scholarly journals Gene Networks Reveal LASP1, TUBA1C, and S100A6 as Likely Drivers of Multiple Sclerosis (MS)

2021 ◽  
Author(s):  
Nafiseh Karimi ◽  
Majid Motovalli Bashi ◽  
Mostafa Ghaderi-Zefrehei
Keyword(s):  
Multiple Sclerosis ◽  
Gene Regulation ◽  
Gene Networks ◽  
Molecular Architecture ◽  
Inherited Disease ◽  
Wide Range ◽  
Transcriptional Gene Regulation ◽  
Therapeutic Tools ◽  
Downstream Analysis ◽  
New Treatments

Abstract Background: Multiple sclerosis (MS), a non-contagious and chronic disease of the central nervous system, is an unpredictable and indirectly inherited disease affecting different people in different ways.Using Omics platforms data i.e. genomics, transcriptomics, proteomics, epigenomics, interactomics, and metabolomics it is now possible to construct sound systems biology models to extract full knowledge of the MS and path the way to likely construct personalized and therapeutic tools.Methods: In this study, we learned many Bayesian Networks in order to find the transcriptional gene regulation networks that drive MS disease. We used a set of BN algorithms using the R add-on package bnlearn. The BN results underwent further downstream analysis and were validated using a wide range of Cytoscape algorithms, web based computational tools and qPCR amplification of blood samples from 56 MS patients and 44 healthy controls. The results were semantically integrated to come up with improved understanding of the complex molecular architecture underlying MS, distinguishing distinct metabolic pathways and providing a valuable foundation for the discovery of deriven genes and possibly new treatments. Results: Results show that the LASP1, TUBA1C, and S100A6 genes were most significant and likely playing a biological role in MS development. Results from qPCR showed a significant increase (P <0.05) in LASP1 and S100A6 gene expression levels in MS patients compared to controls. However, a significant down regulation of TUBA1C was observed in the same comparison. Conclusion: This study provides potential diagnostic and therapeutic biomarkers for increasing understanding of gene regulation underlying MS.

scholarly journals MicroRNA Signatures in Neurological Disorders

2010 ◽  
Vol 37 (2) ◽  
pp. 177-185 ◽  
Author(s):  
Gowhar Shafi ◽  
Nishat Aliya ◽  
Anjana Munshi
Keyword(s):  
Cell Death ◽  
Nervous System ◽  
Gene Regulation ◽  
Neurological Disorders ◽  
Mirna Biogenesis ◽  
Neuronal Function ◽  
Mrna Targets ◽  
Transcriptional Gene Regulation ◽  
Therapeutic Tools ◽  
Intense Research

A class of small, non-coding transcripts called microRNAs (miRNAs) that play a major role in post-transcriptional gene regulation has recently emerged and become the focus of intense research. MicroRNAs are abundant in the nervous system, where they have key roles in development and are likely to be important mediators of plasticity. A highly conserved pathway of miRNA biogenesis is closely linked to the transport and translatability of mRNAs in neurons. MicroRNAs have been shown to modulate programmed cell death during development. Although there are nearly 750 known human miRNA sequences, each of only approximately 20-25 nucleotides in length that bind to multiple mRNA targets, the accurate prediction of miRNA targets seems to lie just beyond our grasp. Nevertheless, the identification of such targets promises to provide new insights into many facets of neuronal function. In this review, we briefly describe miRNA biogenesis and the principle approaches for studying the function of miRNAs and potential application of miRNAs as biomarkers, diagnostic targets, and potential therapeutic tools of human diseases in general and neurological disorders in particular.

The SNPs within 3'UTR of miRNA Target Genes Related to Multiple Sclerosis: A Computational Prediction

2020 ◽  
Vol 17 (2) ◽  
pp. 133-147
Author(s):  
Mina Zafarpiran ◽  
Roya Sharifi ◽  
Zeinab Shirvani-Farsani
Keyword(s):  
Multiple Sclerosis ◽  
Gene Regulation ◽  
Binding Sites ◽  
Target Genes ◽  
Demyelinating Disease ◽  
Target Prediction ◽  
Computational Prediction ◽  
Functional Verification ◽  
Candidate Snps ◽  
Inflammatory Genes

Background: Multiple Sclerosis (MS) is an inflammatory and demyelinating disease of the central nervous system, and genetic factors play an important role in its susceptibility. The expressions of many inflammatory genes implicated in MS are regulated by microRNA (miRNAs), whose function is to suppress the translation by pairing with miRNA Recognition Elements (MREs) present in the 3' untranslated region (3'UTR) of target mRNA. Recently, it has been shown that the Single Nucleotide Polymorphism (SNPs) present within the 3'UTR of mRNAs can affect the miRNA-mediated gene regulation and susceptibility to a variety of human diseases. Objective: The aim of this study was to analyze the SNPs within the 3'UTR of miRNA inflammatory target genes related to multiple sclerosis. Methods: By DisGeNET, dbGaP, Ovid, DAVID, Web of knowledge, and SNPs databases, 3'UTR genetic variants were identified in all inflammatory genes associated with MS. Also, miRNA's target prediction databases were used for predicting the miRNA binding sites. Results: We identified 125 SNPs with MAF>0.05 located in the binding site of the miRNA of 35 genes among 59 inflammatory genes related to MS. Bioinformatics analysis predicted 62 MRE-modulating SNPs and 59 MRE-creating SNPs in the 3'UTR of MSimplicated inflammatory genes. These candidate SNPs within miRNA binding sites of inflammatory genes can alter the miRNAs binding, and consequently lead to the mRNA gene regulation. Conclusion: Therefore, these miRNA and MRE-SNPs may play important roles in personalized medicine of MS, and hence, they would be valuable for further functional verification investigations.

scholarly journals Kinematic Analysis of Lower Limb Joint Asymmetry during Gait in People with Multiple Sclerosis

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 598
Author(s):  
Massimiliano Pau ◽  
Bruno Leban ◽  
Michela Deidda ◽  
Federica Putzolu ◽  
Micaela Porta ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Lower Limb ◽  
Sagittal Plane ◽  
Cross Sectional Study ◽  
Camera Motion ◽  
Cross Sectional ◽  
Temporal Parameters ◽  
Wide Range ◽  
Edss Score ◽  
Spatio Temporal

The majority of people with Multiple Sclerosis (pwMS), report lower limb motor dysfunctions, which may relevantly affect postural control, gait and a wide range of activities of daily living. While it is quite common to observe a different impact of the disease on the two limbs (i.e., one of them is more affected), less clear are the effects of such asymmetry on gait performance. The present retrospective cross-sectional study aimed to characterize the magnitude of interlimb asymmetry in pwMS, particularly as regards the joint kinematics, using parameters derived from angle-angle diagrams. To this end, we analyzed gait patterns of 101 pwMS (55 women, 46 men, mean age 46.3, average Expanded Disability Status Scale (EDSS) score 3.5, range 1–6.5) and 81 unaffected individuals age- and sex-matched who underwent 3D computerized gait analysis carried out using an eight-camera motion capture system. Spatio-temporal parameters and kinematics in the sagittal plane at hip, knee and ankle joints were considered for the analysis. The angular trends of left and right sides were processed to build synchronized angle–angle diagrams (cyclograms) for each joint, and symmetry was assessed by computing several geometrical features such as area, orientation and Trend Symmetry. Based on cyclogram orientation and Trend Symmetry, the results show that pwMS exhibit significantly greater asymmetry in all three joints with respect to unaffected individuals. In particular, orientation values were as follows: 5.1 of pwMS vs. 1.6 of unaffected individuals at hip joint, 7.0 vs. 1.5 at knee and 6.4 vs. 3.0 at ankle (p < 0.001 in all cases), while for Trend Symmetry we obtained at hip 1.7 of pwMS vs. 0.3 of unaffected individuals, 4.2 vs. 0.5 at knee and 8.5 vs. 1.5 at ankle (p < 0.001 in all cases). Moreover, the same parameters were sensitive enough to discriminate individuals of different disability levels. With few exceptions, all the calculated symmetry parameters were found significantly correlated with the main spatio-temporal parameters of gait and the EDSS score. In particular, large correlations were detected between Trend Symmetry and gait speed (with rho values in the range of –0.58 to –0.63 depending on the considered joint, p < 0.001) and between Trend Symmetry and EDSS score (rho = 0.62 to 0.69, p < 0.001). Such results suggest not only that MS is associated with significantly marked interlimb asymmetry during gait but also that such asymmetry worsens as the disease progresses and that it has a relevant impact on gait performances.

scholarly journals BloodGen3Module: Blood transcriptional module repertoire analysis and visualization using R

2021 ◽  
Author(s):  
Darawan Rinchai ◽  
Jessica Roelands ◽  
Mohammed Toufiq ◽  
Wouter Hendrickx ◽  
Matthew C Altman ◽  
...  
Keyword(s):  
Transcript Abundance ◽  
R Package ◽  
Supplementary Information ◽  
Illustrative Case ◽  
Bioinformatic Tools ◽  
Transcriptional Module ◽  
Wide Range ◽  
Downstream Analysis ◽  
Computing Module ◽  
Parallel Workflow

Abstract Motivation We previously described the construction and characterization of generic and reusable blood transcriptional module repertoires. More recently we released a third iteration (“BloodGen3” module repertoire) that comprises 382 functionally annotated gene sets (modules) and encompasses 14,168 transcripts. Custom bioinformatic tools are needed to support downstream analysis, visualization and interpretation relying on such fixed module repertoires. Results We have developed and describe here a R package, BloodGen3Module. The functions of our package permit group comparison analyses to be performed at the module-level, and to display the results as annotated fingerprint grid plots. A parallel workflow for computing module repertoire changes for individual samples rather than groups of samples is also available; these results are displayed as fingerprint heatmaps. An illustrative case is used to demonstrate the steps involved in generating blood transcriptome repertoire fingerprints of septic patients. Taken together, this resource could facilitate the analysis and interpretation of changes in blood transcript abundance observed across a wide range of pathological and physiological states. Availability The BloodGen3Module package and documentation are freely available from Github: https://github.com/Drinchai/BloodGen3Module Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Microglial Pruning: Relevance for Synaptic Dysfunction in Multiple Sclerosis and Related Experimental Models

Cells ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 686
Author(s):  
Maria Concetta Geloso ◽  
Nadia D’Ambrosi
Keyword(s):  
Multiple Sclerosis ◽  
Neuronal Death ◽  
Environmental Changes ◽  
Experimental Models ◽  
Synaptic Dysfunction ◽  
Synapse Elimination ◽  
Neurodegenerative Process ◽  
Immune Mediated ◽  
Wide Range ◽  
Demyelinating Lesions

Microglia, besides being able to react rapidly to a wide range of environmental changes, are also involved in shaping neuronal wiring. Indeed, they actively participate in the modulation of neuronal function by regulating the elimination (or “pruning”) of weaker synapses in both physiologic and pathologic processes. Mounting evidence supports their crucial role in early synaptic loss, which is emerging as a hallmark of several neurodegenerative diseases, including multiple sclerosis (MS) and its preclinical models. MS is an inflammatory, immune-mediated pathology of the white matter in which demyelinating lesions may cause secondary neuronal death. Nevertheless, primitive grey matter (GM) damage is emerging as an important contributor to patients’ long-term disability, since it has been associated with early and progressive cognitive decline (CD), which seriously worsens the quality of life of MS patients. Widespread synapse loss even in the absence of demyelination, axon degeneration and neuronal death has been demonstrated in different GM structures, thus raising the possibility that synaptic dysfunction could be an early and possibly independent event in the neurodegenerative process associated with MS. This review provides an overview of microglial-dependent synapse elimination in the neuroinflammatory process that underlies MS and its experimental models.

scholarly journals Role of Transposable Elements in Gene Regulation in the Human Genome

Life ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 118
Author(s):  
Arsala Ali ◽  
Kyudong Han ◽  
Ping Liang
Keyword(s):  
Gene Regulation ◽  
Transposable Elements ◽  
Regulatory Sequences ◽  
Rna Sequences ◽  
Expression Of Genes ◽  
Wide Range ◽  
Lineage Specificity ◽  
Regulatory Rnas ◽  
Potential Factors ◽  
Interspersed Repeats

Transposable elements (TEs), also known as mobile elements (MEs), are interspersed repeats that constitute a major fraction of the genomes of higher organisms. As one of their important functional impacts on gene function and genome evolution, TEs participate in regulating the expression of genes nearby and even far away at transcriptional and post-transcriptional levels. There are two known principal ways by which TEs regulate the expression of genes. First, TEs provide cis-regulatory sequences in the genome with their intrinsic regulatory properties for their own expression, making them potential factors for regulating the expression of the host genes. TE-derived cis-regulatory sites are found in promoter and enhancer elements, providing binding sites for a wide range of trans-acting factors. Second, TEs encode for regulatory RNAs with their sequences showed to be present in a substantial fraction of miRNAs and long non-coding RNAs (lncRNAs), indicating the TE origin of these RNAs. Furthermore, TEs sequences were found to be critical for regulatory functions of these RNAs, including binding to the target mRNA. TEs thus provide crucial regulatory roles by being part of cis-regulatory and regulatory RNA sequences. Moreover, both TE-derived cis-regulatory sequences and TE-derived regulatory RNAs have been implicated in providing evolutionary novelty to gene regulation. These TE-derived regulatory mechanisms also tend to function in a tissue-specific fashion. In this review, we aim to comprehensively cover the studies regarding these two aspects of TE-mediated gene regulation, mainly focusing on the mechanisms, contribution of different types of TEs, differential roles among tissue types, and lineage-specificity, based on data mostly in humans.

scholarly journals Comparison and evaluation of statistical error models for scRNA-seq

2021 ◽  
Author(s):  
Saket Choudhary ◽  
Rahul Satija
Keyword(s):  
Linear Models ◽  
Negative Binomial ◽  
Statistical Error ◽  
Rna Seq ◽  
Multiple Sources ◽  
Error Models ◽  
Wide Range ◽  
Data Driven Approach ◽  
Downstream Analysis ◽  
Experimental Processing

Heterogeneity in single-cell RNA-seq (scRNA-seq) data is driven by multiple sources, including biological variation in cellular state as well as technical variation introduced during experimental processing. Deconvolving these effects is a key challenge for preprocessing workflows. Recent work has demonstrated the importance and utility of count models for scRNA-seq analysis, but there is a lack of consensus on which statistical distributions and parameter settings are appropriate. Here, we analyze 58 scRNA-seq datasets that span a wide range of technologies, systems, and sequencing depths in order to evaluate the performance of different error models. We find that while a Poisson error model appears appropriate for sparse datasets, we observe clear evidence of overdispersion for genes with sufficient sequencing depth in all biological systems, necessitating the use of a negative binomial model. Moreover, we find that the degree of overdispersion varies widely across datasets, systems, and gene abundances, and argues for a data-driven approach for parameter estimation. Based on these analyses, we provide a set of recommendations for modeling variation in scRNA-seq data, particularly when using generalized linear models or likelihood-based approaches for preprocessing and downstream analysis.

scholarly journals Multiple Sclerosis Recognition by Biorthogonal Wavelet Features and Fitness-Scaled Adaptive Genetic Algorithm

2021 ◽  
Vol 15 ◽  
Author(s):  
Shui-Hua Wang ◽  
Xianwei Jiang ◽  
Yu-Dong Zhang
Keyword(s):  
Multiple Sclerosis ◽  
Genetic Algorithm ◽  
Data Augmentation ◽  
Area Under The Curve ◽  
Adaptive Genetic Algorithm ◽  
Biorthogonal Wavelet ◽  
Wide Range ◽  
Wavelet Features ◽  
The Brain ◽  
Better Than

Aim: Multiple sclerosis (MS) is a disease, which can affect the brain and/or spinal cord, leading to a wide range of potential symptoms. This method aims to propose a novel MS recognition method.Methods: First, the bior4.4 wavelet is used to extract multiscale coefficients. Second, three types of biorthogonal wavelet features are proposed and calculated. Third, fitness-scaled adaptive genetic algorithm (FAGA)—a combination of standard genetic algorithm, adaptive mechanism, and power-rank fitness scaling—is harnessed as the optimization algorithm. Fourth, multiple-way data augmentation is utilized on the training set under the setting of 10 runs of 10-fold cross-validation. Our method is abbreviated as BWF-FAGA.Results: Our method achieves a sensitivity of 98.00 ± 0.95%, a specificity of 97.78 ± 0.95%, and an accuracy of 97.89 ± 0.94%. The area under the curve of our method is 0.9876.Conclusion: The results show that the proposed BWF-FAGA method is better than 10 state-of-the-art MS recognition methods, including eight artificial intelligence-based methods, and two deep learning-based methods.

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