ArticleScientific data2018
Microarray data of transcriptome shifts in blood cell subsets during S1P receptor modulator therapy.
Article in Scientific data, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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.
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Who cites it
12 citing papers in PubMed, 15 citations in OpenAlex.
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Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Treatment with fingolimod, a sphingosine-1-phosphate (S1P) receptor modulator, prevents the egress of immune cell subpopulations from lymphoid tissues into the blood. We obtained peripheral blood samples from patients with relapsing multiple sclerosis before the initiation of fingolimod therapy, after one day and after 3 months. To investigate the differential expression induced by the drug, five different cell populations were isolated. We then employed 150 Human Transcriptome Arrays (HTA 2.0) interrogating >245,000 protein-coding and >40,000 non-coding transcript isoforms. After 3 months of treatment, CD4+ and CD8+ T-cells showed huge transcriptome shifts, whereas the profiles of B-cells (CD19+) were slightly altered and those of monocytes (CD14+) and natural killer cells (CD56+) remained unaffected. With >6 million probes for exons and splice junctions, our large HTA 2.0 dataset provides a deep view into alternative splicing patterns in immune cell subsets. Our data may also be useful for comparing the effects on gene expression signatures of novel S1P receptor modulators, which are currently tested in clinical trials for other autoimmune and neurodegenerative diseases.
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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.