Functional genomics approaches to study healthy and unhealthy aging in the Rhineland Study

Aging is a complex and heterogeneous process, characterized by a decline in physiological functions and an increased risk of various diseases, including cardiovascular, neurodegenerative, and metabolic disorders. Although the molecular hallmarks of aging have been defined, individual aging trajectories vary widely due to a combination of intrinsic and extrinsic factors. This variability complicates the development of effective treatments aimed at promoting healthy aging. <br> Functional genomics offers a valuable framework for investigating the molecular mechanisms underlying aging and its related traits by focusing on intricate and dynamic biological processes, such as gene regulation, epigenetic changes, and RNA activity, and their interactions. In the studies described in this thesis, I leveraged multi-omics data, including genetics, transcriptomics and epigenomics, from the population-based Rhineland Study, to explore molecular signatures associated with aging-related traits. <br> Specifically, <br> 1. I investigated blood-based microRNAs associated with vascular health and cognitive function, identified the biological pathways they may regulate using gene expression data, and examined the influence of genetic variation on their expression. <br> 2. I explored the effects of age and sex on retrotransposable elements and assessed how their dysregulation may impact downstream molecular pathways by integrating their expression profiles with those of nearby genes. <br> 3. Finally, I used gene expression data to functionally interpret genome-wide association study (GWAS) and epigenome-wide association study (EWAS) findings, aiming to uncover biological pathways underlying associations between genetic variants and complex lipids, as well as between DNA methylation patterns and hippocampal volume and asymmetry. <br> I identified blood-based microRNAs associated with vascular traits, such as arterial compliance and cardiac function, and cognitive function. By integrating gene expression data, I found that these microRNAs potentially regulate key biological pathways including blood vessel development, angiogenesis, telomere maintenance, axon guidance, and synapse assembly. Additionally, genetic analyses revealed that specific SNPs influence the expression of certain microRNAs, like miR-3605-3p, highlighting the genetic regulation of microRNA expression and its impact on vascular and brain health. Moreover, I demonstrated that the expression of most retrotransposable elements increases with age, and that there are sex differences, with certain retrotransposable elements highly expressed in men. Integration with nearby gene expression data revealed co-regulation of retrotransposable elements and genes involved in immune and inflammatory pathways. Finally, using gene expression data, I functionally validated findings from GWAS on complex lipids and EWAS on hippocampal volume and asymmetry. These integrative analyses identified several genes, such as <em>FADS1</em>, <em>FADS2</em> and <em>ABCA7</em> influencing lipid metabolism, whose expression levels mediated the effects of the genetic variants on complex lipid traits, and revealed epigenetic signatures affecting hippocampal volume and asymmetry through gene expression and transcription factor regulation. <br> In conclusion, this work demonstrates how functional genomics approaches can identify potential biomarkers of aging-related traits and subsequently uncover the biological pathways in which they are involved. Moreover, they can provide meaningful interpretation of findings from established omics-wide association studies, providing valuable insights into the molecular mechanisms of aging.