Scientific Evidence Backs Antagonistic Pleiotropy Theory of Aging
Comprehensive studies have confirmed the antagonistic pleiotropy theory of aging, indicating a genetic correlation between high fertility and shortened lifespan. Nonetheless, environmental factors are highlighted as major influencers of modern human lifespan and reproductive behavior.
New research further supports the idea that genes promoting early reproduction can accelerate aging but emphasizes the overriding role of environmental factors in determining longevity and reproduction.
Originating in a 1957 theory proposed by evolutionary biologist George Williams, the antagonistic pleiotropy theory posits that genetic mutations favoring early reproduction could simultaneously contribute to aging, making life shorter.
The theory was tested in a new study led by the University of Michigan, involving over 276,000 individuals, reaffirming its validity. The researchers found distinct genome-wide evidence supporting the theory.
A novel breakthrough discovery showcased a strong negative genetic correlation between reproduction and longevity, suggesting that mutations promoting reproduction tend to shorten lifespan. However, this link is also influenced by environmental factors.
It was established that the number and timing of reproduction can impact lifespan. Remarkably, having two children was linked to the longest lifespan, according to this study, reinforcing previous research findings.
The concept of pleiotropy suggests that a single mutation can impact multiple traits, while antagonistic pleiotropy posits that mutations can be beneficial or harmful depending on various circumstances. The evolutionary basis of aging is seen through this lens.
In line with this, the study’s outcome points to significant environmental changes, such as lifestyle and technological advances, as opposed to genetic variants identified as drivers of human phenotypic changes.
Reference: “Evidence for the role of selection for reproductively advantageous alleles in human aging” by Erping Long and Jianzhi Zhang, December 8, 2023. DOI: 10.1126/sciadv.adh4990
Source: scitechdaily.com
