High-Fidelity Lipidomics Co-Clustering Analysis Reveals Critical Lipid Metabolic Crux and Mechanisms in Meibomian Gland Dysfunction (MGD)

High-Fidelity Lipidomics Co-Clustering Analysis Reveals Critical Lipid Metabolic Crux and Mechanisms in Meibomian Gland Dysfunction (MGD) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article High-Fidelity Lipidomics Co-Clustering Analysis Reveals Critical Lipid Metabolic Crux and Mechanisms in Meibomian Gland Dysfunction (MGD) Jingyun Zhu, Liu Liu, Kaixian Ren, Peiyan Zhu, Lang Bai, Minting Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9303325/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Background Meibomian gland dysfunction (MGD) is the leading cause of evaporative dry eye and is characterized by gland obstruction, lipid imbalance, and tear film instability. While inflammatory mechanisms have been extensively studied, the molecular composition of meibum and its regulatory networks remain incompletely understood. Methods High-fidelity lipidomic profiling of meibum from MGD patients (n = 4) and healthy controls (n = 4) was performed using Q-TOF UPLC-MS with four-dimensional identification. Transcriptomic data from normal (n = 6) and MGD-affected (n = 6) meibomian glands were analyzed using GO, KEGG, and protein–protein interaction network analyses. Integrated lipid–enzyme–gene co-clustering was applied to construct regulatory networks. Results MGD samples showed enrichment of long-chain and neutral lipids, particularly cholesteryl esters, whereas controls displayed higher levels of short-chain ceramides and fatty acids. Dysregulated lipid species were enriched in structurally modified sphingolipids. Transcriptomic analysis revealed involvement of PI3K-Akt, MAPK, cytokine signaling, and extracellular matrix remodeling, together with altered transcriptional regulation and membrane transport. Conclusions Excess long-chain neutral lipids increase tear film viscosity and promote ductal obstruction, while short-chain and modified lipids support tear film stability. Coordinated disruption of lipid metabolism, cytoskeletal dynamics, and cellular homeostasis drives progressive gland dysfunction and chronic ocular surface damage in MGD. meibum meibomian gland dysfunction (MGD) high-fidelity lipidomics lipid layer pattern cluster analysis Protein-Protein Interaction (PPI) Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction The global prevalence of dry eye has risen steadily, reaching 11.59% by 2021 1 , making it a significant public health concern. Traditionally, dry eye is classified into aqueous-deficient and evaporative subtypes 2 , with further refinements based on tear film composition, including aqueous and mucin deficiency types. Tear film instability, hyperosmolarity, ocular surface microenvironmental dysregulation, and neurosensory dysfunction are central to its pathogenesis. Meibomian gland dysfunction (MGD), the leading cause of evaporative dry eye 3 , presents clinically with conjunctival congestion, eyelid margin swelling, and ductal obstruction, often accompanied by viscous, toothpaste-like secretions. As specialized sebaceous glands, meibomian glands secrete meibum, which form the tear film’s outermost layer, reducing evaporation and preserving ocular surface homeostasis 4 , 5 . A marked decline in lipid secretion from obstructed glands disrupts tear film integrity, driving disease progression 6 . The mechanism of dry eye based on impaired function of meibomian gland in lipid secretion is illustrated as follows (Fig. 1 ). Given its crucial lipid-secreting role, research on meibomian gland tissue and meibum components has gained traction 7 – 9 . Lipidomics enables the identification and characterization of lipid metabolites by integrating mass spectrometry and chromatography, leveraging advancements in soft ionization techniques such as electrospray ionization and matrix-assisted laser desorption/ionization 10 . Meibum, a specialized lipid secretion, exhibits a complex composition predominantly consisting of nonpolar lipids, including wax esters (WE), cholesteryl esters (CE), and triglycerides (TG), alongside polar lipids such as ceramides (Cer), sphingomyelin, and phospholipids.Existing lipidomic analyses of meibum have identified significant differences between MGD and normal lid lipids, particularly in free fatty acids, cholesteryl esters, and ceramides 11 , 12 . However, most studies remain limited to the identification of a few hundred lipid species and provide only statistical descriptions of a small subset of differentially expressed lipids. Conventional lipidomic assays often struggle with inefficient ionization and poor chromatographic retention of certain metabolites, hindering their detection by mass spectrometry 13 . Furthermore, precise metabolite identification necessitates isotopic internal standards, which are both costly and not universally applicable 14 . Additionally, the accurate interpretation of high-sensitivity ionic signals is highly dependent on instrument performance and methodological precision. Challenges such as small sample sizes, compositional complexity, and technical limitations have hindered comprehensive lipidomic profiling. To overcome these barriers, we employed high-performance lipidomics coupled with isotope labeling, enabling the quantitative detection of nearly 10,000 lipid species from minimal sample volumes. Additionally, we integrated GEO transcriptomic data to perform differential gene expression and clustering analyses, constructing gene expression and protein interaction networks. This approach aims to refine MGD pathogenesis, elucidate key signaling pathways, and bridge mechanistic insights with metabolic phenotypes, ultimately advancing our understanding of disease progression. The meibomian glands, arranged in parallel along the long axis of the upper and lower tarsal plates, consist of approximately 25–40 glands per eyelid. Each gland comprises 10–15 acini surrounding a central duct that opens at the posterior lid margin. Meibum is secreted onto the palpebral conjunctiva and spreads across the ocular surface with each blink, forming the tear film’s outermost lipid layer. These glands operate via a holocrine secretion mechanism, where basal cells proliferate, differentiate, and migrate toward the central duct, accumulating lipids. Upon reaching the duct, the cells undergo disintegration, releasing their lipid contents onto the ocular surface. This process yields a complex lipid mixture essential for tear film stability and ocular surface lubrication. Pathological conditions—such as ductal obstruction and inflammation—disrupt glandular function, leading to meibomian gland dysfunction (MGD), reduced lipid secretion, and the development of evaporative dry eye. Common clinical manifestations of MGD include conjunctival hyperemia, orifice obstruction with inspissated secretions, and gland dropout or distortion. 2. Materials and Methods 2.1. Isotope Dual-Labeling High-Fidelity Lipidomics for Human Meibum In this study, human meibum samples were collected for dual-isotope labeling and high-fidelity lipidomic analysis. Chemical derivatization was applied to lipid metabolites to introduce hydrophobic groups and a tertiary amine structure, significantly enhancing column retention and ionization efficiency. Coupled with Agilent high-resolution mass spectrometry (HRMS), this approach improved detection sensitivity, ionization efficiency, and MS capture rate, thereby enhancing metabolite detection. The dual-isotope labeling method enabled precise quantitative analysis of lipid components, and a specialized three-tier metabolite identification database was established for reliable metabolite identification. 2.1.1. Sample and Study Design A total of 8 participants (16 eyes, 32 meibum samples) were included in the lipidomics study, with a mean age of 30.38 ± 6.90 years (75% female). All participants were recruited from the Southern Hospital Eye Clinic, and written informed consent was obtained. The study adhered to the Declaration of Helsinki 15 and was approved by the Bioethics Committee of Nanfang Hospital (approval number: NFEC-2020-089). The MGD group must meet the diagnostic criteria outlined in the Chinese Expert Consensus on meibomian gland (2023 Definition and Classification), including abnormalities in the levator palpebral gland openings (e.g., blockage, stenosis, displacement, atresia, or congenital absence) or abnormal secretion of the levator glands (e.g., impaired discharge). Additionally, abnormal meibomian gland secretion, including irregular drainage and/or secretion characteristics, is required for diagnosis 16 . Ocular dryness and foreign body sensation, along with slit-lamp evidence of punctate epithelial erosions, decreased tear meniscus height, and abnormal Schirmer test results, also constitute key diagnostic indicators. Exclusion criteria include: recent ocular medication use or corneal contact lens wear within the past week; active ocular infections or inflammation unrelated to MGD; history of ocular burns or surgery; systemic diseases associated with MGD (such as dry eye syndrome, Stevens-Johnson syndrome, hyperthyroidism, pemphigus, or cerebral nerve injury); pregnant or lactating women. 2.1.2. Meibum Sample Collection The operators were experienced healthcare professionals with specialized ophthalmology training. Meibum samples were collected with the subjects seated in front of a slit lamp, their chin resting on a stand. The subjects were instructed to relax their eyelids while gazing at the floor or ceiling during the collection from the upper and lower eyelids. For 30 seconds, the operator gently pressed the upper and lower eyelids with the thumb to facilitate meibum drainage through the meibomian ducts to the ocular margins. Then the meibum samples were then carefully collected from the lid margin using a sterilized stainless steel spatula 9 , 12 . The samples were immediately placed in aseptic enzyme-free EP tubes and frozen at -80℃ within 1 hour for further analysis. 2.1.3. Sample pre-processing Metabolite samples were prepared following standard operating procedures (SOPs) based on the modified Folch liquid-liquid extraction method 17 – 19 . Each sample was homogenized with a lipid tissue internal standard mixture (15 deuterated lipids), methanol, and ceramic beads using a bead mill, followed by the addition of dichloromethane and water for separate homogenization. After 10 minutes of equilibration at room temperature, samples were centrifuged at 15,000 g for 10 minutes at 4℃. The organic layers were then transferred into centrifuge tubes and dried under nitrogen. Solvents A/B, consisting of ultrapure deionized water, chromatographic-grade methanol, propanol, acetonitrile, and ammonium formate (specific ratios are detailed in the next liquid chromatography-mass spectrometry analysis procedure), were prepared. The residue was re-solubilized in mobile phase B (MPB), vortexed for 1 minute, and diluted with mobile phase A (MPA). An extract pool for quality control (QC) was prepared by dividing the mixture into aliquots, drying with nitrogen, and storing at -80℃. Samples were randomly grouped into sets of 9, with one pool sample reconstituted and diluted as QC for the batch. 2.1.4. Liquid Chromatography–Mass Spectrometry Analysis All samples were analyzed in both positive and negative ion modes, with LC-MS and LC-MS/MS data acquired for each mode. Quality control (QC) data for each group of nine samples were collected before and after analysis, with additional QCs performed before and after all sample injections to ensure technical stability. Reversed-phase liquid chromatography separation and mass spectrometry analysis were conducted using an Agilent 1290 LC system coupled with an Agilent 6546 Q-TOF Mass Spectrometer, employing a Waters Acquity CSH C18 column (1.7 µm). The on-column injection volumes were 5 µL for positive ions and 12 µL for negative ions. The column temperature was maintained at 40°C, while the autosampler was kept at 8°C to prevent sample evaporation. The samples were eluted using a 26-minute gradient at a flow rate of 210–250 µL/min, with MPA (methanol/acetonitrile/water containing 10 mM ammonium formate, 50:40:10) and MPB (2-propanol/water containing 10 mM ammonium formate, 95:5). Mass spectrometry was performed in electrospray ionization (ESI) mode, with precursor ions fragmented in the m/z range of 150–1500 and MS/MS collision energies set at 10–60 eV. Data were processed and exported using MassHunter software. 2.1.5. Lipid Annotation Lipid characteristic peaks were extracted and aligned using LipidScreener 1.1.0. Data from both positive and negative ions were combined, creating a unified feature intensity table for all samples. Feature peaks absent in more than 80% of samples were filtered out. Missing values in samples detected in at least 75%, 50%, or fewer than 50% of cases were replaced with the median intensity, minimum intensity, or the overall minimum value, respectively, for all samples and QC. Lipid identification was performed using a three-tier approach based on MS/MS spectral similarity, retention time, and exact mass matching 20 . LipidScreener 1.1.0 employs nine levels of filtering and scoring to calculate MS/MS match scores, limit matches, and select the best identifications. Tier I and II identifications are conducted at the species or molecular type level, including lipid class and subclass definitions, fatty acyl/alkyl residue composition, and functional groups. Tier III identifications are made at the species level, considering lipid classes, carbon atoms, double bond equivalents, and additional atoms such as oxygen. All identified compounds from the three tiers were combined, normalized, and statistically analyzed. 2.1.6. Lipidomics Statistical Analysis A set of 15 deuterated internal standards (LipidRep Internal Standard Basic Mix for Tissue/Cells) representing various lipid classes was used to normalize the data for identified characteristic peaks. Lipids were matched to one of the 15 internal standards based on lipid class similarity and expected retention time ranges. Intensity ratios were calculated, and internal standard normalization was performed by dividing the intensity of each lipid by the intensity of its corresponding internal standard. Table S1 . presents the peak intensity ratios for identified compounds, normalized by both internal standard and median. Non-informative features (e.g., internal standards, common contaminants, and low-reproducibility features) were filtered out. The data were then uploaded to LipidScreener 1.1.0, where additional filtering of near-constant features (the 30% with the smallest relative standard deviation across all samples) and auto-scaling were performed. 2.2. Pathway and functional enrichment analysis Complete open-source GEO data on gene expression differences between normal and MGD-associated blepharoplasty samples (GSE17822) were obtained from the NCBI database, including expression matrices and sample information files 21 . The raw data underwent cleaning and normalization, followed by selective logarithmic transformation based on expression differences, with a logFC value set to 1 and a corrected P-value threshold of 0.05 to identify significant differential genes. Gene ontology (GO) and KEGG analyses were then conducted on the differential genes 22 , 23 , and Fisher's exact test was used to detect significant enrichment in cellular processes and regulatory pathways. 2.3. Protein-Protein Interaction (PPI) analysis Target protein interactions were retrieved from the STRING database and imported into Cytoscape for visualization. Network topology analysis, including node degree and clustering coefficients, was performed using the CytoHubba plug-in to identify key proteins or hub genes 24 , 25 . The network layout was then adjusted to produce an intuitive protein interaction graph. Functional sub-networks were further delineated using module detection algorithms (e.g., MCODE), and biological significance was assessed through GO and KEGG pathway annotation. 3. Results 3.1. Landscape of human meibums was constructed using dual-isotope labeled high-fidelity lipidomics A total of 18 samples (8 experimental and 10 QC) were collected for liquid chromatography analysis, with both positive and negative ion data combined. Only characteristic peaks detected in at least 80% of the samples in a group were retained for identification and normalization, while less reproducible peaks were filtered out to ensure data quality. After filtering, an average of 8939 ± 233 feature peaks were detected per sample. The number of detected peaks per sample is summarized in Table 1 , with Table S1 . listing identified and normalized feature peaks, and Table S2 . summarizing unidentified peaks. Lipid identification was performed using LipidScreener 1.1.0, applying a three-tiered identification approach with nine filtering and scoring levels, including retention time filters based on lipid class and fatty acyl group. This methodology allowed for precise matching of characteristic peaks to the most appropriate lipid type. The high-fidelity lipidomics approach used in this study, with a 40 µL very small meibum sample size, extended lipid identification to 10,000 feature peaks, ensuring comprehensive and sensitive lipid identification and constructing the landscape of MGD-associated meibum. The overall distribution of meibum lipid components in both groups reveals a complex composition of human blepharoplastin, as detailed in Table 2 . The primary dominant components are wax esters (WE) and cholesteryl esters (CAR), while secondary dominant components include sphingolipids (Sphingolipids, NAE), hydroxy fatty acids (HC), and N-acylethanolamines (NAE). These lipid classes collectively form a complex metabolic network, where the dynamic balance is essential for maintaining ocular surface health.​​​​ Table 1 Number of features detected per sample Sample Name Group Number of feature peaks M 1 MGD 9255 M 2 MGD 8853 M 3 MGD 9163 M 4 MGD 8951 N 1 Normal 9302 N 2 Normal 9510 N 4 Normal 9176 N 5 Normal 8866 QC 01 QC 8686 QC 02 QC 8735 QC 03 QC 8732 QC 04 QC 8876 QC 05 QC 8848 QC 06 QC 8676 QC 07 QC 8901 QC 08 QC 8825 QC 1_1 QC 8703 QC 1_2 QC 8846 Abbreviations: Meibomian gland dysfunction (MGD), Quality control (QC) Table 2 A meibum panorama depicted by high-fidelity lipidomics based on MGD and Normal biclass samples Genre Type Structure Detection Example Function Simple Lipids Wax Esters, WE Esters formed from long-chain fatty acids + long-chain fatty alcohols WE 20:3 (Feature 191) WE 22:2 (Feature 781) The core ingredient of the tear film hydrophobic layer prevents evaporation of tears. Cholesteryl Esters, CE Cholesterol + fatty acid esterification CE 15:0;O3 (Feature 73) CE 17:0 (Feature 74) Regulation of tear film fluidity and oxidative CE (e.g., O3 modification) suggest oxidative stress. Glycerolipids Triacylglycerols, TG Glycerol + 3 fatty acids TG detection is limited in negative ion mode. Monoacylglycerols, MG Glycerol + 1 fatty acid. MG 28:0 (Feature 2702) Present in trace amounts, possibly lipid metabolism intermediates. Phospholipids Glycerophos-pholipids Lysophospha- tidylcholine, LPC Glycerol + 1 fatty acid. Glycerol + 1 fatty acid + choline phosphate LPC 18:0 (Feature 461) Pro-inflammatory mediator. Phospha- tidylinositol, PI Phospholipids + Inositol PI-Cer 41:4;O4 (Feature 1595) Pro-inflammatory mediator signaling, possibly involved in apoptosis regulation. Sphingomyelins, SPB Sphingosine base + fatty acid + choline phosphate. 19:0;O3 (Feature 619) SPB 18:0;O2 (Feature 1241) Pro-inflammatory mediator signaling, which may be involved in apoptosis regulating cell membrane components, accumulates abnormally in MGD or leads to catheter obstruction. Sphingolipids Ceramides, Cer Sphingomyelin base + fatty acid Cer 33:2;O (Feature 2172) A key component of the epithelial barrier, oxidized Cer (e.g., O modification) is associated with abnormal MGD keratinization. Hexosylceramides, HexCer Ceramide + Hexose HexCer 29:1;O6 (Feature 2138) Involved in cellular recognition with very low abundance. Sulfatides, ST Galactosylceramide + Sulfated ST 25:4;O3;T (Feature 912) Antimicrobial effects that may influence MGD by modulating the ocular surface microbiota Glycolipids Glycero- glycolipids Monogalactosyldiglyce-rides, MGDG Glycerol backbone + fatty acid chain + galactose moiety Sugar-modified LPS 15:0 (Feature 1665) Stronger polarity, able to interact with water molecules, maintain the stability and function of the vesicle-like membrane, photoprotective function against oxidative damage Complex glyco- sphingolipids MyoInositol Phosphate Ceramide, MIPC Ceramide + Inositol Phosphate MIPC 31:4;O6 (Feature 2918) Signaling molecules, which are extremely low in abundance but may be involved in inflammatory regulation. Derived Lipids Free Fatty Acids, FFA Unesterified fatty acid chains FA 16:1 (Feature 1100) Short-chain FA maintains tear film fluidity, and long-chain oxidized FA (e.g., FA 22:5;O6) is involved in MGD inflammation. Fatty Alcohols, FOH Long-chain primary alcohols FOH 20:3 (Feature 483) WE synthesized precursors, and some FOH abundance was decreased in the MGD group. N-Acylethanolamines, NAE Fatty acids + Ethanolamines NAE 20:2 (Feature 768) Endogenous cannabinoid analogs, pro-inflammatory NAE (e.g., 20:2) were upregulated in the MGD group. N-Acyltaurines, NAT Fatty acids + taurine NAT 27:5 (Feature 972) Bile acid metabolism-associated molecules. Oxidized Lipids Hydroxylated lipids Hydroxyl-containing (-OH) modifications Car 15:0;O3 (Feature 73) Oxidative stress markers, generally elevated in the MGD group Epoxidized/Peroxidized Lipids Epoxy group + unsaturated fatty acid chain FA 22:5;O6 (Feature 2038) NAE 20:2;O2 (Feature 768) Pro-inflammatory mediators that may exacerbate blepharoplasty injury via the LOX/COX pathway. Other special lipids Lyso-phospholipids Monoacylglycerophospholipids LPC 18:0 (Feature 461) Pro-inflammatory effects, elevated concentrations in tears of MGD patients Ether Lipids Alkyl or alkenyl ether bond LPC O-16:0 (Feature 1092) Membrane structure is stable and low in abundance, but enhances tear film toughness. 3.2. Significant expression differences between MGD and normal meibum samples Quality control (QC) checks were performed using LipidScreener 1.1.0, where non-informative features (e.g., internal standards, common contaminants, and peaks with low reproducibility) were filtered out. Additionally, features with near-constant values across groups (the 30% with the smallest relative standard deviation) were excluded and the data were auto-scaled. The two-dimensional (2D) and three-dimensional (3D) principal component analysis (PCA) score plots, with QC samples indicated in green (Fig. 2 . a-f), demonstrate the method's good reproducibility. Volcano plots (Fig. 2 . i) were generated using fold change (FC) and p-value, calculated by comparing the means of groups M and N (Normal) (Table S3 ). p-values were derived from a t-test, while q-values were FDR-adjusted (Storey’s q-value). Using FC > 1.4 or < 0.71, p < 0.05, and q 1.4 and p < 0.05 (red), and 294 lipids had FC < 0.71 and p < 0.05 (blue). P-value thresholds of 0.05 corresponded to q-values ≤ 0.25. VIP values from PCA were calculated, and the top 20 VIP and top 100 p-value lipids were plotted in a heatmap (Fig. 2 . j-k). This showed significant clustering of up- and down-regulated lipids, indicating a marked difference in lipid expression profiles between groups M and N. Among the lipid clusters (Fig. 2 . g-h), sphingolipids dominated (41.1%), followed by fatty acyls (20.6%) and sterols (15.1%), suggesting their coregulatory roles. Glycerophospholipids and glycerolipids, key components of cell membranes, also showed notable changes, though their relatively smaller variation contrasted with the significant fluctuations in sphingolipids. This may reflect selective regulation of membrane stability and lipid metabolism, with abnormal distribution pointing to imbalances in energy storage and structural lipid metabolism. (a, d) PCA 2D and 3D score plots of meibum from MGD and Normal (M/N) groups without quality control (QC); (b, e) PCA 2D and 3D score plots of M/N group meibum with QC; (c, f) Partial Least Squares Discriminant Analysis (PLS-DA) 2D and 3D score plots; (g) Distribution of significantly altered lipid classes when FC > 1.40 or < 0.71, and p-value 1.4 or < 0.71, with p 1.4 and p < 0.05 (red) and 294 lipids with FC < 0.71 and p < 0.05 (blue); (j) Heatmap of the top 20 significant lipids by VIP score from PLS-DA analysis; (k) Heatmap of differential lipid expression for the top 100 lipids ranked by p-value. 3.3. Normal meibum exhibits shorter chains and more modified functional groups compared to MGD Lipidomics analysis revealed significant differences in meibum composition between normal subjects and MGD patients (Fig. 2 . k, Table S3 ). While the α-diversity (number of lipid species identified) was similar in both groups, the β-diversity of meibum was significantly lower in the MGD group, indicating a homogenization of lipid expression (Fig. 2 . j). This suggests that meibum dedifferentiation may contribute to MGD development. Differential lipid expression showed that MGD meibum was enriched with a higher proportion of neutral lipids (CE, WE, long-chain Cer) and medium- to long-chain lipids (saturated fatty acids), whereas normal meibum contained more short-chain lipids (short-chain Cer, polyunsaturated fatty acids) and complex modifications (hydroxylation, glycosylation). Overall, normal meibum maintains high water solubility, protein interactions, and biofilm affinity, whereas MGD meibum exhibits increased melting point and hydrophobicity (Table 3 ), leading to reduced lipid mobility and the formation of lipid plugs that obstruct meibomian gland openings, consistent with the pathological progression of MGD. Table 3 Differences and Identities of dominantly expressed components between MDG and Normal meibums Categories MGD Group Normal Group Key Differences Cholesteryl ester (CE) High ratios (CE30:2, CE33:2, CE27:2, etc.) low content MGD Group is dominated by neutral lipids (cholesterol esters), Normal Group has less CE lipids Ceramide (Cer) Regular ceramides (Cer50:2, Cer38:2, Cer45:0, etc.) Short chain/modified ceramides (Cer9:0, Cer30:1, Cer54:0, etc.) Normal Group contains more short-chain ceramides and complex modifications Fatty acids (FA) Common fatty acids (FA32:1, FA30:1, etc.) FAHFA (Branched fatty acid esters of hydroxy fatty acids), Short-faced FA Normal Group contains hydroxylated modifications (FAHFA) and shorter-chain fatty acids Glycolipid low content MGDG (Monogalactosyldiacylglycerol)、HexCer (Hexosylceramide)、 Hex2Cer (Dihexosylceramide)、 ST(Sulfoquinovosyl diacylglycerol) Normal Group contains large amounts of glycosylated lipids (e.g., MGDG, HexCer), MGD Group has very low content. Sphingolipid derivatives Conventional sphingolipids (Cer, CerP) SPB (sphingomyelin analog), PE-Cer (phospholipid-ceramide conjugate) Normal Group contains bound sphingolipids (PE-Cer) and possibly new types of sphingolipids. glycol ester DG (diglycerides), MG (monoglycerides) DG (diglycerides), MG (monoglycerides) Glycerol esters are present in both groups, but Normal Group contains more short-chained meibums. Other lipids Wax esters (WE), carnitine (Car), NAE (N-acyl ethanolamine) Car (carnitine), LPS (lipopolysaccharide analog), PR (possibly oxidized phospholipids) Normal Group contains more specifically modified lipids, while MGD Group has neutral lipids. Identities Hydrophobicity High (CE, WE, long chain Cer) Low (glycosylation, hydroxylation increase polarity) The sugar and hydroxyl groups of Normal Group make the lipids more soluble in water. Melting Point Higher (high percentage of long-chain saturated fatty acids) Lower (high percentage of short-chain, polyunsaturated fatty acids) The short chains and multiple double bonds of Normal Group reduce intermolecular forces. Ionization Efficiency Prone to ionization in positive ion mode (e.g. CE, Cer) Better in negative ion mode (e.g., glycolipids, FAHFA) Acidic groups of Normal Group (phosphate, sulfate, hydroxyl) deprotonate more readily in negative ion mode. Chromatographic Retention Long retention time in reversed-phase chromatography (highly hydrophobic) Short retention time or need for hydrophilic chromatography (e.g., HILIC) The polar head group of Normal Group reduces reversed-phase chromatographic retention. Biofilm Affinity Predominantly found in lipid droplets or in membrane hydrophobic regionss Tendency to be on the surface of membranes or in lipid rafts (e.g., glycolipids, sphingolipids) The polar head group of Normal Group interacts more strongly with membrane proteins. 3.4. CO-clustering Analysis: Alterations in lipid differentiation, cellular environment, and inflammatory processes contribute to MGD Comparison of gene expression between normal and MGD-associated glabellar glands based on open GO data revealed significant differences in gene expression and functional pathways in MGD (meibomian gland dysfunction) compared to normal samples. Clustering heatmap analysis of the top 100 p-value genes demonstrated significant up- and down-regulation of gene expression between MGD and normal groups (Fig. 3 .a). The volcano plot further confirmed extensive differential gene distribution, suggesting a multidimensional molecular regulatory imbalance in MGD (Fig. 3 .b). GO enrichment analysis of differential genes showed significant enrichment in biological processes such as gland development, axonogenesis, and eye maturation, with close associations to cellular components like intercellular junctions, extracellular matrix, and gland secretion, and molecular functions such as transcriptional receptor activity and ion transport (Fig. 3 .c). These findings suggest that MGD may disrupt signaling networks involved in gland differentiation, metabolism, and development. KEGG pathway analysis identified enrichment in neuroactive ligand-receptor interactions, adhesion patches, and mucocytoskeleton pathways, indicating the involvement of intercellular communication, adhesion migration, and glandular dysfunction as key mechanisms in MGD. Disruption of RNA polymerase II-related pathways supports transcriptional dysregulation, while the MAPK/PI3K-Akt metabolic-inflammation pathway highlights inflammation and cell death throughout MGD progression. Enrichment of pathways related to atherosclerosis and lipid metabolism disorders correlates with meibum expression abnormalities (Fig. 3 .d). In conclusion, MGD's molecular features likely involve extracellular matrix abnormalities, mitochondrial dysfunction, lipid metabolism disruptions, immune dysregulation, and neural signaling impairments, suggesting the need for further functional validation and pathway exploration of key genes. (a) Heatmap of the top 100 differentially expressed genes between MGD and normal meibomian gland tissues based on p-value. (b) Volcano plot of differentially expressed genes selected with FC > 1.4 or < 0.71, p < 0.05, where red indicates upregulation and green indicates downregulation. (c) GO enrichment analysis of the top 10 differentially expressed genes (circle size represents the number of associated differential genes, color intensity indicates p-value). (d) KEGG enrichment analysis of the top 10 differentially expressed genes (circle size represents the number of associated differential genes, color intensity indicates p-value). Protein-Protein Interaction (PPI) network analysis, using STRING, further elucidated the pathogenesis of MGD by calculating the basic topological attributes of differential genes, adjusting for node centrality and network properties. MCODE (Cytoscape plugin) was employed to identify tightly connected sub-networks based on node density. The top 10% of genes were selected using comprehensive topological metrics (Degree, Betweenness, Closeness), and core driver genes were identified by combining differential expression levels (e.g., log2FC) with their topological importance within the module. Functional module annotation was then performed using the R studio clusterProfiler package, constructing the MGD-related molecular action network (Fig. 4 , Table 4 ). PPI analysis identified 10 key molecular patterns closely associated with lipid metabolism, glandular duct function, vesicular transport, and inflammatory damage pathways. Detailed analysis in the subsequent pathway identification section not only complements the lipidomics findings but also provides insights into the pathogenesis and potential targets related to MGD. (a) Functionally annotated protein–protein interaction (PPI) network, with nodes colored according to associated biological processes or pathways. (b) Interaction strength network generated via MCODE clustering, where node color intensity reflects intra-module connectivity (darker nodes indicate higher clustering scores; lighter nodes represent peripheral or lower-scoring nodes). (c) Clustered PPI network delineating ten distinct modules (MCODE1–MCODE10), each colored based on functional annotation. (d) Integrated visualization of the full-scale PPI network, combining modular clustering and functional annotation. [Layer 1: MCODE-defined module color blocks. Layer 2: High-confidence intra-module interactions (bold edges) and lower-confidence inter-module interactions (thin edges). Layer 3: Cross-module intersections highlighting key pathological pathways.] Table 4 Functional module annotation based on PPI analysis of MGD differentially expressed genes MCODE GO Description Log10(P) MCODE_1 R-HSA-9841922 MLL4 and MLL3 complexes regulate expression of PPARG target genes in adipogenesis and hepatic steatosis -8.2 MCODE_1 R-HSA-9851695 Epigenetic regulation of adipogenesis genes by MLL3 and MLL4 complexes -8.2 MCODE_1 R-HSA-9818564 Epigenetic regulation of gene expression by MLL3 and MLL4 complexes -8.2 MCODE_2 M40 PID E2F pathway -5.3 MCODE_2 R-HSA-453279 Mitotic G1 phase and G1/S transition -4.7 MCODE_2 GO:0031647 regulation of protein stability -4.6 MCODE_3 R-HSA-6809371 Formation of the cornified envelope -17.6 MCODE_3 R-HSA-6805567 Keratinization -15.7 MCODE_3 GO:0030216 keratinocyte differentiation -11.7 MCODE_5 GO:0000398 mRNA splicing, via spliceosome -10.2 MCODE_5 GO:0000377 RNA splicing, via transesterification reactions with bulged adenosine as nucleophile -10.2 MCODE_5 GO:0000375 RNA splicing, via transesterification reactions -10.2 MCODE_6 CORUM:1142 SMN complex -9.7 MCODE_6 CORUM:1745 SMN complex -9 MCODE_6 CORUM:1143 SMN complex -9 MCODE_7 R-HSA-1839122 Signaling by activated point mutants of FGFR1 -10 MCODE_7 R-HSA-190375 FGFR2c ligand binding and activation -9.7 MCODE_7 R-HSA-190373 FGFR1c ligand binding and activation -9.7 MCODE_9 hsa04130 SNARE interactions in vesicular transport -8.9 MCODE_9 GO:0061025 membrane fusion -6.8 MCODE_9 GO:0061024 membrane organization -4.8 MCODE_10 R-HSA-390522 Striated Muscle Contraction -9 MCODE_10 R-HSA-397014 Muscle contraction -6.7 MCODE_10 hsa04820 Cytoskeleton in muscle cells -6.4 3.5. Identification of regulatory pathways involved in MGD 3.5.1. Lipid metabolism-related pathways Lipidomics studies reveal significant differences in meibum composition between MGD patients and normal subjects. MGD meibum is enriched in neutral lipids, such as cholesteryl esters, wax lipids, and long-chain fatty acids, which are hydrophobic, have higher melting points, and are prone to forming lipid plugs. In contrast, normal meibum predominantly contains short-chain, multi-modified lipids that exhibit better water solubility, enhanced mobility, and stronger interactions with biofilms, thereby maintaining ocular surface homeostasis. These findings suggest that abnormal lipid metabolism plays a key role in MGD pathogenesis. GO and KEGG clustering analyses indicated that MGD affects lipid elongation by promoting the expression of EC 3.1.2.2 (palmitoyl-CoA hydrolase), which facilitates the formation of hypercoagulable lipids. EC 3.1.2.2 hydrolyzes substrates required for lipid elongation, limiting subsequent elongation reactions. The Coenzyme A (CoASH) released by EC 3.1.2.2 supports β-oxidation and the tricarboxylic acid cycle, maintaining cellular energy homeostasis. During tissue dysfunction and energy stress, CoASH may preferentially support fatty acid catabolism (β-oxidation) over elongation, shifting metabolism to balance the CoASH pool. However, excess acyl-CoA is lipotoxic, and EC 3.1.2.2 helps prevent lipotoxic damage by hydrolyzing acyl-CoA, thus maintaining lipid elongation enzyme system function 26 , 27 . Additionally, PPI analysis identified MCODE_1, suggesting that the MLL3/MLL4 complex regulates PPARG (Peroxisome proliferator-activated receptor Gamma) target genes, mediating epigenetic control of lipid metabolism (Fig. 4 , Table 4 ). MLL3/MLL4, as histone H3K4 methyltransferases, regulate adipogenesis through epigenetic mechanisms. This is associated with sphingolipid metabolism disorders observed in pre-lipidomics studies, indicating that dysregulation of PPARG may contribute to abnormal lipid synthesis in MGD. 3.5.2. Glandular duct function-related pathways During the progression of MGD, differences in meibum composition and reduced quality compared to the normal state contribute to tear film dysfunction, a key manifestation of the disease. Functionally, the glandular state influences meibum production and secretion, which warrants further investigation. Combined protein pathway analysis revealed that glandular ductal keratinization, dysregulated gland regeneration, impaired membrane fusion, and abnormal myogenic glandular motility are strongly associated with MGD pathogenesis (Fig. 3 , Table 4 ). MCODE_3 identified excessive keratinization of the meibomian gland ductal epithelium as the central mechanism of ductal obstruction in MGD. The keratinization module, enriched in keratins (e.g., KRT1, KRT10) and genes related to keratin envelope formation 2830 (e.g., FLG, IVL), suggests that the IL-22/STAT3 pathway may promote abnormal keratinization by upregulating keratin expression 31 . MCODE_7 highlighted the role of FGFR signaling, activated by FGFR1c/2c ligands, in the core pathway of glandular regenerative dysregulation in MGD. FGFR signaling, through MAPK and PI3K-Akt pathways, regulates cell proliferation and differentiation 32 , 33 , and its aberrant activation may lead to blepharoplakic follicle structure disruption (atrophy or overgrowth), which is associated with pathological MGD subtypes. The balance between FGF2 (pro-regenerative) and FGF23 (pro-fibrotic) likely determines the direction of gland repair 34 , 35 . MCODE_9 emphasized the central role of membrane fusion and secretion dysfunction. SNARE-mediated fusion, enriched with vesicular transport proteins 36 , 37 (e.g., VAMP8, SNAP25), may be impaired, leading to dysfunction in meibum lipid granule release. The heatmap-identified Signal Peptidase Complex Subunit 1 (SPCS1) deficiency coincied the diminished lipid secretion, as it facilitates protein maturation through signal peptide cleavage—a prerequisite for vesicular trafficking 38 , 39 . Its functional impairment disrupts secretory processes via compromised vesicle biogenesis and defective lipid-transporter processing. Dysregulated vesicular transport by Rab GTPases may represent a potential therapeutic target 40 , 41 . Additionally, MCODE_10 enriched pathways associated with impaired muscle contraction and glandular emptying. These include the contractile cytoskeleton of the rhabdomyosarcoma muscle, enriched in contraction-associated proteins of the blepharosphenoid myoepithelium 42 , 43 (e.g., MYH2, ACTA1). Dysfunction of these proteins may reduce lipid efflux, leading to lipid accumulation in gland ducts and contributing to glandular obstruction. 3.5.3. Inflammatory-oxidative damage-related pathways From a pathological perspective, inflammation and oxidative stress represent critical mechanisms in MGD, with diverse forms of glandular injury converging to initiate localized inflammatory responses and apoptosis, ultimately leading to tissue dysfunction. The ocular surface, due to its direct exposure to environmental pathogens and harmful agents, is particularly susceptible to inflammatory stimuli. Concurrently, direct air contact and the lipid-rich nature of the tear film promote oxidative processes, further exacerbated by inflammation-induced oxidative stress. PPI network analysis and differential gene expression profiling jointly identified aberrant interactions among core spliceosomal proteins (e.g., SNRNP70, SF3B1), suggesting that dysregulated alternative splicing may impair the production of stress-related isoforms, including members of the heat shock protein (HSP) family 44 – 46 . This splicing dysfunction may intensify oxidative damage in meibomian gland epithelial cells. Moreover, the observed downregulation of WFS1—a marker of endoplasmic reticulum stress—in the heatmap may reflect insufficient compensatory response within this module 47 , further contributing to glandular vulnerability. MCODE_1-identified PPAR signaling plays a multifaceted role in MGD pathogenesis by regulating lipid metabolism-related genes (e.g., MGST2), promoting ductal hyperkeratinization through SPRR2A overexpression (linked to MCODE_3) 48,49 , and impairing anti-inflammatory responses via diminished NF-κB inhibition, thereby sustaining inflammation through MAPK pathway crosstalk. Simultaneously, the PI3K-AKT pathway contributes to disease progression. Significant downregulation of DERL2 and upregulation of MGST2 (involved in glutathione metabolism) suppress cell survival 49 , 50 , reduce anti-apoptotic proteins (e.g., Bcl-2), and promote acinar gland cell apoptosis via the mitochondrial pathway. Decreased AKT-mediated phosphorylation of Nrf2 compromises the expression of antioxidant enzymes (e.g., SOD, CAT), exacerbating redox imbalance and promoting lipid peroxidation 51 , 52 , thereby disrupting meibum composition and vesicular transport (MCODE_9). In parallel, hypoxia and oxidative stress in MGD tissues activate the HIF-1 signaling axis 53 , 54 , with aberrant expression of its target gene VEGFA linked to the hypoxia-induced contractile dysfunction identified in MCODE_10. The hypoxic microenvironment aggravates ductal obstruction and hyperkeratinization (MCODE_3), while HIF-1α-driven VEGF upregulation promotes angiogenesis, potentially leading to abnormal vascular permeability. Furthermore, HIF-1 induces upregulation of GLUT1 and lactate dehydrogenase 55 , shifting glandular metabolism toward anaerobic glycolysis, which intensifies local acidosis and inflammatory damage. 4. Discussion This study elucidates the molecular underpinnings of MGD through integrated high-resolution lipidomics and transcriptomic clustering analyses, identifying key contributors to tear film instability and disease pathogenesis. Our findings demonstrate a distinct shift in meibum composition in MGD, characterized by an increase in long-chain neutral lipids (e.g., cholesteryl esters) and a concomitant depletion of short-chain ceramides and hydroxylated/glycosylated species. These compositional changes enhance the hydrophobicity and viscosity of meibum, promoting glandular obstruction and compromising tear film integrity. In contrast, the presence of short-chain and structurally modified lipids in healthy meibum facilitates solubility and protein interaction, preserving tear film homeostasis. Transcriptomic profiling further highlights lipid differentiation defects, ductal dysfunction, and oxidative-inflammatory stress as central drivers of MGD. Pathway enrichment analyses underscore dysregulation of PPARγ signaling and aberrant activation of PI3K-Akt, MAPK, and cytokine-mediated pathways, contributing to disrupted lipid metabolism, mitochondrial impairment, endoplasmic reticulum stress, and oxidative-inflammatory cascades. Epigenetic regulation by the MLL3/MLL4 complex and dysregulated fibroblast growth factor receptor (FGFR) signaling further emphasize the multifactorial nature of MGD progression. Additionally, pathways involved in keratinization (e.g., FLG, KRT1) and impaired SNARE-dependent vesicular transport (e.g., VAMP8, SNAP25) are closely associated with ductal occlusion and secretory failure. Collectively, these findings delineate a lipid–enzyme–gene regulatory network, offering a framework for precision-targeted interventions aimed at lipid metabolism, glandular regeneration, and oxidative-inflammatory crosstalk. Future research could focus on validating these therapeutic targets in preclinical models and exploring individualized strategies to restore meibum composition and gland function, thereby improving tear film stability and mitigating ocular surface damage. Abbreviations MGD Meibomian gland dysfunction PPARG (γ) Peroxisome proliferator-activated receptorγ PPI Protein-protein Interaction LC-MS Liquid Chromatography–Mass Spectrometry HRMS High-resolution mass spectrometry WE wax esters TG Triacylglycerols CE cholesteryl esters Cer Ceramides CAR Acylcarnitines NAE N-acylethanolamines HC hydroxy fatty acids MG Monoacylglycerol LPC Lysophosphatidylcholines PI Phosphatidylinositols PI-Cer Phosphatidylinositol ceramide SPB Sphingoid base HexCer Hexosylceramide ST Sulfatide MGDG Monogalactosyldiacylglycerol LPS Lipopolysaccharide MIPC Mannosylinositol phosphorylceramide FFA Free fatty acids FOH Fatty alcohols NAT N-acyltransferase LOX Lipoxygenase COX Cyclooxygenase MLL4/3 Mixed-lineage leukemia 4/3 PID Primary immunodeficiency E2F Transcription factor E2F FGFR Fibroblast growth factor receptor SNARE Soluble N-ethylmaleimide-sensitive factor attachment protein receptor KRT Keratin FLG Filaggrin IVL Involucrin IL-22 Interleukin-22 STAT3 Signal transducer and activator of transcription 3 MAPK Mitogen-activated protein kinase PI3K-AKT Phosphoinositide 3-kinase-AKT signaling pathway SPCS1 Signal peptidase complex subunit 1 SNRNP70 Small nuclear ribonucleoprotein U1 subunit 70 SF3B1 Splicing factor 3b subunit 1 WFS1 Wolfram syndrome 1 MGST2 Microsomal glutathione S-transferase 2 SPRR2A Small proline-rich protein 2A DERL2 Derlin 2 AKT Protein kinase B SOD Superoxide dismutase CAT Catalase HIF Hypoxia-inducible factor VEGFA Vascular endothelial growth factor A Declarations Ethics approval and consent to participate This study was conducted in accordance with the principles of the Declaration of Helsinki. Ethical approval was obtained from the Institutional Review Board (IRB) of Southern Medical University.Written informed consent was obtained from all participants (or their legal guardians) prior to inclusion in the study. Consent for publication Written informed consent was obtained from the patient for study and publication Availability of data and materials The raw sequencing data have been uploaded along with the manuscript as supplementary files. The datasets used during the current study are available from the corresponding author on reasonable request. Competing Interests All authors report no conflicts of interest. Funding This work was supported by the President Foundation of Nanfang Hospital, Southern Medical University (Youth Project, Grant No. 2024B053). Authors' contributions J.Zhu, L.Liu , K.Ren and P.Zhu collect and perform the meibum sample, then process lipidomics and GEO analysis. J. Zhu and wrote the text of the man manuscript and prepared Fig 1,2,3,4 and Table 1,2,3,4. L. Bai and M.Chen revised the manuscript and gave specialized academic guidance. All authors reviewed the manuscript. All authors read and approved the final manuscript. Acknowledgements We sincerely appreciate all the participants for their time and valuable insights contributed to this article. Our gratitude extends to Meliomics for their expert technical guidance and assistance with sample testing. We also thank NCBI, STRING, and other open-source databases for their data support, as well as HSBC engineer Peter Wan for his assistance with code development. References Papas EB. The global prevalence of dry eye disease: A Bayesian view. Ophthalmic physiological optics: J Br Coll Ophthalmic Opticians (Optometrists). 2021;41(6):1254–66. Dry Eye. New EnglanDjournal Med, 378(23), 2212–23. McCann P, Abraham AG, Mukhopadhyay A, Panagiotopoulou K, Chen H, Rittiphairoj T, Gregory DG, Hauswirth SG, Ifantides C, Qureshi R, Liu SH, Saldanha IJ, Li T. Prevalence and Incidence of Dry Eye and Meibomian Gland Dysfunction in the United States: A Systematic Review and Meta-analysis. JAMA Ophthalmol. 2022;140(12):1181–92. Butovich IA. Meibomian glands, meibum, anDmeibogenesis. Exp Eye Res. 2017;163:2–16. Zhu J, Liu L, Wu J, Bai L. Rodent models for dry eye syndrome (DES). Contact lens & anterior eye: the. J Br Contact Lens Association. 2025;48(3):102383. Ha M, Oh SE, Whang WJ, Na KS, Kim EC, Kim HS, Kim JS, Hwang HS. Relationship between meibomian gland loss in infrared meibography and meibum quality in dry eye patients. BMC Ophthalmol. 2022;22(1):292. Zhao W, Yang J, Liao Y, Yang B, Lin S, Liu R, Liang L. Alteration of Meibum Lipidomics Profiling in Patients With Chronic Ocular Graft-Versus-Host Disease. Investig Ophthalmol Vis Sci. 2023;64(12):35. Khanna RK, Catanese S, Emond P, Corcia P, Blasco H, Pisella PJ. Metabolomics and lipidomics approaches in human tears: A systematic review. Surv Ophthalmol. 2022;67(4):1229–43. Butovich IA, Uchiyama E, Di Pascuale MA, McCulley JP. Liquid chromatography-mass spectrometric analysis of lipids present in human meibomian gland secretions. Lipids. 2007;42(8):765–76. Han X, Gross RW. The foundations and development of lipidomics. J Lipid Res. 2022;63(2):100164. Zhao H, Wu SN, Shao Y, Xiao D, Tang LY, Cheng Z, Peng J. Lipidomics Profiles Revealed Alterations in Patients With Meibomian Gland Dysfunction After Exposure to Intense Pulsed Light. Front Neurol. 2022;13:827544. Garcia-Queiruga J, Pena-Verdeal H, Sabucedo-Villamarin B, Paz-Tarrio M, Guitian-Fernandez E, Garcia-Resua C, Yebra-Pimentel E, Giraldez MJ. Meibum Lipidomic Analysis in Evaporative Dry Eye Subjects. Int J Mol Sci. 2024;25(9):4782. Contrepois K, Mahmoudi S, Ubhi BK, Papsdorf K, Hornburg D, Brunet A, Snyder M. Cross-Platform Comparison of Untargeted and Targeted Lipidomics Approaches on Aging Mouse Plasma. Sci Rep. 2018;8(1):17747. Sethi S, Hayashi MA, Sussulini A, Tasic L, Brietzke E. Analytical approaches for lipidomics and its potential applications in neuropsychiatric disorders. world J Biol psychiatry: official J World Federation Soc Biol Psychiatry. 2017;18(7):506–20. Goodyear MD, Krleza-Jeric K, Lemmens T. The Declaration of Helsinki. BMJ. 2007;335(7621):624–5. Chinese Branch of the Asian Dry Eye Society; Ocular Surface and Tear Film Diseases Group of Ophthalmology Committee of Cross–Straits Medicine Exchange Association. Ocular Surface and Dry Eye Group of Chinese Ophthalmologist Association. Zhonghua Yan Ke Za Zhi. 2023;59(11):880–7. FOLCH J, LEES M, SLOANE, STANLEY GH. A simple method for the isolation and purification of total lipides from animal tissues. J Biol Chem. 1957;226(1):497–509. Mopuri R, Kalyesubula M, Rosov A, Edery N, Moallem U, Dvir H. Improved Folch Method for Liver-Fat Quantification. Front Vet Sci. 2021;7:594853. Published 2021 Jan 12. Matyash V, Liebisch G, Kurzchalia TV, Shevchenko A, Schwudke D. Lipid extraction by methyl-tert-butyl ether for high-throughput lipidomics. J Lipid Res. 2008;49(5):1137–46. Liebisch G, Fahy E, Aoki J, et al. Update on LIPID MAPS classification, nomenclature, and shorthand notation for MS-derived lipid structures. J Lipid Res. 2020;61(12):1539–55. Liu S, Richards SM, Lo K, Hatton M, Fay A, Sullivan DA. Changes in gene expression in human meibomian gland dysfunction. Invest Ophthalmol Vis Sci. 2011;52(5):2727–40. Published 2011 Apr 25. Barrett T, Wilhite SE, Ledoux P, et al. NCBI GEO: archive for functional genomics data sets–update. Nucleic Acids Res. 2013;41(Database issue):D991–5. 10.1093/nar/gks1193 . Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28(1):27–30. Shannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–504. Doncheva NT, Morris JH, Gorodkin J, Jensen LJ. Cytoscape StringApp: Network Analysis and Visualization of Proteomics Data. J Proteome Res. 2019;18(2):623–32. Steensels S, Ersoy BA. Fatty acid activation in thermogenic adipose tissue. Biochim Biophys Acta Mol Cell Biol Lipids. 2019;1864(1):79–90. Yao H, Ye J. Long chain acyl-CoA synthetase 3-mediated phosphatidylcholine synthesis is required for assembly of very low density lipoproteins in human hepatoma Huh7 cells. J Biol Chem. 2008;283(2):849–54. Deo PN, Deshmukh R. Pathophysiology of keratinization. J Oral Maxillofac Pathol. 2018;22(1):86–91. Shetty S, Gokul S. Keratinization and its disorders. Oman Med J. 2012;27(5):348–57. Park Y, Jung J, Jeong S, et al. Reversine enhances skin barrier functions by suppressing the IL-4- and IL-13-mediated STAT6 pathway. J Dermatol Sci. 2023;111(2):71–3. Song Qian H, Xue Q, Mengbin, et al. STAT3 pathway is involved in interleukin-22 promoting expression of tight junction protein in human colorectal cancer cell line HT29[J]. Basic Clin Med. 2021;41(6):792–8. Katoh M, Nakagama H. FGF receptors: cancer biology and therapeutics. Med Res Rev. 2014;34(2):280–300. DiPeri TP, Zhao M, Evans KW, et al. Convergent MAPK pathway alterations mediate acquired resistance to FGFR inhibitors in FGFR2 fusion-positive cholangiocarcinoma. J Hepatol. 2024;80(2):322–34. Ho BB, Bergwitz C. FGF23 signalling and physiology. J Mol Endocrinol. 2021;66(2):R23–32. Adeeb N, Mortazavi MM. The role of FGF2 in spinal cord trauma and regeneration research. Brain Behav. Yoon TY, Munson M. SNARE complex assembly and disassembly. Curr Biol. 2018;28(8):R397–401. Wesolowski J, Paumet F. Escherichia coli exposure inhibits exocytic SNARE-mediated membrane fusion in mast cells. Traffic. 2014;15(5):516–30. Suzuki R, Matsuda M, Watashi K, et al. Signal peptidase complex subunit 1 participates in the assembly of hepatitis C virus through an interaction with E2 and NS2. PLoS Pathog. 2013;9(8):e1003589. Gao Y, Jian L, Lu W, Xue Y, Machaty Z, Luo H. Vitamin E can promote spermatogenesis by regulating the expression of proteins associated with the plasma membranes and protamine biosynthesis. Gene. 2021;773:145364. Langemeyer L, Fröhlich F, Ungermann C. Rab GTPase Function in Endosome and Lysosome Biogenesis. Trends Cell Biol. 2018;28(11):957–70. Pfeffer SR. Rab GTPases: master regulators that establish the secretory and endocytic pathways. Mol Biol Cell. 2017;28(6):712–5. Fichna JP, Maruszak A, Żekanowski C. Myofibrillar myopathy in the genomic context. J Appl Genet. 2018;59(4):431–9. Lossos A, Oldfors A, Fellig Y, Meiner V, Argov Z, Tajsharghi H. MYH2 mutation in recessive myopathy with external ophthalmoplegia linked to chromosome 17p13.1-p12. Brain. 2013;136(Pt 7):e238. Aubol BE, Wozniak JM, Fattet L, Gonzalez DJ, Adams JA. CLK1 reorganizes the splicing factor U1-70K for early spliceosomal protein assembly. Proc Natl Acad Sci U S A. 2021;118(14):e2018251118. Macri C, Wang F, Tasset I, et al. Modulation of deregulated chaperone-mediated autophagy by a phosphopeptide. Autophagy. 2015;11(3):472–86. Gama-Brambila RA, Chen J, Zhou J, Tascher G, Münch C, Cheng X. A PROTAC targets splicing factor 3B1. Cell Chem Biol. 2021;28(11):1616–e16278. Khanim F, Kirk J, Latif F, Barrett TG. WFS1/wolframin mutations, Wolfram syndrome, and associated diseases. Hum Mutat. Fischer DF, van Drunen CM, Winkler GS, van de Putte P, Backendorf C. Involvement of a nuclear matrix association region in the regulation of the SPRR2A keratinocyte terminal differentiation marker. Nucleic Acids Res. 1998;26(23):5288–94. Thulasingam M, Orellana L, Nji E, Ahmad S, Rinaldo-Matthis A, Haeggström JZ. Crystal structures of human MGST2 reveal synchronized conformational changes regulating catalysis. Nat Commun. 2021;12(1):1728. Published 2021 Mar 19. Eshraghi A, Dixon SD, et al. Cytolethal distending toxins require components of the ER-associated degradation pathway for host cell entry. PLoS Pathog. 2014;10(7):e1004295. Published 2014 Jul 31. Mitsuishi Y, Taguchi K, Kawatani Y, et al. Nrf2 redirects glucose and glutamine into anabolic pathways in metabolic reprogramming. Cancer Cell. 2012;22(1):66–79. Zhang B, Zeng M, Li B, et al. Arbutin attenuates LPS-induced acute kidney injury by inhibiting inflammation and apoptosis via the PI3K/Akt/Nrf2 pathway. Phytomedicine. 2021;82:153466. Balamurugan K. HIF-1 at the crossroads of hypoxia, inflammation, and cancer. Int J Cancer. 2016;138(5):1058–66. Zhang P, Zhou YD, Tan Y, Gao L. Protective effects of piperine on the retina of mice with streptozotocin-induced diabetes by suppressing HIF-1/VEGFA pathway and promoting PEDF expression. Int J Ophthalmol. 2021;14(5):656–65. Published 2021 May 18. Ferrer CM, Lynch TP, Sodi VL, et al. O-GlcNAcylation regulates cancer metabolism and survival stress signaling via regulation of the HIF-1 pathway. Mol Cell. 2014;54(5):820–31. Additional Declarations No competing interests reported. Supplementary Files TableS1.listofidentifiedandnormalizedfeatures.xlsx TableS2.listofunidentifiedfeatures.xlsx TableS3a.differentialfeatures.xlsx TableS3.listofalteredlipids.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 18 May, 2026 Reviewers agreed at journal 18 Apr, 2026 Reviewers invited by journal 16 Apr, 2026 Editor assigned by journal 07 Apr, 2026 Submission checks completed at journal 07 Apr, 2026 First submitted to journal 07 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9303325","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":625407713,"identity":"08ee2541-f942-4428-8acf-3f6fbde9364d","order_by":0,"name":"Jingyun Zhu","email":"","orcid":"","institution":"Southern Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jingyun","middleName":"","lastName":"Zhu","suffix":""},{"id":625407717,"identity":"7c7940d5-16d8-4b83-b799-297540072a93","order_by":1,"name":"Liu Liu","email":"","orcid":"","institution":"Southern Medical University","correspondingAuthor":false,"prefix":"","firstName":"Liu","middleName":"","lastName":"Liu","suffix":""},{"id":625407721,"identity":"65ce2d7e-3a10-487f-a039-c5acc0c9caa3","order_by":2,"name":"Kaixian Ren","email":"","orcid":"","institution":"Southern Medical University","correspondingAuthor":false,"prefix":"","firstName":"Kaixian","middleName":"","lastName":"Ren","suffix":""},{"id":625407726,"identity":"eecd0d3a-2eca-4368-b4d0-93a1f60c5416","order_by":3,"name":"Peiyan Zhu","email":"","orcid":"","institution":"Southern Medical University","correspondingAuthor":false,"prefix":"","firstName":"Peiyan","middleName":"","lastName":"Zhu","suffix":""},{"id":625407729,"identity":"c5422cce-ce78-44e8-93ea-9f8ee49ad7b8","order_by":4,"name":"Lang Bai","email":"","orcid":"","institution":"Southern Medical University","correspondingAuthor":false,"prefix":"","firstName":"Lang","middleName":"","lastName":"Bai","suffix":""},{"id":625407731,"identity":"eaeedf69-f26c-47a8-8f03-75654b062e20","order_by":5,"name":"Minting Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYBAC+/b2AwckftTIMbY3EKnFgOdM4gHLnmPGzD0HiNUikWB8oIKNObF9RgKRWsx5DiQcuMHDltg78/HGGww1NtEEtVi2Nx44OMNCxnjm7LRiC4ZjabkNBPWcOZBwWIKHTXbj7BwzCcaGw0RouZFgcPgPGzPj/ptniNRiANRyQIKNWbFxBg+RWiR7ziQckAQGMmMP0C8JxPiFn7398AdIVB7eeONDjQ0RfkF2pEQCKcohWkjVMQpGwSgYBSMDAADk90ccuhCBMwAAAABJRU5ErkJggg==","orcid":"","institution":"Southern Medical University","correspondingAuthor":true,"prefix":"","firstName":"Minting","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2026-04-02 12:41:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9303325/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9303325/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107637200,"identity":"9452eb86-8fa1-4d30-9721-ab9dc5904f13","added_by":"auto","created_at":"2026-04-23 12:41:34","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":14408548,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOcular signs and tissue function based mechanisms for meibomian gland dysfunction (MGD)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe meibomian glands, arranged in parallel along the long axis of the upper and lower tarsal plates, consist of approximately 25–40 glands per eyelid. Each gland comprises 10–15 acini surrounding a central duct that opens at the posterior lid margin. Meibum is secreted onto the palpebral conjunctiva and spreads across the ocular surface with each blink, forming the tear film’s outermost lipid layer. These glands operate via a holocrine secretion mechanism, where basal cells proliferate, differentiate, and migrate toward the central duct, accumulating lipids. Upon reaching the duct, the cells undergo disintegration, releasing their lipid contents onto the ocular surface. This process yields a complex lipid mixture essential for tear film stability and ocular surface lubrication. Pathological conditions—such as ductal obstruction and inflammation—disrupt glandular function, leading to meibomian gland dysfunction (MGD), reduced lipid secretion, and the development of evaporative dry eye. Common clinical manifestations of MGD include conjunctival hyperemia, orifice obstruction with inspissated secretions, and gland dropout or distortion.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-9303325/v1/aed925264bc9ecfe0bc74db2.png"},{"id":107637197,"identity":"c1942510-b265-412d-b2ef-95ca6ed5797c","added_by":"auto","created_at":"2026-04-23 12:41:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":15153441,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHigh-fidelity lipidomics reveals significant differences between MGD and normal meibum Composition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(a, d) PCA 2D and 3D score plots of meibum from MGD and Normal (M/N) groups without quality control (QC); (b, e) PCA 2D and 3D score plots of M/N group meibum with QC; (c, f) Partial Least Squares Discriminant Analysis (PLS-DA) 2D and 3D score plots; (g) Distribution of significantly altered lipid classes when FC \u0026gt; 1.40 or \u0026lt; 0.71, and p-value \u0026lt; 0.05; (h) Proportions of significantly altered lipid class distributions; (i) Volcano plot showing up/down-regulated lipids when FC \u0026gt; 1.4 or \u0026lt; 0.71, with p \u0026lt; 0.05, indicating 210 lipids with FC \u0026gt; 1.4 and p \u0026lt; 0.05 (red) and 294 lipids with FC \u0026lt; 0.71 and p \u0026lt; 0.05 (blue); (j) Heatmap of the top 20 significant lipids by VIP score from PLS-DA analysis; (k) Heatmap of differential lipid expression for the top 100 lipids ranked by p-value.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-9303325/v1/895a4f281d61acf6d0682579.png"},{"id":107637154,"identity":"b8cd4d08-ce82-4717-a7f5-6829977520a6","added_by":"auto","created_at":"2026-04-23 12:41:21","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":14050749,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGEO Data-based GO and KEGG clustering analysis of MGD-related bioprocess and pathways\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(a) Heatmap of the top 100 differentially expressed genes between MGD and normal meibomian gland tissues based on p-value. (b) Volcano plot of differentially expressed genes selected with FC \u0026gt; 1.4 or \u0026lt; 0.71, p \u0026lt; 0.05, where red indicates upregulation and green indicates downregulation. (c) GO enrichment analysis of the top 10 differentially expressed genes (circle size represents the number of associated differential genes, color intensity indicates p-value). (d) KEGG enrichment analysis of the top 10 differentially expressed genes (circle size represents the number of associated differential genes, color intensity indicates p-value).\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-9303325/v1/7732e525d645bdd4b98cbc90.png"},{"id":107637180,"identity":"4654a1ff-72ac-4c48-81e4-8303894b4e2c","added_by":"auto","created_at":"2026-04-23 12:41:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":5947845,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMultidimensional Analysis of Key Protein–Protein Interaction Networks in MGD: Functional Annotation and Modular Clustering Visualization\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(a) Functionally annotated protein–protein interaction (PPI) network, with nodes colored according to associated biological processes or pathways. (b) Interaction strength network generated via MCODE clustering, where node color intensity reflects intra-module connectivity (darker nodes indicate higher clustering scores; lighter nodes represent peripheral or lower-scoring nodes). (c) Clustered PPI network delineating ten distinct modules (MCODE1–MCODE10), each colored based on functional annotation. (d) Integrated visualization of the full-scale PPI network, combining modular clustering and functional annotation. [Layer 1: MCODE-defined module color blocks. Layer 2: High-confidence intra-module interactions (bold edges) and lower-confidence inter-module interactions (thin edges). Layer 3: Cross-module intersections highlighting key pathological pathways.]\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-9303325/v1/e08d0c8a8365546fa476d91b.png"},{"id":107707910,"identity":"9ec70574-4218-45b6-9b21-f503e302465b","added_by":"auto","created_at":"2026-04-24 09:21:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":36814468,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9303325/v1/4c782b73-9b51-4869-accc-64c36621fe5d.pdf"},{"id":107637199,"identity":"5209678e-19be-45bd-81f2-b6693cb4ada7","added_by":"auto","created_at":"2026-04-23 12:41:33","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":620779,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.listofidentifiedandnormalizedfeatures.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9303325/v1/4418f99f85ea52cf6ffc875f.xlsx"},{"id":107637152,"identity":"5c339e55-53d4-4802-92ea-4bb954404d50","added_by":"auto","created_at":"2026-04-23 12:41:21","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1179614,"visible":true,"origin":"","legend":"","description":"","filename":"TableS2.listofunidentifiedfeatures.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9303325/v1/fa1d21489ebc0ca7c04437ae.xlsx"},{"id":107637198,"identity":"9db3a387-7078-4233-9362-56d373fa28cb","added_by":"auto","created_at":"2026-04-23 12:41:32","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":484144,"visible":true,"origin":"","legend":"","description":"","filename":"TableS3a.differentialfeatures.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9303325/v1/668496bdf87fb773f6f75ee0.xlsx"},{"id":107637153,"identity":"b068029b-4175-41cb-8f89-463028876be4","added_by":"auto","created_at":"2026-04-23 12:41:21","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":364520,"visible":true,"origin":"","legend":"","description":"","filename":"TableS3.listofalteredlipids.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9303325/v1/7ea773d2806565e0226eb54a.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"High-Fidelity Lipidomics Co-Clustering Analysis Reveals Critical Lipid Metabolic Crux and Mechanisms in Meibomian Gland Dysfunction (MGD)","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe global prevalence of dry eye has risen steadily, reaching 11.59% by 2021\u003csup\u003e1\u003c/sup\u003e, making it a significant public health concern. Traditionally, dry eye is classified into aqueous-deficient and evaporative subtypes\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, with further refinements based on tear film composition, including aqueous and mucin deficiency types. Tear film instability, hyperosmolarity, ocular surface microenvironmental dysregulation, and neurosensory dysfunction are central to its pathogenesis. Meibomian gland dysfunction (MGD), the leading cause of evaporative dry eye\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, presents clinically with conjunctival congestion, eyelid margin swelling, and ductal obstruction, often accompanied by viscous, toothpaste-like secretions. As specialized sebaceous glands, meibomian glands secrete meibum, which form the tear film\u0026rsquo;s outermost layer, reducing evaporation and preserving ocular surface homeostasis\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. A marked decline in lipid secretion from obstructed glands disrupts tear film integrity, driving disease progression\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. The mechanism of dry eye based on impaired function of meibomian gland in lipid secretion is illustrated as follows (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGiven its crucial lipid-secreting role, research on meibomian gland tissue and meibum components has gained traction\u003csup\u003e\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Lipidomics enables the identification and characterization of lipid metabolites by integrating mass spectrometry and chromatography, leveraging advancements in soft ionization techniques such as electrospray ionization and matrix-assisted laser desorption/ionization\u003csup\u003e10\u003c/sup\u003e. Meibum, a specialized lipid secretion, exhibits a complex composition predominantly consisting of nonpolar lipids, including wax esters (WE), cholesteryl esters (CE), and triglycerides (TG), alongside polar lipids such as ceramides (Cer), sphingomyelin, and phospholipids.Existing lipidomic analyses of meibum have identified significant differences between MGD and normal lid lipids, particularly in free fatty acids, cholesteryl esters, and ceramides\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. However, most studies remain limited to the identification of a few hundred lipid species and provide only statistical descriptions of a small subset of differentially expressed lipids. Conventional lipidomic assays often struggle with inefficient ionization and poor chromatographic retention of certain metabolites, hindering their detection by mass spectrometry\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Furthermore, precise metabolite identification necessitates isotopic internal standards, which are both costly and not universally applicable\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Additionally, the accurate interpretation of high-sensitivity ionic signals is highly dependent on instrument performance and methodological precision. Challenges such as small sample sizes, compositional complexity, and technical limitations have hindered comprehensive lipidomic profiling. To overcome these barriers, we employed high-performance lipidomics coupled with isotope labeling, enabling the quantitative detection of nearly 10,000 lipid species from minimal sample volumes.\u003c/p\u003e \u003cp\u003eAdditionally, we integrated GEO transcriptomic data to perform differential gene expression and clustering analyses, constructing gene expression and protein interaction networks. This approach aims to refine MGD pathogenesis, elucidate key signaling pathways, and bridge mechanistic insights with metabolic phenotypes, ultimately advancing our understanding of disease progression.\u003c/p\u003e \u003cp\u003eThe meibomian glands, arranged in parallel along the long axis of the upper and lower tarsal plates, consist of approximately 25\u0026ndash;40 glands per eyelid. Each gland comprises 10\u0026ndash;15 acini surrounding a central duct that opens at the posterior lid margin. Meibum is secreted onto the palpebral conjunctiva and spreads across the ocular surface with each blink, forming the tear film\u0026rsquo;s outermost lipid layer. These glands operate via a holocrine secretion mechanism, where basal cells proliferate, differentiate, and migrate toward the central duct, accumulating lipids. Upon reaching the duct, the cells undergo disintegration, releasing their lipid contents onto the ocular surface. This process yields a complex lipid mixture essential for tear film stability and ocular surface lubrication. Pathological conditions\u0026mdash;such as ductal obstruction and inflammation\u0026mdash;disrupt glandular function, leading to meibomian gland dysfunction (MGD), reduced lipid secretion, and the development of evaporative dry eye. Common clinical manifestations of MGD include conjunctival hyperemia, orifice obstruction with inspissated secretions, and gland dropout or distortion.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Isotope Dual-Labeling High-Fidelity Lipidomics for Human Meibum\u003c/h2\u003e \u003cp\u003eIn this study, human meibum samples were collected for dual-isotope labeling and high-fidelity lipidomic analysis. Chemical derivatization was applied to lipid metabolites to introduce hydrophobic groups and a tertiary amine structure, significantly enhancing column retention and ionization efficiency. Coupled with Agilent high-resolution mass spectrometry (HRMS), this approach improved detection sensitivity, ionization efficiency, and MS capture rate, thereby enhancing metabolite detection. The dual-isotope labeling method enabled precise quantitative analysis of lipid components, and a specialized three-tier metabolite identification database was established for reliable metabolite identification.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1. Sample and Study Design\u003c/h2\u003e \u003cp\u003eA total of 8 participants (16 eyes, 32 meibum samples) were included in the lipidomics study, with a mean age of 30.38\u0026thinsp;\u0026plusmn;\u0026thinsp;6.90 years (75% female). All participants were recruited from the Southern Hospital Eye Clinic, and written informed consent was obtained. The study adhered to the Declaration of Helsinki\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e and was approved by the Bioethics Committee of Nanfang Hospital (approval number: NFEC-2020-089). The MGD group must meet the diagnostic criteria outlined in the Chinese Expert Consensus on meibomian gland (2023 Definition and Classification), including abnormalities in the levator palpebral gland openings (e.g., blockage, stenosis, displacement, atresia, or congenital absence) or abnormal secretion of the levator glands (e.g., impaired discharge). Additionally, abnormal meibomian gland secretion, including irregular drainage and/or secretion characteristics, is required for diagnosis\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Ocular dryness and foreign body sensation, along with slit-lamp evidence of punctate epithelial erosions, decreased tear meniscus height, and abnormal Schirmer test results, also constitute key diagnostic indicators. Exclusion criteria include: recent ocular medication use or corneal contact lens wear within the past week; active ocular infections or inflammation unrelated to MGD; history of ocular burns or surgery; systemic diseases associated with MGD (such as dry eye syndrome, Stevens-Johnson syndrome, hyperthyroidism, pemphigus, or cerebral nerve injury); pregnant or lactating women.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.1.2. Meibum Sample Collection\u003c/h2\u003e \u003cp\u003eThe operators were experienced healthcare professionals with specialized ophthalmology training. Meibum samples were collected with the subjects seated in front of a slit lamp, their chin resting on a stand. The subjects were instructed to relax their eyelids while gazing at the floor or ceiling during the collection from the upper and lower eyelids. For 30 seconds, the operator gently pressed the upper and lower eyelids with the thumb to facilitate meibum drainage through the meibomian ducts to the ocular margins. Then the meibum samples were then carefully collected from the lid margin using a sterilized stainless steel spatula\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. The samples were immediately placed in aseptic enzyme-free EP tubes and frozen at -80℃ within 1 hour for further analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.1.3. Sample pre-processing\u003c/h2\u003e \u003cp\u003eMetabolite samples were prepared following standard operating procedures (SOPs) based on the modified Folch liquid-liquid extraction method\u003csup\u003e\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Each sample was homogenized with a lipid tissue internal standard mixture (15 deuterated lipids), methanol, and ceramic beads using a bead mill, followed by the addition of dichloromethane and water for separate homogenization. After 10 minutes of equilibration at room temperature, samples were centrifuged at 15,000 g for 10 minutes at 4℃. The organic layers were then transferred into centrifuge tubes and dried under nitrogen. Solvents A/B, consisting of ultrapure deionized water, chromatographic-grade methanol, propanol, acetonitrile, and ammonium formate (specific ratios are detailed in the next liquid chromatography-mass spectrometry analysis procedure), were prepared. The residue was re-solubilized in mobile phase B (MPB), vortexed for 1 minute, and diluted with mobile phase A (MPA). An extract pool for quality control (QC) was prepared by dividing the mixture into aliquots, drying with nitrogen, and storing at -80℃. Samples were randomly grouped into sets of 9, with one pool sample reconstituted and diluted as QC for the batch.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.1.4. Liquid Chromatography\u0026ndash;Mass Spectrometry Analysis\u003c/h2\u003e \u003cp\u003eAll samples were analyzed in both positive and negative ion modes, with LC-MS and LC-MS/MS data acquired for each mode. Quality control (QC) data for each group of nine samples were collected before and after analysis, with additional QCs performed before and after all sample injections to ensure technical stability. Reversed-phase liquid chromatography separation and mass spectrometry analysis were conducted using an Agilent 1290 LC system coupled with an Agilent 6546 Q-TOF Mass Spectrometer, employing a Waters Acquity CSH C18 column (1.7 \u0026micro;m). The on-column injection volumes were 5 \u0026micro;L for positive ions and 12 \u0026micro;L for negative ions. The column temperature was maintained at 40\u0026deg;C, while the autosampler was kept at 8\u0026deg;C to prevent sample evaporation. The samples were eluted using a 26-minute gradient at a flow rate of 210\u0026ndash;250 \u0026micro;L/min, with MPA (methanol/acetonitrile/water containing 10 mM ammonium formate, 50:40:10) and MPB (2-propanol/water containing 10 mM ammonium formate, 95:5). Mass spectrometry was performed in electrospray ionization (ESI) mode, with precursor ions fragmented in the m/z range of 150\u0026ndash;1500 and MS/MS collision energies set at 10\u0026ndash;60 eV. Data were processed and exported using MassHunter software.\u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.1.5. Lipid Annotation\u003c/h2\u003e \u003cp\u003eLipid characteristic peaks were extracted and aligned using LipidScreener 1.1.0. Data from both positive and negative ions were combined, creating a unified feature intensity table for all samples. Feature peaks absent in more than 80% of samples were filtered out. Missing values in samples detected in at least 75%, 50%, or fewer than 50% of cases were replaced with the median intensity, minimum intensity, or the overall minimum value, respectively, for all samples and QC. Lipid identification was performed using a three-tier approach based on MS/MS spectral similarity, retention time, and exact mass matching\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. LipidScreener 1.1.0 employs nine levels of filtering and scoring to calculate MS/MS match scores, limit matches, and select the best identifications. Tier I and II identifications are conducted at the species or molecular type level, including lipid class and subclass definitions, fatty acyl/alkyl residue composition, and functional groups. Tier III identifications are made at the species level, considering lipid classes, carbon atoms, double bond equivalents, and additional atoms such as oxygen. All identified compounds from the three tiers were combined, normalized, and statistically analyzed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.1.6. Lipidomics Statistical Analysis\u003c/h2\u003e \u003cp\u003eA set of 15 deuterated internal standards (LipidRep Internal Standard Basic Mix for Tissue/Cells) representing various lipid classes was used to normalize the data for identified characteristic peaks. Lipids were matched to one of the 15 internal standards based on lipid class similarity and expected retention time ranges. Intensity ratios were calculated, and internal standard normalization was performed by dividing the intensity of each lipid by the intensity of its corresponding internal standard. Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. presents the peak intensity ratios for identified compounds, normalized by both internal standard and median. Non-informative features (e.g., internal standards, common contaminants, and low-reproducibility features) were filtered out. The data were then uploaded to LipidScreener 1.1.0, where additional filtering of near-constant features (the 30% with the smallest relative standard deviation across all samples) and auto-scaling were performed.\u003c/p\u003e\u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Pathway and functional enrichment analysis\u003c/h2\u003e \u003cp\u003eComplete open-source GEO data on gene expression differences between normal and MGD-associated blepharoplasty samples (GSE17822) were obtained from the NCBI database, including expression matrices and sample information files\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. The raw data underwent cleaning and normalization, followed by selective logarithmic transformation based on expression differences, with a logFC value set to 1 and a corrected P-value threshold of 0.05 to identify significant differential genes. Gene ontology (GO) and KEGG analyses were then conducted on the differential genes\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, and Fisher's exact test was used to detect significant enrichment in cellular processes and regulatory pathways.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Protein-Protein Interaction (PPI) analysis\u003c/h2\u003e \u003cp\u003eTarget protein interactions were retrieved from the STRING database and imported into Cytoscape for visualization. Network topology analysis, including node degree and clustering coefficients, was performed using the CytoHubba plug-in to identify key proteins or hub genes\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. The network layout was then adjusted to produce an intuitive protein interaction graph. Functional sub-networks were further delineated using module detection algorithms (e.g., MCODE), and biological significance was assessed through GO and KEGG pathway annotation.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Landscape of human meibums was constructed using dual-isotope labeled high-fidelity lipidomics\u003c/h2\u003e \u003cp\u003eA total of 18 samples (8 experimental and 10 QC) were collected for liquid chromatography analysis, with both positive and negative ion data combined. Only characteristic peaks detected in at least 80% of the samples in a group were retained for identification and normalization, while less reproducible peaks were filtered out to ensure data quality. After filtering, an average of 8939\u0026thinsp;\u0026plusmn;\u0026thinsp;233 feature peaks were detected per sample. The number of detected peaks per sample is summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, with Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. listing identified and normalized feature peaks, and Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e. summarizing unidentified peaks. Lipid identification was performed using LipidScreener 1.1.0, applying a three-tiered identification approach with nine filtering and scoring levels, including retention time filters based on lipid class and fatty acyl group. This methodology allowed for precise matching of characteristic peaks to the most appropriate lipid type. The high-fidelity lipidomics approach used in this study, with a 40 \u0026micro;L very small meibum sample size, extended lipid identification to 10,000 feature peaks, ensuring comprehensive and sensitive lipid identification and constructing the landscape of MGD-associated meibum. The overall distribution of meibum lipid components in both groups reveals a complex composition of human blepharoplastin, as detailed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The primary dominant components are wax esters (WE) and cholesteryl esters (CAR), while secondary dominant components include sphingolipids (Sphingolipids, NAE), hydroxy fatty acids (HC), and N-acylethanolamines (NAE). These lipid classes collectively form a complex metabolic network, where the dynamic balance is essential for maintaining ocular surface health.​​​​\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\u003eNumber of features detected per sample\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of feature peaks\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMGD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9255\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMGD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8853\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMGD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9163\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMGD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8951\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9510\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9176\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8866\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQC 01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8686\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQC 02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8735\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQC 03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8732\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQC 04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8876\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQC 05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8848\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQC 06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8676\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQC 07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8901\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQC 08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8825\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQC 1_1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8703\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQC 1_2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8846\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eAbbreviations: Meibomian gland dysfunction (MGD), Quality control (QC)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eA meibum panorama depicted by high-fidelity lipidomics based on MGD and Normal biclass samples\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenre\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eType\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStructure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDetection Example\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFunction\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSimple Lipids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eWax Esters, WE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEsters formed from long-chain fatty acids\u0026thinsp;+\u0026thinsp;long-chain fatty alcohols\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWE 20:3\u003c/p\u003e \u003cp\u003e (Feature 191)\u003c/p\u003e \u003cp\u003eWE 22:2 \u003c/p\u003e \u003cp\u003e(Feature 781)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eThe core ingredient of the tear film hydrophobic layer prevents evaporation of tears.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCholesteryl Esters, CE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCholesterol\u0026thinsp;+\u0026thinsp;fatty acid esterification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCE 15:0;O3\u003c/p\u003e \u003cp\u003e (Feature 73)\u003c/p\u003e \u003cp\u003eCE 17:0 \u003c/p\u003e \u003cp\u003e(Feature 74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRegulation of tear film fluidity and oxidative CE (e.g., O3 modification) suggest oxidative stress.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eGlycerolipids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eTriacylglycerols, TG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGlycerol\u0026thinsp;+\u0026thinsp;3 fatty acids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eTG detection is limited in negative ion mode.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eMonoacylglycerols, MG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGlycerol\u0026thinsp;+\u0026thinsp;1 fatty acid.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMG 28:0\u003c/p\u003e \u003cp\u003e (Feature 2702)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePresent in trace amounts, possibly lipid metabolism intermediates.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003ePhospholipids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGlycerophos-pholipids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLysophospha-\u003c/p\u003e \u003cp\u003etidylcholine, LPC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGlycerol\u0026thinsp;+\u0026thinsp;1 fatty acid. Glycerol\u0026thinsp;+\u0026thinsp;1 fatty acid\u0026thinsp;+\u0026thinsp;choline phosphate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLPC 18:0\u003c/p\u003e \u003cp\u003e (Feature 461)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePro-inflammatory mediator.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePhospha-\u003c/p\u003e \u003cp\u003etidylinositol, PI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePhospholipids\u0026thinsp;+\u0026thinsp;Inositol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePI-Cer 41:4;O4\u003c/p\u003e \u003cp\u003e (Feature 1595)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePro-inflammatory mediator signaling, possibly involved in apoptosis regulation.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eSphingomyelins, SPB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSphingosine base\u0026thinsp;+\u0026thinsp;fatty acid\u0026thinsp;+\u0026thinsp;choline phosphate.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19:0;O3 (Feature 619)\u003c/p\u003e \u003cp\u003eSPB 18:0;O2 \u003c/p\u003e \u003cp\u003e(Feature 1241)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePro-inflammatory mediator signaling, which may be involved in apoptosis regulating cell membrane components, accumulates abnormally in MGD or leads to catheter obstruction.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eSphingolipids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCeramides, Cer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSphingomyelin base\u0026thinsp;+\u0026thinsp;fatty acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCer 33:2;O \u003c/p\u003e \u003cp\u003e(Feature 2172)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eA key component of the epithelial barrier, oxidized Cer (e.g., O modification) is associated with abnormal MGD keratinization.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eHexosylceramides, HexCer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCeramide\u0026thinsp;+\u0026thinsp;Hexose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHexCer 29:1;O6\u003c/p\u003e \u003cp\u003e (Feature 2138)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eInvolved in cellular recognition with very low abundance.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eSulfatides, ST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGalactosylceramide\u0026thinsp;+\u0026thinsp;Sulfated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eST 25:4;O3;T \u003c/p\u003e \u003cp\u003e(Feature 912)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAntimicrobial effects that may influence MGD by modulating the ocular surface microbiota\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eGlycolipids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGlycero-\u003c/p\u003e \u003cp\u003eglycolipids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMonogalactosyldiglyce-rides, MGDG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGlycerol backbone\u0026thinsp;+\u0026thinsp;fatty acid chain\u0026thinsp;+\u0026thinsp;galactose moiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSugar-modified LPS 15:0 \u003c/p\u003e \u003cp\u003e (Feature 1665)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStronger polarity, able to interact with water molecules, maintain the stability and function of the vesicle-like membrane, photoprotective function against oxidative damage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplex glyco-\u003c/p\u003e \u003cp\u003esphingolipids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMyoInositol Phosphate Ceramide, MIPC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCeramide\u0026thinsp;+\u0026thinsp;Inositol Phosphate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMIPC 31:4;O6 \u003c/p\u003e \u003cp\u003e(Feature 2918)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSignaling molecules, which are extremely low in abundance but may be involved in inflammatory regulation.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eDerived Lipids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eFree Fatty Acids, FFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnesterified fatty acid chains\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFA 16:1 \u003c/p\u003e \u003cp\u003e(Feature 1100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eShort-chain FA maintains tear film fluidity, and long-chain oxidized FA (e.g., FA 22:5;O6) is involved in MGD inflammation.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eFatty Alcohols, FOH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLong-chain primary alcohols\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFOH 20:3\u003c/p\u003e \u003cp\u003e (Feature 483)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWE synthesized precursors, and some FOH abundance was decreased in the MGD group.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eN-Acylethanolamines, NAE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFatty acids\u0026thinsp;+\u0026thinsp;Ethanolamines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNAE 20:2\u003c/p\u003e \u003cp\u003e (Feature 768)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEndogenous cannabinoid analogs, pro-inflammatory NAE (e.g., 20:2) were upregulated in the MGD group.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eN-Acyltaurines, NAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFatty acids\u0026thinsp;+\u0026thinsp;taurine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNAT 27:5 \u003c/p\u003e \u003cp\u003e(Feature 972)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBile acid metabolism-associated molecules.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eOxidized Lipids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eHydroxylated lipids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHydroxyl-containing (-OH) modifications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCar 15:0;O3 \u003c/p\u003e \u003cp\u003e(Feature 73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOxidative stress markers, generally elevated in the MGD group\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eEpoxidized/Peroxidized Lipids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEpoxy group\u0026thinsp;+\u0026thinsp;unsaturated fatty acid chain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFA 22:5;O6\u003c/p\u003e \u003cp\u003e (Feature 2038)\u003c/p\u003e \u003cp\u003eNAE 20:2;O2 \u003c/p\u003e \u003cp\u003e(Feature 768)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePro-inflammatory mediators that may exacerbate blepharoplasty injury via the LOX/COX pathway.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eOther special lipids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eLyso-phospholipids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMonoacylglycerophospholipids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLPC 18:0 (Feature 461)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePro-inflammatory effects, elevated concentrations in tears of MGD patients\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eEther Lipids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAlkyl or alkenyl ether bond\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLPC O-16:0 \u003c/p\u003e \u003cp\u003e(Feature 1092)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMembrane structure is stable and low in abundance, but enhances tear film toughness.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Significant expression differences between MGD and normal meibum samples\u003c/h2\u003e \u003cp\u003eQuality control (QC) checks were performed using LipidScreener 1.1.0, where non-informative features (e.g., internal standards, common contaminants, and peaks with low reproducibility) were filtered out. Additionally, features with near-constant values across groups (the 30% with the smallest relative standard deviation) were excluded and the data were auto-scaled. The two-dimensional (2D) and three-dimensional (3D) principal component analysis (PCA) score plots, with QC samples indicated in green (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. a-f), demonstrate the method's good reproducibility. Volcano plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. i) were generated using fold change (FC) and p-value, calculated by comparing the means of groups M and N (Normal) (Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). p-values were derived from a t-test, while q-values were FDR-adjusted (Storey\u0026rsquo;s q-value). Using FC\u0026thinsp;\u0026gt;\u0026thinsp;1.4 or \u0026lt;\u0026thinsp;0.71, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and q\u0026thinsp;\u0026lt;\u0026thinsp;0.25 as significance criteria, 210 lipids showed FC\u0026thinsp;\u0026gt;\u0026thinsp;1.4 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (red), and 294 lipids had FC\u0026thinsp;\u0026lt;\u0026thinsp;0.71 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (blue). P-value thresholds of 0.05 corresponded to q-values\u0026thinsp;\u0026le;\u0026thinsp;0.25. VIP values from PCA were calculated, and the top 20 VIP and top 100 p-value lipids were plotted in a heatmap (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. j-k). This showed significant clustering of up- and down-regulated lipids, indicating a marked difference in lipid expression profiles between groups M and N. Among the lipid clusters (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. g-h), sphingolipids dominated (41.1%), followed by fatty acyls (20.6%) and sterols (15.1%), suggesting their coregulatory roles. Glycerophospholipids and glycerolipids, key components of cell membranes, also showed notable changes, though their relatively smaller variation contrasted with the significant fluctuations in sphingolipids. This may reflect selective regulation of membrane stability and lipid metabolism, with abnormal distribution pointing to imbalances in energy storage and structural lipid metabolism.\u003c/p\u003e \u003cp\u003e(a, d) PCA 2D and 3D score plots of meibum from MGD and Normal (M/N) groups without quality control (QC); (b, e) PCA 2D and 3D score plots of M/N group meibum with QC; (c, f) Partial Least Squares Discriminant Analysis (PLS-DA) 2D and 3D score plots; (g) Distribution of significantly altered lipid classes when FC\u0026thinsp;\u0026gt;\u0026thinsp;1.40 or \u0026lt;\u0026thinsp;0.71, and p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05; (h) Proportions of significantly altered lipid class distributions; (i) Volcano plot showing up/down-regulated lipids when FC\u0026thinsp;\u0026gt;\u0026thinsp;1.4 or \u0026lt;\u0026thinsp;0.71, with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, indicating 210 lipids with FC\u0026thinsp;\u0026gt;\u0026thinsp;1.4 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (red) and 294 lipids with FC\u0026thinsp;\u0026lt;\u0026thinsp;0.71 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (blue); (j) Heatmap of the top 20 significant lipids by VIP score from PLS-DA analysis; (k) Heatmap of differential lipid expression for the top 100 lipids ranked by p-value.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Normal meibum exhibits shorter chains and more modified functional groups compared to MGD\u003c/h2\u003e \u003cp\u003eLipidomics analysis revealed significant differences in meibum composition between normal subjects and MGD patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. k, Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). While the α-diversity (number of lipid species identified) was similar in both groups, the β-diversity of meibum was significantly lower in the MGD group, indicating a homogenization of lipid expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. j). This suggests that meibum dedifferentiation may contribute to MGD development. Differential lipid expression showed that MGD meibum was enriched with a higher proportion of neutral lipids (CE, WE, long-chain Cer) and medium- to long-chain lipids (saturated fatty acids), whereas normal meibum contained more short-chain lipids (short-chain Cer, polyunsaturated fatty acids) and complex modifications (hydroxylation, glycosylation). Overall, normal meibum maintains high water solubility, protein interactions, and biofilm affinity, whereas MGD meibum exhibits increased melting point and hydrophobicity (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), leading to reduced lipid mobility and the formation of lipid plugs that obstruct meibomian gland openings, consistent with the pathological progression of MGD.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferences and Identities of dominantly expressed components between MDG and Normal meibums\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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMGD Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKey Differences\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCholesteryl ester (CE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh ratios (CE30:2, CE33:2, CE27:2, etc.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003elow content\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMGD Group is dominated by neutral lipids (cholesterol esters), Normal Group has less CE lipids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCeramide (Cer)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRegular ceramides (Cer50:2, Cer38:2, Cer45:0, etc.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eShort chain/modified ceramides\u003c/p\u003e \u003cp\u003e (Cer9:0, Cer30:1, Cer54:0, etc.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNormal Group contains more short-chain ceramides and complex modifications\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFatty acids (FA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCommon fatty acids (FA32:1, FA30:1, etc.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFAHFA (Branched fatty acid esters of hydroxy fatty acids), Short-faced FA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNormal Group contains hydroxylated modifications (FAHFA) and shorter-chain fatty acids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlycolipid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elow content\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMGDG (Monogalactosyldiacylglycerol)、HexCer (Hexosylceramide)、\u003c/p\u003e \u003cp\u003eHex2Cer (Dihexosylceramide)、\u003c/p\u003e \u003cp\u003eST(Sulfoquinovosyl diacylglycerol)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNormal Group contains large amounts of glycosylated lipids (e.g., MGDG, HexCer), MGD Group has very low content.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSphingolipid derivatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConventional sphingolipids (Cer, CerP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSPB (sphingomyelin analog), PE-Cer (phospholipid-ceramide conjugate)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNormal Group contains bound sphingolipids (PE-Cer) and possibly new types of sphingolipids.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eglycol ester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDG (diglycerides), MG (monoglycerides)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDG (diglycerides), MG (monoglycerides)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGlycerol esters are present in both groups, but Normal Group contains more short-chained meibums.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther lipids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWax esters (WE), carnitine (Car), NAE (N-acyl ethanolamine)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCar (carnitine), LPS (lipopolysaccharide analog), PR (possibly oxidized phospholipids)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNormal Group contains more specifically modified lipids, while MGD Group has neutral lipids.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIdentities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHydrophobicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh (CE, WE, long chain Cer)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow (glycosylation, hydroxylation increase polarity)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe sugar and hydroxyl groups of Normal Group make the lipids more soluble in water.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMelting Point\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigher (high percentage of long-chain saturated fatty acids)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLower (high percentage of short-chain, polyunsaturated fatty acids)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe short chains and multiple double bonds of Normal Group reduce intermolecular forces.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIonization Efficiency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProne to ionization in positive ion mode (e.g. CE, Cer)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBetter in negative ion mode (e.g., glycolipids, FAHFA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAcidic groups of Normal Group (phosphate, sulfate, hydroxyl) deprotonate more readily in negative ion mode.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChromatographic Retention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLong retention time in reversed-phase chromatography (highly hydrophobic)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eShort retention time or need for hydrophilic chromatography (e.g., HILIC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe polar head group of Normal Group reduces reversed-phase chromatographic retention.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiofilm Affinity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePredominantly found in lipid droplets or in membrane hydrophobic regionss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTendency to be on the surface of membranes or in lipid rafts (e.g., glycolipids, sphingolipids)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe polar head group of Normal Group interacts more strongly with membrane proteins.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.4. CO-clustering Analysis: Alterations in lipid differentiation, cellular environment, and inflammatory processes contribute to MGD\u003c/h2\u003e \u003cp\u003eComparison of gene expression between normal and MGD-associated glabellar glands based on open GO data revealed significant differences in gene expression and functional pathways in MGD (meibomian gland dysfunction) compared to normal samples. Clustering heatmap analysis of the top 100 p-value genes demonstrated significant up- and down-regulation of gene expression between MGD and normal groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.a). The volcano plot further confirmed extensive differential gene distribution, suggesting a multidimensional molecular regulatory imbalance in MGD (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.b). GO enrichment analysis of differential genes showed significant enrichment in biological processes such as gland development, axonogenesis, and eye maturation, with close associations to cellular components like intercellular junctions, extracellular matrix, and gland secretion, and molecular functions such as transcriptional receptor activity and ion transport (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.c). These findings suggest that MGD may disrupt signaling networks involved in gland differentiation, metabolism, and development. KEGG pathway analysis identified enrichment in neuroactive ligand-receptor interactions, adhesion patches, and mucocytoskeleton pathways, indicating the involvement of intercellular communication, adhesion migration, and glandular dysfunction as key mechanisms in MGD. Disruption of RNA polymerase II-related pathways supports transcriptional dysregulation, while the MAPK/PI3K-Akt metabolic-inflammation pathway highlights inflammation and cell death throughout MGD progression. Enrichment of pathways related to atherosclerosis and lipid metabolism disorders correlates with meibum expression abnormalities (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.d). In conclusion, MGD's molecular features likely involve extracellular matrix abnormalities, mitochondrial dysfunction, lipid metabolism disruptions, immune dysregulation, and neural signaling impairments, suggesting the need for further functional validation and pathway exploration of key genes.\u003c/p\u003e \u003cp\u003e(a) Heatmap of the top 100 differentially expressed genes between MGD and normal meibomian gland tissues based on p-value. (b) Volcano plot of differentially expressed genes selected with FC\u0026thinsp;\u0026gt;\u0026thinsp;1.4 or \u0026lt;\u0026thinsp;0.71, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, where red indicates upregulation and green indicates downregulation. (c) GO enrichment analysis of the top 10 differentially expressed genes (circle size represents the number of associated differential genes, color intensity indicates p-value). (d) KEGG enrichment analysis of the top 10 differentially expressed genes (circle size represents the number of associated differential genes, color intensity indicates p-value).\u003c/p\u003e \u003cp\u003eProtein-Protein Interaction (PPI) network analysis, using STRING, further elucidated the pathogenesis of MGD by calculating the basic topological attributes of differential genes, adjusting for node centrality and network properties. MCODE (Cytoscape plugin) was employed to identify tightly connected sub-networks based on node density. The top 10% of genes were selected using comprehensive topological metrics (Degree, Betweenness, Closeness), and core driver genes were identified by combining differential expression levels (e.g., log2FC) with their topological importance within the module. Functional module annotation was then performed using the R studio clusterProfiler package, constructing the MGD-related molecular action network (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). PPI analysis identified 10 key molecular patterns closely associated with lipid metabolism, glandular duct function, vesicular transport, and inflammatory damage pathways. Detailed analysis in the subsequent pathway identification section not only complements the lipidomics findings but also provides insights into the pathogenesis and potential targets related to MGD.\u003c/p\u003e \u003cp\u003e(a) Functionally annotated protein\u0026ndash;protein interaction (PPI) network, with nodes colored according to associated biological processes or pathways. (b) Interaction strength network generated via MCODE clustering, where node color intensity reflects intra-module connectivity (darker nodes indicate higher clustering scores; lighter nodes represent peripheral or lower-scoring nodes). (c) Clustered PPI network delineating ten distinct modules (MCODE1\u0026ndash;MCODE10), each colored based on functional annotation. (d) Integrated visualization of the full-scale PPI network, combining modular clustering and functional annotation. [Layer 1: MCODE-defined module color blocks. Layer 2: High-confidence intra-module interactions (bold edges) and lower-confidence inter-module interactions (thin edges). Layer 3: Cross-module intersections highlighting key pathological pathways.]\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFunctional module annotation based on PPI analysis of MGD differentially expressed genes\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\u003eMCODE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLog10(P)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR-HSA-9841922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMLL4 and MLL3 complexes regulate expression of PPARG target genes in adipogenesis and hepatic steatosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-8.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR-HSA-9851695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEpigenetic regulation of adipogenesis genes by MLL3 and MLL4 complexes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-8.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR-HSA-9818564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEpigenetic regulation of gene expression by MLL3 and MLL4 complexes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-8.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePID E2F pathway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR-HSA-453279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMitotic G1 phase and G1/S transition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGO:0031647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eregulation of protein stability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR-HSA-6809371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFormation of the cornified envelope\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-17.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR-HSA-6805567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKeratinization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-15.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGO:0030216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ekeratinocyte differentiation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-11.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGO:0000398\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emRNA splicing, via spliceosome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-10.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGO:0000377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRNA splicing, via transesterification reactions with bulged adenosine as nucleophile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-10.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGO:0000375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRNA splicing, via transesterification reactions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-10.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCORUM:1142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSMN complex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-9.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCORUM:1745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSMN complex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCORUM:1143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSMN complex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR-HSA-1839122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSignaling by activated point mutants of FGFR1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR-HSA-190375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFGFR2c ligand binding and activation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-9.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR-HSA-190373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFGFR1c ligand binding and activation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-9.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehsa04130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSNARE interactions in vesicular transport\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-8.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGO:0061025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emembrane fusion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-6.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGO:0061024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emembrane organization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR-HSA-390522\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStriated Muscle Contraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR-HSA-397014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMuscle contraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-6.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCODE_10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehsa04820\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCytoskeleton in muscle cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-6.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Identification of regulatory pathways involved in MGD\u003c/h2\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e3.5.1. Lipid metabolism-related pathways\u003c/h2\u003e \u003cp\u003eLipidomics studies reveal significant differences in meibum composition between MGD patients and normal subjects. MGD meibum is enriched in neutral lipids, such as cholesteryl esters, wax lipids, and long-chain fatty acids, which are hydrophobic, have higher melting points, and are prone to forming lipid plugs. In contrast, normal meibum predominantly contains short-chain, multi-modified lipids that exhibit better water solubility, enhanced mobility, and stronger interactions with biofilms, thereby maintaining ocular surface homeostasis. These findings suggest that abnormal lipid metabolism plays a key role in MGD pathogenesis. GO and KEGG clustering analyses indicated that MGD affects lipid elongation by promoting the expression of EC 3.1.2.2 (palmitoyl-CoA hydrolase), which facilitates the formation of hypercoagulable lipids. EC 3.1.2.2 hydrolyzes substrates required for lipid elongation, limiting subsequent elongation reactions. The Coenzyme A (CoASH) released by EC 3.1.2.2 supports β-oxidation and the tricarboxylic acid cycle, maintaining cellular energy homeostasis. During tissue dysfunction and energy stress, CoASH may preferentially support fatty acid catabolism (β-oxidation) over elongation, shifting metabolism to balance the CoASH pool. However, excess acyl-CoA is lipotoxic, and EC 3.1.2.2 helps prevent lipotoxic damage by hydrolyzing acyl-CoA, thus maintaining lipid elongation enzyme system function\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Additionally, PPI analysis identified MCODE_1, suggesting that the MLL3/MLL4 complex regulates PPARG (Peroxisome proliferator-activated receptor Gamma) target genes, mediating epigenetic control of lipid metabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). MLL3/MLL4, as histone H3K4 methyltransferases, regulate adipogenesis through epigenetic mechanisms. This is associated with sphingolipid metabolism disorders observed in pre-lipidomics studies, indicating that dysregulation of PPARG may contribute to abnormal lipid synthesis in MGD.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e3.5.2. Glandular duct function-related pathways\u003c/h2\u003e \u003cp\u003eDuring the progression of MGD, differences in meibum composition and reduced quality compared to the normal state contribute to tear film dysfunction, a key manifestation of the disease. Functionally, the glandular state influences meibum production and secretion, which warrants further investigation. Combined protein pathway analysis revealed that glandular ductal keratinization, dysregulated gland regeneration, impaired membrane fusion, and abnormal myogenic glandular motility are strongly associated with MGD pathogenesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). MCODE_3 identified excessive keratinization of the meibomian gland ductal epithelium as the central mechanism of ductal obstruction in MGD. The keratinization module, enriched in keratins (e.g., KRT1, KRT10) and genes related to keratin envelope formation\u003csup\u003e2830\u003c/sup\u003e (e.g., FLG, IVL), suggests that the IL-22/STAT3 pathway may promote abnormal keratinization by upregulating keratin expression\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. MCODE_7 highlighted the role of FGFR signaling, activated by FGFR1c/2c ligands, in the core pathway of glandular regenerative dysregulation in MGD. FGFR signaling, through MAPK and PI3K-Akt pathways, regulates cell proliferation and differentiation\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, and its aberrant activation may lead to blepharoplakic follicle structure disruption (atrophy or overgrowth), which is associated with pathological MGD subtypes. The balance between FGF2 (pro-regenerative) and FGF23 (pro-fibrotic) likely determines the direction of gland repair\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. MCODE_9 emphasized the central role of membrane fusion and secretion dysfunction. SNARE-mediated fusion, enriched with vesicular transport proteins\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e (e.g., VAMP8, SNAP25), may be impaired, leading to dysfunction in meibum lipid granule release. The heatmap-identified Signal Peptidase Complex Subunit 1 (SPCS1) deficiency coincied the diminished lipid secretion, as it facilitates protein maturation through signal peptide cleavage\u0026mdash;a prerequisite for vesicular trafficking\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Its functional impairment disrupts secretory processes via compromised vesicle biogenesis and defective lipid-transporter processing. Dysregulated vesicular transport by Rab GTPases may represent a potential therapeutic target\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Additionally, MCODE_10 enriched pathways associated with impaired muscle contraction and glandular emptying. These include the contractile cytoskeleton of the rhabdomyosarcoma muscle, enriched in contraction-associated proteins of the blepharosphenoid myoepithelium\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e (e.g., MYH2, ACTA1). Dysfunction of these proteins may reduce lipid efflux, leading to lipid accumulation in gland ducts and contributing to glandular obstruction.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e3.5.3. Inflammatory-oxidative damage-related pathways\u003c/h2\u003e \u003cp\u003eFrom a pathological perspective, inflammation and oxidative stress represent critical mechanisms in MGD, with diverse forms of glandular injury converging to initiate localized inflammatory responses and apoptosis, ultimately leading to tissue dysfunction. The ocular surface, due to its direct exposure to environmental pathogens and harmful agents, is particularly susceptible to inflammatory stimuli. Concurrently, direct air contact and the lipid-rich nature of the tear film promote oxidative processes, further exacerbated by inflammation-induced oxidative stress. PPI network analysis and differential gene expression profiling jointly identified aberrant interactions among core spliceosomal proteins (e.g., SNRNP70, SF3B1), suggesting that dysregulated alternative splicing may impair the production of stress-related isoforms, including members of the heat shock protein (HSP) family\u003csup\u003e\u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. This splicing dysfunction may intensify oxidative damage in meibomian gland epithelial cells. Moreover, the observed downregulation of WFS1\u0026mdash;a marker of endoplasmic reticulum stress\u0026mdash;in the heatmap may reflect insufficient compensatory response within this module\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e, further contributing to glandular vulnerability. MCODE_1-identified PPAR signaling plays a multifaceted role in MGD pathogenesis by regulating lipid metabolism-related genes (e.g., MGST2), promoting ductal hyperkeratinization through SPRR2A overexpression (linked to MCODE_3)\u003csup\u003e48,49\u003c/sup\u003e, and impairing anti-inflammatory responses via diminished NF-κB inhibition, thereby sustaining inflammation through MAPK pathway crosstalk. Simultaneously, the PI3K-AKT pathway contributes to disease progression. Significant downregulation of DERL2 and upregulation of MGST2 (involved in glutathione metabolism) suppress cell survival\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e, reduce anti-apoptotic proteins (e.g., Bcl-2), and promote acinar gland cell apoptosis via the mitochondrial pathway. Decreased AKT-mediated phosphorylation of Nrf2 compromises the expression of antioxidant enzymes (e.g., SOD, CAT), exacerbating redox imbalance and promoting lipid peroxidation\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e,\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e, thereby disrupting meibum composition and vesicular transport (MCODE_9). In parallel, hypoxia and oxidative stress in MGD tissues activate the HIF-1 signaling axis\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e, with aberrant expression of its target gene VEGFA linked to the hypoxia-induced contractile dysfunction identified in MCODE_10. The hypoxic microenvironment aggravates ductal obstruction and hyperkeratinization (MCODE_3), while HIF-1α-driven VEGF upregulation promotes angiogenesis, potentially leading to abnormal vascular permeability. Furthermore, HIF-1 induces upregulation of GLUT1 and lactate dehydrogenase\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e, shifting glandular metabolism toward anaerobic glycolysis, which intensifies local acidosis and inflammatory damage.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":" \u003cp\u003eThis study elucidates the molecular underpinnings of MGD through integrated high-resolution lipidomics and transcriptomic clustering analyses, identifying key contributors to tear film instability and disease pathogenesis. Our findings demonstrate a distinct shift in meibum composition in MGD, characterized by an increase in long-chain neutral lipids (e.g., cholesteryl esters) and a concomitant depletion of short-chain ceramides and hydroxylated/glycosylated species. These compositional changes enhance the hydrophobicity and viscosity of meibum, promoting glandular obstruction and compromising tear film integrity. In contrast, the presence of short-chain and structurally modified lipids in healthy meibum facilitates solubility and protein interaction, preserving tear film homeostasis. Transcriptomic profiling further highlights lipid differentiation defects, ductal dysfunction, and oxidative-inflammatory stress as central drivers of MGD. Pathway enrichment analyses underscore dysregulation of PPARγ signaling and aberrant activation of PI3K-Akt, MAPK, and cytokine-mediated pathways, contributing to disrupted lipid metabolism, mitochondrial impairment, endoplasmic reticulum stress, and oxidative-inflammatory cascades. Epigenetic regulation by the MLL3/MLL4 complex and dysregulated fibroblast growth factor receptor (FGFR) signaling further emphasize the multifactorial nature of MGD progression. Additionally, pathways involved in keratinization (e.g., FLG, KRT1) and impaired SNARE-dependent vesicular transport (e.g., VAMP8, SNAP25) are closely associated with ductal occlusion and secretory failure. Collectively, these findings delineate a lipid\u0026ndash;enzyme\u0026ndash;gene regulatory network, offering a framework for precision-targeted interventions aimed at lipid metabolism, glandular regeneration, and oxidative-inflammatory crosstalk. Future research could focus on validating these therapeutic targets in preclinical models and exploring individualized strategies to restore meibum composition and gland function, thereby improving tear film stability and mitigating ocular surface damage.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMGD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMeibomian gland dysfunction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePPARG (γ)\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePeroxisome proliferator-activated receptorγ\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePPI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProtein-protein Interaction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLC-MS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLiquid Chromatography\u0026ndash;Mass Spectrometry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHRMS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHigh-resolution mass spectrometry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ewax esters\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTriacylglycerols\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003echolesteryl esters\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCer\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCeramides\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCAR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAcylcarnitines\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNAE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eN-acylethanolamines\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehydroxy fatty acids\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMonoacylglycerol\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLPC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLysophosphatidylcholines\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePhosphatidylinositols\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePI-Cer\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePhosphatidylinositol ceramide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSPB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSphingoid base\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHexCer\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHexosylceramide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eST\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSulfatide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMGDG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMonogalactosyldiacylglycerol\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLPS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLipopolysaccharide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMIPC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMannosylinositol phosphorylceramide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFFA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFree fatty acids\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFOH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFatty alcohols\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNAT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eN-acyltransferase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLOX\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLipoxygenase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOX\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCyclooxygenase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMLL4/3\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMixed-lineage leukemia 4/3\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePID\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePrimary immunodeficiency\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eE2F\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTranscription factor E2F\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFGFR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFibroblast growth factor receptor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSNARE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSoluble N-ethylmaleimide-sensitive factor attachment protein receptor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKRT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKeratin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFLG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFilaggrin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIVL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInvolucrin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIL-22\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterleukin-22\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSTAT3\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSignal transducer and activator of transcription 3\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMAPK\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMitogen-activated protein kinase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePI3K-AKT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePhosphoinositide 3-kinase-AKT signaling pathway\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSPCS1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSignal peptidase complex subunit 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSNRNP70\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSmall nuclear ribonucleoprotein U1 subunit 70\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSF3B1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSplicing factor 3b subunit 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWFS1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWolfram syndrome 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMGST2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMicrosomal glutathione S-transferase 2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSPRR2A\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSmall proline-rich protein 2A\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDERL2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDerlin 2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAKT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProtein kinase B\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSOD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSuperoxide dismutase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCAT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCatalase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHIF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHypoxia-inducible factor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVEGFA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVascular endothelial growth factor A\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the principles of the Declaration of Helsinki. Ethical approval was obtained from the Institutional Review Board (IRB) of Southern Medical University.Written informed consent was obtained from all participants (or their legal guardians) prior to inclusion in the study.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent was obtained from the patient for study and publication\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw sequencing data have been uploaded along with the manuscript as supplementary files. The datasets used during the current study are available from the corresponding author on reasonable request.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors report no conflicts of interest.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the President Foundation of Nanfang Hospital, Southern Medical University (Youth Project, Grant No. 2024B053).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ.Zhu, L.Liu , K.Ren and P.Zhu collect and perform the meibum sample, then process lipidomics and GEO analysis. J. Zhu and wrote the text of the man manuscript and prepared Fig 1,2,3,4 and Table 1,2,3,4. L. Bai and M.Chen revised the manuscript and gave specialized academic guidance. All authors reviewed the manuscript. All authors read and approved the final manuscript.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe sincerely appreciate all the participants for their time and valuable insights contributed to this article. Our gratitude extends to Meliomics for their expert technical guidance and assistance with sample testing. We also thank NCBI, STRING, and other open-source databases for their data support, as well as HSBC engineer Peter Wan for his assistance with code development.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePapas EB. The global prevalence of dry eye disease: A Bayesian view. Ophthalmic physiological optics: J Br Coll Ophthalmic Opticians (Optometrists). 2021;41(6):1254\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDry Eye. New EnglanDjournal Med, 378(23), 2212\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcCann P, Abraham AG, Mukhopadhyay A, Panagiotopoulou K, Chen H, Rittiphairoj T, Gregory DG, Hauswirth SG, Ifantides C, Qureshi R, Liu SH, Saldanha IJ, Li T. Prevalence and Incidence of Dry Eye and Meibomian Gland Dysfunction in the United States: A Systematic Review and Meta-analysis. JAMA Ophthalmol. 2022;140(12):1181\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eButovich IA. Meibomian glands, meibum, anDmeibogenesis. Exp Eye Res. 2017;163:2\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu J, Liu L, Wu J, Bai L. Rodent models for dry eye syndrome (DES). Contact lens \u0026amp; anterior eye: the. J Br Contact Lens Association. 2025;48(3):102383.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHa M, Oh SE, Whang WJ, Na KS, Kim EC, Kim HS, Kim JS, Hwang HS. Relationship between meibomian gland loss in infrared meibography and meibum quality in dry eye patients. BMC Ophthalmol. 2022;22(1):292.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao W, Yang J, Liao Y, Yang B, Lin S, Liu R, Liang L. Alteration of Meibum Lipidomics Profiling in Patients With Chronic Ocular Graft-Versus-Host Disease. Investig Ophthalmol Vis Sci. 2023;64(12):35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhanna RK, Catanese S, Emond P, Corcia P, Blasco H, Pisella PJ. Metabolomics and lipidomics approaches in human tears: A systematic review. Surv Ophthalmol. 2022;67(4):1229\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eButovich IA, Uchiyama E, Di Pascuale MA, McCulley JP. Liquid chromatography-mass spectrometric analysis of lipids present in human meibomian gland secretions. Lipids. 2007;42(8):765\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHan X, Gross RW. The foundations and development of lipidomics. J Lipid Res. 2022;63(2):100164.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao H, Wu SN, Shao Y, Xiao D, Tang LY, Cheng Z, Peng J. Lipidomics Profiles Revealed Alterations in Patients With Meibomian Gland Dysfunction After Exposure to Intense Pulsed Light. Front Neurol. 2022;13:827544.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarcia-Queiruga J, Pena-Verdeal H, Sabucedo-Villamarin B, Paz-Tarrio M, Guitian-Fernandez E, Garcia-Resua C, Yebra-Pimentel E, Giraldez MJ. Meibum Lipidomic Analysis in Evaporative Dry Eye Subjects. Int J Mol Sci. 2024;25(9):4782.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eContrepois K, Mahmoudi S, Ubhi BK, Papsdorf K, Hornburg D, Brunet A, Snyder M. Cross-Platform Comparison of Untargeted and Targeted Lipidomics Approaches on Aging Mouse Plasma. Sci Rep. 2018;8(1):17747.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSethi S, Hayashi MA, Sussulini A, Tasic L, Brietzke E. Analytical approaches for lipidomics and its potential applications in neuropsychiatric disorders. world J Biol psychiatry: official J World Federation Soc Biol Psychiatry. 2017;18(7):506\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoodyear MD, Krleza-Jeric K, Lemmens T. The Declaration of Helsinki. BMJ. 2007;335(7621):624\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChinese Branch of the Asian Dry Eye Society; Ocular Surface and Tear Film Diseases Group of Ophthalmology Committee of Cross\u0026ndash;Straits Medicine Exchange Association. Ocular Surface and Dry Eye Group of Chinese Ophthalmologist Association. Zhonghua Yan Ke Za Zhi. 2023;59(11):880\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFOLCH J, LEES M, SLOANE, STANLEY GH. A simple method for the isolation and purification of total lipides from animal tissues. J Biol Chem. 1957;226(1):497\u0026ndash;509.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMopuri R, Kalyesubula M, Rosov A, Edery N, Moallem U, Dvir H. Improved Folch Method for Liver-Fat Quantification. Front Vet Sci. 2021;7:594853. Published 2021 Jan 12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatyash V, Liebisch G, Kurzchalia TV, Shevchenko A, Schwudke D. Lipid extraction by methyl-tert-butyl ether for high-throughput lipidomics. J Lipid Res. 2008;49(5):1137\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiebisch G, Fahy E, Aoki J, et al. Update on LIPID MAPS classification, nomenclature, and shorthand notation for MS-derived lipid structures. J Lipid Res. 2020;61(12):1539\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu S, Richards SM, Lo K, Hatton M, Fay A, Sullivan DA. Changes in gene expression in human meibomian gland dysfunction. Invest Ophthalmol Vis Sci. 2011;52(5):2727\u0026ndash;40. Published 2011 Apr 25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarrett T, Wilhite SE, Ledoux P, et al. NCBI GEO: archive for functional genomics data sets\u0026ndash;update. Nucleic Acids Res. 2013;41(Database issue):D991\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/nar/gks1193\u003c/span\u003e\u003cspan address=\"10.1093/nar/gks1193\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28(1):27\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498\u0026ndash;504.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDoncheva NT, Morris JH, Gorodkin J, Jensen LJ. Cytoscape StringApp: Network Analysis and Visualization of Proteomics Data. J Proteome Res. 2019;18(2):623\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSteensels S, Ersoy BA. Fatty acid activation in thermogenic adipose tissue. Biochim Biophys Acta Mol Cell Biol Lipids. 2019;1864(1):79\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYao H, Ye J. Long chain acyl-CoA synthetase 3-mediated phosphatidylcholine synthesis is required for assembly of very low density lipoproteins in human hepatoma Huh7 cells. J Biol Chem. 2008;283(2):849\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDeo PN, Deshmukh R. Pathophysiology of keratinization. J Oral Maxillofac Pathol. 2018;22(1):86\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShetty S, Gokul S. Keratinization and its disorders. Oman Med J. 2012;27(5):348\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark Y, Jung J, Jeong S, et al. Reversine enhances skin barrier functions by suppressing the IL-4- and IL-13-mediated STAT6 pathway. J Dermatol Sci. 2023;111(2):71\u0026ndash;3.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSong Qian H, Xue Q, Mengbin, et al. STAT3 pathway is involved in interleukin-22 promoting expression of tight junction protein in human colorectal cancer cell line HT29[J]. Basic Clin Med. 2021;41(6):792\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKatoh M, Nakagama H. FGF receptors: cancer biology and therapeutics. Med Res Rev. 2014;34(2):280\u0026ndash;300.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDiPeri TP, Zhao M, Evans KW, et al. Convergent MAPK pathway alterations mediate acquired resistance to FGFR inhibitors in FGFR2 fusion-positive cholangiocarcinoma. J Hepatol. 2024;80(2):322\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHo BB, Bergwitz C. FGF23 signalling and physiology. J Mol Endocrinol. 2021;66(2):R23\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdeeb N, Mortazavi MM. The role of FGF2 in spinal cord trauma and regeneration research. Brain Behav.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYoon TY, Munson M. SNARE complex assembly and disassembly. Curr Biol. 2018;28(8):R397\u0026ndash;401.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWesolowski J, Paumet F. Escherichia coli exposure inhibits exocytic SNARE-mediated membrane fusion in mast cells. Traffic. 2014;15(5):516\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuzuki R, Matsuda M, Watashi K, et al. Signal peptidase complex subunit 1 participates in the assembly of hepatitis C virus through an interaction with E2 and NS2. PLoS Pathog. 2013;9(8):e1003589.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGao Y, Jian L, Lu W, Xue Y, Machaty Z, Luo H. Vitamin E can promote spermatogenesis by regulating the expression of proteins associated with the plasma membranes and protamine biosynthesis. Gene. 2021;773:145364.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLangemeyer L, Fr\u0026ouml;hlich F, Ungermann C. Rab GTPase Function in Endosome and Lysosome Biogenesis. Trends Cell Biol. 2018;28(11):957\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePfeffer SR. Rab GTPases: master regulators that establish the secretory and endocytic pathways. Mol Biol Cell. 2017;28(6):712\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFichna JP, Maruszak A, Żekanowski C. Myofibrillar myopathy in the genomic context. J Appl Genet. 2018;59(4):431\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLossos A, Oldfors A, Fellig Y, Meiner V, Argov Z, Tajsharghi H. MYH2 mutation in recessive myopathy with external ophthalmoplegia linked to chromosome 17p13.1-p12. Brain. 2013;136(Pt 7):e238.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAubol BE, Wozniak JM, Fattet L, Gonzalez DJ, Adams JA. CLK1 reorganizes the splicing factor U1-70K for early spliceosomal protein assembly. Proc Natl Acad Sci U S A. 2021;118(14):e2018251118.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMacri C, Wang F, Tasset I, et al. Modulation of deregulated chaperone-mediated autophagy by a phosphopeptide. Autophagy. 2015;11(3):472\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGama-Brambila RA, Chen J, Zhou J, Tascher G, M\u0026uuml;nch C, Cheng X. A PROTAC targets splicing factor 3B1. Cell Chem Biol. 2021;28(11):1616\u0026ndash;e16278.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhanim F, Kirk J, Latif F, Barrett TG. WFS1/wolframin mutations, Wolfram syndrome, and associated diseases. Hum Mutat.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFischer DF, van Drunen CM, Winkler GS, van de Putte P, Backendorf C. Involvement of a nuclear matrix association region in the regulation of the SPRR2A keratinocyte terminal differentiation marker. Nucleic Acids Res. 1998;26(23):5288\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThulasingam M, Orellana L, Nji E, Ahmad S, Rinaldo-Matthis A, Haeggstr\u0026ouml;m JZ. Crystal structures of human MGST2 reveal synchronized conformational changes regulating catalysis. Nat Commun. 2021;12(1):1728. Published 2021 Mar 19.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEshraghi A, Dixon SD, et al. Cytolethal distending toxins require components of the ER-associated degradation pathway for host cell entry. PLoS Pathog. 2014;10(7):e1004295. Published 2014 Jul 31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMitsuishi Y, Taguchi K, Kawatani Y, et al. Nrf2 redirects glucose and glutamine into anabolic pathways in metabolic reprogramming. Cancer Cell. 2012;22(1):66\u0026ndash;79.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang B, Zeng M, Li B, et al. Arbutin attenuates LPS-induced acute kidney injury by inhibiting inflammation and apoptosis via the PI3K/Akt/Nrf2 pathway. Phytomedicine. 2021;82:153466.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBalamurugan K. HIF-1 at the crossroads of hypoxia, inflammation, and cancer. Int J Cancer. 2016;138(5):1058\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang P, Zhou YD, Tan Y, Gao L. Protective effects of piperine on the retina of mice with streptozotocin-induced diabetes by suppressing HIF-1/VEGFA pathway and promoting PEDF expression. Int J Ophthalmol. 2021;14(5):656\u0026ndash;65. Published 2021 May 18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerrer CM, Lynch TP, Sodi VL, et al. O-GlcNAcylation regulates cancer metabolism and survival stress signaling via regulation of the HIF-1 pathway. Mol Cell. 2014;54(5):820\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-ophthalmology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"boph","sideBox":"Learn more about [BMC Ophthalmology](http://bmcophthalmol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/boph","title":"BMC Ophthalmology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"meibum, meibomian gland dysfunction (MGD), high-fidelity lipidomics, lipid layer pattern, cluster analysis, Protein-Protein Interaction (PPI)","lastPublishedDoi":"10.21203/rs.3.rs-9303325/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9303325/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMeibomian gland dysfunction (MGD) is the leading cause of evaporative dry eye and is characterized by gland obstruction, lipid imbalance, and tear film instability. While inflammatory mechanisms have been extensively studied, the molecular composition of meibum and its regulatory networks remain incompletely understood.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eHigh-fidelity lipidomic profiling of meibum from MGD patients (n\u0026thinsp;=\u0026thinsp;4) and healthy controls (n\u0026thinsp;=\u0026thinsp;4) was performed using Q-TOF UPLC-MS with four-dimensional identification. Transcriptomic data from normal (n\u0026thinsp;=\u0026thinsp;6) and MGD-affected (n\u0026thinsp;=\u0026thinsp;6) meibomian glands were analyzed using GO, KEGG, and protein\u0026ndash;protein interaction network analyses. Integrated lipid\u0026ndash;enzyme\u0026ndash;gene co-clustering was applied to construct regulatory networks.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eMGD samples showed enrichment of long-chain and neutral lipids, particularly cholesteryl esters, whereas controls displayed higher levels of short-chain ceramides and fatty acids. Dysregulated lipid species were enriched in structurally modified sphingolipids. Transcriptomic analysis revealed involvement of PI3K-Akt, MAPK, cytokine signaling, and extracellular matrix remodeling, together with altered transcriptional regulation and membrane transport.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eExcess long-chain neutral lipids increase tear film viscosity and promote ductal obstruction, while short-chain and modified lipids support tear film stability. Coordinated disruption of lipid metabolism, cytoskeletal dynamics, and cellular homeostasis drives progressive gland dysfunction and chronic ocular surface damage in MGD.\u003c/p\u003e","manuscriptTitle":"High-Fidelity Lipidomics Co-Clustering Analysis Reveals Critical Lipid Metabolic Crux and Mechanisms in Meibomian Gland Dysfunction (MGD)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-23 12:40:58","doi":"10.21203/rs.3.rs-9303325/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-18T08:25:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"133166703364545797008739395778411352701","date":"2026-04-18T11:33:44+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-16T06:22:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-07T07:30:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-07T07:18:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Ophthalmology","date":"2026-04-07T06:43:54+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-ophthalmology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"boph","sideBox":"Learn more about [BMC Ophthalmology](http://bmcophthalmol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/boph","title":"BMC Ophthalmology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b29167b1-6a99-4c23-b5b1-8c890091ef84","owner":[],"postedDate":"April 23rd, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-18T08:25:48+00:00","index":16,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-23T12:40:59+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-23 12:40:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9303325","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9303325","identity":"rs-9303325","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}