Is Serum Caveolin-1 a Useful Biomarker for Progression in Patients with Colorectal Cancer?.

BACKGROUND: Colorectal cancer (CRC) is the third most common cause of cancer diagnosed in males and the second in females. Survival is strongly related to stage at diagnosis. There is an urgent need to find a noninvasive biomarker that can be commonly applied for screening diagnosis, early detection of recurrence, and monitoring of metastatic CRC. Protein caveolin-1 (CAV-1) has been known to be expressed abnormally in colon cancer and appears to contribute to aberrant signaling and protein trafficking. There are controversial results regarding the role of CAV-1 in cancer. We hypothesized that levels of CAV-1 in serum of patients with CRC might be important to estimate the progression of the disease. Therefore, the purpose of this study is to investigate whether serum CAV-1 might be used as a factor determining progression of CRC. METHODS: A total of 61 patients with CRC (26 male, 35 female) and 46 controls (38 male, 8 female) were enrolled. Serum CAV-1 levels were measured by ELISA. The relationship between CAV-1 and progression-free survival (PFS) was analyzed with use of receiver operating characteristic (ROC) and Kaplan-Meier analysis. Results were given as median (95% CI). Mann-Whitney test was used for the comparison of groups. RESULTS: CAV-1 levels were found to be 11.5 ng/mL (10.4-12.9) in CRC and 11.9 ng/mL (10.7-14.4) in controls (p = 0.465). The serum CAV-1 levels in CRC patients with disease progression and without progression were respectively 10.0 ng/mL (8.5-11.3) and 12.2 ng/mL (11.1-14.8) (p = 0.023). In ROC analysis, if CAV-1 levels are equal or lesser than 10.73 ng/mL, it might show presence of progression with a sensitivity 73.3% and specificity 66.7% in patients with CRC (area under the ROC curve (AUC) = 0.697, p = 0.005). The mean PFS time was found to be 29.7 months (19.8-39.7, 95% CI for the mean) in patients who have CAV-1 level ≤ 10.73 ng/mL and 61.9 months (44.2-79.6) in patients who have CAV-1 level > 10.73 ng/mL [hazard ratios (HR) with 95% CI = 3.49 (1.26 - 9.68) (p = 0.017)]. CONCLUSIONS: Our results strongly suggest that CAV-1 levels might be used as a marker to determine progression of CRC. When considered in combination with other biomarkers of CRC, CAV-1 is clinically informative and instructive.

The Investigation of a Disintegrin and Metalloproteinase with ThromboSpondin Motifs (ADAMTS) 1, 5 and 16 in Thoracic Aortic Aneurysms and Dissections.

BACKGROUND: Disintegrin-like and Metalloproteinase with Thrombospondin Motifs (ADAMTS) proteins that are fundamentally located in the extracellular matrix (ECM) have critical roles on different cellular processes by altering the ECM architecture. It has been known that expression of some members of these proteinases increases in aneurismal and dissectional aortic tissue. The purpose of this study is to investigate ADAMTS1, 5, 16 and tissue inhibitors of metalloproteinases-1, -2 (TIMP-1, -2) levels in aortic tissue obtained from patients with thoracic aortic aneurysms and dissections and to achieve new insights about the function of ADAMTS family members. METHODS: We investigated ADAMTS1, 5, and 16 expression in human thoracic aortic aneurysms (TAA) (n = 22), thoracic aortic dissections (TAD) (n = 12), and thoracic aortas from age-matched control organ donors (n = 6) (a total number of 34 cases and 6 controls). The expression levels of ADAMTS proteins were determined by Western blot technique using anti-ADAMTS1, ADAMTS5, ADAMTS16, TIMP-1 and TIMP-2 antibodies. RESULTS: ADAMTS1, 5, and 16 protein expressions were significantly higher in thoracic aortic aneurysm and dissection tissues compared to control aortic tissues. Furthermore, TIMP-1 protein levels decreased in TAA and TAD tissues, TIMP-2 did not change. CONCLUSIONS: Under the light of our findings, increased expression of ADAMTS1, 5, and 16 proteins may promote deceleration in thoracic aortic aneurysm progression. This is the first study that demonstrates ADAMTS5 and ADAMTS16 proteolytic activity in aneurysm and dissection.

Caffeic acid phenethyl ester as a protective agent against nephrotoxicity and/or oxidative kidney damage: a detailed systematic review.

Caffeic acid phenethyl ester (CAPE), an active component of propolis, has been attracting the attention of different medical and pharmaceutical disciplines in recent years because of its antioxidant, anti-inflammatory, antiproliferative, cytotoxic, antiviral, antifungal, and antineoplastic properties. One of the most studied organs for the effects of CAPE is the kidney, particularly in the capacity of this ester to decrease the nephrotoxicity induced by several drugs and the oxidative injury after ischemia/reperfusion (I/R). In this review, we summarized and critically evaluated the current knowledge regarding the protective effect of CAPE in nephrotoxicity induced by several special medicines such as cisplatin, doxorubicin, cyclosporine, gentamycin, methotrexate, and other causes leading to oxidative renal injury, namely, I/R models and senility.

In vivo and in vitro antineoplastic actions of caffeic acid phenethyl ester (CAPE): therapeutic perspectives.

Cancer prevention and treatment strategies have attracted increasing interest. Caffeic acid phenethyl ester (CAPE), an active component of propolis extract, specifically inhibits NF-κB at µM concentrations and shows ability to stop 5-lipoxygenase-catalyzed oxygenation of linoleic acid and arachidonic acid. Previous studies have demonstrated that CAPE exhibits antioxidant, antiinflammatory, antiproliferative, cytostatic, antiviral, antibacterial, antifungal, and, most improtantly, antineoplastic properties. The primary goal of the present review is to summarize and critically evaluate the current knowledge regarding the anticancer effect of CAPE in different cancer types.

Augmentation of ADAMTS9 gene expression by IL-1ß is reversed by NFκB and MAPK inhibitors, but not PI3 kinase inhibitors.

The pathways involved in the regulation of a disintegrin and metalloproteinase with thrombospondin motifs 9 (ADAMTS9) expression have not yet been elucidated. Therefore, the aim of this study was to investigate the involvement of nuclear factor-κB (NF-κB), mitogen activated protein kinases (MAPK) and Phosphatidylinositol 3-kinase (PI3 kinase) in ADAMTS9 gene regulation, with special focus on the involvement of NF-κB in IL-1ß-induced ADAMTS9 expression. The OUMS-27 chondrosarcoma cells were exposed to IL-1ß. They were pretreated with 20 µM PD98059 (specific inhibitor of p44/42 kinase), 10 µM SB203580 (specific inhibitor of p38 kinase), 20 µM SB600125 (MAPK inhibitor), and 1 µM Wortmannin and 10 µM LY294002 (specific inhibitors of PI3 kinase) for 30 min and subsequently incubated with IL-1ß. For the effects of NF-κB and IκB inhibitors, cells were pretreated with curcumin or BAY117085 for 30 min and subsequently incubated with IL-1ß. BAY117085 and different concentrations of curcumin were applied to the cells just after the first experiment to determine their concentration effect on ADAMTS9 gene expression. After total RNA was extracted, they were reversely transcribed with random primers and then real-time polymerase chain reaction (PCR) was performed on cDNA samples. There was a significant difference between control and stimulated cells in terms of ADAMTS9/ß-actin ratio. Wortmannin and LY294002 did not have any repressive effect on the OUMS-27 whereas SB203580 and SP600125 were found to decrease the expression of ADAMTS9 gene. BAY 117085 and curcumin, which are two NF-κB inhibitors, led to a decrease in the ratio of ADAMTS9/ß-actin. As a conclusion, the pathways MAPK and NF-κB were thought to be responsible pathways for the induction of ADAMTS9 gene.

Metabolomics: An Emerging "Omics" Platform for Systems Biology and Its Implications for Huntington Disease Research.

Huntington's disease (HD) is a progressive, fatal neurodegenerative disease characterized by motor, cognitive, and psychiatric symptoms. The precise mechanisms of HD progression are poorly understood; however, it is known that there is an expansion of the trinucleotide cytosine-adenine-guanine (CAG) repeat in the Huntingtin gene. Important new strategies are of paramount importance to identify early biomarkers with predictive value for intervening in disease progression at a stage when cellular dysfunction has not progressed irreversibly. Metabolomics is the study of global metabolite profiles in a system (cell, tissue, or organism) under certain conditions and is becoming an essential tool for the systemic characterization of metabolites to provide a snapshot of the functional and pathophysiological states of an organism and support disease diagnosis and biomarker discovery. This review briefly highlights the historical progress of metabolomic methodologies, followed by a more detailed review of the use of metabolomics in HD research to enable a greater understanding of the pathogenesis, its early prediction, and finally the main technical platforms in the field of metabolomics.

Lipids and lipoproteins may play a role in the neuropathology of Alzheimer's disease.

Alzheimer's disease (AD) and other classes of dementia are important public health problems with overwhelming social, physical, and financial effects for patients, society, and their families and caregivers. The pathophysiology of AD is poorly understood despite the extensive number of clinical and experimental studies. The brain's lipid-rich composition is linked to disturbances in lipid homeostasis, often associated with glucose and lipid abnormalities in various neurodegenerative diseases, including AD. Moreover, elevated low-density lipoprotein (LDL) cholesterol levels may be related to a higher probability of AD. Here, we hypothesize that lipids, and electronegative LDL (L5) in particular, may be involved in the pathophysiology of AD. Although changes in cholesterol, triglyceride, LDL, and glucose levels are seen in AD, the cause remains unknown. We believe that L5-the most electronegative subfraction of LDL-may be a crucial factor in understanding the involvement of lipids in AD pathology. LDL and L5 are internalized by cells through different receptors and mechanisms that trigger separate intracellular pathways. One of the receptors involved in L5 internalization, LOX-1, triggers apoptotic pathways. Aging is associated with dysregulation of lipid homeostasis, and it is believed that alterations in lipid metabolism contribute to the pathogenesis of AD. Proposed mechanisms of lipid dysregulation in AD include mitochondrial dysfunction, blood-brain barrier disease, neuronal signaling, inflammation, and oxidative stress, all of which lead ultimately to memory loss through deficiency of synaptic integration. Several lipid species and their receptors have essential functions in AD pathogenesis and may be potential biomarkers.

Association of Metabolomic Biomarkers with Sleeve Gastrectomy Weight Loss Outcomes.

This prospective observational study aimed to evaluate the association of metabolomic alterations with weight loss outcomes following sleeve gastrectomy (SG). We evaluated the metabolomic profile of serum and feces prior to SG and three months post-SG, along with weight loss outcomes in 45 adults with obesity. The percent total weight loss for the highest versus the lowest weight loss tertiles (T3 vs. T1) was 17.0 ± 1.3% and 11.1 ± 0.8%, p < 0.001. Serum metabolite alterations specific to T3 at three months included a decrease in methionine sulfoxide concentration as well as alterations to tryptophan and methionine metabolism (p < 0.03). Fecal metabolite changes specific to T3 included a decrease in taurine concentration and perturbations to arachidonic acid metabolism, and taurine and hypotaurine metabolism (p < 0.002). Preoperative metabolites were found to be highly predictive of weight loss outcomes in machine learning algorithms, with an average area under the curve of 94.6% for serum and 93.4% for feces. This comprehensive metabolomics analysis of weight loss outcome differences post-SG highlights specific metabolic alterations as well as machine learning algorithms predictive of weight loss. These findings could contribute to the development of novel therapeutic targets to enhance weight loss outcomes after SG.

The potential usage of caffeic acid phenethyl ester (CAPE) against chemotherapy-induced and radiotherapy-induced toxicity.

Protection of the patients against the side effects of chemotherapy and radiotherapy regimens has attracted increasing interest of clinicians and practitioners. Caffeic acid phenethyl ester (CAPE), which is extracted from the propolis of honeybee hives as an active component, specifically inhibits nuclear factor κB at micromolar concentrations and show ability to stop 5-lipoxygenase-catalysed oxygenation of linoleic acid and arachidonic acid. CAPE has antiinflammatory, antiproliferative, antioxidant, cytostatic, antiviral, antibacterial, antifungal and antineoplastic properties. The purpose of this review is to summarize in vivo and in vitro usage of CAPE to prevent the chemotherapy-induced and radiotherapy-induced damages and side effects in experimental animals and to develop a new approach for the potential usage of CAPE in clinical trial as a protective agent during chemotherapy and radiotherapy regimens.

Methylated Cytochrome P450 and the Solute Carrier Family of Genes Correlate With Perturbations in Bile Acid Metabolism in Parkinson's Disease.

Parkinson's disease (PD) is second most prevalent neurodegenerative disorder following Alzheimer's disease. Parkinson's disease is hypothesized to be caused by a multifaceted interplay between genetic and environmental factors. Herein, and for the first time, we describe the integration of metabolomics and epigenetics (genome-wide DNA methylation; epimetabolomics) to profile the frontal lobe from people who died from PD and compared them with age-, and sex-matched controls. We identified 48 metabolites to be at significantly different concentrations (FDR q < 0.05), 4,313 differentially methylated sites [5'-C-phosphate-G-3' (CpGs)] (FDR q < 0.05) and increased DNA methylation age in the primary motor cortex of people who died from PD. We identified Primary bile acid biosynthesis as the major biochemical pathway to be perturbed in the frontal lobe of PD sufferers, and the metabolite taurine (p-value = 5.91E-06) as being positively correlated with CpG cg14286187 (SLC25A27; CYP39A1) (FDR q = 0.002), highlighting previously unreported biochemical changes associated with PD pathogenesis. In this novel multi-omics study, we identify regulatory mechanisms which we believe warrant future translational investigation and central biomarkers of PD which require further validation in more accessible biomatrices.

Accuracy and uniformity of the nomenclature of biogenic amines and polyamines in metabolomics studies: A preliminary study.

Metabolomics is one of the newest areas in biochemistry dedicated to investigating small biomolecules in biofluids, tissues, and cells. Cutting edge instruments used in metabolomics studies make it possible to identify thousands of biomolecules and determine their interactions with biological networks. This tremendous area has increased the significance of accurate chemical nomenclature of compounds. Therefore, the classification of the organic molecules has become one of the most important issues in the field. Biogenic amines are nitrogenous compounds of low molecular weight formed by the decarboxylation of amino acids or by the amination and the transamination of aldehydes and ketones during normal metabolic processes. This letter covers the topic of nomenclature with respect to the current usage of biogenic amines in scientific literature. We use metabolomics as an example of field reporting data on trace levels of molecules that may be miscategorized in primary literature. We suggest that the incorrect classification of molecules will influence science education adversely because resources used for teaching are drawn from primary literature references that may contain errors.

Lipid Profiling of Alzheimer's Disease Brain Highlights Enrichment in Glycerol(phospho)lipid, and Sphingolipid Metabolism.

Alzheimer's disease (AD) is reported to be closely linked with abnormal lipid metabolism. To gain a more comprehensive understanding of what causes AD and its subsequent development, we profiled the lipidome of postmortem (PM) human brains (neocortex) of people with a range of AD pathology (Braak 0-6). Using high-resolution mass spectrometry, we employed a semi-targeted, fully quantitative lipidomics profiling method (Lipidyzer) to compare the biochemical profiles of brain tissues from persons with mild AD (n = 15) and severe AD (AD; n = 16), and compared them with age-matched, cognitively normal controls (n = 16). Univariate analysis revealed that the concentrations of 420 lipid metabolites significantly (p < 0.05; q < 0.05) differed between AD and controls. A total of 49 lipid metabolites differed between mild AD and controls, and 439 differed between severe AD and mild AD. Interestingly, 13 different subclasses of lipids were significantly perturbed, including neutral lipids, glycerolipids, glycerophospholipids, and sphingolipids. Diacylglycerol (DAG) (14:0/14:0), triacylglycerol (TAG) (58:10/FA20:5), and TAG (48:4/FA18:3) were the most notably altered lipids when AD and control brains were compared (p < 0.05). When we compare mild AD and control brains, phosphatidylethanolamine (PE) (p-18:0/18:1), phosphatidylserine (PS) (18:1/18:2), and PS (14:0/22:6) differed the most (p < 0.05). PE (p-18:0/18:1), DAG (14:0/14:0), and PS (18:1/20:4) were identified as the most significantly perturbed lipids when AD and mild AD brains were compared (p < 0.05). Our analysis provides the most extensive lipid profiling yet undertaken in AD brain tissue and reveals the cumulative perturbation of several lipid pathways with progressive disease pathology. Lipidomics has considerable potential for studying AD etiology and identifying early diagnostic biomarkers.

Why are cardiovascular diseases more common among patients with severe mental illness? The potential involvement of electronegative low-density lipoprotein (LDL) L5.

Despite tremendous efforts of experimental and clinical studies and knowledge, the pathophysiology of severe mental illness (SMI), including bipolar disorder (BD), unipolar depression (mood disorders, MD), and schizophrenia (SCZ), remains poorly understood. Besides their chronic course and high prevalence in society, mental and somatic comorbidities are really serious problems; patients with these disorders have increased risk of cardiovascular (CV) diseases (CVD) including coronary artery diseases (CAD, i.e. myocardial infarction and angina), stroke, sudden cardiac death, hypertension, cardiomyopathy, arrhythmia, and thromboembolic disease. Although it is determined that triglycerides, cholesterol, glucose, and low-density lipoprotein (LDL) levels are increased in MD and SCZ, the underlying reason remains unknown. Considering this, we propose that electronegative LDL (L5) is probably the main crucial element to understanding CVD induced by SMI and to discovering novel remedial approaches for these diseases. When it is hypothesized that L5 is greatly presupposed in CV system abnormalities, it follows that the anti-L5 therapies and even antioxidant treatment options may open new therapeutic opportunities to prevent CVD diseases secondary to SMI. In this review article, we tried to bring a very original subject to the attention of readers who are interested in lipoprotein metabolism in terms of experimental, clinical, and cell culture studies that corroborate the involvement of L5 in physiopathology of CVD secondary to SMI and also the new therapeutic approaches for these disorders.

The Biochemical Profile of Post-Mortem Brain from People Who Suffered from Epilepsy Reveals Novel Insights into the Etiopathogenesis of the Disease.

Epilepsy not-otherwise-specified (ENOS) is one of the most common causes of chronic disorders impacting human health, with complex multifactorial etiology and clinical presentation. Understanding the metabolic processes associated with the disorder may aid in the discovery of preventive and therapeutic measures. Post-mortem brain samples were harvested from the frontal cortex (BA8/46) of people diagnosed with ENOS cases (n = 15) and age- and sex-matched control subjects (n = 15). We employed a targeted metabolomics approach using a combination of proton nuclear magnetic resonance (1H-NMR) and direct injection/liquid chromatography tandem mass spectrometry (DI/LC-MS/MS). We accurately identified and quantified 72 metabolites using 1H-NMR and 159 using DI/LC-MS/MS. Among the 212 detected metabolites, 14 showed significant concentration changes between ENOS cases and controls (p < 0.05; q < 0.05). Of these, adenosine monophosphate and O-acetylcholine were the most commonly selected metabolites used to develop predictive models capable of discriminating between ENOS and unaffected controls. Metabolomic set enrichment analysis identified ethanol degradation, butyrate metabolism and the mitochondrial beta-oxidation of fatty acids as the top three significantly perturbed metabolic pathways. We report, for the first time, the metabolomic profiling of postmortem brain tissue form patients who died from epilepsy. These findings can potentially expand upon the complex etiopathogenesis and help identify key predictive biomarkers of ENOS.

Targeted Metabolic Profiling of Urine Highlights a Potential Biomarker Panel for the Diagnosis of Alzheimer's Disease and Mild Cognitive Impairment: A Pilot Study.

The lack of sensitive and specific biomarkers for the early detection of mild cognitive impairment (MCI) and Alzheimer's disease (AD) is a major hurdle to improving patient management. A targeted, quantitative metabolomics approach using both 1H NMR and mass spectrometry was employed to investigate the performance of urine metabolites as potential biomarkers for MCI and AD. Correlation-based feature selection (CFS) and least absolute shrinkage and selection operator (LASSO) methods were used to develop biomarker panels tested using support vector machine (SVM) and logistic regression models for diagnosis of each disease state. Metabolic changes were investigated to identify which biochemical pathways were perturbed as a direct result of MCI and AD in urine. Using SVM, we developed a model with 94% sensitivity, 78% specificity, and 78% AUC to distinguish healthy controls from AD sufferers. Using logistic regression, we developed a model with 85% sensitivity, 86% specificity, and an AUC of 82% for AD diagnosis as compared to cognitively healthy controls. Further, we identified 11 urinary metabolites that were significantly altered to include glucose, guanidinoacetate, urocanate, hippuric acid, cytosine, 2- and 3-hydroxyisovalerate, 2-ketoisovalerate, tryptophan, trimethylamine N oxide, and malonate in AD patients, which are also capable of diagnosing MCI, with a sensitivity value of 76%, specificity of 75%, and accuracy of 81% as compared to healthy controls. This pilot study suggests that urine metabolomics may be useful for developing a test capable of diagnosing and distinguishing MCI and AD from cognitively healthy controls.

Metabolic Profiling of CSF from People Suffering from Sporadic and LRRK2 Parkinson's Disease: A Pilot Study.

CSF from unique groups of Parkinson's disease (PD) patients was biochemically profiled to identify previously unreported metabolic pathways linked to PD pathogenesis, and novel biochemical biomarkers of the disease were characterized. Utilizing both 1H NMR and DI-LC-MS/MS we quantitatively profiled CSF from patients with sporadic PD (n = 20) and those who are genetically predisposed (LRRK2) to the disease (n = 20), and compared those results with age and gender-matched controls (n = 20). Further, we systematically evaluated the utility of several machine learning techniques for the diagnosis of PD. 1H NMR and mass spectrometry-based metabolomics, in combination with bioinformatic analyses, provided useful information highlighting previously unreported biochemical pathways and CSF-based biomarkers associated with both sporadic PD (sPD) and LRRK2 PD. Results of this metabolomics study further support our group's previous findings identifying bile acid metabolism as one of the major aberrant biochemical pathways in PD patients. This study demonstrates that a combination of two complimentary techniques can provide a much more holistic view of the CSF metabolome, and by association, the brain metabolome. Future studies for the prediction of those at risk of developing PD should investigate the clinical utility of these CSF-based biomarkers in more accessible biomatrices. Further, it is essential that we determine whether the biochemical pathways highlighted here are recapitulated in the brains of PD patients with the aim of identifying potential therapeutic targets.

A Community-Based Study Identifying Metabolic Biomarkers of Mild Cognitive Impairment and Alzheimer's Disease Using Artificial Intelligence and Machine Learning.

BACKGROUND: Currently, there is no objective, clinically available tool for the accurate diagnosis of Alzheimer's disease (AD). There is a pressing need for a novel, minimally invasive, cost friendly, and easily accessible tool to diagnose AD, assess disease severity, and prognosticate course. Metabolomics is a promising tool for discovery of new, biologically, and clinically relevant biomarkers for AD detection and classification. OBJECTIVE: Utilizing artificial intelligence and machine learning, we aim to assess whether a panel of metabolites as detected in plasma can be used as an objective and clinically feasible tool for the diagnosis of mild cognitive impairment (MCI) and AD. METHODS: Using a community-based sample cohort acquired from different sites across the US, we adopted an approach combining Proton Nuclear Magnetic Resonance Spectroscopy (1H NMR), Liquid Chromatography coupled with Mass Spectrometry (LC-MS) and various machine learning statistical approaches to identify a biomarker panel capable of identifying those patients with AD and MCI from healthy controls. RESULTS: Of the 212 measured metabolites, 5 were identified as optimal to discriminate between controls, and individuals with MCI or AD. Our models performed with AUC values in the range of 0.72-0.76, with the sensitivity and specificity values ranging from 0.75-0.85 and 0.69-0.81, respectively. Univariate and pathway analysis identified lipid metabolism as the most perturbed biochemical pathway in MCI and AD. CONCLUSION: A comprehensive method of acquiring metabolomics data, coupled with machine learning techniques, has identified a strong panel of diagnostic biomarkers capable of identifying individuals with MCI and AD. Further, our data confirm what other groups have reported, that lipid metabolism is significantly perturbed in those individuals suffering with dementia. This work may provide additional insight into AD pathogenesis and encourage more in-depth analysis of the AD lipidome.

Evidence that the Kennedy and polyamine pathways are dysregulated in human brain in cases of dementia with Lewy bodies.

Disruptions of brain metabolism are considered integral to the pathogenesis of dementia, but thus far little is known of how dementia with Lewy bodies (DLB) impacts the brain metabolome. DLB is less well known than other neurodegenerative diseases such as Alzheimer's and Parkinson's disease which is perhaps why it is under-investigated. This exploratory study aimed to address current knowledge gaps in DLB research and search for potentially targetable biochemical pathways for therapeutics. It also aimed to better understand metabolic similarities and differences with other dementias. Combined metabolomic analyses of 1H NMR and tandem mass spectrometry of neocortical post-mortem brain tissue (Brodmann region 7) from autopsy confirmed cases of DLB (n = 15) were compared with age/gender-matched, non-cognitively impaired healthy controls (n = 30). Following correction for multiple comparisons, only 2 metabolites from a total of 219 measured compounds significantly differed. Putrescine was suppressed (55.4%) in DLB and O-phosphocholine was elevated (52.5%). We identified a panel of 5 metabolites (PC aa C38:4, O-Phosphocholine, putrescine, 4-Aminobutyrate, and SM C16:0) capable of accurately discriminating between DLB and control subjects. Deep Learning (DL) provided the best predictive model following 10-fold cross validation (AUROC (95% CI) = 0.80 (0.60-1.0)) with sensitivity and specificity equal to 0.92 and 0.88, respectively. Altered brain levels of putrescine and O-phosphocholine indicate that the Kennedy pathway and polyamine metabolism are perturbed in DLB. These are accompanied by a consistent underlying trend of lipid dysregulation. As yet it is unclear whether these are a cause or consequence of DLB onset.