Profiling morphological dynamics of neutrophil granulocytes to diagnose and categorize asthma

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Asthma is the most frequent chronic lung disease affecting more than 300 million people worldwide with increasing number of patients (Masoli 2004). Common symptoms include episodes of wheezing, coughing, chest tightness, and shortness of breath. While the diagnosis of asthma is based on specific patterns of these symptoms, response to therapy, and spirometry (pulmonary function tests), the causes still remain unknown. Population based and clinical studies show a possible correlation of genetic or environmental risk factors and reveal that asthma should be treated rather as a syndrome with many causes instead of a single disease. However, the diagnosis remains quite challenging especially for young children, where the response to different drugs and, most critically, emergency medication can not be tested sufficiently. Recent findings revealed a novel approach to discriminate between asthmatic and nonasthmatic patients using a single drop of blood (Sackmann 2014). This discrimination was solely based on the velocity of neutrophil granulocytes measured in an in vitro chemotaxis gradient implemented as a microfluidic system. We propose to develop a novel approach to the characterization of asthmatic and lung diseases using advanced computational dynamic analysis of induced chemotactic migration of neutrophil granulocytes. We will develop a novel chemotactic migration assay that induces a directed movement of neutrophils and allows for a detailed analysis of their motility, that is, their morphological dynamics. The project relies on advanced image processing, data mining and machine learning tools to identify different subtypes of asthma using the migration profile and morphological dynamics of the observed neutrophils. We believe that different subtypes of neutrophil granulocytes are specific to different phenotypes of asthma. Ultimately, we aim for the personalized diagnosis and treatment of asthmatic and lung diseases via this novel migration based phenotyping.