Multiple Sclerosis Biomarker Discoveries by Proteomics and Metabolomics Approaches

Jafari, Ameneh; Babajani, Amirhesam; Rezaei‐Tavirani, Mostafa

doi:10.1177/11772719211013352

Cited by 33 publications

(28 citation statements)

References 142 publications

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“…Despite many efforts, the identification of a suitable set of biomarkers for MS based on peripheral blood is just beginning due to the complexity of MS [11]. Affinity proteomic methods have been used to identify MS-related proteins both in plasma and in CSF, leading to the identification of IRF8, IL7, SLC30A7, METTL14, and GAP43 [12][13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Plasma Protein Levels Analysis in Multiple Sclerosis Sardinian Families Identified C9 and CYP24A1 as Candidate Biomarkers

Nova

Fazia

Beecham

et al. 2022

Life

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Here we investigate protein levels in 69 multiple sclerosis (MS) cases and 143 healthy controls (HC) from twenty Sardinian families to search for promising biomarkers in plasma. Using antibody suspension bead array technology, the plasma levels of 56 MS-related proteins were obtained. Differences between MS cases and HC were estimated using Linear Mixed Models or Linear Quantile Mixed Models. The proportion of proteins level variability, explained by a set of 119 MS-risk SNPs as to the literature, was also quantified. Higher plasma C9 and CYP24A1 levels were found in MS cases compared to HC (p < 0.05 after Holm multiple testing correction), with protein level differences estimated as, respectively, 0.53 (95% CI: 0.25, 0.81) and 0.42 (95% CI: 0.19, 0.65) times plasma level standard deviation measured in HC. Furthermore, C9 resulted in both statistically significantly higher relapsing-remitting MS (RRMS) and secondary-progressive MS (SPMS) compared to HC, with SPMS showing the highest differences. Instead, CYP24A1 was statistically significantly higher only in RRMS as compared to HC. Respectively, 26% (95% CI: 10%, 44%) and 16% (95% CI: 9%, 39%) of CYP24A1 and C9 plasma level variability was explained by known MS-risk SNPs. Our results highlight C9 and CYP24A1 as potential biomarkers in plasma for MS and allow us to gain insight into molecular disease mechanisms.

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Section: Introductionmentioning

confidence: 99%

Plasma Protein Levels Analysis in Multiple Sclerosis Sardinian Families Identified C9 and CYP24A1 as Candidate Biomarkers

Nova

Fazia

Beecham

et al. 2022

Life

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“…Proteomics has been developed with the support of mass spectrometry and bioinformatics technology which provides a high-resolution, high-accuracy strategy to identify novel MS biomarkers ( 7 , 8 ). In the present study, we aimed to discover the potential biomarkers through a comparative analysis of CSF and blood samples collected from MS patients and controls.…”

Section: Introductionmentioning

confidence: 99%

Discovery of Novel Biomarkers for Diagnosing and Predicting the Progression of Multiple Sclerosis Using TMT-Based Quantitative Proteomics

Shi

Ding

et al. 2021

Front. Immunol.

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ObjectiveHere, we aimed to identify protein biomarkers that could rapidly and accurately diagnose multiple sclerosis (MS) using a highly sensitive proteomic immunoassay.MethodsTandem mass tag (TMT) quantitative proteomic analysis was performed to determine the differentially expressed proteins (DEPs) in cerebrospinal fluid (CSF) samples collected from 10 patients with MS and 10 non-inflammatory neurological controls (NINCs). The DEPs were analyzed using bioinformatics tools, and the candidate proteins were validated using the ELISA method in another cohort comprising 160 samples (paired CSF and plasma of 40 patients with MS, CSF of 40 NINCs, and plasma of 40 healthy individuals). Receiver operating characteristic (ROC) curves were used to determine the diagnostic potential of this method.ResultsCompared to NINCs, we identified 83 CSF-specific DEPs out of a total of 343 proteins in MS patients. Gene ontology (GO) enrichment analysis revealed that these DEPs are mainly involved in platelet degranulation, negative regulation of proteolysis, and post-translational protein modification. Pathway enrichment analysis revealed that the complement and coagulation cascades, Ras signaling pathway, and PI3K-Akt signaling pathway are the main components. Insulin-like growth factor-binding protein 7 (IGFBP7), insulin-like growth factor 2 (IGF2), and somatostatin (SST) were identified as the potential proteins with high scores, degree, and centrality in the protein-protein interaction (PPI) network. We validated the expression of these three proteins using ELISA. Compared to NINCs, the level of CSF IGFBP7 was significantly upregulated, and the level of CSF SST was significantly downregulated in the MS group.ConclusionOur results suggest that SST and IGFBP7 might be associated with the pathogenesis of MS and would be helpful in diagnosing MS. Since IGFBP7 was used to classify relapsing remitting MS (RRMS) and secondary progressive MS (SPMS) patients, therefore, it may act as a potential key marker and therapeutic target in MS.

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“…Computational biology is a rapidly progressing multidisciplinary field ( 189 ). In addition to experimental approaches, computational and bioinformatics strategies play an essential role in peptide design and cancer therapeutics.…”

Section: Computational Approaches In Amp Design Against Cancersmentioning

confidence: 99%

Clinical Applications and Anticancer Effects of Antimicrobial Peptides: From Bench to Bedside

et al. 2022

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Cancer is a multifaceted global health issue and one of the leading causes of death worldwide. In recent years, medical science has achieved great advances in the diagnosis and treatment of cancer. Despite the numerous advantages of conventional cancer therapies, there are major drawbacks including severe side effects, toxicities, and drug resistance. Therefore, the urgency of developing new drugs with low cytotoxicity and treatment resistance is increasing. Antimicrobial peptides (AMPs) have attracted attention as a novel therapeutic strategy for the treatment of various cancers, targeting tumor cells with less toxicity to normal tissues. In this review, we present the structure, biological function, and underlying mechanisms of AMPs. The recent experimental studies and clinical trials on anticancer peptides in different cancer types as well as the challenges of their clinical application have also been discussed.

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Multiple Sclerosis Biomarker Discoveries by Proteomics and Metabolomics Approaches

Cited by 33 publications

References 142 publications

Plasma Protein Levels Analysis in Multiple Sclerosis Sardinian Families Identified C9 and CYP24A1 as Candidate Biomarkers

Plasma Protein Levels Analysis in Multiple Sclerosis Sardinian Families Identified C9 and CYP24A1 as Candidate Biomarkers

Discovery of Novel Biomarkers for Diagnosing and Predicting the Progression of Multiple Sclerosis Using TMT-Based Quantitative Proteomics

Clinical Applications and Anticancer Effects of Antimicrobial Peptides: From Bench to Bedside

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