Lipidomics

Multiomics Analysis-Based Biomarkers in Diagnosis of Polycystic Ovary Syndrome

Polycystic ovarian syndrome is an utmost communal endocrine, psychological, reproductive, and metabolic disorder that occurs in women of reproductive age with extensive range of clinical manifestations. This may even lead to long-term multiple morbidities including obesity, diabetes mellitus, insulin resistance, cardiovascular disease, infertility, cerebrovascular diseases, and ovarian and endometrial cancer. Women affliction from PCOS in midst assemblage of manifestations allied with menstrual dysfunction and androgen exorbitance, which considerably affects eminence of life. PCOS is recognized as a multifactorial disorder and systemic syndrome in first-degree family members; therefore, the etiology of PCOS syndrome has not been copiously interpreted. The disorder of PCOS comprehends numerous allied health conditions and has influenced various metabolic processes. Due to multifaceted pathophysiology engaging several pathways and proteins, single genetic diagnostic tests cannot be supportive to determine in straight way. Clarification of cellular and biochemical pathways and various genetic players underlying PCOS could upsurge our consideration of pathophysiology of this syndrome. It is requisite to know pathophysiological relationship between biomarker and their reflection towards PCOS disease. Biomarkers deliver vibrantly and potent ways to apprehend the spectrum of PCOS with applications in screening, diagnosis, characterization, and monitoring. This paper relies on the endeavor to point out many candidates as potential biomarkers based on omics technologies, thus highlighting correlation between PCOS disease with innovative technologies. Therefore, the objective of existing review is to encapsulate more findings towards cutting-edge advances in prospective use of biomarkers for PCOS disease. Discussed biomarkers may be fruitful in guiding therapies, addressing disease risk, and predicting clinical outcomes in future.

Mammalian lipids: structure, synthesis and function

Lipids are essential constituents of cellular membranes. Once regarded merely as structural components, lipids have taken centre stage with the discovery of their roles in cell signalling and in the generation of bioactive metabolites. Lipids regulate many physiological functions of cells and alterations in membrane lipid metabolism are associated with major diseases including cancer, Type II diabetes, cardiovascular disease and immune disorders. Understanding lipid diversity, their synthesis and metabolism to generate signalling molecules will provide insight into the fundamental function of the cell. This review summarises the biosynthesis of the lipids of the mammalian cell; phospholipids, sphingolipids and cholesterol and how lipid diversity is achieved. The fatty acids (FAs) are the main building blocks of lipids and contribute to the diversity. Lipid synthesis is intimately connected to their transport within cells; the contribution by proteins that transport lipids, lipid transport proteins will be described. Cellular lipids are metabolised by phospholipases, lipid kinases and phosphatases to make new bioactive metabolites. These transient bioactive metabolites allow cells to respond to the external environment to maintain cellular health. The function of individual metabolites is also highlighted. Bioactive metabolites can be second messengers, or released to the external medium to regulate other cells. Alternatively, bioactive lipids also provide a platform for reversible recruitment of proteins to membranes using their lipid-binding domains. The wide range of physiological processes in which a specific involvement of lipids has been identified explains the need for lipid diversity present in mammalian cells.

Screening and identification of potential novel lipid biomarkers for non-small cell lung cancer using ultra-high performance liquid chromatography tandem mass spectrometry

Lung cancer is characterized by a high incidence rate and low survival rate. It is important to achieve early diagnosis of the disease. We applied ultra-high performance liquid chromatography tandem mass spectrometry to screen plasma lipid spectrum in non-small cell lung cancer (NSCLC) patients, healthy controls (HC), and community-acquired pneumonia (CAP) patients. Modeling employing orthogonal partial least squares-discriminant analysis combined with t-test was used to screen the differential lipids. Logistic regression analysis was used to establish the diagnostic model, while the accuracy was verified by 10-fold cross-validation. The results showed that the abnormal metabolism of lipid in NSCLC mainly comprised fatty acid metabolism, phospholipid metabolism, and glyceride metabolism. Four potential biomarkers, including LPC (14:0/0:0), LPI (14:1/0:0), DG (14:0/18:2/0:0), and LPC (16:1/0:0), were fitted by the receiver operating characteristic curve model with the area under curve (AUC) value of 0.856, and the specificity and sensitivity were 87.0 and 78.0%, respectively. The results of cross validation showed that the AUC value of the model was 0.812, the sensitivity was 72.9%, and the specificity was 82.6%. The positive rate of four potential lipid biomarkers in this study (>60.0%) was higher than that of existing tumor biomarkers in the clinical application. We investigated the plasma lipid profile of NSCLC patients and identified lipid biomarkers with potential diagnostic values. From the lipidomics perspective, our study may lay a foundation for the biomarker-based early diagnosis of lung cancer.

Thyroid and Lipid Status in Guide Dogs During Training: Effects of Dietary Protein and Fat Content

Nutrition plays a leading role that most influences thyroid response and energetic metabolism. Aim was to compare the effect of diet on thyroid and lipid status in guide dogs during a 12-weeks training period. Eight Labrador Retrievers were divided into two groups homogeneous for sex, age, body weight, and Body Condition Score (BCS) and fed two commercial diets one, HPF, characterized by low-carbohydrate/high-protein/high-fat (29%:39%:19% as-fed) and the other, LPF, by high-carbohydrate/low-protein/low-fat (50%:24%:12% as-fed) content. The serum thriiodothyronine (T₃), thyroxine (T₄), cholesterol (CHOL), triglycerides (TAGs) and non-esterified fatty acids (NEFA) were determined at Day 0, 28, 56, and 84, before the daily training. Statistical model included the effects of Diet (HPF vs. LPF) and Time (Day 0 to Day 84), and their interaction. In the HPF group, Diet significantly (p < 0.01) increased T₄, CHOL, and TAGs and decreased NEFA. In both groups, Time significantly (p < 0.05) increased T₄ and TAGs, CHOL at Day 28, and NEFA at Day 56. The interaction did not influence serum hormones and lipid pattern. The adjustments in thyroid and lipid responses to moderate exercise in HPF group were driven mainly by the nutrient composition of the diet in relation to the involvement of metabolic homeostasis.

Pro-Resolving Lipid Mediators in the Pathophysiology of Asthma

Asthma is one of the most important medical and social problems of our time due to the prevalence and the complexity of its treatment. Chronic inflammation that is characteristic of asthma is accompanied by bronchial obstruction, which involves various lipid mediators produced from n-6 and n-3 polyunsaturated fatty acids (PUFAs). The review is devoted to modern ideas about the PUFA metabolites—eicosanoids (leukotrienes, prostaglandins, thromboxanes) and specialized pro-resolving lipid mediators (SPMs) maresins, lipoxins, resolvins, protectins. The latest advances in clinical lipidomics for identifying and disclosing the mechanism of synthesis and the biological action of SPMs have been given. The current views on the peculiarities of the inflammatory reaction in asthma and the role of highly specialized metabolites of arachidonic, eicosapentaenoic and docosahexaenoic acids in this process have been described. The possibility of using SPMs as therapeutic agents aimed at controlling the resolution of inflammation in asthma is discussed.

Lipid Isolation Process and Study on Some Molecular Species of Polar Lipid Isolated from Seed of Madhuca ellitica

This study attempted the lipid extraction process from the seeds of Madhuca ellitica, a lipid-rich plant, and conducted a lipidomic analysis on molecular species of the obtained product. Total lipids of the crude seeds were found to contain 11.2% of polar lipids. The major fatty acids (FAs) of the polar lipids were palmitic (16:0), stearic (18:0), oleic (18:1n-9), and linoleic (18:2n-6) acids, which amounted to 28.5, 12.5, 44.8, and 13.2% of total FAs, respectively. The content and chemical structures of individual molecular species of phosphatidylglycerol (PG), phosphatidylethanolamine (PE), phosphatidylcholine (PC), phosphatidylinositol (PI), phosphatidic acid (PA), and sulfoquinovosyldiacylglycerol (SQDG) were determined by HPLC with a tandem high-resolution mass spectrometry (HRMS). The major molecular species were 18:1/18:2 PE, 16:0/18:1 PC, 18:1/18:2 PC, 16:0/18:2 PG, 16:0/18:1 PG, 16:1/18:1 PI, 16:0/18:1 PI, 18:0/18:2 PI, 16:0/18:1 PA, 18:1/18:2 PA, 16:0/18:1 SQDG, and 18:0/18:1 SQDG. The application of a tandem HRMS allows us to determine the content of each isomer in pairs of the monoisotopic molecular species, for example, 18:0/18:2 and 18:1/18:1. The evaluation of the seed polar lipid profile will be helpful for developing the potential of this tree for nutritive and industrial uses.

Understanding mechanisms of oocyte development by follicular fluid lipidomics

PURPOSE

The present study aimed to provide a non-invasive approach to studying mechanisms responsible for oocyte development.

METHODS

To this end, follicular fluid (FF) from 62 patients undergoing in vitro fertilization (IVF) cycles was split into two groups depending on the pregnancy outcome: pregnant (n = 28) and non-pregnant (n = 34) groups. Data were acquired by the MALDI-TOF mass spectrometry. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were applied to the data set. A ROC curve, to predict success rate, was constructed, and the lipids were attributed.

RESULTS

Six ions were differentially represented in FF of pregnant and non-pregnant patients, with an area under the curve of 0.962. Phosphatidic acid, phosphatidylglycerol, and triacylglycerol were hyper-represented in the pregnant group, while glucosylceramide was hyper-represented in the non-pregnant group. Enriched functions related to these lipids are steroidogenesis, cellular response, signal transduction, cell cycle, and activation of protein kinase C for the pregnant group and apoptosis inhibition for the non-pregnant group.

CONCLUSION

Human FF fingerprinting can both improve the understanding concerning mechanisms responsible for oocyte development and its effect on embryo implantation potential and assist in the management of IVF cycles.

Reshaping Lipid Biochemistry by Pushing Barriers in Structural Lipidomics

Lipidomics is a rapidly growing field with numerous examples showing the importance of lipid molecules throughout biology. It has also shed light onto the vast and complex functions performed by many lipids that possess an immense diversity in molecular structures. Mass spectrometry (MS) is the tool of choice for analyzing lipids and has been the key catalyst driving the field forward. However, MS does not yet permit true molecular lipidomics wherein the identification and quantification of lipids having defined molecular structures can be routinely achieved. Here we describe recent advances in MS‐based lipidomics that allow access to higher levels of molecular information in lipidomics experiments. These advances will form a key piece of the puzzle as the field moves towards systems characterization of lipids at the molecular level.

Is the clinical lipidomics a potential goldmine?

Clinical lipidomics is a new extension of lipidomics to study lipid profiles, pathways, and networks by characterizing and quantifying the complete lipid molecules in cells, biopsy, or body fluids of patients. It undoubtfully has more values if lipidomics can be integrated with the data of clinical proteomic, genomic, and phenomic profiles. A number of challenges, e.g., instability, specificity, and sensitivity, in lipidomics have to be faced and overcome before clinical application. The association of lipidomics data with gene expression and sequencing of lipid-specific proteins/enzymes should be furthermore clarified. Therefore, clinical lipidomics is expected to be more stable during handling, sensitive in response to changes, specific for diseases, efficient in data analyses, and standardized in measurements, in order to meet clinical needs. Clinical lipidomics will become a more important approach in clinical applications and will be the part of "natural" measures for early diagnosis and progress of disease. Thus, clinical lipidomics will be one of the most powerful approaches for disease-specific diagnosis and therapy, once the mystery of lipidomic profiles and metabolic enzymes is deciphered.

Novel Phospholipid Signature of Depressive Symptoms in Patients With Coronary Artery Disease

Background

Depression in patients with coronary artery disease (CAD) is associated with increased cardiovascular morbidity. Given the proinflammatory actions of phospholipids, aberrant phospholipid metabolism may be an etiological mechanism linking CAD and depression. Our primary objective was to identify a phospholipid biomarker panel that characterizes CAD patients with significant depressive symptoms from those without.

Methods and Results

We performed a targeted lipidomic analysis on CAD patients with significant depressive symptoms (n=37, Center for Epidemiologic Studies Depression score ≥16) and those without (n=49). Phospholipid species were selected using partial least‐square discriminant analysis, and the ability of the resulting model to discriminate between groups was evaluated using receiver operator characteristic curves. Biosignature scores were calculated from this model, and analyses of covariance were performed to compare intergroup differences in biosignature scores, with adjustment for clinical differences between patients. Those with significant depressive symptoms had lower cardiopulmonary fitness, more prevalent history of depression, and a greater number of vascular risk factors. A model of 10 phospholipid species had an area under the curve value of 0.84 (95% confidence interval 0.72‐0.95), sensitivity of 0.73, and specificity of 0.71. This model passed permutation testing (n=1000, P<0.001). Biosignature scores were higher in those with significant depressive symptoms after adjustment for potential confounders (F[1.86]=14.39, P<0.0005).

Conclusions

The present findings support the role of proinflammatory phospholipid species in the presence of depression in CAD patients from the CAROTID trial (Coronary Artery Disease Randomized Omega‐3 Trial in Depression). Future investigations should aim to replicate findings in larger data sets and clarify possible pathophysiological mechanisms.

Clinical Trial Registration

URL: https://www.clinicaltrials.gov. Unique identifier: NCT00981383.

Biofluid lipidome: a source for potential diagnostic biomarkers

Lipidomics is the identification and quantitation of changes in the lipidome of a cell, tissue, organ or biofluid in health and disease using high resolution mass spectrometry. Lipidome of a particular organism has relevance to the disease manifestation as it reflects the metabolic changes which can be a consequence of the disease. Hence these changes in the molecules can be considered as potential markers for screening and early detection of the disease. Biological fluids as blood/serum/plasma, urine, saliva, tear and cerebrospinal fluid, due to their accessibility, offer ease of collection with minimal or no discomfort to the patient and provide a ready footprint of the metabolic changes occurring during disease. This review provides a brief introduction to lipidomics and its role in understanding the metabolic changes in health and disease followed by discussion on the chemical diversity of the lipid species and their biological role, mammalian lipids and their metabolism and role of lipids in pathogens and the immune response before dwelling further into importance of studying lipidome in various biological fluids. The challenges in performing a lipidomic analysis at the experimental and data analysis stages are discussed.

Modulation of the lipidomic profile due to a lipid challenge and fitness level: a postprandial study

Background

The lipid composition of plasma is known to vary due to both phenotypic factors such as age, gender and BMI as well as with various diseases including cancer and neurological disorders. However, there is little investigation into the variation in the lipidome due to exercise and/ or metabolic challenges. The objectives of this present study were (i) To identify the glycerophospholipid, sphingolipids and ceramide changes in response to an oral lipid tolerance test (OLTT) in healthy adults and (ii) To identify the effect of aerobic fitness level on lipidomic profiles.

Methods

214 healthy adults aged 18–60 years were recruited as part of a metabolic challenge study. A sub-group of 40 volunteers were selected for lipidomic analysis based on their aerobic fitness level. Ceramides, glycerophospholipids and sphingomyelins were quantified in baseline fasting plasma samples as well as at 60, 120, 180, 240 and 300 min following a lipid challenge using high-throughput flow injection ESI-MS/MS.

Results

Mixed model repeated measures analysis identified lipids which were significantly changing over the time course of the lipid challenge. Included in these lipids were lysophosphoethanolamines (LPE), phosphoethanolamines (PE), phosphoglycerides (PG) and ceramides (Cer). Five lipids (LPE a C18:2, LPE a C18:1, PE aa C36:2, PE aa C36:3 and N-C16:1-Cer) had a fold change > 1.5 at 120 min following the challenge and these lipids remained elevated. Furthermore, three of these lipids (LPE a C18:2, PE aa C36:2 and PE aa C36:3) were predictive of fasting and peak plasma TAG concentrations following the OLTT. Further analysis revealed that fitness level has a significant impact on the response to the OLTT: in particular significant differences between fitness groups were observed for phosphatidylcholines (PC), sphingomyelins (SM) and ceramides.

Conclusion

This study identified specific lipids which were modulated by an acute lipid challenge. Furthermore, it identified a series of lipids which were modulated by fitness level. Future lipidomic studies should take into account environmental factors such as diet and fitness level during biomarker discovery work.

Trial registration

Data, clinicaltrials.gov, NCT01172951

Electronic supplementary material

The online version of this article (doi:10.1186/s12944-015-0062-x) contains supplementary material, which is available to authorized users.

Lipid metabolism, apoptosis and cancer therapy

Lipid metabolism is regulated by multiple signaling pathways, and generates a variety of bioactive lipid molecules. These bioactive lipid molecules known as signaling molecules, such as fatty acid, eicosanoids, diacylglycerol, phosphatidic acid, lysophophatidic acid, ceramide, sphingosine, sphingosine-1-phosphate, phosphatidylinositol-3 phosphate, and cholesterol, are involved in the activation or regulation of different signaling pathways. Lipid metabolism participates in the regulation of many cellular processes such as cell growth, proliferation, differentiation, survival, apoptosis, inflammation, motility, membrane homeostasis, chemotherapy response, and drug resistance. Bioactive lipid molecules promote apoptosis via the intrinsic pathway by modulating mitochondrial membrane permeability and activating different enzymes including caspases. In this review, we discuss recent data in the fields of lipid metabolism, lipid-mediated apoptosis, and cancer therapy. In conclusion, understanding the underlying molecular mechanism of lipid metabolism and the function of different lipid molecules could provide the basis for cancer cell death rationale, discover novel and potential targets, and develop new anticancer drugs for cancer therapy.

Lipidomic analysis of plasma samples from women with polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is a common disorder affecting between 5 and 18 % of females of reproductive age and can be diagnosed based on a combination of clinical, ultrasound and biochemical features, none of which on its own is diagnostic. A lipidomic approach using liquid chromatography coupled with accurate mass high-resolution mass-spectrometry (LC-HRMS) was used to investigate if there were any differences in plasma lipidomic profiles in women with PCOS compared with control women at different stages of menstrual cycle. Plasma samples from 40 women with PCOS and 40 controls aged between 18 and 40 years were analysed in combination with multivariate statistical analyses. Multivariate data analysis (LASSO regression and OPLS-DA) of the sample lipidomics datasets showed a weak prediction model for PCOS versus control samples from the follicular and mid-cycle phases of the menstrual cycle, but a stronger model (specificity 85 % and sensitivity 95 %) for PCOS versus the luteal phase menstrual cycle controls. The PCOS vs luteal phase model showed increased levels of plasma triglycerides and sphingomyelins and decreased levels of lysophosphatidylcholines and phosphatidylethanolamines in PCOS women compared with controls. Lipid biomarkers of PCOS were tentatively identified which may be useful in distinguishing PCOS from controls especially when performed during the menstrual cycle luteal phase.

Lipidomic assessment of plasma and placenta of women with early-onset preeclampsia

Introduction

Adipose tissue is responsible for triggering chronic systemic inflammatory response and these changes may be involved in the pathophysiology of preeclampsia.

Objective

To characterize the lipid profile in the placenta and plasma of patients with preeclampsia.

Methodology

Samples were collected from placenta and plasma of 10 pregnant women with preeclampsia and 10 controls. Lipids were extracted using the Bligh–Dyer protocol and were analysed by MALDI TOF-TOF mass spectrometry.

Results

Approximately 200 lipid signals were quantified. The most prevalent lipid present in plasma of patients with preeclampsia was the main class Glycerophosphoserines-GP03 (PS) representing 52.30% of the total lipid composition, followed by the main classes Glycerophosphoethanolamines-GP02 (PEt), Glycerophosphocholines-GP01 (PC) and Flavanoids-PK12 (FLV), with 24.03%, 9.47% and 8.39% respectively. When compared to the control group, plasma samples of patients with preeclampsia showed an increase of PS (p<0.0001), PC (p<0.0001) and FLV (p<0.0001). Placental analysis of patients with preeclampsia, revealed the PS as the most prevalent lipid representing 56.28%, followed by the main class Macrolides/polyketides-PK04 with 32.77%, both with increased levels when compared with patients control group, PS (p<0.0001) and PK04 (p<0.0001).

Conclusion

Lipids found in placenta and plasma from patients with preeclampsia differ from those of pregnant women in the control group. Further studies are needed to clarify if these changes are specific and a cause or consequence of preeclampsia.

Mass spectrometry strategies for clinical metabolomics and lipidomics in psychiatry, neurology, and neuro-oncology

Metabolomics research has the potential to provide biomarkers for the detection of disease, for subtyping complex disease populations, for monitoring disease progression and therapy, and for defining new molecular targets for therapeutic intervention. These potentials are far from being realized because of a number of technical, conceptual, financial, and bioinformatics issues. Mass spectrometry provides analytical platforms that address the technical barriers to success in metabolomics research; however, the limited commercial availability of analytical and stable isotope standards has created a bottleneck for the absolute quantitation of a number of metabolites. Conceptual and financial factors contribute to the generation of statistically under-powered clinical studies, whereas bioinformatics issues result in the publication of a large number of unidentified metabolites. The path forward in this field involves targeted metabolomics analyses of large control and patient populations to define both the normal range of a defined metabolite and the potential heterogeneity (eg, bimodal) in complex patient populations. This approach requires that metabolomics research groups, in addition to developing a number of analytical platforms, build sufficient chemistry resources to supply the analytical standards required for absolute metabolite quantitation. Examples of metabolomics evaluations of sulfur amino-acid metabolism in psychiatry, neurology, and neuro-oncology and of lipidomics in neurology will be reviewed.

Systems-Level Lipid Analysis Methodologies for Qualitative and Quantitative Investigation of Lipid Signaling Events During Wound Healing

OBJECTIVE

Accumulating evidence implicates a prominent role for lipid signaling molecules in the regulation of wound healing. These lipids regulate hemostasis, onset and resolution of inflammation, migration and proliferation cells, angiogenesis, epithelialization, and remodeling of collagen. The objective of this overview is to demonstrate the applicability of systems level lipid analyses to identify and quantify lipid involved in events leading to wound healing.

APPROACH

Current advances in liquid chromatography coupled to tandem mass spectrometry have provided the means for carrying out quantitative and qualitative analysis of lipids at a systems level. This emerging field is collectively referred to as lipidomics and its potential in wound healing research is largely ignored.

RESULTS

While comprehensive applications of lipidomics in wound healing are limited, studies carried out by the authors as well as others demonstrate distinct changes in the lipidome during the wound healing process.

INNOVATION

Until recently, investigations into lipids were limited to the study of a few lipids at a time. Lipidomics approaches provide the capability to quantitatively and qualitatively assay almost the full complement of lipid signaling circuits at the same time. This allows obtaining a system level understanding of changes to the entire lipidome during the wound healing process.

CONCLUSION

The technology provides promising approach to understanding new signaling pathways based on lipids involved in wound healing. The understanding gained from such studies has the potential for the development of novel lipid based treatment strategies to promote wound healing.

Relative quantification of biomarkers using mixed-isotope labeling coupled with MS

The identification and quantification of important biomarkers is a critical first step in the elucidation of biological systems. Biomarkers take many forms as cellular responses to stimuli and can be manifested during transcription, translation, and/or metabolic processing. Increasingly, researchers have relied upon mixed-isotope labeling (MIL) coupled with MS to perform relative quantification of biomarkers between two or more biological samples. MIL effectively tags biomarkers of interest for ease of identification and quantification within the mass spectrometer by using isotopic labels that introduce a heavy and light form of the tag. In addition to MIL coupled with MS, a number of other approaches have been used to quantify biomarkers including protein gel staining, enzymatic labeling, metabolic labeling, and several label-free approaches that generate quantitative data from the MS signal response. This review focuses on MIL techniques coupled with MS for the quantification of protein and small-molecule biomarkers.

NMR spectroscopy of macrophages loaded with native, oxidized or enzymatically degraded lipoproteins

Oxidized and enzymatically modified low-density lipoproteins (oxLDL and eLDL) play a key role in early stages of atherogenesis. Their uptake by recruited macrophages leads to endolysosomal phospholipidosis or foam cell formation, respectively, each of which is preceded by highly differential lipid restructuring processes. We applied ¹H-NMR spectroscopy (NMRS) to elucidate these structural rearrangements both in consequence of lipoprotein modifications and following phagocytosis. Being specifically sensitive to the mobile lipid subset, NMRS of oxLDL and eLDL revealed a partial and total immobilization of lipids, respectively. NMRS of intact macrophages showed a sixfold increase in mobile lipids in case of loading with eLDL but no significant changes for oxLDL or native LDL. This finding reflected the disparate lipid storage in lipid droplets and in multilamellar endolysosomal clusters when loaded with either eLDL or oxLDL, respectively. Moreover, a significant shift of the degree of saturation towards mainly polyunsaturated fatty acid chains was found for the mobile lipid pool in eLDL-loaded macrophages. Additional analyses of lipid extracts by NMRS and mass spectrometry (MS) reflected these changes in lipid content and in fatty acid composition only partially. In summary, in-cell NMRS represents a unique lipidomics tool to investigate structural changes within the mobile lipid pool following atherogenic triggers that can be not detected by the analysis of lipid extracts by MS or NMRS.

A vision for better health: mass spectrometry imaging for clinical diagnostics

BACKGROUND

Mass spectrometry imaging (MSI) is a powerful tool that grants the ability to investigate a broad mass range of molecules from small molecules to large proteins by creating detailed distribution maps of selected compounds. Its usefulness in biomarker discovery towards clinical applications has obtained success by correlating the molecular expression of tissues acquired from MSI with well-established histology.

RESULTS

To date, MSI has demonstrated its versatility in clinical applications, such as biomarker diagnostics of different diseases, prognostics of disease severities and metabolic response to drug treatment, etc. These studies have provided significant insight in clinical studies over the years and current technical advances are further facilitating the improvement of this field. Although the underlying concept is simple, factors such as choice of ionization method, sample preparation, instrumentation and data analysis must be taken into account for successful applications of MSI. Herein, we briefly reviewed these key elements yet focused on the clinical applications of MSI that cannot be addressed by other means.

CONCLUSIONS

Challenges and future perspectives in this field are also discussed to conclude that the ever-growing applications with continuous development of this powerful analytical tool will lead to a better understanding of the biology of diseases and improvements in clinical diagnostics.

Proteomic approaches to predict bioavailability of fatty acids and their influence on cancer and chronic disease prevention

A low intake of fish and PUFA and high dietary trans- and SFA are considered to be among the main preventable causes of death. Unfortunately, epidemiological and preclinical studies have yet to identify biomarkers that accurately predict the influence of fatty acid intake on risk of chronic diseases, including cancer. Changes in protein profile and post-translational modifications in tissue and biofluids may offer important clues about the impact of fatty acids on the etiology of chronic diseases. However, conventional protein methodologies are not adequate for assessing the impact of fatty acids on protein expression patterns and modifications and the discovery of protein biomarkers that predict changes in disease risk and progression in response to fatty acid intake. Although fluctuations in protein structure and abundance and inter-individual variability often mask subtle effects caused by dietary intervention, modern proteomic platforms offer tremendous opportunities to increase the sensitivity of protein analysis in tissues and biofluids (plasma, urine) and elucidate the effects of fatty acids on regulation of protein networks. Unfortunately, the number of studies that adopted proteomic tools to investigate the impact of fatty acids on disease risk and progression is quite small. The future success of proteomics in the discovery of biomarkers of fatty acid nutrition requires improved accessibility and standardization of proteomic methodologies, validation of quantitative and qualitative protein changes (e.g., expression levels, post-translational modifications) induced by fatty acids, and application of bioinformatic tools that can inform about the cause-effect relationships between fatty acid intake and health response.