Developing strategies to cope with increase in the ageing population and age-related chronic diseases is one of the societies biggest challenges. The characteristics of the ageing process shows significant inter-individual variation. Building genomic signatures that could account for variation
in health outcomes with age may facilitate early prognosis of individual age-correlated diseases (e.g. cancer, coronary artery diseases and dementia) and help in developing better targeted
treatments provided years in advance of acquiring disabling symptoms for these diseases. The aim of this thesis was to explore methods for diagnosing molecular features of human ageing. In
particular, we utilise multi-platform transcriptomics, independent clinical data and classification
methods to evaluate which human tissues demonstrate a reproducible molecular signature for age
and which clinical phenotypes correlated with these new RNA biomarkers. [Continues.]
A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.