Current BMI predicts future BMI better than polygenic risk score
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Using a polygenic risk score to project BMI progression into middle age may yield inferior results compared with using BMI earlier in life, according to findings published in JAMA Cardiology.
“The prevention of obesity is of major importance in modern medical care,” Ravi V. Shah, MD, assistant professor of medicine in the cardiology division of the department of medicine at Massachusetts General Hospital in Boston, told Healio. “Understanding what influences weight gain is important so we can work to better treat obesity and its complications.”
Shah, Venkatesh L. Murthy, MD, PhD, associate professor of cardiovascular medicine at the in the department of medicine and Frankel Cardiovascular Center at the University of Michigan, and colleagues compared BMI calculated at baseline and 25 years later for 1,608 white participants (mean age, 25.6 years at baseline and 50.8 years at 25 years; 52.7% women) and 909 black participants (mean age, 24.4 years at baseline and 49.4 years at 25 years; 60.3% women) participating in the Coronary Artery Risk Development in Young Adults (CARDIA) study. The researchers also noted baseline measures of cardiorespiratory fitness and physical activity score and whether participants’ parents had been overweight, and they also incorporated the polygenic risk score.
The researchers found that 13.6% of 25-year BMI for white adults was explained by a combination of the polygenic risk score with age, sex and the overweight status of participants’ parents while 52.3% of variance was explained by a combination of baseline BMI with age, sex and the overweight status of participants’ parents and 81.3% of variance was explained by the total BMI history of participants combined with age, sex and the overweight status of their parents.
In a separate analysis restricted to black participants, 13% of 25-year BMI was explained by a combination of the polygenic risk score with age, sex and the overweight status of participants’ parents while 51.7% of variance was explained by a combination of baseline BMI with age, sex and the overweight status of participants’ parents and 80.9% of variance was explained by the total BMI history of participants combined with age, sex and the overweight status of their parents.
“Although we present our findings for both white and black participants in the CARDIA study, the original polygenic risk score was derived in a largely European population,” the researchers wrote. “Therefore, further race-specific studies to understand the role of genetics in BMI is warranted.”
The researchers also wrote that the polygenic risk score had “poor predictive precision” unless it was combined with baseline BMI, “suggesting that the models with baseline BMI explained a much greater amount of variation in midlife BMI than the polygenic risk score.”
“One key message is that although physical activity and fitness are critical for maintaining a healthy body weight and for cardiovascular health generally, it is also important to monitor BMI with your physician,” Murthy said. “These data suggest that even as early as ages 18-30, people’s BMI has already put them on a lifetime path based on their lifestyle and genetics. Investigating further about how to develop healthy eating and fitness habits in children and teens will be an important part of bending the curve on obesity trends.”– by Phil Neuffer
For more information:
Ravi V. Shah, MD, can be reached at rvshah@partners.org;Twitter: @RaviShah_MD.
Venkatesh L. Murthy, MD, PhD, can be reached at vlmurthy@med.umich.edu; Twitter: @venkmurthy.
Disclosures: Shah reports he received research grants from the NIH, served as a consultant for Amgen, MyoKardia and Best Doctors and was a co-inventor for ex-RNA signatures of cardiac remodeling. Murthy reports that he has stock in General Electric and Cardinal Health, stock options in Ionetix scientific; provided scientific advisory for Ionetix and Curium and expert witness testimony for Curium; served as a paid speaker for Siemens Medical Imaging; received research grants from Siemens Medical Imaging and Singulex and non-financial research support from INVIA Medical Imaging Solutions. Please see the study for all other authors’ relevant financial disclosures.
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