AI tech identifies genetic causes of serious disease

An artificial intelligence (AI)-based technology rapidly diagnoses rare disorders in critically ill children with high accuracy, according to a report by scientists from University of Utah Health and Fabric Genomics, collaborators on a study led by Rady Children’s Hospital in San Diego.

Photo
GEM makes genome sequencing more cost-effective and scalable for NICU applications.
Source: Charlie Ehlert, University of Utah Health

The benchmark finding, foreshadows the next phase of medicine, where technology helps clinicians quickly determine the root cause of disease so they can give patients the right treatment sooner. “This study is an exciting milestone demonstrating how rapid insights from AI-powered decision support technologies have the potential to significantly improve patient care,” says Mark Yandell, Ph.D., professor of human genetics and Edna Benning Presidential Endowed Chair at U of U Health, and a founding scientific advisor to Fabric.

Worldwide, about seven million infants are born with serious genetic disorders each year. For these children, life usually begins in intensive care. A handful of NICUs in the U.S., including at U of U Health, are now searching for genetic causes of disease by reading, or sequencing, the three billion DNA letters that make up the human genome. While it takes hours to sequence the whole genome, it can take days or weeks of computational and manual analysis to diagnose the illness.

For some infants, that is not fast enough, Yandell says. Understanding the cause of the newborn’s illness is critical for effective treatment. Arriving at a diagnosis within the first 24 to 48 hours after birth gives these patients the best chance to improve their condition. Knowing that speed and accuracy are essential, Yandell’s group worked with Fabric to develop the new Fabric GEM algorithm, which incorporates AI to find DNA errors that lead to disease.

In this study, the scientists tested GEM by analyzing whole genomes from 179 previously diagnosed pediatric cases from Rady’s Children’s Hospital and five other medical centers from across the world. GEM identified the causative gene as one of its top two candidates 92% of the time. Doing so outperformed existing tools that accomplished the same task less than 60% of the time.

“Dr. Yandell and the Utah team are at the forefront of applying AI research in genomics,” says Martin Reese, Ph.D., CEO of Fabric Genomics and a co-author on the paper. “Our collaboration has helped Fabric achieve an unprecedented level of accuracy, opening the door for broad use of AI-powered whole genome sequencing in the NICU.”

GEM leverages AI to learn from a vast and ever-growing body of knowledge that has become challenging to keep up with for clinicians and scientists. GEM cross-references large databases of genomic sequences from diverse populations, clinical disease information, and other repositories of medical and scientific data, combining all this with the patient’s genome sequence and medical records. To assist with the medical record search, GEM can be coupled with a natural language processing tool, Clinithink’s CLiX focus, which scans reams of doctors’ notes for the clinical presentations of the patient’s disease.

“Critically ill children rapidly accumulate many pages of clinical notes,” Yandell says. “The need for physicians to manually review and summarize note contents as part of the diagnostic process is a massive time sink. The ability of Clinithink’s tool to automatically convert the contents of these notes in seconds for consumption by GEM is critical for speed and scalability.”

Existing technologies mainly identify small genomic variants that include single DNA letter changes, or insertions or deletions of a small string of DNA letters. By contrast, GEM can also find “structural variants” as causes of disease. These changes are larger and are often more complex. It’s estimated that structural variants are behind 10 to 20% of genetic disease.

“To be able to diagnose with more certainty opens a new frontier,” says Luca Brunelli, M.D., neonatologist and professor of pediatrics at U of U Health, who leads a team using GEM and other genome analysis technologies to diagnose patients in the NICU. His goal is to provide answers to families who would have had to live with uncertainty before the development of these tools. He says these advances now provide an explanation for why a child is sick, enable doctors to improve disease management, and, at times, lead to recovery.

“This is a major innovation, one made possible through AI,” Yandell says. “GEM makes genome sequencing more cost-effective and scalable for NICU applications. It took an international team of clinicians, scientists, and software engineers to make this happen. Seeing GEM at work for such a critical application is gratifying.”

The research was published in Genomic Medicine

Subscribe to our newsletter

Related articles

Precision health in the palm of your hand

Precision health in the palm of your hand

Recent breakthrough developments in technologies for real-time genome sequencing, analysis, and diagnosis are poised to deliver a new standard of personalized care.

AI detects rare diseases

AI detects rare diseases

With artificial intelligence to a diagnosis of rare hereditary diseases: The neural network combines data from portrait images with gene and patient data.

AI Eve augments genetic tests

AI Eve augments genetic tests

AI model called EVE shows remarkable capacity to interpret the meaning of gene variants in humans as benign or disease-causing.

Algorithm to predict psychotic illnesses

Algorithm to predict psychotic illnesses

To detect the symptoms that herald the development of psychotic illnesses, scientists have applied longitudinal network analysis to children.

Machine learning helps diagnose leukemia

Machine learning helps diagnose leukemia

Researchers at the University of Bonn show how artificial intelligence improves the evaluation of blood analysis data.

A pen to pin down the fringes of cancer

A pen to pin down the fringes of cancer

The MasSpec Pen has shown to accurately differentiate healthy and cancerous tissue from banked pancreas samples during surgery.

AI screens and diagnoses glaucoma

AI screens and diagnoses glaucoma

Scientists have developed a novel method that uses artificial intelligence to screen for glaucoma.

Using AI and video for early detection of autism

Using AI and video for early detection of autism

Using artificial intelligence, researchers have developed a device for the early detection of autism spectrum disorder in children.

Has graphene lived up to its potential in medical technology?

Has graphene lived up to its potential in medical technology?

Graphene represents incredible opportunities for advancement in many fields, including medical science.

Popular articles

Subscribe to Newsletter