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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
• 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.
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
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
• 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)
-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).
• 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
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
Paternal Lifespan, years
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
Paternal Lifespan, years
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
Offspring Lifespan at Age 60 as a Function of Paternal Lifespan
Data are adjusted for other predictor variables
Daughters, 6,517 cases Sons, 5,419 cases
Paternal Lifespan, years
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
Paternal Lifespan, years
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
Data are adjusted for other predictor variables
Daughters, 8,284 cases Sons, 8,322 cases
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
Maternal Lifespan, years
40 50 60 70 80 90 100
Lif
esp
an d
iffe
ren
ce, y
ears
-2
2
4
0
p=0.02
Offspring Lifespan at Age 60 as a Function of Maternal Lifespan
Data are adjusted for other predictor variables
Daughters, 6,517 cases Sons, 5,419 cases
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<0.0001
p=0.01
Maternal Lifespan, years
40 50 60 70 80 90 100
Lif
esp
an d
iffe
ren
ce, y
ears
-2
2
4
0
p=0.04
Person’s Lifespan as a Function of Spouse Lifespan
Data are adjusted for other predictor variables
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
Offspring Lifespan at Age 30 as a Function of Paternal Lifespan
Data are adjusted for other predictor variables
Mennonite daughters, 7020 cases Mennonite sons, 8187 cases
Paternal Lifespan, years
40 50 60 70 80 90 100
Lif
esp
an d
iffe
ren
ce, y
ears
-2
2
0
Paternal Lifespan, years
40 50 60 70 80 90 100
Lif
esp
an d
iffe
ren
ce, y
ears
-2
2
4
0
Offspring Lifespan at Age 30 as a Function of Maternal Lifespan
Data are adjusted for other predictor variables
Mennonite daughters, 7020 cases Mennonite sons, 8187 cases
Maternal Lifespan, years
40 50 60 70 80 90 100
Lif
esp
an d
iffe
ren
ce, y
ears
-2
2
4
0
Maternal Lifespan, years
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
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