Abstract
The antagonistic pleiotropy hypothesis posits that natural selection
for pleiotropic mutations that confer earlier or more reproduction but
impair the post-reproductive life causes aging. This hypothesis of the
evolutionary origin of aging is supported by case studies but lacks
unambiguous genomic evidence. Here, we genomically test this hypothesis
using the genotypes, reproductive phenotypes, and death registry of
276,406 U.K. Biobank participants. We observe a strong, negative
genetic correlation between reproductive traits and life span.
Individuals with higher polygenetic scores for reproduction (PGS[R])
have lower survivorships to age 76 (SV[76]), and PGS[R] increased over
birth cohorts from 1940 to 1969. Similar trends are seen from
individual genetic variants examined. The antagonistically pleiotropic
variants are often associated with cis-regulatory effects across
multiple tissues or on multiple target genes. These and other findings
support the antagonistic pleiotropy hypothesis of aging in humans and
point to potential molecular mechanisms of the reproduction–life-span
antagonistic pleiotropy.
__________________________________________________________________
Mutations promoting reproduction tend to shorten lifespan but are
selectively favored in humans.
INTRODUCTION
Aging or senescence refers to a gradual deterioration of bodily
functions that manifests as a decline in reproductive performance and
an increase in the death rate with age ([26]1). The prevalence of aging
across multicellular organisms has been an evolutionary puzzle because
natural selection should favor mutations conferring an extended
reproductive life span ([27]2). In 1957, Williams ([28]3) proposed that
mutations contributing to aging could be positively selected if they
are advantageous early in life, promoting earlier reproduction or more
offspring. This antagonistic pleiotropy hypothesis has become one of
the leading theories of the evolutionary origin of aging (see
Discussion for other theories). Nonetheless, despite observations in
life-history evolution of trade-offs consistent with the antagonistic
pleiotropy hypothesis ([29]4, [30]5), the involvement of mutational
pleiotropy is usually difficult to establish ([31]6). Experimental
studies of model organisms have identified cases of antagonistic
pleiotropy between reproduction and life span ([32]6–[33]9), but how
frequently pleiotropy occurs between reproduction and longevity and how
common this pleiotropy is antagonistic as opposed to concordant are
unknown at the genomic scale. Further complicating the situation is the
fact that phenotypes measured in the laboratory can often deviate from
those measured in nature ([34]6). In humans, cases consistent with the
antagonistic pleiotropy hypothesis are known ([35]10, [36]11). For
example, genetic variants associated with coronary artery disease tend
to be associated with a higher number of children ever born (NEB)
([37]10). Furthermore, Wang et al. ([38]12) observed a significant,
negative genetic correlation between NEB and life span among female
(but not male) participants of the Framingham Heart Study in some of
their analyses. However, evidence for the antagonistic pleiotropy
hypothesis in humans have been contested ([39]13–[40]16), and the
hypothesis still lacks unambiguous genome-wide support. Furthermore, it
is unclear whether mutations contributing to aging were selectively
favored and whether the selection arose from their benefits earlier in
life.
One of the primary reasons why testing the antagonistic pleiotropy
hypothesis is difficult is that life-history traits tend to be
influenced by many small-effect genetic variants ([41]17, [42]18). The
U.K. Biobank has collected the genotypes and various phenotypes of
about 0.5 million participants ([43]19), offering an unprecedented
opportunity for testing the antagonistic pleiotropy hypothesis in
humans. In particular, the data include measures of human reproduction
such as age at menarche, number of offspring, and sexual dysfunction as
well as exact death information ([44]20). These phenotypic data along
with genotypic data allow assessing the genetic relationship between
reproduction and life span at the genomic scale and at the level of
individual segregating variants. Furthermore, functional genomic data
[e.g., expression quantitative trait locus (eQTL)] can be mined to
uncover the putative pathways and mechanisms underlying any
reproduction–life-span relationship ([45]21, [46]22). Taking advantage
of these resources, we performed multiple analyses outlined in
[47]Fig. 1 to address the following questions about the antagonistic
pleiotropy hypothesis. First, do genetic variants influencing
reproduction more likely affect life span than expected by chance?
Second, is the pleiotropy between reproduction and life span largely
antagonistic? Third, are pleiotropic mutations promoting reproduction
but causing aging favored by natural selection? Last, what are the
potential molecular mechanisms linking reproduction and aging?
Fig. 1. Schematics summarizing the approaches and analyses used in the
present study.
[48]Fig. 1.
[49]Open in a new tab
(A) Genetic correlation between reproduction and life span identified
from a list of previously computed genetic correlations for heritable
U.K. Biobank traits. Available traits include three reproductive
traits—nAFB, nAFS, and NCF—as well as two parental life-span
traits—father’s age at death and mother’s age at death. (B) A total of
583 reproduction-associated variants are collected, and PGSs are
calculated for four reproductive traits: (i) nAFB, (ii) nAFS, (iii)
nAMC, and (iv) AMP. The probability of survival to age 76 (SV[76]) is
compared across equal-size groups of individuals with relatively low,
medium, and high PGS for each of the four reproductive traits. The
potential change of PGS over six 5-year birth cohorts from 1940 to 1969
is investigated. (C) Effects of individual variants on life span are
estimated from SV[76]. The observed amount of antagonistic pleiotropy
is compared with the random expectation. Potential allele frequency
changes over six 5-year birth cohorts from 1940 to 1969 are examined.
(D) Potential horizontal pleiotropy between reproduction and life span
is explored by controlling the NEB (NEB = 0, 1, 2, or 3). (E) Potential
molecular mechanisms of antagonistic pleiotropy are explored by
surveying the associated cis-regulatory activity of antagonistically
pleiotropic variants, their target genes, enriched pathways, and
relevance to human diseases. MAF, minor allele frequency; LD, linkage
disequilibrium.
RESULTS
Negative genetic correlation between reproduction and life span
The genetic correlation between two phenotypic traits is the proportion
of variance that the two traits share due to genetic causes and is a
measure of the contribution of pleiotropy to the covariation of the
traits ([50]23). Because the antagonistic pleiotropy hypothesis of
aging posits that the same mutations antagonistically affect
reproduction and life span, the hypothesis predicts a negative genetic
correlation between reproduction and life span. Because the life spans
of most U.K. Biobank participants are unknown (as they are still
living), we examined the genetic correlation between the reproductive
traits of U.K. Biobank participants and the life spans of their parents
by searching the genetic correlations between heritable traits in U.K.
Biobank previously computed by the Neale group ([51]24) (see Materials
and Methods). Note that both the number of offspring and timing of
reproduction impact a person’s fitness because earlier reproduction
means a shorter generation time and thereby a higher fitness even when
the number of offspring is the same. We therefore focused on three
reproductive traits available in the list—negative age at first birth
(nAFB), negative age at first sex (nAFS), and number of children
fathered (NCF); larger values of these traits correspond to higher
reproduction (i.e., earlier reproduction and/or more offspring). Note
that nAFB is a more accurate measure of the earliest reproduction of a
participant than nAFS, but nAFB was measured for female U.K. Biobank
participants only. Hence, we considered both nAFB and nAFS here, the
latter of which was measured for both male and female participants. We
examined two parental life-span traits—father’s age at death and
mother’s age at death. Reproduction and parental life span show a
significant negative genetic correlation in all pairwise comparisons
between the three reproductive traits and two life-span traits
([52]Table 1), supporting the antagonistic pleiotropy hypothesis.
Because NCF is measured in males only, whereas nAFB is measured in
females only, our results indicate that the genetic correlation between
reproduction and life span is negative in both sexes. Because the U.K.
Biobank also recorded the number of full brothers and that of full
sisters of each participant, we further examined the genetic
correlation between a participant’s parental reproduction and parental
life span. A significant genetic correlation was observed (data S1),
further supporting the antagonistic pleiotropy hypothesis.
Table 1. Genetic correlation between reproduction and parental life span.
The R[g] values are from
[53]www.nealelab.is/blog/2019/10/10/genetic-correlation-results-for-her
itable-phenotypes-in-the-uk-biobank and are all significant at P <
10^−7 except for that between NCF and father’s age at death (P = 1.4 ×
10^−5) and that between NCF and mother’s age at death (P = 2.0 ×
10^−5).
Genetic correlation coefficient R[g] nAFS nAFB NCF Father’s age at
death Mother’s age at death
nAFS 1 0.84 0.48 −0.59 −0.75
nAFB 0.84 1 0.45 −0.66 −0.80
NCF 0.48 0.45 1 −0.29 −0.33
Father’s age at death −0.59 −0.66 −0.29 1 0.91
Mother’s age at death −0.75 −0.80 −0.33 0.91 1
[54]Open in a new tab
In addition to biological pleiotropy (one mutation affecting multiple
traits) and statistical pleiotropy (linked mutations affecting multiple
traits), both of which are relevant to the antagonistic pleiotropy
hypothesis, genetic correlation could also be caused by two factors
unrelated to the antagonistic pleiotropy hypothesis. The first is
population stratification and the second is cross-trait assortative
mating ([55]25). Our above results should not be affected by population
stratification because it had been controlled in genome-wide
association analysis (GWAS) based on which genetic correlations were
computed ([56]24). There should be no assortative mating between
reproductive traits and life span because life span is unknown at the
time of mating.
Higher polygenic scores for reproduction predict lower probabilities of
survival to age 76
Although the life spans of many U.K. Biobank participants are unknown,
the deaths of some participants allow reliable estimation of the
probability of survival to various ages (up to the age of 76 years),
providing an opportunity to assess the potential genetic impact of
reproduction on the life span. We focused on 276,406 participants of
British ancestry with no kinship to other participants in the database
(see Materials and Methods) and considered 891 genetic variants
reported to be associated with at least one reproductive trait with
genome-wide significance (P ≤ 5 × 10^−8) ([57]26). After the removal of
variants with high linkage disequilibrium [R^2 (coefficient of
determination) > 0.8; the variant with a relatively high P value is
excluded] and those with low minor allele frequencies (<0.05), 583
genetic variants remained, which are associated with the following
reproductive traits: (i) nAFB, (ii) nAFS, (iii) negative age at
menarche (nAMC), (iv) age at menopause (AMP), (v) NEB, which is the NCF
for a male or number of children mothered for a female, and (vi)
polycystic ovary syndrome (PCOS) (data S2 and see Materials and
Methods).
An individual’s polygenic score (PGS) of a trait reflects the
individual’s estimated genetic predisposition for the trait; it
measures the individual’s likelihood of having the trait based
exclusively on genetics without taking environmental factors into
account. To assess the aggregated effect of the above
reproduction-associated genetic variants, we computed the PGSs of four
reproduction traits each associated with at least 50 variants: nAFB,
nAFS, nAMC, and AMP (see Materials and Methods). nAMC, nAFS, and nAFB
measure the onset of reproduction, while AMP measures the end of
reproduction, so together they inform the timing and potential amount
of reproduction. NEB and PCOS are not considered here because they each
have fewer than 50 variants. The survival rate per year from the age of
40 to 76 years and the cumulative survival probability for homozygotes
of each variant were calculated (see Materials and Methods). The
log-rank method was used to test the difference in survivorship between
two genotypes. For example, individuals ranked in the top third in PGS
for nAFB (PGS[nAFB]) have a significantly lower probability of survival
to age 76 (SV[76] = 0.800) than that of individuals ranked in the
bottom third in PGS[nAFB] (SV[76] = 0.839) (P = 3.5 × 10^−4;
[58]Fig. 2A), supporting the antagonistic pleiotropy hypothesis.
Qualitatively similar results were observed when the PGS for each of
the other three reproductive traits was examined ([59]Fig. 2B and fig.
S1).
Fig. 2. Higher PGSs for reproduction predict lower probabilities of survival
to the age of 76 years (SV[76]).
[60]Fig. 2.
[61]Open in a new tab
(A) SV[76] of three equal-size groups of individuals with relatively
low, medium, and high PGS for nAFB (PGS[nAFB]). SV[76] = 0.839, 0.811,
and 0.800 for relatively low, medium, and high PGS[nAFB] groups,
respectively. Plots of the other three reproductive traits are in
fig. S1. (B) SV[76] of three equal-size groups of individuals with
relatively low, medium, and high PGS for each of the four reproductive
traits (nAFB, nAFS, nAFS, AMP, and nAMC). Error bars show 95%
confidence intervals calculated by Clopper-Pearson exact methods.
Log-rank *P < 0.05 and **P < 0.001 between the relatively low and high
PGS groups. (C) Mean PGS for each reproductive trait inferred from
genotypes of each of the six 5-year birth cohorts. Error bars showing
standard errors are too small to see. *P < 0.05 and **P < 0.001, linear
correlation between mid-point birth year of a cohort and PGS.
Dividing the 276,406 individuals into six 5-year birth cohorts
(1940–1944, 1945–1949, …, and 1965–1969), we investigated the change of
the PGS of each of the four reproductive traits over birth cohorts. As
shown in [62]Fig. 2C, for each of these traits, PGS steadily increased
over time, presumably a result of natural selection for higher
reproduction (see below for the analysis of individual variants that
controls the potential age effect and genetic drift effect).
Together, the analyses of PGS for reproduction provide evidence for (i)
antagonistic pleiotropy between reproduction and life span and (ii)
natural selection for higher reproduction (presumably to the detriment
of life span), supporting the antagonistic pleiotropy hypothesis of the
origin of aging.
Genetic variants exhibiting antagonistic pleiotropy between reproduction and
life span
We further tested the antagonistic pleiotropy hypothesis by identifying
genetic variants associated with both reproduction and life span. On
the basis of the directions of significant effects of an allele on
reproduction and life span (see Materials and Methods), we inferred
whether a variant shows antagonistic pleiotropy ([63]Fig. 3A),
concordant pleiotropy ([64]Fig. 3B), or no pleiotropy. Among the 583
reproduction-associated variants, 123 variants have significant effects
on SV[76] [false discovery rate (FDR) < 0.05], and antagonistic
pleiotropy cases significantly outnumber concordant pleiotropy cases
(98 antagonistic versus 25 concordant pleiotropy cases; P < 0.00001,
two-tailed binomial test; [65]Fig. 3C and data S3). As a negative
control, we sampled 100 sets of 583 random variants with matched allele
frequencies (±1%) and recombination rates (±0.05 cM/Mb), but none of
these sets contained ≥123 variants with significant effects on SV[76].
There is also no significant bias toward antagonistic pleiotropy for
these control variants (on average, 13 antagonistically versus 12
concordantly pleiotropic variants per set if the matched allele is
considered beneficial to reproduction). Therefore, compared with random
polymorphisms, those impacting reproduction are 4.9 times more likely
to affect life span and 7.5 times more likely to affect life span
antagonistically.
Fig. 3. Reproduction-enhancing alleles tend to lower life span and be
selectively favored.
[66]Fig. 3.
[67]Open in a new tab
(A) An example of a variant that has antagonistic effects on
reproduction (nAMC) and probability of survival to age 76 (SV[76]).
SV[76] = 0.835 for G/G (lower reproduction genotype) and 0.804 for A/A
(higher reproduction genotype) (FDR = 1.4 × 10^−6). Δ is the difference
in SV[76] between lower and higher reproduction homozygotes for the
variant considered. (B) An example of a variant with concordant effects
on reproduction (AMP) and SV[76]. V[76] = 0.820 for T/T (lower
reproduction genotype) and 0.836 for C/C (higher reproduction genotype)
(FDR = 0.001). *FDR < 0.05 and **FDR < 0.001. (C) Effects (Δ) on SV[76]
of 583 reproduction-associated variants. Each dot represents one
variant, whose genomic coordinate is shown on the x axis (chromosome 1
to 22, and X for each interval from left to right). Red and blue dots
indicate variants with significant antagonistic and concordant effects
on SV[76], respectively, whereas gray dots indicate variants with no
significant effects on SV[76]. The horizontal line indicates no effects
on SV[76]. (D) Two examples of variants showing allele frequency
changes over six 5-year birth cohorts (red for an increased trend and
blue for a decreased trend). Slope and FDR are from linear regression.
Error bars represent standard errors. (E) Allele frequency changes for
98 antagonistically pleiotropic variants. Each dot represents one
variant, whose genomic coordinate is shown on the x axis (chromosome 1
to 22). Y axis refers to the slope of the linear regression as in (D).
Red and blue dots indicate significantly positive and negative slopes,
respectively, whereas gray dots indicate nonsignificant slopes. The
horizontal line indicates a slope of 0.
Because average participants in the U.K. Biobank live many more years
after the end of reproduction, the antagonistic pleiotropy hypothesis
predicts that most mutations that increase reproduction but reduce life
span have larger fitness advantages than disadvantages so are
selectively favored. To verify this prediction, for each of the 98
variants exhibiting antagonistic pleiotropy between reproduction and
life span, we investigated the frequency change of the allele
beneficial to reproduction over the six birth cohorts after the
correction for different ages of different birth cohorts at the time of
the U.K. Biobank recruitment (see Materials and Methods) ([68]27). At
an FDR of 0.05, we detected significant allele frequency increases at
12 variants and decreases at 2 variants ([69]Fig. 3D), the former being
significantly more prevalent than the latter (P = 0.006, one-tailed
binomial test; [70]Fig. 3E and data S4). To account for the effect of
genetic drift on allele frequency changes ([71]28), we applied a
robustness test (see Materials and Methods) and validated 6 of the
above 14 cases, all showing allele frequency increases (data S4). These
results demonstrate that among polymorphisms with antagonistic
pleiotropy between reproduction and life span, alleles advantageous to
reproduction tend to be selectively favored, supporting the
antagonistic pleiotropy hypothesis.
Horizontal pleiotropy between reproduction and life span
To understand the antagonistic pleiotropy between reproduction and life
span, we investigated the relationship between the PGSs of the four
reproductive traits and SV[76] by controlling the NEB (NEB = 0, 1, 2,
or 3). Individuals with four or more children are too few to allow
reliable estimation of SV[76] in each PGS subgroup. Among individuals
with the same NEB, SV[76] is negatively correlated with the PGS for
each of the four reproductive traits ([72]Fig. 4), suggesting that the
antagonistic pleiotropy between reproduction and life span is, at least
in part, independent from the actual amount of reproduction. In other
words, there must be horizontal antagonistic pleiotropy between
reproduction and life span. We also performed the analysis for males
and females separately and observed a negative correlation between PGS
and SV[76] in each stratified subgroup without significant
gender-specific effects, although the negative correlation is sometimes
not significant due to reduced sample sizes (data S5).
Fig. 4. Probability of survival to age 76 (SV[76]) as a function of the NEB
and PGSs for four reproductive traits.
[73]Fig. 4.
[74]Open in a new tab
The four reproductive traits include nAFB (A), nAFS (B), AMP (C), and
nAMC (D). Each dot represents individuals with the highest, medium, or
lowest third of PGS considered. Error bars show 95% confidence
intervals calculated by Clopper-Pearson exact methods. *P < 0.05 and
**P < 0.001 between the low and high PGS groups. Gender-specific
results are in data S5.
Given the reproductive PGS (regardless of which of the four
reproductive traits is considered), individuals with NEB = 2 had the
highest SV[76] among the four groups of individuals with different NEBs
([75]Fig. 4). Our finding is consistent with the report that females
with two children had the lowest mortality risk among all females in
the Framingham Heart Study ([76]12), although our analysis further
controlled reproductive PGS. These results indicate that the
relationship between NEB and longevity is complex; it is positive in
the low NEB range (below 2) but negative in the high NEB range
(exceeding 2).
Potential molecular mechanisms
To explore the potential mechanisms involved in the antagonistic
pleiotropy between reproduction and life span, we queried an aggregated
eQTL database—eQTL catalog ([77]22). This is because the
antagonistically pleiotropic variants detected are mostly in noncoding
regions and may play cis-regulatory roles in regulating target gene
(eGene) expression. We divided the 583 reproduction-associated variants
into three sets, depending on whether the variants have significant
antagonistic effects on life span (antagonistic pleiotropy set),
significant concordant effects on life span (concordant pleiotropy
set), or no significant effects on life span (control set). Relative to
the control set, antagonistic and concordant pleiotropy sets both
contain a higher fraction of variants associated with cis-regulatory
activities (eQTLs with empirical genome-wide significance)
([78]Table 2). We defined three different types of cis-regulatory
events: multicontext (associated with cis-regulatory activities in
multiple tissues/cell lines), multi-eGene (associated with the
expressions of multiple eGenes), and discordant (discordant effects on
an eGene across tissues/cell lines). When compared with the control
set, antagonistic and concordant pleiotropy sets are enriched with
multicontext and multi-eGene events ([79]Table 2). In addition, the
antagonistic pleiotropy set is enriched with discordant events
([80]Table 2). Note that these differences are not due to potential
disparities in statistical power in eQTL mapping across the three sets
of variants because we found no significant differences in minor allele
frequencies across them. These results suggest that a common molecular
mechanism of antagonistic pleiotropy between reproduction and life span
is for a cis-regulatory mutation to influence the expressions of the
same target gene in different tissues (sometimes with opposite
directions) and to influence the expressions of multiple target genes.
Table 2. Number of reproduction-associated variants associated with
cis-regulatory activities.
*P < 0.05 and **P < 0.001 in a chi-squared test via comparison with the
bottom set of variants.
Set name No. of variants Cis-regulatory activity Multi-context events
Multi-eGene events Discordant events
Antagonistic effect on longevity 98 75* 62** 54* 24*
Concordant effect on longevity 25 18* 15* 15* 6
No effect on longevity 459 221 124 162 64
[81]Open in a new tab
A total of 230 candidate eGenes from the antagonistic pleiotropy set
reached empirical genome-wide significance in eQTL analysis.
Significantly enriched pathways for these eGenes included those related
to hormone (estrogen receptor signaling), immune response (IL-15
production), and age-related pathology (amyloid processing and protein
ubiquitination pathway) (data S6). Additional mechanistic insights can
be gained from examining individual antagonistically pleiotropic
variants. For example, variant rs12203592 at chromosome 6p25.3 has its
major T allele associated with a younger age at first sexual
intercourse and an increased risk of mortality and shows a rise in the
frequency of the T allele over 25 years (data S3). Previous GWAS
suggested that the T allele is additionally associated with decreased
parental life span ([82]29) and increased risk of multiple cancers such
as melanoma ([83]30) and lung cancer ([84]31). This variant is also
associated with multicontext, multi-eGene (IRF4 and EXOC2), and
discordant cis-regulatory events. Specifically, the T allele is
correlated with higher IRF4 expressions in the lung and whole blood but
lower IRF4 expression in skin tissues. Higher IRF4 expressions in the
human lung were reported to promote endogenous DNA damage in lung
fibroblasts ([85]31). Another antagonistically pleiotropic
variant—rs34811474 at chromosome 4p15.2—has its reproduction-enhancing
G allele associated with an increased risk of osteoarthritis, an
age-related degenerative disease ([86]32). The rs7719499 G allele, in
linkage disequilibrium (R^2 = 0.73, European population, 1000 Genome
Project) with the reproduction-enhancing allele of the antagonistically
pleiotropic variant rs13164856, is associated with an increased risk of
cardiovascular diseases ([87]33). These examples show that
susceptibilities to various diseases underlie the antagonistically
pleiotropic effects of reproduction-enhancing alleles, consistent with
findings in several previous studies ([88]10, [89]34, [90]35).
DISCUSSION
Using the U.K. Biobank, we performed a series of trait-level and
variant-level analyses to test the antagonistic pleiotropy hypothesis
of the evolution of human aging at the genomic scale. At the trait
level, we observed a strong negative genetic correlation between
reproduction and parental life span as well as that between parental
reproduction and parental life span, found that the probability of
survival to the age of 76 is negatively correlated with PGSs for
reproduction, and detected increases in these PGSs over 25 years. At
the variant level, we found that alleles associated with higher
reproduction tend to be associated with lower survival to the age of 76
and that frequencies of some of these alleles have increased over the
years in a pattern consistent with the action of positive selection.
These findings together provide strong genome-wide evidence for the
antagonistic pleiotropy hypothesis of aging in humans. That there was
ongoing selection for human reproduction as recent as a few decades ago
suggests that the optimal genotype for reproduction had not been
reached, possibly due to rapid environmental changes. We found that at
least some antagonistically pleiotropic variants exhibit horizontal
pleiotropy, meaning that they influence life span and reproduction
through different pathways (as opposed to affecting life span as a
result of affecting reproduction). Analysis of an eQTL database
suggests that the pleiotropic effects may be often realized through
cis-regulatory effects in multiple tissues and/or on multiple target
genes.
The antagonistic pleiotropy hypothesis of aging posits that at least
some mutations antagonistically affect reproduction and life span,
without requiring that this antagonistic pleiotropy is enriched.
However, relative to comparable mutations selected at random, we found
that mutations impacting reproduction were 4.9 times more likely to
influence life span and 7.5 times more likely to have that influence
reflect antagonistic pleiotropy. In other words, mutational antagonism
between reproduction and life span far exceeds that expected for a
random pair of traits. In terms of the potential biological reasons
behind this phenomenon, it is worth mentioning the disposable soma
theory of aging ([91]36), which posits that organisms have limited
resources, such that a greater investment in reproduction would lead to
a lower investment in DNA repair maintenance, causing accumulation of
somatic mutations and aging. The recent report of an inverse
relationship between somatic mutation rate per year and life span
across 16 mammalian species ([92]37) is consistent with this theory.
Although this theory does not specifically invoke pleiotropy, the
reproduction–life-span tradeoff arising from resource limitation could
be an explanation for antagonistic pleiotropy. Note that some
mechanisms mediating the reproduction–life-span antagonistic pleiotropy
in our study are probably human specific. For instance, a mutation that
negatively affects educational attainment might simultaneously increase
reproduction ([93]38) and reduce longevity ([94]39). By contrast, pure
environmental factors that antagonistically affect reproduction and
longevity (e.g., socioeconomic status) are irrelevant to the
antagonistic pleiotropy hypothesis of aging, nor do they confound our
genetic analyses such as genetic correlation, PGS calculations, and
natural selection.
Given the recently raised concern of a potential publication bias
toward empirical evidence for the reproduction-longevity trade-off
([95]40), it is worth discussing the mutation accumulation theory of
aging proposed by Medawar ([96]41). This theory asserts that aging is
an inevitable consequence of the reduction in the efficacy of natural
selection with age, that is, a mutation killing youth will be strongly
selected against but a lethal mutation exerting its effect only after
reproduction will experience limited or even no negative selection.
Over generations, late-acting deleterious mutations will accumulate,
leading to an increase in mortality rates late in life. Because U.K.
Biobank participants were at least 40 years old at the time of
participation, our life-span analysis was largely concentrated on the
post-reproductive life span; consequently, our finding of
antagonistically pleiotropic variants influencing the life span is
consistent with the mutation accumulation theory. Nevertheless, the
mutation accumulation theory posits that late-acting deleterious
mutations accumulate by genetic drift, while the antagonistic
pleiotropy theory asserts that they are selectively favored due to the
positive effects on reproduction. We found that the frequencies of
reproduction-promoting alleles of some antagonistically pleiotropic
variants and the PGSs for reproduction increased over years, providing
strong support for the antagonistic pleiotropy theory. This, however,
does not reject the mutation accumulation theory because the two
theories are not mutually exclusive, that is, the fixations of some
aging-promoting alleles may follow the antagonistic pleiotropy theory
(i.e., by positive selection), while others may follow the mutation
accumulation theory (i.e., by genetic drift).
While our analysis focused on the genetic relationship (i.e.,
mutational pleiotropy) between reproduction and life span, the
phenotypic relationship between reproduction and life span is debated.
For example, a negative relationship between female fertility and
longevity was reported in Chinese oldest-old individuals ([97]42),
while an opposite trend was found in the Amish ([98]43). In our data,
given PGSs for reproduction, individuals with two children have a
higher probability of survival to 76 than those with 0, 1, or 3
children. Hence, the phenotypic relationship between reproduction and
life span is complex and nonmonotonic. Furthermore, the phenotypic
correlation does not equal causality because of potential confounding
factors such as socioeconomic status.
Human life expectancy, birth rate, and reproductive behavior have all
changed markedly in the last few decades ([99]44–[100]46).
Specifically, more than half of humans live in areas of the world where
birth rates have declined, along with increased incidences of
contraception, abortion, and reproductive disorder ([101]47). The
global human life expectancy at birth, on the other hand, has steadily
increased from 46.5 years in 1950 to 72.8 years in 2019 ([102]48,
[103]49). These trends of phenotypic changes are primarily driven by
substantial environmental shifts including changes of lifestyles and
technologies and are opposite to the phenotypic changes caused by
natural selection of the genetic variants identified in this study.
This contrast indicates that, compared with environmental factors,
genetic factors play a minor role in the human phenotypic changes
studied here. A potential consequence of the environmental shift is
that alleles with increased frequencies over time will tend to
correlate with a longer life span, which would make our conclusion
about antagonistic pleiotropy more conservative. Another potential
consequence is that the extended life expectancy exposes the
antagonistic pleiotropic effects of genetic variants that did not incur
costs in the past when life was, on average, shorter ([104]50).
Our study has several limitations. First, U.K. Biobank participants may
be a biased sample of the general population because rates of all-cause
mortality and the total cancer incidence are lower in the U.K. Biobank
than in the general population ([105]51). Therefore, the survival
probability estimated here may be higher than that in the general
population, but this factor presumably does not influence the allelic
comparisons within the U.K. Biobank. Second, because the life
expectancy of our study samples is beyond 76 years ([106]49), the
genetic effect on life span is likely underestimated in our study,
rendering our conclusion on the negative life-span impact of
reproduction-enhancing mutations conservative. However, if life span
≤76 years and that >76 years are controlled by largely nonoverlapping
loci, our finding would be limited to the former. Third, our
observation of allele frequency changes over the six 5-year birth
cohorts are consistent with the action of natural selection but does
not directly document allele frequency changes between parental and
offspring generations because generations are overlapping and only
members of the first cohort are likely to be parents of some of the
members of the last cohort. Fourth, a substantial fraction of
antagonistically pleiotropic variants (23 of 98 = 23.5%) do not have a
match in the eQTL database, and we do not know how they influence
reproduction and life span. This fraction is on par with the finding
that even multiple bulk tissue eQTL data could not explain ~40% of the
GWAS-identified variants ([107]21, [108]31). Future cell type–specific
eQTL and other molecular trait (e.g., methylation) data might help
elucidate the mechanisms by which these antagonistically pleiotropic
variants act ([109]52). Fifth, our study is solely based on GWAS
findings and health records from European-descent individuals.
Therefore, one needs to be cautious when generalizing our findings to
other populations because of their different social and environmental
factors and genetic backgrounds. Future validation of our findings in
other populations, especially those currently underrepresented in
biobanks ([110]53), is highly desired.
MATERIALS AND METHODS
Study participants and data used
The U.K. Biobank data comprise about 0.5 million participants aged 40
to 70 years, recruited between 2006 and 2010 in 22 assessment centers
throughout the United Kingdom and followed up for a variety of health
conditions from their recruitment date to 17 February 2016 or their
date of death ([111]19). Participants provided a blood sample, from
which DNA was extracted and genotyped using the U.K. BiLEVE Axiom array
or Affymetrix Axiom array ([112]19). We used the imputed genotypes
available from the U.K. Biobank; full details can be found in the U.K.
Biobank imputation document
([113]http://biobank.ctsu.ox.ac.uk/crystal/crystal/docs/impute_ukb_v1.p
df, accessed on 16 April 2022). The current study was approved by the
U.K. Biobank (reference no. 48678), and the analyses presented were
based on data from 488,377 individuals accessed through the U.K.
Biobank ([114]www.ukbiobank.ac.uk) on 12 February 2022.
From the entire set of 488,377 individuals with genotype information,
we removed individuals with any of the following conditions to prevent
population stratification: self-report of non-white British ethnicity,
genetic principal components indicative of non-European ancestry, at
least one relative in the data identified by genetic kinship, outlying
level of genetic heterozygosity, and withdrawal of informed consent.
Our final analysis included 276,406 unrelated individuals of European
ancestry.
Reproduction-associated variants
We collected reproduction-associated variants from National Human
Genome Research Institute GWAS catalog at genome-wide significance (P ≤
5 × 10^−8) by searching three types of reproductive traits: sexual
maturation, reproductive behavior, and infertility risk (full lists in
data S7). GWASs performed or replicated in European populations were
included, resulting in 891 unique variants that are associated with at
least one reproductive trait.
We then tested linkage disequilibrium among these 891 variants in the
European population (1000 Genomes Project, phase 3) by LDlink
([115]54). For two variants with high linkage disequilibrium (R^2 >
0.8), the one with the relatively low P value (more significant in
GWAS) was retained, while the other was discarded. The variants with
minor allele frequencies <0.05 were removed. The final dataset
consisted of 583 genetic variants associated with six reproductive
traits: (i) nAMC, (ii) AMP, (iii) nAFS, (iv) nAFB, (v) NEB, and (vi)
PCOS (data S1). nAMC, nAFS, and nAFB measure the onset of reproduction,
while AMP measures the end of reproduction, so together they inform the
timing and potential amount of reproduction. NEB measures the actual
number of children. PCOS is one of the most common causes of
infertility with a relatively large genetic component ([116]55). By
coincidence, each of these 583 variants is associated with only one of
the above six reproductive traits. Hence, the direction of the allelic
effect of each of these variants on reproduction was unambiguously
determined.
Estimation of survival probabilities
We estimated the survival probability based on Cox proportional hazard
models ([117]56). The death records in the U.K. Biobank were updated
quarterly with the U.K. National Health Service (NHS) Information
Centre for participants from England and Wales and with NHS Central
Register, Scotland for participants from Scotland. The latest date of
death among all registered deaths in the downloaded data is 31 October
2018, and we used this date to approximate the time of last death entry
and assumed that we have no mortality or viability information for the
volunteers after this date. Specifically, we used five entries—age at
recruitment, date of recruitment, year of birth, month of birth, and
age at death—to calculate the number of individuals (N[i]) who are
ascertained from age i to age i + 1, and the occurrence of death
observed (O[i]) from these N[i] individuals during the interval of age
i to age i + 1. Using this information, we calculated the ascertained
age for each individual. The death rate per year is then calculated as
h[i] = O[i]/N[i], and the probability of survival to age i from age 40
is
[MATH:
Si=∏
n=40n=i(1−hn) :MATH]
. The U.K. Biobank data allow estimation of h[40], h[41], …, and h[75]
with N[i] > 800. We estimated h[i] for the homozygotes of each variant.
Allele frequency changes over years and controls of the age effect and
genetic drift effect
We computed the frequency of the allele beneficial to reproduction at
each relevant variant in each birth cohort using PLINK v2 ([118]57).
Because different birth cohorts had different ages at the time of
recruitment by the U.K. Biobank (year 2006–2010; ~66 years old for the
earliest birth cohort and ~41 years old for the latest cohort) and
because some alleles affect longevity, a fair comparison of allele
frequencies across birth cohorts require an equal age of participants
of different cohorts. To this end, we used the probability of survival
to correct the allele frequency to the age of 41 for each birth cohort.
For example, let N[A/A] be the number of individuals with genotype A/A
in the birth cohort of 1940–1944 (age ~ 66 at the U.K. Biobank
recruitment) and let P[66A/A] be the probability of survival to age 66
from 41 for the genotype A/A. The number of A/A individuals at age 41
was inferred to be N[A/A] divided by P[66A/A], and the allele frequency
was then calculated using corrected numbers of individuals of all
genotypes. For each considered variant, allele frequency in a birth
cohort was linearly regressed against the mid-point of the birth years
of the cohort (1942.5, 1947.5, …, 1967.5), as described previously
([119]27). P-values from linear regressions were corrected for multiple
testing by the Benjamini-Hochberg procedure. To consider the effect of
genetic drift on allele frequency changes ([120]28), we used a
robustness test by further dividing individuals into 15 2-year birth
cohorts (1940–1941, 1942–1943,…, 1966–1967, and 1968–1969). The allele
frequency difference between the first (1940–1941) and second
(1942–1943) cohort is denoted as d[1], and the difference between the
third (1944–1945) and fourth (1946–1947) cohort is denoted as d[2], and
so on. This resulted in seven independently estimated d values. We
considered a variant to have changed its allele frequency consistently
over the years when all seven d values are of the same sign because
this event has a chance probability of only 0.5^6 = 1/64 = 0.016.
Polygenic scores
We computed the PGSs for four reproductive traits (nAFB, nAFS, AMP, and
nAMC) each with >50 associated variants. All included variants were
independent from one another in contributing to the trait of concern
and reached genome-wide significance (see above). PLINK v2 ([121]57)
was used to calculate the PGS of each individual with the following
formula
[MATH: PGSj=<
mfrac>∑iN
SiG
ij2Mj :MATH]
where G[ij] is the number of reproduction-enhancing alleles at variant
i in individual j, S[i] is the effect size (beta) of variant i, N is
the number of variants included in the calculation, and M[j] is the
number of nonmissing variants observed in individual j.
Genetic correlation survey
We surveyed the genetic correlations computed for the significantly
heritable phenotypes in the U.K. Biobank that are available at
[122]www.nealelab.is/blog/2019/10/10/genetic-correlation-results-for-he
ritable-phenotypes-in-the-uk-biobank. Methodological details have been
published ([123]24).
eQTL survey
We surveyed uniformly processed eQTLs across 69 distinct cell/tissue
types from 21 available public studies aggregated by eQTL catalog
([124]22). Significant eQTLs were defined using the empirical
genome-wide significance threshold as previously described ([125]21,
[126]22). Antagonistically pleiotropic variants were nominated with
cis-regulatory activities if they displayed significant eQTL signals
for at least one of the significant target genes (eGenes). In addition,
we defined three types of cis-regulatory events: (i) multicontext
events: significant eQTL signals in more than one tissue/cell type;
(ii) multi-eGene events: significant eQTL signals for more than one
eGene; and (iii) discordant events: discordant directions of allelic
effects for a single eGene across tissues/cell types. The nominated
eGenes from antagonistically pleiotropic variants were subjected to
pathway enrichment analysis by Ingenuity Pathway Analysis. Unique
pathways enriched in antagonistically pleiotropic variants were defined
by comparing with the enriched pathways from eGenes of
reproduction-associated variants with no significant effects on life
span (data S6).
Acknowledgments