The Fingerprints of Diabetes…and Other Diseases
If exercise is such a bellwether of health, and one’s metabolic profile reflects fitness and well-being, might the opposite also be true? Could there be metabolic signatures associated with human disease? To find out, Robert Gerszten of Harvard Medical School (HMS) teamed with fellow associate professor of medicine Thomas J. Wang, a cardiologist at Massachusetts General Hospital affiliated with the Framingham Heart Study, to see whether metabolic signatures might presage the onset of disease. They began with diabetes, the most metabolic of diseases, in which the body loses its ability to control blood sugar.
“The Framingham study, the seminal study that identified risk factors associated with heart disease, was begun in 1948,” Gerszten explains. “Researchers followed these people epidemiologically: participants would come religiously every couple of years, give blood, and be subjected to a number of different tests.” Such longitudinal studies are considered the gold standard in research because they follow a large population over a long period of time and eliminate “selection bias”: in this case, the participants were chosen solely on the basis of geography (they all lived in Framingham, Massachusetts), not because of preexisting health conditions, race, gender, or some other factor. In 1948, none of the participants knew whether they would develop a disease.
In 1972, more than 3,000 of the original participants’ offspring were also enrolled in the study. “Over time, the phenotyping or characterization of these people got more and more sophisticated,” Gerszten says. Researchers had begun to do “CT scans, exercise tests, and so on. What Tommy [Wang] pointed out to me was that in 1994 everyone underwent a stress test for diabetes.”
The OGTT (oral glucose tolerance test) delivers a high dose of sugar in the form of glucose and then measures the body’s ability to respond. Although glucose is “one of the last things to go wrong” during the onset of the disease, the test is still the best way to diagnose prediabetes and diabetes. Using blood samples taken in 1994 from 200 people who later developed diabetes, and a matched group who shared all the same risk factors but did not develop the disease, Gerzsten and Wang tried to detect differences in the metabolic responses of the two groups to the oral glucose challenge years before any of the diabetic group became ill. They hoped that one or more of the amino acids in the blood samples would reveal a difference that might identify those individuals who were going to get diabetes a decade or more later.
“We matched [the prediabetic subjects] to controls chosen on the basis of age, body mass index, fasting glucose, and whether or not they had hypertension,” says Gerszten. “This was by design. We didn’t want to compare fat people to thin people, because that would not add information. We raised the bar as high as you could raise it” by excluding thin, fit people outright from the study population. “People who develop diabetes are also likely to have a higher fasting glucose level but we wanted to make glucose equal” to see if anything else was affecting the response.
“We were struck by what we saw,” he reports. “There were some unbelievably significant differences at baseline in the blood.” Six amino acids were higher in the people who became diabetics than in the controls. Isoleucine, leucine, and valine, as well as phenylalanine, tyrosine, and tryptophan, were elevated. “It turns out that these are the most greasy, hydrophobic amino acids,” Gerszten says. Individuals in the top quartile—those in whom these amino acids were highest—were more than 400 percent more likely to develop diabetes. In contrast, the common genetic variants associated with diabetes risk represent just a 20 percent increase in the chance of getting the disease, he explains. “This is an order of magnitude more.”
“These changes [later replicated in a population from Malmö, Sweden] are occurring a dozen years before people develop diabetes, says Gerszten, who justifiably refers to the findings as the highlight of their biomarker research so far. “Many people have realized the importance of metabolism. But to use it on an equal footing with genetics? Not so many people think so yet.” He and his colleagues are now trying to duplicate the diabetes research using lipids (circulating fats) rather than amino acids. And they are working to find markers that will identify individuals at risk of developing heart and kidney disease in the future.
This is important, Gerszten notes, because if the results prove generalizable, physicians will know where to intervene. For example, a study by professor of medicine David M. Nathan demonstrated that either intensive lifestyle interventions (including diet and exercise) or use of the drug metformin can prevent diabetes. “Now,” says Gerszten, “you could identify and focus on those populations most at risk, and get more bang for your buck.”
Gerszten and his colleagues believe that they can now identify at least one representative metabolite from every known metabolic pathway in humans. But the library of metabolites and metabolic signatures of disease that he and his colleagues are assembling is not what intrigues him most. Each metabolite is a stepping stone in a pathway that leads to health or disease, and Gerszten is less interested in the biomarkers themselves than in finding pathways leading to new insights that might cure diseases. “We still don’t really have a clue, for example, why diabetes leads to heart disease,” he points out. “These amino acids are altering some fundamental metabolic response in cells and we just don’t know what it is—yet.”