Evidence map›Paper›PMID 36537079›Full record

ArticleeLife2022

Cross-talk between red blood cells and plasma influences blood flow and omics phenotypes in severe COVID-19.

Steffen M Recktenwald, Greta Simionato, Marcelle G M Lopes, Fabia Gamboni, Monika Dzieciatkowska, Patrick Meybohm, Kai Zacharowski, Andreas von Knethen, Christian Wagner, Lars Kaestner and 2 more

Open access · goldAbstract read
In one paragraph

Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
3.4field-weighted citation impact, top 6% 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

21 citing papers in PubMed, 29 citations in OpenAlex.

  1. High-Throughput Metabolomics in Transfusion Medicine.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
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  3. It's in your blood: The impact of age, sex, genetic factors and exposures on stored red blood cell metabolism.Transfusion and apheresis science : official journal of the World Apheresis Association : official journal of the European Society for Haemapheresis · 2024
    Review
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  15. Big Data in Transfusion Medicine and Artificial Intelligence Analysis for Red Blood Cell Quality Control.Transfusion medicine and hemotherapy : offizielles Organ der Deutschen Gesellschaft fur Transfusionsmedizin und Immunhamatologie · 2023
    Review
  16. Red Blood Cell Omics and Machine Learning in Transfusion Medicine: Singularity Is Near.Transfusion medicine and hemotherapy : offizielles Organ der Deutschen Gesellschaft fur Transfusionsmedizin und Immunhamatologie · 2023
    Review
  17. Article
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  20. Review
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

12 authors at 5 institutions in 3 countries.

Steffen M Recktenwald *Dynamics of Fluids, Department of Experimental Physics, Saarland University, Saarbrücken, Germany.ORCID 0000-0003-1235-1521
Greta Simionato *Dynamics of Fluids, Department of Experimental Physics, Saarland University, Saarbrücken, Germany.ORCID 0000-0001-5452-2275
Marcelle G M LopesDynamics of Fluids, Department of Experimental Physics, Saarland University, Saarbrücken, Germany.ORCID 0000-0002-9668-5504
Fabia GamboniDepartment of Biochemistry and Molecular Genetics, University of Colorado Denver, Aurora, United States.ORCID 0000-0002-0855-9138
Monika DzieciatkowskaDepartment of Biochemistry and Molecular Genetics, University of Colorado Denver, Aurora, United States.
Patrick MeybohmDepartment of Anesthesiology, Intensive Care, Emergency and Pain Medicine, University Hospital Wuerzburg, Wuerzburg, Germany.ORCID 0000-0002-2666-8696
Kai ZacharowskiDepartment of Anesthesiology, Intensive Care Medicine and Pain Therapy, University Hospital Frankfurt, Frankfurt, Germany.ORCID 0000-0002-0212-9110
Andreas von KnethenDepartment of Anesthesiology, Intensive Care Medicine and Pain Therapy, University Hospital Frankfurt, Frankfurt, Germany.ORCID 0000-0002-5831-0365
Christian WagnerDynamics of Fluids, Department of Experimental Physics, Saarland University, Saarbrücken, Germany.ORCID 0000-0001-7788-4594
Lars KaestnerDynamics of Fluids, Department of Experimental Physics, Saarland University, Saarbrücken, Germany.ORCID 0000-0001-6796-9535
Angelo D'AlessandroDepartment of Biochemistry and Molecular Genetics, University of Colorado Denver, Aurora, United States.
Stephan QuintDynamics of Fluids, Department of Experimental Physics, Saarland University, Saarbrücken, Germany.ORCID 0000-0003-4412-7559
Saarland University · DEUniversity of Colorado Denver · USGoethe University Frankfurt · DEUniversitätsklinikum Würzburg · DEUniversity of Luxembourg · LU

Funding

Resuscitation Strategies for Achieving Thrombo-inflammatory HomeostasisRM1GM131968 · NIGMS · UNIVERSITY OF COLORADO DENVER · PI COHEN, MITCHELL, D'ALESSANDRO, ANGELO · 2019 to 2023
$11.3M
The Impact of Oxidative Stress on Erythocyte BiologyR01HL148151 · NHLBI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI D'ALESSANDRO, ANGELO, KARAFIN, MATTHEW S · 2019 to 2022
$8.9M
The role of ferroptosis in red cell aging in vivo and in vitroR01HL146442 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI Angelo D'Alessandro, Adam N. Goldfarb · 2019 to 2026
$5.4M
The paradoxical response to iron in pulmonary hypertension of sickle cell diseaseR01HL161004 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI BUEHLER, PAUL WERNER, D'ALESSANDRO, ANGELO · 2022 to 2025
$2.7M
Interactions between the ADORA2b/Sphk1axis and the AE1-Hb switch in red blood cell aging in vivo and in vitroR01HL149714 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI D'ALESSANDRO, ANGELO · 2020 to 2023
$2.6M
MIRAGES: Metabolic Investigation of Red blood cells as a function of Aging, Genetics, Environment, and StorageR21HL150032 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI D'ALESSANDRO, ANGELO · 2020 to 2021
$414k
NHLBI NIH HHS R01 HL146442NHLBI NIH HHS R01 HL148151NHLBI NIH HHS R01 HL149714NHLBI NIH HHS R01 HL161004NHLBI NIH HHS R21 HL150032NIGMS NIH HHS RM1 GM131968
6 · The paper itself

Abstract

Coronavirus disease 2019 (COVID-19) is caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and can affect multiple organs, among which is the circulatory system. Inflammation and mortality risk markers were previously detected in COVID-19 plasma and red blood cells (RBCs) metabolic and proteomic profiles. Additionally, biophysical properties, such as deformability, were found to be changed during the infection. Based on such data, we aim to better characterize RBC functions in COVID-19. We evaluate the flow properties of RBCs in severe COVID-19 patients admitted to the intensive care unit by using microfluidic techniques and automated methods, including artificial neural networks, for an unbiased RBC analysis. We find strong flow and RBC shape impairment in COVID-19 samples and demonstrate that such changes are reversible upon suspension of COVID-19 RBCs in healthy plasma. Vice versa, healthy RBCs resemble COVID-19 RBCs when suspended in COVID-19 plasma. Proteomics and metabolomics analyses allow us to detect the effect of plasma exchanges on both plasma and RBCs and demonstrate a new role of RBCs in maintaining plasma equilibria at the expense of their flow properties. Our findings provide a framework for further investigations of clinical relevance for therapies against COVID-19 and possibly other infectious diseases.

Indexed as

COVID-19Erythrocyte DeformabilityErythrocytesHumansProteomicsSARS-CoV-2bloodcell biologyCOVID-19humanmicrofluidicsomicsphysics of living systemsred blood cells

Identifiers

PMID36537079
PMCPMC9767455
OpenAlexW4311949574

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.