Evidence mapPaperPMID 34625797Full record

ArticleBlood advances2021

Genome-wide whole-blood transcriptome profiling across inherited bone marrow failure subtypes.

Amanda J Walne, Tom Vulliamy, Findlay Bewicke-Copley, Jun Wang, Jenna Alnajar, Maria G Bridger, Bernard Ma, Hemanth Tummala, Inderjeet Dokal

Open access · goldAbstract read
In one paragraph

Article in Blood advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.5field-weighted citation impact, top 29% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 1 country.

Amanda J WalneCentre for Genomics and Child Health, Blizard Institute, Barts and The London School of Medicine and Dentistry.ORCID 0000-0001-7184-8808
Tom VulliamyCentre for Genomics and Child Health, Blizard Institute, Barts and The London School of Medicine and Dentistry.
Findlay Bewicke-CopleyCentre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, London, UK; and.ORCID 0000-0003-1292-7965
Jun WangCentre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, London, UK; and.ORCID 0000-0003-2509-9599
Jenna AlnajarCentre for Genomics and Child Health, Blizard Institute, Barts and The London School of Medicine and Dentistry.ORCID 0000-0003-2723-1741
Maria G BridgerCentre for Genomics and Child Health, Blizard Institute, Barts and The London School of Medicine and Dentistry.
Bernard MaCentre for Genomics and Child Health, Blizard Institute, Barts and The London School of Medicine and Dentistry.
Hemanth TummalaCentre for Genomics and Child Health, Blizard Institute, Barts and The London School of Medicine and Dentistry.
Inderjeet DokalCentre for Genomics and Child Health, Blizard Institute, Barts and The London School of Medicine and Dentistry.ORCID 0000-0003-4462-4782
Queen Mary University of London · GBNational Health Service · GB

Funding

Blood Cancer UK 14032Medical Research Council MR/P018440/1
6 · The paper itself

Abstract

Gene expression profiling has long been used in understanding the contribution of genes and related pathways in disease pathogenesis and susceptibility. We have performed whole-blood transcriptomic profiling in a subset of patients with inherited bone marrow failure (IBMF) whose diseases are clinically and genetically characterized as Fanconi anemia (FA), Shwachman-Diamond syndrome (SDS), and dyskeratosis congenita (DC). We hypothesized that annotating whole-blood transcripts genome wide will aid in understanding the complexity of gene regulation across these IBMF subtypes. Initial analysis of these blood-derived transcriptomes revealed significant skewing toward upregulated genes in patients with FA when compared with controls. Patients with SDS or DC also showed similar skewing profiles in their transcriptional status revealing a common pattern across these different IBMF subtypes. Gene set enrichment analysis revealed shared pathways involved in protein translation and elongation (ribosome constituents), RNA metabolism (nonsense-mediated decay), and mitochondrial function (electron transport chain). We further identified a discovery set of 26 upregulated genes at stringent cutoff (false discovery rate < 0.05) that appeared as a unified signature across the IBMF subtypes. Subsequent transcriptomic analysis on genetically uncharacterized patients with BMF revealed a striking overlap of genes, including 22 from the discovery set, which indicates a unified transcriptional drive across the classic (FA, SDS, and DC) and uncharacterized BMF subtypes. This study has relevance in disease pathogenesis, for example, in explaining the features (including the BMF) common to all patients with IBMF and suggests harnessing this transcriptional signature for patient benefit.

Indexed as

Bone Marrow DiseasesDyskeratosis CongenitaFanconi AnemiaBone Marrow Failure DisordersGene Expression ProfilingHumans

Identifiers

PMID34625797
PMCPMC9153011
OpenAlexW3203141717

What Socratic holds

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Registered trials

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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 Socratic graph.