Comprehensive mass spectrometry lipidomics of human biofluids and ocular tissues

**Background:** Lipids are critical for cell membrane structure, energy storage, and signaling, and they constitute about 30% of human body weight. The retina, as an extension of the nervous system, is particularly rich in glycerophospholipids, polyunsaturated fatty acids (especially docosahexaenoic acid), and sphingolipids. Disruption of retinal lipid homeostasis is implicated in age-related macular degeneration (AMD), the leading cause of vision loss in Western countries. Lipid-containing deposits called drusen accumulate beneath the retinal pigment epithelium (RPE), triggering inflammation and photoreceptor degeneration. Previous studies have linked specific lipid metabolites (e.g., ceramides, sphingosine-1-phosphate) to photoreceptor survival or death, and plasma lipidomic profiles differ between AMD patients and controls. However, comprehensive lipidomic analysis of both ocular tissues and biofluids using complementary chromatographic methods has been lacking. This study aimed to develop and validate a dual hydrophilic interaction liquid chromatography (HILIC) and reversed-phase chromatography (RPC) approach coupled to high-resolution mass spectrometry (HRMS) for broad lipid coverage in human retina, RPE/choroid, erythrocytes, and plasma.

**Methods:** Tissues and biofluids were obtained from ten healthy human donors (3 females, 7 males; median age 87.5 years, range 77–97 years; median postmortem delay 12.5 h, range 3–24 h). Lipids were extracted from retina and RPE/choroid using Folch's procedure, and from plasma and erythrocytes using the Moilanen and Nikkari method. Samples were spiked with a mixture of 14 internal standards representing different lipid classes. Lipid extracts were analyzed by both HILIC (10 min run time) and RPC (17 min run time) on an Orbitrap Fusion Tribrid mass spectrometer in positive and negative ionization modes. MS² scans were used for lipid annotation via LipidSearch software and manual spectral elucidation. Relative quantification was performed using MS full scan data processed in R. Quality control samples were injected every ten samples.

**Key Results:** The combined approach enabled annotation of 15 lipid classes and approximately 500 lipid species across all sample types. Lipid classes detected included phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylserine (PS), phosphatidylinositol (PI), phosphatidylglycerol (PG), lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), ceramide (Cer), hexosylceramide (HexCer), dihexosylceramide (Hex2Cer), sphingomyelin (SM), free fatty acids (FFA), cholesteryl esters (CE), triglycerides (TAG), diglycerides (DAG), and cholesterol (Chol). Neutral lipids (CE, TAG, Chol, DAG) were detected only by RPC, while very long chain polyunsaturated fatty acid-containing PC (VLC-PC) were uniquely found in retina by both methods. HILIC provided superior separation of glycerophospholipids and sphingolipids, resolving isobaric species (e.g., PE vs. PC, LPE vs. LPC) that coeluted in RPC. For example, in HILIC, PE eluted at RT 2–2.7 min and PC at RT 3–4 min, whereas in RPC they coeluted at RT 4.5–9 min. Relative lipid class distributions varied between tissues: in RPC positive mode, the mean relative intensity of PE+PC was 37.24% ± 6.59%, LPE+LPC 26.42% ± 10.34%, PS 0.12% ± 0.06%, Cer 12.53% ± 5.38%, HexCer 6.75% ± 7.95%, Hex2Cer 1.78% ± 1.23%, and SM 15.17% ± 3.91%. In HILIC positive mode, PE+PC was 46.48% ± 14.51%, LPE+LPC 14.78% ± 3.36%, PS 0.79% ± 0.34%, Cer 0.92% ± 0.56%, HexCer 0.29% ± 0.27%, Hex2Cer 2.32% ± 1.44%, and SM 9.77% ± 3.44%. Notably, subject 10 showed elevated HexCer in retina, and subject 6 showed higher LPC in RPE/choroid and higher FFA in HILIC negative mode, suggesting possible metabolic dysregulation or sample handling effects.

**Clinical Implications:** This study provides a validated, comprehensive lipidomic workflow applicable to both ocular tissues and systemic biofluids, which is essential for understanding lipid metabolism in retinal diseases like AMD. The complementary use of HILIC and RPC overcomes limitations of single-method approaches: HILIC is preferred for analyzing glycerophospholipids and sphingolipids in retina and RPE, while RPC is necessary for neutral lipids abundant in plasma. The identification of VLC-PC exclusively in retina underscores their potential role in retinal health. The observed inter-subject variability in sphingolipid classes (e.g., HexCer) warrants further investigation into their involvement in retinal degeneration. This methodological framework can be applied to future case-control studies to identify lipid biomarkers and therapeutic targets for AMD and other retinal disorders.