Lipid identification and annotation were performed using LipidSearch software (Thermo Fisher Scientific) by matching against the LipidSearch database. Identification parameters included a precursor mass tolerance of 5 ppm and a product mass tolerance of 5 ppm. Qualitative and quantitative information for each lipid species was obtained. For visualization and downstream analysis, volcano plots were generated using the R package ggplot2, integrating VIP value, log2(Fold Change), and -log10(p-value). Clustering heatmaps were generated using the R package pheatmap with z-score normalization. Correlation analysis of differential metabolites was performed using Pearson's correlation coefficient with the R function cor(), and statistical significance (p-value < 0.05) was assessed using cor.mtest(). Correlation plots were generated using the R package corrplot.
Chromatographic separation was performed using a Thermo Vanquish UHPLC system coupled with a Thermo Accucore C30 column (150 mm × 2.1 mm, 2.6 μm particle size, Thermo Fisher Scientific). The column oven temperature was maintained at 40°C. The flow rate was set at 0.35 mL/min, and the injection volume was 5 μL. The mobile phase consisted of solvent A (acetonitrile/water, 60:40, v/v) containing 0.1% formic acid and 10 mM ammonium acetate, and solvent B (isopropanol/acetonitrile, 90:10, v/v) containing 0.1% formic acid and 10 mM ammonium acetate. The gradient elution program was as follows: 0 min (70% A, 30% B), 2 min (70% A, 30% B), 5 min (57% A, 43% B), 5.1 min (45% A, 55% B), 11 min (30% A, 70% B), 16 min (1% A, 99% B), 18 min (1% A, 99% B), 18.1 min (70% A, 30% B), and 20 min (70% A, 30% B) for column re-equilibration.
"],"publication":["Tear lipidomics profiling reveals inflammatory dry eye disease-associated lipid metabolic remodeling at the ocular surface."],"submitter_affiliation":["âSichuan Academy of Medical Sciences â Sichuan Provincial People's Hospital"],"submitter_name":["Wangyi Yang"],"organism_part":["tear"],"technology_type":["mass spectrometry assay"],"disease":[""],"extraction_protocol":["Lipids were extracted from tear samples collected on Schirmer strips. Each Schirmer strip containing tear fluid was placed into a glass centrifuge tube with a PTFE-lined cap, followed by the addition of 0.75 mL of pre-cooled methanol and vortexing. Then, 2.5 mL of pre-cooled methyl tert-butyl ether (MTBE) was added, and the mixture was incubated at room temperature for 1 hour on an orbital shaker. To induce phase separation, 0.625 mL of LC-MS grade water was added, and after vortexing and incubation at room temperature for 10 minutes, the mixture was centrifuged at 1000 × g for 10 minutes. The upper organic phase (MTBE) was collected, and a second extraction was performed on the lower phase using 1 mL of a solvent mixture (MTBE/methanol/water, 10:3:2.5, v/v/v), with the upper organic phase collected again after centrifugation. The combined organic phases were dried under a gentle stream of nitrogen, and the dried lipid extract was reconstituted in 100 μL of isopropanol for subsequent LC-MS/MS analysis. For quality control (QC) samples, an equal volume of supernatant from each processed sample was pooled and mixed thoroughly, and QC samples were analyzed periodically throughout the LC-MS/MS run to monitor system stability and reproducibility. For blank samples, a clean Schirmer strip (without tear collection) was processed using the same extraction procedure as described above, and the blank extract was analyzed to assess background contamination and enable background subtraction during data processing.
"],"organism":["Home sapiens"],"data_transformation_protocol":["Raw data files (.raw) were processed using LipidSearch software (Thermo Fisher Scientific). Peak picking was performed by matching against the LipidSearch database with a precursor mass tolerance of 5 ppm and a product mass tolerance of 5 ppm. Peak alignment across samples was conducted using a retention time tolerance of 0.05 minutes and a signal-to-noise ratio threshold of 3. Blank samples were used to remove background ions. Quantitative results were normalized. For multivariate statistical analysis, data were transformed using the metaX software package. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed to calculate variable importance in projection (VIP) values. For univariate analysis, Student's t-test was used to calculate p-values, and fold change (FC) was calculated for each metabolite between groups (DED vs. control). Differential metabolites were selected based on criteria of VIP > 1, p-value < 0.05, and FC ≥ 2 or FC ≤ 0.5.
"],"study_factor":["Disease status"],"submitter_email":["yangwangyi06032000@163.com"],"metabolights_link":["https://www.ebi.ac.uk/metabolights/MTBLS14218"],"sample_collection_protocol":["Tear samples were collected from participants using Schirmer test strips. Participants were instructed to look upward, and the pre-sterilized Schirmer strip with a rounded end was gently placed at the junction of the outer 1/3 of the lower eyelid and the conjunctival sac, while the other end of the strip was left hanging outside the eyelid. Participants were asked to close their eyes gently during the collection period. Tears were collected for 5 minutes. After collection, the Schirmer strip was immediately placed into a 1.5 mL microcentrifuge tube, snap-frozen in liquid nitrogen for 15 minutes, and subsequently stored at -80°C until shipment. Samples were shipped on sufficient dry ice to the analytical facility.
"],"omics_type":["Metabolomics"],"study_design":["untargeted analysis","LipidSearch","Lipidomics","electrospray ionization","data-dependent acquisition","pooled sample","Thermo Scientific Vanquish UHPLC System","R","tear","Frozen tissue","dry eye syndrome","liquid chromatography-tandem mass spectrometry","Home sapiens","Thermo Scientific Q Exactive HF","Q Exactive HF","metaX"],"curator_keywords":["untargeted analysis","LipidSearch","Lipidomics","electrospray ionization","data-dependent acquisition","pooled sample","Thermo Scientific Vanquish UHPLC System","R","tear","Frozen tissue","dry eye syndrome","liquid chromatography-tandem mass spectrometry","Home sapiens","metaX","Thermo Scientific Q Exactive HF","Q Exactive HF"],"mass_spectrometry_protocol":["Mass spectrometry analysis was performed using a Thermo Q Exactive HF or Q Exactive HF-X mass spectrometer (Thermo Fisher Scientific) coupled with a heated electrospray ionization (HESI) source. Data were acquired in both positive and negative ion modes separately.
The ion source parameters were set as follows: sheath gas pressure at 40 psi, sweep gas flow at 0 L/min, auxiliary gas flow rate at 10 L/min for positive mode and 7 L/min for negative mode, spray voltage at 3.5 kV, capillary temperature at 320°C, heater temperature at 350°C, and S-Lens RF level at 50.
Full MS scans were acquired over a mass range of 114–1700 m/z. The automatic gain control (AGC) target was set at 3e6 ions with a maximum injection time of 100 ms. For data-dependent acquisition (DDA) of MS/MS spectra, the AGC target was set at 2e5 ions, the isolation window was 1 m/z, and the normalized collision energy (NCE) was stepped at 22 eV, 24 eV, and 28 eV for both positive and negative ion modes. Dynamic exclusion was set to 6 seconds.
"],"additional_accession":[]},"is_claimable":false,"name":"Tear lipidomics profiling reveals inflammatory dry eye disease-associated lipid metabolic remodeling at the ocular surface","description":"This study aimed to investigate whether inflammatory dry eye disease (DED) is accompanied by abnormal lipid metabolic remodeling at the ocular surface. Tear samples were collected from patients with DED and matched healthy controls. Lipidomics profiling was performed using LC–MS/MS with a standardized acquisition and computational analysis workflow. Global non-targeted metabolomic analysis revealed extensive alterations in tear lipid composition in the DED group relative to controls. Multivariate statistical modeling, including principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA), demonstrated clear separation between DED and control cohorts, confirming a distinct metabolic phenotype in DED. Unsupervised hierarchical clustering further identified a reproducible disease-specific lipidomic signature. Significantly dysregulated metabolites included multiple lipid classes, particularly sphingolipids, phosphatidylcholines (PCs), and lysophospholipids. Mechanistically, differentially regulated lipid species converged on coordinated functional modules governing ER–mitochondria lipid crosstalk, including MAM-dependent phospholipid flux (PC/PE/PI/PS), neutral lipid buffering (TG/DG), and sphingolipid inflammatory gating (Cer/SM). Pathway enrichment analysis showed that lipids elevated in DED samples were predominantly associated with lipid metabolism and sphingolipid metabolism pathways. This dataset provides a comprehensive resource for understanding lipid metabolic reprogramming at the ocular surface in inflammatory dry eye disease.","dates":{"publication":"2026-04-03","submission":"2026-04-03"},"accession":"MTBLS14218","cross_references":{}}