Asthma is a chronic inflammatory respiratory disorder which is characterised by wheezing and periods of severe airway obstruction. More than 300 million people worldwide suffer from asthma and its prevalence has been increasing over the past decades. Asthma pathogenesis is still not well understood but the disease has been linked to several genetic, infectious and environmental factors. The clinical presentation of asthma and its immunological and molecular ethology varies significantly between patients and multiple phenotypes have been described.
In the lungs, the airway epithelium forms a first barrier against pathogens and inhaled allergens and lies at the intersection between innate and adaptive immunity. Innate immune activation and differentiation is accompanied by comprehensive changes in cellular metabolism. Dysregulation of these metabolic processes can thus lead to an abnormal immune function and pathology. A better understanding of metabolic alteration in asthma can thus offer new therapeutic targets for asthma management.
This project aims at characterising metabolic changes in the asthma bronchial epithelium and how these relate to asthma phenotypes by employing predominantly transcriptome data from major databases (e.g. ArrayExpress, GEO).
Prerequisite: The project requires basic knowledge in R.
Tasks: This project includes carrying out data integration, clustering and network analysis to define metabolic phenotypes in asthma. Students will gain expertise in respiratory diseases and statistics, build on their academic portfolio, and will have the opportunity to pursue their own analysis interests within the given framework.
Contact: Mandy Menzel (mandy.menzel@med.lu.se)