This work presents a strategy for the evaluation of differences in plasma phospholipid content between atherosclerotic and healthy mice from micro volumes (2 muL) spotted on filter paper. Dried plasma spots (DPS) were directly desorbed into a triple quadrupole linear ion trap mass spectrometer using a homemade prototype, ensuring high-throughput analysis of dried spots without any sample pretreatment. Multiple positive and negative neutral loss and precursor ion scans were simultaneously acquired in a single loop, allowing oriented fingerprinting until 2700 potential species including phosphatidic acid (PA), phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylglycerol (PG), phosphatidylinositol (PI), phosphatidylserine (PS), and sphingomyelin (SM) classes. The phospholipidic variations between 15 healthy and 15 atherosclerotic mice were evaluated using t tests, matrix reduction and merging, and principal component analysis (PCA) as a chemometric statistical approach. The discriminating ions in PCA analysis were qualitatively identified in an information dependent acquisition (IDA) manner using enhanced resolution and enhanced product ion scans. PCA demonstrates a clear clustering between healthy and diseased mice. Regarding the most relevant variables identified, this procedure has confirmed the role of SM and PS classes in atherosclerosis and has established potential biomarkers shown to be significantly up- or down-regulated with the disease. The results presented in this work demonstrate the sample processing and analysis potential of the developed strategy to evaluate new biomarkers and the state of a disease.