|Institution:||Universiteit van Amsterdam|
|Full text PDF:||http://hdl.handle.net/11245/1.441264|
Omics-technologies allow detailed characterization of biochemical molecular families enabling data-driven and hypothesis-generating research. In this thesis we explore potential merits and pitfalls of such an approach by studying the volatile metabolome and microbiome in disease diagnosis, phenotyping and prognosis. Diagnosis - The volatile metabolome constitutes of Volatile Organic Compounds (VOCs) reflecting metabolic activity. We describe that analysis of exhaled and fecal VOCs by eNose can discriminate controls from patients with cancer (lung and colorectal), chronic inflammatory conditions (asthma, Cystic Fibrosis, Primary Cilliary Dyskinesia, Crohn’s disease, Ulcerative Colitis) and help to identify patients suffering from fungal (invasive Aspergillosis), bacterial (exacerbation in CF and PCD) and viral (Rhinovirus) infections. These VOCs likely originate from the primary disease process, the systemic response and pathogens directly. Phenotyping - VOCs can differentiate between clinically similar diseases such as CF-PCD and Crohn-Ulcerative Colitis. Furthermore, VOCs can predict whether patients with asthma respond to steroid treatment. These VOCs associate with disease activity, potentially allowing monitoring. Prognosis - We showed VOCs differentiate between children with and without an increased risk to develop asthma, irrespective of symptoms. We made similar observation by analysis of the microbiome (the agglomerate of bacterial species) in the nasopharynx of these children. Omics technologies have a broad potential in medicine allowing diagnosis and characterization of disease processes, potentially prior to clinical onset. Several hurdles however need to be overcome in validation, data-analysis, data-integration, technological development and experiment uniformity. If adequately addressed and integrated into systems medicine, the potential healthcare impact of omics-technologies is profound.