Abstract Machine learning models based on DNA methylation data can predict biological
age but often lack causal insights. By harnessing large-scale genetic data through …

Aging is one of the most important biological processes and is a known risk factor for many
age-related diseases in human. Studying age-related transcriptomic changes in tissues …

Individuals of the same age may not age at the same rate. Quantitative biomarkers of aging
are valuable tools to measure physiological age, assess the extent of 'healthy aging', and …

Biological aging reflects decline in physiological functions and is an effective indicator of
morbidity and mortality. Numerous epigenetic age calculators are available, however …

Ageing leads to dramatic changes in the physiology of many different tissues resulting in a
spectrum of pathology. Nonetheless, many lines of evidence suggest that ageing is driven …

Motivation: Numerous microarray studies of aging have been conducted, yet given the noisy
nature of gene expression changes with age, elucidating the transcriptional features of …

Biological aging is accompanied by increasing morbidity, mortality, and healthcare costs;
however, its molecular mechanisms are poorly understood. Here, we use multi-omic …

Biological age (BA), derived from molecular and physiological measurements, has been
proposed to better predict mortality and disease than chronological age (CA). In the present …

Of all the proposed causes of ageing, DNA damage remains a leading, though still debated
theory. Unlike most other types of age-related cellular damage, which can hypothetically be …

The aging process is characterized by the presence of high interindividual variation between
individuals of the same chronical age prompting a search for biomarkers that capture this …