All experiments were performed on cortical neurons from the brains of E18 Sprague-Dawley rat pups, which were removed under sterile conditions according to the standard protocol approved by the Institutional Animal Care and Use Committee (IACUC), Saint Louis University, St. Louis, MO guidelines. The dissected cortices were cut into small pieces and incubated in an enzymatic solution containing 40 units of papain (Worthington Biochemical, Cat# LS003126), 2 mM CaCl₂ (Sigma, Cat# C4901-100G), 1 mM EDTA (Sigma, Cat# E9884-100G), and 1.5 mM L-cysteine (Sigma, Cat# 168149-25G) in Neurobasal medium (Gibco, Cat# 21103-049). Tissues in solution were incubated for 30 min at 37°C, mixing every few minutes to ensure even dissolution. Tissues were then triturated through fire-polished glass pipettes, then plated on dishes coated with 2 μg/ml laminin (Sigma, Cat# 11243217001) and 100 μg/ml poly-D lysine (Sigma, Cat# P6407-5MG), and cultured in Neurobasal medium supplemented with 1X GlutaMAX (Gibco, Cat# 35050-061), 1% pen/strep (Gibco, Cat# 15140122), 2% B-27 supplement (Gibco, Cat# 17504-044), and 4% fetal bovine serum (Avantor, Cat# 97068-086). One half of the medium was changed every 3 to 4 days, and cells were grown for 10 days in vitro (DIV) before experimentation.

For qPCR and western blot studies in microglia, HMC3 human microglial cells (ATCC, Cat# CRL-3304) were cultured at a density of 120,000 cells/dish in 6-well plates in EMEM (Eagle’s Minimum Essential Medium) (Corning, Cat# MT10009CV) supplemented with 10% fetal bovine serum (Gibco, Cat# 26140-095), 10 U/ml penicillin, and 10 μg/ml streptomycin. Cells were cultured for 24 h, then treated with filtered glucose dissolved in autoclaved water to get a final concentration of 30 mM. An equal volume of autoclaved water was used for the control. Cells were incubated for 72 h, then checked for mRNA and protein levels.

For primary cortical neurons, medium was changed at DIV 10 for equivalent medium supplemented (Sigma, Cat# G6152) to reach a final glucose concentration of 100 mM (with control medium containing 25 mM glucose), similar to other in vitro studies exploring hyperglycemia in neuronal cultures (Chen et al., 2016; Li et al., 2017). PGRN (R&D Systems, Cat# 2557-PG050) was added to the medium at this time to achieve a final concentration of 200 ng/ml, a concentration that is similar to plasma concentrations in patients and used in previous cell culture studies (Youn et al., 2009; Zhou et al., 2019a). Cells were treated under their respective conditions for 24 or 72 h before assay testing or harvest. Status of cells was observed using a phase-contrast microscope (IX73, Olympus) and images were taken with a Retiga R1 camera (QImaging).

For protein harvest, primary neurons were washed thrice in PBS (Gibco, Cat# 10010-031), then lysed using ice-cold N-PER lysis buffer (ThermoFisher, Cat# 87792) containing Halt protease inhibitor (ThermoFisher, Cat# 1860932) and phosphatase inhibitor (ThermoFisher, Cat#78420), then scraped from plates using a cell scraper. For PGRN measurements, HMC3 cells were rinsed with PBS, then lysed in RIPA buffer containing protease inhibitors (cOmplete™, Mini, EDTA-free, Protease Inhibitor Cocktail, Roche, Cat#11836170001). In both cell types, lysates were centrifuged at 14,000 rpm for 10 min and the supernatant was collected. Protein concentration was ascertained using a BCA Protein Assay kit (ThermoFisher, Cat# 23225).

Cell viability was determined using a fluorescence-based reporter dye kit (LIVE-DEAD™ Cell Imaging Kit, ThermoFisher, R37601). After treatment, cells were washed thrice with PBS, then incubated in HBSS containing 1 μM Calcein AM and 2 μM ethidium homodimer for 45 min. Images were taken using a phase-contrast microscope (IX73, Olympus) with fluorescence light source (Lambda XL, Sutter Instrument) and Retiga R1 camera (QImaging). Viability was determined by counting the number of Calcein AM-stained cells through visual observation and calculating as a ratio to total cells in each image.

Total RNA was isolated from cultured HMC3 cells using a RNeasy Mini kit (Qiagen, Cat#74106) with on-column DNase digestion (Qiagen, Cat#79256). RNA was reverse-transcribed to obtain cDNA using the iScript cDNA synthesis kit (Bio-Rad, Cat#1708891), and qPCR was performed using PowerUp SYBR Green Master Mix (ThermoFisher, Cat#A25777) with a Bio-Rad CFX384 Real-Time System. The primer sequences were as follows (with F for forward and R for reverse primers): human CYCLO-F, GGAGATGGCACAGGAGGAAA; human CYCLO-R, CCGTAGTGCTTCAGTTTGAAGTTCT; human GRN-F, AGGAGAACGCTACCACGGA; and human GRN-R, GGCAGCAGGTATAGCCATCTG. Results for qPCR were normalized to the housekeeping gene CYCLO and evaluated by the comparative C_T method.

Samples were treated with Laemmli sample buffer (Bio-Rad, Cat# 1610611) containing 350 mM DTT (Bio-Rad, Cat# 1610747) and run on a pre-cast MES-SDS gel (NuPage, Cat# NP0323BOX) in a Novex Mini-Cell device (Invitrogen, Cat# EI0001). Transfer to a 0.45 μm nitrocellulose membrane (Bio-Rad, Cat# 1620115) was performed in a Mini Protean Tetra System (Bio-Rad, Cat# 1658004). For PGRN measurement, proteins were separated on SDS-PAGE Bio-Rad TGX gels and transferred onto nitrocellulose membranes using the Bio-Rad Turbo-Blot transfer system.

Membranes were blocked in TBST containing 5% milk (Bio-Rad, Cat#1706404), then blotted using primary antibodies for light chain 3B (LC3B) (E7 × 45 XP(R), CST, Cat# 43566S), lysosome-associated membrane protein 2A (LAMP2A) (Abcam, Cat# ab18528), p-ERK1/2 (CST, Cat# 4370S), ERK1/2 (CST, Cat# 4695S), phosphorylated GSK3β (CST, Cat# 9336S), GSK3β (CST, Cat# 9315S), glyceraldehyde 3-phosphate dehydrogenase (GAPDH) (CST, Cat# 2118S), PGRN (R&D Systems, Cat# AF2557), hPGRN (an anti-human PGRN linker 5 polyclonal antibody #614 that recognizes an epitope between residues 497 and 515 (Nguyen et al., 2013a)), and β-actin (CST, Cat# 3700S). All antibodies were used at a 1:1000 dilution, except for hPGRN, which was at a 1:3000 dilution. A goat anti-rabbit (Invitrogen, Cat# 31460) or donkey anti-sheep (ThermoFisher, Cat#A16041) at a 1:5000 dilution or HRP-conjugated AffiniPure goat anti-rabbit and anti-mouse antibodies (Jackson Immuno Research Labs) at a 1:10000 dilution were used for secondary antibody incubation. Western blot data were captured using an imager (ThermoFisher, iBright FL1000) after incubating the membranes in Pierce substrate (ThermoFisher, Cat#32106). hPGRN western blots were visualized using a Chemi-Doc system (Bio-Rad). Densitometric analysis was performed using ImageJ (NIH).

Unless specified, primary cell cultures were fixed with 4% paraformaldehyde (ThermoFisher, Cat# J19943-K2) for 20 min, permeabilized with 0.3% Triton X-100 (VWR, Cat# 0694-1L) for 5 min, and blocked in PBS containing 5% goat serum (Gibco, Cat# 16210-064) for 1 h at room temperature. To visualize autophagosome and lysosome expression, antibodies for LC3B (E7 × 45 XP(R), CST, Cat# 43566S), LAMP2A (Abcam, Cat# ab18528), microtubule-associated protein 2 (MAP2) (Invitrogen, Cat# 13-1500), and glial fibrillary acidic protein (GFAP) (EMD Millipore, Cat# AB5541) were used at a 1:200 dilution in 5% goat serum. To visualize PGRN expression in microglia, a 1:100 dilution of PGRN antibody (R&D Systems, Cat# AF2557) and 1:3000 dilution of allograft inflammatory factor 1 (Iba1) antibody (Wako, Cat# 019-19741) in 5% donkey serum were used. For secondary incubation, the following antibodies were used at a 1:500 dilution in 5% goat serum: goat anti-rabbit conjugated with Alexa Fluor 568 (Invitrogen, Cat# A11036), anti-mouse conjugated with Alexa Fluor 488 (Invitrogen, Cat# A11029), and anti-chick conjugated with Alexa Fluor 488 (Abcam, Cat# ab150169). The following antibodies were used at a 1:500 dilution in 5% donkey serum: donkey anti-rabbit conjugated with Alexa Fluor 546 (Invitrogen, Cat# A10040) and donkey anti-sheep conjugated with Alexa Fluor 647 (Invitrogen, Cat# A21448). Slides were stained with DAPI (1 μg/ml) included in the mounting media (Fluoroshield, Sigma, Cat# F6507), and images were taken using a confocal microscope (Leica, TCS SP8).

Fluorescence intensity analysis was performed by selecting regions of interest (ROIs) of cell bodies, identified by staining with the neuronal marker MAP2 or astrocytic marker GFAP. The mean fluorescence intensity of each ROI was measured, and values were normalized with control equal to 1. To prevent differences in intensity due to user error, slides were viewed under the same acquisition parameters for fluorescence images.

Cortical cells were incubated with 50 μg BSA-AGE (Cayman Chemical, Cat# 22968) for 6 h at the end of the 72-h treatment period. Protein samples were harvested and AGE detection was performed using a fluorometric assay kit (Biovision, Cat# K929-100), measuring emission at 460 nm in response to excitation at 360 nm and using BSA control as the baseline. Levels of AGEs were validated by western blot with anti-AGE antibody (Bioss, Cat# bs-1158R) at a 1:1000 dilution, normalized to GAPDH expression.

Activity of ubiquinone oxidoreductase (UO), succinate dehydrogenase (SDH), and cytochrome C oxidase (COX) were tested to represent mitochondrial complexes I, II, and IV, respectively. Protein samples were harvested after 72 h of treatment at DIV 10 and tested in a 96-well microplate format using a plate reader (Synergy H1, BioTek). Activity was calculated as mΔOD per min, accounting for differences in protein concentration between samples. All reagents listed were obtained from Sigma unless otherwise noted.

UO activity was measured as documented previously (Ma et al., 2011). Samples were added to a reagent containing 25 mM potassium phosphate (pH 7.2) (Cat# P5655), 5 mM MgCl₂ (Cat# M4880), 1 mM KCN (Cat# 60178), 0.13 mM NADH (Cat# N8129), 65 μM coenzyme Q10 (Cat# C9538), 2.5 mg/ml BSA (Cat# A9418), and 2 μg/ml antimycin A (Cat# A8764). The reagent was heated to 30°C for 10 min before adding 2 ug/ml rotenone (Cat# R8875), followed by adding samples. Activity was tied to reduction of NADH, measured as a decrease in absorbance at 340 nm over a 20-min period.

SDH activity was measured as documented previously (Cimen et al., 2010). Samples were added to a reagent containing 10 mM KCl (Cat# P5405), 5 mM MgCl₂, 50 mM sodium succinate (Cat# S2378), 40 mM NaN₃ (Cat# S2002), 300 mM mannitol (Cat# M4125), and 20 mM potassium phosphate (pH 7.2) (all reagents from Sigma). Activity was tied to the reduction of the electron acceptor DPIP (Fisher Chemical, Cat# S286-5) (50 μM), which manifests as a decrease in absorbance at 600 nm over a 30-min period.

COX activity was measured as documented previously (Ma et al., 2011). Samples were added to a reagent containing 20 mM potassium phosphate, pH 7.2, and 0.45 mM n-dodecyl-β-D-maltoside (Sigma, Cat# D4641). Reagent was heated to 30°C for 10 min before adding 15 μM reduced cytochrome C (Sigma, Cat# C2506), followed by adding samples. Activity was tied to oxidation of cytochrome C, measured as a decrease in absorbance at 550 nm over a 30-min period.

Data were analyzed using Graphpad 8.4.3 software, with the threshold for significance at p < 0.05. Values provided are mean ± S.E.M. Student’s t-test was used to assess significance between two groups; for other experiments involving high glucose and PGRN, one-way ANOVA was used. Post hoc testing was performed using Fisher’s Least Significant Difference (LSD). The N and p values for experiments are provided in the figure legend or text.

To start, we examined neurons to determine if there were any readily noticeable phenotypic differences due to high glucose (HG) or PGRN. Since PGRN is a known neurotrophic and neuroprotective factor (Van Damme et al., 2008), we considered whether this property would be maintained under high-glucose conditions. At DIV 10, cells were treated with 100 mM glucose and 200 ng/ml PGRN for 72 h before testing. This concentration was used in other studies (Chen et al., 2016; Li et al., 2017) and in our case because we saw a significant decrease in cell viability under 100 mM, but not 50 mM, glucose (Supplementary Figure 1). Using a fluorescence-based reporter assay, we found that cell viability decreased significantly (F = 5.307, p = 0.005) (Figure 1A). Under high-glucose conditions, viability decreased from 89.55 ± 1.27% to 74.61 ± 4.80% (p = 0.001). Despite no difference compared to control (from 89.55 ± 1.27% to 87.94 ± 1.98%, p = 0.699), PGRN treatment led to increased viability under high glucose, from 74.61 ± 4.80% to 84.35 ± 2.29% (p = 0.025).

Cells viewed under phase-contrast microscopy showed extensive growth of neuritic processes, while cells in high glucose showed less growth of non-primary (i.e., secondary and tertiary) neurites (Figure 1C). Neurite growth appeared to be exceptionally robust with 200 ng/ml PGRN treatment, which was maintained even under high-glucose treatment. While we were unable to perform neurite tracing on matured neurons in culture (>DIV 10) due to the density of cell growth, we were able to assess the effect of PGRN on neurite outgrowth in early developmental (DIV 4) neurons after treatment for 72 h. High glucose incubation resulted in a lower average number of neurites, although this did not reach the threshold of significance (from 9.067 ± 1.181 to 7.325 ± 0.784 neurites, p = 0.197) (Figure 1B). PGRN positively influenced neurite outgrowth under high-glucose conditions (from 7.325 ± 0.784 to 10.353 ± 1.019 neurites, p = 0.030); when viewed in detail, there was a trend toward an increase in primary neurites (4.471 ± 0.438 to 5.471 ± 0.444 primary neurites, p = 0.080), and a significant increase in non-primary neurites (2.765 ± 0.481 to 4.882 ± 0.857 non-primary neurites, p = 0.039). This indicates that PGRN treatment promotes neuronal outgrowth and viability, even when cultured in high glucose.

Prior studies have shown that microglia express high levels of PGRN and may be important in neurodegeneration (Mendsaikhan et al., 2019; Choi et al., 2020), so we explored if high glucose affected the degree of PGRN expression in this cell type. We performed qPCR and western blot analyses on HMC3 cells treated with high glucose (in this case, 25 mM, in medium with a basal glucose level of 5.5 mM), and found that mRNA and protein expression of PGRN were similar among control and high glucose-treated cells (Figures 2A,B). The mRNA level changed from 1.000 ± 0.139 Arbitrary Units, AU, to 1.022 ± 0.099 AU, and the protein level from 1.000 ± 0.212 AU to 1.069 ± 0.232 AU. This finding was confirmed in primary cortical cultures, which showed abundant PGRN expression in microglia (Figure 2C) but no difference due to glucose concentration (from 1.000 ± 0.315 AU to 0.714 ± 0.163 AU (Figure 2D). In summary, PGRN expression does not appear to be significantly altered under high glucose, signifying that hyperglycemia-induced neurodegeneration is unlikely due to differential PGRN levels per se.

Impairment of autophagy is seen in diabetes and neurodegenerative conditions, so we tested how high glucose affected autophagy flux using LC3B as an autophagosome marker. Conjugation of LC3 with phosphatidylethanolamine (PE) is an essential step in maturation of the autophagosome, and the rate of autophagy flux can be estimated by measuring the ratio of conjugated to unconjugated protein (i.e., LC3-II:I ratio) via western blot (Mizushima and Yoshimori, 2007). While the overall ANOVA did not reach the threshold of significance (F = 2.195, p = 0.108), there appears to be a trend toward a decrease in the LC3-II:I ratio due to high glucose compared to control, from 1.000 ± 0.208 AU to 0.464 ± 0.092 AU (Figure 3A). PGRN treatment did not appear to alter LC3B levels in either control (from 1.000 ± 0.208 AU to 0.931 ± 0.309 AU) or high-glucose conditions (to 0.474 ± 0.076 AU). Treatment with the lysosomal inhibitor chloroquine (CQ) led to an increased LC3-II:I ratio (F = 5.643, p = 0.000), indicative of impaired lysosomal clearance (Supplementary Figure 2A). The change in LC3B was significant in all treatment groups except for PGRN alone (0.940 ± 0.426 AU to 2.147 ± 0.595 AU, p = 0.056). Treatment with the autophagy inducer rapamycin also increased LC3B lipidation (F = 2.378, p = 0.042), although this was significant only in cells treated with PGRN (0.940 ± 0.426 AU to 7.012 ± 3.711 AU, p = 0.006) (Supplementary Figure 2B).

Light chain 3B can also be used to measure autophagosome formation by immunofluorescence, with an increase in punctate formation indicating increased autophagosome formation or decreased autophagosome clearance. We performed immunofluorescence in cortical cells, with LC3B as red and co-stained with either MAP2 as a neuronal marker or GFAP as a glial cell marker (both in green). We found significant changes in LC3B expression in neurons (F = 10.45, p = 0.001), with a lower (but not significantly so) level of LC3B fluorescence seen when cultured under high-glucose conditions, from 1.000 ± 0.069 AU to 0.916 ± 0.045 AU (p = 0.331) (Figure 3B). On the other hand, under high-glucose conditions, PGRN increased puncta levels to 1.190 ± 0.097 AU (p = 0.003). It is worth noting that cells labeled with the neuronal marker MAP2 exhibited substantial neurite growth in control conditions, while neurons incubated in high glucose appear to have fewer major primary neurites (Figure 3C), similar to our phase-contrast images (Figure 1C). Differences in LC3B puncta were also pronounced in astrocytes (F = 104.6, p = 0.000), albeit in the opposite direction, with high glucose significantly increasing LC3B fluorescence in these cells from 1.000 ± 0.037 AU to 1.512 ± 0.087 AU (p = 0.001). PGRN increased LC3B intensity even more so, to 2.792 ± 0.099 (p = 0.000), but decreasing under high-glucose conditions from 1.512 ± 0.087 AU to 0.899 ± 0.049 AU (p = 0.000) (Figures 3D,E). These data on LC3B expression collectively suggest that autophagy flux is decreased under high-glucose conditions and that PGRN alleviates this impairment, with neurons and astrocytes being affected in different ways.

Later steps of autophagy consist of autophagosome fusion with lysosomal vesicles, which has been shown to be impaired in diabetes (Ma et al., 2017). To see if this step was affected by PGRN, we performed western blot and immunofluorescence studies for LAMP2A, a lysosome membrane protein that localizes in the perinuclear region upon autophagy activation. By western blot, we observed no change in total LAMP2A levels in cells (F = 3.271, p = 0.621) (Figure 4A) and an increase when cells were treated with the lysosomal inhibitor CQ (F = 5.75, p = 0.002) and autophagy inducer rapamycin (F = 3.763, p = 0.004) (Supplementary Figures 3A,B). LAMP2A protein levels increased in all groups due to rapamycin and due to CQ except control, which trended toward an increase (1.000 ± 0.074 AU to 2.453 ± 0.497 AU, p = 0.094).

However, we observed differential LAMP2A punctate formation in the perinuclear region of cells treated with PGRN. By immunofluorescence, we observed an increase in LAMP2A puncta in neurons (F = 4.423, p = 0.007), with high glucose increasing punctate levels from 1.000 ± 0.137 AU to 1.463 ± 0.108 AU (p = 0.005) (Figures 4B,C). PGRN co-treatment alongside high glucose reduced punctate formation to 1.246 ± 0.096 AU, which was no longer significantly different from control (from 1.000 ± 0.137 AU, p = 0.160) or PGRN treatment alone (from 1.031 ± 0.083 AU, p = 0.152). In astrocytes, we saw a non-significant trend toward an increase in LAMP2A expression in cells treated with PGRN (F = 1.825, p = 0.151) (Figures 4D,E). Combined with our data on LC3B, this indicates that lysosome levels are affected by PGRN in cells under high-glucose stress, and that this effect is also different in neurons and astrocytes.

AGEs build up under hyperglycemic conditions as excess glucose spontaneously glycosylates proteins (Singh et al., 2014). Under conditions of impaired autophagy, these modified proteins build up due to a lack of clearance (Takahashi et al., 2017). As a more direct metric of protein turnover, we incubated cortical cells at the end of a 72-h treatment period with 50 μg of AGE-BSA and continued treatment for 6 h at 37°C before harvest. We observed a significant change in AGE levels (F = 3.271, p = 0.047); in particular, AGE levels were higher in cells under high glucose compared to the control, increasing from 5.067 ± 0.385 μg/mg protein to 8.004 ± 0.852 μg/mg protein (p = 0.007) (Figure 5A). While AGE levels were slightly higher in samples treated with 200 ng/ml PGRN than in control at 6.158 ± 0.734 μg/mg protein, this was not significant (p = 0.266), and high glucose did not increase concentration further (up to 6.033 ± 0.575 μg/mg protein; p = 0.812 between PGRN and HG + PGRN), suggesting that PGRN treatment aided in clearance of AGE from cells. We also found similar results via western blot (F = 3.231, p = 0.047), with an overall increase due to high glucose from 1.000 ± 0.196 AU to 1.726 ± 0.150 AU (p = 0.009 between control and high glucose). There was no significant increase due to PGRN (to 1.195 ± 0.078 AU) compared to control (p = 0.438 between control and PGRN) and high-glucose treatment did not increase this further (to 1.377 ± 0.260; p = 0.472 between PGRN and HG + PGRN) (Figure 5B). These data indicate that PGRN may aid in clearance of protein substrates that accumulate due to high-glucose stress.

Mitochondrial activity is dysregulated in diabetes and neurodegenerative diseases like Parkinson’s. Mitochondrial damage is a major contributor of reactive oxygen species (ROS) leakage and cellular dysfunction, and is also seen in hyperglycemic conditions (Rolo and Palmeira, 2006). Because proper maintenance of mitochondrial function through regular turnover is important to neuronal metabolic health (Rugarli and Langer, 2012), we aimed to see if preserving autophagy also improved mitochondrial function. We therefore monitored mitochondrial enzymatic activity as a metric of mitochondrial function, measuring the function of complex I (ubiquinone oxidoreductase, UO), complex II (succinate dehydrogenase, SDH), and complex IV (cytochrome C oxidase, COX). Our results were mixed, with results varying by complex. UO activity, measured in terms of ΔmOD₃₄₀, did not change under any treatment condition (F = 1.373, p = 0.283) (Figure 6A). SDH activity trended toward significance (F = 2.209, p = 0.119), with a trend toward a decrease under high-glucose conditions, observed as a decrease in ΔmOD₆₀₀ from 1.138 ± 0.069 to 0.817 ± 0.172 (p = 0.060). PGRN treatment attenuated the decrease due to high glucose from 1.203 ± 0.026 to 1.069 ± 0.129 ΔmOD₆₀₀ (p = 0.414 between PGRN and HG + PGRN) (Figure 6B). COX activity was significantly altered by high glucose and PGRN (F = 20.89, p = 0.000), with ΔmOD₅₅₀ increasing under high-glucose conditions from 1.596 ± 0.100 to 2.167 ± 0.122 (p = 0.028). PGRN treatment amplified this increase from 1.948 ± 0.183 to 3.482 ± 0.274 (p = 0.000 between PGRN and HG + PGRN) despite no change when comparing control to PGRN treatment alone (ΔmOD₅₅₀ from 1.596 ± 0.100 to 1.948 ± 0.183, p = 0.156) (Figure 6C). This indicates that the impact of hyperglycemia and PGRN on the mitochondria is complex-specific.

Several signaling pathways are implicated in diabetes, including those involved in cell stress such as GSK3β and ERK1/2. The former is implicated in autophagy activation through downstream ULK1 activation (Lin et al., 2012), and the latter has been shown to promote autophagy induction under stressful conditions (Cagnol and Chambard, 2010). We found that PGRN influences the phosphorylation of these kinases in high-glucose conditions, albeit with different timings. Inhibitory GSK3β phosphorylation at serine 9 was not significantly affected after 24 h of treatment (F = 0.809, p = 0.504) (Figure 7A). After 72 h of treatment, phosphorylation increased significantly (F = 7.606, p = 0.002), with high glucose increasing phosphorylation from 1.000 ± 0.078 AU to 2.044 ± 0.445 AU (p = 0.009) (Figure 7B). PGRN treatment reduced phosphorylation from 1.000 ± 0.078 AU to 0.551 ± 0.112 AU (p = 0.221), although a statistically significant decrease was only observed under high-glucose conditions (2.044 ± 0.445 AU to 0.628 ± 0.178 AU, p = 0.001). On the other hand, we found that activatory threonine 202 and tyrosine 204 phosphorylation of ERK1/2 significantly increased after 24 h of treatment (F = 7.750, p = 0.009) (Figure 7C) and returned to baseline within 72 h (F = 0.759, p = 0.530) (Figure 7D). At 24 h of treatment, it increased under simultaneous high-glucose and PGRN treatment from 1.000 ± 0.145 AU to 2.403 ± 0.381 AU (p = 0.004 between control and HG + PGRN). However, high glucose and PGRN treatments alone did not elicit any change, only changing ERK1/2 phosphorylation to 1.342 ± 0.398 and 0.932 ± 0.241 AU, respectively (p = 0.352 and 0.848, respectively). This effect appears to affect ERK2 (F = 8.436, p = 0.007) as well as ERK1 phosphorylation despite a non-significant change in the latter (F = 1.206, p = 0.368). The lack of significance at 72 h was also present when looking at ERK1 (F = 1.784, p = 0.183) and ERK2 (F = 1.115, p = 0.366) in particular. These findings suggest that GSK3β and ERK1/2 activation may play a role in PGRN’s autophagy-modulating response in neurons cultured in high glucose in a time-dependent manner.