October 18, 2016

DNA changes predict longevity

At a Glance

  • Certain DNA changes can better predict a person’s life expectancy than traditional risk factors such as age.
  • The findings could lead to novel insights into the molecular mechanisms of aging and new ways to evaluate methods for slowing the rate of aging.
Woman at three different stages of life. “Epigenetic age” might represent a person’s biological age more accurately than the number of years they’ve lived.KatarzynaBialasiewicz/iStock/Thinkstock

Our DNA changes as we age. Some of these changes are epigenetic—they modify DNA without altering the genetic sequence itself. Epigenetic changes affect how genes are turned on and off, or expressed, and thus help regulate how cells in different parts of the body use the same genetic code. Previous studies have shown that levels of one type of epigenetic modification, called DNA methylation, roughly reflect a person’s age.

Recent work suggests that epigenetic age might also be associated with health outcomes independent of chronological age. Dr. Steve Horvath from the University of California, Los Angeles, and his colleagues set out to investigate the relationship between epigenetic age and mortality.

The researchers analyzed DNA in blood samples from more than 13,000 people, including non-Hispanic whites, Hispanics, and African Americans. Many of the samples came from large NIH-funded studies, including the Framingham Heart Study and the Women’s Health Initiative. The researchers were funded in part by NIH’s National Institute on Aging (NIA). The team also included scientists from NIA and NIH’s National Heart, Lung, and Blood Institute (NHLBI). The study appeared on September 28, 2016, in Aging.

The researchers tested different models of epigenetic age. Different cell types—even similar ones like various blood cell types—have different epigenetic patterns. As people get older, the mix of immune cells in their blood shifts. When these age-related changes to blood cell composition were factored in, the researchers’ epigenetic age model predicted mortality from all causes better than previous measures of epigenetic age. The relationship between epigenetic age and mortality was significant within both sexes and across all the ethnic groups in the study.

“Our findings show that the epigenetic clock was able to predict the lifespans of Caucasians, Hispanics, and African-Americans in these cohorts, even after adjusting for traditional risk factors like age, gender, smoking, body-mass index, and disease history,” says NIA’s Dr. Brian Chen, the study’s first author.

These results support the notion that epigenetic age captures some aspect of biological aging over and above chronological age and other risk factors. “Our research reveals valuable clues into what causes human aging, marking a first step toward developing targeted methods to slow the process,” Horvath says.

The precise roles that epigenetic factors play in aging and death remain unknown and require further study. It’s important to note that many risk factors, including smoking, diabetes, and high blood pressure, have stronger effects on mortality than epigenetic age.

—by Harrison Wein, Ph.D.

Related Links

References: DNA methylation-based measures of biological age: meta-analysis predicting time to death. Chen BH, Marioni RE, Colicino E, Peters MJ, Ward-Caviness CK, Tsai PC, Roetker NS, Just AC, Demerath EW, Guan W, Bressler J, Fornage M, Studenski S, Vandiver AR, Moore AZ, Tanaka T, Kiel DP, Liang L, Vokonas P, Schwartz J, Lunetta KL, Murabito JM, Bandinelli S, Hernandez DG, Melzer D, Nalls M, Pilling LC, Price TR, Singleton AB, Gieger C, Holle R, Kretschmer A, Kronenberg F, Kunze S, Linseisen J, Meisinger C, Rathmann W, Waldenberger M, Visscher PM, Shah S, Wray NR, McRae AF, Franco OH, Hofman A, Uitterlinden AG, Absher D, Assimes T, Levine ME, Lu AT, Tsao PS, Hou L, Manson JE, Carty CL, LaCroix AZ, Reiner AP, Spector TD, Feinberg AP, Levy D, Baccarelli A, van Meurs J, Bell JT, Peters A, Deary IJ, Pankow JS, Ferrucci L, Horvath S. Aging (Albany NY). 2016 Sep 28;8(9):1844-1865. doi: 10.18632/aging.101020. PMID: 27690265.

Funding: NIH’s National Institute on Aging (NIA) and U.S. Department of Veterans Affairs.