Why does it seem like some people can eat all the ice cream they want without increasing their cholesterol or gaining much weight, while others with high cholesterol have to watch their diets like a hawk? Because no matter what their lifestyle, people’s genes play an overriding role in their cholesterol response.
So says a new study by researchers at the Department of Energy’s Lawrence Berkeley National Laboratory and the Children’s Hospital Oakland Research Institute (CHORI), conducted by Paul Williams of Berkeley Lab’s Life Sciences Division in collaboration with Robin Rawlings and Patricia Blanche of CHORI and Ronald M. Krauss of CHORI and Berkeley Lab’s Genomics Division. They report their findings in the July 8, 2005, issue of the American Journal of Clinical Nutrition.
The investigators analyzed how “bad” cholesterol (low-density lipoprotein, or LDL, cholesterol) responded to diets that were either high or low in fat in 28 pairs of identical male twins — one twin a vigorous exerciser, the other a comparative couch potato.
“Although identical twins share exactly the same genes, we chose these twins because they had very different lifestyles,” says Williams. “One member of each pair was a regular long-distance runner, someone we contacted through Runner’s World magazine or at races around the country. His brother clocked 40 kilometers a week less, at least, if he exercised at all.”
For six weeks the twins ate either a high-fat diet (40 percent of its calories from fat) or a low-fat diet (only 20 percent of its calories from fat); then the pairs switched diets for another six weeks. After each six-week period the twins’ blood cholesterol levels were tested.
The researchers were interested in learning if blood cholesterol changes due to the different diets would be the same or different in each pair of genetically identical twins, even though their lifestyles were very different. A correlation of zero between the two would mean that their responses to the diets had no relation to each other, while a correlation of 1.0 would mean that their responses were identical.
The researchers found an astounding 0.7 correlation in responses to the change in diet, an incredibly strong similarity in the way each pair of twins responded — even though the responses themselves among different pairs of twins differed considerably.
“If one of the twins could eat a high-fat diet without increasing his bad cholesterol, then so could his brother,” says Williams. “But if one of the twins’ LDL cholesterol shot up when they went on the high-fat diet, his brother’s did too.”
The correlations showed that the twins had very similar changes in LDL cholesterol because they had the same genes. Some twins had one or more genes that made them very sensitive to the amount of fat in their diets. Other twins had genes that made them insensitive to dietary fat, no matter how much they exercised.
“Our experiment shows how important our genes are,” says Williams. “Some people have to be careful about their diets, while others have much more freedom in their dietary choices.”
He adds, “This type of experiment allows us to test whether genes are important without having to identify the specific genes involved.” Although several specific genes have been associated with cholesterol changes in response to changes in diet, these cannot account for the large correlations seen in this study. Williams hopes his findings will inspire additional research to identify the specific genes involved.
“Concordant lipoprotein and weight responses to dietary fat change in identical twins with divergent exercise levels,” by Paul T. Williams, Patricia J. Blanche, Robin Rawlings, and Ronald M. Krauss, appears in the July 8, 2005, issue of the American Journal of Clinical Nutrition. The work was supported by Dairy Management Incorporated, with additional support from the National Institutes of Health.
Berkeley Lab is a U.S. Department of Energy national laboratory located in Berkeley, California. It conducts unclassified scientific research and is managed by the University of California. Visit our website at http://www.lbl.gov.
From Lawrence berkeley Laboratory