Despite improvements in asthma management, patient response to treatment have stagnated, particularly for severe asthma cases. Current therapies have limited efficacy across all phenotypes, and many patients remain inadequately controlled. Advanced omics technologies offer potential insights into the molecular mechanisms underlying asthma and may therefore help in refining patient classification and developing targeted therapeutics.

The first chapter explores the relationship between 24 targeted proteins and asthma severity and clinical manifestations. First, associations between asthma-related outcomes and each individual protein are assessed. The study then adopts a more comprehensive approach by clustering patients based on multiple clinical factors, providing a composite measure of severity. This dual methodology allows for a broader understanding of the proteomic markers involved in asthma clinical presentation and its severity, offering potential insights into more effective diagnostic and therapeutic strategies.

Chapter 2 focuses on identifying proteomic signatures of eosinophilic and neutrophilic asthma by examining the inflammatory and immune pathways unique to each phenotype. After combining data from two large asthma cohorts, the study explores how proteomic markers in serum and sputum associated with asthma subtypes. Using stability selection models, the research identifies key proteins associated with each asthma phenotype, offering potentially alternative diagnostic biomarkers and new therapeutic targets tailored to distinct inflammatory pathways.

The final chapter builds on limitations of single-omic studies in characterising asthma phenotypes by using multi-omic approaches to capture the biological interactions underlying asthma phenotypes. Using genomic, transcriptomic, and proteomic data, the research aims to identify multi-omic biomarkers that distinguish asthma subtypes based on clinical blood eosinophil and neutrophil thresholds. The findings contribute to understanding asthma's complex molecular pathways, advancing beyond the limitations of single-omic studies.

The thesis concludes by summarising key insights, discussing limitations, and proposing avenues for future research.