1. New Evidence That Protective Effects of Familial Longevity Expire at Older Ages
Leonid A. Gavrilov, Natalia S. Gavrilova, Vyacheslav N. Krut'ko*
NORC at the University of Chicago, Chicago, IL, United States
ABSTRACT
This study presents new findings that challenge a common belief in sustained protective effects of familial longevity during the human life course. We found that the survival advantage of biological relatives of long-living individuals vanishes at older ages, suggesting that protective effects of longevity assurance genes disappear at age years. We compared survival patterns of 3,664 siblings of U.S. centenarians with survival of a control group of 4,078 siblings of shorter-lived individuals (died at age 65 years). Survival analysis after age 40 years was conducted separately for 4,201 male and 3,541 female siblings born in Although siblings of long-lived individuals have lower mortality at younger ages compared to siblings of shorter lived individuals, their actuarial aging rate (rate of mortality growth with age) is consistently higher, so that their survival advantage practically disappears at older ages. To validate these findings, we analyzed data on survival of 3,408 U.S. centenarians born in with known information on maternal and paternal lifespan. We found that indeed both maternal and paternal longevity (lifespan 90+ years) have no protective effect on survival after age 100 years. These findings challenge predictions of the mutation accumulation theory of aging about higher survival advantage at older ages associated with familial longevity due to lower load of late-acting deleterious mutations. Our findings are compatible with predictions of the reliability theory of aging suggesting higher initial levels of system redundancy (reserves) in individuals with protective familial/genetic background.
METHODS
Database on Exceptional Longevity
About 4,000 records of centenarians born in the United States. Age of centenarians was validated using the Social Security Death Master File linkage (82% validated)
About 4,000 records of shorter-lived controls (died at age 65 years)
Both centenarians and controls have information about lifespan of parents
Both centenarians and controls have information about siblings, children, spouses, siblings-in-law and grandparents
RESULTS
Chart, graph, or photo
Survival of siblings with different levels of familial longevity
BACKGROUND
The Mutation Accumulation Theory of Aging (Medawar, 1946) predicts that the observed pattern of familial transmission of human lifespan is caused by higher equilibrium frequency of late-acting deleterious mutations at older ages (Medawar 1952).
Therefore, children born to long-lived parents should experience survival advantage mostly in their old ages (because they have less late-acting deleterious mutations).
Reliability theory of aging predicts that children born to long living parents will experience survival advantage mostly in their younger adult ages, because of higher redundancy in functional elements (cells) not yet exhausted over time (Gavrilov and Gavrilova 2006).
The third hypothesis suggests the life-long sustained mortality advantage for persons having protection of familial longevity (Perls et al. 2002).
I - siblings of shorter-lived persons (died at age 65)
II - siblings of centenarians
CONCLUSIONS
Familial longevity improves survival mostly at younger adult rather than older ages
Parental longevity has no significant effect on survival of centenarians
These findings support predictions of reliability theory of aging, but do not support predictions of the mutation accumulation theory of aging, as well as the hypothesis of life-long sustained mortality advantage.
Chart, graph, or photo
Mortality of women with different levels of familial longevity
Mortality of men with different levels of familial longevity
ACKNOWLEDGEMENTS
This work was partially supported by the U.S. National Institute on Aging (NG and LG), and the Ministry of Education and Science of the Russian Federation (VK, Unique Project Identifier RFMEFI60715X0123).
*Federal Research Center “Computer Science and Control" of the Russian Academy of Sciences, Moscow, Russian Federation