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Aberrant sterol lipid metabolism is associated with physiological dysfunctions in the aging brain and aging-dependent disorders such as neurodegenerative diseases. There is an unmet demand to comprehensively profile sterol lipids spatially and temporally in different brain regions during aging. Here, we develop an ion mobility-mass spectrometry based four-dimensional sterolomics technology leveraged by a machine learning-empowered high-coverage library (>2000 sterol lipids) for accurate identification. We apply this four-dimensional technology to profile the spatially resolved landscapes of sterol lipids in ten functional regions of the mouse brain, and quantitatively uncover ~200 sterol lipids uniquely distributed in specific regions with concentrations spanning up to 8 orders of magnitude. Further spatial analysis pinpoints age-associated differences in region-specific sterol lipid metabolism, revealing changes in the numbers of altered sterol lipids, concentration variations, and age-dependent coregulation networks. These findings will contribute to our understanding of abnormal sterol lipid metabolism and its role in brain diseases.

Ion mobility-based sterolomics reveals spatially and temporally distinctive sterol lipids in the mouse brain