Evidence map›Paper›PMID 34344933›Full record

ArticleScientific reports2021

Transcriptomic landscape of blood platelets in healthy donors.

Anna Supernat, Marta Popęda, Krzysztof Pastuszak, Myron G Best, Peter Grešner, Sjors In 't Veld, Bartłomiej Siek, Natalia Bednarz-Knoll, Matthew T Rondina, Tomasz Stokowy and 3 more

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07460440 (SPARC - Screening for Lung Cancer With Platelets Via an AI-enabled RNA-based Classifier), which is not on this map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
3.1field-weighted citation impact, top 7% 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.

NCT07460440 not yet recruitingnot on this mapstarted 2026, after this paper: background citation

SPARC - Screening for Lung Cancer With Platelets Via an AI-enabled RNA-based Classifier

TypeobservationalSponsorUniversity of UtahRan2026 to 2028Enrolled240ConditionsLung Cancer, Lung NoduleArmsPlatelet RNA-based assay
3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 48 citations in OpenAlex.

  1. A who's who of cell types in skeletal muscle.Communications biology · 2026
    Review
  2. Review
  3. Single-cell RNA sequencing of platelets: challenges and potential.Journal of thrombosis and thrombolysis · 2026
    Article
  4. Article
  5. Alterations in RNA Expression Profile FollowingInternational journal of molecular sciences · 2025
    Article
  6. Article
  7. Article
  8. Thrombocytopenia in Sepsis.Life (Basel, Switzerland) · 2025
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Review
  18. Article
  19. Article
  20. Single-cell analysis of platelets from patients with periodontitis and diabetes.Research and practice in thrombosis and haemostasis · 2023
    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

13 authors at 5 institutions in 4 countries.

Anna SupernatLaboratory of Translational Oncology, Intercollegiate Faculty of Biotechnology, University of Gdańsk and Medical University of Gdańsk, Dębinki 1, 80-211, Gdańsk, Poland. anna.supernat@gumed.edu.pl.
Marta PopędaLaboratory of Translational Oncology, Intercollegiate Faculty of Biotechnology, University of Gdańsk and Medical University of Gdańsk, Dębinki 1, 80-211, Gdańsk, Poland.
Krzysztof PastuszakLaboratory of Translational Oncology, Intercollegiate Faculty of Biotechnology, University of Gdańsk and Medical University of Gdańsk, Dębinki 1, 80-211, Gdańsk, Poland.
Myron G BestDepartment of Neurosurgery, Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, VU University Medical Center, Amsterdam, The Netherlands.
Peter GrešnerLaboratory of Translational Oncology, Intercollegiate Faculty of Biotechnology, University of Gdańsk and Medical University of Gdańsk, Dębinki 1, 80-211, Gdańsk, Poland.
Sjors In 't VeldDepartment of Neurosurgery, Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, VU University Medical Center, Amsterdam, The Netherlands.
Bartłomiej SiekDepartment of History and Philosophy of Medical Sciences, Medical University of Gdańsk, Gdańsk, Poland.
Natalia Bednarz-KnollLaboratory of Translational Oncology, Intercollegiate Faculty of Biotechnology, University of Gdańsk and Medical University of Gdańsk, Dębinki 1, 80-211, Gdańsk, Poland.
Matthew T RondinaUniversity of Utah Molecular Medicine Program, Salt Lake City, UT, USA.
Tomasz StokowyDepartment of Clinical Science, University of Bergen, Bergen, Norway.
Thomas WurdingerDepartment of Neurosurgery, Brain Tumor Center Amsterdam, Cancer Center Amsterdam, Amsterdam UMC, VU University Medical Center, Amsterdam, The Netherlands.
Jacek JassemDepartment of Oncology and Radiotherapy, Medical University of Gdańsk, Gdańsk, Poland.
Anna J ŻaczekLaboratory of Translational Oncology, Intercollegiate Faculty of Biotechnology, University of Gdańsk and Medical University of Gdańsk, Dębinki 1, 80-211, Gdańsk, Poland.
Gdańsk Medical University · PLAmsterdam UMC Location VUmc · NLGdańsk University of Technology · PLUniversity of Bergen · NOUniversity of Utah · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Blood platelet RNA-sequencing is increasingly used among the scientific community. Aberrant platelet transcriptome is common in cancer or cardiovascular disease, but reference data on platelet RNA content in healthy individuals are scarce and merit complex investigation. We sought to explore the dynamics of platelet transcriptome. Datasets from 204 healthy donors were used for the analysis of splice variants, particularly with regard to age, sex, blood storage time, unit of collection or library size. Genes B2M, PPBP, TMSB4X, ACTB, FTL, CLU, PF4, F13A1, GNAS, SPARC, PTMA, TAGLN2, OAZ1 and OST4 demonstrated the highest expression in the analysed cohort, remaining substantial transcription consistency. CSF3R gene was found upregulated in males (fold change 2.10, FDR q < 0.05). Cohort dichotomisation according to the median age, showed upregulated KSR1 in the older donors (fold change 2.11, FDR q < 0.05). Unsupervised hierarchical clustering revealed two clusters which were irrespective of age, sex, storage time, collecting unit or library size. However, when donors are analysed globally (as vectors), sex, storage time, library size, the unit of blood collection as well as age impose a certain degree of between- and/or within-group variability. Healthy donor platelet transcriptome retains general consistency, with very few splice variants deviating from the landscape. Although multidimensional analysis reveals statistically significant variability between and within the analysed groups, biologically, these changes are minor and irrelevant while considering disease classification. Our work provides a reference for studies working both on healthy platelets and pathological conditions affecting platelet transcriptome.

Indexed as

Blood DonorsGene Expression ProfilingTranscriptomeAdultAgedBlood PlateletsComputational BiologyFemaleHealthy VolunteersHigh-Throughput Nucleotide SequencingHumansMaleMiddle AgedYoung Adult

Identifiers

PMID34344933
PMCPMC8333095
OpenAlexW3193276574

What OpenQuestion holds

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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.