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Zagkos, L.

Publications and source records attributed to Zagkos, L..

2 recordsLinked to original sources
bioRxiv2021

Adolescents' dietary habits and meal patterns influence school performance in the Northern Finland Birth Cohort 1986: mendelian randomisation study

Several observational studies indicate that dietary habits in children and adolescents are associated with school performance. These associations are heavily confounded by socio-economic characteristics, such as household income and parents educational attainment, amongst other factors. In this study, we report observational and causal effects of habitual diet on school performance, using individual level data for 9,220 adolescents in the Northern Finland Birth Cohort 1986. For this purpose, we derived principal components for the dietary variables, meal patterns and school performance variables. The observational study showed a significant association of consumption of foods that are high in fat, salt and sugar (HFSS) with poor performance in all school subjects, and an association of consumption of healthy foods and traditional foods with good school performance in general subjects, science and physical education (PE). Moreover, a positive association was observed between not skipping breakfast and good performance in all school subjects. Mendelian randomisation analysis confirmed a negative effect of HFSS on school performance in general/science subjects (-0.080, -0.128 to -0.033) and a positive effect of healthy food on school performance in general/science subjects (0.071, 0.024 to 0.119) and PE (0.065, 0.021 to 0.110). To conclude, we identified compelling evidence that HFSS foods and healthy foods were causally affecting school performance.

bioinformatics↗
bioRxiv2021

A Mathematical Model which Examines Age-Related Stochastic Fluctuations in DNA Maintenance Methylation

Due to its complexity and its ubiquitous nature the ageing process remains an enduring biological puzzle. Many molecular mechanisms and biochemical process have become synonymous with ageing. However, recent findings have pinpointed epigenetics as having a key role in ageing and healthspan. In particular age related changes to DNA methylation offer the possibility of monitoring the trajectory of biological ageing and could even be used to predict the onset of diseases such as cancer, Alzheimers disease and cardiovascular disease. At the molecular level emerging evidence strongly suggests the regulatory processes which govern DNA methylation are subject to intracellular stochasticity. It is challenging to fully understand the impact of stochasticity on DNA methylation levels at the molecular level experimentally. An ideal solution is to use mathematical models to capture the essence of the stochasticity and its outcomes. In this paper we present a novel stochastic model which accounts for specific methylation levels within a gene promoter. We quantify the uncertainty of the eventual cite-specific methylation levels for different values of methylation age, depending on the initial methylation levels. Our model predicts the observed bistable levels in CpG islands. In addition, simulations with various levels of noise indicate that uncertainty predominantly spreads through the hypermethylated region of stability, especially for large values of input noise. A key outcome of the model is that CpG islands with intermediate methylation levels tend to be more susceptible to dramatic DNA methylation changes towards both hypomethylation and hypermethylation, due to increasing methylation age.

systems biology↗