Novel algorithms for SWATH-MS quantification to study type 2 diabetes progression on a molecular level

The number of patients suffering from type 2 diabetes mellitus (DM2) reached 392 million worldwide in 2015 and its prevalence is expected to increase by more than 50% during the next two decades. Currently, the best way to treat diabetes is to diagnose and prevent at the early stages. There is an urgent need for a better understanding of the disease on a molecular level. Here, we will use a novel high-throughput proteomics method to longitudinally profile an existing cohort of pre-diabetic patients at risk of becoming frank diabetics, thus gaining deeper insight into disease progression at the molecular level.
Blood plasma is a non-invasive source for protein measurement as infected tissue normally secrete proteins in the blood. Snyder lab at Stanford University has collected over 1000 samples from 105 subjects over 4 years in a longitudinal, personalized medicine setup. We will use SWATH-MS, a targeted proteomics method capable of accurate identification and quantification. I will develop novel algorithmic methods including direct chromatogram alignment approach to quantify proteins. Subsequently, software will be developed to scale the measurement across 1000s of samples and use mutual information to get robust quantification […]

Faculty Supervisor:

Hannes Rost

Student:

Partner:

Stanford University

Discipline:

Life Sciences

Sector:

Education

University:

University of Toronto

Program: