scholarly journals Progressive Multiple Sclerosis Transcriptome Deconvolution Indicates Increased M2 Macrophages in Inactive Lesions

2020 ◽  
Vol 83 (4) ◽  
pp. 433-435
Author(s):  
Sai Batchu
Keyword(s):  
Multiple Sclerosis ◽  
Immune Cells ◽  
Gene Signature ◽  
Progressive Multiple Sclerosis ◽  
M2 Macrophages ◽  
Expression Data ◽  
Murine Models ◽  
Sequencing Data ◽  
Normal White Matter ◽  
Signature Matrix

Accumulating evidence suggests M2 macrophages contribute to tissue reparation and limit inflammation in multiple sclerosis (MS). However, most studies have focused on murine models without substantial support through human MS observations. The present study aimed to quantify the relative abundances of M2 macrophages in different lesion types excised from human MS patients. CIBERSORTx, an established RNA deconvolution algorithm, was applied on bulk RNA-sequencing data developed from 98 lesions from 10 progressive MS patients and 5 neuropathological control donors. A validated gene signature matrix for 22 human hematopoietic cell subsets was used to infer the relative proportions of immune cells that were present in the original lesion. Deconvolution of the bulk gene expression data showed that inactive lesions contained significantly more M2 macrophages compared to normal white matter control samples. The findings suggest that M2 macrophages may play a role during lesion inactivity in MS.

T1 relaxation maps allow differentiation between pathologic tissue subsets in relapsing-remitting and secondary progressive multiple sclerosis

2004 ◽  
Vol 10 (5) ◽  
pp. 556-561 ◽  
Author(s):  
A Castriota-Scanderbeg ◽  
F Fasano ◽  
M Filippi ◽  
C Caltagirone
Keyword(s):  
Multiple Sclerosis ◽  
White Matter ◽  
Relaxation Times ◽  
Brain Regions ◽  
Progressive Multiple Sclerosis ◽  
Clinical Group ◽  
Secondary Progressive ◽  
Normal Appearing White Matter ◽  
Relapsing Remitting ◽  
Normal White Matter

In an attempt to clarify whether T1 relaxation time mapping may assist in characterizing the pathological brain tissue substrate of multiple sclerosis (MS), we compared the T1 relaxation times of lesions, areas of normal-appearing white matter (NAWM) located proximal to lesions, and areas of NAWM located distant from lesions in 12 patients with the relapsing-remitting and 12 with the secondary progressive (SP) subtype of disease. Nine healthy volunteers served as controls. Calculated mean T1 values were averaged across all patients within each clinical group, and comparisons were made by means of the Mann-Whitney U-test. Significant differences were found between all investigated brain regions within each clinical subgroup. Significant differences were also detected for each investigated brain region among clinical subgroups. While T1 values of NAWM were significantly higher in patients with SP disease than in normal white matter (NWM) of controls, no differences were detected when corresponding brain areas of patients with RR MS were compared with NWM of controls. T1 maps identify areas of the brain that are damaged to a different extent in patients with MS, and may be of help in monitoring disease progression.

Circulating microRNAs as biomarkers in progressive multiple sclerosis

2016 ◽  
Vol 23 (3) ◽  
pp. 403-412 ◽  
Author(s):  
Julia Vistbakka ◽  
Irina Elovaara ◽  
Terho Lehtimäki ◽  
Sanna Hagman
Keyword(s):  
Multiple Sclerosis ◽  
Immune Cells ◽  
Progressive Multiple Sclerosis ◽  
Body Fluids ◽  
Primary Progressive Multiple Sclerosis ◽  
Circulating Mirnas ◽  
Circulating Micrornas ◽  
Primary Progressive ◽  
Secondary Progressive ◽  
Exceptional Stability

Background: In multiple sclerosis (MS), microRNA (miRNA) dysregulation is mostly reported in different immune cells, but less information is available on circulating miRNAs that exert strong biomarker potential due to their exceptional stability in body fluids. Objective: The aim of this study was to profile expression of circulating miRNAs in primary progressive multiple sclerosis (PPMS) and secondary progressive multiple sclerosis (SPMS) and assess their association with neurological worsening. Methods: The expressions of 84 different miRNAs were profiled in serum of 83 subjects (62 MS and 21 controls) using miScript miRNA techniques. First, they were screened on 18 PPMS and 10 controls; thereafter, 10 most aberrantly expressed miRNAs were validated on a larger cohort. Results: In comparison with controls, upregulation of miR-191-5p was found in both progressive MS subtypes, while miR-376c-3p was overexpressed only in PPMS. Additionally, upregulation of miR-128-3p and miR-24-3p was detected in PPMS when compared to controls and SPMS. Progression index correlated with miR-128-3p in PPMS and miR-375 in SPMS. Conclusion: We detected overexpression of four miRNAs that have not been previously associated with progressive forms of MS. The increased expression of circulating miR-191-5p seems to be associated with progressive forms of MS, while miR-128-3p seems to be associated mostly with PPMS.

scholarly journals ImmuCellAI: a unique method for comprehensive T-cell subsets abundance prediction and its application in cancer immunotherapy

2019 ◽  
Author(s):  
Ya-Ru Miao ◽  
Qiong Zhang ◽  
Qian Lei ◽  
Mei Luo ◽  
Gui-Yan Xie ◽  
...  
Keyword(s):  
T Cell ◽  
Immune Cells ◽  
Immune Cell ◽  
Response Prediction ◽  
Cell Types ◽  
Cancer Immunology ◽  
T Cell Subsets ◽  
Expression Data ◽  
Sequencing Data ◽  
Pre Treatment

AbstractThe distribution and abundance of immune cells, particularly T-cell subsets, play pivotal roles in cancer immunology and therapy. There are many T-cell subsets with specific function, however current methods are limited in estimating them, thus, a method for predicting comprehensive T-cell subsets is urgently needed in cancer immunology research. Here we introduce Immune Cell Abundance Identifier (ImmuCellAI), a novel gene set signature-based method, for precisely estimating the abundance of 24 immune cell types including 18 T-cell subsets, from gene expression data. Performance evaluation on both our sequencing data with flow cytometry results and public expression data indicated that ImmuCellAI can estimate immune cells with superior accuracy than other methods especially on many T-cell subsets. Application of ImmuCellAI to immunotherapy datasets revealed that the abundance of dendritic cells (DC), cytotoxic T, and gamma delta T cells was significantly higher both in comparisons of on-treatment vs. pre-treatment and responders vs. non-responders. Meanwhile, we built an ImmuCellAI result-based model for predicting the immunotherapy response with high accuracy (AUC 0.80~0.91). These results demonstrated the powerful and unique function of ImmuCellAI in tumor immune infiltration estimation and immunotherapy response prediction. The ImmuCellAI online server is freely available at http://bioinfo.life.hust.edu.cn/web/ImmuCellAI/.

scholarly journals Patterns of Immune Infiltration in Endometriosis and Their Relationship to r-AFS Stages

2021 ◽  
Vol 12 ◽  
Author(s):  
Qiyu Zhong ◽  
Fan Yang ◽  
Xiaochuan Chen ◽  
Jinbo Li ◽  
Cailing Zhong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Cells ◽  
Plasma Cells ◽  
Immune Cell ◽  
M2 Macrophages ◽  
Expression Data ◽  
Gene Expression Microarray Data ◽  
And Function ◽  
Ovarian Endometriomas ◽  
Activation Status

Background: Endometriosis (EMS) is an estrogen-dependent disease in which endometrial glands and stroma arise outside the uterus. Current studies have suggested that the number and function of immune cells are abnormal in the abdominal fluid and ectopic lesion tissues of patients with EMS. The developed CIBERSORT method allows immune cell profiling by the deconvolution of gene expression microarray data.Methods: By applying CIBERSORT, we assessed the relative proportions of immune cells in 68 normal endometrial tissues (NO), 112 eutopic endometrial tissues (EU) and 24 ectopic endometrial tissues (EC). The obtained immune cell profiles provided enumeration and activation status of 22 immune cell subtypes. We obtained associations between the immune cell environment and EMS r-AFS stages. Macrophages were evaluated by immunohistochemistry (IHC) in 60 patients with ovarian endometriomas.Results: Total natural killer (NK) cells were significantly decreased in EC, while plasma cells and resting CD4 memory T cells were increased in EC. Total macrophages in EC were significantly increased compared to those of EU and NO, and M2 macrophages were the primary macrophages in EC. Compared to those of EC from patients with r-AFS stage I ~ II, M2 macrophages in EC from patients with stage III ~ IV were significantly increased. IHC experiments showed that total macrophages were increased in EC, with M2 macrophages being the primary subtype.Conclusions: Our data demonstrate that deconvolution of gene expression data by CIBERSORT provides valuable information about immune cell composition in EMS.

Neuroinflammatory State of Multiple Sclerosis and Strategies for Biotherapeutics Development

2021 ◽  
Author(s):  
Samira Soltanmoradi ◽  
Fatemeh Kouhkan ◽  
Iman Rad
Keyword(s):  
Multiple Sclerosis ◽  
Immune System ◽  
Immune Cells ◽  
Inflammatory Responses ◽  
Treg Cells ◽  
Progressive Multiple Sclerosis ◽  
Common Symptom ◽  
The Central Nervous System ◽  
Anti Inflammatory ◽  
Relapsing Remitting Multiple Sclerosis

Multiple Sclerosis (MS) is the most prevalent neurological disability in young adults. The pathogenesis of MS is characterized by demyelination and neurodegeneration in the central nervous system (CNS) as the ruinous result of chronic activation of the immune system. All clinical forms of MS, including relapsing-remitting multiple sclerosis (RRMS), secondary progressive multiple sclerosis (SPMS), and the primary progressive MS (PPMS), demonstrate inflammation as a common symptom. In various autoimmune diseases like MS, the ability of the immune system to set a balance between pro-inflammatory and anti-inflammatory responses is lost. In this review, the imbalance between pro-inflammatory and anti-inflammatory responses of immune cells and their role in MS progression is discussed. Disturbing the balance of Th1/Th2 and Th17/Treg cells and M1/M2 phenotypes of macrophages and microglial plays a key role in the development and progression of MS. In this review, we first depict an outline of regulatory immune cells involved in inflammation. Second, we discuss shreds of evidence that confirm how B cells play both pathogenic and protective roles in MS disease. Third, we point out the pros and cons of B cell/T cell-targeted therapies in clinical trials.

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