Evidence map›Paper›PMID 35012625›Full record

ArticleGenome biology2022

Systematic identification of ACE2 expression modulators reveals cardiomyopathy as a risk factor for mortality in COVID-19 patients.

Navchetan Kaur, Boris Oskotsky, Atul J Butte, Zicheng Hu

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.8field-weighted citation impact, top 8% 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

12 citing papers in PubMed, 28 citations in OpenAlex.

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  6. RummaGEO: Automatic Mining of Human and Mouse Gene Sets from GEO.bioRxiv : the preprint server for biology · 2024
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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

4 authors at 1 institution in 1 country.

Navchetan KaurBakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA.
Boris OskotskyBakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA.
Atul J ButteBakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA.
Zicheng HuBakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA. zicheng.hu@ucsf.edu.ORCID 0000-0002-4168-1725
University of California, San Francisco · US

Funding

Illuminating Druggable Dark MatterU24DK116214 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI JAN, LILY Y, MCMANUS, MICHAEL T · 2017 to 2022
$12.9M
Pan-vaccine Analysis to Test the Impact of Cytomegalovirus on Vaccine EfficacyUH2AI153016 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HU, ZICHENG · 2020 to 2021
$444k
NIAID NIH HHS HHSN272201200028CNIAID NIH HHS UH2 AI153016NIDDK NIH HHS U24 DK116214
6 · The paper itself

Abstract

backgroundAngiotensin-converting enzyme 2 (ACE2) is the cell-entry receptor for SARS-CoV-2. It plays critical roles in both the transmission and the pathogenesis of COVID-19. Comprehensive profiling of ACE2 expression patterns could reveal risk factors of severe COVID-19 illness. While the expression of ACE2 in healthy human tissues has been well characterized, it is not known which diseases and drugs might be associated with ACE2 expression.

resultsWe develop GENEVA (GENe Expression Variance Analysis), a semi-automated framework for exploring massive amounts of RNA-seq datasets. We apply GENEVA to 286,650 publicly available RNA-seq samples to identify any previously studied experimental conditions that could be directly or indirectly associated with ACE2 expression. We identify multiple drugs, genetic perturbations, and diseases that are associated with the expression of ACE2, including cardiomyopathy, HNF1A overexpression, and drug treatments with RAD140 and itraconazole. Our joint analysis of seven datasets confirms ACE2 upregulation in all cardiomyopathy categories. Using electronic health records data from 3936 COVID-19 patients, we demonstrate that patients with pre-existing cardiomyopathy have an increased mortality risk than age-matched patients with other cardiovascular conditions. GENEVA is applicable to any genes of interest and is freely accessible at http://genevatool.org .

conclusionsThis study identifies multiple diseases and drugs that are associated with the expression of ACE2. The effect of these conditions should be carefully studied in COVID-19 patients. In particular, our analysis identifies cardiomyopathy patients as a high-risk group, with increased ACE2 expression in the heart and increased mortality after SARS-COV-2 infection.

Indexed as

Cardiovascular DiseasesAdultAgedAngiotensin-Converting Enzyme 2CardiomyopathiesCOVID-19FemaleGene ExpressionHumansMaleMiddle AgedMortalityRisk FactorsRNA-SeqSARS-CoV-2ACE2 protein, humanAngiotensin-Converting Enzyme 2

Identifiers

PMID35012625
PMCPMC8743438
OpenAlexW4205642148

What OpenQuestion holds

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LicenceCC BY
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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.