ORCID Profile
0000-0002-2645-4292
Current Organisation
The University of Edinburgh
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Publisher: Cold Spring Harbor Laboratory
Date: 15-05-2023
DOI: 10.1101/2023.05.15.540689
Abstract: DNA methylation rates have previously been found to broadly correlate with maximum lifespan in mammals, yet no precise relationship has been observed. We compared methylation rates at conserved age-related sites across mammals in both skin and blood and found that methylation rates scale with maximum lifespan to the power of negative one. The emergence of an explicit scaling law suggests that methylation rate is either a fundamental limiting factor in maximum lifespan across species or is linked to an underlying universal constraint.
Publisher: Cold Spring Harbor Laboratory
Date: 28-05-2021
DOI: 10.1101/2021.05.27.446006
Abstract: The prevalence of clonal haematopoiesis of indeterminate potential (CHIP) in healthy in iduals increases rapidly from age 60 onwards and has been associated with increased risk for malignancy, heart disease and ischemic stroke. CHIP is driven by somatic mutations in stem cells that are also drivers of myeloid malignancies. Since mutations in stem cells often drive leukaemia, we hypothesised that stem cell fitness substantially contributes to transformation from CHIP to leukaemia. Stem cell fitness is defined as the proliferative advantage over cells carrying no or only neutral mutations. It is currently unknown whether mutations in different CHIP genes lead to distinct fitness advantages that could form the basis for patient stratification. We set out to quantify the fitness effects of CHIP drivers over a 12 year timespan in older age, using longitudinal error-corrected sequencing data. We developed a new method based on drift-induced fluctuation (DIF) filtering to extract fitness effects from longitudinal data, and thus quantify the growth potential of variants within each in idual. Our approach discriminates naturally drifting populations of cells and faster growing clones, while taking into account in idual mutational context. We show that gene-specific fitness differences can outweigh inter-in idual variation and therefore could form the basis for personalised clinical management.
Publisher: Cold Spring Harbor Laboratory
Date: 02-03-2023
DOI: 10.1101/2023.03.01.530570
Abstract: The emergence of epigenetic predictors was a pivotal moment in geroscience, propelling the measurement and concept of biological ageing into a quantitative era. However, while current epigenetic clocks have shown strong predictive power, they do not reflect the underlying biological mechanisms driving methylation changes with age. Consequently, biological interpretation of their estimates is limited. Furthermore, our findings suggest that clocks trained on chronological age are confounded by non-age-related phenomena. To address these limitations, we developed a probabilistic model that describes methylation transitions at the cellular level. Our approach reveals two measurable components, acceleration and bias, that directly relate to perturbations of the underlying cellular dynamics. Acceleration is the proportional increase in the speed of methylation transitions across CpG sites, whereas bias is the degree of global change in methylation affecting all CpG sites uniformly. Using data from 7,028 participants from the Generation Scotland study, we found the age acceleration parameter to be associated with physiological traits known to impact healthy ageing. Furthermore, a genome-wide association study of age acceleration identified four genomic loci previously linked with ageing.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Eric Latorre.