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The majority of people living with type 2 diabetes mellitus (T2DM) are overweight or obese due to the additional burden of applying insulin to properly control blood sugar levels. However, some people, especially Asian populations, develop T2DM with a low BMI (normal weight). This discrepancy may be resulted from differences in body fat and muscle mass for a given BMI. In order to investigate the influences of body weight on the onset of T2DM, we collected plasma samples from 9 overweight and 17 normal-weight diabetic patients as a pilot study, then applied untargeted metabolomics profiling on these plasma samples. By combining Hydrophilic Interaction (HILIC) and Reverse-Phase Liquid Chromatography (RPLC)-Mass Spectrometry, we comprehensively detected and relatively quantified 5,469 metabolites. We then employed various pattern recognition algorithms (principal component analysis, hierarchical clustering, Welsh t-test, etc.), clearly separated overweight and normal-weight diabetic groups based on their plasma metabolite profiling. Furthermore, we statistically identified 52 significantly different metabolites between these two groups, mainly involved in lipid metabolism. These results not only demonstrate that untargeted metabolomics is able to serve as an efficient diagnostic tool to distinguish overweight and normal-weight diabetic patients, but also provide meaningful insights into molecular mechanisms about tight relationships between diabetes and obesity, further facilitate biomarker discovery for early diagnosis and differentiation of normal/overweight diabetes. Disclosure L. Faroqi: None.