Liraglutide Attenuates FFA-Induced Retinal Pigment Epithelium Dysfunction via AMPK Activation and Lipid Homeostasis Regulation in ARPE-19 Cells

To identify optimal treatment conditions, an MTT assay evaluated the effects of free fatty acids (oleic acid: palmitic acid = 2:1) and liraglutide on ARPE-19 cells. As shown in Figure 1A, 0.1 μM liraglutide alone did not affect cell viability after 24 h. FFA concentrations of 100 μM and 250 μM had no significant impact on viability, whereas 500 μM markedly reduced survival. Consequently, 250 μM FFA was selected for further experiments. When combined with 250 μM FFA, liraglutide at 0.05 μM and 0.1 μM showed no adverse effects on viability, while 0.5 μM liraglutide significantly reduced survival. Thus, 0.1 μM liraglutide was chosen as the optimal concentration. Bright-field microscopy revealed no observable changes in cell morphology or survival with either 250 μM FFA or 0.1 μM liraglutide alone. Combined treatment also showed no morphological alterations, further supporting the selected concentrations (Figure 1B). LipidTox staining demonstrated that FFA significantly increased intracellular lipid droplet accumulation, while co-treatment with 0.1 μM liraglutide effectively reduced this accumulation (Figure 1C). The quantitative analysis of LDs was performed using high-content analysis (HCA), a computer-assisted imaging method for the automated counting and statistical assessment of lipid droplets. This approach accurately distinguished LDs of different sizes, ensuring the objective and reliable analysis of cellular responses. As shown in Figure 1D, FFA treatment significantly increased the number of LDs larger than 1 μm in diameter. Co-treatment with liraglutide reduced both the total number of LDs and the number of larger LDs while increasing the number of smaller LDs (<1 μm). These results suggest that liraglutide enhances the degradation of larger lipid droplets, potentially improving lipid metabolism in ARPE-19 cells. In summary, liraglutide effectively reduces FFA-induced lipid droplet accumulation in ARPE-19 cells, likely by promoting lipid breakdown. These findings highlight its potential for addressing lipid dysregulation in RPE cells and its relevance to AMD pathology.

Figure 2 illustrates the protective effects of liraglutide against FFA-induced tight junction disruption and EMT in ARPE-19 cells. The immunocytochemistry staining of ZO-1, a tight junction marker (Figure 2A), showed a significant reduction in membrane-associated ZO-1 expression following 24 h of FFA treatment. This reduction was particularly evident in regions with elevated LD accumulation, as confirmed by LipidTox staining. Co-treatment with liraglutide restored ZO-1 expression to control levels, indicating its ability to maintain tight junction integrity. Western blot analysis further confirmed these findings (Figure 2B). FFA treatment significantly decreased the epithelial marker E-cadherin and increased the mesenchymal marker vimentin and phosphorylated Smad2/3 (pSer-Smad2/3), key regulators of EMT. Liraglutide reversed these effects by restoring E-cadherin levels and reducing vimentin and pSer-Smad2/3 expression. These trends were corroborated by the ICC staining of E-cadherin and vimentin (Figure 2C), which showed the following consistent results: FFA reduced E-cadherin and increased vimentin, both of which were reversed with liraglutide co-treatment. The quantitative PCR analysis of EMT-related transcription factors (Figure 2D) demonstrated that FFA treatment significantly upregulated Snail, Twist1, Twist2, and Slug, further confirming its role in EMT induction. Liraglutide co-treatment effectively suppressed the expression of these transcription factors, indicating its ability to counteract EMT at the transcriptional level. Together, these results demonstrate that liraglutide reduces FFA-induced EMT and preserves tight junction integrity in ARPE-19 cells, underscoring its potential therapeutic role in mitigating AMD-associated epithelial dysfunction.

Figure 3 highlights the effects of liraglutide in counteracting the FFA-induced suppression of autophagy and promoting lipophagy, facilitating LD degradation in ARPE-19 cells. Acridine orange (AO) staining (Figure 3A) revealed a significant reduction in acidic vesicular organelles (AVOs) following FFA treatment, indicating inhibited autophagy. Liraglutide co-treatment restored AVO expression, suggesting enhanced autophagic activity. This finding was supported by HCA (Figure 3B), which quantified AVO numbers. FFA reduced AVOs to approximately 10% of control levels, while liraglutide increased AVO numbers to 50% of control levels. Western blot analysis (Figure 3C) further confirmed these observations. FFA significantly decreased phosphorylated AMPK levels, reduced LC3-II expression, and increased p62 accumulation, consistent with suppressed autophagy. Liraglutide co-treatment restored phosphorylated AMPK levels, increased LC3-II expression, and reduced p62 levels, indicating the activation of AMPK-mediated autophagy. In addition, we evaluated the activity of mTOR, a key downstream effector negatively regulated by AMPK. FFA treatment increased phosphorylated mTOR levels, indicating suppressed autophagy and metabolic dysfunction. Liraglutide significantly reduced mTOR phosphorylation, supporting the notion that liraglutide relieves FFA-induced autophagy suppression through the AMPK/mTOR signaling axis. These results suggest that modulation of the mTOR pathway may contribute to the restoration of lipid homeostasis and to improved autophagic activity in RPE cells. To evaluate the role of lipophagy, perilipin 2 (PLIN2), a critical regulator of LD-specific autophagy, was analyzed using immunocytochemistry (Figure 3D). FFA treatment markedly reduced PLIN2 expression, whereas liraglutide restored it. The co-localization of PLIN2 with LDs was observed, indicating that liraglutide facilitates lipophagy and enhances LD degradation. Additionally, qPCR analysis (Figure 3E) demonstrated that FFA significantly downregulated lipophagy-associated genes, including autophagy related 5 (ATG5), as well as lysosomal fatty acid degradation genes such as lysosomal acid lipase (LIPA), ras-related protein 7A (RAB7A), and lysosomal-associated membrane protein 2 (LAMP2). Liraglutide co-treatment restored the expression of these genes, further supporting its role in promoting LD degradation pathways. These results implied that liraglutide alleviates the FFA-induced suppression of autophagy and lipophagy by activating AMPK signaling and upregulating genes that are essential for LD degradation. These findings underscore its therapeutic potential in mitigating lipid dysregulation associated with AMD.

Figure 4 illustrates that AMPK activation is critical for liraglutide's ability to mitigate FFA-induced oxidative stress, lipid accumulation, and EMT in ARPE-19 cells. DCFH-DA staining (Figure 4A) revealed a substantial increase in intracellular ROS following FFA treatment, consistent with oxidative stress observed during AMD progression. Liraglutide markedly reduced ROS levels, but this effect was fully reversed by co-treatment with compound C (CC), an AMPK-specific inhibitor, underscoring the dependence of liraglutide's ROS-lowering effects on AMPK activation. Quantitative fluorescence analysis (Figure 4B) confirmed these findings, showing that FFA increased ROS levels nearly seven-fold compared to controls, while liraglutide reduced this increase by approximately two-thirds. However, co-treatment with CC eliminated this reduction, further validating the requirement for AMPK activation. Western blot analysis (Figure 4C) demonstrated that liraglutide's restoration of autophagy and modulation of EMT markers is AMPK-dependent. FFA treatment reduced phosphorylated AMPK and LC3-II expression while increasing p62 levels, which is indicative of suppressed autophagy. Concurrently, FFA decreased E-cadherin and increased vimentin, which is consistent with EMT induction. Liraglutide reversed these changes, restoring phosphorylated AMPK and LC3-II levels, reducing p62, and normalizing E-cadherin and vimentin expression. However, co-treatment with CC diminished liraglutide's ability to modulate these markers, confirming the necessity of AMPK activation. Nile red staining (Figure 4D) further supported these findings, showing that liraglutide reduced intracellular lipid droplet accumulation induced by FFA, an effect that was completely negated by CC co-treatment. Collectively, these results demonstrate that liraglutide alleviates oxidative stress, lipid accumulation, and EMT in ARPE-19 cells through AMPK activation. The reversal of these protective effects by AMPK inhibition underscores its critical role in mediating liraglutide's therapeutic potential for AMD-related cellular dysfunction.

Figure 5 highlights the effects of liraglutide on exosome secretion, size distribution, and their role in EMT regulation under FFA-induced stress in ARPE-19 cells. Nanoparticle tracking analysis (NTA) (Figure 5A) revealed that FFA significantly increased extracellular vesicle (EV) secretion, with EV numbers approximately 10-fold higher than the control group (Figure 5B). Liraglutide partially reduced this increase, though EV levels remained around eight times higher than in controls. Co-treatment with GW4869, an inhibitor of exosome biogenesis and release, drastically reduced EV secretion, confirming that most of these EVs were exosomes secreted by ARPE-19 cells. Further analysis of particle size distribution (Figure 5C) showed that FFA increased the average diameter of exosomes. While liraglutide did not affect the average diameter, it significantly reduced the median diameter (D50) and the 90th percentile (D90), as well as the mode diameter of EVs. This indicates that liraglutide shifts the particle size distribution toward smaller exosomes, while the 10th percentile (D10) remained unchanged. To evaluate the functional impact of exosomes, EVs isolated from conditioned media were applied to FFA-treated ARPE-19 cells. To evaluate the functional impact of exosomes, EVs isolated from conditioned media under different treatment conditions were adjusted to a concentration of 5 × 10⁷ particles/mL and were co-cultured with FFA-treated ARPE-19 cells for 24 h. The immunocytochemistry analysis of epithelial (E-cadherin) and mesenchymal (vimentin) markers (Figure 5D) demonstrated that exosomes derived from the control and FFA + liraglutide groups enhanced E-cadherin expression and suppressed vimentin expression, indicating anti-EMT effects. Exosomes from the FFA group also reduced EMT, but their effect was weaker compared to those from the control and FFA + liraglutide groups. These findings highlight the ability of exosomes to influence EMT and suggest that liraglutide enhances their regulatory potential under FFA stress. In summary, liraglutide modulates exosome secretion and size distribution under FFA-induced stress and enhances the ability of exosomes to regulate EMT, demonstrating its potential to mitigate AMD-related RPE dysfunction.

All reagents were sourced from Sigma-Aldrich (St. Louis, MO, USA), unless otherwise noted. HCS LipidTox and Nile Red stains were purchased from Thermo Fisher Scientific (Waltham, MA, USA). Liraglutide was generously provided by Novo Nordisk (Bagsvaerd, Denmark). Primary antibodies against AMPK, phosphorylated Thr¹⁷²-AMPK (pThr¹⁷²-AMPK), mTOR, and phosphorylated Ser²⁴⁴⁸-mTOR (pSer²⁴⁴⁸-mTOR) were obtained from Cell Signaling Technology (Danvers, MA, USA). Additional antibodies for phosphorylated Ser-Smad2/3 and Smad2/3 were also procured from Thermo Fisher Scientific (Waltham, MA USA). Antibodies targeting E-cadherin, vimentin, ZO-1, and p62 were acquired from GeneTex (Irvine, CA, USA), and the PLIN2 antibody was sourced from ABclonal (Woburn, MA, USA). All chemicals were dissolved in phosphate-buffered saline (PBS) and stored at −20 °C until use.

ARPE-19 cells, an immortalized human retinal pigment epithelial cell line, were obtained from the American Type Culture Collection (ATCC, Manassas, VA, USA). Cells were routinely cultured in Dulbecco's Modified Eagle Medium: Nutrient Mixture F-12 (DMEM/F-12, 1:1 mixture, Gibco, Thermo Fisher Scientific, Waltham, MA, USA) supplemented with 10% fetal bovine serum (FBS, Gibco) and 1% penicillin-streptomycin (100 U/mL penicillin, 100 μg/mL streptomycin, Gibco). Cultures were maintained at 37 °C in a humidified incubator with 5% CO₂. For experimental procedures, cells were seeded in DMEM/F-12 supplemented with L-alanyl-L-glutamine (GlutaMAX, Gibco), 1% FBS, and antibiotics, at a density of 6 × 10⁴ cells/well in 24-well plates and incubated for 24 h prior to treatment. This reduced-serum medium was used to decrease cell proliferation and promote a more native retinal pigment epithelial phenotype, including polarized morphology and functional traits resembling native RPE cells [41]. For cell viability assays, cells were treated with varying concentrations of free fatty acids (FFA, oleic acid: palmitic acid = 2:1) or liraglutide for 24 h. Viability was assessed using the MTT assay, with absorbance measured at 570 nm using a microplate reader.

Lipid droplet (LD) accumulation was assessed using LipidTox Green Neutral Lipid Stain (Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer's protocol. ARPE-19 cells were seeded in 24-well plates, treated under experimental conditions, and gently washed three times with PBS to remove residual media. LipidTox Green dye was diluted in PBS and incubated with cells for 30 min at 37 °C in the dark. After staining, cells were washed with PBS to eliminate unbound dye. Nuclear staining was performed using Hoechst 33342 (Thermo Fisher Scientific, Waltham, MA, USA) for enhanced visualization. Fluorescence imaging was conducted using an ImageXpress Micro Confocal High-Content imaging system (Molecular Devices, Sunnyvale, CA, USA). A minimum of 100 cells per condition were analyzed, with each experiment performed in triplicate. LD size and number were quantified using the MetaXpress software version 6.7.0.211 (Molecular Devices, Sunnyvale, CA, USA), which enabled automated, high-precision measurements and the detailed statistical analysis of lipid accumulation across all experimental groups.

ARPE-19 cells were fixed with 4% paraformaldehyde for 15 min at room temperature and washed three times with PBS. Cells were then permeabilized using 0.1% Triton X-100 in PBS for 10 min. To prevent non-specific binding, they were blocked with 5% bovine serum albumin in PBS for 1 h at room temperature. Primary antibodies against ZO-1, E-cadherin, and vimentin were diluted 1:100 in the blocking solution and incubated overnight at 4° C. After washing three times with PBS, cells were incubated with Alexa Fluor-conjugated secondary antibodies (Thermo Fisher Scientific, Waltham, MA, USA) for 1 h at room temperature in the dark. Nuclei were counterstained with Hoechst 33342 for 10 min, followed by additional washes with PBS to remove excess dye. Fluorescence images were captured using an Olympus CKX-41 fluorescence microscope equipped with a DP74 camera (Olympus, Tokyo, Japan). Consistent imaging parameters were applied across all samples to ensure accurate and reproducible visualization of the target proteins.

Total protein lysates were prepared from ARPE-19 cells using Gold Lysis Buffer supplemented with protease and phosphatase inhibitors (Sigma-Aldrich, St. Louis, MO, USA) to preserve protein integrity. Protein concentrations were measured using the BCA protein assay kit (Thermo Fisher Scientific) to ensure equal loading for electrophoresis. Equal amounts of protein (20–40 µg per sample) were resolved by SDS-PAGE and transferred onto PVDF membranes (Millipore, Burlington, MA, USA). Membranes were blocked with 5% bovine serum albumin in TBST (Tris-buffered saline containing 0.1% Tween-20) for 1 h at room temperature to minimize non-specific binding. Primary antibodies were diluted 1:1000 in BSA-TBST and incubated with the membranes overnight at 4 °C. After three washes with TBST, membranes were incubated with HRP-conjugated secondary antibodies (diluted 1:10,000 in BSA-TBST) for 1 h at room temperature in the dark. Excess secondary antibodies were removed with three additional washes in TBST. Protein bands were visualized using an enhanced chemiluminescence (ECL) detection system (Bio-Rad, Hercules, CA, USA). Chemiluminescence signals were captured with an AI600 Imaging System (GE Healthcare, Chicago, IL, USA) under standardized exposure conditions. Relative protein expression levels were quantified using ImageJ software version 1.52a (NIH, Bethesda, MD, USA), with β-actin serving as the internal control. All experiments were performed in triplicate to ensure reproducibility and statistical reliability.

Total RNA was extracted from ARPE-19 cells using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) following the manufacturer's instructions. The concentration and purity of RNA were assessed using a spectrophotometer to ensure high-quality samples for downstream applications. Reverse transcription was performed using 1 µg of total RNA with a High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA, USA) according to the manufacturer's protocol. Quantitative PCR (qPCR) was conducted using SYBR Green Master Mix (Applied Biosystems, Foster City, CA, USA) on a 7300 Real-Time PCR System (Applied Biosystems). Each cDNA sample was analyzed in triplicate under the following cycling conditions: an initial denaturation at 95 °C for 10 min, followed by 40 amplification cycles of 95 °C for 15 s and 60 °C for 1 min. A dissociation curve was included at the end of the reaction to confirm the specificity of the amplification. Relative gene expression levels were determined using the 2⁻ΔΔCT method, with GAPDH serving as the internal reference gene for normalization. Primer sequences for target and housekeeping genes are listed in Table 1. Data analysis was performed using the Sequence Detection System software (v2.4.1, Applied Biosystems, Foster City, CA, USA), ensuring accurate and reproducible quantification.

Acridine orange (AO) staining was performed to assess autophagy by detecting acidic vesicular organelles (AVOs) in ARPE-19 cells. Cells were incubated with AO (1 μg/mL) for 15 min at 37 °C in the dark, followed by gentle washing with PBS to remove excess dye. Fluorescence signals were visualized using a fluorescence microscope, and images were captured under standardized settings to ensure consistency across samples. To quantify AVOs, HCA was conducted using an automated imaging system (Molecular Devices, Sunnyvale, CA, USA). A minimum of 100 cells per condition were analyzed, with each experiment performed in triplicate.

Intracellular ROS levels were evaluated using the fluorescent dye DCFH-DA. Cells were incubated with 10 μM DCFH-DA for 30 min at 37 °C in the dark to allow dye uptake and oxidation. After incubation, cells were gently washed with PBS to remove excess dye. Stained cells were imaged using an Olympus CKX-41 fluorescence microscope equipped with a DP74 camera (Olympus, Tokyo, Japan) to capture fluorescence signals under consistent imaging conditions. Fluorescence intensity was quantified using the iD5 microplate reader (Molecular Devices, Sunnyvale, CA, USA) at excitation/emission wavelengths of 485/528 nm. For normalization, ROS levels in treated samples were quantified as a percentage relative to the untreated control. The fluorescence intensity of the untreated control samples was used to establish baseline ROS fluorescence, and ROS levels in treated samples were calculated using the following formula: R e l a t i v e R O S L e v e l % ( ) = × F l u o r e s c e n c e I n t e n s i t y o f T r e a t e d S a m p l e F l u o r e s c e n c e I n t e n s i t y o f C o n t r o l S a m p l e 100

Each treatment condition was assessed in triplicate to ensure reproducibility. This normalization approach facilitated the direct comparison of ROS levels across different treatments, with results expressed as a percentage relative to the control ROS level.

Nile Red dye (1 μg/mL) was used to stain intracellular lipids for the assessment of lipid accumulation. Cells were incubated with the dye for 15 min at 37 °C in the dark. After incubation, fluorescence images were captured using an Olympus CKX-41 fluorescence microscope equipped with a DP74 camera (Olympus, Tokyo, Japan).

EVs were isolated from conditioned media using qEV original 35 nm size exclusion columns (Izon Science, Christchurch, New Zealand). Before use, the columns were equilibrated to room temperature for 30 min. Conditioned media were pre-cleared by centrifugation at 300× g for 10 min to remove cells, followed by 10,000× g for 30 min to eliminate debris. The pellet was resuspended in 200 μL of PBS and loaded onto the qEV column. Fractions were collected using an automatic fraction collector-V2 (AFC-V2, Izon Science, Christchurch, New Zealand). The void volume (F0, 1 mL) was discarded, and fractions F1 through F7 (250 μL each) were collected per the manufacturer's instructions. Fractions containing EVs were pooled and analyzed for size and concentration using a NanoSight NS300 system (Malvern Panalytical, Malvern, UK) equipped with a 488 nm laser. For the nanoparticle tracking analysis (NTA), samples were diluted 1:500 to 1:1000 in 0.22 µm-filtered PBS. The absence of background was confirmed using 0.2 µm-filtered PBS as a negative control. Camera level and detection threshold were set at 13 and 5, respectively. For each sample, four videos of 60 s each were recorded and analyzed using NTA 3.0 software (Malvern Panalytical, Malvern, UK). Particle size distribution and concentration data were obtained, and all measurements were conducted in triplicate to ensure accuracy and reproducibility.

All experiments were conducted in triplicate, and data are presented as mean ± standard deviation (SD). Statistical significance was evaluated using one-way analysis of variance (ANOVA) followed by Tukey's post hoc test for multiple comparisons. A p-value <0.05 was considered statistically significant. Data analysis was performed using SPSS Statistics 25 (SPSS, Inc., Chicago, IL, USA).