Early-Life Programming of Human Longevity Empirical Evidence

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

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.

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.

Month of Birth

FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC JAN FEB.

Lif

es

pa

n D

iffe

ren

ce

(y

r)

1

2

0

3

p=0.02

p=0.006

Season of Birth and Female Lifespan6,517 females from European aristocratic families

born in 1800-1880Seasonal Differences in Adult Lifespan at Age 60



Month of Birth


Lif

es

pa

n D

iffe

ren

ce

(y

r)

1

2

0

p=0.04

p=0.008

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

• Life expectancy of adult women (30+) as a function of year of birth

Mean Lifespan of FemalesBorn in December and February

as a Function of Birth Year

Year of Birth

1800 1820 1840 1860 1880

Mea

n L

ifes

pan

, yea

rs

60

65

70

75

80

Born in FebruaryBorn in December

Linear Regression Fit

Season of Birth and Female Lifespan7,020 Mennonite females born in 1800-1890

Seasonal Differences in Adult Lifespan at Age 30



Month of Birth


Lif

es

pa

n D

iffe

ren

ce

(y

r)

-2

-1

1

2

-3

0

3

Season of Birth and Male Lifespan8,187 Mennonite males born in 1800-1890

Seasonal 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).


Month of Birth


Lif

es

pan

Dif

fere

nce

(y

r)

-2

-1

1

2

-3

0

3

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

Molecular Effects on AgeingNew 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

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

Micronutrient Undernutrition in Americans

25%50%90; 75 mgMen; Women C

5; ~10-25%10-20; 25-50 %2.4 mcgMen; Women B12

25%; 50%75%400 mcgMen; Women Folate**

10% 50%1.7; 1.5 mgMen; Women B6

Vitamins

5-10% 25%8 mgWomen 50+ years

25% 75%18 mgWomen 20-30 years Iron

Minerals

<50% RDA

% ingesting

< RDA Population GroupNutrient

•Wakimoto and Block (2001) J Gerontol A Biol Sci Med Sci. Oct; 56 Spec No 2(2):65-80.

** Before U.S. Food Fortification Source: Presentation by Bruce Ames at the IABG Congress

RDA % ingesting < 50% RDA

Zinc Men; Women 50+ years 11; 8 mg 50% 10%

Daughters' Lifespan (30+) as a Functionof Paternal Age at Daughter's Birth

6,032 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.

Paternal Age at Reproduction

15-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59

Lif

es

pa

n D

iffe

ren

ce

(y

r)

-4

-3

-2

-1

1

0

p = 0.04

Daughters' Lifespan (60+) as a Functionof Paternal Age at Daughter's Birth

4,832 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.

Paternal Age at Reproduction

15-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59

Lif

es

pa

n D

iffe

ren

ce

(y

r)

-3

-2

-1

1

0

p = 0.004

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.

Paternal age Maternal age

Pa

ren

tal a

ge

at

ch

ild

bir

th (

ye

ars

)

25

30

35

40

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

p = 0.04

p=0.04

NS

NSNS

NS

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.

Daughter's Lifespan(Mean Deviation from Cohort Life Expectancy)

as a Function of Paternal Lifespan

Paternal Lifespan, years

40 50 60 70 80 90 100

Da

ug

hte

r's

Lif

es

pa

n (

de

via

tio

n),

ye

ars

-2

2

4

6

0

• 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

Offspring Lifespan at Age 30 as a Function of Paternal Lifespan

Data are adjusted for other predictor variables

Daughters, 8,284 cases Sons, 8,322 cases


40 50 60 70 80 90 100

Lif

esp

an d

iffe

ren

ce, y

ears

-2

2

4

0

p=0.05

p=0.0003

p=0.006


40 50 60 70 80 90 100

Lif

esp

an d

iffe

ren

ce, y

ears

-2

2

4

0

p<0.0001p=0.001

p=0.001





40 50 60 70 80 90 100

Lif

esp

an d

iffe

ren

ce, y

ears

-2

2

4

0

p=0.04

p=0.0001

p=0.04


40 50 60 70 80 90 100

Lif

esp

an d

iffe

ren

ce, y

ears

-2

2

4

0

p=0.006

p=0.004

p=0.0003

Offspring Lifespan at Age 30 as a Function of Maternal Lifespan



Maternal Lifespan, years

40 50 60 70 80 90 100

Lif

esp

an d

iffe

ren

ce, y

ears

-2

2

4

0

p=0.01

p=0.0004

p=0.05


40 50 60 70 80 90 100

Lif

esp

an d

iffe

ren

ce, y

ears

-2

2

4

0

p=0.02





40 50 60 70 80 90 100

Lif

esp

an d

iffe

ren

ce, y

ears

-2

2

4

0

p=0.01

p<0.0001

p=0.01


40 50 60 70 80 90 100

Lif

esp

an d

iffe

ren

ce, y

ears

-2

2

4

0

p=0.04

Person’s Lifespan as a Function of Spouse Lifespan


Married Women, 6,442 cases Married Men, 6,596 cases

Spouse Lifespan, years

40 50 60 70 80 90 100

Lif

esp

an d

iffe

ren

ce, y

ears

-4

-2

2

4

6

0

Spouse Lifespan, years

40 50 60 70 80 90 100

Lif

esp

an d

iffe

ren

ce, y

ears

-2

2

4

6

0



Mennonite daughters, 7020 cases Mennonite sons, 8187 cases


40 50 60 70 80 90 100

Lif

esp

an d

iffe

ren

ce, y

ears

-2

2

0


40 50 60 70 80 90 100

Lif

esp

an d

iffe

ren

ce, y

ears

-2

2

4

0



Mennonite daughters, 7020 cases Mennonite sons, 8187 cases


40 50 60 70 80 90 100

Lif

esp

an d

iffe

ren

ce, y

ears

-2

2

4

0


40 50 60 70 80 90 100

Lif

esp

an d

iffe

ren

ce, y

ears

-2

2

4

0

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

AcknowledgmentsThis 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

Documents

Early-Life Programming of Human Longevity Empirical Evidence