The association of the lipid profile with knee and hand osteoarthritis severity: the IMI-APPROACH cohort.

OBJECTIVE: To investigate the association of the lipidomic profile with osteoarthritis (OA) severity, considering the outcomes radiographic knee and hand OA, pain and function. DESIGN: We used baseline data from the Applied Public-Private Research enabling OsteoArthritis Clinical Headway (APPROACH) cohort, comprising persons with knee OA fulfilling the clinical American College of Rheumatology classification criteria. Radiographic knee and hand OA severity was quantified with Kellgren-Lawrence sum scores. Knee and hand pain and function were assessed with validated questionnaires. We quantified fasted plasma higher order lipids and oxylipins with liquid chromatography with tandem mass spectrometry (LC-MS/MS)-based platforms. Using penalised linear regression, we assessed the variance in OA severity explained by lipidomics, with adjustment for clinical covariates (age, sex, body mass index (BMI) and lipid lowering medication), measurement batch and clinical centre. RESULTS: In 216 participants (mean age 66 years, mean BMI 27.3 kg/m2, 75% women) we quantified 603 higher order lipids (triacylglycerols, diacylglycerols, cholesteryl esters, ceramides, free fatty acids, sphingomyelins, phospholipids) and 28 oxylipins. Lipidomics explained 3% and 2% of the variance in radiographic knee and hand OA severity, respectively. Lipids were not associated with knee pain or function. Lipidomics accounted for 12% and 6% of variance in hand pain and function, respectively. The investigated OA severity outcomes were associated with the lipidomic fraction of bound and free arachidonic acid, bound palmitoleic acid, oleic acid, linoleic acid and docosapentaenoic acid. CONCLUSIONS: Within the APPROACH cohort lipidomics explained a minor portion of the variation in OA severity, which was most evident for the outcome hand pain. Our results suggest that eicosanoids may be involved in OA severity.

Targeted lipidomics reveals activation of resolution pathways in knee osteoarthritis in humans.

OBJECTIVE: To investigate the presence of inflammation and resolution pathways in osteoarthritis (OA). DESIGN: Tissues were obtained from knee OA patients and control rheumatoid arthritis (RA) patients. Cells in synovial fluid (SF) were visualized by flow cytometry. Cytokines and chemokines were measured by multiplex assay. Lipid mediators (LMs) were determined by targeted lipidomics using liquid-chromatography mass spectrometry. RESULTS: SF of OA patients contained less cells, especially neutrophils, less cytokines and comparable levels of chemokines compared to RA controls. Thirty-seven lipids were detected in the soluble fraction of SF, including polyunsaturated fatty acids (PUFAs) and their pro-inflammatory and pro-resolving lipoxygenase (LOX) and cyclooxygenase (COX) pathway markers in both OA and RA patients. Among these, pro-inflammatory LM such as prostaglandin E2 (PGE2) and thromboxane B2, as well as precursors and pathway markers of resolution such as 17-HDHA and 18-HEPE were detected. Interestingly, the pro-resolving lipid RvD2 could also be detected, but only in the insoluble fraction (cells and undigested matrix). Ratios of metabolites to their precursors indicated a lower activity of 5-LOX and 15-LOX in OA compared to RA, with no apparent differences in COX-derived products. Interestingly, synovial tissue and SF cells could produce 5-LOX and 15-LOX metabolites, indicating these cells as possible source of LM. CONCLUSIONS: By using a state-of-the-art technique, we show for the first time that resolution pathways are present in OA patients. A better understanding of these pathways could guide us to more effective therapeutic approaches to inhibit inflammation and further structural damage in OA and RA.

Amino acid analysis using chromatography-mass spectrometry: An inter platform comparison study.

The analysis of amino acids has become a central task in many aspects. While amino acid analysis has traditionally mainly been carried out using either gas chromatography (GC) in combination with flame ionization detection or liquid chromatography (LC) with either post-column derivatization using ninhydrin or pre-column derivatization using o-phthalaldehyde, many of today's analysis platforms are based on chromatography in combination with mass spectrometry (MS). While derivatization is mandatory for the GC-based analysis of amino acids, several LC platforms have emerged, particularly in the dawn of targeted metabolite profiling using hydrophilic interaction liquid chromatography (HILIC) coupled to MS, allowing the analysis of underivatized amino acids. Among the numerous analytical platforms available for amino acid analysis today, we here compare three prominent approaches, being GC-MS and LC-MS after amino acid derivatization using chloroformate and HILIC-MS of underivatized amino acids. We compare and discuss practical issues as well as performance characteristics, e.g., the use of (13)C-labeled internal standards, of the different platforms and present data on their practical implementation in our laboratory. Finally, we compare the real-life applicability of all three platforms for a complex biological sample. While all three platforms are very-well suited for the analysis of complex biological samples they all show advantages and disadvantages for some analytes as discussed in detail in this manuscript.

Identification and quantification of drug-albumin adducts in serum samples from a drug exposure study in mice.

The formation of drug-protein adducts following the bioactivation of drugs to reactive metabolites has been linked to adverse drug reactions (ADRs) and is a major complication in drug discovery and development. Identification and quantification of drug-protein adducts in vivo may lead to a better understanding of drug toxicity, but is challenging due to their low abundance in the complex biological samples. Human serum albumin (HSA) is a well-known target of reactive drug metabolites due to the free cysteine on position 34 and is often the first target to be investigated in covalent drug binding studies. Presented here is an optimized strategy for targeted analysis of low-level drug-albumin adducts in serum. This strategy is based on selective extraction of albumin from serum through affinity chromatography, efficient sample treatment and clean-up using gel filtration chromatography followed by tryptic digestion and LC-MS analysis. Quantification of the level of albumin modification was performed through a comparison of non-modified and drug-modified protein based on the relative peak area of the tryptic peptide containing the free cysteine residue. The analysis strategy was applied to serum samples resulting from a drug exposure experiment in mice, which was designed to study the effects of different acetaminophen (APAP) treatments on drug toxicity. APAP is bioactivated to N-acetyl-p-benzoquinoneimine (NAPQI) in both humans and mice and is known to bind to cysteine 34 (cys34) of HSA. Analysis of the mouse serum samples revealed the presence of extremely low-level NAPQI-albumin adducts of approximately 0.2% of the total mouse serum albumin (MSA), regardless of the length of drug exposure. Due to the targeted nature of the strategy, the NAPQI-adduct formation on cys34 could be confirmed while adducts to the second free cysteine on position 579 of MSA were not detected.

Derivatization of the tricarboxylic acid cycle intermediates and analysis by online solid-phase extraction-liquid chromatography-mass spectrometry with positive-ion electrospray ionization.

The analysis of cellular metabolic processes is of fundamental biological interest. Cellular metabolites, such as the intermediates of the tricarboxylic acid (TCA) cycle, provide essential information about the metabolic state of the cell. Not only is the TCA cycle a key factor in the energy regulation within aerobic cells, it possibly also plays a role in cell signaling. This paper describes a novel derivatization strategy, using the empirically selected N-methyl-2-phenylethanamine as derivatization reagent with a carbodiimide as co-reagent, for the selective derivatization of carboxylic acids, such as the di- and tri-carboxylic acids of the TCA cycle. Optimization of the derivatization protocol is described. This procedure enables analysis of the derivatives using on-line solid-phase extraction and reversed-phase liquid chromatography in combination with sensitive positive-ion electrospray ionization mass spectrometry. The complete procedure, involving the use of core-shell silica column material, allows the rapid analysis of TCA cycle intermediates in sample matrices, here shown for pig heart tissue extracts, with a good linearity over 3-4 orders of magnitude. Detection limits range from 12 to 1000 nM, depending on the analyte.

Protein digestion optimization for characterization of drug-protein adducts using response surface modeling.

The formation of drug-protein adducts in vivo may have important clinical and toxicological implications. Consequently, there is a great interest in the detection of these adducts and the elucidation of their role in the processes leading to adverse and idiosyncratic drug reactions. Enzymatic digestion is a crucial step in bottom-up proteomics strategies for the analysis of drug-protein adducts. The chosen proteolytic enzyme and digestion conditions have a large influence on the protein coverage of the modified protein and identification of its modification site. In this work, the enzymatic digestion conditions (pH, temperature and time) of trypsin and thermolysin were optimized specifically for the characterization of Human Serum Albumin (HSA) adducts. Using a Design of Experiments (DOE), it was found that of the three optimized parameters mainly pH and temperature showed strong effects on both responses. The optimized digestion conditions were different from those obtained from the suppliers or literature. Their application to HSA adducts resulted in improved protein coverage and signal intensity regarding the peptide containing the modification site, thereby highlighting the importance of a detailed optimization of digestion conditions.

Derivatization of carboxylic acids with 4-APEBA for detection by positive-ion LC-ESI-MS(/MS) applied for the analysis of prostanoids and NSAID in urine.

In order to develop a generic positive ionization ESI LC-MS method for a variety of interesting substance classes, a new derivatization strategy for carboxylic acids was developed. The carboxylic acid group is labeled with the bromine containing 4-APEBA reagent based on carbodiimide chemistry. The derivatization reaction can be carried out under aqueous conditions, thereby greatly simplifying sample preparation. In this paper, the derivatization of carboxylic acids is exemplified for the determination of prostanoids and non-steroidal anti-inflammatory drugs (NSAID). Optimization of the derivatization conditions was studied. In order to prove the applicability of the presented approach, we applied the described protocol to urine samples from complex regional pain syndrome (CRPS) patients and were able to detect several prostanoids not visible in the urine of healthy volunteers. Further, the determination of the non-steroidal anti-inflammatory drug ibuprofen in a urine sample was possible.

Haloperidol disrupts lipid rafts and impairs insulin signaling in SH-SY5Y cells.

Haloperidol exerts its therapeutic effects basically by acting on dopamine receptors. We previously reported that haloperidol inhibits cholesterol biosynthesis in cultured cells. In the present work we investigated its effects on lipid-raft composition and functionality. In both neuroblastoma SH-SY5Y and promyelocytic HL-60 human cell lines, haloperidol inhibited cholesterol biosynthesis resulting in a decrease of the cell cholesterol content and the accumulation of different sterol intermediates (7-dehydrocholesterol, zymostenol and cholesta-8,14-dien-3beta-ol) depending on the dose of the drug. As a consequence, the cholesterol content in lipid rafts was greatly reduced, and several pre-cholesterol sterols, particularly cholesta-8,14-dien-3beta-ol, were incorporated into the cell membrane. This was accompanied by the disruption of lipid rafts, with redistribution of flotillin-1 and Fyn and the impairment of insulin-Akt signaling. Supplementing the medium with free cholesterol abrogated the effects of haloperidol on lipid-raft composition and functionality. LDL (low-density lipoprotein), a physiological vehicle of cholesterol in plasma, was much less effective in preventing the effects of haloperidol, which is attributed to the drug's inhibition of intracellular vesicular trafficking. These effects on cellular cholesterol homeostasis that ultimately result in the alteration of lipid-raft-dependent insulin signaling action may underlie some of the metabolic effects of this widely used antipsychotic.