Evidence map›Paper›PMID 39497142›Full record

ArticleRetrovirology2024

Shared and unique patterns of autonomous human endogenous retrovirus loci transcriptomes in CD14 + monocytes from individuals with physical trauma or infection with COVID-19.

Hyunmin Koo, Casey D Morrow

Abstract read
In one paragraph

Article in Retrovirology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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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

2 authors.

Hyunmin KooDepartment of Genetics Hugh Kaul Precision Medicine Institute, University of Alabama at Birmingham, Birmingham, Alabama, United States of America. khmkhm87@uab.edu.
Casey D MorrowDepartment of Cell, Developmental and Integrative Biology Hugh Kaul Precision Medicine Institute, University of Alabama at Birmingham, Birmingham, Alabama, United States of America. caseym@uab.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since previous studies have suggested that the RNAs of human endogenous retrovirus (HERV) might be involved in regulating innate immunity, it is important to investigate the HERV transcriptome patterns in innate immune cell types such as CD14 + monocytes. Using single cell RNA-seq datasets from resting or stimulated PBMCs mapped to 3,220 known discrete autonomous proviral HERV loci, we found individual-specific variation in HERV transcriptomes between HERV loci in CD14 + monocytes. Analysis of paired datasets from the same individual that were cultured in vitro with LPS or without (i.e. control) revealed 36 HERV loci in CD14 + monocytes that were detected only after activation. To extend our analysis to in vivo activated CD14 + monocytes, we used two scRNA-seq datasets from studies that had demonstrated activation of circulating CD14 + monocytes in patients with physical trauma or patients hospitalized with COVID-19 infections. For direct comparison between the trauma and COVID-19 datasets, we first analyzed 1.625 billion sequence reads from a composite pangenome control of 21 normal individuals. Comparison of the sequence read depth of HERV loci in the trauma or COVID-19 samples to the pangenome control revealed that 39 loci in the COVID-19 and 11 HERV loci in the trauma samples were significantly different (Mann-Whitney U test), with 9 HERV loci shared between the COVID-19 and trauma datasets. The capacity to compare HERV loci transcriptome patterns in innate immune cells, like CD14 + monocytes, across different pathological conditions will lead to greater understanding of the physiological role of HERV expression in health and disease.

Indexed as

COVID-19Endogenous RetrovirusesLipopolysaccharide ReceptorsMonocytesSARS-CoV-2TranscriptomeWounds and InjuriesFemaleGenetic LociHumansImmunity, InnateMaleCD14 protein, humanLipopolysaccharide ReceptorsAutonomous HERV transcriptomeCD14+monocytesCOVID-19Innate immunityPangenomeScRNA-seq

Identifiers

PMID39497142
PMCPMC11533341

What Socratic holds

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LicenceCC BY
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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.