Gene that Influences When You Wake Also Predicts Time of Death

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Researchers have identified a common gene variant that is responsible for a person’s tendency to be an early riser or a night owl. This common genetic variant also helps determine the time of day a person is most likely to die. The findings appear in the November 2012 issue of the Annals of Neurology.

Body clock

A person’s internal circadian clock regulates many aspects of human biology and behavior, such as metabolic changes, cognition and sleep. It also can influence the timing of acute medical events such as stroke or heart attack. Previous research suggests that the timing of a person’s internal clock may be influenced by specific genes.

Investigators from Beth Israel Deaconess Medical Center and Brigham and Women’s Hospital, both in Boston performed a gene association study, comparing the wake-sleep behavior of 1,200 healthy 65-year-olds with their DNA genotypes. They discovered that a single nucleotide polymorphism or SNP (pronounced “snip”) near a gene called Period 1 (PER1) varied between two groups that differed in their wake-sleep behavior.

SNPs (pronounced “snips”) are DNA sequence variations that occur when a single nucleotide — A, T, C or G — in the genome is changed, producing different alleles (meaning sequences that code for the same gene).

At the site, 60% of subjects had an adenine nucleotide (A) and 40% had a guanine nucleotide (G). Because everyone has two sets of chromosomes, in any given individual, there’s a ~36% chance of having two As, a ~16% chance of having two Gs, and a ~48% chance of having one chromosome with an A and the other chromosome with a G at the site.

People who have two As — the A-A genotype — wake up about an hour earlier than the people who have two Gs — the G-G genotype. People with the A-G genotype wake up almost exactly in the middle. In addition, subjects with the G-G genotype had a lower level of daytime Period 1 gene expression in their brains and white blood cells than in people with the A-A genotype.

Almost all physiological processes have a circadian rhythm, the approximately 24-hour “body clock“.  In fact, there’s even a circadian rhythm of death; in the general population, people tend on average to die in the morning hours around 11 am.

When the researchers reviewed people in the study who had died, they found that this same genotype predicted six hours of the variation in the time of death: people with the A-A or A-G genotype died just before 11 a.m., like most of the population, but those with the G-G genotype died on average just before 6 p.m.

Lead author of the study, Andrew Lim, MD, an Assistant Professor in the Division of Neurology at the University of Toronto, said that additional work is needed to determine the mechanisms by which this gene variant influences the body’s biological clock. According to Lim [2]:

Working out which causes of death are influenced by gene variants like the one we identified may eventually lead to rational timed interventions—such as taking heart medications at particular times depending on which version of the gene variant one carries—to provide protection during an individuals’ period of greatest risk.

The research further suggests that work scheduling and the monitoring of vulnerable patient populations should be personalized to an individual’s genotype. Additional study may help to develop therapies to treat disturbances of a person’s body clock, such as jet lag or shift work.


  1. Lim et al. A common polymorphism near PER1 and the timing of human behavioral rhythms. Ann Neurol. 2012 Sep;72(3):324-34. doi: 10.1002/ana.23636.
    View abstract
  2. Gene That Distinguishes Early Birds from Night Owls Also Predicts Time of Death. Beth Israel Deaconess Medical Center press release. 2012 Nov 16.
About the Author

Walter Jessen, Ph.D. is a Data Scientist, Digital Biologist, and Knowledge Engineer. His primary focus is to build and support expert systems, including AI (artificial intelligence) and user-generated platforms, and to identify and develop methods to capture, organize, integrate, and make accessible company knowledge. His research interests include disease biology modeling and biomarker identification. He is also a Principal at Highlight Health Media, which publishes Highlight HEALTH, and lead writer at Highlight HEALTH.