scholarly journals Expression analysis of protein inhibitor of activated STAT (PIAS) genes in IFNβ-treated multiple sclerosis patients

2018 ◽  
Vol Volume 11 ◽  
pp. 457-463 ◽  
Author(s):  
Mohammad Taheri ◽  
Ghazaleh Azimi ◽  
Arezou Sayad ◽  
Mehrdokht Mazdeh ◽  
Shahram Arsang-Jang ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Expression Analysis ◽  
Protein Inhibitor ◽  
Multiple Sclerosis Patients

scholarly journals Expression analysis of protein inhibitor of activated STAT (PIAS) genes in IFNβ-treated multiple sclerosis patients [Corrigendum]

2019 ◽  
Vol Volume 12 ◽  
pp. 23-24
Author(s):  
Mohammad Taheri ◽  
Ghazaleh Azimi ◽  
Arezou Sayad ◽  
Mehrdokht Mazdeh ◽  
Shahram Arsang-Jang ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Expression Analysis ◽  
Protein Inhibitor ◽  
Multiple Sclerosis Patients

TRAIL gene expression analysis in multiple sclerosis patients

2016 ◽  
Vol 24 (1-2) ◽  
pp. 33-38 ◽  
Author(s):  
Mohammad Taheri ◽  
Shirin Nemati ◽  
Abolfazl Movafagh ◽  
Mohammad Saberi ◽  
Reza Mirfakhraie ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Sclerosis ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Multiple Sclerosis Patients

Expression analysis of long non-coding RNAs and their target genes in multiple sclerosis patients

2019 ◽  
Vol 40 (4) ◽  
pp. 801-811 ◽  
Author(s):  
Maziar Ganji ◽  
Arezou Sayad ◽  
Mir Davood Omrani ◽  
Shahram Arsang-Jang ◽  
Mehrdokht Mazdeh ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Expression Analysis ◽  
Target Genes ◽  
Non Coding Rnas ◽  
Multiple Sclerosis Patients

Phospholipase D1 expression analysis in relapsing-remitting multiple sclerosis patients

2017 ◽  
Vol 38 (5) ◽  
pp. 865-872 ◽  
Author(s):  
Mohammad Mahdi Eftekharian ◽  
Tahereh Azimi ◽  
Soudeh Ghafouri-Fard ◽  
Arezou Sayad ◽  
Mir Davood Omrani ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Expression Analysis ◽  
Relapsing Remitting ◽  
Phospholipase D1 ◽  
Remitting Multiple Sclerosis ◽  
Multiple Sclerosis Patients ◽  
Relapsing Remitting Multiple Sclerosis

scholarly journals Profiling of plasma extracellular vesicle transcriptome reveals that circRNAs are prevalent and differ between multiple sclerosis patients and healthy controls

2021 ◽  
Author(s):  
Leire Iparraguirre ◽  
Ainhoa Alberro ◽  
Thomas Birkballe Hansen ◽  
Tamara Castillo-Triviño ◽  
Maider Muñoz-Culla ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Differential Expression ◽  
Extracellular Vesicles ◽  
Expression Analysis ◽  
Secondary Structure Prediction ◽  
Differential Expression Analysis ◽  
Circular Rnas ◽  
Healthy Controls ◽  
Type Distribution ◽  
Multiple Sclerosis Patients

Abstract Background Extracellular vesicles (EVs) are released by almost all cell types and are implicated in a number of biological and pathological processes including autoimmune diseases such as multiple sclerosis (MS). Differences in the number and cargo of plasma derived EVs have been described in MS. In this work, we attempt to characterise the EV RNA cargo of MS patients with particular attention to a recently discovered non coding RNA type, circular RNAs (circRNAs), which have been shown to play important roles in physiology and disease and hold a great biomarker potential. Methods Plasma was collected from 20 MS patients and 8 healthy controls (HC) and total RNA was isolated from plasma-derived extracellular vesicles isolated by differential centrifugation. Samples were pooled in disease status, sex and age paired groups and RNA-Sequenced with Illumina HiSeq X Ten after rRNA depletion. CircRNAs were detected by both find_circ and CIRI2 and their quantification was based on BSJ-spanning reads. Linear transcripts were quantified by HTSEq. Differential expression analysis was performed using DESeq2. RNA type distribution was analyzed based on biomart classification. MiRNA binding site number and density for circRNAs was calculated based on the TargetScan prediction performed by Circinteractome. CircRNA secondary structure prediction was calculated by their length normalized Gibbs free energy. All the statistical analysis were performed in Rstudio. Results The EV linear and circular transcriptome of MS patients and controls is characterized and compared to the transcriptome previously described in leucocytes. Results reveal differences in the RNA type distribution, showing that circRNAs are enriched in EVs compared to leucocytes. Nevertheless, highly structured circRNAs are preferentially retained in leukocytes. Additionally, differential expression analysis reports significant differences in circRNA and linear RNA expression between MS patients and controls as well as between different MS types. Conclusions The plasma derived EV RNA cargo is not a representation of leukocytes’ cytoplasm but a message that must be studied. Moreover, our results reveal the interest of circRNAs as part of this message highlighting the importance to further understand the RNA regulation in MS.

Expression Analysis of Long Non-coding RNAs in the Blood of Multiple Sclerosis Patients

2017 ◽  
Vol 63 (3-4) ◽  
pp. 333-341 ◽  
Author(s):  
Mohammad Mahdi Eftekharian ◽  
Soudeh Ghafouri-Fard ◽  
Mohammad Soudyab ◽  
Mir Davood Omrani ◽  
Mahnoosh Rahimi ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Expression Analysis ◽  
Non Coding Rnas ◽  
Multiple Sclerosis Patients

Nicotinamide nucleotide transhydrogenase expression analysis in multiple sclerosis patients

2019 ◽  
Vol 129 (12) ◽  
pp. 1256-1260 ◽  
Author(s):  
Mohammad Mahdi Eftekharian ◽  
Mohammad Taheri ◽  
Shahram Arsang-Jang ◽  
Alireza Komaki ◽  
Soudeh Ghafouri-Fard
Keyword(s):  
Multiple Sclerosis ◽  
Expression Analysis ◽  
Nicotinamide Nucleotide Transhydrogenase ◽  
Multiple Sclerosis Patients

Ecotropic Viral Integration Site 5 (EVI5) expression analysis in multiple sclerosis patients

2018 ◽  
Vol 26 (3) ◽  
pp. 113-119
Author(s):  
Mehrdokht Mazdeh ◽  
Mahnoosh Rahimi ◽  
Mohammad Mahdi Eftekharian ◽  
Mir Davood Omrani ◽  
Arezou Sayad ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Expression Analysis ◽  
Integration Site ◽  
Viral Integration ◽  
Multiple Sclerosis Patients
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