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Loss of MFE-2 impairs microglial lipid homeostasis and drives neuroinflammation in Alzheimer’s pathogenesis

Nature Aging volume 5, pages 2279–2296 (2025)Cite this article

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An Author Correction to this article was published on 24 November 2025

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Abstract

Dysregulated lipid metabolism promotes persistent microglial activation and neuroinflammation in Alzheimer’s disease (AD), but the underlying pathogenic mechanisms remain to be elucidated, and druggable targets remain to be identified. Here we found that multifunctional enzyme type 2 (MFE-2), the key enzyme regulating fatty acid β-oxidation in the peroxisome, was downregulated in the microglia of humans with AD and AD model mice. Microglia-specific ablation of MFE-2 drove microglial abnormalities, neuroinflammation and Aβ deposition in AD models. Mechanistically, MFE-2 deficiency facilitated lipid accumulation, resulting in excessive arachidonic acid, mitochondrial reactive oxygen species and proinflammatory cytokine production by microglia. The compound 3-O-cyclohexane carbonyl-11-keto-β-boswellic acid (CKBA) bound to MFE-2 and restored MFE-2 levels, ameliorating AD pathology by inhibiting microglial overactivation. Collectively, our data revealed a pathogenic role of microglia with impaired lipid metabolism in AD and identified MFE-2 as a druggable target of CKBA, which restores its expression and has therapeutic potential for treating AD.

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Fig. 1: MFE-2 expression deficiency in microglia correlated with neurodegeneration in AD.
Fig. 2: MFE-2−/− microglia showed chronically proinflammatory activation.
Fig. 3: MFE-2-deficient microglia exhibited AD-associated proinflammatory phenotype.
Fig. 4: MFE-2 loss induced excessive mitochondrial ROS and accumulation of arachidonic acid.
Fig. 5: MFE-2 knockout microglia highly responsive to Aβ-containing brain extracts and high-fat diet treatment.
Fig. 6: CKBA targets MFE-2 to alleviate neurodegeneration progress in AD brains.

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Data availability

Source data is provided with this paper. The source data for all main figures have also been deposited in Zenodo and can be accessed at https://zenodo.org/records/16732189 (ref. 68). Raw scRNA-seq data have been deposited in the Genome Sequence Archive (accession code CRA017222). Bulk RNA-seq data have been deposited in OMIX (accession code OMIX011442).

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Acknowledgements

This work was supported by the National Natural Science Foundation of China Original Exploration Program (no. 82450903), the Experimental Animal Research Project of ‘Scientific and Technological Innovation Action Plan’ (no. 22140903100), the National Natural Science Foundation of China (no. 82073428 to J.B.), China Postdoctoral Science Foundation (2021M692114 to M.G., no. GZB20230431 to Z.W. and no. 2023M742313 to Z.W.) and the Innovative Research Team of High-Level Local Universities in Shanghai (to H.W. if not otherwise noted). We thank the Xiangya Brain Bank, School of Basic Medical Science, Central South University, for providing the brain blocks of the patients with AD and control patients. We thank X. Yan for supplying the patient materials. We also thank D. Li for providing Aβ PFF. We thank L. Shi for CKBA modification for the click chemistry experiment.

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  1. These authors contributed equally: Min Gao, Jing Bai.

Authors and Affiliations

  1. Precision Research Center for Refractory Diseases, Shanghai Jiao Tong University Pioneer Research Institute for Molecular and Cell Therapies, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Min Gao, Jing Bai, Fangzhou Lou, Yang Sun, Zhikai Wang, Xiaojie Cai, Yan Li, Fengjiao Zhang, Jihuan Liang, Xiangxiao Li, Yue Wu, Ziyang Zhang, Li Fan, Xinping Jin & Honglin Wang

  2. State Key Laboratory of Innovative Immunotherapy, School of Pharmaceutical Sciences, Shanghai Jiao Tong University, Shanghai, China

    Honglin Wang

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Contributions

Experiments were designed and conceived by H.W., M.G., F.L., Y.S., J.B. and Z.W. with the support of Y.L. and X.C. Cell and mouse experiments were performed and analyzed by H.W., M.G. and J.B., with the support of X.L., Z.Z. and F.Z. RNA-seq analysis was performed by M.G. with the support of Y.S., X.C. and Y.W. F.Z. and J.L. performed and analyzed the Airyscan microscopy data. L.F. and X.J. performed in situ staining and analysis of microglial morphology under the supervision of M.G. J.B. generated MFE-2 conditional mice. H.W. and M.G. conceived of the idea and wrote the paper with the support of F.L. All authors contributed to the editing of the paper and supported the conclusions.

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Correspondence to Honglin Wang.

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Extended data

Extended Data Table 1 Human brain tissue sample
Full size table

Extended Data Fig. 1 MFE-2 defect was related to microglial activation in AD mice.

a. The specificity of MFE-2 antibody used in this study was verified by immunofluorescences of MFE-2 in cultured primary microglia from Flox and ΔMFE-2 mice brain. Experiments were repeated three times. b. Representative RNAscope result of MFE-2 mRNA in microglia of 8-month-old untreated and 5xFAD mouse models (n = 3 per each group, male). Hsd17b4 in red, microglia in green and nuclei in blue. Scale bar, 25 μm. c. Schematic depicting brain microglia isolation by FACS experimental setup. And sorting strategy of brain microglia (CD45intCD11b+) by FACS. d. Western blot of MFE-2 in microglia from 8-month-old 5xFAD and untreated mice brain isolated by FACS. (Each sample contained a pool of microglia from 3 brains. Four samples per group were analyzed. Both male and female mice were used.) e. Overview of conditional MFE-2 knockout mice (ΔMFE-2) and MFE-2 knockout 5xFAD mice (5xFADΔMFE-2) production. f. Western blot of MFE-2 in isolated microglia by FACS from 8-week-old Flox and ΔMFE-2 mice brain (n = 4. Each lane counting for protein extracted from microglia of 3 brains p < 0.05. Both male and female mice were used.) g. Results of Morris water maze assays in Fig. 1g. Time in targeted quadrant and total swimming length were calculated. h. Representative immunofluorescences result of microglia distribution and morphology at early stage of AD (2 - 3-month-old) in 5xFAD and 5xFADΔMFE-2 mouse models (n = 5 per each group, male.) Mean microglial branch length was calculated by averaging the total length of branches using Leica software. Microglia in red and nuclei in blue. Scale bar, 100 μm. Statistical analyses were performed by two-tailed Student’s t-test. All data were presented as mean values ± SEM. Specific p values are indicated in the figure.

Source Data

Extended Data Fig. 2 Identification of microglia clusters by scRNA-seq in Flox and ΔMFE-2 mice.

a. t-SNE plots showing the expression of selected genes that are enriched in microglia. These genes were used to identify microglia from non-microglia. Each dot represents a cell. The normalized gene expression levels of the selected genes for each cell were projected onto the t-SNE plots. b. Cell fraction distribution of pooled microglia from 8-month-old Flox, ΔMFE-2, 5xFAD and 5xFADΔMFE-2 mice in Fig. 2a. c. Heatmap to show highly expressed marker genes in 18 microglial clusters by scRNA in Fig. 2a. Z scores across microglia states were used for the plot. d. Pathways upregulated in microglia from ΔMFE-2 microglia compared to Flox mice in Fig. 2b. In blue, highlighting inflammatory pathways related to the MFE-2 knockout microglia states. The enrichment was evaluated using a two-sided hypergeometric test. e. t-SNE plots showing marker genes that were enriched in MFE-2 deficiency related clusters (cKO-related cluster III/IV). f. Pathways upregulated in MFE-2 deficiency-related microglia (cKO-related IV cluster). The enrichment was evaluated using a two-sided hypergeometric test. g. mRNA levels of Il6 in MFE-2KO and mock BV2 cell line by qPCR with or without LPS (10 μg/ml) and IFN-γ (100 ng/ml) treatment (n = 3 per each group, male). Data normalized to Gapdh and shown relative to control. Statistical analyses were performed by one-way ANOVA (g). All data were presented as mean values ± SEM. Specific p values are indicated in the figure.

Source Data

Extended Data Fig. 3 Identification of microglia features in AD and ADΔMFE-2 by scRNA-seq.

a. t-SNE plots show marker genes that are enriched in DAM clusters in Fig. 3a. b. Pathways enriched in microglia DAM I cluster. The enrichment was evaluated using a two-sided hypergeometric test. c. Pathways upregulated microglia DAM II cluster. The enrichment was evaluated using a two-sided hypergeometric test. d. Flow cytometer analysis of TNF-α and IL-6 in brain microglia (CD45intCD11b+) from 8-month-old Flox, ΔMFE-2, 5xFAD and 5xFADΔMFE-2 mice. (n = 5 per group. Both male and female mice were used.) e. NS-TEM image of Aβ fibrils. Scale bar, 200 nm. Experiments were performed three independent times. Statistical analyses were performed by one-way ANOVA (d). All data were presented as mean values ± SEM. Specific p values are indicated in the figure.

Source Data

Extended Data Fig. 4 MFE-2 mediated peroxisomes and mitochondria contacts.

a. Representative immunofluorescences result of mitochondria (stained with anti-Tom20) in microglia of ΔMFE-2 and Flox mice. (n = 3 per sample, male). Mitochondria (Tom20+) in green, microglia in red and nuclei in blue. Scale bar, 25 μm. b. Flow cytometer analysis of MitoSOX of cultured microglia from P0 Flox and ΔMFE-2 mice in Fig. 4e. Rot/AA, rotenone–antimycin A. c. Primary brain microglia were isolated from P0 brains of ΔMFE-2 and Flox mice. The cultured microglia were used for the Seahorse long chain fatty acid Oxidation Stress Test combined with Seahorse XF Palmitate–BSA FAO Substrate setup. (n = 4 per each group, both male and female mice were used.) d. Overview of the construct of SPLICS Po-Mt Short P2A. And schematic showing SPLICS reporter displaying GFP over a dark background only in the regions of peroxisomes and mitochondria membrane proximity sites. e. The cultured microglia from P0 and ΔMFE-2 mice were transfected with SPLICS using lipo2000 and NATE. Another microglia group without SPLICS plasmid transfection was set as the blank control. Representative immunofluorescences result of SPLICS signal distribution in primary microglia from Flox and ΔMFE-2 mice were shown. (n = 9) Scale bar, 50 μm. Statistical analyses were performed by one-way ANOVA (e). All data were presented as mean values ± SEM. Specific p values are indicated in the figure.

Source Data

Extended Data Fig. 5 MFE-2 deficiency drove dysregulated lipid β-oxidation and exacerbated microglial activation in response to Aβ.

a. Untargeted metabolism profile in FACS sorted microglia from 8-month-old ΔMFE-2 and Flox mice by LC-MS. Differential metabolites were identified using a two-sided Student’s t-test. (n = 4 in Flox group and n = 6 in MFE-2 knockout group. Microglia from three brains were pooled for each sample, male.) b. The cultured primary microglia from P0 Flox and ΔMFE-2 mice were input for FFAs quantitative evaluation by GC-MS. (n = 4 per group. Microglia from more than 10 brains were pooled for each sample. Both male and female mice were used.) Data are presented as mean values ± SEM. Differential metabolites were identified using a two-sided Student’s t-test.c. Heatmap for DEGs of cultured primary microglia from P0 Flox and ΔMFE-2 mice treated with brain extraction containing Aβ plaques from 8-month-old 5xFAD mice by bulk RNAseq. (n = 3 per sample. Microglia from more than 5 brains were pooled for each sample. Both male and female mice were used.) d. Flow cytometer analysis of inflammatory phenotype of primary microglia from 8-month-old Flox, ΔMFE-2, 5xFAD, and 5xFADΔMFE-2 mice after high-fat diet or control diet treatment. (n = 3 per each group, male) in Fig. 5f.

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Extended Data Fig. 6 CKBA targeting MFE-2 without affecting its enzyme activity.

a. Representative results of CKBA-biotin pull-down of different domains and full length of MFE-2. b. Representative results of CKBA-biotin pull-down MFE-2 in BV2 cells. Experiments were repeated three times. c. Schematic diagram of synthesis of modified CKBA probe for labeling targets in living cell by click chemistry response. d. Representative immunofluorescences result of CKBA-Cy5.5 colocalization with MFE-2 (MFE-2-mCherry) in primary microglia from P0 untreated mice transfected with MFE-2-mCherry plasmid. To distinguish it from CKBA-Cy5.5 fluorescence, the fluorescence of MFE-2-mCherry was artificially set to green. Experiments were repeated three times. Scale bar, 10 μm. e. Representative immunofluorescences result of CKBA-MFE-2 labeling images stained with DBCO-Cy5.5. Scale bar, 10 μm. (n = 9) f. Measurement of the dehydrogenase activity of MFE-2 with or without CKBA by fluorometric monitoring of NAD+ reduction. And measurement of the hydratase activity of MFE-2 with or without CKBA by monitoring NADH production at 340 nm. Statistical analyses were performed by one-way ANOVA (e). All data were presented as mean values ± SEM. Specific p values are indicated in the figure.

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Extended Data Fig. 7 CKBA targeting MFE-2 to resolve neuroinflammation.

a. Representative immunofluorescences result of MitoSOX stain in primary microglia treated with 100 μM AA (Arachidonic acid) combined with or without 5 μM CKBA. (n = 5 per each group). Scale bar, 100 μm. b. Timeline of the study and overview of the experimental design for vehicle or CKBA treatment in the 5xFAD mice experimental setup. c. LC-MS analysis of CKBA concentration in blood serum and brain tissue 12 hours after a single dose of CKBA administration at various dosages for wildtype mice. d. Results of Morris water maze assays of 1-year-old Vehicle-5xFAD, CKBA-5xFAD and CKBA-5xFADΔMFE-2. (n = 10 per each group. Both male and female mice were used.) Time in targeted quadrant and total swimming length were quantified. e. Representative immunofluorescences result of CD68 in sections from Vehicle-5xFAD, CKBA-5xFAD and CKBA-5xFADΔMFE-2 mice. (n = 4 per each sample, male). CD68 in green, microglia in red and nuclei in blue. Scale bar, 10 μm. Statistical analyses were performed by one-way ANOVA (a, c, d, e) and two-way ANOVA (d). All data were presented as mean values ± SEM. Specific p values are indicated in the figure.

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Gao, M., Bai, J., Lou, F. et al. Loss of MFE-2 impairs microglial lipid homeostasis and drives neuroinflammation in Alzheimer’s pathogenesis. Nat Aging 5, 2279–2296 (2025). https://doi.org/10.1038/s43587-025-00976-1

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