Evidence map›Paper›PMID 39049875›Full record

ArticleMolecular therapy. Nucleic acids2024

Unbiased plasma profiling using pre-selected RNA aptamer pools predicts mortality in COVID-19 and identifies protein risk factors.

Asger Givskov Jørgensen, Daniel Miotto Dupont, Søren Fjelstrup, Claus Bus, Cecilie Bo Hansen, Thomas Benfield, Peter Garred, Peter M H Heegaard, Jørgen Kjems

Abstract read
In one paragraph

Article in Molecular therapy. Nucleic acids, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. 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.

Asger Givskov JørgensenInterdisciplinary Nanoscience Center, Department of Molecular Biology and Genetics, Aarhus University, 8000 Aarhus C, Denmark.
Daniel Miotto DupontInterdisciplinary Nanoscience Center, Department of Molecular Biology and Genetics, Aarhus University, 8000 Aarhus C, Denmark.
Søren FjelstrupInterdisciplinary Nanoscience Center, Department of Molecular Biology and Genetics, Aarhus University, 8000 Aarhus C, Denmark.
Claus BusInterdisciplinary Nanoscience Center, Department of Molecular Biology and Genetics, Aarhus University, 8000 Aarhus C, Denmark.
Cecilie Bo HansenLaboratory of Molecular Medicine, Department of Clinical Immunology, Rigshospitalet, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen N, Denmark.
Thomas BenfieldDepartment of Infectious Diseases, Copenhagen University Hospital - Amager and Hvidovre, 2650 Hvidovre, Denmark.
Peter GarredLaboratory of Molecular Medicine, Department of Clinical Immunology, Rigshospitalet, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen N, Denmark.
Peter M H HeegaardDepartment of Health Technology, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark.
Jørgen KjemsInterdisciplinary Nanoscience Center, Department of Molecular Biology and Genetics, Aarhus University, 8000 Aarhus C, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The impact of the COVID-19 pandemic demands effective prognostic tools for precise risk evaluation and timely intervention. This study utilized the APTASHAPE technology to profile plasma proteins in COVID-19 patient samples. Employing a highly diverse 2'-fluoro-protected RNA aptamer pool enriched toward proteins in the plasma samples from COVID-19 patients, we performed a single round of parallel selection on the derivation cohort and identified 93 discriminatory aptamers capable of distinguishing COVID-19 and healthy plasma samples. A subset of these aptamers was then used to predict 30-day mortality with high sensitivity and specificity in a validation cohort of 165 patients. We predicted 30-day mortality with areas under the curve (AUCs) of 0.91 in females and 0.68 in males. Affinity purification coupled with mass spectrometry analysis of the aptamer-targeted proteins identified potential biomarkers associated with disease severity, including complement system components. The study demonstrates the APTASHAPE technology as an unbiased approach that not only aids in predicting disease outcomes but also offers insights into gender-specific differences, shedding light on the nuanced aspects of COVID-19 pathophysiology. In conclusion, the findings highlight the promise of APTASHAPE as a valuable tool for estimating risk factors in COVID-19 patients and enabling stratification for personalized treatment management.

Indexed as

biomarker discoveryblood analysishigh-throughput screeningMT: Oligonucleotides: Diagnostics and Biosensorsnanotechnologynext-generation sequencingNGSprecision medicineprognostic applicationsprotein biomarkersproteomicsRNA aptamers

Identifiers

PMID39049875
PMCPMC11268108

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.