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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

The role of electronegative low-density lipoprotein in cardiovascular diseases and its therapeutic implications.

Cardiovascular disease (CVD) is a health problem of great concern to both the public and medical authorities. Low-density lipoprotein (LDL) has been reported to play an important role in both the development and progression of CVD, but studies are underway to determine how LDL exerts its effects. In recent years, it has been found that LDL has several subfractions, each of which affects endothelial function differently; L5, the most electronegative fraction, has been shown to be unique in that it induces an atherogenic response. This review examines the current knowledge concerning the relationships between L5 and CVD and highlights the role of L5 in the pathophysiology of CVD, especially with regards to atherosclerosis.

Update on ADAMTS13 and VWF in cardiovascular and hematological disorders.

Endothelial cells (EC) respond to injury by releasing numerous factors, including von Willebrand factor (VWF). High circulating levels of unusually large VWF multimers (UL-VWFM) have strong procoagulant activity and facilitate platelet adhesion and aggregation by interacting with platelets after an acute event superimposed on peripheral arterial disease and coronary artery disease. ADAMTS13-a disintegrin-like metalloproteinase with thrombospondin motif type 1 member 13-regulates a key physiological process of coagulation in the circulation by cleaving VWF multimers into small, inactive fragments. Low levels of ADAMTS13 in the blood may play a role in cardiovascular and hematological disorders, and clarifying its role may help improve disease management. The genetic, pharmacological, physiological, and pathological aspects related to ADAMTS13/VWF have been extensively investigated. Here, we provide an update on recent findings of the relationship between ADAMTS13 and hematological/cardiovascular disorders, including thrombotic thrombocytopenic purpura, arterial thrombosis, thrombotic microangiopathy, myocardial infarction, ischemic stroke, heart failure, and hypertension.

Pathophysiological Function of ADAMTS Enzymes on Molecular Mechanism of Alzheimer's Disease.

The extracellular matrix (ECM) is an environment that has various enzymes attended in regeneration and restoration processes which is very important to sustain physiological and biological functions of central nervous system (CNS). One of the participating enzyme systems in ECM turnover is matrix metalloproteinases. A disintegrin-like and metalloproteinase with thrombospondin type 1 motifs (ADAMTS) is a unique family of ECM proteases found in mammals. Components of this family may be distinguished from the ADAM (A Disintegrin and Metalloproteinase) family based on the multiple copies of thrombospondin 1-like repeats. The considerable role of the ADAMTS in the CNS continues to develop. Evidences indicate that ADAMTS play an important role in neuroplasticity as well as nervous system pathologies such as Alzheimer's disease (AD). It is hopeful and possible that ADAMTS family members may be utilized to develop therapies for CNS pathologies, ischemic injuries, neurodegenerative and neurological diseases. To understand and provide definitive data on ADAMTS to improve structural and functional recovery in CNS injury and diseases, this review aimed to enlighten the subject extensively to reach certain information on metalloproteinases and related molecules/enzymes. It will be interesting to examine how ADAMTS expression and action would affect the initiation/progression of above-mentioned clinical situations, especially AD.

The consumption of propolis and royal jelly in preventing upper respiratory tract infections and as dietary supplementation in children.

Propolis and royal jelly (RJ), two important honeybee products, have been used commonly all over the world as traditional and ethnopharmacological nutrients since ancient times. Both of them have a lot of active ingredients which are known to be effective for several medical conditions. In this article, medical databases were searched for the usage of RJ and propolis in upper respiratory tract infections (URTI) and as a dietary supplementation, together and separately. 10-hydroxy-2-decenoic acid is the most prominent active compound showing antimicrobial effect within RJ. Caffeic acid phenethyl ester is the most famous one that shows antimicrobial and anti-inflammatory effect within propolis. When compared with propolis, RJ was found to have richer content for all three main nutrients; proteins, carbohydrates, and lipids. More clinical, experimental, and basic studies are needed to find out the best standardized mixture to cope with URTI in which RJ and propolis will be main ingredients in addition to the other secondary compounds that have health-beneficial effects.

Possible role of antioxidants and nitric oxide inhibitors against carbon monoxide poisoning: Having a clear conscience because of their potential benefits.

Carbon monoxide poisoning is one of the important emergency situations manifested by primarily acute and chronic anoxic central nervous system (CNS) injuries and other organ damages. Current descriptions and therapeutic approaches have been focused on the anoxic pathophysiology. However, this point of view incompletely explains some of the outcomes and needs to be investigated extensively. Considering this, we propose that reactive oxygen species (ROS) including especially nitric oxide (NO) are likely to be a key concept to understand the emergency related to CO poisoning and to discover new therapeutic modalities in CO toxicity. If we consider the hypothesis that ROS is involved greatly in acute and chronic toxic effects of CO on CNS and some other vital organs such as heart, it follows that the antioxidant and anti-NO therapies might give the clinicians more opportunities to prevent deep CNS injury. In support of this, we review the subject in essence and summarize clinical and experimental studies that support a key role of ROS in the explanation of pathophysiology of CO toxicity as well as new treatment modalities after CO poisoning.

The Role of ADAMTS1 and Versican in Human Myocardial Infarction: A Postmortem Study.

OBJECTIVE: To determine the role of a disintegrin and metalloproteinase with thrombospondin type 1 motif (ADAMTS1) and fragmented versican in the myocardial infarction (MI) process in humans and to evaluate the diagnostic efficacy of ADAMTS1 for postmortem diagnosis of MI. METHODS: Thirty autopsied individuals were allocated into 2 groups, namely, a study group of individuals who died of myocardial infarction (n = 20), and a control group who died of trauma (n = 10). We performed standard immunohistochemical staining on myocardial tissue specimens, studying anti-ADAMTS1, anti-versican, and anti-versican C terminal peptide sequence (DPEAAE) fragments. RESULTS: Strong, diffuse staining was observed throughout myocardial tissue for ADAMTS1 in the 2 groups. However, in the study group, we observed no expression for ADAMTS1 around fibrotic areas but detected slight staining in coagulative and necrotic zones. CONCLUSION: Similar localizations of ADAMTS and fragmented versican in human heart tissue indicate that versican presumably is cleaved by ADAMTS1. Hence, ADAMTS1 can be regarded as a new marker for postmortem differential diagnosis of MI.

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.