DNA repair and anti-cancer mechanisms in the longest-living mammal: the bowhead whale

Gabriel Arantes dos Santos, Gustavo Daniel Vega Magdaleno, João Pedro de Magalhães

Using machine learning, the researchers analyzed stemness—the fundamental properties of stem cells—in 17,382 healthy human tissue samples, aged between 20 and 79 years. They found that most tissues showed a significant decrease in stemness as age increased. The exception was the uterus, which showed increased stemness with age. Additionally, there was a general trend of stemness correlating positively with cell proliferation and negatively with cellular senescence. This evidence supports the hypothesis that stem cell deterioration contributes to human aging.

Thomas Duffield, Laura Csuka, Arda Akalan, Gustavo Daniel Vega Magdaleno, Daniel Palmer, João Pedro de Magalhães

This study proposes a new theory of biological systemic ageing centered on the role of epigenetic changes, particularly DNA methylation, in ageing processes. Researchers observed that certain classes of CpG DNA methylation loci demonstrate a variance increase correlated with chronological age, suggesting a built-in, unavoidable limitation in the fidelity of the epigenetic system. They propose that this fidelity limitation causes a progressive deregulation, leading to a 'phenotype of age'. A developed deep-learning model, utilizing knowledge of this deregulation, accurately predicts age across species. The study suggests that the inability to maintain perfect fidelity in all epigenetic information results in a feedback cycle of deregulation that accelerates ageing.

Anna Kankaanpää, Asko Tolvanen, Laura Joensuu, Katja Waller, Aino Heikkinen, Jaakko Kaprio, Miina Ollikainen, Elina Sillanpää

The study investigates the association between long-term leisure-time physical activity (LTPA), biological ageing, and mortality. It seeks to understand if LTPA patterns influence biological ageing and mortality, potentially mediating the beneficial relationship between LTPA and death from all causes. It also aims to account for reverse causality and genetic/environmental factors through prevalent disease accounting and a twin study design, as some suggest that LTPA may not prevent premature mortality, but reflect underlying good health.