Neurolipid Atlas Maps Brain Fat Signatures Across Alzheimer's and Other Diseases

Lipids make up roughly 60% of the brain's dry weight and are increasingly recognized as key players in neurodegenerative disease, yet lipidomics data remain fragmented across studies and cell types. To address this, an international team assembled the Neurolipid Atlas—a dynamic, open-access data commons at neurolipidatlas.com—pre-populated with harmonized lipidomics datasets from isogenic iPSC-derived neurons, microglia, and astrocytes carrying disease-relevant mutations, as well as human and mouse brain tissue.

Using this multi-dataset resource, the investigators first confirmed that each brain cell type carries a signature lipid profile that closely recapitulates what is observed in vivo, validating iPSC-derived models as relevant lipidomic surrogates for human brain biology. This cell-type specificity underscores that studying whole-brain or mixed-cell homogenates obscures critical disease signals.

The most striking disease-specific finding involved ApoE4, the strongest genetic risk factor for late-onset Alzheimer's disease. ApoE4 drove significant accumulation of cholesterol esters (CEs) selectively in iPSC-derived human astrocytes but not in neurons or microglia. Crucially, CE accumulation was also detected in whole-brain lipidomics from individuals with AD, suggesting the astrocyte-derived signal is detectable at the tissue level and may serve as a biomarker.

To understand the functional consequences, the team performed integrated multiomics (lipidomics plus transcriptomics/proteomics) on iPSC-derived astrocytes. Perturbed cholesterol metabolism was linked to dysregulation of immune pathways, specifically the immunoproteasome and MHC class I antigen presentation machinery. This places astrocyte cholesterol homeostasis at the intersection of lipid metabolism and neuroinflammation, two processes central to AD pathology.

The Neurolipid Atlas is designed as a living resource: the community can deposit new datasets, enabling cross-disease and cross-model comparisons at scale. The platform's user-friendly interface and standardized annotation make it accessible to both lipid specialists and neuroscientists without deep metabolomics expertise. Together, the resource and its initial findings position lipid dyshomeostasis—particularly cholesterol metabolism in glia—as a tractable therapeutic and biomarker target in neurodegeneration.