Large-scale exposome research shows how multiple factors influence disease risk

For decades, scientists have been carefully unraveling the role of genes in disease by examining how small variations in a person's genetic code can shape lifelong risk of developing common conditions such as cancer, diabetes, or heart disease.

But genetics only tell part of the story.

The other part comes from all the external and internal exposures a person experiences during their lifetime, which can range from pollution to infections to diet and lifestyle. Cumulatively, these exposures - and the body's biological response to them - make up what scientists have termed the exposome.

 A team led by scientists at Harvard Medical School has now conducted what may be the largest-scale study to date to quantify the relationships between exposures and health outcomes, testing more than 100,000 associations. The work demonstrates the importance of studying potential environmental disease risks in aggregate rather than one at a time.

Analyzing preexisting survey data from U.S. populations, the researchers found that individual exposures had only a moderate impact on health outcomes - but that this impact increased when considering multiple exposures at the same time.

While one single exposure might not make a massive difference in your health, the cumulative soup of exposures can be just as powerful as your DNA in determining your risk of certain diseases."

Chirag Patel, first author, associate professor of biomedical informatics, Blavatnik Institute at HMS

The findings, published March 18 in Nature Medicine, demonstrate the value of using existing data for exposomics research and highlight the need for more large-scale studies to pinpoint which combinations of exposures have the greatest impact on human health and disease.

The hope is that a deeper understanding of the human exposome will yield insights that researchers, clinicians, and patients can use to improve health at the individual level.

Borrowing a blueprint

Patel and senior author Arjun (Raj) Manrai, assistant professor of biomedical informatics at HMS, trace their entry into exposome research to their interest in precision medicine - a field devoted to developing disease treatments tailored to individual patients.

"To date, the field has been imbalanced. More has been done on the side of using genetics to individualize treatment, and not much has been done on the side of environmental exposures," Patel said.

Manrai noted that while many studies have looked at a single exposure and health outcome, this one-at-a-time approach often leads to conflicting findings - for example, about whether any random ingredient found in a cookbook is harmful, beneficial, or unimportant for human health.

Patel and Manrai saw a need for a comprehensive study that systematically and simultaneously examined the relationships between many environmental exposures and health outcomes.

"We really wanted to build a robust, large-scale compendium of these associations for the exposome," Manrai said.

To do so, Manrai and Patel teamed up with John Ioannidis, a physician-scientist at Stanford University who specializes in meta-research and large-scale analyses.

The team borrowed a blueprint from genetics research, which is known for comprehensive studies such as genome-wide association studies (GWAS) that scan the entire genetic code for disease links.

In fact, Patel and Manrai are part of the Network for Exposomics in the United States  and the Human Exposome Project, the latter of which was conceived in the vein of the Human Genome Project. 

Exploring the exposome

In the new study, the researchers analyzed 20 years of existing data from the National Health and Nutrition Examination Survey (NHANES) conducted annually by the Centers for Disease Control and Prevention.

They tested more than 115,000 associations between 619 environmental exposures and 305 clinically relevant health outcomes. Exposures encompassed things like pollutants and nutrients, whereas health outcomes included things like body mass index, blood sugar level, and lung function.

The team identified more than 5,600 associations that were considered statistically significant.

Single exposures explained less than 1 percent of the variation in health outcomes between people across hundreds of health outcomes. Considering up to 20 exposures at once boosted this explanatory power to an average of 3.5 percent across 120 health outcomes - comparable to the contribution of some individual genetic variants.

The results revealed a few especially strong associations between exposures and outcomes. For example, a mix of 20 particular exposures - including trans fats, common pollutants called polychlorinated biphenyls, and vitamin E levels - explained 43 percent of the variation in people's triglyceride levels, which is a risk factor for heart disease.

The researchers emphasized that although there was a wide range of explanatory power, most combinations of exposures explained only a modest amount of the variation between people.

"On the whole, there's no smoking gun; every exposure seems to matter a little bit, and exposures matter more when you consider them in aggregate," Patel said.

A jumping-off point

The study provides "a snapshot of exposure" that can serve as a jumping-off point for future exposome research, the researchers said.

Patel and Manrai want to expand to even more environmental exposures and health outcomes and explore connections between earlier exposures and disease later in life.

They are also interested in whether and how information about exposures should be incorporated into tools clinicians use to assess a patient's risk of developing conditions such as heart disease and tools patients use to navigate their own health.

So that other research groups can further investigate connections the study revealed, the team has made its data and software freely available online to other research groups in The Phenome-Exposure Atlas of Health and Disease Risk. 

"Large-scale analyses like this are an agnostic, systematic way of generating hypotheses, but we then need to conduct detailed mechanistic evaluations of exposures and their associations with disease to determine causation," Manrai said. "We're zooming out to figure out where to zoom back in."

The potential of applying exposomic insights to safeguard health is especially relevant in an era when many people wear devices that continuously monitor a wide range of health metrics, the authors said.

"It may seem like a pie-in-the-sky, Star Trek-y vision, but I see a future where exposomic information is integrated into these systems with AI so that a person can understand, in real time, how exposures may be impacting their day-to-day or even hour-to-hour health," Patel said.