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The Neurolipid Atlas: a lipidomics resource for neurodegenerative diseases

ABSTRACT: Lipid alterations in the brain have been implicated in many neurodegenerative diseases. To facilitate comparative lipidomic research across brain diseases here we establish a data common named the Neurolipid Atlas, that we have pre-populated with isogenic induced pluripotent stem cell (iPSC)-derived lipidomics data for different brain diseases. Additionally, the resource contains lipidomics data of human and mouse brain tissue. Leveraging multiple datasets, we demonstrate that iPSC-derived neurons, microglia, and astrocytes exhibit distinct lipid profiles that recapitulate in vivo lipotypes. Notably, the AD risk gene ApoE4 drives cholesterol ester (CE) accumulation specifically in human astrocytes, and we also observe CE accumulation in whole human AD brain lipidomics. Multi-omics interrogation of iPSC-derived astrocytes revealed that altered cholesterol metabolism plays a major role in astrocyte interferon-dependent pathways such as the immunoproteasome and major histocompatibility complex class I antigen presentation. Our data commons, available at neurolipidatlas.com, and allows for data deposition by the community and provides a user-friendly tool and knowledge base for a better understanding of lipid dyshomeostasis in neurodegenerative diseases.

ORGANISM(S): Homo sapiens

PROVIDER: GSE302826 | GEO | 2025/07/18

REPOSITORIES: GEO

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Project description:MartínJiménez2017 - Genome-scale reconstruction of the human astrocyte metabolic network This model is described in the article: Genome-Scale Reconstruction of the Human Astrocyte Metabolic Network. Martín-Jiménez CA, Salazar-Barreto D, Barreto GE, González J. Front Aging Neurosci 2017; 9: 23 Abstract: Astrocytes are the most abundant cells of the central nervous system; they have a predominant role in maintaining brain metabolism. In this sense, abnormal metabolic states have been found in different neuropathological diseases. Determination of metabolic states of astrocytes is difficult to model using current experimental approaches given the high number of reactions and metabolites present. Thus, genome-scale metabolic networks derived from transcriptomic data can be used as a framework to elucidate how astrocytes modulate human brain metabolic states during normal conditions and in neurodegenerative diseases. We performed a Genome-Scale Reconstruction of the Human Astrocyte Metabolic Network with the purpose of elucidating a significant portion of the metabolic map of the astrocyte. This is the first global high-quality, manually curated metabolic reconstruction network of a human astrocyte. It includes 5,007 metabolites and 5,659 reactions distributed among 8 cell compartments, (extracellular, cytoplasm, mitochondria, endoplasmic reticle, Golgi apparatus, lysosome, peroxisome and nucleus). Using the reconstructed network, the metabolic capabilities of human astrocytes were calculated and compared both in normal and ischemic conditions. We identified reactions activated in these two states, which can be useful for understanding the astrocytic pathways that are affected during brain disease. Additionally, we also showed that the obtained flux distributions in the model, are in accordance with literature-based findings. Up to date, this is the most complete representation of the human astrocyte in terms of inclusion of genes, proteins, reactions and metabolic pathways, being a useful guide for in-silico analysis of several metabolic behaviors of the astrocyte during normal and pathologic states. This model is hosted on BioModels Database and identified by: MODEL1608180000. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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The Neurolipid Atlas: a lipidomics resource for neurodegenerative diseases

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