Evaluation of rodent models of osteoarthritis using lipidomic profiling and behavioural studies

Osteoarthritis (OA) is a complex, multifactorial, and slowly progressive disease where there is currently no effective medical treatment. Research in understanding the mechanisms of OA has been advanced by preclinical studies in rodent models of OA. Recent evidence highlights the role of different classes of lipids in OA pathogenesis. Therefore, the main aim of this thesis was to apply both targeted and untargeted (global) lipidomics mass spectrometry based an alytical methods, in conjunction with univariate and multivariate statistical analysis, in various tissues from three established rodent models of OA; meniscal transection (MNX), monosodium iodoacetate (MIA), and destabilization of the medial meniscus (DMM). The overall goal was to identify statistically differentiated lipids between controls versus OA rodents that may reflect changes in the pathophysiology of OA and associated pain. In addition, a global lipidomics workflow was developed by me, following the latest trends used within the wider metabolomics community, ensuring robustness and reproducibility in the identification of putative metabolite/lipid biomarkers for diseases. Experiments in this thesis using a targeted oxylipin liquid chromatography tandem mass spectrometry (LC-MS/MS) method showed that statistical significant changes in the levels of certain oxylipins were observed. More specifically, 11,12-DHET (mean concentration: 0.26 pmol/g in control, 0.54 pmol/g in MNX; p<0.01), 14,15-DHET (0.46 pmol/g in control, 0.75 pmol/g in MNX; p<0.05) and 8-HETE (5.46 pmol/g in control, 7.40 pmol/g in MNX; p<0.05) were statistically increased in the MNX compared to control (sham) rats in ventral spinal cord in the MNX rat model of OA. These findings are supported by literature since these three lipids exhibit pro-inflammatory properties and thus are expected to increase in the OA group where inflammation is the main feature of OA. Regarding the MIA rat model levels of other oxylipins in synovial fluid were differentially expressed in the MIA compared to saline (control) rats. Arachidonic acid (AA), (272.3 pmol/g in control, 435.3 pmol/g in MIA; p<0.05) was increased in the MIA-treated compared to saline-treated rats, while 9-HODE (4.42 pmol/g in control; 1.21 pmol/g in MIA; p<0.05) was statistically decreased in the MIA compared to saline rats. Since AA has been reported to be released from membrane phospholipids in OA, the observation that AA is statistically increased in synovial fluid in MIA- compared to saline-treated rats bears strong significance. In addition, maps of oxylipins metabolism were generated to visualize the pathways underlying the changes of lipid concentrations in plasma between control and OA rats for both MNX and MIA rat models. Therefore, applying a targeted oxylipin LC-MS/MS method in different tissues of MNX and MIA rat models of OA is a successful approach and informative about changes in pathophysiology of OA, underlying significant alterations in oxylipins concentrations. Although the global lipidomics approach was able to measure different classes of lipids that might account for differences in plasma between MNX/MIA and sham/saline-treated rats, this approach exhibited weak MVA (multivariate analysis) models. In contrast to MNX and MIA rat models, the global LC-MS lipidomics profile in plasma from a DMM mouse model of OA exhibited excellent MVA models with good prediction scores. Twenty-six statistically significant lipids were identified, using the lipidomics workflow that I have developed, and when four of these lipids were used to build Receiver Operative Curves (ROC) the model produced high prediction (84%) power in separating sham from DMM mice. The identity of these four lipids was classified as being fatty acids (FAs), sterols, sphingolipids, and diacylglycerols (DAG). In addition, MS/MS experiments were performed to confirm the identity of significant lipids. Thus, it was shown herein that applying a global lipidomics LC-MS approach in plasma from the mouse DMM model, using only a small number of mice (15 in total), can be informative about significant changes in the “lipidome” in OA and can be used as a robust means of predicting OA in mice based on their global lipidomics profile. Lastly, correlation statistical analysis was applied between levels of lipids in the various tissues, pain behaviour, and histopathology parameters in the three rodent models of OA. Although many oxylipins/lipids levels were found to be statistically correlated with the aforementioned parameters, the most striking finding is that 9-HODE and AA were both found to be positively correlated with Weight Bearing (WB), a parameter of pain behaviour, in plasma and synovial fluid in the MIA rat model of OA. Since plasma reflects systemic inflammation and synovial fluid reflects local (inflammation) 9-HODE (p<0.01 in plasma; p<0.05 in synovial fluid) and AA (p<0.01 in plasma and synovial fluid) are oxylipins that potentially depict systemic and local changes in WB differences, and subsequently in OA related pain. This finding is supported by literature since both AA and 9-HODE are both agonists of a pain receptor (i.e. transient receptor potential vanilloid 1, TRPV-1). Thus, it was proved in this thesis that correlation analysis can be used as an additional and complementary statistical tool in an effort to determine the role of lipids in OA pathogenesis in rodent models of OA. In conclusion, applying both targeted oxylipin LC-MS/MS and global lipidomics LC-MS analytical methods capable of measuring either oxylipins or the whole “lipidome” in vivo, have provided novel findings to support the involvement of these lipids in OA and associated pain

Lipidomic UPLC-MS/MS Profiles of Normal-Appearing White Matter Differentiate Primary and Secondary Progressive Multiple Sclerosis

Multiple sclerosis (MS) is a neurodegenerative inflammatory disease where an autoimmune response to components of the central nervous system leads to a loss of myelin and subsequent neurological deterioration. People with MS can develop primary or secondary progressive disease (PPMS, SPMS) and differentiation of the specific differences in the pathogenesis of these two courses, at the molecular level, is currently unclear. Recently, lipidomics studies using human biofluids, mainly plasma and cerebrospinal fluid, have highlighted a possible role for lipids in the initiation and progression of MS. However, there is a lack of lipidomics studies in MS on CNS tissues, such as normal-appearing white matter (NAWM), where local inflammation initially occurs. Herein, we developed an untargeted reverse phase ultra-performance liquid chromatography time of flight tandem mass spectrometry (RP-UPLC-TOF MSE)-based workflow, in combination with multivariate and univariate statistical analysis, to assess significant differences in lipid profiles in brain NAWM from post-mortem cases of PPMS, SPMS and controls. Groups of eight control, nine PPMS and seven SPMS NAWM samples were used. Correlation analysis of the identified lipids by RP-UPLC-TOF MSE was undertaken to remove those lipids that correlated with age, gender and post-mortem interval as confounding factors. We demonstrate that there is a significantly altered lipid profile of control cases compared with MS cases and that progressive disease, PPMS and SPMS, can be differentiated on the basis of the lipidome of NAWM with good sensitivity, specificity and prediction accuracy based on receiver operating characteristic (ROC) curve analysis. Metabolic pathway analysis revealed that the most altered lipid pathways between PPMS and SPMS were glycerophospholipid metabolism, glycerophosphatidyl inositol (GPI) anchor synthesis and linoleic acid metabolism. Further understanding of the impact of these lipid alterations described herein associated with progression will provide an increased understanding of the mechanisms underpinning progression and highlight possible new therapeutic targets

Lipidomic identification of plasma lipids associated with pain behaviour and pathology in a mouse model of osteoarthritis

© 2020, The Author(s). Introduction: Osteoarthritis (OA) is the most common form of joint disease, causing pain and disability. Previous studies have demonstrated the role of lipid mediators in OA pathogenesis. Objectives: To explore potential alterations in the plasma lipidomic profile in an established mouse model of OA, with a view to identification of potential biomarkers of pain and/or pathology. Methods: Pain behaviour was assessed following destabilisation of the medial meniscus (DMM) model of OA (n = 8 mice) and compared to sham controls (n = 7). Plasma and knee joints were collected at 16weeks post-surgery. Plasma samples were analysed using ultra-high performance liquid chromatography accurate mass high resolution mass spectrometry (UHPLC-HR-MS) to identify potential differences in the lipidome, using multivariate and univariate statistical analyses. Correlations between pain behaviour, joint pathology and levels of lipids were investigated. Results: 24 lipids, predominantly from the lipid classes of cholesterol esters (CE), fatty acids (FA), phosphatidylcholines (PC), N-acylethanolamines (NAE) and sphingomyelins (SM), were differentially expressed in DMM plasma compared to sham plasma. Six of these lipids which were increased in the DMM model were identified as CE(18:2), CE(20:4), CE(22:6), PC(18:0/18:2), PC(38:7) and SM(d34:1). CEs were positively correlated with pain behaviour and all six lipid species were positively correlated with cartilage damage. Pathways shown to be involved in altered lipid homeostasis in OA were steroid biosynthesis and sphingolipid metabolism. Conclusion: We identify plasma lipid species associated with pain and/or pathology in a DMM model of OA

Targeting the D-series resolvin receptor system for the treatment of osteoarthritic pain

Objective: Pain is a major symptom of osteoarthritis (OA); current analgesics either do not offer adequate pain relief or are associated with serious side effects. Herein we have investigated the therapeutic potential of targeting the resolvin receptor system to modify OA pain and pathology. Methods: Gene expression of two resolvin receptors (ALX and ChemR23) was quantified in synovia and medial tibial plateau collected from patients at joint replacement for OA. Two models of OA joint pain were used for mechanistic studies. Gene expression in the periphery and CNS were quantified. Effects of exogenous administration of the D-series resolvin precursor 17(R)-hydroxy Docosahexaenoic Acid (17(R)-HDoHE on pain behaviour, joint pathology, spinal microglia and astroglyosis were quantified. Plasma levels of relevant lipids, resolvin D2, 17R-HDoHE and arachidonic acid was determined in rats using LC-MS-MS. Results: There was a positive correlation between resolvin receptor and IL6 expression in human OA synovia and medial tibial plateau. In the rat, synovia gene expression of ALX was positively correlated with IL1β, TNFα and COX2. Treatment with 17(R)-HDoHE reversed established pain behaviour in two models of OA pain, but not joint pathology. This was associated with a significant elevation in plasma levels of resolvin D2 and a significant reduction in astrogliosis in the spinal cord in the MIA model. Conclusion: Our preclinical data demonstrate robust analgesics effects of activating the D series resolvin pathways in two different animal models of OA. Our data support a predominant central mechanism of action in this clinically relevant model of OA pain

Evaluation of rodent models of osteoarthritis using lipidomic profiling and behavioural studies

Osteoarthritis (OA) is a complex, multifactorial, and slowly progressive disease where there is currently no effective medical treatment. Research in understanding the mechanisms of OA has been advanced by preclinical studies in rodent models of OA. Recent evidence highlights the role of different classes of lipids in OA pathogenesis. Therefore, the main aim of this thesis was to apply both targeted and untargeted (global) lipidomics mass spectrometry based an alytical methods, in conjunction with univariate and multivariate statistical analysis, in various tissues from three established rodent models of OA; meniscal transection (MNX), monosodium iodoacetate (MIA), and destabilization of the medial meniscus (DMM). The overall goal was to identify statistically differentiated lipids between controls versus OA rodents that may reflect changes in the pathophysiology of OA and associated pain. In addition, a global lipidomics workflow was developed by me, following the latest trends used within the wider metabolomics community, ensuring robustness and reproducibility in the identification of putative metabolite/lipid biomarkers for diseases. Experiments in this thesis using a targeted oxylipin liquid chromatography tandem mass spectrometry (LC-MS/MS) method showed that statistical significant changes in the levels of certain oxylipins were observed. More specifically, 11,12-DHET (mean concentration: 0.26 pmol/g in control, 0.54 pmol/g in MNX; p<0.01), 14,15-DHET (0.46 pmol/g in control, 0.75 pmol/g in MNX; p<0.05) and 8-HETE (5.46 pmol/g in control, 7.40 pmol/g in MNX; p<0.05) were statistically increased in the MNX compared to control (sham) rats in ventral spinal cord in the MNX rat model of OA. These findings are supported by literature since these three lipids exhibit pro-inflammatory properties and thus are expected to increase in the OA group where inflammation is the main feature of OA. Regarding the MIA rat model levels of other oxylipins in synovial fluid were differentially expressed in the MIA compared to saline (control) rats. Arachidonic acid (AA), (272.3 pmol/g in control, 435.3 pmol/g in MIA; p<0.05) was increased in the MIA-treated compared to saline-treated rats, while 9-HODE (4.42 pmol/g in control; 1.21 pmol/g in MIA; p<0.05) was statistically decreased in the MIA compared to saline rats. Since AA has been reported to be released from membrane phospholipids in OA, the observation that AA is statistically increased in synovial fluid in MIA- compared to saline-treated rats bears strong significance. In addition, maps of oxylipins metabolism were generated to visualize the pathways underlying the changes of lipid concentrations in plasma between control and OA rats for both MNX and MIA rat models. Therefore, applying a targeted oxylipin LC-MS/MS method in different tissues of MNX and MIA rat models of OA is a successful approach and informative about changes in pathophysiology of OA, underlying significant alterations in oxylipins concentrations. Although the global lipidomics approach was able to measure different classes of lipids that might account for differences in plasma between MNX/MIA and sham/saline-treated rats, this approach exhibited weak MVA (multivariate analysis) models. In contrast to MNX and MIA rat models, the global LC-MS lipidomics profile in plasma from a DMM mouse model of OA exhibited excellent MVA models with good prediction scores. Twenty-six statistically significant lipids were identified, using the lipidomics workflow that I have developed, and when four of these lipids were used to build Receiver Operative Curves (ROC) the model produced high prediction (84%) power in separating sham from DMM mice. The identity of these four lipids was classified as being fatty acids (FAs), sterols, sphingolipids, and diacylglycerols (DAG). In addition, MS/MS experiments were performed to confirm the identity of significant lipids. Thus, it was shown herein that applying a global lipidomics LC-MS approach in plasma from the mouse DMM model, using only a small number of mice (15 in total), can be informative about significant changes in the “lipidome” in OA and can be used as a robust means of predicting OA in mice based on their global lipidomics profile. Lastly, correlation statistical analysis was applied between levels of lipids in the various tissues, pain behaviour, and histopathology parameters in the three rodent models of OA. Although many oxylipins/lipids levels were found to be statistically correlated with the aforementioned parameters, the most striking finding is that 9-HODE and AA were both found to be positively correlated with Weight Bearing (WB), a parameter of pain behaviour, in plasma and synovial fluid in the MIA rat model of OA. Since plasma reflects systemic inflammation and synovial fluid reflects local (inflammation) 9-HODE (p<0.01 in plasma; p<0.05 in synovial fluid) and AA (p<0.01 in plasma and synovial fluid) are oxylipins that potentially depict systemic and local changes in WB differences, and subsequently in OA related pain. This finding is supported by literature since both AA and 9-HODE are both agonists of a pain receptor (i.e. transient receptor potential vanilloid 1, TRPV-1). Thus, it was proved in this thesis that correlation analysis can be used as an additional and complementary statistical tool in an effort to determine the role of lipids in OA pathogenesis in rodent models of OA. In conclusion, applying both targeted oxylipin LC-MS/MS and global lipidomics LC-MS analytical methods capable of measuring either oxylipins or the whole “lipidome” in vivo, have provided novel findings to support the involvement of these lipids in OA and associated pain

Untargeted Metabolomics Pilot Study Using UHPLC-qTOF MS Profile in Sows’ Urine Reveals Metabolites of Bladder Inflammation

Urinary tract infections (UTI) of sows (characterized by ascending infections of the urinary bladder (cyst), ureters, and renal pelvis), are major health issues with a significant economic impact to the swine industry. The current detection of UTI incidents lacks sensitivity; thus, UTIs remain largely under-diagnosed. The value of metabolomics in unraveling the mechanisms of sow UTI has not yet been established. This study aims to investigate the urine metabolome of sows for UTI biomarkers. Urine samples were collected from 58 culled sows from a farrow-to-finish herd in Greece. Urine metabolomic profiles in 31 healthy controls and in 27 inflammatory ones were evaluated. UHPLC-qTOF MS/MS was applied for the analysis with a combination of multivariate and univariate statistical analysis. Eighteen potential markers were found. The changes in several urine metabolites classes (nucleosides, indoles, isoflavones, and dipeptides), as well as amino-acids allowed for an adequate discrimination between the study groups. Identified metabolites were involved in purine metabolism; phenylalanine; tyrosine and tryptophan biosynthesis; and phenylalanine metabolism. Through ROC analysis it was shown that the 18 identified metabolite biomarkers exhibited good predictive accuracy. In summary, our study provided new information on the potential targets for predicting early and accurate diagnosis of UTI. Further, this information also sheds light on how it could be applied in live animals