Clinical Whole Genome Sequencing - by Eric Topol

I remember a day when genetic testing was very expensive and only used for rare diseases.

Times and our ability have changed diagnosis and treatment for many diseases previously thought to not be worth genetic analysis.

So much attention has been placed on the cost of whole genome sequencing (WGS) over the years, from about $300 million for the first one in 2000 (some estimates are as high as $3 billion), to now starting to approach $100. That’s a long-sought and remarkable reduction in cost.  

But what is equally impressive is that a team at the University of Washington, led by Danny Miller, set a world record in September 2022, reducing the time from the sample (at the birth of a baby) to interpretation to 3 hours! That diagnosis (of lacking the pathogenic gene variant of concern) in a newborn was facilitated by knowledge of familial risk. Nevertheless, that acceleration of sequencing and analysis comes in the wake of the Stanford team, led by Euan Ashley, performing WGS in 12 people ranging from 3 months to 57 years, in a critical care setting, in as little as 7 hours and 18 minutes.

This acceleration of gene technology almost allows genetic testing to be available at the bedside for a cost approaching a complete blood count.

At times the advances are announced first in lay publications such as the NY Times.

Time course from presentation to diagnosis

At Scripps Research, our SRTI team works closely with Rady Children’s Institute for Genomic Medicine, the group that has pioneered WGS in sick newborns who do not have a diagnosis, accomplishing this from sample to interpretation and management recommendations all within 13 hours, using multiple AI tools (labeled 1-3 below) to expedite the readout and care of the baby.

An automated 13.5 hour system for scalable diagnosis and acute management guidance for genetic diseases

The reduction in cost and time for whole genome sequencing is historic and one of the most important advances that has occurred in life science in recent years. With the increasing use of AI tools to make the variant calling and interpretation more accurate and rapid, along with contextualizing the medical literature for a molecular diagnosis and possible treatment, this could become someday an exemplar, beyond the prediction of protein folding from the amino acid sequence (AlphaFold), for AI’s contribution to biomedicine. Hopefully, someday we will harness its value to advance individualized medicine.

Clinical Whole Genome Sequencing - by Eric Topol