Alterations in metabolism are known to play profound roles inthe health ofindividuals with type 1 diabetes (T1D). These alterations lead to disruptions in cell structure, signaling, and energy homeostasis. While most studies focus on identifying genetic or protein signatures of disease, the metabolic profile is a far more dynamic, sensitive, and rapidly-responding molecular measure of phenotype. Free fatty acids (FFAs) in particular represent a class of metabolites known to play key roles in protective activities such as preventing beta-cell apoptosis, regulating plasma glucose levels, and enhancing insulin sensitivity as well as destructive activities such as exacerbating insulin resistance and producing lipotoxic conditions conducive to apoptosis. The nature of these roles is in part determined by the concentration of the FFAs as well as their molecular identity. Unambiguous detection and identification of these metabolites by conventional, antibody-based fluorescent imaging approaches is not feasible. Instead, we will leverage chromatography-tandem mass spectrometry (LC-MS/MS) to analyze homogenized tissues. However, LC-MS/MS lacksa spatial component to the measurement and does not provide for the direct in situmeasurement of metabolites in intact tissue sections. Detecting the spatial distributionand diversity of FFAs directly in pancreatic tissue, before these metabolites have been diluted in the bloodstream, would provide an unprecedented view of T1D metabolism. Herein, we propose to use label-free imaging mass spectrometry to enable the multiplexed and facile discrimination of metabolites in human pancreas tissue sections. We will analyze and quantify differences in the expression of free fatty acids between unaffected and T1D pancreases. Our preliminary data suggest that multiple genes involved in fatty acid biosynthesis are significantly upregulated in T1D tissue compared to unaffected pancreases. The generation of molecular maps by imaging mass spectrometry will determine whether the metabolic phenotypes agree with the genetic profiles of these individuals.