A groundbreaking advance in the understanding of neurodegenerative diseases has emerged from the comprehensive development of the Neurolipid Atlas, a pioneering lipidomics resource that maps lipid species across various brain cell types and disease states. This resource provides unprecedented insights into the complex lipid alterations underpinning neurodegenerative pathology. In an extensive multi-omic approach integrating lipidomics, proteomics, transcriptomics, and cell biology, researchers have charted the intricate lipid landscapes of human induced pluripotent stem cell (iPSC)–derived brain cells, as well as postmortem human brain samples, offering a novel framework for future explorations of brain lipid metabolism in health and disease.
Central to this initiative was the use of isogenic human iPSC lines harboring distinct APOE genotypes, notorious for their implication in Alzheimer’s disease risk modulation. Through meticulous cell culture techniques, the investigators generated iPSC-derived neurons, astrocytes, and microglia, ensuring stringent quality control via SNP arrays to monitor genomic integrity and repeated mycoplasma testing. The differentiation protocols were finely tuned, employing transcription factor-driven approaches for neuron induction, neurosphere formation for astrocytes, and embryoid body–based induction for microglia, each optimized to recapitulate key features of their in vivo counterparts.
Lipidomic profiling harnessed a methyl tert-butyl ether (MTBE)-based extraction method combined with advanced liquid chromatography–mass spectrometry (LC-MS) on a Sciex QTrap 5500 platform equipped with differential mobility spectrometry. This enabled precise quantification of a comprehensive panel of lipid species, with the incorporation of 54 deuterated internal standards facilitating robust normalization and quality control. Critically, data analysis incorporated stringent blank filtering and sophisticated bioinformatics tools such as SLA and SODA-Light, which provided interactive visualization and integration of multi-dimensional lipidomics data, enhancing interpretability and fostering data accessibility through the Neurolipid Atlas web portal.
The multi-omics strategy was further exemplified by simultaneous proteomic and transcriptomic analyses derived from matched iAstrocyte populations of APOE3/3 and APOE4/4 genotypes and subjected to reactive and control conditions. Proteomic workflows employed data-independent acquisition on an Orbitrap Exploris 480 mass spectrometer paired with cutting-edge software (Spectronaut version 18) to deliver high-confidence protein quantification with stringent false discovery rates. Meanwhile, transcriptomic sequencing utilized ribosomal RNA–depletion protocols and high-throughput paired-end Illumina sequencing, allowing deep characterization of gene expression changes linked to genotype and inflammatory activation states.
Complementing human cell models, primary mouse astrocyte cultures derived from embryonic and early postnatal cortices were utilized to validate lipidomic signatures and investigate reactive phenotypes under cytokine-induced inflammatory conditions. These in vitro models provided essential cross-species validation and facilitated functional interrogation of lipid remodeling in neuroinflammatory contexts. Notably, the integration of cholesterol metabolism dynamics was probed through methyl-β-cyclodextrin-mediated cholesterol loading and pharmacological modulation with avasimibe and atorvastatin, illustrating nuanced lipid alterations underpinning cellular responses in disease-relevant scenarios.
In parallel to cell culture systems, postmortem brain tissue lipidomics from well-characterized donor cohorts, including Alzheimer’s disease and non-demented control cases, unveiled distinct lipidomic shifts within the frontal cortex and cerebellum. These brain region–specific lipid alterations were meticulously quantified, normalized to tissue homogenate mass, and rigorously controlled for potential confounding variables such as postmortem interval and APOE genotype. This approach illuminated lipid species potentially involved in neurodegenerative processes, offering critical correlations between cellular lipid signatures and disease pathology.
The Neurolipid Atlas notably advances data sharing, with an open-access platform designed to incorporate external lipidomic datasets coupled with standardized metadata formatting to ensure reproducibility and interoperability. This democratization of data invites comprehensive cross-study comparisons and replication, propelling the field toward an integrative systems-level understanding of brain lipid metabolism. By including up-to-date software tools fully available on GitHub, the resource empowers researchers globally to analyze, visualize, and interpret complex lipidomic datasets with enhanced precision.
Methodological rigor permeates every facet of the study, from cell culture to omics data acquisition. iPSC-derived cells underwent rigorous validation including copy-number variation (CNV) analysis to exclude genomic anomalies potentially influencing data integrity. Immunocytochemical assessments ensured high purity of differentiated cells, quantified by automated computational methods leveraging signal-to-noise ratios to distinguish specific marker expression. Flow cytometric analyses further characterized microglial precursors using established surface markers like CD45 and CD11b, guaranteeing the authenticity of cell identities before downstream lipidomic profiling.
The integrative experimental design also incorporated the generation of TMEM106B-knockout neurons, leveraging a genetically engineered iPSC line to probe the influence of this gene—associated with frontotemporal lobar degeneration—on neuronal lipid composition. This element underscored the utility of the Atlas in accommodating diverse genetic backgrounds and pathologies, highlighting its adaptability to study gene-centric lipidomic perturbations relevant to neurodegeneration.
A particular strength of this research lies in the longitudinal and combinatorial analyses conducted on reactive versus control astrocytes. Treatment with a cytokine cocktail containing TNF, IL-1α, and C1q simulated neuroinflammatory stimuli, enabling characterization of lipidomic and proteomic shifts concomitant with astrocyte activation. The data revealed distinct lipid signatures reflective of reactive states, implicating altered phospholipid saturation patterns and cholesterol metabolism in astrocyte-mediated inflammatory responses—a finding with profound implications for understanding the molecular underpinnings of neuroinflammation in disorders such as Alzheimer’s disease.
State-of-the-art analytical techniques were meticulously applied across all data types. Quantitative PCR protocols employed rigorously validated primers and normalization schemes, while western blotting utilized PVDF membranes combined with fluorescence-based detection for sensitive quantification of immune-related protein expression changes. Moreover, the use of multiplex mesoscale discovery immunoassays to quantify secreted cytokines from astrocyte cultures added a vital functional dimension, linking lipid alterations to inflammatory mediator secretion.
In synthesizing lipidomics, proteomics, and transcriptomics data, the Neurolipid Atlas facilitates a holistic view of neurodegenerative disease biology focused on membrane and lipid metabolism alterations. The identification of genotype-dependent differences in lipid saturation and composition, supported by complementary gene expression shifts, exemplifies the depth of insight achievable through multi-omic integration. This resource not only charts fundamental biological processes but also opens new avenues for therapeutic intervention targeting lipid metabolic pathways that have thus far remained elusive in neurodegenerative disease research.
Finally, by establishing standardized, reproducible protocols for sample collection, processing, and analysis, the Neurolipid Atlas sets a new benchmark for rigor in neuro-lipidomics. The careful documentation of culture conditions, cell differentiation timelines, reagent sources, and data normalization methods provides a transparent framework fostering reproducibility and comparability across laboratories. As such, this monumental effort stands to catalyze further longitudinal and translational research initiatives, ultimately fostering breakthroughs in biomarkers, mechanistic understanding, and treatment development for devastating neurological disorders.
Subject of Research: Lipidomic characterization of neurodegenerative diseases using human iPSC-derived brain cells, mouse astrocytes, and postmortem brain tissue with multi-omics integration.
Article Title: The Neurolipid Atlas: a lipidomics resource for neurodegenerative diseases.
Article References:
Feringa, F.M., Koppes-den Hertog, S.J., Wang, L.Y. et al. The Neurolipid Atlas: a lipidomics resource for neurodegenerative diseases. Nat Metab (2025). https://doi.org/10.1038/s42255-025-01365-z
Tags: advanced mass spectrometry in lipid analysisAlzheimer’s disease risk factorsAPOE genotype implicationsbrain lipid metabolism studiescell culture techniques for neurobiologyhuman-induced pluripotent stem cellslipid profiling techniqueslipidomics in brain healthmulti-omic approaches in neuroscienceneurodegenerative diseases researchneuroinflammation and brain lipidsneurolipid atlas
