Leonid A. Gavrilov Natalia S. Gavrilova Center on Aging, NORC/University of Chicago,

1. Testing Biological Ideas on Evolution, Ageing and Longevity with Demographic and Genealogical Data Leonid A. Gavrilov Natalia S. Gavrilova Center on Aging, NORC/University of Chicago, 1155 East 60th Street, Chicago, IL 60637

2. Is There Any Link Between Longevity and Fertility? What are the data and the predictions of the evolutionary theory on this issue?

3. Brief Historical Note • Beeton, M., Yule, G.U., Pearson, K. 1900. Data for the problem of evolution in man. V. On the correlation between duration of life and the number of offspring. Proc. R. Soc. London, 67: 159-179. • Data used: English Quaker records and Whitney Family of Connectucut records for females and American Whitney family and Burke’s ‘Landed Gentry’ for males.

4. Findings and Conclusions by Beeton et al., 1900 • They tested predictions of the Darwinian evolutionary theory that the fittest individuals should leave more offspring. • Findings: Slightly positive relationship between postreproductive lifespan (50+) of both mothers and fathers and the number of offspring. • Conclusion: “fertility is correlated with longevity even after the fecund period is passed” and “selective mortality reduces the numbers of the offspring of the less fit relatively to the fitter.”

5. Other Studies, Which Found Positive Correlation Between Reproduction and Postreproductive Longevity • Alexander Graham Bell (1918): “The longer lived parents were the most fertile.” • Bettie Freeman (1935): Weak positive correlations between the duration of postreproductive life in women and the number of offspring borne. Human Biology, 7: 392-418. • Bideau A. (1986): Duration of life in women after age 45 was longer for those women who borne 12 or more children. Population 41: 59-72.

6. Studies that Found no Relationship Between Postreproductive Longevity and Reproduction • Henry L. 1956. Travaux et Documents. • Gauter, E. and Henry L. 1958. Travaux et Documents, 26. • Knodel, J. 1988. Demographic Behavior in the Past. • Le Bourg et al., 1993. Experimental Gerontology, 28: 217-232.

7. Study that Found a Trade-Off Between Reproductive Success and Postreproductive Longevity • Westendorp RGJ, Kirkwood TBL. 1998. Human longevity at the cost of reproductive success. Nature 396: 743-746. • Extensive media coverage including BBC and over 70 citations in scientific literature as an established scientific fact. Previous studies were not quoted and discussed in this article.

8. Do longevous women have impaired fertility ?Why is this question so important and interesting: • Scientific Significance. This is a testable prediction of some evolutionary theories of aging (disposable soma theory of aging, Westendorp, Kirkwood, 1998) • Practical Importance. Do we really wish to live a long life at the cost of infertility? Based these concerns a suggestion was made: "... increasing longevity through genetic manipulation of the mechanisms of aging raises deep biological and moral questions. These questions should give us pause before we embark on the enterprise of extending our lives“ Walter Glennon "Extending the Human Life Span", Journal of Medicine and Philosophy, 2002, Vol. 27, No. 3, pp. 339-354 • Educational Significance. Do we teach our students right? Impaired fertility of longevous women is often presented in scientific literature and mass media as already established fact (Kirkwood, 2002; Westendorp, 2002; Glennon, 2002; Perls et al., 2002 etc.) Is it a fact or artifact ?

9. Point estimates of progeny number for married aristocratic women from different birth cohorts as a function of age at death.The estimates of progeny number are adjusted for trends over calendar time using multiple regression. Source: Westendorp, R. G. J., Kirkwood, T. B. L. Human longevity at the cost of reproductive success. Nature, 1998, 396, pp 743-746

10. Number of progeny and age at first childbirth dependent on the age at death of married aristocratic women Source: Westendorp, R. G. J., Kirkwood, T. B. L. Human longevity at the cost of reproductive success. Nature, 1998, 396, pp 743-746

11. Table 1 Relationship between age at death and number of children for married aristocratic women Age at death Proportion childless Number of children (years) mean for all women mean for women having children <20 0.66 0.45 1.32 21-30 0.39 1.35 2.21 31-40 0.26 2.05 2.77 41-50 0.31 2.01 2.91 51-60 0.28 2.4 3.33 61-70 0.33 2.36 3.52 71-80 0.31 2.64 3.83 81-90 0.45 2.08 3.78 >90 0.49 1.80 3.53 “… it is not a matter of reduced fertility, but a case of 'to have or have not'.“ Source: Toon Ligtenberg & Henk Brand. Longevity — does family size matter? Nature, 1998, 396, pp 743-746

12. Source: Westendorp, R. G. J., Kirkwood, T. B. L. Human longevity at the cost of reproductive success. Nature, 1998, 396, pp 743-746

13. General Methodological Principle: • Before making strong conclusions, consider all other possible explanations, including potential flaws in data quality and analysis • Previous analysis by Westendorp and Kirkwood was made on the assumption of data completeness:Number of children born = Number of children recorded • Potential concerns: data incompleteness, under-reporting of short-lived children, women (because of patrilineal structure of genealogical records), persons who did not marry or did not have children.Number of children born   >> Number of children recorded

14. Test for Data Completeness Direct Test: Cross-checking of the initial dataset with other data sources We examined 335 claims of childlessness in the dataset used by Westendorp and Kirkwood. When we cross-checked these claims with other professional sources of data, we  found that at least 107 allegedly childless women (32%) did have children! At least 32% of childlessness claims proved to be wrong ("false negative claims") ! Some illustrative examples: Henrietta Kerr (1653­1741) was apparently childless in the dataset used by Westendorp and Kirkwood and lived 88 years. Our cross-checking revealed that she did have at least one child, Sir William Scott (2nd Baronet of Thirlstane, died on October 8, 1725). Charlotte Primrose (1776­1864) was also considered childless in the initial dataset and lived 88 years. Our cross-checking of the data revealed that in fact she had as many as five children: Charlotte (1803­1886), Henry (1806­1889), Charles (1807­1882), Arabella (1809-1884), and William (1815­1881). Wilhelmina Louisevon Anhalt-Bernburg (1799­1882), apparently childless, lived 83 years. In reality, however, she had at least two children, Alexander (1820­1896) and Georg (1826­1902).

15. Point estimates of progeny number for married aristocratic women from different birth cohorts as a function of age at death. The estimates of progeny number are adjusted for trends over calendar time using multiple regression. Source: Westendorp, R. G. J., Kirkwood, T. B. L. Human longevity at the cost of reproductive success. Nature, 1998, 396, pp 743-746

16. Antoinette de Bourbon(1493-1583) Lived almost 90 years She was claimed to have only one child in the dataset used by Westendorp and Kirkwood: Marie (1515-1560), who became a mother of famous Queen of Scotland, Mary Stuart. Our data cross-checking revealed that in fact Antoinette had 12 children! • Marie 1515-1560 • Francois Ier 1519-1563 • Louise 1521-1542 • Renee 1522-1602 • Charles 1524-1574 • Claude 1526-1573 • Louis 1527-1579 • Philippe 1529-1529 • Pierre 1529 • Antoinette 1531-1561 • Francois 1534-1563 • Rene 1536-1566

17. Testing Evolutionary Theories of Ageing and Mutation Accumulation Theory in Particular • Mutation accumulation theory predicts that those deleterious mutations that are expressed in later life should have higher frequencies (because mutation-selection balance is shifted to higher equilibrium frequencies due to smaller selection pressure). • Therefore, ‘expressed’ genetic variability should increase with age. • This should result in higher heritability estimates for lifespan of offspring born to longer-lived parents.

18. Characteristics of Our Data Sample for ‘Reproduction-Longevity’ Studies • 3,723 married women born in 1500-1875 and belonging to the upper European nobility. • Women with two or more marriages (5%) were excluded from the analysis in order to facilitate the interpretation of results (continuity of exposure to childbearing). • Every case of childlessness has been checked using at least two different genealogical sources.

22. 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.

23. 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

24. 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

25. 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

26. 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

27. 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

28. 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

29. 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.

30. 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.

31. 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.

32. 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.

33. 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

34. 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% C Men; Women 90; 75 mg 50% 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

35. 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

36. 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.

37. 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.

38. 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

39. Aging is a Very General Phenomenon!

40. What Should the Aging Theory Explain: • Why do most biological species deteriorate with age? • Specifically, why do mortality rates increase exponentially with age in many adult species (Gompertz law)? • Why does the age-related increase in mortality rates vanish at older ages (mortality deceleration)? • How do we explain the so-called compensation law of mortality (Gavrilov & Gavrilova, 1991)?

41. Exponential Increase of Death Rate with Age in Fruit Flies(Gompertz Law of Mortality) Linear dependence of the logarithm of mortality force on the age of Drosophila. Based on the life table for 2400 females of Drosophila melanogaster published by Hall (1969). Mortality force was calculated for 3-day age intervals. Source: Gavrilov, Gavrilova, “The Biology of Life Span” 1991

42. Age-Trajectory of Mortality in Flour Beetles(Gompertz-Makeham Law of Mortality) Dependence of the logarithm of mortality force (1) and logarithm of increment of mortality force (2) on the age of flour beetles (Tribolium confusum Duval). Based on the life table for 400 female flour beetles published by Pearl and Miner (1941). Mortality force was calculated for 30-day age intervals. Source: Gavrilov, Gavrilova, “The Biology of Life Span” 1991

43. Age-Trajectory of Mortality in Italian Women(Gompertz-Makeham Law of Mortality) Dependence of the logarithm of mortality force (1) and logarithm of increment of mortality force (2) on the age of Italian women. Based on the official Italian period life table for 1964-1967. Mortality force was calculated for 1-year age intervals. Source: Gavrilov, Gavrilova, “The Biology of Life Span” 1991

44. Compensation Law of MortalityConvergence of Mortality Rates with Age 1 – India, 1941-1950, males 2 – Turkey, 1950-1951, males 3 – Kenya, 1969, males 4 - Northern Ireland, 1950-1952, males 5 - England and Wales, 1930-1932, females 6 - Austria, 1959-1961, females 7 - Norway, 1956-1960, females Source: Gavrilov, Gavrilova, “The Biology of Life Span” 1991

45. Compensation Law of Mortality in Laboratory Drosophila 1 – drosophila of the Old Falmouth, New Falmouth, Sepia and Eagle Point strains (1,000 virgin females) 2 – drosophila of the Canton-S strain (1,200 males) 3 – drosophila of the Canton-S strain (1,200 females) 4 - drosophila of the Canton-S strain (2,400 virgin females) Mortality force was calculated for 6-day age intervals. Source: Gavrilov, Gavrilova, “The Biology of Life Span” 1991

46. Mortality at Advanced Ages Source:Gavrilov L.A., Gavrilova N.S. The Biology of Life Span: A Quantitative Approach, NY: Harwood Academic Publisher, 1991

48. M. Greenwood, J. O. Irwin. BIOSTATISTICS OF SENILITY

49. Survival Patterns After Age 90 Percent surviving (in log scale) is plotted as a function of age of Swedish women for calendar years 1900, 1980, and 1999 (cross-sectional data). Note that after age 100, the logarithm of survival fraction is decreasing without much further acceleration (aging) in almost a linear fashion. Also note an increasing pace of survival improvement in history: it took less than 20 years (from year 1980 to year 1999) to repeat essentially the same survival improvement that initially took 80 years (from year 1900 to year 1980). Source: cross-sectional (period) life tables at the Berkeley Mortality Database (BMD): http://www.demog.berkeley.edu/~bmd/

50. Non-Gompertzian Mortality Kinetics of Four Invertebrate Species Non-Gompertzian mortality kinetics of four invertebrate species: nematodes, Campanularia flexuosa, rotifers and shrimp. Source: A. Economos. A non-Gompertzian paradigm for mortality kinetics of metazoan animals and failure kinetics of manufactured products. AGE, 1979, 2: 74-76.