Genetic Testing for Obesity Risk May Not Translate to Weight Loss
A new study in JAMA Cardiology finds that genetic testing to identify those at high risk for obesity has not translated into weight loss, suggesting it is better to focus on body mass index (BMI), a measure of weight and height.
Researchers from the Michigan Medicine Frankel Cardiovascular Center and the Massachusetts General Hospital Cardiovascular Research Center found that more traditional tools help individuals best combat obesity.
“We found fitness is a better predictor than genetics of where your BMI will go over time,” said lead author Venkatesh Murthy, M.D., Ph.D., a cardiologist at the Frankel CVC. “Genetics clearly has some influence, but other factors are stronger.”
Murthy’s research discovered a person’s BMI measurement from 25 years ago was a better predictor of their current BMI than a polygenic risk score.
“There’s been a lot of attention to the idea of using genetic information to understand your risk of obesity or being overweight, and for potential drug development to address those genetic risks,” says Murthy.
“We wanted to understand how, if at all, genetic data would add to the information already routinely available in clinic. It turns out, our standard clinical exam, including an assessment of BMI, actually has vastly more information to help guide patient care.”
Alongside senior author Ravi Shah, M.D., from the Massachusetts General Hospital, Murthy’s new research evaluated 25 years of health data from a National Institutes of Health-sponsored study. More than 2,500 young adults from across the United States participated in a longitudinal study, CARDIA (Coronary Artery Risk Development in Young Adults). Data was collected between 1985 and 2010 to explore the development of cardiovascular disease.
Murthy, Shah and colleagues used a modern “polygenic risk score” (a composite measure of genetic risk of obesity) to calculate genetic risk of obesity for each person in their subset of the CARDIA study and compare it to the measurements taken during the 25 years of the study.
Baseline BMI in young adulthood explained 52.3 percent of a person’s BMI 25 years later when it was considered in combination with age, sex and history of a parent ever being very overweight. The prediction could explain up to around 80 percent of BMI variation after following someone’s BMI over time, rather than just at baseline and 25 years later.
Those same combinations of age, sex and parental weight history, when considered with a polygenic risk score instead of BMI, were also associated with BMI but in a weaker association that only explained 13.6 percent of BMI in midlife.
The PRS was also more effective at predicting future BMI in the 1,608 white individuals than the 909 black individuals. Murthy noted there’s more genetic data available in European populations for constructing genetic risk profiles, leading to some concern about methodology for determining polygenic risk scores for non-white patients.
Murthy said these data serve as a reminder that human genetics might be interesting in large population studies, but that caution is still needed toward incorporating them when providing clinical care and advice to patients.
However, he noted that clinicians are seeing more and more patients who have already purchased a genetic report from a direct-to-consumer company and want to go over it with their doctor. It’s important for clinicians to be aware of the strengths and limitations of those direct-to-consumer products, Murthy urges.
He said the rising interest in genetic risk scores also brings up the idea of how incorporating them into clinical practice could change behavior. If someone is told they were born more likely to become obese, for example, how will that change their behavior today or this year, or 25 years down the road?
Conversely, will people who learn they’re less disposed to obesity become more motivated to lose that stubborn weight that’s been difficult to shed?
“We don’t know those answers very well yet,” Murthy says. “However, some data says, whether based on a real genetic score or not, people may perform better in fitness tests if they’re told they’re genetically more likely to be fit.”
The good news is that calculating your BMI, which Murthy said is a useful marker for most people who aren’t elite athletes, is significantly more affordable than purchasing a genetic test.
Physicians should already have weight and height records for their patients over time, Murthy said, and the conversations around modifiable risk factors relating to BMI should already be happening during patient visits.
Source: University of Michigan