Navoly, Georgina; (2024) Insights into human ageing and related traits using Transcriptome-Wide Association Studies. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Technological advances in genomics, including large-scale data analysis and integrative omics approaches offer unprecedented opportunities to study complex traits. In my PhD research I explored two interconnected areas of genetic research: ageing and major depression (MD). I conducted a comprehensive analysis into the genetic architecture of human ageing traits using a Transcriptome-Wide Association Study (TWAS). TWAS proved highly successful for discovery. Leveraging data from over 1 million lifespans, I identified 139 genes associated with at least two ageing outcomes, significantly more than the 12 genetic loci identified by previous ageing GWAS. This demonstrates the importance of combining different ageing outcomes for a more comprehensive understanding of the genetics of ageing. Together with our collaborators, we took this approach to the next level. We integrated findings from the TWAS with experimental work and validation in Drosophila. Two of the four genes tested, COASY and SH3PXD2A, showed a significant extension of lifespan in Drosophila, suggesting that integrative approaches could be a promising strategy for future studies. In the second part of my PhD, I highlighted the importance of ancestral diversity in genetics. Using data from 21 multi-ancestry studies with 88,000 cases, I carried out a TWAS, which uncovered 354 MD-associated genes. Including multiple ancestry groups in our study, we identified novel genes that are potentially druggable for depression, findings that might have been missed if research were limited to a single population. Finally, to better understand sexual dimorphism in MD and ageing, I explored the causal impact of sex hormone binding globulin (SHBG) using Mendelian Randomisation. I demonstrated that elevated SHBG levels were causally linked to worse MD outcomes in women. This sex-specific effect highlighted the interplay between hormonal regulation and genetic predispositions in MD. By integrating diverse populations and methodologies, this PhD research provides insights into novel genetic associations and causal pathways.

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