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Early-Life Programming of Human Longevity Empirical Evidence

Early-Life Programming of Human Longevity Empirical Evidence. Natalia S. Gavrilova, Leonid A. Gavrilov Victoria Semyonova, Galina Evdokushkina Center on Aging, NORC/University of Chicago, 1155 East 60th Street, Chicago, IL 60637. Characteristic of our Dataset.

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Early-Life Programming of Human Longevity Empirical Evidence

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  1. Early-Life Programming of Human LongevityEmpirical Evidence Natalia S. Gavrilova, Leonid A. Gavrilov Victoria Semyonova, Galina Evdokushkina Center on Aging, NORC/University of Chicago, 1155 East 60th Street, Chicago, IL 60637

  2. Characteristic of our Dataset • Over 16,000 persons belonging to the European aristocracy • 1800-1880 extinct birth cohorts • Adult persons aged 30+ • Data extracted from the professional genealogical data sources including Genealogisches Handbook des Adels, Almanac de Gotha, Burke Peerage and Baronetage.

  3. Season of Birth and Female Lifespan8,284 females from European aristocratic families born in 1800-1880Seasonal Differences in Adult Lifespan at Age 30 • Life expectancy of adult women (30+) as a function of month of birth (expressed as a difference from the reference level for those born in February). • The data are point estimates (with standard errors) of the differential intercept coefficients adjusted for other explanatory variables using multivariate regression with categorized nominal variables.

  4. Season of Birth and Female Lifespan6,517 females from European aristocratic families born in 1800-1880Seasonal Differences in Adult Lifespan at Age 60 • Life expectancy of adult women (60+) as a function of month of birth (expressed as a difference from the reference level for those born in February). • The data are point estimates (with standard errors) of the differential intercept coefficients adjusted for other explanatory variables using multivariate regression with categorized nominal variables.

  5. Models Used in the Season-of-Birth Analyses • Multiple linear regression models with nominal variables • Multilevel linear regression models (with family as a second level) • Proportional hazard models with stratification

  6. Mean Lifespan of FemalesBorn in December and Februaryas a Function of Birth Year • Life expectancy of adult women (30+) as a function of year of birth

  7. Season of Birth and Female Lifespan7,020 Mennonite females born in 1800-1890Seasonal Differences in Adult Lifespan at Age 30 • Life expectancy of adult women (30+) as a function of month of birth (expressed as a difference from the reference level for those born in February). • The data are point estimates (with standard errors) of the differential intercept coefficients adjusted for other explanatory variables using multivariate regression with categorized nominal variables.

  8. Season of Birth and Male Lifespan8,187 Mennonite males born in 1800-1890Seasonal Differences in Adult Lifespan at Age 30 • Life expectancy of adult men (30+) as a function of month of birth (expressed as a difference from the reference level for those born in February). • The data are point estimates (with standard errors) of the differential intercept coefficients adjusted for other explanatory variables using multivariate regression with categorized nominal variables.

  9. Season-of-Birth Effects Found in Other Studies • Female childlessness (born in January, July) – Smits et al., 1997. • Schizoprenia is more frequent for persons born in February (Dassa et al., 1996) and this effect is more expressed among females

  10. Molecular Effects on Ageing New Ideas and Findings by Bruce Ames: • The rate of mutation damage is NOT immutable, but it can be dramatically decreased by very simple measures: -- Through elimination of deficiencies in vitamins and other micronutrients (iron, zinc, magnesium, etc). • Micronutrient deficiencies are very common even in the modern wealthy populations • These deficiencies are much more important than radiation, industrial pollution and most other hazards Our hypothesis: Remarkable improvement in the oldest-old survival may reflect an unintended retardation of the aging process, caused by decreased damage accumulation, because of improving the micronutrient status in recent decades

  11. Molecular Effects on Ageing (2) Ideas and Findings by Bruce Ames: • The rate of damage accumulation is NOT immutable, but it can be dramatically decreased by PREVENTING INFLAMMATION: Inflammation causes tissue damage through many mechanisms including production of Hypochlorous acid (HOCl), which produces DNA damage (through incorporation of chlorinated nucleosides). Chronic inflammation may contribute to many age-related degenerative diseases including cancer Hypothesis: Remarkable improvement in the oldest-old survival may reflect an unintended retardation of the aging process, caused by decreased damage accumulation, because of partial PREVENTION of INFLAMMATION through better control over infectious diseases in recent decades

  12. Micronutrient Undernutrition in Americans Nutrient Population Group % ingesting <RDA <50% RDA % ingesting < 50% RDA RDA Minerals Iron Women20-30 years 18 mg 75% 25% Women 50+ years 8 mg 25% 5-10% Men; Women 50+ years 11; 8 mg 10% 50% Zinc Vitamins B6 Men; Women 1.7; 1.5 mg 50% 10% Folate** Men; Women 400 mcg 75% 25%; 50% B12 Men; Women 2.4 mcg 10-20; 25-50 % 5; ~10-25% 90; 75 mg 50% C Men; Women 25% •Wakimoto and Block (2001) J Gerontol A Biol Sci Med Sci. Oct; 56 Spec No 2(2):65-80. ** Before U.S. Food FortificationSource: Presentation by Bruce Ames at the IABG Congress

  13. Daughters' Lifespan (30+) as aFunctionof Paternal Age at Daughter's Birth6,032 daughters from European aristocratic familiesborn in 1800-1880 • Life expectancy of adult women (30+) as a function of father's age when these women were born (expressed as a difference from the reference level for those born to fathers of 40-44 years). • The data are point estimates (with standard errors) of the differential intercept coefficients adjusted for other explanatory variables using multiple regression with nominal variables. • Daughters of parents who survived to 50 years.

  14. Daughters' Lifespan (60+) as aFunctionof Paternal Age at Daughter's Birth4,832 daughters from European aristocratic familiesborn in 1800-1880 • Life expectancy of older women (60+) as a function of father's age when these women were born (expressed as a difference from the reference level for those born to fathers of 40-44 years). • The data are point estimates (with standard errors) of the differential intercept coefficients adjusted for other explanatory variables using multiple regression with nominal variables. • Daughters of parents who survived to 50 years.

  15. Paternal Age as a Risk Factor for Alzheimer Disease • MGAD - major gene for Alzheimer Disease • Source: L. Bertram et al. Neurogenetics, 1998, 1: 277-280.

  16. Paternal Age and Risk of Schizophrenia • Estimated cumulative incidence and percentage of offspring estimated to have an onset of schizophrenia by age 34 years, for categories of paternal age. The numbers above the bars show the proportion of offspring who were estimated to have an onset of schizophrenia by 34 years of age. • Source: Malaspina et al., Arch Gen Psychiatry.2001.

  17. Daughter's Lifespan(Mean Deviation from Cohort Life Expectancy)as a Function of Paternal Lifespan • Offspring data for adult lifespan (30+ years) are smoothed by 5-year running average. • Extinct birth cohorts (born in 1800-1880) • European aristocratic families. 6,443 cases

  18. Offspring Lifespan at Age 30 as a Function of Paternal LifespanData are adjusted for other predictor variables Daughters, 8,284 cases Sons, 8,322 cases

  19. Offspring Lifespan at Age 60 as a Function of Paternal LifespanData are adjusted for other predictor variables Daughters, 6,517 cases Sons, 5,419 cases

  20. Offspring Lifespan at Age 30 as a Function of Maternal LifespanData are adjusted for other predictor variables Daughters, 8,284 cases Sons, 8,322 cases

  21. Offspring Lifespan at Age 60 as a Function of Maternal LifespanData are adjusted for other predictor variables Daughters, 6,517 cases Sons, 5,419 cases

  22. Person’s Lifespan as a Function of Spouse LifespanData are adjusted for other predictor variables Married Women, 6,442 cases Married Men, 6,596 cases

  23. Offspring Lifespan at Age 30 as a Function of Paternal LifespanData are adjusted for other predictor variables Mennonite daughters, 7020 cases Mennonite sons, 8187 cases

  24. Offspring Lifespan at Age 30 as a Function of Maternal LifespanData are adjusted for other predictor variables Mennonite daughters, 7020 cases Mennonite sons, 8187 cases

  25. Other Early-Life Markers • Death of siblings before age 18 - a proxy for early childhood infections and risk factor for late-life mortality • Found both in aristocratic and Mennonite populations

  26. Acknowledgments This study was made possible thanks to: generous support from the National Institute on Aging, and stimulating working environment at the Center on Aging, NORC/University of Chicago

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