Inflammation-induced lysosomal dysfunction in human iPSC-derived microglia is exacerbated by APOE 4/4 genotype

Inflammation-induced lysosomal dysfunction in human iPSC-derived microglia is exacerbated by APOE 4/4 genotype | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Inflammation-induced lysosomal dysfunction in human iPSC-derived microglia is exacerbated by APOE 4/4 genotype Marianna Hellén, Isabelle Weert, Stephan A. Müller, Šárka Lehtonen, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6241569/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Jun, 2025 Read the published version in Journal of Neuroinflammation → Version 1 posted 11 You are reading this latest preprint version Abstract Background. The ε4 isoform of apolipoprotein E (ApoE) is the most significant genetic risk factor for Alzheimer’s disease. Glial cells are the main source of ApoE in the brain, and in microglia, the ε4 isoform of ApoE has been shown to impair mitochondrial metabolism and the uptake of lipids and Aβ42. However, whether the ε4 isoform alters autophagy or lysosomal activity in microglia in basal and inflammatory conditions is unknown. Methods. Altogether, microglia-like cells (iMGs) from eight APOE 3/3 and six APOE 4/4 human induced pluripotent stem cell (iPSC) lines were used in this study. The responses of iMGs to Aβ42, LPS and IFNγ were studied by metabolomics, proteomics, and functional assays. Results. Here, we demonstrate that iMGs with the APOE 4/4 genotype exhibit reduced basal level pinocytosis and an overall downregulation of lysosomal proteins compared to APOE 3/3 iMGs. Inflammatory stimulation with a combination of LPS and IFNγ or Aβ42 induced PI3K/AKT/mTORC signaling pathway, increased pinocytosis, and blocked autophagic flux, leading to the accumulation of sequestosome 1 in both APOE 4/4 and APOE 3/3 iMGs. Exposure to Aβ42 furthermore caused lysosomal membrane permeabilization, which was significantly stronger in APOE 4/4 iMGs and positively correlated with the secretion of the proinflammatory chemokine IL-8. Metabolomics analysis indicated a dysregulation in amino acid metabolism, primarily L-glutamine, in APOE 4/4 iMGs. Conclusions. Overall, our results suggest that inflammation-induced metabolic reprogramming places lysosomes under substantial stress. Lysosomal stress is more detrimental in APOE 4/4 microglia, which exhibit defects in lysosomal biogenesis. microglia Alzheimer’s disease apolipoprotein E iPSC lysosomal dysfunction Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Lysosomal dysfunction is a common feature of aging-associated neurodegenerative diseases, including Alzheimer’s disease (AD), which is characterized by the accumulation of toxic beta-amyloid (Aβ) and tau protein aggregates in the brain [1]. Since autophagy and endocytosis/phagocytosis pathways deliver dysfunctional organelles, extracellular material, and debris to lysosomes for degradation, lysosomal dysfunction has been suggested as a key factor promoting the accumulation of dysfunctional organelles and protein aggregates in AD [2]. Lysosome biogenesis is controlled by the microphthalmia-associated transcription factor/transcription factor E (MIT/TFE) family of transcription factors, including TFEB, TFE3, MITF, and TFEC [3]. These transcription factors bind to Coordinated Lysosomal Expression and Regulation (CLEAR) motifs and co-operate to fine-tune lysosomal gene expression in various conditions [4]. Disruption of TFEB-mediated signaling has been reported to exacerbate tau pathology [4, 5], while TFEB overexpression in neurons and astrocytes may enhance the clearance of Aβ and tau in mouse models of AD [6-8], highlighting a strong link between lysosomal dysfunction and AD pathology. Apolipoprotein E (ApoE) is the primary carrier of cholesterol and triglycerides in the bloodstream and is predominantly produced by glial cells in the brain. Among the three human isoforms (ε2, ε3, and ε4), ApoE ε3 (further referred to as E3) is considered neutral, while ApoE ε4 (henceforth referred to as E4) represents the most significant genetic risk factor for AD [9-11]. It is estimated that up to 50% of AD patients carry at least one E4 allele [10]. E4 profoundly alters lipid metabolism in various cell types [12-16] and impairs autophagy and lysosomal activity in astrocytes and neurons [17-21]. In fibroblasts, E4 may directly interfere with TFEB binding to CLEAR motifs, thereby decreasing the transcription of lysosomal genes [22]. Microglia, the immune cells of the brain, play a critical role in AD pathogenesis by regulating the clearance, deposition, and propagation of Aβ and tau aggregates, as well as mounting the inflammatory response [23-25]. Previous studies have reported that, compared to human E3/E3 homozygous microglia, E4/E4 microglia exhibit significant transcriptional alterations, impaired uptake of lipids and Aβ, and deficits in mitochondrial metabolism, calcium signaling, and migration [12-14, 26-28]. However, whether the E4 variant alters autophagy or lysosomal activity in microglia in basal or inflammatory conditions is unknown. To address this question, we utilized human induced pluripotent stem cell (iPSC)-derived microglia (iMGs) with E4/E4 and E3/E3 genotypes to investigate whether E4/E4, as a significant genetic risk factor for AD, compromises microglial endocytosis-lysosome pathways or autophagy in homeostatic or inflammatory conditions. Our study provides evidence that the E4/E4 genotype impairs pinocytosis and lysosomal activity via the mammalian target of rapamycin (mTORC)1 pathway in both homeostatic and activated iMGs compared to the E3/E3 genotype. In contrast, autophagy appears unaffected by the APOE genotype. Materials and Methods 2.1. Differentiation of human iPSC-derived microglia (iMGs) The iPSC lines used in this study are listed in Supplementary materials, Table 1. Human iPSC lines were maintained in Essential 8 medium (Thermo Fisher Scientific) on Matrigel (growth factor reduced; Corning; 1:200)-coated 3.5 cm dishes at 37 °C and 5% CO2. The cells were passaged with 0.5 mM EDTA every 4–5 days. The iMGs were differentiated from iPSCs as described previously [29-31]. In brief, iPSC colonies were detached using ReLeSR reagent (STEMCELL Technologies), plated at density of 3-6 colonies per cm 2 on Matrigel-coated 6-well plates (1:200) in Essential 8 medium supplemented with 5 µM ROCK inhibitor Y-27632 (Selleckchem), and differentiated into hematopoietic progenitors using the commercial STEMdiff Hematopoietic kit (STEMCELL Technologies) for 11-13 days. Floating hematopoietic progenitors were then collected and plated at a density of 7000-8000 cells per cm 2 on new Matrigel-coated 6-well plates. The cells were grown for 27 days in microglial differentiation medium containing DMEM/F12, 2× insulin-transferrin-selenite, 2× B27, 0.5× N2, 1× Glutamax, 1× non-essential amino acids (all from Thermo Fisher Scientific), 400 μM monothioglycerol (Merck Millipore), 5 μg/mL human insulin (Merck Millipore), 100 ng/mL human interleukin-34 (IL-34) (Sino Biological), 50 ng/mL human transforming growth factor beta 1 (TGF-β1), and 25 ng/mL human macrophage colony-stimulating factor (M-CSF) (Peprotech, Thermo Fisher Scientific). Fresh medium was added every other day. To promote microglial maturation, 100 ng/mL human CD200 (Biolegend) and 100 ng/mL human C-X3-C motif chemokine ligand 1 (CX3CL1) (Peprotech, Thermo Fisher Scientific) were added to the cells during the last 4 days of culture. The generated cells exhibited immunopositivity for the microglial markers Iba1 (ionized calcium binding adaptor molecule 1), CD18 (β2 integrin), CX3CR1 (C-X3-C motif chemokine receptor 1), and TREM2 (triggering receptor expressed on myeloid cells 2) (Supplementary Fig. 2A). 1.2. LPS and LPS plus IFNγ treatment The iMGs were replated at the density of 50,000 to 70,000 cells per cm 2 4-5 days before the experiment in the maturation medium. The cells were then treated with 100 ng/ml LPS (Merck Millipore) alone or with the combination of 50 ng/ml LPS and 15 ng/ml human IFNγ (Peprotech, Thermo Fisher Scientific) for 24h or 48h in iMG medium containing only IL-34 and M-CSF but no other cytokines. 1.3. Soluble Aβ42 treatment Human Aβ (1-42 trifluoroacetate, Bachem) was solubilized completely using 1,1,1,3,3,3-Hexafluoro-2-propanol (HIFP). After complete evaporation of HIFP using SpeedVac Vacuum concentrator, Aβ was reconstituted in dimethyl sulfoxide (DMSO) at a final concentration of 2.5 mM and sonicated for 10 min in the water bath sonicator. Then Aβ was diluted to 100 μM concentration in cold phosphate-buffered saline Dulbecco’s phosphate-buffered saline (D-PBS; Thermo Fisher Scientific) and incubated for three days at RT. The endotoxin concentration (48 EU/ml) of the 100 μM Aβ42 was quantitatively measured by using ToxinSensorTM Chromogenic LAL Endotoxin Assay Kit (GenScript, Cat L00350C) according to the manufacturer’s instructions. Then Aβ42 was subsequently added to the cells at final concentration of 200 nM and incubated for 48 h at 37 °C before harvesting the cells and media. For Western blot (WB), the iMGs were maturated on Matrigel-coated (1:100) 6-well plates at density of 47,000 cells per cm 2 for 4 days. The treatment was started 48 hours before collection by replacing half of the old media with fresh iMG medium containing only IL-34 and M-CSF cytokines with or without soluble Aβ42 oligomers. For one E4/E4 cell line, rapamycin was given at a final concentration of 100 nM 24 h before collection. On a day of collection, bafilomycin-treated cells were incubated for 3 h at 37°C with bafilomycin A1 (Lysosomal Activity Assay Kit ab234622, Abcam), diluted according to the manufacturer’s instructions) before lysing the cells. 1.4. L-leucyl-L-leucine methyl ester (LLOMe) treatment For studying the lysosomal membrane permeabilization by the LLOMe treatment assay, the cells were plated at a density of 45,500 cells per cm 2 onto coverslips coated with Matrigel (1:100). On the treatment day, H-Leu-Leu-OMe Hydrochloride (LLOMe) (#6491-83-4, Santa Cruz Biotechnology) was dissolved in DMSO, old media was removed from the cells and 250 μl of fresh iMG medium without cytokines supplemented with DMSO (vehicle) or 200 μM LLOME was added on top of the cells. The iMGs were incubated for 2h at 37°C before fixation with 4% formaldehyde in D-PBS supplemented with 0.9 mM CaCl 2 and 0.5 mM MgCl 2 at RT for 20 min. 1.5. Immunocytochemistry The iMGs were permeabilized and unspecific binding sites blocked with 0.3% Triton X-100 in 5% normal goat serum in D-PBS at RT for 1h. The iMGs were incubated with primary antibody (Supplementary materials, Table 2) in 5% normal goat serum in D-PBS at 4°C overnight following secondary antibody incubation (Supplementary materials, Table 2) at RT for 1 h. Nuclei were visualized by DAPI (Merck Millipore) staining at RT for 5 min and the coverslips were mounted with Fluoromount-G Mounting Medium (Thermo Fisher Scientific). LGALS1 primary antibody was a generous gift from Prof. P. Laakkonen, University of Helsinki. The images of LGALS1-stained cells were acquired with Zeiss LSM980 confocal microscope with C-Apochromat 63x/1.20 W Korr UV VIS IR objective . LGALS1 puncta were quantified with Fiji ImageJ v. 1.53 software using the Gaussian blur filter and the difference of Gaussians. The number of puncta in the image was normalized by the number of cell nuclei. Three images per iPSC line per treatment were quantified. 1.6. Reverse transcription quantitative real-time PCR (RT-qPCR) for in vitro iMGs RNA was isolated by using Qiagen RNeasy Mini Kit (#74106, Qiagen) according to manufacturer’s instructions. cDNA was synthetized from isolated RNA by using Maxima reverse transcriptase enzyme (#EP0742, Thermo Fisher Scientific) according to manufacturer’s instructions. The expression levels of genes of interest were measured by using Maxima Probe/ROX qPCR Master Mix (#11813923, Thermo Fisher Scientific) and the Taqman primers listed in Supplementary materials, Table 3 on Bio-Rad CFX96 Real-Time System (Bio-Rad). The relative mRNA expression results were normalized to the ΔC T averages of two housekeeping genes GAPDH and ACTB using 2 -ΔΔCT method. 1.7. Cell Mito Stress mitochondrial function assay The Seahorse XF Cell Mito Stress Test (Agilent) was used to measure the key parameters of the mitochondrial function in the cells. The manufacturer’s instructions were followed for the workflow of the experiment. Briefly, the cells were plated 40,000 cells per well in 200 μl maturation medium one week before the experiment, and half of the medium was replaced with a fresh medium every other day. On the day of the experiment, the Seahorse XF Assay medium was prepared by supplementing the Seahorse DMEM medium with Glutamax (Gibco, Thermo Fisher Scientific) to a final concentration of 2 mM. The cells were rinsed with 180 μl of Seahorse XF medium followed by the addition of Seahorse XF medium to a final volume of 180 μl. The cells were incubated in a non-CO 2 incubator at 37°C for 1 h before running on the XFe96 Analyzer (Agilent). At the beginning of the assay, glucose and sodium pyruvate (Gibco) were added by the XFe96 Analyzer to cells to final concentrations of 10 mM and 1 mM, respectively. Next, modulators of the electron transport chain all 1 μM were injected in the following order: oligomycin (Cayman Chemical) to inhibit ATP synthase and determine ATP production of the cells, Carbonyl cyanide-4 (trifluoromethoxy) phenylhydrazone (FCCP) (Cayman Chemical) to collapse the proton gradient and disrupt the mitochondrial membrane potential and to determine the maximal and spare respiratory capacity of the cells, a mixture of rotenone (Cayman Chemical) and antimycin a (Merck Millipore) to inhibit complexes I and III and to determine nonmitochondrial respiration of the cells. Oxygen consumption rate (OCR) was directly measured by XFe96 Analyzer during the assay. Results were normalized by the cell confluence analyzed by IncuCyte S3 at the Biomedicum Stem Cell Center, University of Helsinki, before the beginning of the assay and the key parameters of the mitochondrial function of the cells were calculated using Seahorse Wave Software and exported to Excel. 1.8. Glycolysis Stress Test The Agilent Seahorse XF Glycolysis Stress Test was used to measure the glycolytic function of the cells, and it was performed simultaneously with the Agilent Seahorse XF Cell Mito Stress Test. Extracellular acidification rate (ECAR) was directly measured by the XFe96 Analyzer during the assay. The manufacturer’s instructions were followed for the workflow of the experiment. First, glucose and sodium pyruvate were injected by XFe96 Analyzer on cells to final concentrations of 10 mM and 1 mM, respectively. Glucose was partially catabolized by the cells through the glycolytic pathway to pyruvate, leading to a rapid increase in ECAR, which was reported as glycolysis under basal conditions. Next oligomycin was injected on cells to inhibit ATP synthase and to shift the energy production to glycolysis. The following increase in ECAR was used to determine the cellular maximum glycolytic capacity. The obtained ECAR values were normalized to the cell confluence assessed by IncuCyte S3, and the key parameters of the glycolytic function of the cells were calculated using Seahorse Wave Software and exported to Excel. 1.9. Cytokine quantification Media were collected and centrifuged at 16,000 G 10 min 4 °C to remove debris. The cells were lysed using RIPA Lysis and Extraction Buffer (#89900) supplemented with protease (#A32955) and phosphatase (#A32957) inhibitors (all from Thermo Fisher Scientific). The protein concentration was measured using BCA kit (#10741395, Thermo Fisher Scientific). The media and lysates were stored at -80 °C until analysis. The levels of human TNFα (tumor necrosis factor alpha), CCL5 (C-C motif chemokine ligand 5), CCL3 (C-C motif chemokine ligand 5), IL6 (interleukin-6), and IL8 (interleukin-8) in the media, were measured using the mixture of corresponding Cytometric Bead Array (CBA) Flex sets and Human Soluble Protein Master Buffer Kit (both from BD Biosciences) according to manufacturer’s instructions. The samples were analyzed using the BD Accuri C6 Plus flow cytometer with BD CSampler Plus software (BD Biosciences) at the Biomedicum Flow Cytometry Core Facility, University of Helsinki. Mean PE-Height fluorescence intensity values were used to construct the standard curves. Concentration values were derived from standard curves using log-log regression and normalized to protein concentration in cell lysates. 1.10. Western Blot To study the autophagic flux in basal conditions, the iMGs were maturated on Matrigel-coated (1:200) 12-well plates at 200,000 cells per well for 5 days. On the day of the collection, the cells were treated with either rapamycin only at a final concentration of 100 nM for 6 h, bafilomycin A1 only (Lysosomal Activity Assay Kit ab234622, Abcam, diluted according to the manufacturer’s instructions) for 3h or a combination of rapamycin (100 nM) and bafilomycin A1 for 6 h before collecting the cells. The cells were lysed with RIPA Lysis and Extraction Buffer (#89900) supplemented with protease (#A32955) and phosphatase (#A32957) inhibitors (all from Thermo Fisher Scientific). The protein concentration was measured using BCA kit (#10741395, Thermo Fisher Scientific) and the proteins were denatured by boiling in 4xSample Buffer (62.5mM Tris-HCl pH6.8, 2.5% SDS, 0.002% Bromophenol blue, 5% β-mercaptoethanol and 10% glycerol). Total amount of 5-10 μg of protein were loaded and separated on a 4-20% Mini-PROTEAN® TGX™ Gels (#4561094, Bio-Rad) and transferred to polyvinylidene fluoride (PVDF) membranes using the Trans-Blot Turbo Transfer system (Bio-Rad). The membranes were blocked in 5% fat-free milk in TBS-0.05% Tween (TBST) buffer at RT for 1h and incubated overnight with the primary antibody diluted in 5% bovine serum albumin – 0,02% Na azide in TBST at 4°C. The following day the membranes were washed and incubated with the horseradish peroxidase (HRP)-conjugated secondary antibodies for 1h at RT. After washes the chemiluminescence signal was detected by using ECL Plus (#32132) or ECL (#32106) Western Blotting Substrate (both Thermo Fisher Scientific) and G:BOX Chemi XX6 (Syngene) imaging system. ImageJ software was used for semi-quantitive analysis of the membranes. 1.11. Lysosomal activity For assaying lysosomal activity, we used the Lysosomal Intracellular Activity Assay Kit (#ab234622, Abcam) and the assay was conducted according to the protocol provided by the manufacturer. Briefly, the iMGs were plated on 12-well plates at a density of 57,000 iMGs per cm 2 and maturation was started 3-5 days prior to the experiment. One day before the experiment half of the media was replaced with iMG medium containing only IL-34 and M-CSF cytokines. On the day of the experiment the control cells and the cells to be treated with bafilomycin A1 were pelleted by centrifuging the 12-well plates at 300xg for 5 min at RT. After centrifugation the old media was removed and replaced by fresh media with or without bafilomycin A1 and the cells were incubated 1h at 37°C with 5% CO 2 . After incubation the cells were pelleted as above and after centrifugation the old media was removed and 500 μl of new media supplemented with Self-Quenched Substrate provided by the kit (15 μl per 1ml of media) with or without bafilomycin A1 was added on top of the cells. The cells were then incubated 1h at 37°C, 5% CO 2, before removing all the media and adding 1ml of ice-cold 1% bovine serum albumin in D-PBS. The cells were scraped off, washed with ice-cold 1xAssay buffer and resuspended to 500 μl of D-PBS. The mean fluorescence intensity (MFI) in FITC channel was analyzed using the BD Accuri C6 Plus flow cytometer. 1.12. Endocytosis For pHrodo dextran endocytosis assays, the cells were plated at a density of 62,500 cells per cm 2 into a black-walled 96-well imaging plate in 100μl iMG medium containing the maturation factors (CD200 and CX3CL1) 2-3 days before performing the assay. One day before the experiment half of the media was removed and 50 μl of fresh media containing treatments (final concentrations 50 ng/ml LPS and 15 ng/ml IFNγ) were added on top of cells. On a day of the assay, Invitrogen TM pHrodo TM Red (#10361) or Green (#P35368) 10 kDa Dextran conjugates were dissolved in D-PBS in a final concentration of 0.1mg/ml. After removing 20 μl of old media from the wells, added 20 μl of conjugate suspension on top of the cells to a final concentration of 16,7-20 μg/ml. The endocytosis assay was performed using IncuCyte S3 live cell imaging system (Sartorius) at the Biomedicum Stem Cell Center core facility, University of Helsinki. The cells were imaged first every 30 minutes and after 4.5 h every 1 h for 20 h and the integrated intensity of the fluorescence signal was normalized to cell confluence assessed by IncuCyte S3 before adding the pHrodo dextran conjugates. In case of apilimod treatment, the treatments for the control and apilimod treated cells were added on the day of the assay by removing 20 μl of the old media and adding 20 μl of fresh media with DMSO as a vehicle or apilimod in a final concentration of 0.683 μM before the addition of the conjugate suspension on top of the cells. 1.13. Non-targeted metabolomics Sample preparation. Non-targeted metabolomics analysis was run by the company Afekta Technologies, Kuopio, Finland (www.afekta.com). The cell pellets, containing 560,000 to 600,000 cells each, were dissociated with 60 μl of Milli-Q water at RT. The suspension was sonicated for 5 min at RT to homogenize the cells, after which 240 μl of cold 80% aqueous methanol was immediately added to stop any remaining cellular activity and to extract the metabolites. The samples were then vortexed for 10 s at RT and let settle down for 5-10 min. The centrifugation was performed at 13 000 rpm and 4 °C for 5 min. Immediately after centrifugation, the supernatant was collected carefully without disturbing the pellet with a 1 ml syringe and injected into an HPLC vial with a glass insert. The samples were stored at –20 °C until analysis. LC–MS analysis. The samples were analyzed by liquid chromatography–mass spectrometry, consisting of a Vanquish Flex UHPLC system (Thermo Fisher Scientific) coupled with a high-resolution Orbitrap mass spectrometer (Q Exactive Focus, Thermo Fisher Scientific). The analytical method has been described in detail previously [32, 33]. In brief, a Zorbax Eclipse XDB-C18 column (2.1 × 100 mm, 1.8 μm; Agilent Technologies) was used for the reversed-phase (RP) separation and an Aqcuity UPLC BEH amide column (Waters) for the hydrophilic interaction chromatography (HILIC) separation. After each chromatographic run, the ionization was carried out using jet stream electrospray ionization (ESI) in the positive and negative mode, yielding four data files per sample. The collision energies for the MS/MS analysis were selected as 10, 20 and 40 V, for compatibility with spectral databases. Data analysis. Peak detection and alignment were performed in MS-DIAL ver. 4.60 [34]. For the peak collection, m/z values between 50 and 1500 and all retention times were considered. The amplitude of the minimum peak height was set at 120000. The peaks were detected using the linear weighted moving average algorithm. For the alignment of the peaks across samples, the retention time tolerance was 0.05 min, and the m/z tolerance was 0.015 Da. The differential features between the genotypes were detected using featurewise linear mixed models, where feature levels were predicted by genotype and cell ID was used as a random effect. The mixed models were fitted separately for samples in each of the two treatments. Benjamini–Hochberg false discovery rate (FDR) correction was performed on the p -values to account for multiple tests. All analyses were conducted with R version 3.6.3 and notame version 0.0.6. Compound identification. The chromatographic and mass spectrometric characteristics (retention time, exact mass, and MS/MS spectra) of the significantly differential molecular features were compared with entries in an in-house standard library and publicly available databases, such as METLIN and HMDB, as well as with published literature. For molecular features without a match in publicly available spectral databases, a secondary annotation attempt was performed in MS-FINDER software [35] by calculating the molecular formula based on the isotopic pattern and exact mass and comparing the experimental MS/MS (if available) with in silico MS/MS spectra generated from databases of known natural and other compounds. 1.14. Proteomics The cells were maturated on original 6-well plates for 4 days prior to the experiment. Further, the cells were treated for 48 h with 50 ng/ml LPS and 15 ng/ml IFNγ in iMG medium supplemented only with IL-34 and M-CSF or left untreated. Then the cells were washed with 1 ml of ice-cold D-PBS and harvested by scraping and centrifuging at 1000 G for 5 min at 4 °C. The cells were then washed one more time with ice-cold D-PBS, and pellets were frozen on dry ice and kept at -80 °C until analysis. Samples were lysed in STET lysis buffer (1% (v/v) Triton X-100, 150 mM NaCl, 2 mM EDTA, 50 mM TrisHCl pH 7.5). Cell debris and undissolved material was removed by centrifugation at 16,000 g at 4°C for 10 min. The protein concentration was estimated using the Pierce 660 nm assay (Thermo Fisher Scientific). A modified protocol for single-pot solid-phase enhanced sample preparation (SP3) was applied. In brief, 15 µg of protein lysate MgCl 2 was added to a final concentration of 10 mM. DNA was digested using 25 U of Benzonase (Sigma-Aldrich) per sample at 37°C for 30 minutes. Proteins were reduced by adding dithiothreitol (Biozol) to a final concentration of 10 mM, followed by incubation for 30 minutes at 37°C. For cysteine alkylation, iodoacetamide (Sigma-Aldrich) was added to a final concentration of 40 mM and samples were incubated 30 minutes at roo temperature in the dark. The reaction was quenched with an additional dose of dithiothreitol. Proteins were bound to 200 µg of a 1:1 mixture of hydrophilic and hydrophobic magnetic Sera-Mag SpeedBeads (Cytiva) by adding ethanol (Sigma-Aldrich) to a final concentration of 80% (v/v) and mixing on a thermomixer (Eppendorf) for 30 minutes at RT. The beads were washed four times with 200 µL of 80% ethanol using a Dynamag-2 magnetic rack (Thermo Fisher Scientific). For proteolytic digestion, 190 ng of LysC and 190 ng of trypsin (Promega) were added in 40 µL of 50 mM ammonium bicarbonate, followed by 16 hours of incubation at RT. The supernatants were filtered using 0.22 µm spin-filters (Costar Spin-X, Corning) and then dried via vacuum centrifugation. The dried peptides were re-dissolved in 20 µL of 0.1% formic acid. The peptide concentration after digestion was quantified using the Qubit protein assay (Thermo Fisher Scientific). An amount of 350 ng of peptides per sample were subjected to the LC-MS/MS proteomic analyses on a nanoElute system (Bruker Daltonics) which was online coupled with a timsTOF pro mass spectrometer (Bruker Daltonics) equipped with an column oven. An amount of 350 ng of Peptides were separated on a 15 cm (75 µm ID) column self-packed with ReproSil-Pur 120 C18-AQ resin (1.9 µm, Dr. Maisch GmbH) using a 120 min long binary gradient of water and acetonitrile supplemented with 0.1% formic acid at a flow rate of 300 nL/min and a column temperature of 50°C. Data independent acquisition Parallel Accumulation Serial Fragmentation (DIA-PASEF) was used. One MS1 full scan was followed by 34 sequential DIA windows with 26 m/z width for peptide fragment ion spectra with an overlap of 1 m/z covering a scan range of 350 to 1200 m/z. The ramp time was fixed to 100 ms and 2 windows were scanned per ramp resulting in a total cycle time of 1.9 s.For protein label free quantification (LFQ), the LC-MS/MS raw data was analysed with the software DIA-NN [36] (version 1.8) using a library-free search against a canonical one-protein gene database of Homo sapiens from UniProt (download: 2022-01-12, 20600 entries) supplemented with a contaminants database from Maxquant (240 entries) [37]. Trypsin was defined as protease and maximum 2 missed cleavages were allowed. Acetylation of protein N-termini and methionine oxidation were defined as variable modifications whereas carbamidomethylation of cysteines was defined as fixed modification. Tolerances for mass accuracy and ion mobility were automatically optimized by DIA-NN. The false discovery rates for precursors and proteins were set to 1%. For statistical analysis, the software Perseus (v 1.6.2.3) [38] was used. Protein LFQ values were accepted on the basis of at least 2 peptides. Contaminants were removed and protein LFQ were log2 transformed. A Student’s ttest was applied between the different groups for statistical testing of abundance differences. A permutation-based FDR correction for multiple hypotheses was applied with a p-value of 0.05 and s0 of 0.1 [39]. The FDR thresholds are visualized as hyperbolic curves. The differentially expressed protein data that met the p -value < 0.05 and fold change ≥ 2 (in both directions) cutoffs were further analyzed using QIAGEN Ingenuity Pathway Analysis (IPA) as described [40]. 1.15. Statistics Statistical analysis was done using GraphPad Prism 9.2.0 (Insight Partners, New York, NY, USA) using Student’s t-test, Mann-Whitney non-parametric test or repeated measures two-way ANOVA, with Šidák’s-corrected posthoc tests. Statistical significance was assumed at p < 0.05. Results 3.1. Basal levels of lipidated LC3 and macropinocytosis are reduced in E4/E4 iMGs To generate human iMGs, we used a protocol adapted from previously published studies [29, 30]. E3/E3 and E4/E4 iMGs expressed similar levels of microglial marker genes P2RY12 (purinergic receptor P2Y12) and TREM2 (Supplementary Fig. 2B). Autophagy is commonly studied by analyzing the microtubule-associated protein light chain 3 (LC3), which is conjugated to phosphatidylethanolamine (LC3-II), using WB. During autophagy, cytosolic LC3-I is converted into lipidated LC3-II, which associates with nascent phagophore membranes that enclose intracellular material to form autophagosomes. Under basal conditions, E4/E4 iMGs exhibited significantly lower LC3-II levels compared to E3/E3 cells (Figure 1A, B). As expected, blocking autophagic flux by inhibiting lysosomal acidification with bafilomycin A led to increased LC3-II:LC3-I ratio compared to the basal levels (Figure 1 C, D), but there was no significant difference between the genotypes. Similarly, treatment with rapamycin, an inhibitor of the mTORC1 complex and a well-known autophagy inducer, did not reveal any significant differences between the genotypes (Figure 1 C, E). Collectively, these results suggest that, compared to E3/E3 iMGs, E4/E4 iMGs exhibit reduced basal levels of LC3-II but no significant differences in basal or rapamycin-induced autophagic flux, indicating that autophagy is not affected by the APOE genotype. Since total levels of LC3 and many other endolysosomal proteins can be transcriptionally regulated by TFEB, the master regulator of lysosomal biosynthesis [41, 42], we assessed the mRNA levels of MAP1LC3B , the more abundant of two genes encoding for LC3, and two abundant lysosomal endopeptidases, CTSD (cathepsin D) and CTSB (cathepsin B). RT-qPCR analysis showed that CTSD was significantly downregulated in E4/E4 iMGs, while there was no difference in CTSB or MAP1LC3B expression between the genotypes (Figure 1F), suggesting that LC3 protein levels were not primarily regulated by transcription. Since cathepsins play an essential role in lysosomal degradation, we further analyzed lysosomal activity in iMGs using flow cytometry with a self-quenched substrate and found that E4/E4 iMGs exhibited significantly lower lysosomal degradation activity compared to E3/E3 cells (Figure 1G-H). Bafilomycin-treated cells served as a negative control (Figure 1I). Lysosomal degradation activity can be influenced by the efficiency of substrate uptake into endosomes. Additionally, lipidated LC3-II associates not only with autophagosomes but also with endosomes, macropinosomes, and phagosomes, where it plays a role in vesicle recycling [43, 44]. Therefore, we next investigated endocytosis in iMGs. To assess pinocytosis (fluid-phase endocytosis), we added pHrodo-conjugated dextran (MW 10 kDa) and monitored intracellular fluorescence over 20 h using the IncuCyte live imaging system (Figure 1 J, K). Under basal conditions, pinocytosis was significantly reduced in E4/E4 iMGs compared to E3/E3 iMGs (two-way repeated measures ANOVA, time x genotype p = 0.01; Figure 1J, L). Moreover, when endosome maturation and degradation were blocked by apilimod, a significant accumulation of dextran was observed over 24 h, irrespective of the APOE genotype (repeated measures ANOVA, time x treatment p < 0.001, Figure 1M). Interestingly, the APOE genotype did not significantly affect the uptake of pHrodo-conjugated zymosan-coated beads (Supplementary Fig. 2 C-E) or fibrillar Aβ42 (Supplementary Fig.2 F, G). Collectively, these findings indicate that E4/E4 iMGs exhibit reduced endocytosis under basal conditions but no alteration in the rate of phagocytosis. 2.2. APOE 4/4 microglia exhibit reduced metabolic flexibility and dysregulated amino acid metabolism Pinocytosis serves as a mechanism to scavenge nutrients and promote cell growth in low-nutrient conditions [45]. The mitochondrial stress test, performed using Agilent Seahorse XFe96 analyzer, revealed that E4/E4 iMGs have similar basal respiration and ATP production but lower maximal respiration capacity compared to E3/E3 cells (Figure 2 A, B). The finding aligns with previous studies suggesting that E4/E4 iMGs may have a reduced ability to rapidly enhance mitochondrial activity in response to an acute increase in energy demand [26]. No significant differences between the genotypes were observed in glycolysis or glycolytic capacity (Figure 2 C, D). To investigate iMG metabolism under metabolic stress, we induced strong inflammation using a combination of bacterial lipopolysaccharide (LPS) and interferon-gamma (IFNγ) (LPS/IFNγ). As expected, this inflammatory stimulation triggered the secretion of proinflammatory cytokines and chemokines, including TNFα, CCL5, CCL3, IL6, and IL8 (Figure 2 E). To meet the increased energy demand during inflammation, microglia must significantly enhance their metabolic rate. Accordingly, LPS/IFNγ stimulation induced glycolysis, glycolytic capacity, and proton leak in mitochondria, with no significant effect of the APOE genotype (Figure 2 F, G). However, when glucose and pyruvate were unavailable, the inflammatory-stimulated iMGs displayed enhanced glutamine-dependent mitochondrial respiration. This effect was less pronounced in E4/E4 iMGs (Figure 2 G), demonstrating reduced metabolic flexibility of E4/E4 iMGs. When iMGs were subjected to 48-h LPS/IFNγ inflammatory stimulation and analyzed using un-targeted metabolomics, principal component analysis (PCA) of normalized data revealed two distinct clusters corresponding to unstimulated and stimulated cells, confirming that inflammatory stimulation induced metabolic reprogramming in iMGs (Supplementary Fig. 3 A, B). Figure 2 H highlights selected metabolites altered by LPS/IFNγ treatment, including amino acids, fatty acids, and glucose metabolites. While APOE genotypes did not cause clear clustering of the samples, a total of 50 molecular features were differentially produced (q-value < 0.1) between the E3/E3 and E4/E4 iMGs in the unstimulated group and 132 molecular features in the stimulated group. Ultimately, nine significantly altered metabolites were reliably identified: L-glutamine and plasmalogen PC O-38:7 under basal conditions (Figure 2 H; Table S1) and seven metabolites (L-tryptophan, L-methionine, L-kynurenine, phenylacetylglycine, tripeptide Pro-Ala-Arg, adenine, and pyridoxine) in the stimulated group. All identified metabolites were elevated in E4/E4 iMGs, except for plasmalogen PC O-38:7 (Figure 2H). The exact identity of this plasmalogen could not be determined from the data alone; however, in mammalian cells, the most likely candidate is PC(P-16:0/22:6(4Z,7Z,10Z,13Z,16Z,19Z)), with the longer fatty acid being docosahexaenoic acid (DHA) [46]. Since inflammation induces the hydrolysis of plasmalogens to generate pro- or anti-inflammatory mediators [47], a lower basal level of plasmalogen in E4/E4 iMGs may indicate a chronic inflammatory state. Collectively, our metabolomics results demonstrate that E4/4 iMGs exhibit dysregulated amino acid and phospholipid metabolism. 2.3. Inflammation induces lysosomal dysfunction in iMG To verify that LPS/IFNγ treatment changes the levels of key proteins regulating amino acid metabolism, we conducted proteomic analysis of five control E3/E3 iMG lines (Supplementary Fig. 3C). In line with the metabolomics data and existing literature [48], we detected an upregulation in the levels of tryptophan-metabolizing proteins (indoleamine 2,3-dioxygenase (IDO)1, kynurenine 3-monooxygenase (KMO) and kynureninase (KYNU)) following the 48h LPS/IFNγ stimulation (Table S2). We also observed increased levels of some proteins involved in glutamine uptake (SLC1A5), synthesis (GLUL) and hydrolysis (ASNS) (Table S2). When comparing the proteome of two (isogenic to each other)E4/E4 lines with E3/E3 lines, no significant differences (threshold 2-fold change, p < 0.05) were observed in the levels of the proteins involved in the tryptophan or glutamine metabolism (Tables S4, S5). The IPA analysis showed that in addition to common inflammatory pathways, such as interferon alpha/beta signaling, interferon gamma signaling and inflammasome pathway, LPS/IFNγ treatment induced PI3K/AKT signaling and autophagy pathways (Figure 3 A). The autophagy pathway included LC3 (MAP1LC3A/B) and SQSTM1/p62, a commonly recognized marker of impaired autophagic flux [49] (Figure 3B, Table S3). We also observed increased levels of cholesterol transfer protein GRAMD1A (Figure 3B, Table S2), which was recently identified as a regulator of autophagosome biogenesis [50]. In contrast, inflammatory stimulation decreased the levels of several lysosomal proteases, including cathepsin D (CTSD), lysosomal acid lipase (LIPA), lysosomal alpha-mannosidase (MAN2B1), and lysosomal pro-X carboxypeptidase (PRCP) (Figure 3B, Table S2), suggesting that strong inflammatory activation may impair lysosomal degradation. To validate the alterations identified by proteomic analysis, immunoblotting was done using the samples from an independent experiment. Consistent with the proteomics data, this WB analysis confirmed that 48-h stimulation with LPS/IFNγ strongly increased the accumulation of LC3-II as well as glutamine synthetase (GLUL), although the protein levels were not affected by the APOE genotype (Figure 3 C, D). To investigate whether the differences in protein levels were determined by transcriptional regulation, we performed RT-qPCR analysis on iMGs treated with LPS for 24 h. In agreement with the proteomics data, CTSD mRNA expression was significantly reduced following the LPS treatment (Figure 3 E). In contrast, CTSB mRNA was significantly upregulated by both LPS alone (two-way ANOVA, p = 0.015; Figure 3 E) and LPS/IFNγ stimulation (two-way ANOVA, p = 0.015; Figure 3 F), which in combination with lower protein levels at 48h suggested increased degradation or leakage of cathepsin B. The glutamate transporter SLC1A2 has recently been implicated in inflammatory responses in macrophages by sustaining macropinocytosis and mTORC1 activation [51]. While our iMGs did not express SLC1A2 under basal condition, the expression was upregulated in response to LPS stimulation and was significantly stronger in E4/E4 iMGs compared to E3/E3 iMGs (Figure 3 E). In contrast, there was no APOE genotype effect on the mRNA levels of IL1B (Figure 3 E). LPS/IFNγ stimulation increased the rate of pinocytosis in both E3/E3 and E4/E4 iMGs (Figure 3 G, H), thereby placing a greater burden on the endo-lysosomal system. 2.4. APOE 4/4 iMGs exhibit higher lysosomal membrane permeabilization upon Aβ42 exposure To determine whether comparable results could be achieved using an alternative inflammatory stimulus, more relevant for AD, we treated iMGs for 48 h with soluble Aβ42 oligomers containing 0.1 EU endotoxin per μg peptide. First, we measured cytokine secretion after Aβ42 treatment using CBA as above and found that iMGs of both genotypes secreted cytokines at levels comparable to those observed after LPS/IFNγ treatment (Figure 4 A). Further, we analyzed SQSTM1/p62 levels by WB, and found that, similarly to LPS/IFNγ stimulation, Aβ42 strongly increased intracellular p62 (p < 0.01), irrespective of the APOE genotype (Figure 4 B, C). Bafilomycin treatment did not further increase SQSTM1/p62 levels, suggesting that Aβ42 stimulation blocked lysosomal degradation. Interestingly, lysosomal-associated membrane protein 2 (LAMP-2), a key mediator of autophagosome-lysosome fusion [52, 53], was unaffected by Aβ42 stimulation but was significantly reduced in E4/E4 iMGs (Figure 4 B, C). Since proteomic analysis comparing two (isogenic to each other) E4/E4 lines to E3/E3 lines revealed a downregulation of two other lysosomal proteins MFSD1 and GLMP in E4/E4 iMGs at basal conditions (Figure 3 B, Table S4), the overall lysosomal protein content may be reduced by E4/E4 genotype. Similarly to SQSTM1/p62, LC3-II levels were significantly increased following Aβ42 stimulation (p = 0.04), however, adding bafilomycin to Aβ42-stimulated iMGs did not result in a significant change (p = 0.27; Figure 4 D, E). Phospho-NF-κB p65 (Ser536) is an active form of NF-κB (nuclear factor kappa B subunit p65), a key mediator of inflammation. As expected, Aβ42 stimulation significantly increased p-NF-κB p65 levels (p = 0.02; Figure 4 D, E). Interestingly, inhibition of lysosomal acidification with bafilomycin further increased p-NF-κB p65 in E3/E3 iMGs but not in E4/E4 iMGs, suggesting that lysosomal enzyme activity selectively affected the inflammatory response in E3/E3 iMGs. Since the accumulation of SQSTM1/p62 and LC3-II following Aβ42 exposure suggested impaired lysosomal degradation and elevated lysosomal stress, we next analyzed lysosomal membrane permeabilization (LMP) using the lysosomal galectin puncta assay [54]. As shown in Figure 4 F, G, the formation of galectin puncta, detected with galectin (LGALS)-1-specific antibody, was significantly higher in E4/E4 iMGs than in E3/E3 iMGs after Aβ42 exposure, indicating increased lysosomal leakage in E4/E4 iMGs. A two-hour treatment with LLOME served as a positive control (Figure 4 F, H). Interestingly, the levels of secreted IL8 significantly correlated with galectin puncta after Aβ42 stimulation, suggesting that lysosomal leakage exacerbated the inflammatory response (Figure 4 I). It has been demonstrated that IL8 production can be regulated by mTORC1 activity [55]. Since mTORC1 is a critical regulator of lysosomal biogenesis and autophagy [41, 56], we assessed its activity via WB by measuring phosphorylation of the S6 ribosomal protein (Ser235/236), a downstream component of mTORC1 signaling complex. Figures 4 J, K show that phosphorylated S6 levels were significantly higher in E4/E4 iMGs stimulated with Aβ42 as compared to E3/E3 iMGs, indicating increased mTORC1 activity in E4/E4 cells. Since mTORC1 can promote cell proliferation, we performed KI67 immunostaining to visualize proliferating cells. Aβ42 stimulation significantly increased cell proliferation; however, no effect of the APOE genotype was observed (Supplementary Fig. 3 D, E). As expected, treatment with the mTORC1 inhibitor rapamycin reduced NF-κB p65 phosphorylation [57] by half in an E4/E4 line (Fig. 4 L, M), suggesting that mTORC1 activity promoted inflammatory response in E4/E4 iMGs. Discussion The ε4 isoform of ApoE is the most prevalent genetic risk factor for AD. In this study, E4/E4 iMGs showed diminished basal levels of pinocytosis and lipidated LC3 in vitro . In macrophages and microglia, the primary function of constitutive pinocytosis is continuous environmental sampling for pathogens [ 58 ]. Additionally, pinocytosis has been shown to facilitate the uptake and clearance of soluble Aβ species [ 59 ]. Thus, E4/E4 iMGs may be less responsive to homeostatic perturbations and less efficient at clearing soluble waste, potentially contributing to impaired proteostasis in AD. However, we did not observe significant differences in the uptake of solid particles, such as zymosan-coated beads or fibrillar Aβ42. This suggests that the APOE genotype selectively affects fluid-phase endocytosis rather than phagocytosis. Inflammatory stimulation strongly increased autophagosome formation, pinocytosis and mTORC1 activity, while blocking autophagic flux and abolishing genotype-related differences. The blockade of the autophagic flux was further confirmed by elevated SQSTM1/p62 levels, indicating that inflammatory conditions override basal autophagic and endocytic differences between APOE genotypes. Both autophagic and endocytic pathways culminate in lysosomal degradation. Substrate overload can lead to lysosomal membrane permeabilization (LMP), allowing intralysosomal components such as cathepsins to be released into the cytoplasm, further impairing lysosomal protein degradation [ 60 ]. LMP is a hallmark of lysosomal dysfunction, which has been implicated in neurodegeneration and chronic inflammation. Interestingly, we observed an increased number of LGALS1-positive puncta in Aβ42-stimulated E4/E4 iMGs, suggesting elevated LMP. Since damaged lysosomes are cleared by autophagy (lysophagy) [ 61 ], an increased number of LGALS1 puncta may also indicate impaired lysophagy. LMP can further induce inflammasome activation in macrophages and microglia [ 62 – 65 ], a process which can be triggered by the leakage of active cathepsin B from lysosomes into the cytosol [ 63 , 64 ]. These findings suggest that APOE 4/4 microglia exhibit heightened vulnerability to lysosomal leakage and associated inflammatory cascades, potentially contributing to chronic neuroinflammation in AD. Although we did not directly assess inflammasome activation or cathepsin B activity in our study, we found a significant correlation between LMP and secreted IL8 (CXCL8), a major neutrophil chemokine known to be involved in AD [ 66 ] and regulated by inflammasome activation [ 67 ]. Furthermore, we found that bafilomycin, an inhibitor of lysosomal acidification and protease activity, exhibited a proinflammatory effect in E3/E3 iMGs, but not in E4/E4 iMGs, indicating genotype-dependent differences in lysosomal regulation of inflammation. Additionally, we observed an upregulation of cathepsin B mRNA in LPS/IFNγ-stimulated E4/4 iMGs, while its protein levels were decreased. In human iPSC-derived macrophages, LMP has recently been linked to metabolic reprogramming in mitochondria [ 68 ], and the LMP-induced changes in mitochondrial respiration and glycolysis were similar to those we observed in iMGs following LPS/IFNγ stimulation. These findings further support a role for LMP in driving inflammatory activation in E4/E4 iMGs, which may be mitigated by targeting lysosomal acidification. Our results are consistent with previous studies in murine models, where prolonged exposure to Aβ42 resulted in the accumulation of autophagosomes, LMP, and cathepsin D leakage in murine microglial cell line [ 69 ]. Although it has been shown before that E4/E4 potentiates LMP in neuroblastoma cells after Aβ treatment in vitro [ 70 , 71 ], our study is the first to demonstrate the effect of E4/E4 genotype on LMP in human microglia, which are central to late-onset AD pathophysiology. We also observed elevated levels of amino acids, particularly L-glutamine, in E4/E4 iMGs, along with increased mRNA expression of the glutamate transporter SLC1A2 following inflammatory stimulation. Glutamine and glutamate metabolism are tightly linked. Glutaminase (GLS) catalyzes glutamine conversion into glutamate, thus facilitating its utilization in the TCA cycle and activating mTORC1 [ 72 ]. In microglia/macrophages, M1 polarization and inflammasome activation require increased glutamine utilization in the TCA cycle [ 49 , 72 ]. High levels of glutamine and leucine in the extracellular environment have been shown to stimulate protein synthesis, suppress autophagy, promote inflammatory responses via the mTORC1 pathway, and reduce lysosomal acidification [ 73 – 78 ]. However, our E4/E4 iMGs exhibited lower, rather than higher, mitochondrial utilization of glutamine, as indicated by mitochondrial stress test results. This suggests that instead of enhanced glutamine-to-glutamate conversion, E4/E4 iMGs might have increased lysosomal glutamate efflux, sustaining mTORC1 activation [ 51 ]. Additionally, the elevated kynurenine levels detected in E4/E4 iMGs after LPS/IFNγ stimulation may have contributed to mTORC1 activation, as kynurenine has been shown to directly activate mTORC1 in human lymphocytes [ 79 ]. These findings indicate that targeting mTORC1 signaling could be beneficial in mitigating inflammation in ApoE ε4-associated neurodegeneration. Although we did not detect APOE genotype-associated differences in basal autophagic flux, we found that E4/E4 iMGs exhibited lower levels of several key lysosomal markers, including cathepsin D and LAMP2, suggesting a reduced lysosomal content. Notably, LAMP2 overexpression in ischemic cardiomyocytes has been shown to restore autophagic flux, promote cathepsin trafficking, and mitigate lysosomal membrane permeabilization (LMP) [ 80 ]. These results highlight the potential therapeutic relevance of enhancing lysosomal biogenesis in APOE 4/4 carriers. We could not replicate previously reported glycolytic abnormalities in E4/E4 iMGs. Prior studies have reported conflicting data regarding aerobic glycolysis levels in E4/E4 iMGs. While Konttinen et al. [ 26 ] reported a significant decrease in glycolysis and glycolytic capacity, Victor et al. [ 27 ] found upregulation of the glucose transporters GLUT1 (SLC2A1) and GLUT3, suggesting increased glycolysis. Additionally, a recent study of mouse E4/E4 microglia reported elevated aerobic glycolysis levels [ 81 ]. Given that glycolysis is often linked to inflammation-driven metabolic reprogramming, its levels may be highly dependent on experimental conditions. Conclusion Our study provides new insights into ApoE ε4-mediated alterations in microglial lysosomal function, metabolism, and inflammation. We demonstrate that APOE 4/4 microglia exhibit reduced basal endocytosis, heightened lysosomal membrane permeabilization, and increased susceptibility to inflammatory activation. Our findings suggest that ApoE ε4 enhances lysosomal stress and impairs proteostasis through increased mTORC1 signaling, dysregulated amino acid metabolism, and reduced lysosomal biogenesis. Given the role of microglia in AD pathogenesis, these results highlight the potential of targeting lysosomal function and mTORC1 signaling as therapeutic strategies for ApoE ε4-associated neurodegeneration. Abbreviations AD Alzheimer’s disease ApoE apolipoprotein E Aβ beta-amyloid Bafi bafilomycin CBA cytometric bead array CCL3 C-C motif chemokine ligand 3, MIP1α CCL5 C-C motif chemokine ligand 5, RANTES CLEAR coordinated lysosomal expression and regulation CTSB cathepsin B CTSD cathepsin D CX3CL1 C-X3-C motif chemokine ligand 1 DMSO dimethyl sulfoxide D-PBS Dulbecco’s phosphate-buffered saline E3 ApoE isoform ε3 E4 ApoE isoform ε4 ECAR extracellular acidification rate FCCP carbonyl cyanide-4 (trifluoromethoxy) phenylhydrazone FDR false discovery rate GLUL glutamine synthetase HIFP 1,1,1,3,3,3-Hexafluoro-2-propanol IFNγ interferon-gamma IL interleukin iMG induced pluripotent stem cell-derived microglia IPA Ingenuity Pathway Analysis iPSC induced pluripotent stem cell LAMP-2 lysosomal-associated membrane protein 2 LC3 microtubule-associated protein light chain 3 LC3- II LC3 conjugated to phosphatidylethanolamine LLOMe L-leucyl-L-leucine methyl ester LMP lysosomal membrane permeabilization LPS lipopolysaccharide M-CSF macrophage colony-stimulating factor MFI mean fluorescence intensity MITF microphthalmia-associated transcription factor mTORC mammalian target of rapamycin NF-κB nuclear factor kappa B subunit NT basal conditions/untreated OCR oxygen consumption rate RAPA rapamycin RT room temperature RT-qPCR reverse transcription quantitative real-time PCR SQSTM1/p62 sequestosome 1 TBST TBS-0.05% Tween TFEB transcription factor EB TNFα tumor necrosis factor alpha TREM2 triggering receptor expressed on myeloid cells 2 WB Western Blot Declarations Ethics approval The use of human iPSC lines was approved by the Committee on Research Ethics of Northern Savo Hospital District (license no. 123/2016). Availability of data and materials Full metabolomic and proteomic datasets generated in this study are available from the corresponding authors on reasonable request. Acknowledgements We would like to thank the technicians Anne Nyberg and Agnes Viherä for the assistance with the expansion of iPSCs and mycoplasma testing. We would also like to thank the technician Erja Huttu for the assistance with RT-qPCRs. The live imaging analysis was performed at the Biomedicum Stem Cell Center, University of Helsinki, funded by HILIFE and Biocenter Finland. The flow cytometry analysis was performed at the HILIFE Flow Cytometry Unit, University of Helsinki. The metabolomic analysis was done by Afekta Technologies, Kuopio, Finland. Funding This project has received funding from JPco-fuND2 2019 Personalized Medicine for Neurodegenerative Diseases (PMG-AD, grant number 01ED2002A/ 334802) to MiH and JK; Business Finland (Go for Growth with Novel Stem Cell Platform to JK and TR); the Academy of Finland (grant 334525, JK; grant 338182, MiH; UHBrain Profi 6, TR); German Research Foundation under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy– ID 390857198) to SFL; Alzheimer Forschung Initiative e.V. to SFL; the Finnish Concordia Fund and Föreningen Granatenhjelm R.F. to MaH. The funders had no role in the study design, data collection, or interpretation. We declare no competing interests. Authors’ contributions Conceptualization and study design: TR, JK, MaH; methodology: MaH, MK, SM, SFL, SL, MT, MiH, JK, TR; investigation: MaH, IW, SM, TR; formal analysis: MaH, SM, TR; visualization: MaH, SM, TR; resources: SL, MP, KF, SFL, VL, AR, MiH, JK; funding acquisition: MaH, SFL, MiH, JK; project administration: TR; supervision: JK, TR; writing- original draft: TR, MaH, JK; writing-review & editing: all authors. Consent for publication All the authors have approved the final version of the manuscript and provided their consent for publication. Competing interests The authors declare that they have no competing interests. References Nixon, R.A. and D.S. Yang, Autophagy failure in Alzheimer's disease--locating the primary defect. Neurobiol Dis, 2011. 43 (1): p. 38-45. Quick, J.D., et al., Lysosomal acidification dysfunction in microglia: an emerging pathogenic mechanism of neuroinflammation and neurodegeneration. J Neuroinflammation, 2023. 20 (1): p. 185. 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Maxson, Constitutive and stimulated macropinocytosis in macrophages: roles in immunity and in the pathogenesis of atherosclerosis. Philos Trans R Soc Lond B Biol Sci, 2019. 374 (1765): p. 20180147. Mandrekar, S., et al., Microglia Mediate the Clearance of Soluble Aβ through Fluid Phase Macropinocytosis. Journal of Neuroscience, 2009. 29 (13): p. 4252-4262. Marques, A.R.A. and P. Saftig, Lysosomal storage disorders - challenges, concepts and avenues for therapy: beyond rare diseases. Journal of Cell Science, 2019. 132 (2). Hoyer, M.J., S. Swarup, and J.W. Harper, Mechanisms Controlling Selective Elimination of Damaged Lysosomes. Curr Opin Physiol, 2022. 29 . Muñoz-Planillo, R., et al., K Efflux Is the Common Trigger of NLRP3 Inflammasome Activation by Bacterial Toxins and Particulate Matter. Immunity, 2013. 38 (6): p. 1142-1153. Jessop, F., et al., Phagolysosome acidification is required for silica and engineered nanoparticle-induced lysosome membrane permeabilization and resultant NLRP3 inflammasome activity. Toxicology and Applied Pharmacology, 2017. 318 : p. 58-68. Chevriaux, A., et al., Cathepsin B Is Required for NLRP3 Inflammasome Activation in Macrophages, Through NLRP3 Interaction. Frontiers in Cell and Developmental Biology, 2020. 8 . Katsnelson, M.A., et al., NLRP3 inflammasome signaling is activated by low-level lysosome disruption but inhibited by extensive lysosome disruption: roles for K+ efflux and Ca2+ influx. American Journal of Physiology-Cell Physiology, 2016. 311 (1): p. C83-C100. Righi, D., et al., Investigating interleukin-8 in Alzheimer's disease: A comprehensive review. Journal of Alzheimers Disease, 2025. 103 (1): p. 38-55. Busch, M., et al., Assessing the NLRP3 Inflammasome Activating Potential of a Large Panel of Micro- and Nanoplastics in THP-1 Cells. Biomolecules, 2022. 12 (8). Bussi, C., et al., Lysosomal damage drives mitochondrial proteome remodelling and reprograms macrophage immunometabolism. Nat Commun, 2022. 13 (1): p. 7338. Pomilio, C., et al., Microglial autophagy is impaired by prolonged exposure to β-amyloid peptides: evidence from experimental models and Alzheimer's disease patients. Geroscience, 2020. 42 (2): p. 613-632. Persson, T., et al., Apolipoprotein E4 Elicits Lysosomal Cathepsin D Release, Decreased Thioredoxin-1 Levels, and Apoptosis. J Alzheimers Dis, 2017. 56 (2): p. 601-617. Ji, Z.S., et al., Apolipoprotein E4 potentiates amyloid beta peptide-induced lysosomal leakage and apoptosis in neuronal cells. J Biol Chem, 2002. 277 (24): p. 21821-8. Zhang, Z.X., et al., Glutamine metabolism modulates microglial NLRP3 inflammasome activity through mitophagy in Alzheimer's disease. Journal of Neuroinflammation, 2024. 21 (1). Chen, R., et al., The general amino acid control pathway regulates mTOR and autophagy during serum/glutamine starvation. Journal of Cell Biology, 2014. 206(2) (2): p. 173-182. Jewell, J.L., et al., Differential regulation of mTORC1 by leucine and glutamine. Science, 2015. 347(6218) (6218): p. 194-198. Yoon, B.R., et al., Role of SLC7A5 in Metabolic Reprogramming of Human Monocyte/Macrophage Immune Responses. Frontiers in Immunology, 2018. 9 . Baik, S.H., et al., A Breakdown in Metabolic Reprogramming Causes Microglia Dysfunction in Alzheimer's Disease. Cell Metab, 2019. 30 (3): p. 493-507 e6. Nicklin, P., et al., Bidirectional Transport of Amino Acids Regulates mTOR and Autophagy. Cell, 2009. 136(3) (3): p. 521-534. Xiong, J., et al., Glutamine Produces Ammonium to Tune Lysosomal pH and Regulate Lysosomal Function. Cells, 2022. 12 (1). Perl, A., et al., Comprehensive metabolome analyses reveal N-acetylcysteine-responsive accumulation of kynurenine in systemic lupus erythematosus: implications for activation of the mechanistic target of rapamycin. Metabolomics, 2015. 11 (5): p. 1157-1174. Cui, L., et al., The Lysosomal Membrane Protein Lamp2 Alleviates Lysosomal Cell Death by Promoting Autophagic Flux in Ischemic Cardiomyocytes. Frontiers in Cell and Developmental Biology, 2020. 8 . Lee, S., et al., APOE modulates microglial immunometabolism in response to age, amyloid pathology, and inflammatory challenge. Cell Rep, 2023. 42 (3): p. 112196. Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterialsandfigures.docx SupplementaryTables.xlsx RawWesternBlots.pdf Cite Share Download PDF Status: Published Journal Publication published 02 Jun, 2025 Read the published version in Journal of Neuroinflammation → Version 1 posted Editorial decision: Revision requested 16 Apr, 2025 Reviews received at journal 16 Apr, 2025 Reviews received at journal 14 Apr, 2025 Reviews received at journal 25 Mar, 2025 Reviewers agreed at journal 19 Mar, 2025 Reviewers agreed at journal 19 Mar, 2025 Reviewers agreed at journal 19 Mar, 2025 Reviewers invited by journal 19 Mar, 2025 Editor assigned by journal 18 Mar, 2025 Submission checks completed at journal 17 Mar, 2025 First submitted to journal 17 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Müller","email":"","orcid":"","institution":"German Center for Neurodegenerative Diseases","correspondingAuthor":false,"prefix":"","firstName":"Stephan","middleName":"A.","lastName":"Müller","suffix":""},{"id":433827758,"identity":"f634e4f5-9f8d-44be-99cd-483c76d68044","order_by":3,"name":"Šárka Lehtonen","email":"","orcid":"","institution":"University of Eastern Finland","correspondingAuthor":false,"prefix":"","firstName":"Šárka","middleName":"","lastName":"Lehtonen","suffix":""},{"id":433827759,"identity":"49ee7e09-85ff-4f53-b5ef-d2bb04b76dab","order_by":4,"name":"Michael Peitz","email":"","orcid":"","institution":"University of Bonn Medical Faculty \u0026 University Hospital Bonn","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Peitz","suffix":""},{"id":433827760,"identity":"cd43b15c-f450-46db-b306-bc8f48efbf30","order_by":5,"name":"Klaus Fließbach","email":"","orcid":"","institution":"University of Bonn Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Klaus","middleName":"","lastName":"Fließbach","suffix":""},{"id":433827761,"identity":"72e3d2f0-a98b-4e3a-8da9-5e47cb4efd72","order_by":6,"name":"Mari Takalo","email":"","orcid":"","institution":"University of Eastern Finland","correspondingAuthor":false,"prefix":"","firstName":"Mari","middleName":"","lastName":"Takalo","suffix":""},{"id":433827762,"identity":"409376b0-876f-4fd1-ba83-d1183dcaead8","order_by":7,"name":"Marja Koskuvi","email":"","orcid":"","institution":"University of Helsinki","correspondingAuthor":false,"prefix":"","firstName":"Marja","middleName":"","lastName":"Koskuvi","suffix":""},{"id":433827763,"identity":"6529a37a-accb-4eea-8d45-f7e9e16d1cb8","order_by":8,"name":"Stefan F. 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B, quantification of the lipidated form of LC3 (II) in iMGs in basal conditions. C, representative WB images of iMGs with (+) or without (-) rapamycin (rapa) and bafilomycin (bafi) treatment. D, E, quantifications of the LC3 (II) to LC3 (I) ratios in iMGs with (+) or without (-) rapamycin (rapa) and bafilomycin (bafi) treatment. F, the relative expression of \u003cem\u003eCTSD\u003c/em\u003e, \u003cem\u003eCTSB\u003c/em\u003eand \u003cem\u003eMAP1LC3B\u003c/em\u003e mRNA as detected by RT-qPCR. G, the mean fluorescence intensity (MFI) of iMGs incubated for 1 h with the substrate, which emits fluorescence following lysosomal degradation. H, the flow cytometry gating strategy, cleaved substrate emitted fluorescence in FITC channel. FSC-A, forward scatter area; SSC-A, side scatter area; FSC-H, forward scatter height. I, the MFI of control (E3/E3) iMGs with or without bafilomycin treatment. J, K, representative images (J) and the quantification of pHrodo signal (K) in iMGs incubated with pHrodo dextran for different periods of time. Scale bar 300 μm. Arrows, iMGs with dextran in endo-lysosomal compartment. Dots represent the mean of 3-5 iPSC lines. L, the quantification of dextran uptake at 3h. M, The quantification of dextran uptake in E3/3 and E4/4 iMGs in the presence or absence of apilimod, N = 3 iPSC lines. In B, F, G, L, the data from different differentiation batches are shown as individual dots. Same color dots are derived from the same iPSC line. Data in the graphs are shown as mean ± SEM. P values are derived from unpaired t-test (B, F, H, I, L), two-way ANOVA (D, E) or Mann-Whitney test (G). *, p \u0026lt; 0.05; **, p \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6241569/v1/37d676a0e7bbd9e4273c05ab.png"},{"id":79430797,"identity":"f4407db1-d44f-4d20-ba25-6a7f1364e046","added_by":"auto","created_at":"2025-03-28 10:41:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":449865,"visible":true,"origin":"","legend":"\u003cp\u003eE4/4 iMGs exhibit reduced metabolic flexibility and dysregulated amino acid metabolism. A, C, the oxygen consumption rate (OCR, A) and acidification rate (ECAR, C) assessed using the Seahorse analyzer. The graphs show the average of 3-4 iPSC lines obtained from one differentiation batch. B, D, the quantification of basal ATP production, maximal mitochondrial respiration, proton leak, basal glycolysis, maximal glycolytic capacity, and non-glycolytic acidification. The data from different differentiation batches are shown as individual dots. Same color dots are derived from the same iPSC line (Supplementary materials, Table 1). Data in the graphs are shown as mean ± SEM. P values are derived from Mann-Whitney non-parametric test. *, p \u0026lt; 0.05. E, the levels of cytokines/chemokines released into cell culture medium from iMGs in basal conditions and over 24h and 48h of LPS + IFNγ stimulation measured using the Cytometric Bead Array and normalized to the protein content in cell lysates. Individual dots represent individual iPSC lines and individual differentiation batches. Data in the graphs are shown as mean ± SEM. F, non-glycolytic acidification, glycolysis, maximal glycolytic capacity, and glycolytic reserve in iMGs in basal conditions (NT) and following the 24h of LPS + IFNγ stimulation (LI) as measured using Seahorse analyzer. G, the oxygen consumption rate (OCR) in basal conditions in glutamine (gln)-only medium and with the addition of pyruvate and glucose, the maximal and spare respiratory capacity, and protein leak in iMGs in basal conditions (NT) and following the 24h of LPS + IFNγ stimulation (LI). Individual dots represent the averages of technical replicates for individual iPSC lines and individual differentiation batches. P values are derived from two-way ANOVA with Sidak’s posthoc tests. *, p \u0026lt; 0.05; **, p \u0026lt; 0.01. H, a heatmap of some metabolites up (green)-or downregulated (purple) in iMGs following 48h of LPS + IFNγ stimulation. The metabolites marked in bold letters were significantly affected by E4/4 genotype. The iPSC lines are indicated at the bottom of the heatmap.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6241569/v1/92db554c153998b7a02d22c2.png"},{"id":79430799,"identity":"ea7e08f7-f8da-4223-aaa5-eefcca48d295","added_by":"auto","created_at":"2025-03-28 10:41:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":368995,"visible":true,"origin":"","legend":"\u003cp\u003eInflammation induces lysosomal dysfunction in iMGs. A, top enriched pathways for proteins upregulated (green) in LPS + IFNγ-stimulated E3/3 iMGs based on MSigDB Hallmark 2020 database. B, the heatmap of selected lysosomal proteins in iMGs in basal conditions (NT) and after 48h of LPS + IFNγ stimulation. C, D the representative Western blot images and the quantification analysis of LC3II in iMGs in basal conditions (NT) and after 48h of LPS + IFNγ stimulation. E, the relative expression of CTSD, CTSB, SLC1A2, and IL1B mRNA in basal conditions (NT) and after 24h of LPS stimulation as detected by RT-qPCR. F, the relative expression of CTSB in basal conditions (NT) and after 48h of LPS/IFNγ stimulation as detected by RT-qPCR. G, the quantification of pHrodo dextran uptake in APOE3 and APOE4 iMGs in basal conditions (NT) and after 24h LPS+IFNγ treatment. Dots represent the mean of 3-5 iPSC lines. Data in the graphs are shown as mean ± SEM. G, the quantification of dextran uptake at 3h. Dots represent individual differentiation batches and iPSC lines. P values are derived from two-way ANOVA with Sidak’s posthoc test; *, p \u0026lt; 0.05; **, p \u0026lt; 0.01; ***, p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6241569/v1/82e0710170512dee4d27e44a.png"},{"id":79430798,"identity":"7bdf2693-77a4-4ad8-9072-3c8672bf0614","added_by":"auto","created_at":"2025-03-28 10:41:47","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":359858,"visible":true,"origin":"","legend":"\u003cp\u003eE4/E4 iMGs exhibit higher lysosomal membrane permeabilization upon Aβ42 exposure. A, the levels of cytokines/chemokines released into cell culture medium from iMGs over 48h of Aβ42 stimulation measured using the Cytometric Bead Array and normalized to the protein content in cell lysates. B-E, the representative Western blot image (B, D) and quantification data (C, E) of iMGs treated with (+) and without (-) Aβ42 and bafilomycin (bafi) for 48h. F-H, representative images of LGALS1 staining (F) and quantification data of LGALS1 puncta (G, H) in iMGs treated with Aβ42, LLOME or left untreated (NT). Scale bar 20 μm. Arrows, iMGs with LGALS1 puncta. I, Correlation of the levels of secreted IL8 (y-axis) and LGALS1 puncta (x-axis) in iMGs after Aβ42 stimulation. P value and R squared value derived from Simple linear regression analysis. J-M the quantification (K, M) and representative Western blot images (J, L) of phospho-S6 ribosomal protein (Ser235/236) and phospho-NF-κB p65 (Ser536). Individual dots represent iMGs from individual iPSC lines. P values are derived from two-way repeated measures ANOVA with Sidak’s posthoc tests (C, E, G) or unpaired t-test (H). *, p \u0026lt; 0.05; **, p \u0026lt; 0.01; ***, p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6241569/v1/679b2a1b9af825f6dd147a94.png"},{"id":84242691,"identity":"baef3b9d-023c-4343-8b4f-b4f57e4fd070","added_by":"auto","created_at":"2025-06-09 16:11:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2453113,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6241569/v1/853a8cb7-bf64-4958-9502-2931b8675453.pdf"},{"id":79430809,"identity":"76c26a3e-4250-42bd-8185-fe9627f01fad","added_by":"auto","created_at":"2025-03-28 10:41:47","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2872772,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterialsandfigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-6241569/v1/3bf7c10db765d9da140cc0b1.docx"},{"id":79430802,"identity":"2d1b0ed8-e9c7-4ed9-a77b-887c1000e0fb","added_by":"auto","created_at":"2025-03-28 10:41:47","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":120295,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6241569/v1/5b857fba88e88a53231801bf.xlsx"},{"id":79430806,"identity":"ddc86e2a-40c9-41e0-81b6-beb0ca1fe9ad","added_by":"auto","created_at":"2025-03-28 10:41:47","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1173447,"visible":true,"origin":"","legend":"","description":"","filename":"RawWesternBlots.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6241569/v1/c63e76f3f70978d4b4c21f8d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Inflammation-induced lysosomal dysfunction in human iPSC-derived microglia is exacerbated by APOE 4/4 genotype","fulltext":[{"header":"Background","content":"\u003cp\u003eLysosomal dysfunction is a common feature of aging-associated neurodegenerative diseases, including Alzheimer\u0026rsquo;s disease (AD), which is characterized by the accumulation of toxic beta-amyloid (A\u0026beta;) and tau protein aggregates in the brain [1]. Since autophagy and endocytosis/phagocytosis pathways deliver dysfunctional organelles,\u0026nbsp;extracellular material, and debris\u0026nbsp;to lysosomes for degradation, lysosomal dysfunction has been suggested as a key factor promoting the accumulation of dysfunctional organelles and protein aggregates in AD\u0026nbsp;[2].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLysosome biogenesis is controlled by the microphthalmia-associated transcription factor/transcription factor E (MIT/TFE) family of transcription factors, including TFEB, TFE3, MITF, and TFEC [3].\u0026nbsp;These transcription factors bind to Coordinated Lysosomal Expression and Regulation (CLEAR) motifs and co-operate to fine-tune lysosomal gene expression in various conditions [4]. Disruption of TFEB-mediated signaling has been reported to exacerbate tau pathology\u0026nbsp;[4, 5], while TFEB overexpression in neurons and astrocytes may enhance the clearance of A\u0026beta; and tau in mouse models of AD\u0026nbsp;[6-8], highlighting a strong link between lysosomal dysfunction and AD pathology.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eApolipoprotein E (ApoE) is the primary carrier of cholesterol and triglycerides in the bloodstream and is predominantly produced by glial cells in the brain. Among the three human isoforms (\u0026epsilon;2, \u0026epsilon;3, and \u0026epsilon;4), ApoE \u0026epsilon;3 (further referred to as E3) is considered neutral, while ApoE \u0026epsilon;4 (henceforth referred to as E4) represents the most significant genetic risk factor for AD [9-11]. It is estimated that up to 50% of AD patients carry at least one E4 allele [10].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eE4 profoundly alters lipid metabolism in various cell types [12-16] and impairs autophagy and lysosomal activity in astrocytes and neurons [17-21]. \u0026nbsp;In fibroblasts, E4 may directly interfere with TFEB binding to CLEAR motifs, thereby decreasing the transcription of lysosomal genes [22].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMicroglia, the immune cells of the brain, play a critical role in AD pathogenesis by regulating the clearance, deposition, and propagation of A\u0026beta; and tau aggregates, as well as mounting the inflammatory response [23-25]. Previous studies have reported that, compared to human E3/E3 homozygous microglia, E4/E4 microglia exhibit significant transcriptional alterations, impaired uptake of lipids and A\u0026beta;, and deficits in mitochondrial metabolism, calcium signaling, and migration [12-14, 26-28]. However, whether the E4 variant alters autophagy or lysosomal activity in microglia in basal or inflammatory conditions is unknown.\u003c/p\u003e\n\u003cp\u003eTo address this question, we utilized human induced pluripotent stem cell (iPSC)-derived microglia (iMGs) with E4/E4 and E3/E3 genotypes to investigate whether E4/E4, as a significant genetic risk factor for AD, compromises microglial endocytosis-lysosome pathways or autophagy in homeostatic or inflammatory conditions. Our study\u0026nbsp;provides evidence that the E4/E4 genotype impairs pinocytosis and lysosomal activity via the mammalian target of rapamycin (mTORC)1 pathway in both homeostatic and activated iMGs compared to the E3/E3 genotype. In contrast, autophagy appears unaffected by the \u003cem\u003eAPOE\u003c/em\u003e genotype.\u0026nbsp;\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e2.1.\u0026nbsp;Differentiation of human iPSC-derived microglia (iMGs)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The iPSC lines used in this study are listed in Supplementary materials, Table 1. Human iPSC lines were maintained in Essential 8 medium (Thermo Fisher Scientific) on Matrigel (growth factor reduced; Corning; 1:200)-coated 3.5 cm dishes at 37 \u0026deg;C and 5% CO2. The cells were passaged with 0.5 mM EDTA every 4\u0026ndash;5 days. The iMGs were differentiated from iPSCs as described previously [29-31]. In brief, iPSC colonies were detached using ReLeSR reagent (STEMCELL Technologies), plated at density of 3-6 colonies per cm\u003csup\u003e2\u003c/sup\u003e on Matrigel-coated 6-well plates (1:200) in Essential 8 medium supplemented with 5 \u0026micro;M ROCK inhibitor Y-27632 (Selleckchem), and differentiated into hematopoietic progenitors using the commercial STEMdiff Hematopoietic kit (STEMCELL Technologies) for 11-13 days. Floating hematopoietic progenitors were then collected and plated at a density of 7000-8000 cells per cm\u003csup\u003e2\u0026nbsp;\u003c/sup\u003eon new Matrigel-coated 6-well plates. The cells were grown for 27 days in microglial differentiation medium containing DMEM/F12, 2\u0026times; insulin-transferrin-selenite, 2\u0026times; B27, 0.5\u0026times; N2, 1\u0026times; Glutamax, 1\u0026times; non-essential amino acids (all from Thermo Fisher Scientific), 400\u0026thinsp;\u0026mu;M monothioglycerol (Merck Millipore), 5\u0026thinsp;\u0026mu;g/mL human insulin (Merck Millipore), 100\u0026thinsp;ng/mL human interleukin-34 (IL-34) (Sino Biological), 50\u0026thinsp;ng/mL human transforming growth factor beta 1 (TGF-\u0026beta;1), and 25 ng/mL human macrophage colony-stimulating factor (M-CSF) (Peprotech, Thermo Fisher Scientific). Fresh medium was added every other day. To promote microglial maturation, 100\u0026thinsp;ng/mL human CD200 (Biolegend) and 100\u0026thinsp;ng/mL human C-X3-C motif chemokine ligand 1 (CX3CL1) (Peprotech, Thermo Fisher Scientific) were added to the cells during the last 4 days of culture. The generated cells exhibited immunopositivity for the microglial markers Iba1 (ionized calcium binding adaptor molecule 1), CD18 (\u0026beta;2 integrin), CX3CR1 (C-X3-C motif chemokine receptor 1), and TREM2 (triggering receptor expressed on myeloid cells 2) (Supplementary Fig. 2A).\u003c/p\u003e\n\u003cp\u003e1.2. LPS and LPS plus IFN\u0026gamma;\u0026nbsp;treatment\u003c/p\u003e\n\u003cp\u003eThe iMGs were replated at the density of 50,000 to 70,000 cells per cm\u003csup\u003e2\u003c/sup\u003e 4-5 days before the experiment in the maturation medium. The cells were then treated with 100 ng/ml LPS (Merck Millipore) alone or with the combination of 50 ng/ml LPS and 15 ng/ml human IFN\u0026gamma; (Peprotech, Thermo Fisher Scientific) for 24h or 48h in iMG medium containing only IL-34 and M-CSF but no other cytokines.\u003c/p\u003e\n\u003cp\u003e1.3. Soluble A\u0026beta;42 treatment\u003c/p\u003e\n\u003cp\u003eHuman A\u0026beta; (1-42 trifluoroacetate, Bachem) was solubilized completely using 1,1,1,3,3,3-Hexafluoro-2-propanol (HIFP). After complete evaporation of HIFP using SpeedVac Vacuum concentrator, A\u0026beta; was reconstituted in dimethyl sulfoxide (DMSO) at a final concentration of 2.5 mM and sonicated for 10 min in the water bath sonicator.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThen A\u0026beta; was diluted to 100 \u0026mu;M concentration in cold phosphate-buffered saline Dulbecco\u0026rsquo;s phosphate-buffered saline (D-PBS; Thermo Fisher Scientific) and incubated for three days at RT. The endotoxin concentration (48 EU/ml) of the 100 \u0026mu;M A\u0026beta;42 was quantitatively measured by using ToxinSensorTM Chromogenic LAL Endotoxin Assay Kit (GenScript, Cat L00350C) according to the manufacturer\u0026rsquo;s instructions. Then A\u0026beta;42 was subsequently added to the cells at final concentration of 200 nM and incubated for 48 h at 37 \u0026deg;C before harvesting the cells and media.\u003c/p\u003e\n\u003cp\u003eFor Western blot (WB), the iMGs were maturated on Matrigel-coated (1:100) 6-well plates at density of 47,000 cells per cm\u003csup\u003e2\u003c/sup\u003e for 4 days. The treatment was started 48 hours before collection by replacing half of the old media with fresh iMG medium containing only IL-34 and M-CSF cytokines with or without soluble A\u0026beta;42 oligomers. For one E4/E4 cell line, rapamycin was given at a final concentration of 100 nM 24 h before collection. On a day of collection, bafilomycin-treated cells were incubated for 3 h at 37\u0026deg;C with bafilomycin A1 (Lysosomal Activity Assay Kit ab234622, Abcam), diluted according to the manufacturer\u0026rsquo;s instructions) before lysing the cells.\u003c/p\u003e\n\u003cp\u003e1.4.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp; L-leucyl-L-leucine methyl ester (LLOMe) treatment\u003c/p\u003e\n\u003cp\u003eFor studying the lysosomal membrane permeabilization by the LLOMe treatment assay, the cells were plated at a density of 45,500 cells per cm\u003csup\u003e2\u003c/sup\u003e onto coverslips coated with Matrigel (1:100). On the treatment day, H-Leu-Leu-OMe Hydrochloride (LLOMe) (#6491-83-4, Santa Cruz Biotechnology) was dissolved in DMSO, old media was removed from the cells and 250 \u0026mu;l of fresh iMG medium without cytokines supplemented with DMSO (vehicle) or 200 \u0026mu;M LLOME was added on top of the cells. The iMGs were incubated for 2h at 37\u0026deg;C before fixation with 4% formaldehyde in D-PBS supplemented with 0.9 mM CaCl\u003csub\u003e2\u003c/sub\u003e and 0.5 mM MgCl\u003csub\u003e2\u003c/sub\u003e at RT for 20 min.\u003c/p\u003e\n\u003cp\u003e1.5. Immunocytochemistry\u003c/p\u003e\n\u003cp\u003eThe iMGs were permeabilized and unspecific binding sites blocked with 0.3% Triton X-100 in 5% normal goat serum in D-PBS at RT for 1h. The iMGs were incubated with primary antibody (Supplementary materials, Table 2) in 5% normal goat serum in D-PBS at 4\u0026deg;C overnight following secondary antibody incubation (Supplementary materials, Table 2) at RT for 1 h. Nuclei were visualized by DAPI (Merck Millipore) staining at RT for 5 min and the coverslips were mounted with Fluoromount-G Mounting Medium (Thermo Fisher Scientific). LGALS1 primary antibody was a generous gift from Prof. P. Laakkonen, University of Helsinki. The images of LGALS1-stained cells were acquired with Zeiss LSM980 confocal microscope with C-Apochromat 63x/1.20 W Korr UV VIS IR objective\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eLGALS1 puncta were quantified with Fiji ImageJ v. 1.53 software using the Gaussian blur filter and the difference of Gaussians. The number of puncta in the image was normalized by the number of cell nuclei. Three images per iPSC line per treatment were quantified.\u003c/p\u003e\n\u003cp\u003e1.6.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp; Reverse transcription quantitative real-time PCR (RT-qPCR) for \u003cem\u003ein vitro\u003c/em\u003e iMGs\u003c/p\u003e\n\u003cp\u003eRNA was isolated by using Qiagen RNeasy Mini Kit (#74106, Qiagen) according to manufacturer\u0026rsquo;s instructions. cDNA was synthetized from isolated RNA by using Maxima reverse transcriptase enzyme (#EP0742, Thermo Fisher Scientific) according to manufacturer\u0026rsquo;s instructions. The expression levels of genes of interest were measured by using Maxima Probe/ROX qPCR Master Mix (#11813923, Thermo Fisher Scientific) and the Taqman primers listed in Supplementary materials, Table 3 on Bio-Rad CFX96 Real-Time System (Bio-Rad). The relative mRNA expression results were normalized to the \u0026Delta;C\u003csub\u003eT\u003c/sub\u003e averages of two housekeeping genes \u003cem\u003eGAPDH\u003c/em\u003e and \u003cem\u003eACTB\u003c/em\u003e using 2\u003csup\u003e-\u0026Delta;\u0026Delta;CT\u003c/sup\u003e method.\u003c/p\u003e\n\u003cp\u003e1.7.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp; Cell Mito Stress mitochondrial function assay\u003c/p\u003e\n\u003cp\u003eThe Seahorse XF Cell Mito Stress Test (Agilent) was used to measure the key parameters of the mitochondrial function in the cells. The manufacturer\u0026rsquo;s instructions were followed for the workflow of the experiment. Briefly, the cells were plated 40,000 cells per well in 200 \u0026mu;l maturation medium one week before the experiment, and half of the medium was replaced with a fresh medium every other day. On the day of the experiment, the Seahorse XF Assay medium was prepared by supplementing the Seahorse DMEM medium with Glutamax (Gibco, Thermo Fisher Scientific) to a final concentration of 2 mM. The cells were rinsed with 180 \u0026mu;l of Seahorse XF medium followed by the addition of Seahorse XF medium to a final volume of 180 \u0026mu;l. The cells were incubated in a non-CO\u003csub\u003e2\u003c/sub\u003e incubator at 37\u0026deg;C for 1 h before running on the XFe96 Analyzer (Agilent). At the beginning of the assay, glucose and sodium pyruvate (Gibco) were added by the XFe96 Analyzer to cells to final concentrations of 10 mM and 1 mM, respectively. Next, modulators of the electron transport chain all 1 \u0026mu;M were injected in the following order: oligomycin (Cayman Chemical) to inhibit ATP synthase and determine ATP production of the cells, Carbonyl cyanide-4 (trifluoromethoxy) phenylhydrazone (FCCP) (Cayman Chemical) to collapse the proton gradient and disrupt the mitochondrial membrane potential and to determine the maximal and spare respiratory capacity of the cells, a mixture of rotenone (Cayman Chemical) and antimycin a (Merck Millipore) to inhibit complexes I and III and to determine nonmitochondrial respiration of the cells. Oxygen consumption rate (OCR) was directly measured by XFe96 Analyzer during the assay. Results were normalized by the cell confluence analyzed by IncuCyte S3 at the Biomedicum Stem Cell Center, University of Helsinki, before the beginning of the assay and the key parameters of the mitochondrial function of the cells were calculated using Seahorse Wave Software and exported to Excel.\u003c/p\u003e\n\u003cp\u003e1.8.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp; Glycolysis Stress Test\u003c/p\u003e\n\u003cp\u003eThe Agilent Seahorse XF Glycolysis Stress Test was used to measure the glycolytic function of the cells, and it was performed simultaneously with the Agilent Seahorse XF Cell Mito Stress Test. Extracellular acidification rate (ECAR) was directly measured by the XFe96 Analyzer during the assay. The manufacturer\u0026rsquo;s instructions were followed for the workflow of the experiment.\u0026nbsp;First, glucose and sodium pyruvate were injected by XFe96 Analyzer on cells to final concentrations of 10 mM and 1 mM, respectively. Glucose was partially catabolized by the cells through the glycolytic pathway to pyruvate, leading to a rapid increase in ECAR, which was reported as glycolysis under basal conditions. Next oligomycin was injected on cells to inhibit ATP synthase and to shift the energy production to glycolysis. The following increase in ECAR was used to determine the cellular maximum glycolytic capacity. The obtained ECAR values were normalized to the cell confluence assessed by IncuCyte S3, and the key parameters of the glycolytic function of the cells were calculated using Seahorse Wave Software and exported to Excel.\u003c/p\u003e\n\u003cp\u003e1.9.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp; Cytokine quantification\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMedia were collected and centrifuged at 16,000 G 10 min 4 \u0026deg;C to remove debris. The cells were lysed using\u0026nbsp;RIPA Lysis and Extraction Buffer (#89900) supplemented with protease (#A32955) and phosphatase (#A32957) inhibitors (all from Thermo Fisher Scientific). The protein concentration was measured using BCA kit (#10741395, Thermo Fisher Scientific). The media and lysates were stored at -80 \u0026deg;C until analysis.\u003c/p\u003e\n\u003cp\u003eThe levels of human TNF\u0026alpha; (tumor necrosis factor alpha), CCL5 (C-C motif chemokine ligand 5), CCL3 (C-C motif chemokine ligand 5), IL6 (interleukin-6), and IL8 (interleukin-8) in the media, were measured using the mixture of corresponding Cytometric Bead Array (CBA) Flex sets and Human Soluble Protein Master Buffer Kit (both from BD Biosciences) according to manufacturer\u0026rsquo;s instructions. The samples were analyzed using the BD Accuri C6 Plus flow cytometer with BD CSampler Plus software (BD Biosciences) at the Biomedicum Flow Cytometry Core Facility, University of Helsinki. Mean PE-Height fluorescence intensity values were used to construct the standard curves. Concentration values were derived from standard curves using log-log regression and normalized to protein concentration in cell lysates.\u003c/p\u003e\n\u003cp\u003e1.10.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Western Blot\u003c/p\u003e\n\u003cp\u003eTo study the autophagic flux in basal conditions, the iMGs were maturated on Matrigel-coated (1:200) 12-well plates at 200,000 cells per well for 5 days. On the day of the collection, the cells were treated with either rapamycin only at a final concentration of 100 nM for 6 h, bafilomycin A1 only (Lysosomal Activity Assay Kit ab234622, Abcam, diluted according to the manufacturer\u0026rsquo;s instructions) for 3h or a combination of rapamycin (100 nM) and bafilomycin A1 for 6 h before collecting the cells.\u003c/p\u003e\n\u003cp\u003eThe cells were lysed with RIPA Lysis and Extraction Buffer (#89900) supplemented with protease (#A32955) and phosphatase (#A32957) inhibitors (all from Thermo Fisher Scientific). The protein concentration was measured using BCA kit (#10741395, Thermo Fisher Scientific) and the proteins were denatured by boiling in 4xSample Buffer (62.5mM Tris-HCl pH6.8, 2.5% SDS, 0.002% Bromophenol blue, 5% \u0026beta;-mercaptoethanol and 10% glycerol). Total amount of 5-10 \u0026mu;g of protein were loaded and separated on a 4-20% Mini-PROTEAN\u0026reg; TGX\u0026trade; Gels (#4561094, Bio-Rad) and transferred to polyvinylidene fluoride (PVDF) membranes using the Trans-Blot Turbo Transfer system (Bio-Rad). The membranes were blocked in 5% fat-free milk in TBS-0.05% Tween (TBST) buffer at RT for 1h and incubated overnight with the primary antibody diluted in 5% bovine serum albumin \u0026ndash; 0,02% Na azide in TBST at 4\u0026deg;C. The following day the membranes were washed and incubated with the horseradish peroxidase (HRP)-conjugated secondary antibodies for 1h at RT. After washes the chemiluminescence signal was detected by using ECL Plus (#32132) or ECL (#32106) Western Blotting Substrate (both Thermo Fisher Scientific) and G:BOX Chemi XX6 (Syngene) imaging system. ImageJ software was used for semi-quantitive analysis of the membranes.\u003c/p\u003e\n\u003cp\u003e1.11.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Lysosomal activity\u003c/p\u003e\n\u003cp\u003eFor assaying lysosomal activity, we used the Lysosomal Intracellular Activity Assay Kit (#ab234622, Abcam) and the assay was conducted according to the protocol provided by the manufacturer. Briefly, the iMGs were plated on 12-well plates at a density of 57,000 iMGs per cm\u003csup\u003e2\u003c/sup\u003e and maturation was started 3-5 days prior to the experiment. One day before the experiment half of the media was replaced with iMG medium containing only IL-34 and M-CSF cytokines. On the day of the experiment the control cells and the cells to be treated with bafilomycin A1 were pelleted by centrifuging the 12-well plates at 300xg for 5 min at RT. After centrifugation the old media was removed and replaced by fresh media with or without bafilomycin A1 and the cells were incubated 1h at 37\u0026deg;C with 5% CO\u003csub\u003e2\u003c/sub\u003e. After incubation the cells were pelleted as above and after centrifugation the old media was removed and 500\u0026nbsp;\u0026mu;l of new media supplemented with Self-Quenched Substrate provided by the kit (15 \u0026mu;l per 1ml of media) with or without bafilomycin A1 was added on top of the cells. The cells were then incubated 1h at 37\u0026deg;C, 5% CO\u003csub\u003e2,\u003c/sub\u003e before removing all the media and adding 1ml of ice-cold 1% bovine serum albumin in D-PBS. The cells were scraped off, washed with ice-cold 1xAssay buffer and resuspended to 500 \u0026mu;l of D-PBS. The mean fluorescence intensity (MFI) in FITC channel was analyzed using the BD Accuri C6 Plus flow cytometer.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.12.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Endocytosis\u003c/p\u003e\n\u003cp\u003eFor pHrodo dextran endocytosis assays, the cells were plated at a density of 62,500 cells per cm\u003csup\u003e2\u003c/sup\u003e into a black-walled 96-well imaging plate in 100\u0026mu;l iMG medium containing the maturation factors (CD200 and CX3CL1) 2-3 days before performing the assay. One day before the experiment half of the media was removed and 50 \u0026mu;l of fresh media containing treatments (final concentrations 50 ng/ml LPS and 15 ng/ml IFN\u0026gamma;) were added on top of cells. On a day of the assay, Invitrogen\u003csup\u003eTM\u003c/sup\u003epHrodo\u003csup\u003eTM\u003c/sup\u003e Red (#10361) or Green (#P35368) 10 kDa Dextran conjugates were dissolved in D-PBS in a final concentration of 0.1mg/ml. After removing 20 \u0026mu;l of old media from the wells, added 20 \u0026mu;l of conjugate suspension on top of the cells to a final concentration of 16,7-20 \u0026mu;g/ml. The endocytosis assay was performed using IncuCyte S3 live cell imaging system (Sartorius) at the Biomedicum Stem Cell Center core facility, University of Helsinki. The cells were imaged first every 30 minutes and after 4.5 h every 1 h for 20 h and the integrated intensity of the fluorescence signal was normalized to cell confluence assessed by IncuCyte S3 before adding the pHrodo dextran conjugates. In case of apilimod treatment, the treatments for the control and apilimod treated cells were added on the day of the assay by removing 20 \u0026mu;l of the old media and adding 20 \u0026mu;l of fresh media with DMSO as a vehicle or apilimod in a final concentration of 0.683 \u0026mu;M before the addition of the conjugate suspension on top of the cells.\u003c/p\u003e\n\u003cp\u003e1.13. Non-targeted metabolomics\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSample preparation.\u0026nbsp;\u003c/em\u003eNon-targeted metabolomics analysis was run by the company Afekta Technologies, Kuopio, Finland (www.afekta.com). The cell pellets, containing 560,000 to 600,000 cells each, were dissociated with 60 \u0026mu;l of Milli-Q water at RT. The suspension was sonicated for 5 min at RT to homogenize the cells, after which 240 \u0026mu;l of cold 80% aqueous methanol was immediately added to stop any remaining cellular activity and to extract the metabolites. The samples were then vortexed for 10 s at RT and let settle down for 5-10 min. The centrifugation was performed at 13 000 rpm and 4 \u0026deg;C for 5 min. Immediately after centrifugation, the supernatant was collected carefully without disturbing the pellet with a 1 ml syringe and injected into an HPLC vial with a glass insert. The samples were stored at \u0026ndash;20 \u0026deg;C until analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLC\u0026ndash;MS analysis.\u003c/em\u003eThe samples were analyzed by liquid chromatography\u0026ndash;mass spectrometry, consisting of a Vanquish Flex UHPLC system (Thermo Fisher Scientific) coupled with a high-resolution Orbitrap mass spectrometer (Q Exactive Focus, Thermo Fisher Scientific). The analytical method has been described in detail previously [32, 33]. In brief, a Zorbax Eclipse XDB-C18 column (2.1 \u0026times; 100 mm, 1.8 \u0026mu;m; Agilent Technologies) was used for the reversed-phase (RP) separation and an Aqcuity UPLC BEH amide column (Waters) for the hydrophilic interaction chromatography (HILIC) separation. After each chromatographic run, the ionization was carried out using jet stream electrospray ionization (ESI) in the positive and negative mode, yielding four data files per sample. The collision energies for the MS/MS analysis were selected as 10, 20 and 40 V, for compatibility with spectral databases.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData analysis.\u003c/em\u003ePeak detection and alignment were performed in MS-DIAL ver. 4.60 [34]. For the peak collection, \u003cem\u003em/z\u0026nbsp;\u003c/em\u003evalues between 50 and 1500 and all retention times were considered. The amplitude of the minimum peak height was set at 120000. The peaks were detected using the linear weighted moving average algorithm. For the alignment of the peaks across samples, the retention time tolerance was 0.05 min, and the \u003cem\u003em/z\u0026nbsp;\u003c/em\u003etolerance was 0.015 Da.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe differential features between the genotypes were detected using featurewise linear mixed models, where feature levels were predicted by genotype and cell ID was used as a random effect. The mixed models were fitted separately for samples in each of the two treatments. Benjamini\u0026ndash;Hochberg false discovery rate (FDR) correction was performed on the \u003cem\u003ep\u003c/em\u003e-values to account for multiple tests. All analyses were conducted with R version 3.6.3 and notame version 0.0.6.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompound identification.\u003c/em\u003eThe chromatographic and mass spectrometric characteristics (retention time, exact mass, and MS/MS spectra) of the significantly differential molecular features were compared with entries in an in-house standard library and publicly available databases, such as METLIN and HMDB, as well as with published literature. For molecular features without a match in publicly available spectral databases, a secondary annotation attempt was performed in MS-FINDER software [35] by calculating the molecular formula based on the isotopic pattern and exact mass and comparing the experimental MS/MS (if available) with \u003cem\u003ein silico\u0026nbsp;\u003c/em\u003eMS/MS spectra generated from databases of known natural and other compounds.\u003c/p\u003e\n\u003cp\u003e1.14.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Proteomics\u003c/p\u003e\n\u003cp\u003eThe cells were maturated on original 6-well plates for 4 days prior to the experiment. Further, the cells were treated for 48 h with 50 ng/ml LPS and 15 ng/ml IFN\u0026gamma; in iMG medium supplemented only with IL-34 and M-CSF or left untreated. Then the cells were washed with 1 ml of ice-cold D-PBS and harvested by scraping and centrifuging at 1000 G for 5 min at 4 \u0026deg;C. The cells were then washed one more time with ice-cold D-PBS, and pellets were frozen on dry ice and kept at -80 \u0026deg;C until analysis.\u003c/p\u003e\n\u003cp\u003eSamples were lysed in STET lysis buffer (1% (v/v) Triton X-100, 150 mM NaCl, 2 mM EDTA, 50 mM TrisHCl pH 7.5). Cell debris and undissolved material was removed by centrifugation at 16,000 g at 4\u0026deg;C for 10 min. The protein concentration was estimated using the Pierce 660 nm assay (Thermo Fisher Scientific). A modified protocol for single-pot solid-phase enhanced sample preparation (SP3) was applied. In brief, 15 \u0026micro;g of protein lysate MgCl\u003csub\u003e2\u003c/sub\u003e was added to a final concentration of 10 mM. DNA was digested using 25 U of Benzonase (Sigma-Aldrich) per sample at 37\u0026deg;C for 30 minutes. Proteins were reduced by adding dithiothreitol (Biozol) to a final concentration of 10 mM, followed by incubation for 30 minutes at 37\u0026deg;C. For cysteine alkylation, iodoacetamide (Sigma-Aldrich) was added to a final concentration of 40 mM and samples were incubated 30 minutes at roo temperature in the dark. The reaction was quenched with an additional dose of dithiothreitol. Proteins were bound to 200 \u0026micro;g of a 1:1 mixture of hydrophilic and hydrophobic magnetic Sera-Mag SpeedBeads (Cytiva) by adding ethanol (Sigma-Aldrich) to a final concentration of 80% (v/v) and mixing on a thermomixer (Eppendorf) for 30 minutes at RT. The beads were washed four times with 200 \u0026micro;L of 80% ethanol using a Dynamag-2 magnetic rack (Thermo Fisher Scientific). For proteolytic digestion, 190 ng of LysC and 190 ng of trypsin (Promega) were added in 40 \u0026micro;L of 50 mM ammonium bicarbonate, followed by 16 hours of incubation at RT. The supernatants were filtered using 0.22 \u0026micro;m spin-filters (Costar Spin-X, Corning) and then dried via vacuum centrifugation. The dried peptides were re-dissolved in 20 \u0026micro;L of 0.1% formic acid. The peptide concentration after digestion was quantified using the Qubit protein assay (Thermo Fisher Scientific). An amount of 350 ng of peptides per sample were subjected to the LC-MS/MS proteomic analyses on a nanoElute system (Bruker Daltonics) which was online coupled with a timsTOF pro mass spectrometer (Bruker Daltonics) equipped with an column oven. An amount of 350 ng of Peptides were separated on a 15 cm (75 \u0026micro;m ID) column self-packed with ReproSil-Pur 120 C18-AQ resin (1.9 \u0026micro;m, Dr. Maisch GmbH) using a 120 min long binary gradient of water and acetonitrile supplemented with 0.1% formic acid at a flow rate of 300 nL/min and a column temperature of 50\u0026deg;C.\u003c/p\u003e\n\u003cp\u003eData independent acquisition Parallel Accumulation Serial Fragmentation (DIA-PASEF) was used. One MS1 full scan was followed by 34 sequential DIA windows with 26 m/z width for peptide fragment ion spectra with an overlap of 1 m/z covering a scan range of 350 to 1200 m/z. The ramp time was fixed to 100 ms and 2 windows were scanned per ramp resulting in a total cycle time of 1.9 s.For protein label free quantification (LFQ), the LC-MS/MS raw data was analysed with the software DIA-NN [36] (version 1.8) using a library-free search against a canonical one-protein gene database of Homo sapiens from UniProt (download: 2022-01-12, 20600 entries) supplemented with a contaminants database from Maxquant (240 entries) [37]. Trypsin was defined as protease and maximum 2 missed cleavages were allowed. Acetylation of protein N-termini and methionine oxidation were defined as variable modifications whereas carbamidomethylation of cysteines was defined as fixed modification. Tolerances for mass accuracy and ion mobility were automatically optimized by DIA-NN. The false discovery rates for precursors and proteins were set to 1%.\u003c/p\u003e\n\u003cp\u003eFor statistical analysis, the software Perseus (v 1.6.2.3) [38] was used. Protein LFQ values were accepted on the basis of at least 2 peptides. Contaminants were removed and protein LFQ were log2 transformed. A Student\u0026rsquo;s ttest was applied between the different groups for statistical testing of abundance differences. A permutation-based FDR correction for multiple hypotheses was applied with a p-value of 0.05 and s0 of 0.1 [39]. The FDR thresholds are visualized as hyperbolic curves.\u003c/p\u003e\n\u003cp\u003eThe differentially expressed protein data that met the \u003cem\u003ep\u003c/em\u003e-value \u0026lt; 0.05 and fold change \u0026ge; 2 (in both directions) cutoffs were further analyzed using QIAGEN Ingenuity Pathway Analysis (IPA) as described [40]. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.15.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Statistics\u003c/p\u003e\n\u003cp\u003eStatistical analysis was done using GraphPad Prism 9.2.0 (Insight Partners, New York, NY, USA) using Student\u0026rsquo;s t-test, Mann-Whitney non-parametric test or repeated measures two-way ANOVA, with \u0026Scaron;id\u0026aacute;k\u0026rsquo;s-corrected posthoc tests. Statistical significance was assumed at p \u0026lt; 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e3.1. Basal levels of lipidated LC3 and macropinocytosis are reduced in E4/E4 iMGs\u003c/p\u003e\n\u003cp\u003eTo generate human iMGs, we used a protocol adapted from previously published studies [29, 30]. E3/E3 and E4/E4 iMGs expressed similar levels of microglial marker genes \u003cem\u003eP2RY12\u003c/em\u003e (purinergic receptor P2Y12) and \u003cem\u003eTREM2\u003c/em\u003e (Supplementary Fig. 2B).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAutophagy is commonly studied by analyzing the microtubule-associated protein light chain 3 (LC3), which is conjugated to phosphatidylethanolamine (LC3-II), using WB. During autophagy, cytosolic LC3-I is converted into lipidated LC3-II, which associates with nascent phagophore membranes that enclose intracellular material to form autophagosomes. Under basal conditions, E4/E4 iMGs exhibited significantly lower LC3-II levels compared to E3/E3 cells (Figure 1A, B). As expected, blocking autophagic flux by inhibiting lysosomal acidification with bafilomycin A led to increased LC3-II:LC3-I ratio compared to the basal levels (Figure 1 C, D), but there was no significant difference between the genotypes. Similarly, treatment with rapamycin, an inhibitor of the mTORC1 complex and a well-known autophagy inducer, did not reveal any significant differences between the genotypes (Figure 1 C, E). Collectively, these results suggest that, compared to E3/E3 iMGs, E4/E4 iMGs exhibit reduced basal levels of LC3-II but no significant differences in basal or rapamycin-induced autophagic flux, indicating that autophagy is not affected by the \u003cem\u003eAPOE\u003c/em\u003e genotype.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSince total levels of LC3 and many other endolysosomal proteins can be transcriptionally regulated by TFEB, the master regulator of lysosomal biosynthesis [41, 42], we assessed the mRNA levels of \u003cem\u003eMAP1LC3B\u003c/em\u003e, the more abundant of two genes encoding for LC3, and two abundant lysosomal endopeptidases, \u003cem\u003eCTSD\u003c/em\u003e (cathepsin D) and \u003cem\u003eCTSB\u003c/em\u003e (cathepsin B). RT-qPCR analysis showed that \u003cem\u003eCTSD\u003c/em\u003e was significantly downregulated in E4/E4 iMGs, while there was no difference in \u003cem\u003eCTSB\u003c/em\u003e or \u003cem\u003eMAP1LC3B\u003c/em\u003e expression between the genotypes (Figure 1F), suggesting that LC3 protein levels were not primarily regulated by transcription.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSince cathepsins play an essential role in lysosomal degradation, we further analyzed lysosomal activity in iMGs using flow cytometry with a self-quenched substrate and found that E4/E4 iMGs exhibited significantly lower lysosomal degradation activity compared to E3/E3 cells (Figure 1G-H). Bafilomycin-treated cells served as a negative control (Figure 1I). Lysosomal degradation activity can be influenced by the efficiency of substrate uptake into endosomes. Additionally, lipidated LC3-II associates not only with autophagosomes but also with endosomes, macropinosomes, and phagosomes, where it plays a role in vesicle recycling\u0026nbsp;[43, 44]. Therefore, we next investigated endocytosis in iMGs. To assess pinocytosis (fluid-phase endocytosis), we added pHrodo-conjugated dextran (MW 10 kDa) and monitored intracellular fluorescence over 20 h using the IncuCyte live imaging system (Figure 1 J, K). Under basal conditions, pinocytosis was significantly reduced in E4/E4 iMGs compared to E3/E3 iMGs (two-way repeated measures ANOVA, time x genotype p = 0.01; Figure 1J, L). Moreover, when endosome maturation and degradation were blocked by apilimod, a significant accumulation of dextran was observed over 24 h, irrespective of the \u003cem\u003eAPOE\u003c/em\u003e genotype (repeated measures ANOVA, time x treatment p \u0026lt; 0.001, Figure 1M). Interestingly, the \u003cem\u003eAPOE\u003c/em\u003e genotype did not significantly affect the uptake of pHrodo-conjugated zymosan-coated beads (Supplementary Fig. 2 C-E) or fibrillar Aβ42 (Supplementary Fig.2 F, G). Collectively, these findings indicate that E4/E4 iMGs exhibit reduced endocytosis under basal conditions but no alteration in the rate of phagocytosis.\u003c/p\u003e\n\u003cp\u003e2.2. APOE 4/4 microglia exhibit reduced metabolic flexibility and dysregulated amino acid metabolism\u003c/p\u003e\n\u003cp\u003ePinocytosis serves as a mechanism to scavenge nutrients and promote cell growth in low-nutrient conditions\u0026nbsp;[45]. The mitochondrial stress test, performed using Agilent Seahorse XFe96 analyzer, revealed that E4/E4 iMGs have similar basal respiration and ATP production but lower maximal respiration capacity compared to E3/E3 cells (Figure 2 A, B). The finding aligns with previous studies suggesting that E4/E4 iMGs may have a reduced ability to rapidly enhance mitochondrial activity in response to an acute increase in energy demand [26]. No significant differences between the genotypes were observed in glycolysis or glycolytic capacity (Figure 2 C, D).\u003c/p\u003e\n\u003cp\u003eTo investigate iMG metabolism under metabolic stress, we induced strong inflammation using a combination of bacterial lipopolysaccharide (LPS) and interferon-gamma (IFNγ) (LPS/IFNγ). As expected, this inflammatory stimulation triggered the secretion of proinflammatory cytokines and chemokines, including TNFα, CCL5, CCL3, IL6, and IL8 (Figure 2 E). To meet the increased energy demand during inflammation, microglia must significantly enhance their metabolic rate. Accordingly, LPS/IFNγ stimulation induced glycolysis, glycolytic capacity, and proton leak in mitochondria, with no significant effect of the \u003cem\u003eAPOE\u003c/em\u003e genotype (Figure 2 F, G). However, when glucose and pyruvate were unavailable, the inflammatory-stimulated iMGs displayed enhanced glutamine-dependent mitochondrial respiration. This effect was less pronounced in E4/E4 iMGs (Figure 2 G), demonstrating reduced metabolic flexibility of E4/E4 iMGs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhen iMGs were subjected to 48-h LPS/IFNγ inflammatory stimulation and analyzed using un-targeted metabolomics, principal component analysis (PCA) of normalized data revealed two distinct clusters corresponding to unstimulated and stimulated cells, confirming that inflammatory stimulation induced metabolic reprogramming in iMGs (Supplementary Fig. 3 A, B). Figure 2 H highlights selected metabolites altered by LPS/IFNγ treatment, including amino acids, fatty acids, and glucose metabolites. While \u003cem\u003eAPOE\u0026nbsp;\u003c/em\u003egenotypes did not cause clear clustering of the samples, a total of 50 molecular features were differentially produced (q-value \u0026lt; 0.1) between the E3/E3 and E4/E4 iMGs in the unstimulated group and 132 molecular features in the stimulated group. Ultimately, nine significantly altered metabolites were reliably identified: L-glutamine and plasmalogen PC O-38:7 under basal conditions (Figure 2 H; Table S1) and seven metabolites (L-tryptophan, L-methionine, L-kynurenine, phenylacetylglycine, tripeptide Pro-Ala-Arg, adenine, and pyridoxine) in the stimulated group. \u0026nbsp;All identified metabolites were elevated in E4/E4 iMGs, except for plasmalogen PC O-38:7 (Figure 2H). The exact identity of this plasmalogen could not be determined from the data alone; however, in mammalian cells, the most likely candidate is PC(P-16:0/22:6(4Z,7Z,10Z,13Z,16Z,19Z)), with the longer fatty acid being docosahexaenoic acid (DHA) [46]. Since inflammation induces the hydrolysis of plasmalogens to generate pro- or anti-inflammatory mediators [47], a lower basal level of plasmalogen in E4/E4 iMGs may indicate a chronic inflammatory state. Collectively, our metabolomics results demonstrate that E4/4 iMGs exhibit dysregulated amino acid and phospholipid metabolism.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2.3. \u0026nbsp;Inflammation induces lysosomal dysfunction in iMG\u003c/p\u003e\n\u003cp\u003eTo verify that LPS/IFNγ treatment changes the levels of key proteins regulating amino acid metabolism, we conducted proteomic analysis of five control E3/E3 iMG lines (Supplementary Fig. 3C). In line with the metabolomics data and existing literature [48], we detected an upregulation in the levels of tryptophan-metabolizing proteins (indoleamine 2,3-dioxygenase (IDO)1, kynurenine 3-monooxygenase (KMO) and kynureninase (KYNU)) following the 48h LPS/IFNγ stimulation (Table S2). We also observed increased levels of some proteins involved in glutamine uptake (SLC1A5), synthesis (GLUL) and hydrolysis (ASNS) (Table S2). \u0026nbsp;When comparing the proteome of two (isogenic to each other)E4/E4 lines with E3/E3 lines, no significant differences (threshold 2-fold change, p \u0026lt; 0.05) were observed in the levels of the proteins involved in the tryptophan or glutamine metabolism (Tables S4, S5).\u003c/p\u003e\n\u003cp\u003eThe IPA analysis showed that in addition to common inflammatory pathways, such as interferon alpha/beta signaling, interferon gamma signaling and inflammasome pathway, LPS/IFNγ treatment induced PI3K/AKT signaling and autophagy pathways (Figure 3 A). The autophagy pathway included LC3 (MAP1LC3A/B) and SQSTM1/p62, a commonly recognized marker of impaired autophagic flux [49] (Figure 3B, Table S3). We also observed increased levels of cholesterol transfer protein GRAMD1A (Figure 3B, Table S2), which was recently identified as a regulator of autophagosome biogenesis [50]. In contrast, inflammatory stimulation decreased the levels of several lysosomal proteases, including cathepsin D (CTSD), lysosomal acid lipase (LIPA), lysosomal alpha-mannosidase (MAN2B1), and lysosomal pro-X carboxypeptidase (PRCP) (Figure 3B, Table S2), suggesting that strong inflammatory activation may impair lysosomal degradation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo validate the alterations identified by proteomic analysis, immunoblotting was done using the samples from an independent experiment. Consistent with the proteomics data, this WB analysis confirmed that 48-h stimulation with LPS/IFNγ strongly increased the accumulation of LC3-II as well as glutamine synthetase (GLUL), although the protein levels were not affected by the \u003cem\u003eAPOE\u003c/em\u003e genotype (Figure 3 C, D). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo investigate whether the differences in protein levels were determined by transcriptional regulation, we performed RT-qPCR analysis on iMGs treated with LPS for 24 h. In agreement with the proteomics data, \u003cem\u003eCTSD\u003c/em\u003e mRNA expression was significantly reduced following the LPS treatment (Figure 3 E). In contrast, \u003cem\u003eCTSB\u003c/em\u003e mRNA was significantly upregulated by both LPS alone (two-way ANOVA, p = 0.015; Figure 3 E) and LPS/IFNγ stimulation (two-way ANOVA, p = 0.015; Figure 3 F), which in combination with lower protein levels at 48h suggested increased degradation or leakage of cathepsin B. The glutamate transporter SLC1A2 has recently been implicated in inflammatory responses in macrophages by sustaining macropinocytosis and mTORC1 activation [51]. While our iMGs did not express \u003cem\u003eSLC1A2\u003c/em\u003e under basal condition, the expression was upregulated in response to LPS stimulation and was significantly stronger in E4/E4 iMGs compared to E3/E3 iMGs (Figure 3 E). In contrast, there was no \u003cem\u003eAPOE\u003c/em\u003e genotype effect on the mRNA levels of \u003cem\u003eIL1B\u003c/em\u003e (Figure 3 E). LPS/IFNγ stimulation increased the rate of pinocytosis in both E3/E3 and E4/E4 iMGs (Figure 3 G, H), thereby placing a greater burden on the endo-lysosomal system.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2.4.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp; APOE 4/4 iMGs exhibit higher lysosomal membrane permeabilization upon Aβ42 exposure\u003c/p\u003e\n\u003cp\u003eTo determine whether comparable results could be achieved using an alternative inflammatory stimulus, more relevant for AD, we treated iMGs for 48 h with soluble Aβ42 oligomers containing 0.1 EU endotoxin per μg peptide. \u0026nbsp;First, we measured cytokine secretion after Aβ42 treatment using CBA as above and found that iMGs of both genotypes secreted cytokines at levels comparable to those observed after LPS/IFNγ treatment (Figure 4 A).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurther, we analyzed SQSTM1/p62 levels by WB, and found that, similarly to\u0026nbsp;LPS/IFNγ stimulation, Aβ42 strongly increased intracellular p62 (p \u0026lt; 0.01), irrespective of the \u003cem\u003eAPOE\u003c/em\u003e genotype (Figure 4 B, C). Bafilomycin treatment did not further increase\u0026nbsp;SQSTM1/p62 levels, suggesting that\u0026nbsp;Aβ42 stimulation blocked lysosomal degradation. Interestingly, lysosomal-associated membrane protein 2 (LAMP-2), a key mediator of autophagosome-lysosome fusion [52, 53],\u0026nbsp;was unaffected by Aβ42 stimulation but was significantly reduced in E4/E4 iMGs (Figure 4 B, C). Since proteomic analysis comparing two (isogenic to each other) E4/E4 lines to E3/E3 lines revealed a downregulation of two other lysosomal proteins MFSD1 and GLMP in E4/E4 iMGs at basal conditions (Figure 3 B, Table S4), the overall lysosomal protein content may be reduced by E4/E4 genotype. Similarly to\u0026nbsp;SQSTM1/p62,\u0026nbsp;LC3-II levels were significantly increased following Aβ42 stimulation (p = 0.04), however, adding bafilomycin to Aβ42-stimulated iMGs did not result in a significant change (p = 0.27; Figure 4 D, E).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePhospho-NF-κB p65 (Ser536) is an active form of NF-κB (nuclear factor kappa B subunit p65), a key mediator of inflammation. As expected, Aβ42 stimulation significantly increased p-NF-κB p65 levels (p = 0.02; Figure 4 D, E). Interestingly, inhibition of lysosomal acidification with bafilomycin further increased p-NF-κB p65 in E3/E3 iMGs but not in E4/E4 iMGs, suggesting that lysosomal enzyme activity selectively affected the inflammatory response in E3/E3 iMGs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSince the accumulation of SQSTM1/p62 and LC3-II following Aβ42 exposure suggested impaired lysosomal degradation and elevated lysosomal stress, we next analyzed lysosomal membrane permeabilization (LMP) using the lysosomal galectin puncta assay [54]. As shown in Figure 4 F, G, the formation of galectin puncta, detected with galectin (LGALS)-1-specific antibody, was significantly higher in E4/E4 iMGs than in E3/E3 iMGs after Aβ42 exposure, indicating increased lysosomal leakage in E4/E4 iMGs. A two-hour treatment with LLOME served as a positive control (Figure 4 F, H). Interestingly, the levels of secreted IL8 significantly correlated with galectin puncta after Aβ42 stimulation, suggesting that lysosomal leakage exacerbated the inflammatory response (Figure 4 I). It has been demonstrated that IL8 production can be regulated by mTORC1 activity [55]. Since mTORC1 is a critical regulator of lysosomal biogenesis and autophagy [41, 56], we assessed its activity via WB by measuring phosphorylation of the S6 ribosomal protein (Ser235/236), a downstream component of mTORC1 signaling complex. Figures 4 J, K show that phosphorylated S6 levels were significantly higher in E4/E4 iMGs stimulated with Aβ42 as compared to E3/E3 iMGs, indicating increased mTORC1 activity in E4/E4 cells. Since mTORC1 can promote cell proliferation, we performed KI67 immunostaining to visualize proliferating cells. Aβ42 stimulation significantly increased cell proliferation; however, no effect of the \u003cem\u003eAPOE\u003c/em\u003e genotype was observed (Supplementary Fig. 3 D, E). As expected, treatment with the mTORC1 inhibitor rapamycin reduced NF-κB p65 phosphorylation [57] by half in an E4/E4 line (Fig. 4 L, M), suggesting that mTORC1 activity promoted inflammatory response in E4/E4 iMGs.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe ε4 isoform of ApoE is the most prevalent genetic risk factor for AD. In this study, E4/E4 iMGs showed diminished basal levels of pinocytosis and lipidated LC3 \u003cem\u003ein vitro\u003c/em\u003e. In macrophages and microglia, the primary function of constitutive pinocytosis is continuous environmental sampling for pathogens [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Additionally, pinocytosis has been shown to facilitate the uptake and clearance of soluble Aβ species [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Thus, E4/E4 iMGs may be less responsive to homeostatic perturbations and less efficient at clearing soluble waste, potentially contributing to impaired proteostasis in AD. However, we did not observe significant differences in the uptake of solid particles, such as zymosan-coated beads or fibrillar Aβ42. This suggests that the \u003cem\u003eAPOE\u003c/em\u003e genotype selectively affects fluid-phase endocytosis rather than phagocytosis. Inflammatory stimulation strongly increased autophagosome formation, pinocytosis and mTORC1 activity, while blocking autophagic flux and abolishing genotype-related differences. The blockade of the autophagic flux was further confirmed by elevated SQSTM1/p62 levels, indicating that inflammatory conditions override basal autophagic and endocytic differences between \u003cem\u003eAPOE\u003c/em\u003e genotypes.\u003c/p\u003e \u003cp\u003eBoth autophagic and endocytic pathways culminate in lysosomal degradation. Substrate overload can lead to lysosomal membrane permeabilization (LMP), allowing intralysosomal components such as cathepsins to be released into the cytoplasm, further impairing lysosomal protein degradation [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. LMP is a hallmark of lysosomal dysfunction, which has been implicated in neurodegeneration and chronic inflammation. Interestingly, we observed an increased number of LGALS1-positive puncta in Aβ42-stimulated E4/E4 iMGs, suggesting elevated LMP. Since damaged lysosomes are cleared by autophagy (lysophagy) [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e], an increased number of LGALS1 puncta may also indicate impaired lysophagy. LMP can further induce inflammasome activation in macrophages and microglia [\u003cspan additionalcitationids=\"CR63 CR64\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e], a process which can be triggered by the leakage of active cathepsin B from lysosomes into the cytosol [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. These findings suggest that \u003cem\u003eAPOE\u003c/em\u003e4/4 microglia exhibit heightened vulnerability to lysosomal leakage and associated inflammatory cascades, potentially contributing to chronic neuroinflammation in AD.\u003c/p\u003e \u003cp\u003eAlthough we did not directly assess inflammasome activation or cathepsin B activity in our study, we found a significant correlation between LMP and secreted IL8 (CXCL8), a major neutrophil chemokine known to be involved in AD [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e] and regulated by inflammasome activation [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Furthermore, we found that bafilomycin, an inhibitor of lysosomal acidification and protease activity, exhibited a proinflammatory effect in E3/E3 iMGs, but not in E4/E4 iMGs, indicating genotype-dependent differences in lysosomal regulation of inflammation. Additionally, we observed an upregulation of cathepsin B mRNA in LPS/IFNγ-stimulated E4/4 iMGs, while its protein levels were decreased. In human iPSC-derived macrophages, LMP has recently been linked to metabolic reprogramming in mitochondria [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e], and the LMP-induced changes in mitochondrial respiration and glycolysis were similar to those we observed in iMGs following LPS/IFNγ stimulation. These findings further support a role for LMP in driving inflammatory activation in E4/E4 iMGs, which may be mitigated by targeting lysosomal acidification.\u003c/p\u003e \u003cp\u003eOur results are consistent with previous studies in murine models, where prolonged exposure to Aβ42 resulted in the accumulation of autophagosomes, LMP, and cathepsin D leakage in murine microglial cell line [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. Although it has been shown before that E4/E4 potentiates LMP in neuroblastoma cells after Aβ treatment \u003cem\u003ein vitro\u003c/em\u003e [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e], our study is the first to demonstrate the effect of E4/E4 genotype on LMP in human microglia, which are central to late-onset AD pathophysiology.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eWe also observed elevated levels of amino acids, particularly L-glutamine, in E4/E4 iMGs, along with increased mRNA expression of the glutamate transporter \u003cem\u003eSLC1A2\u003c/em\u003e following inflammatory stimulation. Glutamine and glutamate metabolism are tightly linked. Glutaminase (GLS) catalyzes glutamine conversion into glutamate, thus facilitating its utilization in the TCA cycle and activating mTORC1 [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. In microglia/macrophages, M1 polarization and inflammasome activation require increased glutamine utilization in the TCA cycle [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. High levels of glutamine and leucine in the extracellular environment have been shown to stimulate protein synthesis, suppress autophagy, promote inflammatory responses via the mTORC1 pathway, and reduce lysosomal acidification [\u003cspan additionalcitationids=\"CR74 CR75 CR76 CR77\" citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. However, our E4/E4 iMGs exhibited lower, rather than higher, mitochondrial utilization of glutamine, as indicated by mitochondrial stress test results. This suggests that instead of enhanced glutamine-to-glutamate conversion, E4/E4 iMGs might have increased lysosomal glutamate efflux, sustaining mTORC1 activation [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Additionally, the elevated kynurenine levels detected in E4/E4 iMGs after LPS/IFNγ stimulation may have contributed to mTORC1 activation, as kynurenine has been shown to directly activate mTORC1 in human lymphocytes [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. These findings indicate that targeting mTORC1 signaling could be beneficial in mitigating inflammation in ApoE ε4-associated neurodegeneration.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eAlthough we did not detect \u003cem\u003eAPOE\u003c/em\u003e genotype-associated differences in basal autophagic flux, we found that E4/E4 iMGs exhibited lower levels of several key lysosomal markers, including cathepsin D and LAMP2, suggesting a reduced lysosomal content. Notably, LAMP2 overexpression in ischemic cardiomyocytes has been shown to restore autophagic flux, promote cathepsin trafficking, and mitigate lysosomal membrane permeabilization (LMP) [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. These results highlight the potential therapeutic relevance of enhancing lysosomal biogenesis in \u003cem\u003eAPOE\u003c/em\u003e4/4 carriers.\u003c/p\u003e \u003cp\u003eWe could not replicate previously reported glycolytic abnormalities in E4/E4 iMGs. Prior studies have reported conflicting data regarding aerobic glycolysis levels in E4/E4 iMGs. While Konttinen et al. [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] reported a significant decrease in glycolysis and glycolytic capacity, Victor et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] found upregulation of the glucose transporters GLUT1 (SLC2A1) and GLUT3, suggesting increased glycolysis. Additionally, a recent study of mouse E4/E4 microglia reported elevated aerobic glycolysis levels [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. Given that glycolysis is often linked to inflammation-driven metabolic reprogramming, its levels may be highly dependent on experimental conditions.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study provides new insights into ApoE ε4-mediated alterations in microglial lysosomal function, metabolism, and inflammation. We demonstrate that \u003cem\u003eAPOE\u003c/em\u003e4/4 microglia exhibit reduced basal endocytosis, heightened lysosomal membrane permeabilization, and increased susceptibility to inflammatory activation. Our findings suggest that ApoE ε4 enhances lysosomal stress and impairs proteostasis through increased mTORC1 signaling, dysregulated amino acid metabolism, and reduced lysosomal biogenesis. Given the role of microglia in AD pathogenesis, these results highlight the potential of targeting lysosomal function and mTORC1 signaling as therapeutic strategies for ApoE ε4-associated neurodegeneration.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Alzheimer\u0026rsquo;s disease\u003c/p\u003e\n\u003cp\u003eApoE\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;apolipoprotein E\u003c/p\u003e\n\u003cp\u003eA\u0026beta;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;beta-amyloid\u003c/p\u003e\n\u003cp\u003eBafi\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;bafilomycin\u003c/p\u003e\n\u003cp\u003eCBA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;cytometric bead array\u003c/p\u003e\n\u003cp\u003eCCL3 C-C motif chemokine ligand 3, MIP1\u0026alpha;\u003c/p\u003e\n\u003cp\u003eCCL5\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;C-C motif chemokine ligand 5, RANTES\u003c/p\u003e\n\u003cp\u003eCLEAR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;coordinated lysosomal expression and regulation\u003c/p\u003e\n\u003cp\u003eCTSB\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;cathepsin B\u003c/p\u003e\n\u003cp\u003eCTSD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;cathepsin D\u003c/p\u003e\n\u003cp\u003eCX3CL1\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;C-X3-C motif chemokine ligand 1\u003c/p\u003e\n\u003cp\u003eDMSO \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;dimethyl sulfoxide\u003c/p\u003e\n\u003cp\u003eD-PBS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Dulbecco\u0026rsquo;s phosphate-buffered saline\u003c/p\u003e\n\u003cp\u003eE3\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;ApoE isoform \u0026epsilon;3\u003c/p\u003e\n\u003cp\u003eE4\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;ApoE isoform \u0026epsilon;4\u003c/p\u003e\n\u003cp\u003eECAR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;extracellular acidification rate\u003c/p\u003e\n\u003cp\u003eFCCP\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;carbonyl cyanide-4 (trifluoromethoxy) phenylhydrazone\u003c/p\u003e\n\u003cp\u003eFDR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;false discovery rate\u003c/p\u003e\n\u003cp\u003eGLUL\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;glutamine synthetase\u003c/p\u003e\n\u003cp\u003eHIFP\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;1,1,1,3,3,3-Hexafluoro-2-propanol\u003c/p\u003e\n\u003cp\u003eIFN\u0026gamma;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;interferon-gamma\u003c/p\u003e\n\u003cp\u003eIL\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;interleukin\u003c/p\u003e\n\u003cp\u003eiMG\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;induced pluripotent stem cell-derived microglia\u003c/p\u003e\n\u003cp\u003eIPA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Ingenuity Pathway Analysis\u003c/p\u003e\n\u003cp\u003eiPSC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;induced pluripotent stem cell\u003c/p\u003e\n\u003cp\u003eLAMP-2\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;lysosomal-associated membrane protein 2\u003c/p\u003e\n\u003cp\u003eLC3\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;microtubule-associated protein light chain 3\u003c/p\u003e\n\u003cp\u003eLC3- II\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;LC3 conjugated to phosphatidylethanolamine\u003c/p\u003e\n\u003cp\u003eLLOMe\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;L-leucyl-L-leucine methyl ester\u003c/p\u003e\n\u003cp\u003eLMP\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;lysosomal membrane permeabilization\u003c/p\u003e\n\u003cp\u003eLPS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;lipopolysaccharide\u003c/p\u003e\n\u003cp\u003eM-CSF\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;macrophage colony-stimulating factor\u003c/p\u003e\n\u003cp\u003eMFI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;mean fluorescence intensity\u003c/p\u003e\n\u003cp\u003eMITF \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;microphthalmia-associated transcription factor\u003c/p\u003e\n\u003cp\u003emTORC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;mammalian target of rapamycin\u003c/p\u003e\n\u003cp\u003eNF-\u0026kappa;B\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;nuclear factor kappa B subunit\u003c/p\u003e\n\u003cp\u003eNT\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;basal conditions/untreated\u003c/p\u003e\n\u003cp\u003eOCR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;oxygen consumption rate\u003c/p\u003e\n\u003cp\u003eRAPA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;rapamycin\u003c/p\u003e\n\u003cp\u003eRT\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;room temperature\u003c/p\u003e\n\u003cp\u003eRT-qPCR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;reverse transcription quantitative real-time PCR\u003c/p\u003e\n\u003cp\u003eSQSTM1/p62\u0026nbsp;\u0026nbsp;sequestosome 1\u003c/p\u003e\n\u003cp\u003eTBST\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;TBS-0.05% Tween\u003c/p\u003e\n\u003cp\u003eTFEB\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;transcription factor EB\u003c/p\u003e\n\u003cp\u003eTNF\u0026alpha;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;tumor necrosis factor alpha\u003c/p\u003e\n\u003cp\u003eTREM2\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;triggering receptor expressed on myeloid cells 2\u003c/p\u003e\n\u003cp\u003eWB \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Western Blot\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe use of human iPSC lines was approved by the Committee on Research Ethics of Northern Savo Hospital District (license no. 123/2016).\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eFull metabolomic and proteomic datasets generated in this study are available from the corresponding authors on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank the technicians Anne Nyberg and Agnes Viherä for the assistance with the expansion of iPSCs and mycoplasma testing. We would also like to thank the technician Erja Huttu for the assistance with RT-qPCRs. The live imaging analysis was performed at the Biomedicum Stem Cell Center, University of Helsinki, funded by HILIFE and Biocenter Finland. The flow cytometry analysis was performed at the HILIFE Flow Cytometry Unit, University of Helsinki. The metabolomic analysis was done by Afekta Technologies, Kuopio, Finland.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project has received funding from JPco-fuND2 2019 Personalized Medicine for Neurodegenerative Diseases (PMG-AD, grant number 01ED2002A/ 334802) to MiH and JK; Business Finland (Go for Growth with Novel Stem Cell Platform to JK and TR); the Academy of Finland (grant 334525, JK; grant 338182, MiH; UHBrain Profi 6, TR); German Research Foundation under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy– ID 390857198) to SFL;\u0026nbsp;Alzheimer Forschung Initiative e.V. to SFL; the Finnish Concordia Fund and Föreningen Granatenhjelm R.F. to MaH. The funders had no role in the study design, data collection, or interpretation. We declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization and study design: TR, JK, MaH; methodology: MaH, MK, SM, SFL, SL, MT, MiH, JK, TR; investigation: MaH, IW, SM, TR; formal analysis: MaH, SM, TR; visualization: MaH, SM, TR; resources: SL, MP, KF, SFL, VL, AR, MiH, JK; funding acquisition: MaH, SFL, MiH, JK; project administration: TR; supervision: JK, TR; writing- original draft: TR, MaH, JK; writing-review \u0026amp; editing: all authors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the authors have approved the final version of the manuscript and provided their consent for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNixon, R.A. and D.S. 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\u003cstrong\u003e8\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eLee, S., et al., \u003cem\u003eAPOE modulates microglial immunometabolism in response to age, amyloid pathology, and inflammatory challenge.\u003c/em\u003e Cell Rep, 2023. \u003cstrong\u003e42\u003c/strong\u003e(3): p. 112196.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-neuroinflammation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jneu","sideBox":"Learn more about [Journal of Neuroinflammation](http://jneuroinflammation.biomedcentral.com)","snPcode":"12974","submissionUrl":"https://submission.nature.com/new-submission/12974/3","title":"Journal of Neuroinflammation","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"microglia, Alzheimer’s disease, apolipoprotein E, iPSC, lysosomal dysfunction","lastPublishedDoi":"10.21203/rs.3.rs-6241569/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6241569/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground.\u003c/h2\u003e \u003cp\u003eThe ε4 isoform of apolipoprotein E (ApoE) is the most significant genetic risk factor for Alzheimer\u0026rsquo;s disease. Glial cells are the main source of ApoE in the brain, and in microglia, the ε4 isoform of ApoE has been shown to impair mitochondrial metabolism and the uptake of lipids and Aβ42. However, whether the ε4 isoform alters autophagy or lysosomal activity in microglia in basal and inflammatory conditions is unknown.\u003c/p\u003e\u003ch2\u003eMethods.\u003c/h2\u003e \u003cp\u003eAltogether, microglia-like cells (iMGs) from eight \u003cem\u003eAPOE\u003c/em\u003e3/3 and six \u003cem\u003eAPOE\u003c/em\u003e4/4 human induced pluripotent stem cell (iPSC) lines were used in this study. The responses of iMGs to Aβ42, LPS and IFNγ were studied by metabolomics, proteomics, and functional assays.\u003c/p\u003e\u003ch2\u003eResults.\u003c/h2\u003e \u003cp\u003eHere, we demonstrate that iMGs with the \u003cem\u003eAPOE\u003c/em\u003e4/4 genotype exhibit reduced basal level pinocytosis and an overall downregulation of lysosomal proteins compared to \u003cem\u003eAPOE\u003c/em\u003e3/3 iMGs. Inflammatory stimulation with a combination of LPS and IFNγ or Aβ42 induced PI3K/AKT/mTORC signaling pathway, increased pinocytosis, and blocked autophagic flux, leading to the accumulation of sequestosome 1 in both \u003cem\u003eAPOE\u003c/em\u003e4/4 and \u003cem\u003eAPOE\u003c/em\u003e3/3 iMGs. Exposure to Aβ42 furthermore caused lysosomal membrane permeabilization, which was significantly stronger in \u003cem\u003eAPOE\u003c/em\u003e4/4 iMGs and positively correlated with the secretion of the proinflammatory chemokine IL-8. Metabolomics analysis indicated a dysregulation in amino acid metabolism, primarily L-glutamine, in \u003cem\u003eAPOE\u003c/em\u003e4/4 iMGs.\u003c/p\u003e\u003ch2\u003eConclusions.\u003c/h2\u003e \u003cp\u003eOverall, our results suggest that inflammation-induced metabolic reprogramming places lysosomes under substantial stress. Lysosomal stress is more detrimental in \u003cem\u003eAPOE\u003c/em\u003e4/4 microglia, which exhibit defects in lysosomal biogenesis.\u003c/p\u003e","manuscriptTitle":"Inflammation-induced lysosomal dysfunction in human iPSC-derived microglia is exacerbated by APOE 4/4 genotype","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-28 10:41:42","doi":"10.21203/rs.3.rs-6241569/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-16T14:44:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-16T14:35:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-14T15:54:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-25T14:29:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"108896763117094534228960520185838752738","date":"2025-03-19T14:21:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"292696662954909921199670141075636029999","date":"2025-03-19T13:52:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"143190408808719279701135929813298344545","date":"2025-03-19T13:14:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-19T13:04:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-18T04:23:33+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-18T03:40:28+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Neuroinflammation","date":"2025-03-17T06:23:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-neuroinflammation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jneu","sideBox":"Learn more about [Journal of Neuroinflammation](http://jneuroinflammation.biomedcentral.com)","snPcode":"12974","submissionUrl":"https://submission.nature.com/new-submission/12974/3","title":"Journal of Neuroinflammation","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"174f204f-fae6-456c-954a-580bbd50c408","owner":[],"postedDate":"March 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-06-09T16:05:27+00:00","versionOfRecord":{"articleIdentity":"rs-6241569","link":"https://doi.org/10.1186/s12974-025-03470-y","journal":{"identity":"journal-of-neuroinflammation","isVorOnly":false,"title":"Journal of Neuroinflammation"},"publishedOn":"2025-06-02 15:57:10","publishedOnDateReadable":"June 2nd, 2025"},"versionCreatedAt":"2025-03-28 10:41:42","video":"","vorDoi":"10.1186/s12974-025-03470-y","vorDoiUrl":"https://doi.org/10.1186/s12974-025-03470-y","workflowStages":[]},"version":"v1","identity":"rs-6241569","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6241569","identity":"rs-6241569","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}