Lipidomics from sample preparation to data analysis: a primer

Coupling Machine Learning and Lipidomics as a Tool to Investigate Metabolic Dysfunction-Associated Fatty Liver Disease. A General Overview

Hepatic biopsy is the gold standard for staging nonalcoholic fatty liver disease (NAFLD). Unfortunately, accessing the liver is invasive, requires a multidisciplinary team and is too expensive to be conducted on large segments of the population. NAFLD starts quietly and can progress until liver damage is irreversible. Given this complex situation, the search for noninvasive alternatives is clinically important. A hallmark of NAFLD progression is the dysregulation in lipid metabolism. In this context, recent advances in the area of machine learning have increased the interest in evaluating whether multi-omics data analysis performed on peripheral blood can enhance human interpretation. In the present review, we show how the use of machine learning can identify sets of lipids as predictive biomarkers of NAFLD progression. This approach could potentially help clinicians to improve the diagnosis accuracy and predict the future risk of the disease. While NAFLD has no effective treatment yet, the key to slowing the progression of the disease may lie in predictive robust biomarkers. Hence, to detect this disease as soon as possible, the use of computational science can help us to make a more accurate and reliable diagnosis. We aimed to provide a general overview for all readers interested in implementing these methods.

Lipidomics Provides New Insight into Pathogenesis and Therapeutic Targets of the Ischemia-Reperfusion Injury

Lipids play an essential role in both tissue protection and damage. Tissue ischemia creates anaerobic conditions in which enzyme inactivation occurs, and reperfusion can initiate oxidative stress that leads to harmful changes in membrane lipids, the formation of aldehydes, and chain damage until cell death. The critical event in such a series of harmful events in the cell is the unwanted accumulation of fatty acids that leads to lipotoxicity. Lipid analysis provides additional insight into the pathogenesis of ischemia/reperfusion (I/R) disorders and reveals new targets for drug action. The profile of changes in the composition of fatty acids in the cell, as well as the time course of these changes, indicate both the mechanism of damage and new therapeutic possibilities. A therapeutic approach to reperfusion lipotoxicity involves attenuation of fatty acids overload, i.e., their transport to adipose tissue and/or inhibition of the adverse effects of fatty acids on cell damage and death. The latter option involves using PPAR agonists and drugs that modulate the transport of fatty acids via carnitine into the interior of the mitochondria or the redirection of long-chain fatty acids to peroxisomes.

Integrating lipidomics and genomics: emerging tools to understand cardiovascular diseases

Cardiovascular diseases (CVDs) are the leading cause of mortality and morbidity worldwide leading to 31% of all global deaths. Early prediction and prevention could greatly reduce the enormous socio-economic burden posed by CVDs. Plasma lipids have been at the center stage of the prediction and prevention strategies for CVDs that have mostly relied on traditional lipids (total cholesterol, total triglycerides, HDL-C and LDL-C). The tremendous advancement in the field of lipidomics in last two decades has facilitated the research efforts to unravel the metabolic dysregulation in CVDs and their genetic determinants, enabling the understanding of pathophysiological mechanisms and identification of predictive biomarkers, beyond traditional lipids. This review presents an overview of the application of lipidomics in epidemiological and genetic studies and their contributions to the current understanding of the field. We review findings of these studies and discuss examples that demonstrates the potential of lipidomics in revealing new biology not captured by traditional lipids and lipoprotein measurements. The promising findings from these studies have raised new opportunities in the fields of personalized and predictive medicine for CVDs. The review further discusses prospects of integrating emerging genomics tools with the high-dimensional lipidome to move forward from the statistical associations towards biological understanding, therapeutic target development and risk prediction. We believe that integrating genomics with lipidome holds a great potential but further advancements in statistical and computational tools are needed to handle the high-dimensional and correlated lipidome.

Comparison of lipidome profiles of Caenorhabditis elegans-results from an inter-laboratory ring trial

INTRODUCTION

Lipidomic profiling allows 100s if not 1000s of lipids in a sample to be detected and quantified. Modern lipidomics techniques are ultra-sensitive assays that enable the discovery of novel biomarkers in a variety of fields and provide new insight in mechanistic investigations. Despite much progress in lipidomics, there remains, as for all high throughput "omics" strategies, the need to develop strategies to standardize and integrate quality control into studies in order to enhance robustness, reproducibility, and usability of studies within specific fields and beyond.

OBJECTIVES

We aimed to understand how much results from lipid profiling in the model organism Caenorhabditis elegans are influenced by different culture conditions in different laboratories.

METHODS

In this work we have undertaken an inter-laboratory study, comparing the lipid profiles of N2 wild type C. elegans and daf-2(e1370) mutants lacking a functional insulin receptor. Sample were collected from worms grown in four separate laboratories under standardized growth conditions. We used an UPLC-UHR-ToF-MS system allowing chromatographic separation before MS analysis.

RESULTS

We found common qualitative changes in several marker lipids in samples from the individual laboratories. On the other hand, even in this controlled experimental system, the exact fold-changes for each marker varied between laboratories.

CONCLUSION

Our results thus reveal a serious limitation to the reproducibility of current lipid profiling experiments and reveal challenges to the integration of such data from different laboratories.

The use of molecular markers in the verification of fish and seafood authenticity and the detection of adulteration

The verification of authenticity and detection of food mislabeling are elements that have been of high importance for centuries. During the last few decades there has been an increasing consumer demand for the verification of food identity and the implementation of stricter controls around these matters. Fish and seafood are among the most easily adulterated foodstuffs mainly due to the significant alterations of the species' morphological characteristics that occur during the different types of processing, which render the visual identification of the animals impossible. Even simple processes, such as filleting remove very important morphological elements and suffice to prevent the visual identification of species in marketed products. Novel techniques have therefore been developed that allow identification of species, the differentiation between species and also the differentiation of individuals that belong to the same species but grow in different populations and regions. Molecular markers have been used during the last few decades to fulfill this purpose and several improvements have been implemented rendering their use applicable to a commercial scale. The reliability, accuracy, reproducibility, and time-and cost-effectiveness of these techniques allowed them to be established as routine methods in the industry and research institutes. This review article aims at presenting the most important molecular markers used for the authentication of fish and seafood. The most important techniques are described, and the results of numerous studies are outlined and discussed, allowing interested parties to easily access and compare information about several techniques and fish/seafood species.

UHPLC-IM-Q-ToFMS analysis of maradolipids, found exclusively in Caenorhabditis elegans dauer larvae

Lipid identification is one of the current bottlenecks in lipidomics and lipid profiling, especially for novel lipid classes, and requires multidimensional data for correct annotation. We used the combination of chromatographic and ion mobility separation together with data-independent acquisition (DIA) of tandem mass spectrometric data for the analysis of lipids in the biomedical model organism Caenorhabditis elegans. C. elegans reacts to harsh environmental conditions by interrupting its normal life cycle and entering an alternative developmental stage called dauer stage. Dauer larvae show distinct changes in metabolism and morphology to survive unfavorable environmental conditions and are able to survive for a long time without feeding. Only at this developmental stage, dauer larvae produce a specific class of glycolipids called maradolipids. We performed an analysis of maradolipids using ultrahigh performance liquid chromatography-ion mobility spectrometry-quadrupole-time of flight-mass spectrometry (UHPLC-IM-Q-ToFMS) using drift tube ion mobility to showcase how the integration of retention times, collisional cross sections, and DIA fragmentation data can be used for lipid identification. The obtained results show that combination of UHPLC and IM separation together with DIA represents a valuable tool for initial lipid identification. Using this analytical tool, a total of 45 marado- and lysomaradolipids have been putatively identified and 10 confirmed by authentic standards directly from C. elegans dauer larvae lipid extracts without the further need for further purification of glycolipids. Furthermore, we putatively identified two isomers of a lysomaradolipid not known so far.

Membrane lipids and transporter function

Transport proteins are essential for cells in allowing the exchange of substances between cells and their environment across the lipid bilayer forming a tight barrier. Membrane lipids modulate the function of transmembrane proteins such as transporters in two ways: Lipids are tightly and specifically bound to transport proteins and in addition they modulate from the bulk of the lipid bilayer the function of transport proteins. This overview summarizes currently available information at the ultrastructural level on lipids tightly bound to transport proteins and the impact of altered bulk membrane lipid composition. Human diseases leading to altered lipid homeostasis will lead to altered membrane lipid composition, which in turn affect the function of transporter proteins.

Linking Gut Microbiome and Lipid Metabolism: Moving beyond Associations

Various studies aiming to elucidate the role of the gut microbiome-metabolome co-axis in health and disease have primarily focused on water-soluble polar metabolites, whilst non-polar microbial lipids have received less attention. The concept of microbiota-dependent lipid biotransformation is over a century old. However, only recently, several studies have shown how microbial lipids alter intestinal and circulating lipid concentrations in the host, thus impacting human lipid homeostasis. There is emerging evidence that gut microbial communities play a particularly significant role in the regulation of host cholesterol and sphingolipid homeostasis. Here, we review and discuss recent research focusing on microbe-host-lipid co-metabolism. We also discuss the interplay of human gut microbiota and molecular lipids entering host systemic circulation, and its role in health and disease.

Application of comprehensive lipidomics to biomarker research on adverse drug reactions

Lipidomics is a relatively new field of omics that focuses on lipids, one of the major categories of metabolites. Owing to their various functions, lipids are considered suitable targets for biomarker development; in addition, lipidomics analysis of adverse drug reactions (ADRs) has been conducted recently. In this review, I have summarized information on comprehensive lipidomics, which involves the analysis of global lipids in a non-targeted manner. Mass spectrometry-based platforms are currently the dominant lipidomics platform owing to their versatile features. I have also summarized the application of lipidomics in biomarker research on ADRs caused by therapeutic drugs in humans and rodents. Additionally, general concerns in and emerging approaches of lipidomics research on ADR have been highlighted. Although biomarkers identified using the lipidomics analysis of ADRs have not been qualified, reported candidates will be evaluated for clinical application. In addition, novel biomarker candidates will be developed via classical and new approaches exemplified in this review.

Lipidome is lipids regulator in gastrointestinal tract and it is a life collar in COVID-19: A review

The term lipidome is mentioned to the total amount of the lipids inside the biological cells. The lipid enters the human gastrointestinal tract through external source and internal source. The absorption pathway of lipids in the gastrointestinal tract has many ways; the 1^st way, the lipid molecules are digested in the lumen before go through the enterocytes, digested products are re-esterified into complex lipid molecules. The 2^nd way, the intracellular lipids are accumulated into lipoproteins (chylomicrons) which transport lipids throughout the whole body. The lipids are re-synthesis again inside the human body where the gastrointestinal lipids are: (1) Transferred into the endoplasmic reticulum; (2) Collected as lipoproteins such as chylomicrons; or (3) Stored as lipid droplets in the cytosol. The lipids play an important role in many stages of the viral replication cycle. The specific lipid change occurs during viral infection in advanced viral replication cycle. There are 47 lipids within 11 lipid classes were significantly disturbed after viral infection. The virus connects with blood-borne lipoproteins and apolipoprotein E to change viral infectivity. The viral interest is cholesterol- and lipid raft-dependent molecules. In conclusion, lipidome is important in gastrointestinal fat absorption and coronavirus disease 2019 (COVID-19) infection so lipidome is basic in gut metabolism and in COVID-19 infection success.

Lithium Hydroxide Hydrolysis Combined with MALDI TOF Mass Spectrometry for Rapid Sphingolipid Detection

Sphingolipids have diverse structural and bioactive functions that play important roles in many key biological processes. Factors such as low relative abundance, varied structures, and a dynamic concentration range provide a difficult analytical challenge for sphingolipid detection. To further improve mass-spectrometry-based sphingolipid analysis, lithium adduct consolidation was implemented to decrease spectral complexity and combine signal intensities, leading to increased specificity and sensitivity. We report the use of lithium hydroxide as a base in a routine hydrolysis procedure in order to effectively remove common ionization suppressants (such as glycolipids and glycerophospholipids) and introduce a source of lithium into the sample. In conjunction, an optimized MALDI matrix system, featuring 2',4',6'-trihydroxyacetophenone (THAP) is used to facilitate lithium adduct consolidation during the MALDI process. The result is a robust and high-throughput sphingolipid detection scheme, particularly of low-abundance ceramides. Application of our developed workflow includes the detection of differentially expressed liver sphingolipid profiles from a high-fat-induced obesity mouse model. We also demonstrate the method's effectiveness in detecting various sphingolipids in brain and plasma matrices. These results were corroborated with data from UHPLC HR MS/MS and MALDI FT-ICR, verifying the efficacy of the method application. Overall, we demonstrate a high-throughput workflow for sphingolipid analysis in various biological matrices by the use of MALDI TOF and lithium adduct consolidation.

Analytical Platforms for the Determination of Phospholipid Turnover in Breast Cancer Tissue: Role of Phospholipase Activity in Breast Cancer Development

Altered lipid metabolism has been associated with the progression of various cancers, and aberrant expression of enzymes involved in the lipid metabolism has been detected in different stages of cancer. Breast cancer (BC) is one of the cancer types known to be associated with alterations in the lipid metabolism and overexpression of enzymes involved in this metabolism. It has been demonstrated that inhibition of the activity of certain enzymes, such as that of phospholipase A₂ in BC cell lines sensitizes these cells and decreases the IC₅₀ values for forthcoming therapy with traditional drugs, such as doxorubicin and tamoxifen. Moreover, other phospholipases, such as phospholipase C and D, are involved in intracellular signal transduction, which emphasizes their importance in cancer development. Finally, BC is assumed to be dependent on the diet and the composition of lipids in nutrients. Despite their importance, analytical approaches that can associate the activity of phospholipases with changes in the lipid composition and distribution in cancer tissues are not yet standardized. In this review, an overview of various analytical platforms that are applied on the study of lipids and phospholipase activity in BC tissues will be given, as well as their association with cancer diagnosis and tumor progression. The methods that are applied to tissues obtained from the BC patients will be emphasized and critically evaluated, regarding their applicability in oncology.

Applications of Lipidomics in Tumor Diagnosis and Therapy

Lipids have many critical biological functions in cancer. There are characteristic changes of lipid metabolism and metabolites in different physiological and pathological processes. Lipidomics is an emerging discipline of metabolomics for systematic analysis of lipids in organisms, tissues, or cells and the molecules that interact with them. With the development of new analytical techniques, especially the application and development of mass spectrometry techniques, the determination of lipids can be carried out quickly and accurately and has a high throughput. A large number of studies have shown that abnormal lipid metabolism is closely related to the occurrence and development of tumors. The application of lipidomics technology can reveal changes in lipids and relative abnormal metabolic pathways associated with tumors. Moreover, it shows a wide range of application prospects in the identification of tumor lipid biomarkers, early tumor diagnosis, and the discovery of antitumor drug targets. This chapter mainly introduces the application and development direction of lipidomics in the diagnosis and therapy of different tumors.

Mass Spectrometry-Based Lipidomics: An Overview

Over the last few decades, MS-based lipidomics has emerged as a powerful tool to study lipids in biological systems. This success is driven by the constant demand for complete and reliable data. The improvement of MS-based lipidomics will continue to be dependent on the advances in the technology of mass spectrometry and related techniques including separation and bioinformatics, and more importantly, on gaining insight into the knowledge of lipid chemistry essential to develop methodology for lipid analysis. It is hoped that the protocols in this book, collected from experts in their fields, can offer the beginner and the advanced user alike, useful tips toward successful lipidomic analysis.

A concise review on lipidomics analysis in biological samples

Lipids are a complex and critical heterogeneous molecular entity, playing an intricate and key role in understanding biological activities and disease processes. Lipidomics aims to quantitatively define the lipid classes, including their molecular species. The analysis of the biological tissues and fluids are challenging due to the extreme sample complexity and occurrence of the molecular species as isomers or isobars. This review documents the overview of lipidomics workflow, beginning from the approaches of sample preparation, various analytical techniques and emphasizing the state-of-the-art mass spectrometry either by shotgun or coupled with liquid chromatography. We have considered the latest ion mobility spectroscopy technologies to deal with the vast number of structural isomers, different imaging techniques. All these techniques have their pitfalls and we have discussed how to circumvent them after reviewing the power of each technique with examples..

Generation of immune cell containing adipose organoids for in vitro analysis of immune metabolism

Adipose tissue is an organized endocrine organ with important metabolic and immunological functions and immune cell-adipocyte crosstalk is known to drive various disease pathologies. Suitable 3D adipose tissue organoid models often lack resident immune cell populations and therefore require the addition of immune cells isolated from other organs. We have created the first 3D adipose tissue organoid model which could contain and maintain resident immune cell populations of the stromal vascular fraction (SVF) and proved to be effective in studying adipose tissue biology in a convenient manner. Macrophage and mast cell populations were successfully confirmed within our organoid model and were maintained in culture without the addition of growth factors. We demonstrated the suitability of our model for monitoring the lipidome during adipocyte differentiation in vitro and confirmed that this model reflects the physiological lipidome better than standard 2D cultures. In addition, we applied mass spectrometry-based lipidomics to track lipidomic changes in the lipidome upon dietary and immunomodulatory interventions. We conclude that this model represents a valuable tool for immune-metabolic research.

A comprehensive comparison of four methods for extracting lipids from Arabidopsis tissues

BACKGROUND

The plant lipidome is highly complex, and the composition of lipids in different tissues as well as their specific functions in plant development, growth and stress responses have yet to be fully elucidated. To do this, efficient lipid extraction protocols which deliver target compounds in solution at concentrations adequate for subsequent detection, quantitation and analysis through spectroscopic methods are required. To date, numerous methods are used to extract lipids from plant tissues. However, a comprehensive analysis of the efficiency and reproducibility of these methods to extract multiple lipid classes from diverse tissues of a plant has not been undertaken.

RESULTS

In this study, we report the comparison of four different lipid extraction procedures in order to determine the most effective lipid extraction protocol to extract lipids from different tissues of the model plant Arabidopsis thaliana.

CONCLUSION

While particular methods were best suited to extract different lipid classes from diverse Arabidopsis tissues, overall a single-step extraction method with a 24 h extraction period, which uses a mixture of chloroform, isopropanol, methanol and water, was the most efficient, reproducible and the least labor-intensive to extract a broad range of lipids for untargeted lipidomic analysis of Arabidopsis tissues. This method extracted a broad range of lipids from leaves, stems, siliques, roots, seeds, seedlings and flowers of Arabidopsis. In addition, appropriate methods for targeted lipid analysis of specific lipids from particular Arabidopsis tissues were also identified.

Rapid automated diagnosis of primary hepatic tumour by mass spectrometry and artificial intelligence

BACKGROUND AND AIMS

Complete surgical resection with negative margin is one of the pillars in treatment of liver tumours. However, current techniques for intra-operative assessment of tumour resection margins are time-consuming and empirical. Mass spectrometry (MS) combined with artificial intelligence (AI) is useful for classifying tissues and provides valuable prognostic information. The aim of this study was to develop a MS-based system for rapid and objective liver cancer identification and classification.

METHODS

A large dataset derived from 222 patients with hepatocellular carcinoma (HCC, 117 tumours and 105 non-tumours) and 96 patients with mass-forming cholangiocarcinoma (MFCCC, 50 tumours and 46 non-tumours) were analysed by Probe Electrospray Ionization (PESI) MS. AI by means of support vector machine (SVM) and random forest (RF) algorithms was employed. For each classifier, sensitivity, specificity and accuracy were calculated.

RESULTS

The overall diagnostic accuracy exceeded 94% in both the AI algorithms. For identification of HCC vs non-tumour tissue, RF was the best, with 98.2% accuracy, 97.4% sensitivity and 99% specificity. For MFCCC vs non-tumour tissue, both algorithms gave 99.0% accuracy, 98% sensitivity and 100% specificity.

CONCLUSIONS

The herein reported MS-based system, combined with AI, permits liver cancer identification with high accuracy. Its bench-top size, minimal sample preparation and short working time are the main advantages. From diagnostics to therapeutics, it has the potential to influence the decision-making process in real-time with the ultimate aim of improving cancer patient cure.

Comparative Lipidomics of Different Yeast Species Associated to Drosophila suzukii

Yeasts constitute a dietary source for the spotted wing drosophila (SWD) and produce compounds that attract these flies. The study of the chemical composition of the yeast communities associated with SWD should therefore help to understand the relationship between the biology of the insect and the yeast's metabolism. In the present study, the lipidome of five yeast species isolated from grapes infested by SWD (three Hanseniaspora uvarum strains, Candida sp., Issatchenkia terricola, Metschnikowia pulcherrima and Saccharomycopsis vini) and a laboratory strain of Saccharomyces cerevisiae was explored using an untargeted approach. Additionally, the lipid profile of two species, S. cerevisiae and H. uvarum, which were reported to elicit different responses on SWD flies based on feeding and behavioral trials, was compared with a chemical enrichment approach. Overall, 171 lipids were annotated. The yeast species could be distinguished from each other based on their lipid profile, except for the three strains of H. uvarum, which were very similar to each other. The chemical enrichment analysis emphasized diversities between S. cerevisiae and H. uvarum, that could not be detected based on their global lipid profile. The information concerning differences between species in their lipidome may be of interest to future entomological studies concerning the yeast-insect interaction and could help to explain the responses of SWD to diverse yeast species.

Lipid Annotation by Combination of UHPLC-HRMS (MS), Molecular Networking, and Retention Time Prediction: Application to a Lipidomic Study of In Vitro Models of Dry Eye Disease

Annotation of lipids in untargeted lipidomic analysis remains challenging and a systematic approach needs to be developed to organize important datasets with the help of bioinformatic tools. For this purpose, we combined tandem mass spectrometry-based molecular networking with retention time (t_R) prediction to annotate phospholipid and sphingolipid species. Sixty-five standard compounds were used to establish the fragmentation rules of each lipid class studied and to define the parameters governing their chromatographic behavior. Molecular networks (MNs) were generated through the GNPS platform using a lipid standards mixture and applied to lipidomic study of an in vitro model of dry eye disease, i.e., human corneal epithelial (HCE) cells exposed to hyperosmolarity (HO). These MNs led to the annotation of more than 150 unique phospholipid and sphingolipid species in the HCE cells. This annotation was reinforced by comparing theoretical to experimental t_R values. This lipidomic study highlighted changes in 54 lipids following HO exposure of corneal cells, some of them being involved in inflammatory responses. The MN approach coupled to t_R prediction thus appears as a suitable and robust tool for the discovery of lipids involved in relevant biological processes.

The hepatic lipidome: From basic science to clinical translation

The liver is the key organ involved in lipid metabolism and transport. Excessive lipid accumulation due to dysregulated lipid metabolism predisposes the liver to steatosis, cirrhosis, and hepatocellular carcinoma. Lipids are generally compartmentalized in specialized organelles called lipid droplets that enable cells to store and release lipids in a regulated manner. However, during flux-in and flux-out of droplets, lipids are converted into toxic species leading to lipid-mediated liver damage. Lipids are categorized into 'toxic' or 'healthy' lipids that are involved in liver disease pathogenesis or resolution, respectively. Lipidomic analysis have revealed unique lipid signature that correlates with the disease progression therefore being used for disease diagnosis. In this comprehensive review, we provide an overview on hepatic lipid homeostasis, lipid compartmentalization mechanisms and lipidomic profiles in different liver diseases. We further discuss promising therapeutics targeting the hepatic lipidome including pro-resolving lipids, liposomes, and small-molecule inhibitors for the treatment of liver diseases.

Lipidomics reveal the protective effects of a vegetable-derived isothiocyanate against retinal degeneration

Background: Age-related macular degeneration (AMD) is a leading cause of blindness in the ageing population. Without effective treatment strategies that can prevent disease progression, there is an urgent need for novel therapeutic interventions to reduce the burden of vision loss and improve patients' quality of life. Dysfunctional innate immune responses to oxidative stress observed in AMD can be caused by the formation of oxidised lipids, whilst polyunsaturated fatty acids have shown to increase the risk of AMD and disease progression in affected individuals. Previously, our laboratory has shown that the vegetable-derived isothiocyanate, L-sulforaphane (LSF), can protect human adult pigment epithelial cells from oxidative damage by upregulating gene expression of the oxidative stress enzyme Glutathione-S-Transferase µ1. This study aims to validate the protective effects of LSF on human retinal cells under oxidative stress conditions and to reveal the key players in fatty acid and lipid metabolism that may facilitate this protection. Methods: The in vitro oxidative stress model of AMD was based on the exposure of an adult retinal pigment epithelium-19 cell line to 200µM hydrogen peroxide. Percentage cell proliferation following LSF treatment was measured using tetrazolium salt-based assays. Untargeted fatty acid profiling was performed by gas chromatography-mass spectrometry. Untargeted lipid profiling was performed by liquid chromatography-mass spectrometry. Results: Under hydrogen peroxide-induced oxidative stress conditions, LSF treatment induced dose-dependent cell proliferation. The key fatty acids that were increased by LSF treatment of the retinal cells include oleic acid and eicosatrienoic acid. LSF treatment also increased levels of the lipid classes phosphatidylcholine, cholesteryl ester and oxo-phytodienoic acid but decreased levels of phosphatidylethanolamine lipids. Conclusions: We propose that retinal cells at risk of oxidative damage and apoptosis can be pre-conditioned with LSF to regulate levels of selected fatty acids and lipids known to be implicated in the pathogenesis and progression of AMD.