Functional genomics uses high throughput genome-wide technologies to investigate the functional consequences of genetic variants on gene expression and protein products. In the context of disease, using integrative functional genomic approaches to understand the genetic variation which underlies disease susceptibility and aetiology may contribute to better diagnosis, treatment and prevention. This thesis investigated genetic determinants of variation in response to infection by applying a functional genomics approach to investigate three clinical cohorts: patients with severe sepsis, an influenza challenge study and patients with common variable immune deficiency disorders. The transcriptomic response to severe sepsis is reported here for the largest known adult severe sepsis community acquired pneumonia cohort. Two clusters within the cohort, based on gene expression signatures, which have different survival rates and identify individuals with distinct immune responses to sepsis, highlight the value of functional genomics for identifying heterogeneity within patient cohorts. This was further complemented by the resolution of gene expression signatures in healthy individuals following influenza challenge which identified individuals with moderate to severe disease. Shared gene expression signatures between the cohorts highlighted components of the immune response to viral infection important across multiple clinical settings and may assist with the identification of viral infections in the sepsis patients. Gene expression was mapped as a quantitative trait (eQTL). Comparison to data sets for healthy individuals and from innate immune stimulated cells identified regulatory variants specific to the context of sepsis. Whole genome sequencing for a cohort of patients with common variable immune deficiency disorders was performed. This identified novel variants and pathways which may play a role in the underlying immunopathogenesis of disease. Integration with RNA-seq for a small number of patients allowed prioritisation of non-coding variants based on evidence of altered gene expression. Comparison to the sepsis cohort analysis identified key immune related genes involved in rare and common responses to bacterial infection. This thesis has demonstrated the value of integrating multiple functional genomic techniques to further our understanding of the mechanisms underlying variation in the response to infection.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:644672 |
| Date | January 2014 |
| Creators | Davenport, Emma Elisabeth |
| Contributors | Knight, Julian |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://ora.ox.ac.uk/objects/uuid:528edf20-f948-4a9c-aa23-1e295b11c8cc |
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