Health

A genetic window on ‘All of Us’

Max Larkin

Harvard Staff Writer

July 14, 2026

8 min read

Broad Institute researcher details U.S. biobank’s value as global resource in study of roots of disease, health

Just as this country celebrated its 250th birthday, some geneticists were celebrating America, too.

At the end of June, the National Institutes of Health announced its “All of Us” Research Program had become the world’s largest database of integrated health and genomic information. The project, launched in 2015 under the Obama administration, aimed to collect comprehensive genetic information and health records from at least a million Americans. Eleven years later, they’re approaching that goal, with 747,000 volunteers sharing their whole genomes, lifelong health records, or both.

Comparable nonprofit efforts had already taken shape in the U.K., Canada, Germany, and Japan. But Alicia Martin of the Broad Institute hopes the U.S. repository will be the most valuable resource of its kind for the study of disease’s genetic and environmental roots, given the nation’s size, diversity, and patchwork healthcare system.

In this edited conversation with the Gazette, Martin explains the value of such a resource in a country that’s home to over 342 million genomes and counting.

I know you didn’t work on this project directly but what excites you about “All of Us”?

No, I wasn’t directly affiliated with the project. I would love to give some kudos to some colleagues — like Stacey Gabriel, Niall Lennon, Heidi Rehm, and the team they led at the Broad Institute — who’ve done an enormous amount of work to generate this data, including the majority of the whole-genome sequencing.

I’m a population and statistical geneticist, so I work on large-scale biobanks around the world to understand the genetic, phenotypic, and social determinants of health that impact disease risk overall. So mostly I’m excited as a researcher who’s using the “All of Us” database.

It’s been around a quarter-century since scientists — including Eric Lander, founding director of the Broad Institute — first “mapped” the human genome. How does a database like “All of Us” build on that work?

We’re way beyond where we were with the Human Genome Project. There, for $3 billion, we sequenced one genome — that’s three billion base pairs of DNA. Here, we have the full genomes of over half a million individuals, deeply sequenced.

And this is an incredibly comprehensive resource, so it also includes electronic health records that are longitudinal, allowing us to understand a disease’s course and trajectories, rather than simply who has a disease now. And it includes multi-omic data.

What does it mean for the bank to contain multi-omic data?

Well, in high school biology, you might have learned the central dogma that DNA makes RNA makes protein. Your DNA is fixed from birth.

But other parts of the “multi-ome” are dynamic. They change throughout your life course, and they differ depending on your cell types, what age you are — all sorts of things. So your multi-ome is a much more comprehensive capture of what’s happening in your body at any given time.

“A resource like ‘All of Us’ will be beneficial for treating everybody, even if a given discovery was made using a subpopulation in the bank.”

There are, by now, many biobanks operating around the world — the U.K.’s is famous, for example. What is different about this one?

It’s true that global biobanks are abounding, and each one is really a national treasure, given how much they can teach us about disease biology. You mentioned the UK Biobank, and that has an amazing amount of whole-genome sequencing, whole-exome, other multi-omic data as well, in addition to an incredible depth of electronic health records going back decades.

But “All of Us” has a unique focus on drawing on representative populations from the U.S. And the unique thing about the U.S. is that our ancestors come from all over the world. With that, we’re able to identify novel biology that we wouldn’t necessarily see if we were only studying populations in the U.K., say.

One of the poster children of the genomic drug development pipelines is PCSK9 inhibitors, which lower LDL cholesterol levels. And they’re a proof of the power of representative genetic study. They came out of discoveries for loss-of-function variants that were identified at much higher frequencies in African American populations, in a few thousand individuals in the Dallas Heart Study. It took far, far larger numbers of individuals of European ancestry to validate that loss-of-function finding in large biobanks elsewhere.

So this is not necessarily just about knowing how to treat a specific subpopulation for specific diseases. In fact, a resource like “All of Us” will be beneficial for treating everybody, even if a given discovery was made using a subpopulation in the bank.

In many cases, the genetic mutations that increase risk of a disease are not sure things — the mutated gene may interact with other exposures or conditions so that the disease takes root, or it may not.

Can a biobank heighten our level of granular understanding, to know about all that a given participant’s life that might have caused or prevented health problems?

I think resources like this are so valuable because they’ll push really hard on what we’d call the “exposomics” space: In other words, all of the things you’ve been exposed to in your life that, as you said, can combine with genetics to affect your total disease risk.

For example, when we study proteomics — the proteins your body produces based on genetic instructions — we can develop a quantitative, objective measure of, say, how much you’ve smoked over your life course, and how the cumulative biological load of that affects your overall disease risk. Same with alcohol use, or pollution exposure through PM2.5 measures.

And in the end, you can integrate all of that information to try to understand better. And conversely, sometimes people can have very protective lifestyles or habits that mitigate their underlying genetic predispositions toward disease.

We’re interested not just in whether someone gets a disease, but whether and how that disease progresses, or whether they respond to therapeutics. And all of those things are to some extent informed by the new types of data that “All of Us” has released.

This would seem to have a new usefulness as gene therapies begin to become more commonplace.

Yes. We have these incredible examples of biomedical successes. Like Victoria Gray — an amazingly brave woman, a sickle-cell patient — who got the first CRISPR gene-editing therapy. She underwent clinical trials with CRISPR editing in 2019, and that paved the way for Casgevy [a gene therapy used to treat sickle-cell disease and beta thalassemia, both inherited blood disorders].

Or Baby KJ, who had an incredibly rare mutation — one in more than a million babies — that is lethal in about half of infants. He had personalized CRISPR editing therapy that effectively cured him. He got to graduate from the NICU.

But those involved millions of dollars of therapy for treatment of a single individual, and treatment that might only work in a subset of patients. “All of Us” can help us quickly identify that subset of patients for a given disease, and we can turn it into a learning platform that teaches clinicians which patients they should be on the lookout for, to target these therapeutics to the patients who need the treatment and who will respond.

You could see how a national biobank would be much easier to build in a country with a national health service of some sort: standardized forms, standard procedures, just one bureaucracy to deal with. How did this get done in the U.S., with its private healthcare providers, private and religious hospitals, not to mention the rural and military and Indigenous contexts?

The team of researchers behind “All of Us” took electronic records as they were. And you’re right — it’s inherently incredibly messy in this country, which has a highly fragmented approach to healthcare. We have to take everyone at their word.

But wherever people are getting care, that generates diagnostic and billing codes. And you can use billing codes to try to understand genetic predispositions to all sorts of diseases.

For example, you know who has Type 2 diabetes, since that’s been diagnosed in their health record previously. And I want to applaud participants, who were — I think — exercising a high degree of beneficence by allowing us to see their entire health records, sharing a lot of personal information. We owe them.