Postdoctoral researcher in statistical functional genomics
My research involves using a functional genomics approach to explore heterogeneity in inflammatory and infectious disease. I am particularly interested in the role of regulatory variation in disease susceptibility and severity, and how an improved understanding of this may inform clinical decision making and drug discovery.
I obtained my DPhil in Clinical Medicine in the Knight group as part of the Nuffield Department of Medicine PhD programme. My thesis focused on sepsis, which is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection, and is a leading cause of death both in the UK and worldwide. It is a complex and heterogeneous disease, and the factors underlying mortality and morbidity are poorly understood. As part of the UK Genomic Advances in Sepsis (GAinS) study, we were interested in how inter-individual variation in the host response to sepsis related to disease susceptibility and outcome. Subsequent to completing my DPhil, I have continued working on this project, using complementary -omics data sets to explore disease subgroups or endotypes revealed by host transcriptomics that could present an opportunity for a precision medicine approach to sepsis management.
In addition, I am working with a large cohort of Emirati individuals (Abu Dhabi, United Arab Emirates) with a high incidence of Type 2 diabetes. Through analysis of genotyping information from patients and controls, together with RNA sequencing data, we hope to identify population-specific gene regulation and disease risk variants. My role in the project is analysis of the RNA-seq data and mapping of expression quantitative trait loci (eQTL) in this population.
A genetics-led approach defines the drug target landscape of 30 immune-related traits
Fang H. et al, (2019), Nature Genetics, 51, 1082 - 1091
Transcriptomic Signatures in Sepsis and a Differential Response to Steroids. From the VANISH Randomized Trial
Antcliffe DB. et al, (2019), American Journal of Respiratory and Critical Care Medicine, 199, 980 - 986
A community approach to mortality prediction in sepsis via gene expression analysis
Sweeney TE. et al, (2018), Nature Communications, 9
Classification of patients with sepsis according to blood genomic endotype: a prospective cohort study
Scicluna BP. et al, (2017), The Lancet Respiratory Medicine, 5, 816 - 826
Shared and Distinct Aspects of the Sepsis Transcriptomic Response to Fecal Peritonitis and Pneumonia
Burnham KL. et al, (2017), American Journal of Respiratory and Critical Care Medicine, 196, 328 - 339