Grant: Project Grant

Over the last decades, we have learned to use information about small molecules to predict disease risk, help in diagnosis, select the right drug and monitor the effectiveness of a given therapy. However, doctors and researchers currently have to order specific lab tests one at a time, which drives up costs and carries the risk of missing something important that was not explicitly tested for. We propose to combine recent advances in measurement technologies and new algorithms to implement a method that can measure thousands of small molecules in the blood of a patient, creating a comprehensive molecular profile. Our method can store this profile in a "digital biobank" for later analysis and comparison, essentially allowing us to convert a biological sample (blood, urine, tissue) into a digital representation of the sample containing all the information needed for scientific and diagnostic analysis. Our approach uses a novel acquisition method available in high resolution mass spectrometry called "DIA", which has not yet been systematically applied to small molecule analysis. The method will be capable of performing the equivalent of thousands of blood tests all at once on a single patient sample, thus allowing researchers and doctors to gain a much more detailed view of patient samples on a molecular level. If successful, we will demonstrate the capability of the DIA method by optimizing it for two important patient samples: blood samples and patient-derived stem cells. We will study blood samples of pre-diabetic patients and follow these patients over several years. By comparing the molecular profile of the same patient over time, we will be able to tell which molecules change when the patients get better or worse. Secondly, we will use DIA to profile patient-derived stem cells from the same patients, trying to understand how their cells react to stimulation with various factors.