Children's Institute began performing genomic sequencing in July 2016. As of the end of March 2019, the team had completed testing and interpretation of the genomes of more than 750 children. One-third of those children have received a genetic diagnosis with 25 percent of those benefitting from an immediate change in clinical care based on that diagnosis.
Abstract
When treating seriously ill children, time is of the essence. Clark et al. built an automated pipeline to analyze EHR data and genome sequencing data from dried blood spots to deliver a potential diagnosis for hospitalized, often critically ill, children with suspected genetic diseases. Their pipeline required minimal user intervention, increasing usability and shortening time to diagnosis, delivering a provisional finding in a median time of less than 24 hours. Although this pipeline would need to be adapted for use at different hospital systems, such an automated tool could aid clinicians to expedite an accurate genetic disease diagnosis, potentially hastening lifesaving changes to patient care.
Authors
Michelle M. Clark, Amber Hildreth, Sergey Batalov, Yan Ding, Shimul Chowdhury, Kelly Watkins, Katarzyna Ellsworth, Brandon Camp, Cyrielle I. Kint, Calum Yacoubian, Lauge Farnaes, Matthew N. Bainbridge, Curtis Beebe, Joshua J. A. Braun, Margaret Bray, Jeanne Carroll, Julie A. Cakici, Sara A. Caylor, Christina Clarke, Mitchell P. Creed, Jennifer Friedman, Alison Frith, Richard Gain, Mary Gaughran, Shauna George, Sheldon Gilmer, Joseph Gleeson, Jeremy Gore, Haiying Grunenwald, Raymond L. Hovey, Marie L. Janes, Kejia Lin, Paul D. McDonagh, Kyle McBride, Patrick Mulrooney, Shareef Nahas, Daeheon Oh, Albert Oriol, Laura Puckett, Zia Rady, Martin G. Reese, Julie Ryu, Lisa Salz, Erica Sanford, Lawrence Stewart, Nathaly Sweeney, Mari Tokita, Luca Van Der Kraan, Sarah White, Kristen Wigby, Brett Williams, Terence Wong, Meredith S. Wright, Catherine Yamada, Peter Schols, John Reynders, Kevin Hall, David Dimmock, Narayanan Veeraraghavan, Thomas Defay and Stephen F. Kingsmore.
Acknowledgements
About Rady Children's Institute for Genomic Medicine:
The Institute is leading the way in advancing precision healthcare for infants and children through genomic and systems medicine research. Discoveries at the Institute are enabling rapid diagnosis and targeted treatment of critically ill newborns and pediatric patients at Rady Children's Hospital-San Diego and partnering hospitals. The vision is to expand delivery of this life-saving technology to enable the practice of precision pediatric medicine at children's hospitals across California, the nation and the world. RCIGM is a subsidiary of Rady Children's Hospital and Health Center. Learn more at http://www.RadyGenomics.org. Follow us on Twitter @RadyGenomics.
About Rady Children's Hospital - San Diego:
Rady Children's Hospital-San Diego is a 524-bed pediatric care facility providing the largest source of comprehensive pediatric medical services in San Diego, southern Riverside and Imperial counties. Rady Children's is the only hospital in the San Diego area dedicated exclusively to pediatric healthcare and is the region's only designated pediatric trauma center. In June 2018, U.S. News & World Report ranked Rady Children's among the best children's hospitals in the nation in all ten pediatric specialties the magazine surveyed. Rady Children's is a nonprofit organization that relies on donations to support its mission. For more information, visit http://www.rchsd.org and find us on Facebook, Twitter and Vimeo.
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May 7 2019 Fetal Timeline Maternal Timeline News
 Diagnosis of genetic diseases in seriously ill children by use of rapid whole-genome sequencing is increasing and rapidly shortening time to diagnosis - sometimes to within 24 hours.
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