Testing Biological Ideas on Evolution, Aging and Longevity

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Transcript Testing Biological Ideas on Evolution, Aging and Longevity

Testing Biological Theories of Aging with Demographic and Genealogical Data

Natalia S. Gavrilova Leonid A. Gavrilov

Center on Aging, NORC/University of Chicago, 1155 East 60th Street, Chicago, IL 60637

What are the data and the predictions of the evolutionary theory on

Links between human longevity and fertility

Lifespan heritability in humans

Quality of offspring conceived to older parents

Founding Fathers

  Beeton, M., Yule, G.U., 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.

Pearson, K.

, Data used: English Quaker records and Whitney Family of Connectucut records for females and American Whitney family and Burke’s ‘Landed Gentry’ for males.

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: “

longevity even after the fecund period is passed fertility is correlated with

” and “

selective mortality reduces the numbers of the offspring of the less fit

relatively to the fitter.

Other Studies, Which Found Positive Correlation Between Reproduction and Postreproductive Longevity Telephone inventor 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. 392-418.

Human Biology , 7: 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.

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.

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 100 citations in scientific literature as an established scientific fact. Previous studies were not quoted and discussed in this article.

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, Kirkwood, Human longevity at the cost of reproductive success. Nature, 1998, 396, pp 743 746

“… it is not a matter of reduced fertility, but a case of 'to have or have not'.“

Table 1

Relationship between age at death and number of children for married aristocratic women

Age at death (years) Proportion childless Number of children

mean for all women mean for women having children

<20 21-30 31-40 41-50 51-60

0.66 0.39 0.26 0.31 0.28 0.45 1.35 2.05 2.01 2.4 1.32 2.21 2.77 2.91 3.33

61-70 71-80 81-90

0.33 0.31 0.45 2.36 2.64 2.08 3.52 3.83 3.78

>90

0.49 1.80 3.53 Source: Toon Ligtenberg & Henk Brand. Longevity — does family size matter? Nature, 1998, 396, pp 743-746

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

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

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 (Kirkwood)

"The disposable soma theory on the evolution of ageing states

that longevity requires investments in somatic maintenance that

reduce the resources available for reproduction“ (Westendorp, Kirkwood, Nature, 1998).

Do longevous women have impaired fertility ?

Practical Importance.

Do we really wish to live a long life at the cost of infertility?: “

the next generations of Homo sapiens will have even longer life spans but at the cost of impaired fertility

” Rudi Westendorp “Are we becoming less disposable? EMBO Reports , 2004, 5: 2-6.

"... 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 (Brandt et al., 2005; Fessler et al., 2005; Schrempf et al., 2005; Tavecchia et al., 2005; Kirkwood, 2002; Westendorp, 2002, 2004; Glennon, 2002; Perls et al., 2002, etc.).

This "fact" is now included in teaching curriculums in biology, ecology and anthropology world-wide (USA, UK, Denmark).

Is it a fact or artifact ?

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

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 1881).

(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 (1815 Wilhelmina Louise von Anhalt-Bernburg (17991882), apparently childless, lived 83 years. In reality, however, she had at least two children, Alexander (18201896) and Georg (18261902).

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

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

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.

Typical Mistakes in Biological Studies of Human Longevity

   Using lifespan data for non-extinct birth cohorts (“cemetery effect”) Failure to control for birth cohort – spurious correlations may be found if variables have temporal dynamics Failure to take into account social events and factors – e.g., failure to control for age at marriage in longevity-reproduction studies

Fertility Longevity Time

Childlessness human data is better outcome than number of children for testing evolutionary theories of aging on

   Applicable even for population practicing birth control (few couple are voluntarily childless) Lifespan is not affected by physiological load of multiple pregnancies Lifespan is not affected by economic hardship experienced by large families

Source: Gavrilova et al. Does exceptional human longevity come with high cost of infertility? Testing the evolutionary theories of aging. New York Academy of Sciences Annals of the , 2004, 1019: 513-517.

Source: Gavrilova, Gavrilov. Human longevity and reproduction: An evolutionary perspective. In: Grandmotherhood The Evolutionary Significance of the Second Half of Female Life . Rutgers University Press, 2005, 59-80.

Short Conclusion:

Exceptional human longevity is NOT associated with infertility or childlessness

More Detailed Conclusions

We have found that previously reported high rate of childlessness among long-lived women is an artifact of data incompleteness has disappeared.

, caused by under reporting of children. After data cleaning, cross checking and supplementation the association between exceptional longevity and childlessness

Thus, it is important now to revise a highly publicized scientific students.

concept of heavy reproductive costs for human longevity . and to make corrections in related teaching curriculums for

More Detailed Conclusions (2)

It is also important to disavow the doubts and concerns over further extension of human lifespan , that were recently cast in biomedical ethics because of gullible acceptance of the idea of harmful side effects of lifespan extension, including infertility (Glannon, 2002).

There is little doubt that the number of children can affect human longevity through complications of pregnancies and childbearing, as well as through changes in socioeconomic status, etc. However, infertility cost of human longevity is not supported by data the concept of heavy , when these data are carefully reanalyzed.

 

Mutation Accumulation Theory of Aging (Medawar, 1946)

From the evolutionary perspective, aging is an inevitable result of the declining force of natural selection with age. So, over successive generations, late-acting deleterious mutations will accumulate, leading to an increase in mortality rates late in life.

  

Predictions of the Mutation Accumulation Theory of Aging

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 (Charlesworth, 1994. Evolution in Age-structured Populations ).

This should result in higher heritability estimates for lifespan of offspring born to longer-lived parents.

40 30 20 10 0 0 20 40

Parental Lifespan

60 80

Linearity Principle of Inheritance in Quantitative Genetics

Dependence between parental traits and offspring traits is linear

The Best Possible Source on Familial Longevity Genealogies of European Royal and Noble Families Charles IX d’Anguleme (1550-1574) Henry VIII Tudor (1491-1547) Marie-Antoinette von Habsburg-Lothringen (1765-1793)

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.

Daughter's Lifespan

(Mean Deviation from Cohort Life Expectancy) as a Function of Paternal Lifespan 6 4 2 0 -2 40

  

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 50 60 70 80 Paternal Lifespan, years 90 100

Paradox of low heritability of lifespan vs high familial clustering of longevity

“The Heritability of Life-Spans Is Small” C.E. Finch, R.E. Tanzi, Science , 1997, p.407

“… long life runs in families”

A. Cournil, T.B.L. Kirkwood, Trends in Genetics, 2001, p.233

Heritability Estimates of Human Lifespan

Author(s)

McGue et al., 1993

Heritability estimate

0.22

Population

Danish twins Ljungquist et al., 1998 Bocquet-Appel, Jacobi, 1990 Mayer, 1991 <0.33

0.10-0.30

0.10-0.33

Swedish twins French village Cournil et al., 2000 Mitchell et al., 2001 0.27

0.25

New England families French village Old Order Amish

Is the effect of non-linear inheritance remain valid after controlling for other explanatory variables?

Lifespan of other parent

Parental ages at child’s conception

 

Ethnicity Month of birth

Offspring Lifespan at Age 30 as a Function of Paternal Lifespan

Data are adjusted for other predictor variables

p=0.0003

4 2 p=0.006

p=0.05

0 -2 40 50 60 70 80 Paternal Lifespan, years 90 100 Daughters, 8,284 cases 4 2 0 p=0.001

p<0.0001

p=0.001

-2 40 50 60 70 80 Paternal Lifespan, years 90 100 Sons, 8,322 cases

Offspring Lifespan at Age 30 as a Function of Maternal Lifespan

Data are adjusted for other predictor variables

4 2 0 p=0.0004

p=0.05

p=0.01

-2 40 50 60 70 80 Maternal Lifespan, years 90 100 Daughters, 8,284 cases 4 2 0 p=0.02

-2 40 50 60 70 80 Maternal Lifespan, years 90 100 Sons, 8,322 cases

Is the effect of non-linear inheritance observed for non-biological relatives?

We need to test an alternative hypothesis that positive effects of long lived parents on the offspring survival may be non-biological and caused by common environment and life style What about lifespan of spouses?

Person’s Lifespan as a Function of Spouse Lifespan

Data are adjusted for other predictor variables

4 3 2 1 0 -1 -2 -3 -4 40 50 60 70 80 Husband Lifespan, years 90 Married Women, 4,530 cases 2 1 4 3 0 -1 -2 -3 -4 40 50 60 70 Wife Lifespan, years 80 Married Men, 5,102 cases 90

Parental-Age Effects in Humans

(accumulation of mutation load in parental germ cells)

What are the Data and the Predictions of Evolutionary Theory on the Quality of Offspring Conceived to Older Parents?

Does progeny conceived to older parents live shorter lives?

Evolutionary Justification for Parental-Age Effects

   "

The evolutionary explanation of senescence proposes that selection against alleles with deleterious effects manifested only late in life is weak because most individuals die earlier for extrinsic reasons. This argument also applies to alleles whose deleterious effects are nongenetically transmitted from mother to progeny, that is, that affect the performance of progeny produced at late ages rather than of the aging individuals themselves.

… a decline of offspring quality with parental age should receive more attention in the context of the evolution of aging

Evolution .” Stearns et al. "Decline in offspring viability as a manifestation of aging in Drosophila melianogaster." , 2001, Vol. 55, No. 9, pp. 1822–1831.

Genetic Justification for Paternal Age Effects

 Advanced paternal age at child conception is the main source of new mutations in human populations.

James F. Crow, geneticist Professor Crow (University of Wisconsin-Madison) is recognized as a leader and statesman of science. He is a member of the National Academy of Sciences, the National Academy of Medicine, The American Philosophical Society, the American Academy of Arts and Sciences, the World Academy of Art and Science.

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.

25 30 35 40

Paternal Age as a Risk Factor for Alzheimer Disease

p = 0.04

p=0.04

NS  MGAD - major gene for Alzheimer Disease NS NS NS

Paternal age Maternal age Sporadic Alzheimer Disease (low likelihood of MGAD) Familial Alzheimer Disease (high likelihood of MGAD) Controls

 Source: L. Bertram et al. Neurogenetics , 1998, 1: 277-280.

Daughters' Lifespan (30+) as a Function of Paternal Age at Daughter's Birth 6,032 daughters from European aristocratic families born in 1800-1880 1 0

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).

-1 -2 -3

The data are point estimates (with standard errors) of the differential intercept coefficients adjusted for other explanatory variables using multiple regression with nominal variables. p = 0.04

Daughters of parents who survived to 50 years.

-4 15-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 Paternal Age at Reproduction

Contour plot for daughters’ lifespan (deviation from cohort mean) as a function of paternal lifespan (X axis) and paternal age at daughters’ birth (Y axis) 65 60 55

3 2 1 0 -1 -2 -3

7984 cases 50 45 1800-1880 birth cohorts 40 35 European aristocratic families 30 25 Distance weighted least squares smooth 20 40 50 60 70 Paternal Lifespan, years 80 90

Daughters’ Lifespan as a Function of Paternal Age at Daughters’ Birth

Data are adjusted for other predictor variables

4 1 -2 -3 0 -1 -4 15-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 Paternal Age at Person's Birth Daughters of shorter-lived fathers (<80), 6727 cases 2 0 -2 -4 15-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 Paternal Age at Person's Birth Daughters of longer-lived fathers (80+), 1349 cases

Conclusions

Being conceived to old fathers is a risk factor, but it is moderated by paternal longevity It is OK to be conceived to old father if he lives more than 80 years Methodological implications: Paternal lifespan should be taken into account in the studies of paternal-age effects

The Most Recent and Interesting Developments:

Young Mother and Exceptional Longevity

Within-Family Study of Exceptional Longevity Cases - 198 Centenarians born in U.S. in 1890-1893 Controls – Their own siblings Method : Conditional logistic regression Advantage : Allows researchers to eliminate confounding effects of between family variation

Design of the Study

A typical image of ‘centenarian’ family in 1900 census

Birth Order and Odds to Become a Centenarian

Can the birth-order effect be a result of selective child mortality, thus not applicable to adults?

Approach:  To compare centenarians with those siblings only who survived to adulthood (age 20)

First-born adult siblings (20+years) are more likely to become centenarians (odds ratio= 1.95)

Conditional (fixed-effects) logistic regression Number of obs = 797 LR chi2(2) = 27.54

Prob > chi2 = 0.0000

Log likelihood = -247.93753 Pseudo R2 = 0.0526

--------------------------------------------------------------------------------- Variable | Odds Ratio P>|z| [95% Conf. Interval] -------------+------------------------------------------------------------------- First-born status | 1.949

0.003

1.261 3.010

Male sex | .458 0.000 .318 .658

----------------------------------------------------------------------------------

Even at age 75 it still helps to be a first-born child (odds ratio= 1.7)

Conditional (fixed-effects) logistic regression Number of obs = 557 LR chi2(2) = 19.03

Prob > chi2 = 0.0001

Log likelihood = -186.22869 Pseudo R2 = 0.0486

--------------------------------------------------------------- Variable Odds Ratio P>|z| [95% Conf. Interval] -------------+------------------------------------------------- First-born status 1.659

0.040

1.022 2.693

Male sex .459 0.000 .306 .687

----------------------------------------------------------------

Birth order is more important than paternal age for chances to become a centenarian

Conditional (fixed-effects) logistic regression Number of obs = 950 LR chi2(3) = 34.24

Prob > chi2 = 0.0000

Log likelihood = -281.97993 Pseudo R2 = 0.0572

--------------------------------------------------------------- Variable Odds Ratio P>|z| [95% Conf. Interval] -------------+------------------------------------------------- First-born status 1.635 0.039

1.025 2.607

Born to young father 1.294 0.484 .628 2.668

Male sex .407 0.000 .285 .580

--------------------------------------------------------------------------------------

Are young mothers responsible for the birth order effect?

Conditional (fixed-effects) logistic regression Number of obs = 950 LR chi2(2) = 37.35

Prob > chi2 = 0.0000

Log likelihood = -280.42473 Pseudo R2 = 0.0624

------------------------------------------------------------------------------------ Variable Odds Ratio P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------------- Born to young mother 2.031

0.001 1.326 3.110

Male sex .412 0.000 .289 .586

-------------------------------------------------------------------------------------

Maternal Age at Person’s Birth and Odds to Become a Centenarian

Birth order effect explained: Being born to young mother!

Conditional (fixed-effects) logistic regression Number of obs = 950

LR chi2(3) = 39.05

Prob > chi2 = 0.0000

Log likelihood = -279.57165 Pseudo R2 = 0.0653

------------------------------------------------------------------------------------ Variable Odds Ratio P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------------- First-born status 1.360 0.189 .859 2.153

Born to young mother 1.760

0.021

1.089 2.846

Male sex .407 0.000 .285 .580

--------------------------------------------------------------------------------------

Even at age 75 it still helps to be born to young mother (age <25) (odds ratio= 1.9)

Conditional (fixed-effects) logistic regression Number of obs = 557

LR chi2(2) = 21.31

Prob > chi2 = 0.0000

Log likelihood = -185.08639 Pseudo R2 = 0.0544

--------------------------------------------------------------------------------- Variable Odds Ratio P>|z| [95% Conf. Interval] -------------+------------------------------------------------------------------- Born to young mother 1.869

0.012

1.145 3.051

Male sex .461 0.000 .307 .690

----------------------------------------------------------------------------------

Younger Moms' Kids Get Longevity Edge Children of women under 25 twice as likely to live to 100, study finds HealthDay Monday , April 17, 2006 MONDAY, April 17 (HealthDay News) -- Society's oldest members are most likely to be born to its youngest mothers, new research suggests.

The odds of living to 100 and beyond double when a person is born to a woman under 25 years of age, compared to those people born to older mothers, according to one of the most rigorous studies on the subject yet conducted.

The finding may also help clear up a statistical mystery -- three years ago, the same husband-and-wife team of researchers found that being the first-born child in a family also boosted longevity, although no one knew why.

Being born to Young Mother Helps Laboratory Mice to Live Longer

 Source: Tarin et al., Delayed Motherhood Decreases Life Expectancy of Mouse Offspring. Biology of Reproduction 2005 72: 1336-1343.

Conclusions

 The shortest conclusion was suggested in the title of the York Times study New article about this

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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