Evidence map›Paper›PMID 39183295›Full record

ArticleBMC medicine2024

No evidence that ACE2 or TMPRSS2 drive population disparity in COVID risks.

Nathaniel M Pearson, John Novembre

Abstract readLetter
In one paragraph

Article in BMC medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Nathaniel M PearsonRoot Deep Insight, Boston, MA, USA. nathaniel.pearson@gmail.com.ORCID 0000-0002-9458-4435
John NovembreDepartment of Human Genetics, University of Chicago, Chicago, IL, USA.

Funding

Theory, Methods, and Resources for Understanding and Leveraging Spatial Variation in Population Genetic DataR35GM149521 · NIGMS · UNIVERSITY OF CHICAGO · PI John Novembre · 2023 to 2026
$1.7M
NIGMS NIH HHS R35 GM149521
6 · The paper itself

Abstract

Early in the SARS-CoV2 pandemic, in this journal, Hou et al. (BMC Med 18:216, 2020) interpreted public genotype data, run through functional prediction tools, as suggesting that members of particular human populations carry potentially COVID-risk-increasing variants in genes ACE2 and TMPRSS2 far more often than do members of other populations. Beyond resting on predictions rather than clinical outcomes, and focusing on variants too rare to typify population members even jointly, their claim mistook a well known artifact (that large samples reveal more of a population's variants than do small samples) as if showing real and congruent population differences for the two genes, rather than lopsided population sampling in their shared source data. We explain that artifact, and contrast it with empirical findings, now ample, that other loci shape personal COVID risks far more significantly than do ACE2 and TMPRSS2-and that variation in ACE2 and TMPRSS2 per se unlikely exacerbates any net population disparity in the effects of such more risk-informative loci.

Indexed as

Angiotensin-Converting Enzyme 2COVID-19SARS-CoV-2Serine EndopeptidasesGenetic Predisposition to DiseaseHumansACE2 protein, humanAngiotensin-Converting Enzyme 2Serine EndopeptidasesTMPRSS2 protein, humanACE2COVIDCOVID19Functional predictionGWASHost geneticsHuman genesImmunityInfectionPolygenic riskPopulation geneticsPopulation structureRare variantsSample designSample sizeSamplingSARS-CoV2TMPRSS2

Identifiers

PMID39183295
PMCPMC11346279

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.