ADVERTISEMENT
latest stories:

New Mass-Screening Method Finds Additional Environmental Risks for Diabetes

The first environment-wide association study borrows from genomics to reveal new leads in major complex diseases
environmental wide association study disease genetic



ISTOCKPHOTO/BRYTTA

With a scan through a sample of genomes from several individuals, researchers can tease out links among genetic variations and particular diseases. These genome-wide association studies have clarified some of the genes involved in predisposing people for  rheumatoid arthritis, bipolar disorder, Crohn's disease, diabetes and other disorders, paving the way for new study and better treatments.

For many complex diseases, however, genetics tell only part of the story. Environmental factors, such as diet and chemical exposure, have become increasingly obvious players in determining a person's risk of various diseases. But these environmental exposures have long been regarded as too nuanced and variable to measure with the same specificity as genetics.

A team of researchers at Stanford University is hoping to change that. In a study, published online May 20 in the journal PLoS ONE, they describe a new, environmental-based risk factor screening for type 2 diabetes, a technique they have dubbed environmental-wide association study (or EWAS, after GWAS, which stands for genome-wide association study). It promises to uncover new environmental links for this disease and others.

"Everyone's been focused on the genetic causes of the disease," says Atul Butte, an assistant professor of biomedical informatics and pediatrics at Stanford. But, he notes, lately "people are dissatisfied with the little amount of risk we can explain with genetics."

Genetic flags for type 2 diabetes, from which 23.6 million people in the U.S. suffer, have failed to explain away much of an individual's apparent risk. And even though macro lifestyle factors, such as high sugar intake and little exercise, have been shown to increase a person's risk for diabetes, Butte and his colleagues were not satisfied. "Are we that sure nothing else in the environment is playing a role in diabetes?" he asks.

According to their new analysis of 266 environmental variables and the presence of type 2 diabetes in thousands of individuals who participated in a national health survey, Butte and his team were able to confirm suspected links, including PCBs (polychlorinated biphenyls, which are now banned in the U.S. but can still be found in old capacitors, fiberglass and adhesives), and also uncover new ones, such as a pesticide product and a common form of vitamin E.

Bioinformatics for the environment

The environmental components people come into contact with throughout their lives are basically endless, so assessing an individual's total history of exposure might seem impossible. But with data from the National Health and Nutrition Examination Survey (administered by the U.S. Centers for Disease Control and Prevention), Butte and his colleagues were able to get solid information on environmental factors (measured from blood and urine samples and logged in databases) and individuals' health, disease diagnoses and fasting blood sugar levels (an indicator that can show the presence of diabetes).

Though the studied list of environmental factors is by no means exhaustive, the chemical variables can be analyzed along the same lines as selected single-nucleotide polymorphisms (SNPs) that geneticists run on a genetic chip. "They can't put every variant on there," Butte says of genomic researchers. But when a scan does pick up a particular SNP, it might represent dozens of others that were not specifically being tested. So rather than providing a comprehensive list, both genetics and the EWAS model can detect a signal that indicates "we should be looking at that entire category" of chemicals or SNPs, he says.

The project came about as an idea from a Stanford graduate student, Chirag Patel, the lead author on the study, who approached Butte wanting to find a way "to use bioinformatics for the environment," Butte explains.

Patel created a specialized computer program to assess the relevant information gathered from the CDC's health survey databases. After controlling for age, sex, body mass index, ethnicity and socioeconomic status, the group found that those with high levels of PCBs had a 15 percent chance of having type 2 diabetes, a correlation that had been shown in previous studies. They also found that high levels of beta-carotene seemed to have a protective effect, reducing risk of having diabetes by about 9 percent (another link that had been seen in other studies, though had not been proven in clinical trials).

The big surprises came from a chemical previously found in pesticides and a common form of vitamin E—levels of which seemed to influence the chances that an individual would have diabetes. Heptachlor epoxide is derived from a pesticide that was banned in the U.S. in the 1980s. It is still found in soil and water supplies and can turn up in food and be passed along in breast milk. High levels of it seemed to increase type 2 diabetes risk to about 7 percent. And having low levels of the gamma-tocopherol form of vitamin E, found in fruits, nuts and vegetables, seemed to improve the chances an individual would not have type 2 diabetes by 7 percent.

The links uncovered through EWAS do not prove that exposure to PCBs or eating more fruits increases a person's risk for getting diabetes. Causation can only be established through longitudinal studies that follow individuals over long periods of time. These links could signify biological differences in how those in the disease population process or deal with various compounds. Further research both in laboratory and population-based studies will be necessary to better understand the nature of these links, notes Butte. 

New leads
Like scanning genetic microarrays, this mass assessment of environmental risk factors can uncover new links that researchers might not have thought to investigate. Many chemicals and compounds have already been linked to diseases, such as with asbestos and cancer, or vitamin D deficiency and osteoporosis, but by hunting through a broad range of exposures, new links could help lead the way toward better understanding of biological mechanisms behind diseases as well as better treatment and prevention.

"This gives us a clue that we should be studying that particular chemical more closely," Butte says.

This level of study also paves the way for a more unified investigation of environmental and genetic factors in the future. "A lot of these factors do interact with each other," Butte says. But, he cautions, "the interrelationships are incredibly complex." Although Butte does not expect that his team's analytic system will be immediately integrated with genome-wide association studies, he and his colleagues noted in their study that "the results from EWAS can better inform about environmental factors that need to be measured in genetic studies to begin to provide us insight in regards to disease etiology."

Catching up to genetics
Epidemiologists have been investigating the connection between environmental exposures and disease for decades, but, notes Butte, they have depended largely on specific events, such as chemical spills or other disasters, and then looked for spikes in different conditions. Researchers were thus largely stuck investigating environmental factors "the same way genetics was 15 years ago—one by one," he says.

With mass, population-based assessments, that could change, both in the speed and breadth of figuring out environmental roles in disease.

Butte hopes that biotech companies will soon be producing chips to run parallel screening for environmental factors, akin to genetic chips that can now be run rapidly and cheaply. The biological assessments are done using relatively simple analyses of blood and urine samples, which means that, "a lot of these tests could be done on a parallel method," Butte says.

The goal, he says is "to elevate the study of environment to where genetics is."

But the gap between the two fields might be closing anyway, as the number of variables on the genetic side, with epigenetics and other subtler dynamics, seems to grow every day.

In the meantime Butte and his team are already turning EWAS loose on a number of other complex, common conditions, including cholesterol and lipid levels. They are already noticing separate spikes for different environmental exposures between different cholesterol and lipid levels, some of which are "incredibly intriguing," he says. 

The results from the new assay underscore the need for more collaboration between environmental and genetic epidemiologists, according to Butte. He and his colleagues concluded in their paper that the findings "demand a rethinking and restructuring" of how genetics and environment are studied in the context of disease risk. "The time is ripe," they wrote, "to usher in 'enviromics'."

Rights & Permissions
Share this Article:

Comments

You must sign in or register as a ScientificAmerican.com member to submit a comment.
Scientific American Holiday Sale

Limited Time Only!

Get 50% off Digital Gifts

Hurry sale ends 12/31 >

X

Email this Article

X