ArticleFrontiers in genetics2021
Genome-wide Identification and Analysis of Splicing QTLs in Multiple Sclerosis by RNA-Seq Data.
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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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
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- A Comprehensive Exploration of the Transcriptomic Landscape in Multiple Sclerosis: A Systematic Review.International journal of molecular sciences · 2023Pooled it
- Splicing-based biomarkers define a robust multigene classifier for relapsing-remitting multiple sclerosis.Journal of translational autoimmunity · 2025Article
- Integrating whole genome and transcriptome sequencing to characterize the genetic architecture of isoform variation.Nature communications · 2025Article
- Tensor decomposition of multi-dimensional splicing events across multiple tissues to identify splicing-mediated risk genes associated with complex traits.PLoS computational biology · 2025Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multiple sclerosis (MS) is an autoimmune disease characterized by inflammatory demyelinating lesions in the central nervous system. Recently, the dysregulation of alternative splicing (AS) in the brain has been found to significantly influence the progression of MS. Moreover, previous studies demonstrate that many MS-related variants in the genome act as the important regulation factors of AS events and contribute to the pathogenesis of MS. However, by far, no genome-wide research about the effect of genomic variants on AS events in MS has been reported. Here, we first implemented a strategy to obtain genomic variant genotype and AS isoform average percentage spliced-in values from RNA-seq data of 142 individuals (51 MS patients and 91 controls). Then, combing the two sets of data, we performed a
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Registered trials
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