Project description:Multiple sclerosis is a chronic demyelinating disease of the central nervous system. There is a need for new circulating biomarkers for multiple sclerosis, in particular, markers that differentiate multiple sclerosis subtypes (relapsing-remitting, secondary progressive and primary progressive multiple sclerosis), as this can help in making treatment decisions. In this study, we explore two classes of potential multiple sclerosis biomarkers-proteins and microRNAs-circulating in the cerebrospinal fluid and serum. Targeted medium-throughput proteomics (92 proteins) and microRNA sequencing were performed on serum samples collected in a cross-sectional case-control cohort (cohort I, controls n = 30, multiple sclerosis n = 75) and a prospective multiple sclerosis cohort (cohort II, n = 93). For cohort I, we also made these measurements in paired cerebrospinal fluid samples. In the cohort I cerebrospinal fluid, we observed differences between multiple sclerosis and controls for 13 proteins, including some previously described to be markers for multiple sclerosis [e.g. CD27, C-X-C motif chemokine 13 (CXCL13) and interleukin-7 (IL7)]. No microRNAs were significantly differentially expressed between multiple sclerosis and controls in the cerebrospinal fluid. In serum, 10 proteins, including angiopoietin-1 receptor (TIE2), and 16 microRNAs were significantly different between relapsing-remitting multiple sclerosis and secondary progressive multiple sclerosis after performing a meta-analysis combining both cohorts. In the prospective part of the study, participants with relapsing-remitting multiple sclerosis were followed for around 3 years, during which time 12 participants converted to secondary progressive multiple sclerosis. In these longitudinally collected serum samples, we observed a peak in granzyme B, A and H proteins around the time of conversion. Single-sample enrichment analysis of serum microRNA profiles revealed that the peak in granzyme B levels around conversion coincides with enrichment for microRNAs that are enriched in CD4+, CD8+ and natural killer cells (e.g. miRNA-150). We identified several proteins and microRNAs in serum that represent potential biomarkers for relapsing-remitting and secondary progressive multiple sclerosis. Conversion to secondary progressive disease is marked by a peak in granzyme B levels and enrichment for immune-related microRNAs. This indicates that specific immune cell-driven processes may contribute to the conversion of relapsing-remitting multiple sclerosis to secondary progressive multiple sclerosis.

Project description:Background:One of the most significant challenges in colorectal cancer (CRC) management is the use of compliant early stage population-based diagnostic tests as adjuncts to confirmatory colonoscopy. Despite the near curative nature of early clinical stage surgical resection, mortality remains unacceptably high-as the majority of patients diagnosed by faecal haemoglobin followed by colonoscopy occur at latter stages. Additionally, current population-based screens reliant on fecal occult blood test (FOBT) have low compliance (~ 40%) and tests suffer low sensitivities. Therefore, blood-based diagnostic tests offer survival benefits from their higher compliance (≥ 97%), if they can at least match the sensitivity and specificity of FOBTs. However, discovery of low abundance plasma biomarkers is difficult due to occupancy of a high percentage of proteomic discovery space by many high abundance plasma proteins (e.g., human serum albumin). Methods:A combination of high abundance protein ultradepletion (e.g., MARS-14 and an in-house IgY depletion columns) strategies, extensive peptide fractionation methods (SCX, SAX, High pH and SEC) and SWATH-MS were utilized to uncover protein biomarkers from a cohort of 100 plasma samples (i.e., pools of 20 healthy and 20 stages I-IV CRC plasmas). The differentially expressed proteins were analyzed using ANOVA and pairwise t-tests (p < 0.05; fold-change > 1.5), and further examined with a neural network classification method using in silico augmented 5000 patient datasets. Results:Ultradepletion combined with peptide fractionation allowed for the identification of a total of 513 plasma proteins, 8 of which had not been previously reported in human plasma (based on PeptideAtlas database). SWATH-MS analysis revealed 37 protein biomarker candidates that exhibited differential expression across CRC stages compared to healthy controls. Of those, 7 candidates (CST3, GPX3, CFD, MRC1, COMP, PON1 and ADAMDEC1) were validated using Western blotting and/or ELISA. The neural network classification narrowed down candidate biomarkers to 5 proteins (SAA2, APCS, APOA4, F2 and AMBP) that had maintained accuracy which could discern early (I/II) from late (III/IV) stage CRC. Conclusion:MS-based proteomics in combination with ultradepletion strategies have an immense potential of identifying diagnostic protein biosignature.

Project description:Eighty-five percent of multiple sclerosis cases begin with a discrete attack termed clinically isolated syndrome, but 37% of clinically isolated syndrome patients do not experience a relapse within 20 years of onset. Thus, the identification of biomarkers able to differentiate between individuals who are most likely to have a second clinical attack from those who remain in the clinically isolated syndrome stage is essential to apply a personalized medicine approach. We sought to identify biomarkers from biochemical, metabolic and proteomic screens that predict clinically defined conversion from clinically isolated syndrome to multiple sclerosis and generate a multi-omics-based algorithm with higher prognostic accuracy than any currently available test. An integrative multi-variate approach was applied to the analysis of cerebrospinal fluid samples taken from 54 individuals at the point of clinically isolated syndrome with 2-10 years of subsequent follow-up enabling stratification into clinical converters and non-converters. Leukocyte counts were significantly elevated at onset in the clinical converters and predict the occurrence of a second attack with 70% accuracy. Myo-inositol levels were significantly increased in clinical converters while glucose levels were decreased, predicting transition to multiple sclerosis with accuracies of 72% and 63%, respectively. Proteomics analysis identified 89 novel gene products related to conversion. The identified biochemical and protein biomarkers were combined to produce an algorithm with predictive accuracy of 83% for the transition to clinically defined multiple sclerosis, outperforming any individual biomarker in isolation including oligoclonal bands. The identified protein biomarkers are consistent with an exaggerated immune response, perturbed energy metabolism and multiple sclerosis pathology in the clinical converter group. The new biomarkers presented provide novel insight into the molecular pathways promoting disease while the multi-omics algorithm provides a means to more accurately predict whether an individual is likely to convert to clinically defined multiple sclerosis.

Project description:Multiple sclerosis (MS) is a chronic autoimmune disease that affects the myelination of the neurons present in the central nervous system (CNS). The exact etiology of MS development is unclear, but various environmental and genetic factors might play a role in initiating the disease. Current treatments for MS enhance the quality of life and reduce the symptoms. One of these treatments is dimethyl fumarate (DMF), commercially known as Tecfidera. Experimental autoimmune encephalomyelitis (EAE) is a mouse model that is used to study the pathophysiology of MS disease as well as the effects of possible therapeutic agents. In this study, we investigated the effects of SIMR1707 which is a novel compound designed at Sharjah Institute for Medical Research (SIMR). . Single and multiple doses of SIMR1707 demonstrated high safety in mice studies. Treatment of EAE mice with SIMR1707 was able to reduce the EAE clinical scores and maintain their body weight similar to the MS FDA-approved (DMF, Tecfidera), when they were used preventively, prophylactically, or therapeutically. The histological and immunohistochemistry evaluations showed reduced clinical features such as signs of inflammation, demyelination, and infiltration of CD3-positive T cells into the brains of the EAE mice, as compared to vehicle-treated, or untreated EAE mice. Moreover, multi-OMICS experiments including Transcriptomics, Proteomics and Metabolomics were performed to gain insights into the relevant mechanism of action of the SIMR1707 in EAE and thus its therapeutic efficacy to treat MS. Same tissue samples extracted from the cerebellum part of the brain of normal, EAE vehicle-treated, and therapeutic SIMR1707 treated mice, were subjected for the whole RNA-sequencing for transcriptomics, Nano MS for proteomics analysis and LC-MS metabolomics analysis. The multi-OMICs integrative analysis showed that the treatment with SIMR1707 downregulated key biomarkers functionally associated with top pathways including calcium signaling, PI3K/AKT, and mTOR signaling pathways, which may play important roles in EAE and MS pathophysiology. Additionally, the metabolomics-based enriched-for-action pathway analysis showed that the top significantly activated metabolites (FC > 2, p < 0.05) are cholic acid, propionic acid, sphinganine, and nutriacholic acid. Consisting with the functional enrichment pathway analysis, two potent markers, Snta1 and Fscn1, involved in the actin-binding and cytoskeleton are commonly shared between transcriptomics and proteomics and showed mRNA-protein expression correlation in SIMR1707 treated compared to vehicle EAE mice. Importantly, these two markers are involved in the MT2/AKT/GSK3 pathway and may potentially play role in MS and EAE disease

Project description:BackgroundMultiple sclerosis (MS) is a demyelinating disease of the central nervous system characterized by increased inflammation and immune responses, oxidative injury, mitochondrial dysfunction, and iron dyshomeostasis leading to demyelination and axonal damage. In MS, incomplete remyelination results in chronically demyelinated axons and degeneration coinciding with disability. This suggests a failure in the ability to remyelinate in MS, however, the precise underlying mechanisms remain unclear. We aimed to identify proteins whose expression was altered in chronic inactive white matter lesions and periplaque white matter in MS tissue to reveal potential pathophysiological mechanisms.MethodsLaser capture microdissection coupled to proteomics was used to interrogate spatially altered changes in formalin-fixed paraffin-embedded brain tissue from three chronic MS individuals and three controls with no apparent neurological complications. Histopathological maps guided the capture of inactive lesions, periplaque white matter, and cortex from chronic MS individuals along with corresponding white matter and cortex from control tissue. Label free quantitation by liquid chromatography tandem mass spectrometry was used to discover differentially expressed proteins between the various brain regions.ResultsIn addition to confirming loss of several myelin-associated proteins known to be affected in MS, proteomics analysis of chronic inactive MS lesions revealed alterations in myelin assembly, metabolism, and cytoskeletal organization. The top altered proteins in MS inactive lesions compared to control white matter consisted of PPP1R14A, ERMN, SIRT2, CARNS1, and MBLAC2.ConclusionOur findings highlight proteome changes in chronic inactive MS white matter lesions and periplaque white matter, which may be crucial for proper myelinogenesis, bioenergetics, focal adhesions, and cellular function. This study highlights the importance and feasibility of spatial approaches such as laser capture microdissection-based proteomics analysis of pathologically distinct regions of MS brain tissue. Identification of spatially resolved changes in the proteome of MS brain tissue should aid in the understanding of pathophysiological mechanisms and the development of novel therapies.

Project description:Multiple sclerosis (MS) is a chronic autoimmune disease that affects the myelination of the neurons present in the central nervous system (CNS). The exact etiology of MS development is unclear, but various environmental and genetic factors might play a role in initiating the disease. Current treatments for MS enhance the quality of life and reduce the symptoms. One of these treatments is dimethyl fumarate (DMF), commercially known as Tecfidera. Experimental autoimmune encephalomyelitis (EAE) is a mouse model that is used to study the pathophysiology of MS disease as well as the effects of possible therapeutic agents. In this study, we investigated the effects of SIMR1707 which is a novel compound designed at Sharjah Institute for Medical Research (SIMR). . Single and multiple doses of SIMR1707 demonstrated high safety in mice studies. Treatment of EAE mice with SIMR1707 was able to reduce the EAE clinical scores and maintain their body weight similar to the MS FDA-approved (DMF, Tecfidera), when they were used preventively, prophylactically, or therapeutically. The histological and immunohistochemistry evaluations showed reduced clinical features such as signs of inflammation, demyelination, and infiltration of CD3-positive T cells into the brains of the EAE mice, as compared to vehicle-treated, or untreated EAE mice. Moreover, multi-OMICS experiments including Transcriptomics, Proteomics and Metabolomics were performed to gain insights into the relevant mechanism of action of the SIMR1707 in EAE and thus its therapeutic efficacy to treat MS. Same tissue samples extracted from the cerebellum part of the brain of normal, EAE vehicle-treated, and therapeutic SIMR1707 treated mice, were subjected for the whole RNA-sequencing for transcriptomics, Nano MS for proteomics analysis and LC-MS metabolomics analysis. The multi-OMICs integrative analysis showed that the treatment with SIMR1707 downregulated key biomarkers functionally associated with top pathways including calcium signaling, PI3K/AKT, and mTOR signaling pathways, which may play important roles in EAE and MS pathophysiology. Additionally, the metabolomics-based enriched-for-action pathway analysis showed that the top significantly activated metabolites (FC > 2, p < 0.05) are cholic acid, propionic acid, sphinganine, and nutriacholic acid. Consisting with the functional enrichment pathway analysis, two potent markers, Snta1 and Fscn1, involved in the actin-binding and cytoskeleton are commonly shared between transcriptomics and proteomics and showed mRNA-protein expression correlation in SIMR1707 treated compared to vehicle EAE mice. Importantly, these two markers are involved in the MT2/AKT/GSK3 pathway and may potentially play role in MS and EAE disease

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The clinical potential of blood-proteomics in multiple sclerosis.

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The clinical potential of blood-proteomics in multiple sclerosis.

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