Final Report Summary - INTEGRAGEING (Modelling human ageing: developing and interrogating an integrated model of ageing to identify causal relationships between hormonal changes and gene expression changes) The process of ageing is characterized by multiple changes, both physiological and at gene expression level. In this project we integrated and analyze these types of changes and by employing mathematical models and computational methods we investigated the relationships between gene expression changes and hormonal changes with age. Specifically, we have reviewed and collected age-related changes from the scientific literature and categorized them in the "Digital Ageing Atlas" (http://ageing-map.org/) database (including hormonal and molecular changes). At the moment, data exists for more than 2600 gene expression changes, as well as for many hormones, including insulin-like growth factor, growth hormone, testosterone, gonadotropin-releasing hormone, luteinizing hormone, follicle stimulating hormone, sex hormone binding globulin, adrenocorticotropic hormone and thymic hormone. Many of the curated changes (limited by the availability of existing raw data) have been converted to mathematical representations (linear and non-linear). These models have in turn been used to better understand the links between downstream targets and signalling pathways triggered by the activation of hormones, and more widespread gene-expression changes. While our focus has been so far on well-known signalling pathways of major hormones implicated in ageing (like growth hormone, insulin and IGF1) and on previously associated longevity-associated genes, a computational pipeline has been developed, and the methodology can be easily used for other sets of genes or biological processes. Although our initial aims did not include flies as a model organism for the current project, a new collaboration project has also provided us with the unique opportunity to look into the differences between tissue-specific gene-expression changes under dietary manipulations of ageing. This has led us to investigate the communication between the different gene expression signatures for various tissues, how these signatures are linked to each other, and whether this inter-tissue communication could take place through neuropeptides and hormonal signaling. Overall, we believe that this project will have a strong impact both in the field of ageing, by providing fundamental insights into the coordination of physiological and molecular changes with age, but also, more generally, in bioinformatics and computational biology through the developed bioinformatics methods.