Why covid-19 might finally usher in the era of health care based on a patient’s data

Davis believes the key to understanding why covid affects people in such varied ways is to identify the differences between the immune systems of those who successfully fight the disease and those who succumb. Those differences could range from the simple, such as whether someone has been exposed to other coronaviruses in the past, to factors as complex as genetically determined variations in how certain cells display viral protein fragments on their surfaces for inspection by circulating immune cells. These proteins can influence how likely the immune cell is to recognize the presence of a dangerous pathogen, sound the alarm, and mobilize an army of antibodies to go on the attack.

“Now there is a flood of data, and it’s the highest quality that we’ve ever had, and also the most we’ve ever had,” Davis says. 

A boon for the science, to be sure. But will the ISB study change how patients are treated and help prepare us for future pandemics? Hood is optimistic. “This absolutely validates everything I have been arguing for the past 20 years,” he says. 

The needed tools

Hood made a major contribution to immunology early in his career, after attending medical school and getting his PhD from Caltech. He helped solve the mystery of how the body can produce roughly 10 billion varieties of antibodies, Y-shaped proteins that can bind to the outer surface of a distinctly shaped invading pathogen and destroy it with the specificity of a guided missile. 

Despite his early success, Hood recognized from the start that without major advances in technology, he would never answer the most intriguing biological questions that remained about the immune system: those revealing how it coordinates its remarkably complex collection of cell types and proteins. If immunologists were ever to understand how all these parts worked together, Hood realized, they would first need to recognize, characterize, and measure them. 

Jim Heath, president of the Institute for Systems Biology

IAN ALLEN

Hood’s Caltech lab played a key role in developing a wide range of tools, including instruments that would enable biologists to read and write sequences of amino acids, and machines that could string together DNA nucleotides (the letters of the genetic code). Perhaps most famously, in 1986 he helped invent the automated DNA sequencer, a machine able to quickly read the nucleotides in the genome and determine their order; it paved the way for the Human Genome Project, the $3 billion, 13-year effort to produce the first draft of a complete human genome. 

In the years that followed, Hood advocated for a reinvention of modern health care that relied on the new tools of molecular biology to collect data from individual patients: genome sequences, and complete inventories of proteins circulating in the bloodstream. This data could then be analyzed, using early systems of machine learning and pattern recognition to pull out interesting patterns and correlations. Insights could be harnessed to maximize a person’s health and head off diseases far earlier than previously possible. 

It all made perfect scientific sense. But nearly two decades after the Human Genome Project’s completion in 2003, and despite much progress in genomic sciences as well as in data science, Hood’s predicted revolution in health care has still not arrived. 

Hood says one reason is that the tools used to be expensive. Now, however, a genome can be sequenced for $300 or less. And, he says, researchers have gained access to computational tools “that can really integrate the data, and turn data into knowledge.” 

But the biggest roadblock is that the health-care system is inefficient and resistant to change. There’s a “lack of understanding about how important it is to get diverse types of data and integrate them,” Hood says. “Most physicians went to medical school five or 10 or 20 years ago, and they never learned anything about any of this.”

“Everybody is really busy, and changing takes time, so you have to persuade leadership as well as physicians this is in their interest,” he says. “That all turned out to be far more difficult than I ever thought it would be.” 

Pandemic lessons

These days, Hood is still pushing hard, and despite the years of frustration, he is characteristically optimistic. One reason for his renewed hope is that he finally has ready access to patients  and the money to begin his next grand experiment. 

In 2016, ISB merged with Providence Health & Services in Seattle, a massive network with 51 hospitals, billions of dollars in cash, and a hunger to develop a more robust research program. 

Soon after the merger, Hood was talking up an impossibly ambitious-­sounding campaign to start what he calls the Million Person Project. It would apply phenotyping and genetic analysis to, yes, a million people. In January 2020, Hood kicked off a pilot project, having recruited 5,000 patients, and began to sequence their genomes.