{"paper_id":"1ea45488-cd03-4184-bbb4-308166d258a4","body_text":"Erythrocyte-Targeted Therapy for Glaucoma: Neuroprotection Through Erythrocyte-Derived Sphingosine 1-Phosphate-Enhanced Fatty Acid β-Oxidation via the AMPKα-CPT1A Axis | 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 Article Erythrocyte-Targeted Therapy for Glaucoma: Neuroprotection Through Erythrocyte-Derived Sphingosine 1-Phosphate-Enhanced Fatty Acid β-Oxidation via the AMPKα-CPT1A Axis Yang Xia, Yanxiu Li, Qingyang Liu, Tian-Sheng Chou, Cheng Luo, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8165516/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Glaucoma is characterized by retinal ganglion cell (RGC) loss. While the role of vascular insufficiency is recognized, the specific contribution of erythrocytes has remained elusive. This study identifies a novel erythrocyte-centric pathway in glaucoma pathogenesis using integrated metabolomic, lipidomic, and functional analyses of human erythrocytes and validated mouse models. We uncover compensatory erythrocyte reprogramming: elevated intracellular bisphosphoglycerate mutase drives glycolysis toward the Rapoport-Luebering pathway to enhance oxygen release, but at the cost of pentose phosphate pathway suppression and oxidative vulnerability, which led to ROS-induced lipid peroxidation and compromise cell membrane. Concomitant L-carnitine depletion impairs the Lands cycle, failing to repair membrane sphingosine 1-phosphate (S1P) transporter MFSD2B and curtailing extracellular S1P release, yielding systemic S1P deficiency. L-carnitine supplementation emerges as a targeted erythrocyte therapy, replenishing acylcarnitine pools to restore Lands cycle flux (lysophosphatidylcholine (LPC) to phosphatidylcholine (PC) conversion) and support membrane repair of proteins like MFSD2B and GLUT1. This repair facilitates S1P release and glucose uptake, with the latter channeled into the PPP to bolster antioxidant defenses and inhibit ROS-induced lipid peroxidation, thereby preventing further membrane compromise. Extracellular S1P triggers the AMPKα-CPT1A axis to support fatty acid β-oxidation, rescuing TCA cycle, ATP levels, and cell survival of glaucoma RGCs. Integrating data from the UK Biobank and our cohort supports plasma S1P as a novel pathogenic biomarker for glaucoma, linking erythrocyte dysfunction to neurodegenerative diseases. Our work repositions erythrocytes as pivotal mediators of glaucoma, framing the glaucoma as a systemic hematologic-ophthalmic disorder and providing a translational framework for erythrocyte metabolism-targeted interventions. Health sciences/Diseases/Eye diseases Biological sciences/Cell biology/Mechanisms of disease Glaucoma Erythrocyte Sphingosine-1-phosphate Lands cycle Metabolic reprogramming L-carnitine Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Glaucoma is a prevalent eye condition globally and is the first leading cause of irreversible blindness worldwide, affecting approximately 3% of the global population aged 40 to 80 years. This condition encompasses a spectrum of eye diseases that damage the optic nerve, primarily due to increased intraocular pressure (IOP). Primary glaucoma is mainly including two main types: open-angle glaucoma (POAG) and angle-closure glaucoma (PACG) 1 – 3 . Central to the pathophysiology of glaucoma is the degeneration of retinal ganglion cells (RGCs), which are crucial for transmitting visual information from the retina to the brain 4 , 5 . Glaucoma is a complex and multi-factory disease. While mechanical stress from increased IOP remains a key factor, early genetic studies have identified multiple loci associated with POAG across diverse ancestries, implicating pathways such as extracellular matrix remodeling, intracellular ion channels, and adipose metabolism 6 . Besides, oxygen regulation is also pivotal in glaucoma progression, particularly in maintaining blood vessel health and the optic nerve head. Local hypoxia in glaucoma-affected tissues, including the retina and trabecular meshwork of anterior chamber angle, can exacerbate disease progression by driving neuroinflammation, retinal damage, and ultimately the loss of RGCs 7 – 10 . Erythrocytes, as primary and sole oxygen carriers, are essential for delivering oxygen to every organ within our body. Thus, it is possible that efficient oxygen transport by erythrocytes may help alleviate local hypoxia, reducing oxidative stress and potentially slowing RGC and trabecular meshwork damage. In addition to oxygen transport, erythrocytes are critical regulators of metabolite transport and homeostasis, contributing to neuronal protection. They deliver essential metabolites such as pyruvate, lactate, and amino acids, which are vital for neuronal metabolism and energy production, while simultaneously removing metabolic waste products like urea and ammonia to prevent neurotoxicity 11 . One of the pathways central to erythrocyte function is the Lands cycle 12 , a phospholipid remodeling pathway essential for maintaining membrane fluidity and function. By modifying the fatty acid composition of phospholipids, the Lands cycle ensures membrane stability, deformability, and erythrocyte lifespan. Although erythrocytes lack nuclei and have limited synthetic capabilities, their membrane integrity is crucial for effective oxygen delivery and metabolic regulation. Dysregulation of the Lands cycle may compromise these processes, making it a critical area of study in diseases influenced by hypoxia and oxidative stress 13 . Despite their fundamental role in oxygen and metabolite transport, erythrocytes have been largely overlooked in glaucoma research. As the most abundant circulating cell type and highly sensitive to hypoxia 14 , erythrocytes may play an unrecognized role in glaucoma pathophysiology, linking systemic metabolic dysfunction to local retinal damage. Understanding erythrocyte function in glaucoma offers a novel perspective on disease progression and potential therapeutic targets. Therefore, here we took multi-disciplinary approaches including accurately measuring erythrocyte oxygen delivery capacity and comprehensive metabolomics and lipidomic profiling in glaucoma human cohort coupled with a sophisticate murine genetic tool and isotopically labelled glucose flux tracing analyses to define erythrocyte oxygen release and its potential role and underlying mechanism with a goal to develop early circulating pathogenic biomarkers and intervention for the disease. Materials and Methods Human subjects In this study, inclusion criteria for POAG are IOP > 21 mmHg, glaucomatous optic disc and RNFL damage, typical visual field defects, and an open anterior chamber angle. PACG criteria include glaucomatous optic disc changes, visual field damage, IOP > 21 mmHg, and a narrow or closed anterior chamber angle. Exclusion criteria cover diseases including secondary glaucoma, other conditions affecting vision, and unreliable visual field tests. Our glaucoma cohort comprised both newly diagnosed and patients with established disease who were receiving topical medications (e.g., prostaglandin analogues, β-blockers, α-agonists, carbonic-anhydrase inhibitors) or had undergone prior surgery (e.g., trabeculectomy and laser Peripheral Iridotomy,) ( Table S1 ) . Healthy volunteers were matched for age and biological sex and had normal examination results. Demographic and clinical information of human subjects are listed in Table 1 . All participants were examined by board-certified ophthalmologists at Xiangya Hospital, Central South University, Changsha, Hunan, China, using slit-lamp biomicroscopy, Goldmann applanation tonometry, funduscopy, optical coherence tomography (OCT), and standard automated perimetry to confirm glaucoma diagnoses or to verify normal ocular status in control subjects. Approximately 3 mL of whole blood was collected from the forearm vein of human subjects. Human blood samples were collected in lavender-top plasma separation tubes containing spray-dried dipotassium ethylenediaminetetraacetic acid (K₂EDTA) as the anticoagulant. The samples were centrifuged at 2,000 rpm for 10 minutes at 4°C. After separation, the plasma and erythrocytes were aliquoted into 100 µL per tube and immediately stored at -80°C for further analysis. The research protocol, including informed consent from the subjects, was approved by the Central South University Committee for the Protection of Human Subjects. Table 1 Clinical information of human subjects. Variable Control (n = 40) Primary glaucoma(n = 40) P value Age(yr) 57.00 ± 12.34 57.52 ± 11.94 0.927 Sex(Female/Male) 25/15 25/15 N/A SBP(mm Hg) 115.32 ± 14.18 132.46 ± 21.21* < 0.001 DBP(mm Hg) 78.85 ± 6.85 83.69 ± 13.84 0.055 OPP (mmHg) 45.42 ± 6.13 37.56 ± 15.55* 0.005 IOP (mmHg) 15.25 ± 3.0 29.08 ± 11.69* < 0.001 RNFL Thickness (µm) 104.1 ± 9.7 69.29 ± 17.48* < 0.001 Mean Deviation (dB) -0.98 ± 0.60 -21.24 ± 10.75* < 0.001 Cup-to-Disc Ratio 0.4 ± 0.1 0.67 ± 0.27* < 0.001 WBC(10 9 /L) 5.80 ± 1.25 6.42 ± 1.27* 0.036 RBC(10 12 /L) 4.69 ± 0.38 4.47 ± 0.44* 0.045 Hb(g/L) 139.95 ± 13.97 135.03 ± 11.86 0.103 PLT(10 9 /L) 214.15 ± 40.05 213.45 ± 50.74 0.948 HCT(%) 41.90 ± 3.71 40.72 ± 3.29 0.148 Neu(10 9 /L) 3.33 ± 1.02 4.04 ± 0.99* 0.003 Lym(10 9 /L) 1.90 ± 0.51 1.78 ± 0.58 0.356 Eos(10 9 /L) 0.12 ± 0.09 0.11 ± 0.08 0.657 Mono(10 9 /L) 0.40 ± 0.12 0.46 ± 0.15 0.077 MCV(fl) 89.30 ± 4.27 90.53 ± 5.40 0.281 MCH(PG) 29.81 ± 1.89 30.01 ± 2.02 0.651 MCHC(g/L) 333.51 ± 8.81 331.37 ± 6.87 0.241 RDW(%) 13.84 ± 1.10 13.07 ± 0.77* 0.001 PCT(%) 0.19 ± 0.03 0.20 ± 0.05 0.535 MPV(fl) 9.07 ± 1.00 9.37 ± 1.41 0.298 PDW(%) 16.39 ± 1.11 16.19 ± 2.01 0.601 TP(g/L) 75.28 ± 3.23 71.15 ± 6.00* < 0.001 ALB(g/L) 45.62 ± 2.85 42.99 ± 4.08* 0.002 GLOB(g/L) 29.66 ± 3.23 28.16 ± 3.98 0.081 A/B 1.56 ± 0.22 1.56 ± 0.25 0.901 Tbil(µmol/L) 13.69 ± 4.94 13.27 ± 5.98 0.742 Dbil(µmol/L) 3.67 ± 1.25 3.72 ± 1.55 0.897 TBA(µmol/L) 4.42 ± 6.13 4.31 ± 3.97 0.924 ALT(U/L) 23.81 ± 11.69 21.80 ± 12.33 0.475 AST(U/L) 25.51 ± 6.55 24.15 ± 11.10 0.531 Urea(mg/dL) 5.47 ± 1.48 5.14 ± 1.45 0.329 CREA(µmol/L) 68.41 ± 18.49 62.62 ± 13.41 0.128 UA(µmol/L) 360.66 ± 106.87 316.26 ± 86.36 0.054 GLU(mmol/L) 4.89 ± 0.75 5.40 ± 1.10* 0.033 CHOL(mmol/L) 5.29 ± 1.17 4.67 ± 1.32 0.059 HDL-c(mmol/L) 1.37 ± 0.34 1.32 ± 0.46 0.606 LDL-c(mmol/L) 3.36 ± 0.76 2.96 ± 0.75* 0.042 HDL/TC 0.26 ± 0.05 0.27 ± 0.07 0.500 nonHDL-C(mmol/L) 3.92 ± 0.97 3.45 ± 0.81 0.059 Data were expressed as mean ± SD. P values were assessed using two-tailed unpaired t test with Welch's unequal variances t-test. * P < 0.05. Systolic Blood Pressure(SBP, in mmHg), Diastolic Blood Pressure(DBP, in mmHg), Ocular Perfusion Pressure (OPP, in mmHg), Intraocular Pressure (IOP, in mmHg), White Blood Cell count(WBC, in 10⁹/L), Red Blood Cell count(RBC, in 10¹²/L), Hemoglobin(Hb, in g/L), Platelet count(PLT, in 10⁹/L), Hematocrit(HCT, in%), Neutrophils(Neu, in 10⁹/L), Lymphocytes(Lym, in 10⁹/L), Eosinophils(Eos, in 10⁹/L), Monocytes(Mono, in 10⁹/L), Mean Corpuscular Volume(MCV, in fl), Mean Corpuscular Hemoglobin(MCH, in pg), Mean Corpuscular Hemoglobin Concentration(MCHC, in g/L), Red Cell Distribution Width(RDW, in%), Platelet Crit(PCT, in%), Mean Platelet Volume(MPV, in fl), Platelet Distribution Width(PDW, in%), Total Protein(TP, in g/L), Albumin(ALB, in g/L), Globulin(GLOB, in g/L), Albumin/Globulin ratio(A/B), Total Bilirubin(Tbil, in µmol/L), Direct Bilirubin(Dbil, in µmol/L), Total Bile Acids(TBA, in µmol/L), Alanine Aminotransferase(ALT, in U/L), Aspartate Aminotransferase(AST, in U/L), Urea(in mg/dL), Creatinine(CREA, in µmol/L), Uric Acid(UA,in µmol/L), Glucose(GLU, in mmol/L), Cholesterol(CHOL, in mmol/L), High-Density Lipoprotein Cholesterol(HDL-c, in mmol/L), Low-Density Lipoprotein Cholesterol(LDL-c, in mmol/L), High-Density Lipoprotein Cholesterol/Total Cholesterol ratio(HDL/TC), and Non-High-Density Lipoprotein Cholesterol(nonHDL-C, in mmol/L). Animals All animal experiments conformed to the relevant regulatory standards and the animal protocol was approved by the Animal Care and Use Committees at Central South University. The animals used in this study are C57BL/6J background. Erythrocyte-specific deletion of SphK1 mice ( SphK1 f/f /EpoR- Cre+ , eSphK1 −/− ) was generated as described previously 15 . All mice were kept under a regular rodent chow ad libitum and exposed to the standard 12 h light/12 h dark cycle. All experiments were performed on 6- to 8-week-old mice and assigned to experimental groups in a balanced manner to ensure approximately equal representation of both sexes. The glaucoma model establishment Ocular hypertension was induced using the magnetic microbead occlusion model 16 . Briefly, 2µL of 4.5 µm magnetic microbeads were injected into the anterior chamber of anesthetized mice using a bevelled glass microneedle. A handheld magnet was employed to guide the microbeads to the iridocorneal angle, ensuring sustained blockade of aqueous humor outflow and reproducible intraocular pressure elevation. For reagents delivery, intraperitoneal injections of PBS or 400 mg/kg L-carnitine were administered every other day. Mice were euthanized at 6 weeks post-injection for further examinations. All animal experiments were reviewed and approved by the Animal Care and Use Committee of the Laboratory Animal Research Center at the Xiangya Medical School of Central South University. Measurement of P50 For P50 measurement, 15 µL of erythrocyte was mixed with 3 mL of Hemox Buffer (TCS Scientific Corporation, PA), 5 µL of anti-foaming reagent (TCS Scientific Corporation, PA), and 5 µL of 22% BSA in PBS. This mixture was injected into the Hemox Analyzer (TCS Scientific Corporation, PA) to measure the oxygen equilibrium curve at 37°C. Erythrocyte ROS detection To detect erythrocyte ROS levels by flow cytometry, 1 µL of erythrocytes cells pellet was resuspended in 100 µL PBS and then incubated with ROS-sensitive fluorescent dye (100 µL,10 µM) (Reactive Oxygen Species Assay Kit, Biosharp, BL714A) at 37°C for 30 minutes in the dark. After incubation, excess dye is removed through 3 times PBS washing, and the cells are resuspended in 100 µL PBS for analysis. Stained samples were acquired for fluorescence in the fluorescein isothiocyanate (FITC) channel on a BD FACS Celesta cytometer and data were analyzed with FlowJo version 10.0.7. Data from at least 10,0000 cells per sample are collected and analyzed for assessment of ROS levels. SPHK1 activity assay Erythrocyte SPHK1 activity was determined as previously described 17 . Briefly, erythrocytes were lysed in a buffer containing 50 mM HEPES (pH 7.4), 15 mM MgCl2, 0.05% Triton X-100, and 10 mM KCl, along with protease inhibitors. erythrocytes lysate (100–300 µg) was then incubated with 5 µM NBD-sphingosine (Avanti 810205) in a reaction buffer (50 mM HEPES pH 7.4, 15 mM MgCl2, 0.05% Triton X-100, 10 mM KCl, 10 mM NaF, 1.5 mM semicarbazide, and 1 mM ATP) containing 1% fatty acid-free BSA, in a total volume of 100 µL. The reaction was conducted at 37°C for 30 minutes. Subsequently, the NBD-S1P lipid was extracted with 100 µL of 1 M potassium phosphate buffer (pH 8.5) and 500 µL of chloroform/methanol (2:1), followed by centrifugation at 15,000 rpm for 1 minute. Then, 100 µL of the supernatant was transferred to a 96-well fluorescence assay plate, and fluorescence was measured at 489/535 nm (excitation/emission) to quantify NBD-S1P levels using NBD-S1P standards. Metabolomics and lipidomic profiling Metabolomics analysis was performed as previously described 18 . All human blood samples were stored at -80°C until metabolomic analysis. Erythrocytes and plasma were extracted using a 1:10 and 1:25 dilution, respectively, in a cold solvent mixture of methanol, acetonitrile, and water (5:3:2 v/v/v ). All samples were vigorously vortexed for 30 minutes at 4°C, followed by centrifugation at 18,213 g for 10 minutes at 4°C to pellet insoluble materials. The supernatants were harvested and subjected to ultra-high-pressure liquid chromatography coupled with mass spectrometry (UHPLC-MS) using a Thermo Vanquish UHPLC system connected to a Thermo Q Exactive MS. The samples were randomized and analyzed in both positive and negative ion modes with injection volumes of 10 µL for red blood cells and 20 µL for plasma. UHPLC separations were carried out using water (Phase A) and acetonitrile (Phase B) with 0.1% formic acid for positive mode and 1 mM ammonium acetate for negative mode. A Kinetex C18 column (150 x 2.1 mm, 1.7 µm, Phenomenex) was used with a 5-minute gradient at a flow rate of 0.45 mL/min, a column temperature of 45°C, and a sample compartment temperature of 7°C. The solvent gradient conditions were as follows: 0-0.5 min at 5% B, 0.5–1.1 min at 5–95% B, 1.1–2.75 min hold at 95% B, 2.75-3 min at 95 − 5% B, and 3–5 min hold at 5% B. The mass spectrometer operated in full MS mode with a resolution of 70,000, a scan range of 65–900 m/z, a maximum injection time of 200 ms, 2 microscans, an automatic gain control (AGC) target of 3 x 10 6 ions, an electrospray voltage of 4.0 kV, a capillary temperature of 320°C, and nitrogen gas flows of 45 for sheath gas, 15 for auxiliary gas, and 0 for sweep gas. For indicated amino acid and S1P quantification, samples were prepared as previously described and operated in positive mode. Raw data files were converted to mzXML format using RawConverter (Scripps Research Institute) and analyzed with Maven (Princeton University). Relative quantification was performed based on the integrated peak areas of extracted ion chromatograms at the MS1 level. Instrument stability and quality control were maintained through replicate injections of a technical mixture every 10 runs. For the lipidomic analysis, 50 µL of human blood samples were processed for lipid extraction using a modified isopropanol (IPA) precipitation method. Each sample was placed in an Eppendorf tube, and 200 µL of IPA was added. The samples were vortex-mixed at room temperature for 10 minutes to ensure thorough mixing. Following vortexing, the samples were stored overnight at -20°C to enhance protein precipitation. The following day, the samples were centrifuged at 14,000g for 10 minutes. The resulting organic phase was carefully collected, and 200 µL of the organic solvent was dried using a vacuum centrifuge. The dried lipid extracts were then stored at -80°C until further analysis. Prior to MS analysis, the dried lipid extracts were reconstituted in 200 µL of a solvent mixture consisting of isopropanol, acetonitrile, and water in a 2:1:1 ratio (v:v). For the lipidomics analyses, lipids were separated on the reversed-phase column with a gradient elution, and MS/MS data were acquired in both positive and negative ion modes to ensure comprehensive lipid identification and quantification. Data analysis was performed using LipidSearch software to annotate lipid species based on accurate mass and fragmentation patterns. Glucose isotopically labeled flux tracing Erythrocytes were isolated from whole blood using EDTA anticoagulant, followed by three washes with 1× PBS. A 100 µl aliquot of erythrocytes was mixed with F-10 Nutrient Mix (Invitrogen) to achieve a hematocrit of 4%. The erythrocytes were incubated with 6mM 1,2,3- 13 C 3 -labeled glucose (Sigma-Aldrich) for 30 minutes at 37°C under normoxia conditions. Erythrocytes and supernatants were collected and analyzed using Vanquish ultra-high-performance liquid chromatography coupled with Q Exactive HF MS (Thermo Fisher, Bremen, Germany). Metabolite partitioning and isotope distribution were performed using Maven (Princeton, NJ). For in vivo isotope tracing experiment, mice were intravenously injected with 5% [U-13C 6 ]-glucose (5ml/kg body weight) (Sigma-Aldrich). Mice were euthanized and blood were collected through cardiac puncture after 30 minutes. Erythrocytes and plasma were extracted and processed as described above. Primary culture and treatment of retinal cells Prepare a digestion solution by supplementing DMEM with FBS and Collagenase Type II to achieve final concentrations of 10% FBS and 1 mg/mL Collagenase Type II. For every two retinas, prepare 500 µL of digestion solution and add to retinal tissue. Triturate gently five times, then incubate at 37°C with rotation for 30 minutes. Wash the tissue three times with PBS post-digestion. To establish an oxygen-glucose deprivation/reoxygenation (OGD/R) model, initiate oxygen-glucose deprivation by culturing cells in glucose-free DMEM within a hypoxia incubator chamber at 37°C under 0.5% O2, 94.5% N2, and 5% CO2 in presence of indicated concentration of S1P for 1 h. Subsequently, transfer the cells to normal medium and culture under standard conditions (95% air, 5% CO2, 37°C) for 1 day to induce reoxygenation. Electroretinogram (ERG) and visual evoked potential (VEP) detection Prior to examination, the animals were adapted to darkness for more than 12 hours. The mice were anesthetized with 1% pentobarbital sodium, and their pupils were fully dilated. The mice were then positioned prone on the operating table, with a heating pad maintaining a temperature of 37°C. Carboxymethyl cellulose eyedrops were applied to both eyes to maintain corneal moisture. The testing environment was kept dark and illuminated with red light. Two corneal ring electrodes and three needle electrodes were prepared for the procedure. The electrodes were placed as follows: bilateral recording electrodes were positioned in contact with the cornea, with carboxymethyl cellulose eyedrops applied to enhance current conduction and maintain corneal moisture. Reference electrodes were inserted subcutaneously on both side of the nose, while the ground electrode was inserted subcutaneously at the tail. Stimulation and detection were conducted in accordance with ISCEV standards 19 . After detection, the amplitude and peak time of the a-wave and b-wave for each group were analyzed. For VEP detection, mice were anesthetized with 1% pentobarbital sodium. Carboxymethyl cellulose eyedrops were applied to maintain corneal moisture. Subcutaneous needle electrodes were placed at the occipital midpoint (recording electrode), nose (reference electrode), and tail (ground electrode). Following international standards, one eye was covered while recordings were performed, then repeated for the contralateral eye. Mouse Blood Pressure Measurements Systolic blood pressure (SBP) was recorded non-invasively with the CODA High-Throughput tail-cuff system (Kent Scientific, Torrington, CT) before and after osmotic-pump implantation, following previously protocols 20 . Mice were housed in a temperature-controlled chamber (37°C) and systolic blood pressure was monitored by tail-cuff plethysmography. Baseline recordings were obtained immediately prior to osmotic mini-pump implantation; subsequent measurements were performed continuously at defined post-surgical intervals. Each recording session consisted of 25 automated inflation–deflation cycles; the initial five cycles were discarded to allow acclimatization, and the remaining 20 cycles were averaged to yield the final systolic blood pressure value for analysis. Flow cytometry To prepare a single-cell suspension from retinal tissue, we followed a previously described method 21 . Specifically, we processed retinas in pairs. For each pair, we prepared a 500 µL digestion solution by mixing DMEM with a final concentration of 10% fetal bovine serum (FBS) and 1 mg/mL collagenase. The solution was then mixed thoroughly and warmed to 37°C using a water bath. Next, the retinal cells were stained with surface antibody anti-Thy1 (Biolegend, clone 53 − 2.1) and incubated the cells for 25 minutes on ice. Following surface staining, the cells were fixed and permeabilized using the Transcription Factor Staining Buffer Kit (Tonbo Biosciences) according to the manufacturer's instructions. This step allowed for intracellular staining of the following antibodies: anti-RBPMS (Abcam, ab152101), anti-AMPKα Phospho (Thr172) (Biolegend, A20017A), anti-CPT1A (Proteintech, 5D8G9), anti-CPT2 (Proteintech, 26555-1-AP), and Cleaved Caspase-3 (Asp175) (Cell Signaling Technology, #9661). The cells were incubated with these antibodies in permeabilization buffer on ice for at least 30 minutes. Finally, the stained cells were acquired using a BD FACS Celesta flow cytometer and analyzed using FlowJo software version 10. Western blot Erythrocyte membrane protein was extracted as described previously 20 , briefly, fresh erythrocytes were washed three times with cold PBS. A 100 µL erythrocytes pellet was lysed in 5 mL of 0.4% NaCl supplemented with 1X protease inhibitors (ThermoFisher) and phosphatase inhibitors (Roche), then incubated on ice for 15 minutes with intermittent vortexing. The lysate was centrifuged at 500g for 10 minutes at 4°C. After discarding the supernatant, 5 mL of 0.4% NaCl containing 1X protease and phosphatase inhibitors was added, followed by vortexing and centrifugation at 500g for 10 minutes at 4°C. This centrifugation step was repeated five times in total. The final pellet was resuspended in 100 µL of RIPA buffer and sonicated twice for 10 seconds each. The lysate was then incubated on ice for 30 minutes, followed by centrifugation at 15,000 x g for 10 minutes at 4°C. The resulting supernatant was collected and stored at -80°C for future use. Total erythrocyte protein was extracted by lysing cells in H₂O at a 1:10 volume ratio with 1X protease inhibitor cocktail (Roche, #11697498001), 1X phosphatase inhibitor cocktail (Roche, #04906837001), and 10 µM MG132 (Santa Cruz, #sc-201270) or 1 µM Bortezomib (Santa Cruz, #sc-217785) as proteasome inhibitors. Following lysis, 10X PBS was added to the lysate to neutralize the buffer. Protein concentration was measured using the BC A Protein Assay Kit (Pierce). Indicated protein samples were then boiled in Laemmli Sample Buffer (Bio-Rad) for 10 minutes at 95°C, separated on a 10% SDS-PAGE gel, and transferred onto a nitrocellulose membrane for further analysis. Western blotting was performed using primary antibodies MFSD2B (Invitrogen, #PA5-21050, 1:500), BPGM (Proteintech, #17173-1-AP, 1:1,000), GAPDH (Invitrogen, # PA1-987, 1:1,000), ubiquitin antibody (CST, #3936S, 1:500) and b-actin (Proteintech, 66009-1-PBS, 1:2000) in Odyssey Blocking Buffer with 0.2% Tween 20, followed by incubation with secondary antibodies from Abiowell (Goat anti-Rabbit IgG (H + L), AWS0002, 1:10000; Goat anti-Mouse IgG (H + L), AWS0001, 1:10000). The blots were scanned using the Odyssey Imaging System. Immunoprecipitation Immunoprecipitation (IP) was performed in a 0.5 mL IP solution containing protein lysate and IP buffer (50 mM Tris-HCl, pH 7.5, 150 mM NaCl, and 1% Triton X-100), supplemented with protease inhibitors and 20 mM N-ethylmaleimide. Procedures followed the protocol from BeyoMag Protein A/G Beads Kit (Beyotime, #P2108). Briefly, 3 µg of MFSD2B (Invitrogen, #PA5-21050) was incubated with pre-washed beads in the IP solution, rotating for 2 hours at room temperature. The beads were then washed three times by applying a magnetic field for 10 seconds each. Washed beads were added to 150 µL of protein lysate (1 µg/µL) and incubated overnight at 4°C. After incubation, the beads were isolated with a magnetic field for 30 seconds, and the supernatant was saved as a negative control. The bead pellets were then washed three times, each wash lasting 5 minutes. The IP proteins were eluted by boiling the beads in 30 µL of 2X Laemmli Sample Buffer (Bio-Rad, #1610737) at 100°C for 10 minutes. The supernatant was then collected by applying a magnetic field for 30 seconds, followed by separation on 10% SDS-PAGE gels for Western blot analysis. Immunofluorescence staining The mouse eyeball was fixed in 4% paraformaldehyde for 60 minutes, followed by dissection to isolate the retinal tissue. Retinal tissues were blocked with 0.5% Triton X-100 and 2% goat serum in PBS for 1.5 hours at room temperature to permeabilize the tissue and block nonspecific binding. The tissues were then incubated with primary antibody RBPMS (Abcam, ab152101, 1:200) overnight at 4°C. The next day, sections were washed in PBS and incubated with Alexa Fluor 488-conjugated goat anti-rabbit IgG (Invitrogen, A11008) for 2 hours at room temperature in the dark. Afterward, the sections were rinsed thoroughly in PBS, counterstained with DAPI for 5 minutes at room temperature, and washed four times with PBS. Images were captured using fluorescence microscopy, and staining intensity for the target protein was quantified using ImageJ. Toluidine blue Fresh retinal samples were carefully excised into 1 mm³ pieces and immediately fixed in EM fixative at 4°C. After washing with 0.1 M phosphate buffer (PB, pH 7.4), the tissue was post-fixed with 1% osmium tetroxide in PB, dehydrated through graded ethanol and acetone, and embedded in 812 resin. Polymerization was performed at 60°C for 48 hours. Semi-thin sections (1.5 µm) were cut, stained with 1% toluidine blue, and mounted for light microscopy observation. RGC axons were quantified by using ImageJ with the AxonJ plugin. Anterograde axon transport assay Anterograde axon transport assay was performed as previously described 20 . Briefly, mice were anesthetized (ketamine/xylazine) and intravitreally injected with 2 µL Alexa Fluor 555-conjugated cholera toxin subunit B (CT-B; 1 mg/mL in PBS) (Thermo Fisher Scientific). After 72 h, mice were perfused with 4% PFA, and brains/eyes were postfixed (24 h), cryoprotected (30% sucrose), OCT-embedded, and sectioned (20 µm). Alexa Fluor 555 signal was imaged (Zeiss LSM880) in the dorsal lateral geniculate nucleus (LGN) and superior colliculus (SC). CTB intensity was quantified using ImageJ (mean pixel intensity). UK biobank database From UK biobank database, participants with pre-existing infectious diseases, cancer, or glaucoma at baseline were excluded, and newly diagnosed POAG cases were identified using the ICD-10 diagnosis of ‘primary open-angle glaucoma,’ ‘other glaucoma,’ or ‘unspecified glaucoma’ during the follow-up period. Specifically, we identified individuals with glaucoma at baseline (larger than 100,000 cases) based on the following criteria: (i) an ICD-10 diagnosis of ‘primary open-angle glaucoma,’ ‘other glaucoma,’ or ‘unspecified glaucoma’ prior to inclusion; (ii) a positive response to the question, ‘Has a doctor told you that you have any of the following eye problems?’; or (iii) a response of ‘glaucoma’ to the question, ‘In the touchscreen, you indicated that a doctor told you about other serious illnesses or disabilities. Could you specify what they are? (non-cancer illnesses)’. Although this definition of glaucoma is broad, approximately 80% of glaucoma cases in white British individuals are likely to meet the diagnostic criteria for POAG 22 . The number of ICD-10 POAG cases was significantly lower, reducing statistical power. Finally, we also identified individuals diagnosed with glaucoma based on an ICD-10 code after cohort inclusion. The control group, comprising 218,331 individuals, was meticulously selected by excluding a total of 66,722 cases based on the following specific criteria: 1. Diabetes-related ocular pathologies. 2. Glaucoma. 3. Visual impairment due to injury or trauma. 4. Cataracts. 5. Macular degeneration. 6. Other significant ocular conditions. 7. Participants who opted not to disclose their eye health status. 8. Participants who were unaware of their eye health status. Statistical analysis All data were presented as mean ± standard deviation. A Student’s t-test was used for comparing two independent samples, while one-way ANOVA followed by Tukey’s post hoc test was applied for multiple group comparisons. Parametric analyses (Student’s t-tests and one-/two-way ANOVA) were applied only after the underlying distributional assumptions had been formally verified. Statistical analyses were conducted using GraphPad Prism 10.0 software. A p -value of < 0.05 was considered statistically significant. Results Erythrocyte Metabolic Reprogramming in Glaucoma Enhances Oxygen Release at the Cost of Redox and Energy Homeostasis To provide insights into the oxygen supply in glaucoma conditions, we measured oxygen release from erythrocytes via detecting P50 (the oxygen tension corresponding to 50% saturation) value of glaucoma and healthy control erythrocytes (Fig. 1 A). Notably, we observed a significant correlation between the oxygen release capacity from erythrocytes, denoted as P50, and the severity of glaucomatous optic nerve damage in patients. Specifically, P50 values demonstrated a positive correlation with Mean Deviation (MD) values (r = 0.4674, p = 0.014) of visual field, indicating that higher P50 values are associated with less visual field loss. Conversely, P50 values exhibited a negative correlation with the Cup-to-Disc (C/D) ratio 23 (r = -0.5461, p = 0.0032), suggesting that higher P50 values are linked to a smaller C/D ratio, which corresponds to less severe optic nerve damage (Fig. 1 B). This finding demonstrated that enhanced oxygen release from erythrocyte in glaucoma patients, which is a compensatory an adaptive response to the increased oxygen demands or hypoxic stress seen in glaucoma 24 , 25 . Enhanced oxygen release in erythrocytes is often linked to shifts in key metabolic pathways, such as the glycolytic pathway and the RL shunt 26 . To understand the mechanisms driving the enhanced oxygen release observed in glaucoma erythrocytes, we performed high throughput untargeted metabolomics profiling of erythrocytes and plasma collected from glaucoma patients and age/sex-matched healthy controls. The results of PLSDA analysis performed by MetaboAnalyst 6.0 ( http://www.metaboanalyst.ca ) showed healthy control and the glaucoma group could be well distinguished based on metabolite characteristics (Fig. 1 C). In detail, a total of 300 metabolites were identified and 138 differential metabolites from erythrocytes and 86 differential metabolites from plasma, respectively, were identified based on VIP > 1, P < 0.05 criteria ( Table S2 ). For pathway enrichment analysis, we used the MetaboAnalyst 6.0 pathway analysis module, employing the hypergeometric test for over-representation analysis and relative-betweenness centrality for pathway topology analysis, with the Kyoto Encyclopedia of Genes and Genomes (KEGG) human metabolic pathway library as the reference database. The background set for enrichment analysis consisted of all quantified metabolites detected in our untargeted metabolomics dataset, ensuring comprehensive representation of the metabolic landscape in erythrocytes and plasma. The analysis revealed that differential metabolites were significantly enriched in purine metabolism, glutathione metabolism, sphingolipid metabolism, glycolysis, and the pentose phosphate pathway (PPP). These metabolic pathways are closely related to the regulation of oxygen release, energy balance, fatty acid synthesis and the homeostasis of ROS in erythrocytes 27 , 28 (Fig. 1 D and S1A-B). Glycolysis is the most important metabolic pathway for erythrocytes, providing the necessary ATP for their survival and function. Notably, most glycolytic intermediates, including fructose 1,6-bisphosphate (FBP), 3-phosphoglycerate (3PG), and pyruvate (PYR), were significantly reduced in glaucoma erythrocytes, however, our quantitative analysis revealed a significant increase in 2,3-bisphosphoglycerate (2,3-BPG) levels in glaucoma erythrocytes (Fig. 1 E), a key product of the RL shunt known to facilitate oxygen release from erythrocytes 29 . Under hypoxic conditions, up to 25% of glucose in erythrocytes is directed through the RL shunt within glycolysis, rather than PPP, to increase 2,3-BPG production 30 . Thus, our findings raise a possibility that, as demand of oxygen from tissues, such as retina and optic nerve head 8 , 9 , in glaucoma conditions, increased 2,3-BPG production is under regulation by channeling glucose metabolism toward RL shunt within glycolysis versus PPP in glaucoma erythrocytes to enhance oxygen release. To test this intriguing hypothesis, we performed in vitro glucose flux analysis using isotopically labeled 1,2,3- 13 C 3 -glucose in both control and glaucoma erythrocytes. This allowed tracking of glucose uptake, metabolic routing, and reprogramming in primary erythrocytes. Consistent with metabolomics profiling, the data from glucose isotopically labeled flux tracing revealed a notable increase in glycolytic flux towards 2,3-BPG via the RL shunt in glaucoma erythrocytes (Fig. 1 F). Mechanistically, we observed significant elevated protein levels of Bisphosphoglycerate Mutase (BPGM), which is the enzyme that is responsible for the production of 2,3-BPG through the RL shunt, in glaucoma erythrocytes (Fig. 1 G). Consequently, lower levels of glycolysis and PPP caused defective energy homeostasis, as determined by adenylate pool ( Figure S1 C ), and impaired oxidative balance, as indicated by higher ROS levels and reduced glutathione (GSH) to oxidized glutathione (GSSG) ratio (Fig. 1 H), in glaucoma erythrocytes. Additionally, our data suggested that glucose uptake was significantly lower in glaucoma erythrocytes compared to controls, as evidenced by reduced levels of labeled glucose inside glaucoma erythrocytes and increased labeled glucose remaining in the supernatant after 30 minutes of incubation (Figs. 1 F and I ). We further confirmed significantly increased plasma glucose levels in glaucoma patients (Fig. 1 J and Table 1 ). Thus, these results prompted us to examine the glucose transporter GLUT1 in control and glaucoma erythrocytes. Consistently, GLUT1 protein levels were reduced in glaucoma erythrocytes compared to controls (Fig. 1 K). Altogether, we provide human evidence that glaucoma pathogenesis involves a systemic recalibration of erythrocyte metabolism. This reprogramming prioritizes oxygen release, driven by BPGM-mediated enhancement of the RL shunt, to satisfy heightened tissue demand. However, this adaptation forces a detrimental trade-off, ultimately undermining the erythrocyte's own energy stability and oxidative resilience (Fig. 1 L). Defective MFSD2B Transporter Drives Erythrocyte S1P Dyshomeostasis in Glaucoma Our comprehensive metabolomic analysis, encompassing both untargeted metabolomics and quantitative analysis revealed significant alterations in the erythrocyte metabolome of glaucoma patients. Interestingly, we found elevated intracellular levels of sphingosine 1-phosphate (S1P) across both POAG and PACG erythrocytes (Figs. 2 A-B and S2A). S1P as an erythrocyte enriched biolipid is well known to enhance oxygen delivery under hypoxia, suggesting a potential adaptive mechanism in glaucoma similar to that observed in other hypoxic states 15 , 31 . The observed reduction in ceramide and sphingosine levels (Figs. 2 C and S2B), the metabolic precursors to S1P, prompted us to assess sphingosine kinase activity. We found that SPHK1, the sole sphingosine kinase in erythrocytes 31 , exhibited significantly increased activity in glaucoma (Fig. 2 D), demonstrating enhanced intracellular S1P biogenesis. Interestingly, accurate quantification revealed that plasma S1P levels were markedly reduced despite elevated intracellular S1P levels in erythrocytes, suggesting impaired S1P release under glaucomatous conditions, affecting both POAG and PACG (Figs. 2 E-F and S2C). To address this, we assessed MFSD2B, the primary erythrocyte S1P transporter 32 , and found significantly reduced membrane MFSD2B levels in glaucoma erythrocytes (Fig. 2 G). Further investigation revealed that ubiquitination, a key process for modifying protein levels and functions in erythrocytes, was significantly increased for membrane MFSD2B in glaucoma erythrocytes (Fig. 2 H). Thus, we revealed that increased erythrocyte SphK1 activity and reduced MFSD2 protein are dual mechanisms underlying accumulation of intracellular S1P but substantially reduction of circulating S1P in glaucoma patients. More importantly, we observed a positive correlation between plasma S1P levels in glaucoma patients and the thickness of the retinal nerve fiber layer (RNFL) (Fig. 2 I), a parameter that is closely associated with the density of RGCs 33 . This finding aligns with previous studies indicating that S1P signaling is essential for RGC survival 34 , 35 . Given our findings of elevated SphK1 in erythrocytes in glaucoma patients, we prompted to conduct proof-of-principle genetic studies to determine the role of erythrocyte SphK1-mediated production of both intracellular and plasma S1P using erythrocyte-specific SphK1 knockout mice (eSphK1 −/− ) . Consistent with previous study 15 , under normal physiological conditions, the baseline P50 levels showed no significant differences between young (3 months-old) and aged (14 months-old) eSphK1 −/− mice and their SphK1 flox control counterparts ( Figure S2D ). However, eSphK1 −/− mice exhibited a significant reduction in RGC density. Additionally, aged eSphK1 −/− mice displayed elevated IOP compared to controls (Fig. 2 J-K and S2E). These results demonstrate that proper S1P release from erythrocytes is essential for the protection of RGCs. L-Carnitine Restores Erythrocyte Membrane Integrity and Redox Balance via the Lands cycle and PPP Since the protein levels of both MFSD2B and GLUT1 in erythrocyte membranes were significantly reduced under glaucoma conditions (Fig. 1 K), we hypothesized that membrane integrity of glaucoma erythrocytes was compromised. Given that ROS potentially induce lipid peroxidation 36 and increased in glaucoma erythrocytes (Fig. 1 H), and lipid peroxidation product 9-oxononanoic acid 37 also increased in glaucoma erythrocytes (Fig. 3 A). Using BODIPY 581/591 C11, we confirmed increased membrane lipid peroxidation in glaucoma erythrocytes (Fig. 3 B), indicating that glaucoma-associated oxidative stress induces ROS, leading to lipid peroxidation and impairing membrane protein integrity 38 . To further investigate lipid peroxidation, which preferentially oxidizes polyunsaturated phosphatidylcholines (PUFA-PCs) than saturated fatty acid phosphatidylcholines (SFA-PC) 39 , we conducted a lipidomic analysis. This revealed a marked decrease in the ratio of key PUFA-PCs (including PC (16:0_20:4) and PC (16:0_22:6)) to the SFA-PC(16:0_16:0) (Fig. 3 C). This signature lipid profile confirms that glaucoma erythrocytes undergo significant lipid peroxidation. The Lands cycle is critical for maintaining erythrocyte membrane integrity by remodeling phospholipids 40 . Lipidomic analysis also revealed reduced levels of lysophosphatidylcholine (LPC) and phosphatidylcholine (PC) species in glaucoma erythrocytes ( Figure S3A ), with no significant change in the sum LPC-to-PC ratio ( Figure S3B ), suggesting that the activities of phospholipase A2 (PLA2) and lysophosphatidylcholine acyltransferase (LPCAT), are likely unaffected by glaucoma conditions 41 . However, the LPC(16:0)/PC(16:0) ratio, a key indicator of membrane repairing regulated by acyl-CoA 42 , 43 , was significantly altered (Fig. 3 D), indicating defective membrane repair due to impaired conversion of LPC(16:0) to PC(16:0). Although erythrocytes lack fatty acid β-oxidation capacity, carnitine-dependent acyl-carnitine pools is essential for fueling the Lands cycle for damaged membrane lipid repair 44 . Quantitative metabolomics analysis revealed decreased levels of L-carnitine, in both erythrocytes and plasma of glaucoma patients (Figs. 3 E), alongside a deficient acyl-carnitine pool (Fig. 3 F). These findings suggest that impaired Lands cycle activity in glaucoma erythrocytes potentially results from reduced carnitine-derived acyl-carnitine. To investigate this, we cultured glaucoma patient erythrocytes in 20% autologous plasma and treated them with 100 µM L-carnitine for 6 hours. This treatment significantly potentiated the LPC-to-PC conversion of the Lands cycle (Figs. 3 G and S3C), which consequently restored MFSD2B protein expression on the erythrocyte membrane (Fig. 3 H) and increased S1P release into the culture supernatant (Fig. 3 I). Concurrently, L-carnitine treatment improved glucose metabolism. We observed a modest recovery of GLUT1 protein levels (Fig. 3 J) and a significant increase in glucose uptake (Fig. 3 K). More importantly, L-carnitine redirected glucose flux into the pentose phosphate pathway (PPP), which was associated with a marked improvement in redox homeostasis, as evidenced by reduced ROS levels and an increased GSH/GSSG ratio (Figs. 3 L-M). To determine if the antioxidant effect of L-carnitine was dependent on the PPP, we also treated erythrocytes with the PPP inhibitor 6-aminonicotinamide (6AN) 45 . The blockade of PPP flux completely abrogated L-carnitine's ability to reduce ROS in glaucoma erythrocytes (Fig. 3 N). Subsequently, we found that L-carnitine's reduction of ROS-induced membrane lipid peroxidation was also dependent on the PPP, as this protection was nullified by 6AN (Fig. 3 O). L-carnitine Modulates Erythrocyte Homeostasis and Restores Circulating S1P Levels in Glaucoma Models To evaluate the therapeutic potential of L-carnitine, we employed a chronic glaucoma (cGLA) model induced by magnetic bead occlusion, which elicited a sustained intraocular pressure (IOP) elevation (Fig. 4 A and S4A). This model recapitulated key systemic features of human glaucoma, including elevated systolic blood pressure and a pro-inflammatory leukogram with peripheral neutrophilia ( Figure S4B-C , Table 1 ). Furthermore, circulating erythrocytes exhibited enhanced oxygen release, mirroring our observations in glaucoma patients, after constant IOP elevated ( Figure S4D ). These concordant systemic findings corroborate the translational relevance of our cGLA paradigm for evaluating therapeutic interventions targeting both intra-ocular pathology and associated systemic sequelae. In SphK1 flox cGLA mice, L-carnitine slightly reduced IOP but restored the compensatory erythrocyte oxygen release, a response that was absent in eSphK1 −/− mice, confirming the essential role of S1P in this hypoxic adaptation Although IOP was only slightly reduced by L-carnitine in SphK1 flox cGLA mice, treatment restored compensatory oxygen release, a response absents in eSphK1 −/− mice, confirming S1P’s role in hypoxia adaptation (Figs. 4 A-B and S4E). Metabolomic profiling of erythrocytes revealed a significant depletion of L-carnitine and long-chain acylcarnitines (C16, C18) in cGLA, which were replenished by L-carnitine treatment (Fig. 4 C). This restoration of acyl-carnitine pools is poised to fuel the Lands cycle for membrane lipid repair. Accordingly, L-carnitine maintained membrane expression of the S1P transporter MFSD2B, which is defective in cGLA, without altering SphK1 activity (Figs. 4 D-E). This led to a significant restoration of circulating S1P levels (Fig. 4 F). Concurrently, L-carnitine restored GLUT1 expression (Fig. 4 G) and enhanced glucose uptake, preferentially directing flux into the PPP over glycolysis (Figs. 4 H-I). This metabolic shift attenuated oxidative stress, as shown by reduced ROS levels and an improved GSH/GSSG ratio (Figs. 4 J-K), and decreased ROS-induced lipid peroxidation and their products (Fig. 4 L and S4F). The ATP/ADP ratio in cGLA erythrocytes was also partially restored (Fig. 4 M). As a result, L-carnitine preserved erythrocyte integrity and prolonged circulating erythrocytes survival, thereby reversing the anemia and erythrocyte depletion consistently reported in human glaucoma (Fig. 4 N). Collectively, our in vitro and in vivo data support a mechanistic model wherein L-carnitine replenishes acyl-carnitine pools to fuel the Lands cycle, thereby repairing membrane proteins like MFSD2B and GLUT1. This repair facilitates S1P release and glucose uptake, with the latter being channeled into the PPP to bolster antioxidant defenses and inhibit lipid peroxidation to prevent further membrane compromise (Fig. 4 O). L-Carnitine Preserves RGC Survival and Function via S1P-Dependent Manners in Glaucoma Models To further evaluate the neuroprotective effects of L-carnitine on RGCs in IOP-induced damage, hematoxylin-eosin (HE) staining of the anterior chamber angle revealed magnetic bead accumulation and demonstrated significant thinning of the RNFL and loss of RGCs in SphK1 flox cGLA mice compared to normal controls (Fig. 5 A). L-carnitine treatment significantly reduced RGC loss and preserved anterograde axoplasmic transport, assessed by cholera toxin B (CTB) tracing to the dorsal lateral geniculate nucleus (LGN) and superior colliculus (SC), in SphK1 flox cGLA mice but not in eSphK1 −/− cGLA mice (Figs. 5 B-D). Electrophysiological assessments further elucidated L-carnitine’s neuroprotective effects. Flash visual evoked potentials (FVEP), which reflect the functional integrity of the visual pathway from retina to occipital cortex, showed prolonged P1 latency and reduced N1-P1 amplitude in SphK1 flox cGLA mice, indicative of axonal damage and reduced RGC numbers or visual pathway dysfunction, respectively (Fig. 5 E). L-carnitine treatment significantly shortened P1 latency and increased N1-P1 amplitude in SphK1 flox cGLA mice, but not in eSphK1 −/− cGLA mice, highlighting S1P-dependent restoration of visual pathway function (Fig. 5 E). Flash electroretinography (FERG), assessing overall retinal function, revealed significantly reduced a-wave (photoreceptor function) and b-wave (inner retinal layer function) amplitudes in SphK1 flox cGLA mice (Fig. 5 F). L-carnitine treatment mitigated these deficits in SphK1 flox cGLA mice, preserving overall retinal function (Fig. 5 F). Given that plasma S1P remains significantly deficient in eSphK1 −/− cGLA mice despite L-carnitine treatment (Fig. 4 F), while oxygen release is comparably restored in both SphK1 flox and eSphK1 −/− cGLA treated with L-carnitine ( Figure S4E ), we suggest that the differential therapeutic efficacy of L-carnitine is primarily attributable to the restoration of systemic S1P, rather than the improvement in oxygen delivery. S1P Supports RGCs by Enhancing Fatty Acid β-Oxidation to Restore TCA Cycle and ATP Production To elucidate the mechanism by which erythrocyte-derived S1P mediates RGCs survival in L-carnitine-treated glaucoma, we analyzed retinal metabolism in the cGLA model. Metabolomic profiling revealed a pronounced bioenergetic deficit in cGLA retinas, characterized by significantly depleted TCA cycle intermediates and ATP levels, alongside reduced pyruvate and elevated lactate, a profile indicative of a forced shift toward anaerobic glycolysis despite adequate glucose. L-carnitine treatment effectively restored TCA cycle metabolites and ATP (Figs. 6 A and B ). However, isotopic glucose tracing confirmed that the glycolytic flux toward lactate persisted despite treatment, demonstrating that the restoration of the TCA cycle was not fueled by glucose-derived pyruvate (Fig. 6 C). This pointed to fatty acid β-oxidation (FAO) as an alternative source of acetyl-CoA. Indeed, the restoration of TCA cycle intermediates by L-carnitine was entirely absent in the RGCs of eSphK1 −/− cGLA mice, indicating a strict dependence on erythrocyte-derived S1P for this metabolic rescue (Figs. 6 D, S5A). We then investigated the carnitine shuttle, a prerequisite for FAO. While L-carnitine and its long-chain fatty acid substrates (e.g., palmitic acid) were not deficient in cGLA RGCs (Figs. 6 E, S5B), a critical divergence was observed upon L-carnitine treatment: only in SphK1 flox mice did we detect a significant accumulation of long-chain acylcarnitines (C16, C18) with a concomitant consumption of their fatty acid substrates (Figs. 6 E-F, S5B). This specific metabolic signature, successful substrate conversion only in the presence of erythrocyte SPHK1, identifies the esterification of long-chain fatty acids into acylcarnitines, the CPT1A-mediated rate-limiting step of FAO, as the S1P-dependent bottleneck. Guided by single-cell RNA-seq data showing high expression of CPT1A and S1PR1/2 in RGCs ( Figure S5C ), we found that L-carnitine treatment robustly increased CPT1A, but not CPT2, protein expression in RGCs, an effect that was abolished in eSphK1 −/− mice (Fig. 6 G and S5D). This established that erythrocyte-derived S1P is essential for upregulating CPT1A. Mechanistically, S1P treatment directly enhanced the phosphorylation of AMPKα (Thr172) in RGCs under oxygen-glucose deprivation/reperfusion conditions (Fig. 6 H). Furthermore, both pharmacological AMPKα activation and inhibition demonstrated that S1P induce CPT1A expression is regulated through an AMPKα-dependent pathway 46 , 47 (Fig. 6 I), which was strongly correlated with AMPKα phosphorylation levels ( Figure S5E ). Functionally, this S1P-AMPKα-CPT1A axis was essential for bioenergetic and survival outcomes. S1P treatment boosted ATP generation and prevented apoptosis in stressed RGCs, in the presence of L-carnitine (Fig. 6 J, S5F). Critically, translating these findings to a human context, we showed that plasma from glaucoma patients failed to protect murine RGCs in stress culture. L-carnitine alone provided only a modest benefit, but the combination of L-carnitine and S1P robustly prevented RGC death under oxygen-glucose deprivation (Fig. 6 K). In summary, we define a coherent neuroprotective pathway wherein L-carnitine-stimulated erythrocyte S1P release activates an S1PR1-AMPKα-CPT1A signaling axis in RGCs. This enhances the utilization of L-carnitine for fatty acid β-oxidation, restoring mitochondrial energy production and preventing apoptosis, thereby salvaging RGCs in glaucoma (Fig. 6 L). S1P is a Newly Identified Biomarker in Primary Glaucoma Patients Our findings highlight that glaucoma is not just a localized ocular disease but a systemic condition marked by extensive metabolic and lipid reprogramming in both erythrocytes and plasma. Plasma metabolites, which provide insights into dynamic metabolic states, serve as important indicators for assessing glaucoma’s systemic impact. To validate our findings, we took advantage of analyzing the UK Biobank data using NMR-based metabolomics data from more than 100,000 individuals. Intriguingly, strong associations between specific metabolites and the risk of POAG, as determined by Cox proportional hazards regression adjusted for age, sex, and BMI. Notably, protective metabolites, including citrate, lactate, and pyruvate, were associated with a reduced POAG risk (Odds ratio (OR) < 1.0), while higher levels of metabolites including tyrosine, glucose, phenylalanine, valine, leucine, isoleucine, branched-chain amino acids (BCAAs), and glutamine were associated with an increased POAG risk (OR > 1.0) (Figs. 7 A and S6A). Targeted metabolic profiling of our glaucoma cohort corroborated these findings, showing reduced levels of protective metabolites (e.g., lactate, pyruvate) and elevated levels of risk-associated metabolites (e.g., glucose, tyrosine, phenylalanine, valine, glutamine) in glaucoma patient plasma compared to controls (Figs. 7 B and S6B-C). This alignment between datasets strengthens the validity of our metabolomic findings and underscores the potential of these metabolic signatures as indicators of glaucoma’s systemic pathology. To identify novel biomarkers for glaucoma, we applied a random forest-based biomarker discovery approach using metabolomic profiles from erythrocytes and plasma. This analysis revealed the top 10 candidate biomarkers, prominently highlighting L-arginine with area under the curve (AUC) of 78 in erythrocytes and 98 in plasma, aligning with previous studies 48 , 49 . Additionally, we found S1P showed strong biomarker potential, with AUC values of 74 in erythrocytes and 99 in plasma (Fig. 7 C). Further pathway analysis of lipid metabolites from both control and glaucoma erythrocyte and plasma identified sphingosine metabolism as significantly enriched, emphasizing its possible involvement in glaucoma pathogenesis (Fig. 7 D). In conclusion, our findings emphasize that glaucoma extends beyond a localized ocular disorder to involve systemic metabolic alterations, underscoring its complex pathophysiology. Our data, validated between the UK Biobank and our own cohort, reinforces the robustness of these metabolic signatures. Furthermore, S1P emerged as a robust biomarker, showing strong diagnostic potential with high AUC values, suggesting it may serve as a valuable indicator for early detection and monitoring of glaucoma. The enrichment of the sphingosine metabolic pathway in glaucoma-affected samples further highlights the importance of S1P metabolism in disease progression and offers promising targets for therapeutic intervention. Furthermore, the significant reduction in L-carnitine and acyl-carnitine levels, particularly acyl-C18:2-OH (Fig. 7 C), in erythrocytes suggests their utility as additional diagnostic indicators for the early detection and monitoring of glaucoma. Together, these insights advance our understanding of glaucoma's systemic nature and provide a foundation for biomarker-driven diagnostics and targeted metabolic therapies. Discussion This study establishes that glaucoma fundamentally reprograms erythrocyte metabolism, shifting glycolytic flux toward the Rapoport-Luebering shunt via elevated BPGM. While this adaptation enhances oxygen release (increased P50) to counter retinal hypoxia, it occurs at the expense of pentose phosphate pathway activity, compromising antioxidant defenses and promoting lipid peroxidation. Concurrent deficiencies in L-carnitine and acylcarnitine pools impair the Lands cycle, preventing repair of membrane transporters MFSD2B and GLUT1. The resulting trapped intracellular S1P and reduced glucose uptake create a vicious cycle: impaired erythrocyte glucose metabolism contributes to systemic glucose dysregulation, potentially explaining the glaucoma-diabetes comorbidity 50 , 51 , while S1P deficiency exacerbates retinal ganglion cell loss. Notably, L-carnitine administration reverses this pathology through a coordinated mechanism: replenishing acyl-carnitine pools to fuel Lands cycle-mediated membrane repair, restoring S1P release and glucose uptake. The redirected glucose flux through the PPP enhances antioxidant capacity, while circulating S1P induces the AMPKα-CPT1A axis, promoting fatty acid oxidation and restoring mitochondrial function in RGCs in glaucoma conditions. Particularly, the genotype-specific efficacy of L-carnitine, observed in SphK1 flox but not eSphK1 −/− mice, definitively establishes S1P as a central mediator of this protection. The observed metabolic shift toward anaerobic glycolysis and impaired oxidative phosphorylation, indicated by reduced pyruvate, depleted TCA cycle metabolites, and increased lactate in cGLA retina, aligns with prior reports of mitochondrial dysfunction in glaucoma 52 . The correlation between AMPKα phosphorylation, CPT1A expression, and RGC survival underscores a coherent signaling axis that integrates extracellular S1P cues with intracellular metabolic reprogramming (Fig. 7 E). These results expand the known roles of S1P beyond its canonical functions in vascular regulation and inflammation 53 . By demonstrating that S1P signaling directly enhances FAO in RGCs, a cell type with high energy demands, we identify a previously unrecognized neuroprotective pathway. This neuroprotective pathway is conserved across glaucoma subtypes, as both POAG and PACG patients exhibit similar erythrocyte S1P dysregulation, positioning the SPHK1-S1P axis as a unifying therapeutic target. Our findings also expand S1P's role beyond vascular regulation to direct metabolic support of neurons and reconcile age-related glaucoma risk with observed erythrocyte aging phenotypes 54 , 55 . Finally, we integrated data from the UK Biobank with our own cohort to examine the association between plasma metabolites and glaucoma development. The findings further underscore that glaucoma is not merely a localized ocular condition but a systemic disease involving widespread metabolic reprogramming. Analysis of UK Biobank data confirmed significant associations between specific metabolites and POAG risk and these results align with our own cohort data, where we observed decreased levels of protective metabolites and elevated levels of detrimental metabolites in glaucoma patients, reinforcing the robustness of our metabolic profiling. Through comprehensive untargeted metabolomics, we identified distinct metabolic changes in both erythrocytes and plasma, which together reveal a complex interaction between systemic metabolic dysregulation and glaucoma pathogenesis. The fact that many of these metabolites are involved in key energy and oxidative stress pathways supports the notion that systemic metabolic imbalances may exacerbate the progression of glaucoma. Particularly, our investigation into potential glaucoma biomarkers through random forest-based analysis identified S1P emerged as a particularly promising biomarker, achieving high diagnostic accuracy with AUC values of 74 in erythrocytes and 99 in plasma. It’s worth noting that while S1P is recognized for its role in neuroprotective effects, it also has pro-inflammatory properties that could precipitate significant side effects if administered directly 56 . Excessive S1P could inadvertently amplify inflammatory pathways, which is particularly concerning given the delicate balance of immune modulation in glaucoma pathology. In contrast, our approach with L-carnitine aims to support the endogenous release of S1P in a regulated, physiologically compatible manner, thereby mitigating potential inflammatory side effects while still sustaining S1P’s neuroprotective role in glaucoma. However, this study may be subject to several limitations, including small sample sizes and the generalizability of our observed erythrocyte metabolic reprogramming and systemic S1P deficiency to normal-tension glaucoma (NTG) patients remains to be determined. Given the shared endpoint of RGCs degeneration, it would be of particular interest for future studies to investigate whether similar disruptions in the SPHK1-S1P axis and the efficacy of L-carnitine are also present in NTG. In sum, our findings highlight the systemic nature of glaucoma, with significant metabolic reprogramming in erythrocytes. We also elucidate the role of intracellular S1P accumulation in driving metabolic reprogramming in glaucoma erythrocytes. The observed alterations in glucose uptake, glycolytic flux, PPP activity, antioxidant capacity, and Lands cycle underscore the multifaceted metabolic challenges faced by glaucoma erythrocytes. Our findings not only expand our understanding of glaucoma as a systemic disease but also offer new avenues for erythrocyte-based therapeutic interventions, with L-carnitine emerging as a potential strategy to slow glaucoma progression. Declarations Ethics approval and consent to participate The patient cohort was approved by the Institutional Review Board of Central South University Committee for the Protection of Human Subjects (2024121597), and written informed consent was obtained from all participants. Consent for publication Not applicable. Availability of data and materials Not applicable. Competing interests The authors declare no competing interests. Funding This work was supported by NSFC82230023 (Y.X.), NSFC82171058 (X.X.) and Feifan Scholar Fund of Xiangya Hospital of Central South University (Y.X.), NKRDPC2024YFA1108704 (X.X.), RDPHFRL2024PT5107 (X.X.), NSFC82301202 (Y.L), CPSF2023M733953 (Y.L.), NSFHP2025JJ60575 (Y.L.), NSFHP2024JJ4087 (Q.L.), NSFC82402081 (Q.L.), CPSF GZB20240866 (C.C.), NSFC82400873 (C.C.), Authors’ Contributions Y.L., Q.L. and YD.W designed and conducted the mouse experiments and human sample measurements, analyzed the experimental data, drew the figures and wrote the manuscript; T.C. performed the lipidomic analysis; C.L. analyzed UK biobank data; C.C. and T.X. provided expertise in metabolomics design and analyses; YY.W. provided expertise in immunoprecipitation design; X.X. provided expertise in determining clinical types of glaucoma and helped with human subject; Y.X. oversaw the design of experiments and interpretation of results, the writing and organization of the manuscript and did final editing. Acknowledgements We are grateful to the Biomedical Center, Institute for Advanced Study of Central South University for providing the equipment used in this study, including the flow cytometry, confocal microscopy, visual evoked potential (VEP), and electroretinography (ERG) instruments. National Natural Science Foundation of China References Marando, C. M., Shen, Lucy Q. Glaucoma. (2021). https://doi.org/10.1007/978-3-030-63978-5_1 Best, S. Glaucoma Diagnosis and Management. Clinical & Experimental Ophthalmology 34 , 706-707 (2006). https://doi.org/10.1111/j.1442-9071.2006.01326.x Zhou, X. J. W., Ren Yi. Current situation and prospect of minimally invasive glaucoma surgery in childhood glaucoma. 23 (2023). https://doi.org/10.3980/j.issn.1672-5123.2023.1.10 Davis, B. M., Crawley, L., Pahlitzsch, M., Javaid, F. & Cordeiro, M. F. Glaucoma: the retina and beyond. Acta Neuropathol 132 , 807-826 (2016). https://doi.org/10.1007/s00401-016-1609-2 Basavarajappa, D. et al. 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Supplementary Files SupplementaryMaterials1118.docx Supplementary Materials Cite Share Download PDF Status: Under Review Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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16:27:48\",\"extension\":\"html\",\"order_by\":19,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"acdc-reference\",\"size\":215408,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"earlyproof.html\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8165516/v1/853ff24854574a2ce43857f0.html\"},{\"id\":97348376,\"identity\":\"b1718f1a-a787-4a32-b2ac-4136b35798c5\",\"added_by\":\"auto\",\"created_at\":\"2025-12-03 11:58:34\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1805261,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eMetabolomic insights into the systemic metabolic signatures of glaucoma. \\u003c/strong\\u003e(A) P50 of glaucoma and control erythrocytes was measured by Hemox Analyzer (n=37). (B) Pearson correlation analysis between P50 and mean deviation (MD) and Cup-to-Disc ratio was conducted (n=37). (C) PLS-DA analysis of metabolic profiling of erythrocytes (R\\u003csup\\u003e2\\u003c/sup\\u003eY=0.82 and Q\\u003csup\\u003e2\\u003c/sup\\u003e=0.69) and plasma (R\\u003csup\\u003e2\\u003c/sup\\u003eY=0.79 and Q\\u003csup\\u003e2\\u003c/sup\\u003e=0.63) of human samples (n=40 each group). (D) Pathway analysis of metabolites with differential abundance in control and glaucoma erythrocytes. The metabolome view showing all the matched pathways as circles arranged according to the scores from enrichment analysis (\\u003cem\\u003ey\\u003c/em\\u003e\\u0026nbsp;axis) and from topology analysis (\\u003cem\\u003ex\\u003c/em\\u003e\\u0026nbsp;axis). The color and size of each circle is based on\\u0026nbsp;\\u003cem\\u003eP\\u003c/em\\u003e\\u0026nbsp;and pathway impact values, respectively (n=40). (E) Schematic graph of the significant alterations in metabolic intermediates within glycolysis-RL shunt pathway and levels of 2,3-BPG in glaucoma erythrocytes compared to control erythrocytes. (F) In vitro flux experiments with 1,2,3-\\u003csup\\u003e13\\u003c/sup\\u003eC\\u003csub\\u003e3\\u003c/sub\\u003e-glucose to trace glucose metabolism between glycolysis-RL shunt and PPP in glaucoma and control erythrocytes (n=5-6 each group). Isotopically labeled glucose (M+3), G6P/F6P(M+3), FBP(M+3), G3P(M+3), 2,3-BPG(M+3), pyruvate(M+3), 6PGL(M+3), 6PG(M+3), R5P(M+3), S7P(M+3) and the ratio of lactate(M+3)/lactate(M+2). G6P/F6P: glucose 6-phosphate/fructose 6-phosphate, FBP: fructose 1,6-bisphosphate, G3P: glyceraldehyde 3-phosphate, 2,3-BPG: 2,3-biphosphoglycerate, 3-PG: 3-phosphoglycerate, 6PGL: glucono-1,5-lactone 6-phosphate, 6PG: 6-phospho-D-gluconate, R5P: ribose 5-phosphate, S7P: sedoheptulose 7-phosphate. (G) Protein levels of BPGM in glaucoma and control erythrocytes was measured by western blot (n=6). (H) ROS and the ratio of GSH to GSSG, were measured in glaucoma and control erythrocytes using flow cytometry and untargeted metabolomics (n=9 for ROS and n=40 for GSH/GSSG). (I) The levels of isotopically labeled glucose (M+3) in supernatant of in vitro flux experiments culture (n=6). (J) The levels of glucose in plasma of primary glaucoma subgroup and control group (n=40). (K) The levels of membrane GLUT1 protein expression on glaucoma and control erythrocytes were determined by flow cytometry (n=6). (L) Schematic hypothesis linking the metabolomic insights of glaucoma erythrocytes. \\u003csup\\u003e*\\u003c/sup\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u0026nbsp;\\u0026lt; 0. 05.\\u0026nbsp;\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8165516/v1/b1d3cc7a186e2d5faf194d8a.png\"},{\"id\":97371095,\"identity\":\"a3bd15c5-9afa-4033-9c5e-c1d691041a67\",\"added_by\":\"auto\",\"created_at\":\"2025-12-03 16:28:24\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1222904,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eDefective transporter MFSD2B restricts S1P release from erythrocytes.\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e(A) Featured metabolites with significant differences between erythrocytes of primary glaucoma and control group were shown in volcano plot (n=40). (B) Quantitative analysis of S1P levels in erythrocytes of primary glaucoma and control group (n=40). (C) Heat map of metabolic intermediate from sphingolipid metabolism in erythrocytes (n=5). (D) Activity of SPHK1 in glaucoma and control erythrocytes (n=23). (E) Featured metabolites with significant differences between plasma of primary glaucoma and control group were shown in volcano plot (n=40). (F) Quantitative analysis of S1P levels in plasma of primary glaucoma subgroup and control group (n=26 for PACG and n=14 for POAG). (G) Levels of membrane MFSD2B ubiquitination in glaucoma and control erythrocytes was measured by western blot (n=6). (H) MFSD2B ubiquitination in erythrocyte membranes from two glaucoma patients and sex- and age-matched controls, quantified by western blot. (I) Pearson correlation analysis was conducted between the plasma S1P concentration and the retinal nerve fiber layer (RNFL) thickness in glaucoma patients (n=35). (J) RGC density of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e and \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e-/-\\u003c/em\\u003e\\u003c/sup\\u003e mice in normal conditions (n=12). (K) The IOP of eyes in young and aged \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e and \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e-/-\\u003c/em\\u003e\\u003c/sup\\u003e mice in normal conditions (n=8-10). \\u003csup\\u003e*\\u003c/sup\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u0026nbsp;\\u0026lt; 0. 05.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8165516/v1/e7780e5f2ada22a798050991.png\"},{\"id\":97348377,\"identity\":\"b1b2694f-f690-4e8e-bc4d-dd2d7f967f9c\",\"added_by\":\"auto\",\"created_at\":\"2025-12-03 11:58:34\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1955972,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eL-Carnitine restores membrane integrity and redox homeostasis via the Lands cycle and PPP\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e(A) The levels of oxidized lipid 9-oxononanoic acid in glaucoma and control erythrocytes (n=40). (B) The levels of lipid peroxidation of glaucoma and control erythrocytes was measured via BODIPY 581/591 C11. (C) Lipidomic analysis revealed the key PUFA-PCs/ SFA-PC (16:0) ratio in glaucoma and control erythrocytes. (D) Lipidomic analysis revealed the LPC(16:0)/ PC(16:0) ratio in glaucoma and control erythrocytes. (E) Quantitative analysis of L-carnitine levels in primary glaucoma subgroup and control group (n=26 for PACG and n=14 for POAG). (F) Heat map of acyl-carnitine in erythrocytes and plasma of glaucoma and control group (n=40). (G) Lipidomic analysis revealed the LPC(16:0)/ PC(16:0) ratio in glaucoma erythrocytes cultured with or without optimized dosage (100 μM) of L-carnitine (n=4). (H) Protein expression of membrane MFSD2B in glaucoma erythrocytes treated with or without 100μM L-carnitine (n=8). (I) Quantitative analysis of S1P levels in glaucoma erythrocytes and the corresponding supernatant from in vitro culture medium, with and without the addition of L-carnitine (n=8). (J) Protein expression of membrane GLUT1 in glaucoma erythrocytes treated with or without L-carnitine (n=7-8). (K) Untargeted metabolic analysis of glucose and indicated metabolic intermediates in erythrocytes and supernatant from in vitro culture medium, with and without the addition of L-carnitine (n=7-8). (L-M) ROS and the ratio of GSH to GSSG, were measured in glaucoma erythrocytes treated with or without L-carnitine (n=7-8). (N-O) ROS and lipid peroxidation levels in control and glaucoma erythrocytes, treated under the indicated conditions, were measured by flow cytometry. \\u003csup\\u003e*\\u003c/sup\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u0026nbsp;\\u0026lt; 0. 05.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8165516/v1/57d41cb6a8f1e2dcfaa319ce.png\"},{\"id\":97348380,\"identity\":\"36c575fe-121c-4a73-b441-b9aff9aba70d\",\"added_by\":\"auto\",\"created_at\":\"2025-12-03 11:58:34\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":2403104,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eL-carnitine restores erythrocyte homeostasis and circulating S1P levels in cGLA\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;(A) The IOP was monitored in magnetic bead model (chronic glaucoma model, cGLA) of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e mice treated with or without L-carnitine (n=6). (B) P50 of erythrocytes from \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA model treated with or without L-carnitine (n=6). (C) Heat map and graphs of representative acylcarnitine in erythrocytes of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA model treated with or without L-carnitine (n=6). (D) The activity of SPHK1 of erythrocytes of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA model treated with or without L-carnitine (n=6). (E) Protein expression of membrane MFSD2B in erythrocytes of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA treated with or without L-carnitine (n=6). (F) Quantitative analysis of S1P levels in erythrocytes and plasma of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e and \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e-/-\\u003c/em\\u003e\\u003c/sup\\u003ecGLA treated with or without L-carnitine. (G) The protein expression of membrane GLUT1 from erythrocytes of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e GLA treated with or without L-carnitine (n=6). (H) Untargeted metabolic analysis of indicated metabolic intermediates in erythrocytes of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA treated with or without L-carnitine (n=6). (I) In vivo injection of U-\\u003csup\\u003e13\\u003c/sup\\u003eC\\u003csub\\u003e­6\\u003c/sub\\u003e-glucose to trace glucose metabolism between glycolysis and PPP in erythrocytes of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA treated with or without L-carnitine (n=6). (J) The ROS levels of erythrocytes from \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA model treated with or without L-carnitine (n=6). (K) The ratio of GSH to GSSG were measured erythrocytes of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e and \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e-/-\\u003c/em\\u003e\\u003c/sup\\u003e cGLA treated with or without L-carnitine (n=6). (L) The levels of lipid peroxidation were measured, via BODIPY 581/591 C11, in erythrocytes from \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA model treated with or without L-carnitine. (M) The ratio of ATP to AMP were measured in erythrocytes of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA treated with or without L-carnitine (n=6). (N) The cell number of circulating erythrocytes of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA treated with or without L-carnitine (n=6). (O) Graphical abstract depicting the proposed regulations of L-carnitine in RBCs in glaucoma conditions.\\u003csup\\u003e *\\u003c/sup\\u003e\\u003cem\\u003eP\\u003c/em\\u003e \\u0026lt; 0.05\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8165516/v1/e2c53515ef4ebb098a71dd0b.png\"},{\"id\":97371268,\"identity\":\"b4fef5cc-2eea-474c-908f-216145c8dd87\",\"added_by\":\"auto\",\"created_at\":\"2025-12-03 16:28:39\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":2996312,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eL-carnitine restores retinal morphology, RGC function, and visual acuity in cGLA.\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e(A) Histology of retinal tissue of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e and \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e-/-\\u003c/em\\u003e\\u003c/sup\\u003e cGLA model treated with or without L-carnitine was detected by hematoxylin and eosin (H\\u0026amp;E) staining (n=6). (B) RGCs density in retinal tissue of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e and \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e-/-\\u003c/em\\u003e\\u003c/sup\\u003e cGLA model treated with or without L-carnitine was detected by immunofluorescence staining with RBPMS (n=6). (C) Axon morphology was determined by toluidine blue staining in optic nerve from \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e and \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e-/-\\u003c/em\\u003e\\u003c/sup\\u003e cGLA model treated with or without L-carnitine. (D) The anterograde axoplasmic transport was assessed by cholera toxin B (CTB) tracing to the lateral geniculate nucleus (LGN) and superior colliculus (SC) area of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e and \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e-/-\\u003c/em\\u003e\\u003c/sup\\u003e cGLA model treated with or without L-carnitine. (E-F) The electrical activity (VEP and ERG) of the retina in response to a light stimulus was measured in \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e and \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e-/-\\u003c/em\\u003e\\u003c/sup\\u003ecGLA model treated with or without L-carnitine (n=6). \\u003csup\\u003e*\\u003c/sup\\u003e\\u003cem\\u003eP\\u003c/em\\u003e \\u0026lt; 0.05.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8165516/v1/f82d5e19bf6192d06c4380a5.png\"},{\"id\":97348382,\"identity\":\"b7f077d6-2a06-4fc1-a31a-2f75f038d655\",\"added_by\":\"auto\",\"created_at\":\"2025-12-03 11:58:34\",\"extension\":\"png\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":2000392,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eS1P promotes RGC survival under stress by supporting FAO to restore bioenergetic capacity\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e(A) Untargeted metabolic analysis of indicated metabolic intermediates in glycolysis and TCA cycle in retina of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA treated with or without L-carnitine (n=6). (B) The ratio of ATP to AMP were measured in retina of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA treated with or without L-carnitine (n=6). (C) In vivo injection of U-\\u003csup\\u003e13\\u003c/sup\\u003eC\\u003csub\\u003e­6\\u003c/sub\\u003e-glucose to trace glucose metabolism between glycolysis and TCA cycle in retina of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e and \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e-/-\\u003c/em\\u003e\\u003c/sup\\u003e cGLA model treated with or without L-carnitine (n=6). (D) Untargeted metabolic analysis of TCA cycle metabolites in retina of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e and \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e-/-\\u003c/em\\u003e\\u003c/sup\\u003e cGLA treated with or without L-carnitine (n=6). (E) L-carnitine and palmitic acid levels in retina of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e and \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e-/-\\u003c/em\\u003e\\u003c/sup\\u003e cGLA treated with or without L-carnitine (n=6). (F) Heat map of acyl-carnitine in retina of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e and \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e-/-\\u003c/em\\u003e\\u003c/sup\\u003e cGLA treated with or without L-carnitine. (G) The protein levels of CPT1A in RGCs from retina of \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e and \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e-/-\\u003c/em\\u003e\\u003c/sup\\u003e cGLA treated with or without L-carnitine (n=6). (H) The levels of phosphorylated (Thr172) AMPKa in RGCs cultured with or without S1P under oxygen-glucose deprivation/reperfusion conditions (n=6). (I) The protein levels of CPT1A in RGCs cultured with S1P, AMPKa activator AICAR, or inhibitor BAY-3827 as indicated, under oxygen-glucose deprivation/reperfusion conditions (n=6). (J) The protein levels of cleaved caspase-3 (Asp175) in RGCs cultured under oxygen-glucose deprivation/reperfusion conditions, with or without S1P in the presence of L-carnitine (n=6). (K) The protein levels of cleaved caspase-3 (Asp175) in RGCs cultured under oxygen-glucose deprivation/reperfusion conditions, with 20% glaucoma patient plasma or matched control plasma, with or without S1P in the presence of L-carnitine (n=12-17). (L) Graphical abstract depicting the proposed protective roles of L-carnitine in RGCs in this study. \\u003csup\\u003e*\\u003c/sup\\u003e\\u003cem\\u003eP\\u003c/em\\u003e \\u0026lt; 0.05.\\u0026nbsp;\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"6.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8165516/v1/d38e7fdab33bf80f1251dc89.png\"},{\"id\":97370287,\"identity\":\"90e4c1d2-f576-4e89-a22c-08d97731e094\",\"added_by\":\"auto\",\"created_at\":\"2025-12-03 16:27:06\",\"extension\":\"png\",\"order_by\":7,\"title\":\"Figure 7\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":2439870,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eIdentification of S1P as a biomarker in primary glaucoma patients\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e(A) Age, sex, BMI-adjusted forest plot of plasma metabolites significantly associated with individuals with POAG from the UK Biobank. (B) Untargeted metabolic analysis of pyruvate and lactate in plasma of primary glaucoma and control group (n=40). (C) Metabolites biomarker for primary glaucoma development was evaluated using receiver operating characteristic (ROC) curves analyzed by random forest (n=40).\\u0026nbsp;(D) Pathway enrichment analysis\\u0026nbsp;was performed by using data from lipidomic analysis of glaucoma and control erythrocytes and plasma (n=40). (E) Graphical abstract of key findings from this study. \\u003csup\\u003e*\\u003c/sup\\u003e\\u003cem\\u003eP\\u003c/em\\u003e \\u0026lt; 0.05.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"7.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8165516/v1/4118358b3156171a2f72a642.png\"},{\"id\":103049170,\"identity\":\"813585a1-3df7-476c-abe7-c4be04207f6d\",\"added_by\":\"auto\",\"created_at\":\"2026-02-20 07:36:34\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":19258910,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8165516/v1/7693b624-7f16-443b-8487-c8ea16989acd.pdf\"},{\"id\":97348378,\"identity\":\"26717008-a9ca-4fce-bc7f-e79bad4ce110\",\"added_by\":\"auto\",\"created_at\":\"2025-12-03 11:58:34\",\"extension\":\"docx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":9935717,\"visible\":true,\"origin\":\"\",\"legend\":\"Supplementary Materials\",\"description\":\"\",\"filename\":\"SupplementaryMaterials1118.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8165516/v1/e554ce889d9f78c4580cf748.docx\"}],\"financialInterests\":\"There is \\u003cb\\u003eNO\\u003c/b\\u003e Competing Interest.\",\"formattedTitle\":\"Erythrocyte-Targeted Therapy for Glaucoma: Neuroprotection Through Erythrocyte-Derived Sphingosine 1-Phosphate-Enhanced Fatty Acid β-Oxidation via the AMPKα-CPT1A Axis\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eGlaucoma is a prevalent eye condition globally and is the first leading cause of irreversible blindness worldwide, affecting approximately 3% of the global population aged 40 to 80 years. This condition encompasses a spectrum of eye diseases that damage the optic nerve, primarily due to increased intraocular pressure (IOP). Primary glaucoma is mainly including two main types: open-angle glaucoma (POAG) and angle-closure glaucoma (PACG)\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR2\\\" citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e\\u003c/sup\\u003e. Central to the pathophysiology of glaucoma is the degeneration of retinal ganglion cells (RGCs), which are crucial for transmitting visual information from the retina to the brain\\u003csup\\u003e\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e\\u003cp\\u003eGlaucoma is a complex and multi-factory disease. While mechanical stress from increased IOP remains a key factor, early genetic studies have identified multiple loci associated with POAG across diverse ancestries, implicating pathways such as extracellular matrix remodeling, intracellular ion channels, and adipose metabolism\\u003csup\\u003e\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e\\u003c/sup\\u003e. Besides, oxygen regulation is also pivotal in glaucoma progression, particularly in maintaining blood vessel health and the optic nerve head. Local hypoxia in glaucoma-affected tissues, including the retina and trabecular meshwork of anterior chamber angle, can exacerbate disease progression by driving neuroinflammation, retinal damage, and ultimately the loss of RGCs\\u003csup\\u003e\\u003cspan additionalcitationids=\\\"CR8 CR9\\\" citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e\\u003c/sup\\u003e. Erythrocytes, as primary and sole oxygen carriers, are essential for delivering oxygen to every organ within our body. Thus, it is possible that efficient oxygen transport by erythrocytes may help alleviate local hypoxia, reducing oxidative stress and potentially slowing RGC and trabecular meshwork damage. In addition to oxygen transport, erythrocytes are critical regulators of metabolite transport and homeostasis, contributing to neuronal protection. They deliver essential metabolites such as pyruvate, lactate, and amino acids, which are vital for neuronal metabolism and energy production, while simultaneously removing metabolic waste products like urea and ammonia to prevent neurotoxicity\\u003csup\\u003e\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e\\u003c/sup\\u003e. One of the pathways central to erythrocyte function is the Lands cycle\\u003csup\\u003e\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e\\u003c/sup\\u003e, a phospholipid remodeling pathway essential for maintaining membrane fluidity and function. By modifying the fatty acid composition of phospholipids, the Lands cycle ensures membrane stability, deformability, and erythrocyte lifespan. Although erythrocytes lack nuclei and have limited synthetic capabilities, their membrane integrity is crucial for effective oxygen delivery and metabolic regulation. Dysregulation of the Lands cycle may compromise these processes, making it a critical area of study in diseases influenced by hypoxia and oxidative stress\\u003csup\\u003e\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e\\u003cp\\u003eDespite their fundamental role in oxygen and metabolite transport, erythrocytes have been largely overlooked in glaucoma research. As the most abundant circulating cell type and highly sensitive to hypoxia\\u003csup\\u003e\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e\\u003c/sup\\u003e, erythrocytes may play an unrecognized role in glaucoma pathophysiology, linking systemic metabolic dysfunction to local retinal damage. Understanding erythrocyte function in glaucoma offers a novel perspective on disease progression and potential therapeutic targets. Therefore, here we took multi-disciplinary approaches including accurately measuring erythrocyte oxygen delivery capacity and comprehensive metabolomics and lipidomic profiling in glaucoma human cohort coupled with a sophisticate murine genetic tool and isotopically labelled glucose flux tracing analyses to define erythrocyte oxygen release and its potential role and underlying mechanism with a goal to develop early circulating pathogenic biomarkers and intervention for the disease.\\u003c/p\\u003e\"},{\"header\":\"Materials and Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eHuman subjects\\u003c/h2\\u003e\\u003cp\\u003eIn this study, inclusion criteria for POAG are IOP\\u0026thinsp;\\u0026gt;\\u0026thinsp;21 mmHg, glaucomatous optic disc and RNFL damage, typical visual field defects, and an open anterior chamber angle. PACG criteria include glaucomatous optic disc changes, visual field damage, IOP\\u0026thinsp;\\u0026gt;\\u0026thinsp;21 mmHg, and a narrow or closed anterior chamber angle. Exclusion criteria cover diseases including secondary glaucoma, other conditions affecting vision, and unreliable visual field tests. Our glaucoma cohort comprised both newly diagnosed and patients with established disease who were receiving topical medications (e.g., prostaglandin analogues, β-blockers, α-agonists, carbonic-anhydrase inhibitors) or had undergone prior surgery (e.g., trabeculectomy and laser Peripheral Iridotomy,) (\\u003cb\\u003eTable \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e)\\u003c/b\\u003e. Healthy volunteers were matched for age and biological sex and had normal examination results. Demographic and clinical information of human subjects are listed in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e. All participants were examined by board-certified ophthalmologists at Xiangya Hospital, Central South University, Changsha, Hunan, China, using slit-lamp biomicroscopy, Goldmann applanation tonometry, funduscopy, optical coherence tomography (OCT), and standard automated perimetry to confirm glaucoma diagnoses or to verify normal ocular status in control subjects. Approximately 3 mL of whole blood was collected from the forearm vein of human subjects. Human blood samples were collected in lavender-top plasma separation tubes containing spray-dried dipotassium ethylenediaminetetraacetic acid (K₂EDTA) as the anticoagulant. The samples were centrifuged at 2,000 rpm for 10 minutes at 4\\u0026deg;C. After separation, the plasma and erythrocytes were aliquoted into 100 \\u0026micro;L per tube and immediately stored at -80\\u0026deg;C for further analysis. The research protocol, including informed consent from the subjects, was approved by the Central South University Committee for the Protection of Human Subjects.\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eClinical information of human subjects.\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"4\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eVariable\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eControl (n\\u0026thinsp;=\\u0026thinsp;40)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003ePrimary glaucoma(n\\u0026thinsp;=\\u0026thinsp;40)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eP value\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eAge(yr)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e57.00\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;12.34\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e57.52\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;11.94\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.927\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSex(Female/Male)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e25/15\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e25/15\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eN/A\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSBP(mm Hg)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e115.32\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;14.18\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e132.46\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;21.21*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eDBP(mm Hg)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e78.85\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;6.85\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e83.69\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;13.84\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.055\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eOPP (mmHg)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e45.42\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;6.13\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e37.56\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;15.55*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.005\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eIOP (mmHg)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e15.25\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e29.08\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;11.69*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eRNFL Thickness (\\u0026micro;m)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e104.1\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;9.7\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e69.29\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;17.48*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMean Deviation (dB)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e-0.98\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.60\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-21.24\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;10.75*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eCup-to-Disc Ratio\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.4\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.67\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.27*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eWBC(10\\u003csup\\u003e9\\u003c/sup\\u003e/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e5.80\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.25\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e6.42\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.27*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.036\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eRBC(10\\u003csup\\u003e12\\u003c/sup\\u003e/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e4.69\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.38\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e4.47\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.44*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.045\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eHb(g/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e139.95\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;13.97\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e135.03\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;11.86\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.103\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePLT(10\\u003csup\\u003e9\\u003c/sup\\u003e/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e214.15\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;40.05\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e213.45\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;50.74\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.948\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eHCT(%)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e41.90\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.71\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e40.72\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.29\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.148\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eNeu(10\\u003csup\\u003e9\\u003c/sup\\u003e/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e3.33\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.02\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e4.04\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.99*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.003\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eLym(10\\u003csup\\u003e9\\u003c/sup\\u003e/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e1.90\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.51\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1.78\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.58\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.356\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eEos(10\\u003csup\\u003e9\\u003c/sup\\u003e/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.12\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.09\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.11\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.08\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.657\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMono(10\\u003csup\\u003e9\\u003c/sup\\u003e/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.40\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.12\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.46\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.15\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.077\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMCV(fl)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e89.30\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.27\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e90.53\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.40\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.281\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMCH(PG)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e29.81\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.89\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e30.01\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.02\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.651\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMCHC(g/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e333.51\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;8.81\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e331.37\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;6.87\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.241\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eRDW(%)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e13.84\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.10\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e13.07\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.77*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.001\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePCT(%)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.19\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.03\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.20\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.05\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.535\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMPV(fl)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e9.07\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.00\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e9.37\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.41\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.298\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePDW(%)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e16.39\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.11\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e16.19\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.01\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.601\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTP(g/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e75.28\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.23\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e71.15\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;6.00*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eALB(g/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e45.62\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.85\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e42.99\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.08*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.002\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGLOB(g/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e29.66\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.23\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e28.16\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.98\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.081\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eA/B\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e1.56\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.22\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1.56\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.25\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.901\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTbil(\\u0026micro;mol/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e13.69\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.94\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e13.27\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.98\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.742\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eDbil(\\u0026micro;mol/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e3.67\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.25\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e3.72\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.55\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.897\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTBA(\\u0026micro;mol/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e4.42\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;6.13\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e4.31\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.97\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.924\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eALT(U/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e23.81\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;11.69\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e21.80\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;12.33\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.475\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eAST(U/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e25.51\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;6.55\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e24.15\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;11.10\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.531\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eUrea(mg/dL)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e5.47\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.48\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e5.14\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.45\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.329\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eCREA(\\u0026micro;mol/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e68.41\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;18.49\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e62.62\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;13.41\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.128\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eUA(\\u0026micro;mol/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e360.66\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;106.87\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e316.26\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;86.36\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.054\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGLU(mmol/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e4.89\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.75\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e5.40\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.10*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.033\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eCHOL(mmol/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e5.29\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.17\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e4.67\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.32\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.059\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eHDL-c(mmol/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e1.37\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.34\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1.32\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.46\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.606\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eLDL-c(mmol/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e3.36\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.76\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e2.96\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.75*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.042\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eHDL/TC\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.26\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.05\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.27\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.07\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.500\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003enonHDL-C(mmol/L)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e3.92\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.97\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e3.45\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.81\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.059\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003ctfoot\\u003e\\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003eData were expressed as mean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;SD. P values were assessed using two-tailed unpaired t test with Welch's unequal variances t-test. \\u003csup\\u003e*\\u003c/sup\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05. Systolic Blood Pressure(SBP, in mmHg), Diastolic Blood Pressure(DBP, in mmHg), Ocular Perfusion Pressure (OPP, in mmHg), Intraocular Pressure (IOP, in mmHg), White Blood Cell count(WBC, in 10⁹/L), Red Blood Cell count(RBC, in 10\\u0026sup1;\\u0026sup2;/L), Hemoglobin(Hb, in g/L), Platelet count(PLT, in 10⁹/L), Hematocrit(HCT, in%), Neutrophils(Neu, in 10⁹/L), Lymphocytes(Lym, in 10⁹/L), Eosinophils(Eos, in 10⁹/L), Monocytes(Mono, in 10⁹/L), Mean Corpuscular Volume(MCV, in fl), Mean Corpuscular Hemoglobin(MCH, in pg), Mean Corpuscular Hemoglobin Concentration(MCHC, in g/L), Red Cell Distribution Width(RDW, in%), Platelet Crit(PCT, in%), Mean Platelet Volume(MPV, in fl), Platelet Distribution Width(PDW, in%), Total Protein(TP, in g/L), Albumin(ALB, in g/L), Globulin(GLOB, in g/L), Albumin/Globulin ratio(A/B), Total Bilirubin(Tbil, in \\u0026micro;mol/L), Direct Bilirubin(Dbil, in \\u0026micro;mol/L), Total Bile Acids(TBA, in \\u0026micro;mol/L), Alanine Aminotransferase(ALT, in U/L), Aspartate Aminotransferase(AST, in U/L), Urea(in mg/dL), Creatinine(CREA, in \\u0026micro;mol/L), Uric Acid(UA,in \\u0026micro;mol/L), Glucose(GLU, in mmol/L), Cholesterol(CHOL, in mmol/L), High-Density Lipoprotein Cholesterol(HDL-c, in mmol/L), Low-Density Lipoprotein Cholesterol(LDL-c, in mmol/L), High-Density Lipoprotein Cholesterol/Total Cholesterol ratio(HDL/TC), and Non-High-Density Lipoprotein Cholesterol(nonHDL-C, in mmol/L).\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tfoot\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003c/div\\u003e\\n\\u003ch3\\u003eAnimals\\u003c/h3\\u003e\\n\\u003cp\\u003e All animal experiments conformed to the relevant regulatory standards and the animal protocol was approved by the Animal Care and Use Committees at Central South University. The animals used in this study are C57BL/6J background. Erythrocyte-specific deletion of \\u003cem\\u003eSphK1\\u003c/em\\u003e mice (\\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003ef/f\\u003c/em\\u003e\\u003c/sup\\u003e\\u003cem\\u003e/EpoR-\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eCre+\\u003c/em\\u003e\\u003c/sup\\u003e, \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e\\u0026minus;/\\u0026minus;\\u003c/em\\u003e\\u003c/sup\\u003e) was generated as described previously\\u003csup\\u003e\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e\\u003c/sup\\u003e. All mice were kept under a regular rodent chow ad libitum and exposed to the standard 12 h light/12 h dark cycle. All experiments were performed on 6- to 8-week-old mice and assigned to experimental groups in a balanced manner to ensure approximately equal representation of both sexes.\\u003c/p\\u003e\\n\\u003ch3\\u003eThe glaucoma model establishment\\u003c/h3\\u003e\\n\\u003cp\\u003eOcular hypertension was induced using the magnetic microbead occlusion model\\u003csup\\u003e\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e\\u003c/sup\\u003e. Briefly, 2\\u0026micro;L of 4.5 \\u0026micro;m magnetic microbeads were injected into the anterior chamber of anesthetized mice using a bevelled glass microneedle. A handheld magnet was employed to guide the microbeads to the iridocorneal angle, ensuring sustained blockade of aqueous humor outflow and reproducible intraocular pressure elevation. For reagents delivery, intraperitoneal injections of PBS or 400 mg/kg L-carnitine were administered every other day. Mice were euthanized at 6 weeks post-injection for further examinations. All animal experiments were reviewed and approved by the Animal Care and Use Committee of the Laboratory Animal Research Center at the Xiangya Medical School of Central South University.\\u003c/p\\u003e\\n\\u003ch3\\u003eMeasurement of P50\\u003c/h3\\u003e\\n\\u003cp\\u003eFor P50 measurement, 15 \\u0026micro;L of erythrocyte was mixed with 3 mL of Hemox Buffer (TCS Scientific Corporation, PA), 5 \\u0026micro;L of anti-foaming reagent (TCS Scientific Corporation, PA), and 5 \\u0026micro;L of 22% BSA in PBS. This mixture was injected into the Hemox Analyzer (TCS Scientific Corporation, PA) to measure the oxygen equilibrium curve at 37\\u0026deg;C.\\u003c/p\\u003e\\n\\u003ch3\\u003eErythrocyte ROS detection\\u003c/h3\\u003e\\n\\u003cp\\u003eTo detect erythrocyte ROS levels by flow cytometry, 1 \\u0026micro;L of erythrocytes cells pellet was resuspended in 100 \\u0026micro;L PBS and then incubated with ROS-sensitive fluorescent dye (100 \\u0026micro;L,10 \\u0026micro;M) (Reactive Oxygen Species Assay Kit, Biosharp, BL714A) at 37\\u0026deg;C for 30 minutes in the dark. After incubation, excess dye is removed through 3 times PBS washing, and the cells are resuspended in 100 \\u0026micro;L PBS for analysis. Stained samples were acquired for fluorescence in the fluorescein isothiocyanate (FITC) channel on a BD FACS Celesta cytometer and data were analyzed with FlowJo version 10.0.7. Data from at least 10,0000 cells per sample are collected and analyzed for assessment of ROS levels.\\u003c/p\\u003e\\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eSPHK1 activity assay\\u003c/h2\\u003e\\u003cp\\u003eErythrocyte SPHK1 activity was determined as previously described\\u003csup\\u003e\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e\\u003c/sup\\u003e. Briefly, erythrocytes were lysed in a buffer containing 50 mM HEPES (pH 7.4), 15 mM MgCl2, 0.05% Triton X-100, and 10 mM KCl, along with protease inhibitors. erythrocytes lysate (100\\u0026ndash;300 \\u0026micro;g) was then incubated with 5 \\u0026micro;M NBD-sphingosine (Avanti 810205) in a reaction buffer (50 mM HEPES pH 7.4, 15 mM MgCl2, 0.05% Triton X-100, 10 mM KCl, 10 mM NaF, 1.5 mM semicarbazide, and 1 mM ATP) containing 1% fatty acid-free BSA, in a total volume of 100 \\u0026micro;L. The reaction was conducted at 37\\u0026deg;C for 30 minutes. Subsequently, the NBD-S1P lipid was extracted with 100 \\u0026micro;L of 1 M potassium phosphate buffer (pH 8.5) and 500 \\u0026micro;L of chloroform/methanol (2:1), followed by centrifugation at 15,000 rpm for 1 minute. Then, 100 \\u0026micro;L of the supernatant was transferred to a 96-well fluorescence assay plate, and fluorescence was measured at 489/535 nm (excitation/emission) to quantify NBD-S1P levels using NBD-S1P standards.\\u003c/p\\u003e\\u003c/div\\u003e\\n\\u003ch3\\u003eMetabolomics and lipidomic profiling\\u003c/h3\\u003e\\n\\u003cp\\u003eMetabolomics analysis was performed as previously described\\u003csup\\u003e\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e\\u003c/sup\\u003e. All human blood samples were stored at -80\\u0026deg;C until metabolomic analysis. Erythrocytes and plasma were extracted using a 1:10 and 1:25 dilution, respectively, in a cold solvent mixture of methanol, acetonitrile, and water (5:3:2 \\u003cem\\u003ev/v/v\\u003c/em\\u003e). All samples were vigorously vortexed for 30 minutes at 4\\u0026deg;C, followed by centrifugation at 18,213 g for 10 minutes at 4\\u0026deg;C to pellet insoluble materials. The supernatants were harvested and subjected to ultra-high-pressure liquid chromatography coupled with mass spectrometry (UHPLC-MS) using a Thermo Vanquish UHPLC system connected to a Thermo Q Exactive MS. The samples were randomized and analyzed in both positive and negative ion modes with injection volumes of 10 \\u0026micro;L for red blood cells and 20 \\u0026micro;L for plasma. UHPLC separations were carried out using water (Phase A) and acetonitrile (Phase B) with 0.1% formic acid for positive mode and 1 mM ammonium acetate for negative mode. A Kinetex C18 column (150 x 2.1 mm, 1.7 \\u0026micro;m, Phenomenex) was used with a 5-minute gradient at a flow rate of 0.45 mL/min, a column temperature of 45\\u0026deg;C, and a sample compartment temperature of 7\\u0026deg;C. The solvent gradient conditions were as follows: 0-0.5 min at 5% B, 0.5\\u0026ndash;1.1 min at 5\\u0026ndash;95% B, 1.1\\u0026ndash;2.75 min hold at 95% B, 2.75-3 min at 95\\u0026thinsp;\\u0026minus;\\u0026thinsp;5% B, and 3\\u0026ndash;5 min hold at 5% B. The mass spectrometer operated in full MS mode with a resolution of 70,000, a scan range of 65\\u0026ndash;900 m/z, a maximum injection time of 200 ms, 2 microscans, an automatic gain control (AGC) target of 3 x 10\\u003csup\\u003e6\\u003c/sup\\u003e ions, an electrospray voltage of 4.0 kV, a capillary temperature of 320\\u0026deg;C, and nitrogen gas flows of 45 for sheath gas, 15 for auxiliary gas, and 0 for sweep gas. For indicated amino acid and S1P quantification, samples were prepared as previously described and operated in positive mode. Raw data files were converted to mzXML format using RawConverter (Scripps Research Institute) and analyzed with Maven (Princeton University). Relative quantification was performed based on the integrated peak areas of extracted ion chromatograms at the MS1 level. Instrument stability and quality control were maintained through replicate injections of a technical mixture every 10 runs.\\u003c/p\\u003e\\u003cp\\u003eFor the lipidomic analysis, 50 \\u0026micro;L of human blood samples were processed for lipid extraction using a modified isopropanol (IPA) precipitation method. Each sample was placed in an Eppendorf tube, and 200 \\u0026micro;L of IPA was added. The samples were vortex-mixed at room temperature for 10 minutes to ensure thorough mixing. Following vortexing, the samples were stored overnight at -20\\u0026deg;C to enhance protein precipitation. The following day, the samples were centrifuged at 14,000g for 10 minutes. The resulting organic phase was carefully collected, and 200 \\u0026micro;L of the organic solvent was dried using a vacuum centrifuge. The dried lipid extracts were then stored at -80\\u0026deg;C until further analysis. Prior to MS analysis, the dried lipid extracts were reconstituted in 200 \\u0026micro;L of a solvent mixture consisting of isopropanol, acetonitrile, and water in a 2:1:1 ratio (v:v). For the lipidomics analyses, lipids were separated on the reversed-phase column with a gradient elution, and MS/MS data were acquired in both positive and negative ion modes to ensure comprehensive lipid identification and quantification. Data analysis was performed using LipidSearch software to annotate lipid species based on accurate mass and fragmentation patterns.\\u003c/p\\u003e\\n\\u003ch3\\u003eGlucose isotopically labeled flux tracing\\u003c/h3\\u003e\\n\\u003cp\\u003eErythrocytes were isolated from whole blood using EDTA anticoagulant, followed by three washes with 1\\u0026times; PBS. A 100 \\u0026micro;l aliquot of erythrocytes was mixed with F-10 Nutrient Mix (Invitrogen) to achieve a hematocrit of 4%. The erythrocytes were incubated with 6mM 1,2,3-\\u003csup\\u003e13\\u003c/sup\\u003eC\\u003csub\\u003e3\\u003c/sub\\u003e-labeled glucose (Sigma-Aldrich) for 30 minutes at 37\\u0026deg;C under normoxia conditions. Erythrocytes and supernatants were collected and analyzed using Vanquish ultra-high-performance liquid chromatography coupled with Q Exactive HF MS (Thermo Fisher, Bremen, Germany). Metabolite partitioning and isotope distribution were performed using Maven (Princeton, NJ).\\u003c/p\\u003e\\u003cp\\u003eFor in vivo isotope tracing experiment, mice were intravenously injected with 5% [U-13C\\u003csub\\u003e6\\u003c/sub\\u003e]-glucose (5ml/kg body weight) (Sigma-Aldrich). Mice were euthanized and blood were collected through cardiac puncture after 30 minutes. Erythrocytes and plasma were extracted and processed as described above.\\u003c/p\\u003e\\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003ePrimary culture and treatment of retinal cells\\u003c/h2\\u003e\\u003cp\\u003ePrepare a digestion solution by supplementing DMEM with FBS and Collagenase Type II to achieve final concentrations of 10% FBS and 1 mg/mL Collagenase Type II. For every two retinas, prepare 500 \\u0026micro;L of digestion solution and add to retinal tissue. Triturate gently five times, then incubate at 37\\u0026deg;C with rotation for 30 minutes. Wash the tissue three times with PBS post-digestion.\\u003c/p\\u003e\\u003cp\\u003eTo establish an oxygen-glucose deprivation/reoxygenation (OGD/R) model, initiate oxygen-glucose deprivation by culturing cells in glucose-free DMEM within a hypoxia incubator chamber at 37\\u0026deg;C under 0.5% O2, 94.5% N2, and 5% CO2 in presence of indicated concentration of S1P for 1 h. Subsequently, transfer the cells to normal medium and culture under standard conditions (95% air, 5% CO2, 37\\u0026deg;C) for 1 day to induce reoxygenation.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eElectroretinogram (ERG) and visual evoked potential (VEP) detection\\u003c/h2\\u003e\\u003cp\\u003ePrior to examination, the animals were adapted to darkness for more than 12 hours. The mice were anesthetized with 1% pentobarbital sodium, and their pupils were fully dilated. The mice were then positioned prone on the operating table, with a heating pad maintaining a temperature of 37\\u0026deg;C. Carboxymethyl cellulose eyedrops were applied to both eyes to maintain corneal moisture. The testing environment was kept dark and illuminated with red light. Two corneal ring electrodes and three needle electrodes were prepared for the procedure. The electrodes were placed as follows: bilateral recording electrodes were positioned in contact with the cornea, with carboxymethyl cellulose eyedrops applied to enhance current conduction and maintain corneal moisture. Reference electrodes were inserted subcutaneously on both side of the nose, while the ground electrode was inserted subcutaneously at the tail. Stimulation and detection were conducted in accordance with ISCEV standards\\u003csup\\u003e\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e\\u003c/sup\\u003e. After detection, the amplitude and peak time of the a-wave and b-wave for each group were analyzed.\\u003c/p\\u003e\\u003cp\\u003eFor VEP detection, mice were anesthetized with 1% pentobarbital sodium. Carboxymethyl cellulose eyedrops were applied to maintain corneal moisture. Subcutaneous needle electrodes were placed at the occipital midpoint (recording electrode), nose (reference electrode), and tail (ground electrode). Following international standards, one eye was covered while recordings were performed, then repeated for the contralateral eye.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eMouse Blood Pressure Measurements\\u003c/h2\\u003e\\u003cp\\u003eSystolic blood pressure (SBP) was recorded non-invasively with the CODA High-Throughput tail-cuff system (Kent Scientific, Torrington, CT) before and after osmotic-pump implantation, following previously protocols\\u003csup\\u003e\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e\\u003c/sup\\u003e. Mice were housed in a temperature-controlled chamber (37\\u0026deg;C) and systolic blood pressure was monitored by tail-cuff plethysmography. Baseline recordings were obtained immediately prior to osmotic mini-pump implantation; subsequent measurements were performed continuously at defined post-surgical intervals. Each recording session consisted of 25 automated inflation\\u0026ndash;deflation cycles; the initial five cycles were discarded to allow acclimatization, and the remaining 20 cycles were averaged to yield the final systolic blood pressure value for analysis.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eFlow cytometry\\u003c/h2\\u003e\\u003cp\\u003eTo prepare a single-cell suspension from retinal tissue, we followed a previously described method\\u003csup\\u003e\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e\\u003c/sup\\u003e. Specifically, we processed retinas in pairs. For each pair, we prepared a 500 \\u0026micro;L digestion solution by mixing DMEM with a final concentration of 10% fetal bovine serum (FBS) and 1 mg/mL collagenase. The solution was then mixed thoroughly and warmed to 37\\u0026deg;C using a water bath. Next, the retinal cells were stained with surface antibody anti-Thy1 (Biolegend, clone 53\\u0026thinsp;\\u0026minus;\\u0026thinsp;2.1) and incubated the cells for 25 minutes on ice. Following surface staining, the cells were fixed and permeabilized using the Transcription Factor Staining Buffer Kit (Tonbo Biosciences) according to the manufacturer's instructions. This step allowed for intracellular staining of the following antibodies: anti-RBPMS (Abcam, ab152101), anti-AMPKα Phospho (Thr172) (Biolegend, A20017A), anti-CPT1A (Proteintech, 5D8G9), anti-CPT2 (Proteintech, 26555-1-AP), and Cleaved Caspase-3 (Asp175) (Cell Signaling Technology, #9661). The cells were incubated with these antibodies in permeabilization buffer on ice for at least 30 minutes. Finally, the stained cells were acquired using a BD FACS Celesta flow cytometer and analyzed using FlowJo software version 10.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eWestern blot\\u003c/h2\\u003e\\u003cp\\u003eErythrocyte membrane protein was extracted as described previously\\u003csup\\u003e\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e\\u003c/sup\\u003e, briefly, fresh erythrocytes were washed three times with cold PBS. A 100 \\u0026micro;L erythrocytes pellet was lysed in 5 mL of 0.4% NaCl supplemented with 1X protease inhibitors (ThermoFisher) and phosphatase inhibitors (Roche), then incubated on ice for 15 minutes with intermittent vortexing. The lysate was centrifuged at 500g for 10 minutes at 4\\u0026deg;C. After discarding the supernatant, 5 mL of 0.4% NaCl containing 1X protease and phosphatase inhibitors was added, followed by vortexing and centrifugation at 500g for 10 minutes at 4\\u0026deg;C. This centrifugation step was repeated five times in total. The final pellet was resuspended in 100 \\u0026micro;L of RIPA buffer and sonicated twice for 10 seconds each. The lysate was then incubated on ice for 30 minutes, followed by centrifugation at 15,000 x g for 10 minutes at 4\\u0026deg;C. The resulting supernatant was collected and stored at -80\\u0026deg;C for future use. Total erythrocyte protein was extracted by lysing cells in H₂O at a 1:10 volume ratio with 1X protease inhibitor cocktail (Roche, #11697498001), 1X phosphatase inhibitor cocktail (Roche, #04906837001), and 10 \\u0026micro;M MG132 (Santa Cruz, #sc-201270) or 1 \\u0026micro;M Bortezomib (Santa Cruz, #sc-217785) as proteasome inhibitors. Following lysis, 10X PBS was added to the lysate to neutralize the buffer. Protein concentration was measured using the BC A Protein Assay Kit (Pierce). Indicated protein samples were then boiled in Laemmli Sample Buffer (Bio-Rad) for 10 minutes at 95\\u0026deg;C, separated on a 10% SDS-PAGE gel, and transferred onto a nitrocellulose membrane for further analysis. Western blotting was performed using primary antibodies MFSD2B (Invitrogen, #PA5-21050, 1:500), BPGM (Proteintech, #17173-1-AP, 1:1,000), GAPDH (Invitrogen, # PA1-987, 1:1,000), ubiquitin antibody (CST, #3936S, 1:500) and b-actin (Proteintech, 66009-1-PBS, 1:2000) in Odyssey Blocking Buffer with 0.2% Tween 20, followed by incubation with secondary antibodies from Abiowell (Goat anti-Rabbit IgG (H\\u0026thinsp;+\\u0026thinsp;L), AWS0002, 1:10000; Goat anti-Mouse IgG (H\\u0026thinsp;+\\u0026thinsp;L), AWS0001, 1:10000). The blots were scanned using the Odyssey Imaging System.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec16\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eImmunoprecipitation\\u003c/h2\\u003e\\u003cp\\u003eImmunoprecipitation (IP) was performed in a 0.5 mL IP solution containing protein lysate and IP buffer (50 mM Tris-HCl, pH 7.5, 150 mM NaCl, and 1% Triton X-100), supplemented with protease inhibitors and 20 mM N-ethylmaleimide. Procedures followed the protocol from BeyoMag Protein A/G Beads Kit (Beyotime, #P2108). Briefly, 3 \\u0026micro;g of MFSD2B (Invitrogen, #PA5-21050) was incubated with pre-washed beads in the IP solution, rotating for 2 hours at room temperature. The beads were then washed three times by applying a magnetic field for 10 seconds each. Washed beads were added to 150 \\u0026micro;L of protein lysate (1 \\u0026micro;g/\\u0026micro;L) and incubated overnight at 4\\u0026deg;C. After incubation, the beads were isolated with a magnetic field for 30 seconds, and the supernatant was saved as a negative control. The bead pellets were then washed three times, each wash lasting 5 minutes. The IP proteins were eluted by boiling the beads in 30 \\u0026micro;L of 2X Laemmli Sample Buffer (Bio-Rad, #1610737) at 100\\u0026deg;C for 10 minutes. The supernatant was then collected by applying a magnetic field for 30 seconds, followed by separation on 10% SDS-PAGE gels for Western blot analysis.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec17\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eImmunofluorescence staining\\u003c/h2\\u003e\\u003cp\\u003eThe mouse eyeball was fixed in 4% paraformaldehyde for 60 minutes, followed by dissection to isolate the retinal tissue. Retinal tissues were blocked with 0.5% Triton X-100 and 2% goat serum in PBS for 1.5 hours at room temperature to permeabilize the tissue and block nonspecific binding. The tissues were then incubated with primary antibody RBPMS (Abcam, ab152101, 1:200) overnight at 4\\u0026deg;C. The next day, sections were washed in PBS and incubated with Alexa Fluor 488-conjugated goat anti-rabbit IgG (Invitrogen, A11008) for 2 hours at room temperature in the dark. Afterward, the sections were rinsed thoroughly in PBS, counterstained with DAPI for 5 minutes at room temperature, and washed four times with PBS. Images were captured using fluorescence microscopy, and staining intensity for the target protein was quantified using ImageJ.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec18\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eToluidine blue\\u003c/h2\\u003e\\u003cp\\u003e Fresh retinal samples were carefully excised into 1 mm\\u0026sup3; pieces and immediately fixed in EM fixative at 4\\u0026deg;C. After washing with 0.1 M phosphate buffer (PB, pH 7.4), the tissue was post-fixed with 1% osmium tetroxide in PB, dehydrated through graded ethanol and acetone, and embedded in 812 resin. Polymerization was performed at 60\\u0026deg;C for 48 hours. Semi-thin sections (1.5 \\u0026micro;m) were cut, stained with 1% toluidine blue, and mounted for light microscopy observation. RGC axons were quantified by using ImageJ with the AxonJ plugin.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec19\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eAnterograde axon transport assay\\u003c/h2\\u003e\\u003cp\\u003eAnterograde axon transport assay was performed as previously described\\u003csup\\u003e\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e\\u003c/sup\\u003e. Briefly, mice were anesthetized (ketamine/xylazine) and intravitreally injected with 2 \\u0026micro;L Alexa Fluor 555-conjugated cholera toxin subunit B (CT-B; 1 mg/mL in PBS) (Thermo Fisher Scientific). After 72 h, mice were perfused with 4% PFA, and brains/eyes were postfixed (24 h), cryoprotected (30% sucrose), OCT-embedded, and sectioned (20 \\u0026micro;m). Alexa Fluor 555 signal was imaged (Zeiss LSM880) in the dorsal lateral geniculate nucleus (LGN) and superior colliculus (SC). CTB intensity was quantified using ImageJ (mean pixel intensity).\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec20\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eUK biobank database\\u003c/h2\\u003e\\u003cp\\u003eFrom UK biobank database, participants with pre-existing infectious diseases, cancer, or glaucoma at baseline were excluded, and newly diagnosed POAG cases were identified using the ICD-10 diagnosis of \\u0026lsquo;primary open-angle glaucoma,\\u0026rsquo; \\u0026lsquo;other glaucoma,\\u0026rsquo; or \\u0026lsquo;unspecified glaucoma\\u0026rsquo; during the follow-up period. Specifically, we identified individuals with glaucoma at baseline (larger than 100,000 cases) based on the following criteria: (i) an ICD-10 diagnosis of \\u0026lsquo;primary open-angle glaucoma,\\u0026rsquo; \\u0026lsquo;other glaucoma,\\u0026rsquo; or \\u0026lsquo;unspecified glaucoma\\u0026rsquo; prior to inclusion; (ii) a positive response to the question, \\u0026lsquo;Has a doctor told you that you have any of the following eye problems?\\u0026rsquo;; or (iii) a response of \\u0026lsquo;glaucoma\\u0026rsquo; to the question, \\u0026lsquo;In the touchscreen, you indicated that a doctor told you about other serious illnesses or disabilities. Could you specify what they are? (non-cancer illnesses)\\u0026rsquo;. Although this definition of glaucoma is broad, approximately 80% of glaucoma cases in white British individuals are likely to meet the diagnostic criteria for POAG\\u003csup\\u003e\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e\\u003c/sup\\u003e. The number of ICD-10 POAG cases was significantly lower, reducing statistical power. Finally, we also identified individuals diagnosed with glaucoma based on an ICD-10 code after cohort inclusion. The control group, comprising 218,331 individuals, was meticulously selected by excluding a total of 66,722 cases based on the following specific criteria: 1. Diabetes-related ocular pathologies. 2. Glaucoma. 3. Visual impairment due to injury or trauma. 4. Cataracts. 5. Macular degeneration. 6. Other significant ocular conditions. 7. Participants who opted not to disclose their eye health status. 8. Participants who were unaware of their eye health status.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec21\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eStatistical analysis\\u003c/h2\\u003e\\u003cp\\u003eAll data were presented as mean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;standard deviation. A Student\\u0026rsquo;s t-test was used for comparing two independent samples, while one-way ANOVA followed by Tukey\\u0026rsquo;s post hoc test was applied for multiple group comparisons. Parametric analyses (Student\\u0026rsquo;s t-tests and one-/two-way ANOVA) were applied only after the underlying distributional assumptions had been formally verified. Statistical analyses were conducted using GraphPad Prism 10.0 software. A \\u003cem\\u003ep\\u003c/em\\u003e-value of \\u0026lt;\\u0026thinsp;0.05 was considered statistically significant.\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003e\\u003cb\\u003eErythrocyte Metabolic Reprogramming in Glaucoma Enhances Oxygen Release at the Cost of Redox and Energy Homeostasis\\u003c/b\\u003e\\u003c/p\\u003e\\u003cp\\u003eTo provide insights into the oxygen supply in glaucoma conditions, we measured oxygen release from erythrocytes via detecting P50 (the oxygen tension corresponding to 50% saturation) value of glaucoma and healthy control erythrocytes (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eA). Notably, we observed a significant correlation between the oxygen release capacity from erythrocytes, denoted as P50, and the severity of glaucomatous optic nerve damage in patients. Specifically, P50 values demonstrated a positive correlation with Mean Deviation (MD) values (r\\u0026thinsp;=\\u0026thinsp;0.4674, p\\u0026thinsp;=\\u0026thinsp;0.014) of visual field, indicating that higher P50 values are associated with less visual field loss. Conversely, P50 values exhibited a negative correlation with the Cup-to-Disc (C/D) ratio\\u003csup\\u003e\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e\\u003c/sup\\u003e (r = -0.5461, p\\u0026thinsp;=\\u0026thinsp;0.0032), suggesting that higher P50 values are linked to a smaller C/D ratio, which corresponds to less severe optic nerve damage (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eB). This finding demonstrated that enhanced oxygen release from erythrocyte in glaucoma patients, which is a compensatory an adaptive response to the increased oxygen demands or hypoxic stress seen in glaucoma\\u003csup\\u003e\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e\\u003cp\\u003e\\u003c/p\\u003e\\u003cp\\u003eEnhanced oxygen release in erythrocytes is often linked to shifts in key metabolic pathways, such as the glycolytic pathway and the RL shunt\\u003csup\\u003e\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e\\u003c/sup\\u003e. To understand the mechanisms driving the enhanced oxygen release observed in glaucoma erythrocytes, we performed high throughput untargeted metabolomics profiling of erythrocytes and plasma collected from glaucoma patients and age/sex-matched healthy controls. The results of PLSDA analysis performed by MetaboAnalyst 6.0 (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://www.metaboanalyst.ca\\u003c/span\\u003e\\u003cspan address=\\\"http://www.metaboanalyst.ca\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) showed healthy control and the glaucoma group could be well distinguished based on metabolite characteristics (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eC). In detail, a total of 300 metabolites were identified and 138 differential metabolites from erythrocytes and 86 differential metabolites from plasma, respectively, were identified based on VIP\\u0026thinsp;\\u0026gt;\\u0026thinsp;1, P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05 criteria (\\u003cb\\u003eTable S2\\u003c/b\\u003e). For pathway enrichment analysis, we used the MetaboAnalyst 6.0 pathway analysis module, employing the hypergeometric test for over-representation analysis and relative-betweenness centrality for pathway topology analysis, with the Kyoto Encyclopedia of Genes and Genomes (KEGG) human metabolic pathway library as the reference database. The background set for enrichment analysis consisted of all quantified metabolites detected in our untargeted metabolomics dataset, ensuring comprehensive representation of the metabolic landscape in erythrocytes and plasma. The analysis revealed that differential metabolites were significantly enriched in purine metabolism, glutathione metabolism, sphingolipid metabolism, glycolysis, and the pentose phosphate pathway (PPP). These metabolic pathways are closely related to the regulation of oxygen release, energy balance, fatty acid synthesis and the homeostasis of ROS in erythrocytes\\u003csup\\u003e\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e\\u003c/sup\\u003e (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eD and S1A-B). Glycolysis is the most important metabolic pathway for erythrocytes, providing the necessary ATP for their survival and function. Notably, most glycolytic intermediates, including fructose 1,6-bisphosphate (FBP), 3-phosphoglycerate (3PG), and pyruvate (PYR), were significantly reduced in glaucoma erythrocytes, however, our quantitative analysis revealed a significant increase in 2,3-bisphosphoglycerate (2,3-BPG) levels in glaucoma erythrocytes (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eE), a key product of the RL shunt known to facilitate oxygen release from erythrocytes\\u003csup\\u003e\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e\\u003c/sup\\u003e. Under hypoxic conditions, up to 25% of glucose in erythrocytes is directed through the RL shunt within glycolysis, rather than PPP, to increase 2,3-BPG production\\u003csup\\u003e\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e\\u003c/sup\\u003e. Thus, our findings raise a possibility that, as demand of oxygen from tissues, such as retina and optic nerve head\\u003csup\\u003e\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e\\u003c/sup\\u003e, in glaucoma conditions, increased 2,3-BPG production is under regulation by channeling glucose metabolism toward RL shunt within glycolysis versus PPP in glaucoma erythrocytes to enhance oxygen release. To test this intriguing hypothesis, we performed \\u003cem\\u003ein vitro\\u003c/em\\u003e glucose flux analysis using isotopically labeled 1,2,3-\\u003csup\\u003e13\\u003c/sup\\u003eC\\u003csub\\u003e3\\u003c/sub\\u003e-glucose in both control and glaucoma erythrocytes. This allowed tracking of glucose uptake, metabolic routing, and reprogramming in primary erythrocytes. Consistent with metabolomics profiling, the data from glucose isotopically labeled flux tracing revealed a notable increase in glycolytic flux towards 2,3-BPG via the RL shunt in glaucoma erythrocytes (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eF). Mechanistically, we observed significant elevated protein levels of Bisphosphoglycerate Mutase (BPGM), which is the enzyme that is responsible for the production of 2,3-BPG through the RL shunt, in glaucoma erythrocytes (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eG). Consequently, lower levels of glycolysis and PPP caused defective energy homeostasis, as determined by adenylate pool (\\u003cb\\u003eFigure \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003eC\\u003c/b\\u003e), and impaired oxidative balance, as indicated by higher ROS levels and reduced glutathione (GSH) to oxidized glutathione (GSSG) ratio (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eH), in glaucoma erythrocytes.\\u003c/p\\u003e\\u003cp\\u003eAdditionally, our data suggested that glucose uptake was significantly lower in glaucoma erythrocytes compared to controls, as evidenced by reduced levels of labeled glucose inside glaucoma erythrocytes and increased labeled glucose remaining in the supernatant after 30 minutes of incubation (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eF \\u003cb\\u003eand I\\u003c/b\\u003e). We further confirmed significantly increased plasma glucose levels in glaucoma patients (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eJ \\u003cb\\u003eand\\u003c/b\\u003e Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). Thus, these results prompted us to examine the glucose transporter GLUT1 in control and glaucoma erythrocytes. Consistently, GLUT1 protein levels were reduced in glaucoma erythrocytes compared to controls (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eK). Altogether, we provide human evidence that glaucoma pathogenesis involves a systemic recalibration of erythrocyte metabolism. This reprogramming prioritizes oxygen release, driven by BPGM-mediated enhancement of the RL shunt, to satisfy heightened tissue demand. However, this adaptation forces a detrimental trade-off, ultimately undermining the erythrocyte's own energy stability and oxidative resilience (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eL).\\u003c/p\\u003e\\u003cdiv id=\\\"Sec23\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eDefective MFSD2B Transporter Drives Erythrocyte S1P Dyshomeostasis in Glaucoma\\u003c/h2\\u003e\\u003cp\\u003eOur comprehensive metabolomic analysis, encompassing both untargeted metabolomics and quantitative analysis revealed significant alterations in the erythrocyte metabolome of glaucoma patients. Interestingly, we found elevated intracellular levels of sphingosine 1-phosphate (S1P) across both POAG and PACG erythrocytes (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA-B and S2A). S1P as an erythrocyte enriched biolipid is well known to enhance oxygen delivery under hypoxia, suggesting a potential adaptive mechanism in glaucoma similar to that observed in other hypoxic states\\u003csup\\u003e\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e\\u003c/sup\\u003e. The observed reduction in ceramide and sphingosine levels (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eC and S2B), the metabolic precursors to S1P, prompted us to assess sphingosine kinase activity. We found that SPHK1, the sole sphingosine kinase in erythrocytes\\u003csup\\u003e\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e\\u003c/sup\\u003e, exhibited significantly increased activity in glaucoma (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eD), demonstrating enhanced intracellular S1P biogenesis. Interestingly, accurate quantification revealed that plasma S1P levels were markedly reduced despite elevated intracellular S1P levels in erythrocytes, suggesting impaired S1P release under glaucomatous conditions, affecting both POAG and PACG (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eE-F and S2C). To address this, we assessed MFSD2B, the primary erythrocyte S1P transporter\\u003csup\\u003e\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e\\u003c/sup\\u003e, and found significantly reduced membrane MFSD2B levels in glaucoma erythrocytes (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eG). Further investigation revealed that ubiquitination, a key process for modifying protein levels and functions in erythrocytes, was significantly increased for membrane MFSD2B in glaucoma erythrocytes (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eH). Thus, we revealed that increased erythrocyte SphK1 activity and reduced MFSD2 protein are dual mechanisms underlying accumulation of intracellular S1P but substantially reduction of circulating S1P in glaucoma patients. More importantly, we observed a positive correlation between plasma S1P levels in glaucoma patients and the thickness of the retinal nerve fiber layer (RNFL) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eI), a parameter that is closely associated with the density of RGCs\\u003csup\\u003e\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e\\u003c/sup\\u003e. This finding aligns with previous studies indicating that S1P signaling is essential for RGC survival\\u003csup\\u003e\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e\\u003cp\\u003e\\u003c/p\\u003e\\u003cp\\u003eGiven our findings of elevated SphK1 in erythrocytes in glaucoma patients, we prompted to conduct proof-of-principle genetic studies to determine the role of erythrocyte SphK1-mediated production of both intracellular and plasma S1P using erythrocyte-specific \\u003cem\\u003eSphK1\\u003c/em\\u003e knockout mice \\u003cem\\u003e(eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e\\u0026minus;/\\u0026minus;\\u003c/em\\u003e\\u003c/sup\\u003e\\u003cem\\u003e)\\u003c/em\\u003e. Consistent with previous study\\u003csup\\u003e\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e\\u003c/sup\\u003e, under normal physiological conditions, the baseline P50 levels showed no significant differences between young (3 months-old) and aged (14 months-old) \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e\\u0026minus;/\\u0026minus;\\u003c/em\\u003e\\u003c/sup\\u003e mice and their \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e control counterparts (\\u003cb\\u003eFigure S2D\\u003c/b\\u003e). However, \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e\\u0026minus;/\\u0026minus;\\u003c/em\\u003e\\u003c/sup\\u003e mice exhibited a significant reduction in RGC density. Additionally, aged \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e\\u0026minus;/\\u0026minus;\\u003c/em\\u003e\\u003c/sup\\u003e mice displayed elevated IOP compared to controls (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eJ-K and S2E). These results demonstrate that proper S1P release from erythrocytes is essential for the protection of RGCs.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec24\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eL-Carnitine Restores Erythrocyte Membrane Integrity and Redox Balance via the Lands cycle and PPP\\u003c/h2\\u003e\\u003cp\\u003eSince the protein levels of both MFSD2B and GLUT1 in erythrocyte membranes were significantly reduced under glaucoma conditions (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eK), we hypothesized that membrane integrity of glaucoma erythrocytes was compromised. Given that ROS potentially induce lipid peroxidation\\u003csup\\u003e\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e\\u003c/sup\\u003e and increased in glaucoma erythrocytes (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003eH), and lipid peroxidation product 9-oxononanoic acid\\u003csup\\u003e\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e\\u003c/sup\\u003e also increased in glaucoma erythrocytes (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eA). Using BODIPY 581/591 C11, we confirmed increased membrane lipid peroxidation in glaucoma erythrocytes (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eB), indicating that glaucoma-associated oxidative stress induces ROS, leading to lipid peroxidation and impairing membrane protein integrity\\u003csup\\u003e\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e\\u003c/sup\\u003e. To further investigate lipid peroxidation, which preferentially oxidizes polyunsaturated phosphatidylcholines (PUFA-PCs) than saturated fatty acid phosphatidylcholines (SFA-PC)\\u003csup\\u003e\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e\\u003c/sup\\u003e, we conducted a lipidomic analysis. This revealed a marked decrease in the ratio of key PUFA-PCs (including PC (16:0_20:4) and PC (16:0_22:6)) to the SFA-PC(16:0_16:0) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eC). This signature lipid profile confirms that glaucoma erythrocytes undergo significant lipid peroxidation. The Lands cycle is critical for maintaining erythrocyte membrane integrity by remodeling phospholipids\\u003csup\\u003e\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e\\u003c/sup\\u003e. Lipidomic analysis also revealed reduced levels of lysophosphatidylcholine (LPC) and phosphatidylcholine (PC) species in glaucoma erythrocytes (\\u003cb\\u003eFigure S3A\\u003c/b\\u003e), with no significant change in the sum LPC-to-PC ratio (\\u003cb\\u003eFigure S3B\\u003c/b\\u003e), suggesting that the activities of phospholipase A2 (PLA2) and lysophosphatidylcholine acyltransferase (LPCAT), are likely unaffected by glaucoma conditions\\u003csup\\u003e\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e\\u003c/sup\\u003e. However, the LPC(16:0)/PC(16:0) ratio, a key indicator of membrane repairing regulated by acyl-CoA\\u003csup\\u003e\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e\\u003c/sup\\u003e, was significantly altered (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eD), indicating defective membrane repair due to impaired conversion of LPC(16:0) to PC(16:0). Although erythrocytes lack fatty acid β-oxidation capacity, carnitine-dependent acyl-carnitine pools is essential for fueling the Lands cycle for damaged membrane lipid repair\\u003csup\\u003e\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e\\u003c/sup\\u003e. Quantitative metabolomics analysis revealed decreased levels of L-carnitine, in both erythrocytes and plasma of glaucoma patients (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eE), alongside a deficient acyl-carnitine pool (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eF). These findings suggest that impaired Lands cycle activity in glaucoma erythrocytes potentially results from reduced carnitine-derived acyl-carnitine.\\u003c/p\\u003e\\u003cp\\u003e\\u003c/p\\u003e\\u003cp\\u003eTo investigate this, we cultured glaucoma patient erythrocytes in 20% autologous plasma and treated them with 100 \\u0026micro;M L-carnitine for 6 hours. This treatment significantly potentiated the LPC-to-PC conversion of the Lands cycle (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eG and S3C), which consequently restored MFSD2B protein expression on the erythrocyte membrane (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eH) and increased S1P release into the culture supernatant (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eI). Concurrently, L-carnitine treatment improved glucose metabolism. We observed a modest recovery of GLUT1 protein levels (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eJ) and a significant increase in glucose uptake (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eK). More importantly, L-carnitine redirected glucose flux into the pentose phosphate pathway (PPP), which was associated with a marked improvement in redox homeostasis, as evidenced by reduced ROS levels and an increased GSH/GSSG ratio (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eL-M). To determine if the antioxidant effect of L-carnitine was dependent on the PPP, we also treated erythrocytes with the PPP inhibitor 6-aminonicotinamide (6AN)\\u003csup\\u003e\\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e\\u003c/sup\\u003e. The blockade of PPP flux completely abrogated L-carnitine's ability to reduce ROS in glaucoma erythrocytes (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eN). Subsequently, we found that L-carnitine's reduction of ROS-induced membrane lipid peroxidation was also dependent on the PPP, as this protection was nullified by 6AN (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eO).\\u003c/p\\u003e\\u003cdiv id=\\\"Sec25\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003eL-carnitine Modulates Erythrocyte Homeostasis and Restores Circulating S1P Levels in Glaucoma Models\\u003c/h2\\u003e\\u003cp\\u003eTo evaluate the therapeutic potential of L-carnitine, we employed a chronic glaucoma (cGLA) model induced by magnetic bead occlusion, which elicited a sustained intraocular pressure (IOP) elevation (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eA and S4A). This model recapitulated key systemic features of human glaucoma, including elevated systolic blood pressure and a pro-inflammatory leukogram with peripheral neutrophilia (\\u003cb\\u003eFigure S4B-C\\u003c/b\\u003e, Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). Furthermore, circulating erythrocytes exhibited enhanced oxygen release, mirroring our observations in glaucoma patients, after constant IOP elevated (\\u003cb\\u003eFigure S4D\\u003c/b\\u003e). These concordant systemic findings corroborate the translational relevance of our cGLA paradigm for evaluating therapeutic interventions targeting both intra-ocular pathology and associated systemic sequelae. In \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA mice, L-carnitine slightly reduced IOP but restored the compensatory erythrocyte oxygen release, a response that was absent in \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e\\u0026minus;/\\u0026minus;\\u003c/em\\u003e\\u003c/sup\\u003e mice, confirming the essential role of S1P in this hypoxic adaptation\\u003c/p\\u003e\\u003cp\\u003e\\u003c/p\\u003e\\u003cp\\u003eAlthough IOP was only slightly reduced by L-carnitine in \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA mice, treatment restored compensatory oxygen release, a response absents in \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e\\u0026minus;/\\u0026minus;\\u003c/em\\u003e\\u003c/sup\\u003e mice, confirming S1P\\u0026rsquo;s role in hypoxia adaptation (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eA-B and S4E). Metabolomic profiling of erythrocytes revealed a significant depletion of L-carnitine and long-chain acylcarnitines (C16, C18) in cGLA, which were replenished by L-carnitine treatment (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eC). This restoration of acyl-carnitine pools is poised to fuel the Lands cycle for membrane lipid repair. Accordingly, L-carnitine maintained membrane expression of the S1P transporter MFSD2B, which is defective in cGLA, without altering SphK1 activity (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eD-E). This led to a significant restoration of circulating S1P levels (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eF). Concurrently, L-carnitine restored GLUT1 expression (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eG) and enhanced glucose uptake, preferentially directing flux into the PPP over glycolysis (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eH-I). This metabolic shift attenuated oxidative stress, as shown by reduced ROS levels and an improved GSH/GSSG ratio (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eJ-K), and decreased ROS-induced lipid peroxidation and their products (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eL and S4F). The ATP/ADP ratio in cGLA erythrocytes was also partially restored (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eM). As a result, L-carnitine preserved erythrocyte integrity and prolonged circulating erythrocytes survival, thereby reversing the anemia and erythrocyte depletion consistently reported in human glaucoma (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eN). Collectively, our in vitro and in vivo data support a mechanistic model wherein L-carnitine replenishes acyl-carnitine pools to fuel the Lands cycle, thereby repairing membrane proteins like MFSD2B and GLUT1. This repair facilitates S1P release and glucose uptake, with the latter being channeled into the PPP to bolster antioxidant defenses and inhibit lipid peroxidation to prevent further membrane compromise (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eO).\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec26\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003eL-Carnitine Preserves RGC Survival and Function via S1P-Dependent Manners in Glaucoma Models\\u003c/h2\\u003e\\u003cp\\u003eTo further evaluate the neuroprotective effects of L-carnitine on RGCs in IOP-induced damage, hematoxylin-eosin (HE) staining of the anterior chamber angle revealed magnetic bead accumulation and demonstrated significant thinning of the RNFL and loss of RGCs in \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA mice compared to normal controls (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eA). L-carnitine treatment significantly reduced RGC loss and preserved anterograde axoplasmic transport, assessed by cholera toxin B (CTB) tracing to the dorsal lateral geniculate nucleus (LGN) and superior colliculus (SC), in \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA mice but not in \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e\\u0026minus;/\\u0026minus;\\u003c/em\\u003e\\u003c/sup\\u003e cGLA mice (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eB-D). Electrophysiological assessments further elucidated L-carnitine\\u0026rsquo;s neuroprotective effects. Flash visual evoked potentials (FVEP), which reflect the functional integrity of the visual pathway from retina to occipital cortex, showed prolonged P1 latency and reduced N1-P1 amplitude in \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA mice, indicative of axonal damage and reduced RGC numbers or visual pathway dysfunction, respectively (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eE). L-carnitine treatment significantly shortened P1 latency and increased N1-P1 amplitude in \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA mice, but not in \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e\\u0026minus;/\\u0026minus;\\u003c/em\\u003e\\u003c/sup\\u003e cGLA mice, highlighting S1P-dependent restoration of visual pathway function (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eE). Flash electroretinography (FERG), assessing overall retinal function, revealed significantly reduced a-wave (photoreceptor function) and b-wave (inner retinal layer function) amplitudes in \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA mice (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eF). L-carnitine treatment mitigated these deficits in \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e cGLA mice, preserving overall retinal function (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eF). Given that plasma S1P remains significantly deficient in \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e\\u0026minus;/\\u0026minus;\\u003c/em\\u003e\\u003c/sup\\u003e cGLA mice despite L-carnitine treatment (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eF), while oxygen release is comparably restored in both \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e and \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e\\u0026minus;/\\u0026minus;\\u003c/em\\u003e\\u003c/sup\\u003e cGLA treated with L-carnitine (\\u003cb\\u003eFigure S4E\\u003c/b\\u003e), we suggest that the differential therapeutic efficacy of L-carnitine is primarily attributable to the restoration of systemic S1P, rather than the improvement in oxygen delivery.\\u003c/p\\u003e\\u003cp\\u003e\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec27\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003eS1P Supports RGCs by Enhancing Fatty Acid β-Oxidation to Restore TCA Cycle and ATP Production\\u003c/h2\\u003e\\u003cp\\u003eTo elucidate the mechanism by which erythrocyte-derived S1P mediates RGCs survival in L-carnitine-treated glaucoma, we analyzed retinal metabolism in the cGLA model. Metabolomic profiling revealed a pronounced bioenergetic deficit in cGLA retinas, characterized by significantly depleted TCA cycle intermediates and ATP levels, alongside reduced pyruvate and elevated lactate, a profile indicative of a forced shift toward anaerobic glycolysis despite adequate glucose. L-carnitine treatment effectively restored TCA cycle metabolites and ATP (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003eA \\u003cb\\u003eand B\\u003c/b\\u003e). However, isotopic glucose tracing confirmed that the glycolytic flux toward lactate persisted despite treatment, demonstrating that the restoration of the TCA cycle was not fueled by glucose-derived pyruvate (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003eC). This pointed to fatty acid β-oxidation (FAO) as an alternative source of acetyl-CoA. Indeed, the restoration of TCA cycle intermediates by L-carnitine was entirely absent in the RGCs of \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e\\u0026minus;/\\u0026minus;\\u003c/em\\u003e\\u003c/sup\\u003e cGLA mice, indicating a strict dependence on erythrocyte-derived S1P for this metabolic rescue (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003eD, S5A). We then investigated the carnitine shuttle, a prerequisite for FAO. While L-carnitine and its long-chain fatty acid substrates (e.g., palmitic acid) were not deficient in cGLA RGCs (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003eE, S5B), a critical divergence was observed upon L-carnitine treatment: only in \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e mice did we detect a significant accumulation of long-chain acylcarnitines (C16, C18) with a concomitant consumption of their fatty acid substrates (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003eE-F, S5B). This specific metabolic signature, successful substrate conversion only in the presence of erythrocyte SPHK1, identifies the esterification of long-chain fatty acids into acylcarnitines, the CPT1A-mediated rate-limiting step of FAO, as the S1P-dependent bottleneck.\\u003c/p\\u003e\\u003cp\\u003e\\u003c/p\\u003e\\u003cp\\u003eGuided by single-cell RNA-seq data showing high expression of \\u003cem\\u003eCPT1A\\u003c/em\\u003e and S1PR1/2 in RGCs (\\u003cb\\u003eFigure S5C\\u003c/b\\u003e), we found that L-carnitine treatment robustly increased CPT1A, but not CPT2, protein expression in RGCs, an effect that was abolished in \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e\\u0026minus;/\\u0026minus;\\u003c/em\\u003e\\u003c/sup\\u003e mice (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003eG and S5D). This established that erythrocyte-derived S1P is essential for upregulating CPT1A. Mechanistically, S1P treatment directly enhanced the phosphorylation of AMPKα (Thr172) in RGCs under oxygen-glucose deprivation/reperfusion conditions (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003eH). Furthermore, both pharmacological AMPKα activation and inhibition demonstrated that S1P induce CPT1A expression is regulated through an AMPKα-dependent pathway\\u003csup\\u003e\\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e\\u003c/sup\\u003e (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003eI), which was strongly correlated with AMPKα phosphorylation levels (\\u003cb\\u003eFigure S5E\\u003c/b\\u003e). Functionally, this S1P-AMPKα-CPT1A axis was essential for bioenergetic and survival outcomes. S1P treatment boosted ATP generation and prevented apoptosis in stressed RGCs, in the presence of L-carnitine (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003eJ, S5F). Critically, translating these findings to a human context, we showed that plasma from glaucoma patients failed to protect murine RGCs in stress culture. L-carnitine alone provided only a modest benefit, but the combination of L-carnitine and S1P robustly prevented RGC death under oxygen-glucose deprivation (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003eK). In summary, we define a coherent neuroprotective pathway wherein L-carnitine-stimulated erythrocyte S1P release activates an S1PR1-AMPKα-CPT1A signaling axis in RGCs. This enhances the utilization of L-carnitine for fatty acid β-oxidation, restoring mitochondrial energy production and preventing apoptosis, thereby salvaging RGCs in glaucoma (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003eL).\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec28\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eS1P is a Newly Identified Biomarker in Primary Glaucoma Patients\\u003c/h2\\u003e\\u003cp\\u003eOur findings highlight that glaucoma is not just a localized ocular disease but a systemic condition marked by extensive metabolic and lipid reprogramming in both erythrocytes and plasma. Plasma metabolites, which provide insights into dynamic metabolic states, serve as important indicators for assessing glaucoma\\u0026rsquo;s systemic impact. To validate our findings, we took advantage of analyzing the UK Biobank data using NMR-based metabolomics data from more than 100,000 individuals. Intriguingly, strong associations between specific metabolites and the risk of POAG, as determined by Cox proportional hazards regression adjusted for age, sex, and BMI. Notably, protective metabolites, including citrate, lactate, and pyruvate, were associated with a reduced POAG risk (Odds ratio (OR)\\u0026thinsp;\\u0026lt;\\u0026thinsp;1.0), while higher levels of metabolites including tyrosine, glucose, phenylalanine, valine, leucine, isoleucine, branched-chain amino acids (BCAAs), and glutamine were associated with an increased POAG risk (OR\\u0026thinsp;\\u0026gt;\\u0026thinsp;1.0) (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig7\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003eA and S6A). Targeted metabolic profiling of our glaucoma cohort corroborated these findings, showing reduced levels of protective metabolites (e.g., lactate, pyruvate) and elevated levels of risk-associated metabolites (e.g., glucose, tyrosine, phenylalanine, valine, glutamine) in glaucoma patient plasma compared to controls (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig7\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003eB and S6B-C). This alignment between datasets strengthens the validity of our metabolomic findings and underscores the potential of these metabolic signatures as indicators of glaucoma\\u0026rsquo;s systemic pathology.\\u003c/p\\u003e\\u003cp\\u003e\\u003c/p\\u003e\\u003cp\\u003eTo identify novel biomarkers for glaucoma, we applied a random forest-based biomarker discovery approach using metabolomic profiles from erythrocytes and plasma. This analysis revealed the top 10 candidate biomarkers, prominently highlighting L-arginine with area under the curve (AUC) of 78 in erythrocytes and 98 in plasma, aligning with previous studies\\u003csup\\u003e\\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e\\u003c/sup\\u003e. Additionally, we found S1P showed strong biomarker potential, with AUC values of 74 in erythrocytes and 99 in plasma (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig7\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003eC). Further pathway analysis of lipid metabolites from both control and glaucoma erythrocyte and plasma identified sphingosine metabolism as significantly enriched, emphasizing its possible involvement in glaucoma pathogenesis (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig7\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003eD). In conclusion, our findings emphasize that glaucoma extends beyond a localized ocular disorder to involve systemic metabolic alterations, underscoring its complex pathophysiology. Our data, validated between the UK Biobank and our own cohort, reinforces the robustness of these metabolic signatures. Furthermore, S1P emerged as a robust biomarker, showing strong diagnostic potential with high AUC values, suggesting it may serve as a valuable indicator for early detection and monitoring of glaucoma. The enrichment of the sphingosine metabolic pathway in glaucoma-affected samples further highlights the importance of S1P metabolism in disease progression and offers promising targets for therapeutic intervention. Furthermore, the significant reduction in L-carnitine and acyl-carnitine levels, particularly acyl-C18:2-OH (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig7\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003eC), in erythrocytes suggests their utility as additional diagnostic indicators for the early detection and monitoring of glaucoma. Together, these insights advance our understanding of glaucoma's systemic nature and provide a foundation for biomarker-driven diagnostics and targeted metabolic therapies.\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThis study establishes that glaucoma fundamentally reprograms erythrocyte metabolism, shifting glycolytic flux toward the Rapoport-Luebering shunt via elevated BPGM. While this adaptation enhances oxygen release (increased P50) to counter retinal hypoxia, it occurs at the expense of pentose phosphate pathway activity, compromising antioxidant defenses and promoting lipid peroxidation. Concurrent deficiencies in L-carnitine and acylcarnitine pools impair the Lands cycle, preventing repair of membrane transporters MFSD2B and GLUT1. The resulting trapped intracellular S1P and reduced glucose uptake create a vicious cycle: impaired erythrocyte glucose metabolism contributes to systemic glucose dysregulation, potentially explaining the glaucoma-diabetes comorbidity\\u003csup\\u003e\\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e\\u003c/sup\\u003e, while S1P deficiency exacerbates retinal ganglion cell loss.\\u003c/p\\u003e\\u003cp\\u003eNotably, L-carnitine administration reverses this pathology through a coordinated mechanism: replenishing acyl-carnitine pools to fuel Lands cycle-mediated membrane repair, restoring S1P release and glucose uptake. The redirected glucose flux through the PPP enhances antioxidant capacity, while circulating S1P induces the AMPKα-CPT1A axis, promoting fatty acid oxidation and restoring mitochondrial function in RGCs in glaucoma conditions. Particularly, the genotype-specific efficacy of L-carnitine, observed in \\u003cem\\u003eSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003eflox\\u003c/em\\u003e\\u003c/sup\\u003e but not \\u003cem\\u003eeSphK1\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e\\u0026minus;/\\u0026minus;\\u003c/em\\u003e\\u003c/sup\\u003e mice, definitively establishes S1P as a central mediator of this protection. The observed metabolic shift toward anaerobic glycolysis and impaired oxidative phosphorylation, indicated by reduced pyruvate, depleted TCA cycle metabolites, and increased lactate in cGLA retina, aligns with prior reports of mitochondrial dysfunction in glaucoma\\u003csup\\u003e\\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e52\\u003c/span\\u003e\\u003c/sup\\u003e. The correlation between AMPKα phosphorylation, CPT1A expression, and RGC survival underscores a coherent signaling axis that integrates extracellular S1P cues with intracellular metabolic reprogramming (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig7\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003eE). These results expand the known roles of S1P beyond its canonical functions in vascular regulation and inflammation\\u003csup\\u003e\\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e53\\u003c/span\\u003e\\u003c/sup\\u003e. By demonstrating that S1P signaling directly enhances FAO in RGCs, a cell type with high energy demands, we identify a previously unrecognized neuroprotective pathway. This neuroprotective pathway is conserved across glaucoma subtypes, as both POAG and PACG patients exhibit similar erythrocyte S1P dysregulation, positioning the SPHK1-S1P axis as a unifying therapeutic target. Our findings also expand S1P's role beyond vascular regulation to direct metabolic support of neurons and reconcile age-related glaucoma risk with observed erythrocyte aging phenotypes\\u003csup\\u003e\\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e,\\u003cspan citationid=\\\"CR55\\\" class=\\\"CitationRef\\\"\\u003e55\\u003c/span\\u003e\\u003c/sup\\u003e.\\u003c/p\\u003e\\u003cp\\u003eFinally, we integrated data from the UK Biobank with our own cohort to examine the association between plasma metabolites and glaucoma development. The findings further underscore that glaucoma is not merely a localized ocular condition but a systemic disease involving widespread metabolic reprogramming. Analysis of UK Biobank data confirmed significant associations between specific metabolites and POAG risk and these results align with our own cohort data, where we observed decreased levels of protective metabolites and elevated levels of detrimental metabolites in glaucoma patients, reinforcing the robustness of our metabolic profiling. Through comprehensive untargeted metabolomics, we identified distinct metabolic changes in both erythrocytes and plasma, which together reveal a complex interaction between systemic metabolic dysregulation and glaucoma pathogenesis. The fact that many of these metabolites are involved in key energy and oxidative stress pathways supports the notion that systemic metabolic imbalances may exacerbate the progression of glaucoma. Particularly, our investigation into potential glaucoma biomarkers through random forest-based analysis identified S1P emerged as a particularly promising biomarker, achieving high diagnostic accuracy with AUC values of 74 in erythrocytes and 99 in plasma. It\\u0026rsquo;s worth noting that while S1P is recognized for its role in neuroprotective effects, it also has pro-inflammatory properties that could precipitate significant side effects if administered directly\\u003csup\\u003e\\u003cspan citationid=\\\"CR56\\\" class=\\\"CitationRef\\\"\\u003e56\\u003c/span\\u003e\\u003c/sup\\u003e. Excessive S1P could inadvertently amplify inflammatory pathways, which is particularly concerning given the delicate balance of immune modulation in glaucoma pathology. In contrast, our approach with L-carnitine aims to support the endogenous release of S1P in a regulated, physiologically compatible manner, thereby mitigating potential inflammatory side effects while still sustaining S1P\\u0026rsquo;s neuroprotective role in glaucoma. However, this study may be subject to several limitations, including small sample sizes and the generalizability of our observed erythrocyte metabolic reprogramming and systemic S1P deficiency to normal-tension glaucoma (NTG) patients remains to be determined. Given the shared endpoint of RGCs degeneration, it would be of particular interest for future studies to investigate whether similar disruptions in the SPHK1-S1P axis and the efficacy of L-carnitine are also present in NTG.\\u003c/p\\u003e\\u003cp\\u003eIn sum, our findings highlight the systemic nature of glaucoma, with significant metabolic reprogramming in erythrocytes. We also elucidate the role of intracellular S1P accumulation in driving metabolic reprogramming in glaucoma erythrocytes. The observed alterations in glucose uptake, glycolytic flux, PPP activity, antioxidant capacity, and Lands cycle underscore the multifaceted metabolic challenges faced by glaucoma erythrocytes. Our findings not only expand our understanding of glaucoma as a systemic disease but also offer new avenues for erythrocyte-based therapeutic interventions, with L-carnitine emerging as a potential strategy to slow glaucoma progression.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe patient cohort was approved by the Institutional Review Board of Central South University Committee for the Protection of Human Subjects (2024121597), and written informed consent was obtained from all participants.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare no competing interests.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis work was supported by NSFC82230023 (Y.X.), NSFC82171058 (X.X.) and Feifan Scholar Fund of Xiangya Hospital of Central South University (Y.X.), NKRDPC2024YFA1108704 (X.X.), RDPHFRL2024PT5107 (X.X.), NSFC82301202 (Y.L), CPSF2023M733953 (Y.L.), NSFHP2025JJ60575 (Y.L.), NSFHP2024JJ4087 (Q.L.), NSFC82402081 (Q.L.), CPSF GZB20240866 (C.C.), NSFC82400873 (C.C.),\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors\\u0026rsquo; Contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eY.L., Q.L. and YD.W designed and conducted the mouse experiments and human sample measurements, analyzed the experimental data, drew the figures and wrote the manuscript; T.C. performed the lipidomic analysis; C.L. analyzed UK biobank data; C.C. and T.X. provided expertise in metabolomics design and analyses; YY.W. provided expertise in immunoprecipitation design; X.X. provided expertise in determining clinical types of glaucoma and helped with human subject; Y.X. oversaw the design of experiments and interpretation of results, the writing and organization of the manuscript and did final editing.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWe are grateful to the Biomedical Center, Institute for Advanced Study of Central South University for providing the equipment used in this study, including the flow cytometry, confocal microscopy, visual evoked potential (VEP), and electroretinography (ERG) instruments. National Natural Science Foundation of China\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eMarando, C. M., Shen, Lucy Q. Glaucoma. (2021). https://doi.org/10.1007/978-3-030-63978-5_1\\u003c/li\\u003e\\n\\u003cli\\u003eBest, S. Glaucoma Diagnosis and Management. \\u003cem\\u003eClinical \\u0026amp; Experimental Ophthalmology\\u003c/em\\u003e \\u003cstrong\\u003e34\\u003c/strong\\u003e, 706-707 (2006). https://doi.org/10.1111/j.1442-9071.2006.01326.x\\u003c/li\\u003e\\n\\u003cli\\u003eZhou, X. J. W., Ren Yi. Current situation and prospect of minimally invasive glaucoma surgery in childhood glaucoma. \\u003cstrong\\u003e23\\u003c/strong\\u003e (2023). https://doi.org/10.3980/j.issn.1672-5123.2023.1.10\\u003c/li\\u003e\\n\\u003cli\\u003eDavis, B. M., Crawley, L., Pahlitzsch, M., Javaid, F. \\u0026amp; Cordeiro, M. F. Glaucoma: the retina and beyond. \\u003cem\\u003eActa Neuropathol\\u003c/em\\u003e \\u003cstrong\\u003e132\\u003c/strong\\u003e, 807-826 (2016). https://doi.org/10.1007/s00401-016-1609-2\\u003c/li\\u003e\\n\\u003cli\\u003eBasavarajappa, D.\\u003cem\\u003e et al.\\u003c/em\\u003e Signalling pathways and cell death mechanisms in glaucoma: Insights into the molecular pathophysiology. \\u003cem\\u003eMol Aspects Med\\u003c/em\\u003e \\u003cstrong\\u003e94\\u003c/strong\\u003e, 101216 (2023). https://doi.org/10.1016/j.mam.2023.101216\\u003c/li\\u003e\\n\\u003cli\\u003eWang, Z., Wiggs, J. L., Aung, T., Khawaja, A. P. \\u0026amp; Khor, C. C. The genetic basis for adult onset glaucoma: Recent advances and future directions. \\u003cem\\u003eProg Retin Eye Res\\u003c/em\\u003e \\u003cstrong\\u003e90\\u003c/strong\\u003e, 101066 (2022). https://doi.org/10.1016/j.preteyeres.2022.101066\\u003c/li\\u003e\\n\\u003cli\\u003eSiegfried, C. J., Shui, Y. B., Holekamp, N. M., Bai, F. \\u0026amp; Beebe, D. C. Oxygen distribution in the human eye: relevance to the etiology of open-angle glaucoma after vitrectomy. \\u003cem\\u003eInvest Ophthalmol Vis Sci\\u003c/em\\u003e \\u003cstrong\\u003e51\\u003c/strong\\u003e, 5731-5738 (2010). https://doi.org/10.1167/iovs.10-5666\\u003c/li\\u003e\\n\\u003cli\\u003eHusain, S. \\u0026amp; Leveckis, R. Pharmacological regulation of HIF-1alpha, RGC death, and glaucoma. \\u003cem\\u003eCurr Opin Pharmacol\\u003c/em\\u003e \\u003cstrong\\u003e77\\u003c/strong\\u003e, 102467 (2024). https://doi.org/10.1016/j.coph.2024.102467\\u003c/li\\u003e\\n\\u003cli\\u003eTezel, G. \\u0026amp; Wax, M. B. Hypoxia-inducible factor 1alpha in the glaucomatous retina and optic nerve head. \\u003cem\\u003eArch Ophthalmol\\u003c/em\\u003e \\u003cstrong\\u003e122\\u003c/strong\\u003e, 1348-1356 (2004). https://doi.org/10.1001/archopht.122.9.1348\\u003c/li\\u003e\\n\\u003cli\\u003eJassim, A. H. \\u0026amp; Inman, D. M. 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While the role of vascular insufficiency is recognized, the specific contribution of erythrocytes has remained elusive. This study identifies a novel erythrocyte-centric pathway in glaucoma pathogenesis using integrated metabolomic, lipidomic, and functional analyses of human erythrocytes and validated mouse models. We uncover compensatory erythrocyte reprogramming: elevated intracellular bisphosphoglycerate mutase drives glycolysis toward the Rapoport-Luebering pathway to enhance oxygen release, but at the cost of pentose phosphate pathway suppression and oxidative vulnerability, which led to ROS-induced lipid peroxidation and compromise cell membrane. Concomitant L-carnitine depletion impairs the Lands cycle, failing to repair membrane sphingosine 1-phosphate (S1P) transporter MFSD2B and curtailing extracellular S1P release, yielding systemic S1P deficiency. L-carnitine supplementation emerges as a targeted erythrocyte therapy, replenishing acylcarnitine pools to restore Lands cycle flux (lysophosphatidylcholine (LPC) to phosphatidylcholine (PC) conversion) and support membrane repair of proteins like MFSD2B and GLUT1. This repair facilitates S1P release and glucose uptake, with the latter channeled into the PPP to bolster antioxidant defenses and inhibit ROS-induced lipid peroxidation, thereby preventing further membrane compromise. Extracellular S1P triggers the AMPKα-CPT1A axis to support fatty acid β-oxidation, rescuing TCA cycle, ATP levels, and cell survival of glaucoma RGCs. Integrating data from the UK Biobank and our cohort supports plasma S1P as a novel pathogenic biomarker for glaucoma, linking erythrocyte dysfunction to neurodegenerative diseases. Our work repositions erythrocytes as pivotal mediators of glaucoma, framing the glaucoma as a systemic hematologic-ophthalmic disorder and providing a translational framework for erythrocyte metabolism-targeted interventions.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Erythrocyte-Targeted Therapy for Glaucoma: Neuroprotection Through Erythrocyte-Derived Sphingosine 1-Phosphate-Enhanced Fatty Acid β-Oxidation via the AMPKα-CPT1A Axis\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-12-03 11:58:29\",\"doi\":\"10.21203/rs.3.rs-8165516/v1\",\"editorialEvents\":[],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"nature-communications\",\"isNatureJournal\":true,\"hasQc\":false,\"allowDirectSubmit\":false,\"externalIdentity\":\"NCOMMS\",\"sideBox\":\"Learn more about [Nature Communications](http://www.nature.com/ncomms/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://mts-ncomms.nature.com/\",\"title\":\"Nature Communications\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"ejp\",\"reportingPortfolio\":\"Nature Communications\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false}}],\"origin\":\"\",\"ownerIdentity\":\"162678d4-5a0e-4366-a61c-9f6a9549a0ae\",\"owner\":[],\"postedDate\":\"December 3rd, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"under-review\",\"subjectAreas\":[{\"id\":58961108,\"name\":\"Health sciences/Diseases/Eye diseases\"},{\"id\":58961109,\"name\":\"Biological sciences/Cell biology/Mechanisms of disease\"}],\"tags\":[],\"updatedAt\":\"2026-03-30T07:05:39+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-12-03 11:58:29\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-8165516\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-8165516\",\"identity\":\"rs-8165516\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}