ArticlePloS one2010
A transcription factor map as revealed by a genome-wide gene expression analysis of whole-blood mRNA transcriptome in multiple sclerosis.
Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
27 citing papers in PubMed, 3 syntheses or guidelines pooled it, 64 citations in OpenAlex.
- Meta-Analysis of Differential Connectivity in Gene Co-Expression Networks in Multiple Sclerosis.International journal of molecular sciences · 2016Pooled it
- Meta-Analysis of Multiple Sclerosis Microarray Data Reveals Dysregulation in RNA Splicing Regulatory Genes.International journal of molecular sciences · 2015Pooled it
- Pooled it
- CLNS1A regulates genome stability and cell cycle progression to control CD4 T cell function and autoimmunity.Science immunology · 2025Article
- EMImR: a Shiny application for identifying transcriptomic and epigenomic changes.GigaByte (Hong Kong, China) · 2025Article
- Article
- In Silico Analysis Highlights Potential Predictive Indicators Associated with Secondary Progressive Multiple Sclerosis.International journal of molecular sciences · 2024Article
- Transcription factor EGR2 controls homing and pathogenicity of TNature immunology · 2023Article
- Understanding Abnormal c-JNK/p38MAPK Signaling Overactivation Involved in the Progression of Multiple Sclerosis: Possible Therapeutic Targets and Impact on Neurodegenerative Diseases.Neurotoxicity research · 2021Review
- Constructing and validating a diagnostic nomogram for multiple sclerosis via bioinformatic analysis.3 Biotech · 2021Article
- Single-cell transcriptomics analysis of mild cognitive impairment in World Trade Center disaster responders.Alzheimer's & dementia (Amsterdam, Netherlands) · 2021Article
- Dense module searching for gene networks associated with multiple sclerosis.BMC medical genomics · 2020Article
- CSF microRNAs discriminate MS activity and share similarity to other neuroinflammatory disorders.Neurology(R) neuroimmunology & neuroinflammation · 2020Article
- Analysis of microRNA and Gene Expression Profiles in Multiple Sclerosis: Integrating Interaction Data to Uncover Regulatory Mechanisms.Scientific reports · 2016Article
- Sox5 and Th17 cell differentiation.Oncotarget · 2015Article
- Sox5 and c-Maf cooperatively induce Th17 cell differentiation via RORγt induction as downstream targets of Stat3.The Journal of experimental medicine · 2014Article
- Gene expression in superior temporal cortex of schizophrenia patients.European archives of psychiatry and clinical neuroscience · 2014Article
- Article
- (GTG)5 MSP-PCR fingerprinting as a technique for discrimination of wine associated yeasts?PloS one · 2014Article
- Blood RNA profiling in a large cohort of multiple sclerosis patients and healthy controls.Human molecular genetics · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors at 7 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSeveral lines of evidence suggest that transcription factors are involved in the pathogenesis of Multiple Sclerosis (MS) but complete mapping of the whole network has been elusive. One of the reasons is that there are several clinical subtypes of MS and transcription factors that may be involved in one subtype may not be in others. We investigate the possibility that this network could be mapped using microarray technologies and contemporary bioinformatics methods on a dataset derived from whole blood in 99 untreated MS patients (36 Relapse Remitting MS, 43 Primary Progressive MS, and 20 Secondary Progressive MS) and 45 age-matched healthy controls. METHODOLOGY/PRINCIPAL
findingsWe have used two different analytical methodologies: a non-standard differential expression analysis and a differential co-expression analysis, which have converged on a significant number of regulatory motifs that are statistically overrepresented in genes that are either differentially expressed (or differentially co-expressed) in cases and controls (e.g., V$KROX_Q6, p-value <3.31E-6; V$CREBP1_Q2, p-value <9.93E-6, V$YY1_02, p-value <1.65E-5). CONCLUSIONS/SIGNIFICANCE: Our analysis uncovered a network of transcription factors that potentially dysregulate several genes in MS or one or more of its disease subtypes. The most significant transcription factor motifs were for the Early Growth Response EGR/KROX family, ATF2, YY1 (Yin and Yang 1), E2F-1/DP-1 and E2F-4/DP-2 heterodimers, SOX5, and CREB and ATF families. These transcription factors are involved in early T-lymphocyte specification and commitment as well as in oligodendrocyte dedifferentiation and development, both pathways that have significant biological plausibility in MS causation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.