Evidence map›Paper›PMID 38897207›Full record

ArticleCell genomics2024

eQTLs identify regulatory networks and drivers of variation in the individual response to sepsis.

Katie L Burnham, Nikhil Milind, Wanseon Lee, Andrew J Kwok, Kiki Cano-Gamez, Yuxin Mi, Cyndi G Geoghegan, Ping Zhang, GAinS Investigators, Stuart McKechnie and 4 more

Abstract read
In one paragraph

Article in Cell genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  6. Progenitor CD8Apoptosis : an international journal on programmed cell death · 2026
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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

14 authors.

Katie L BurnhamWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Nikhil MilindWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK; University of Cambridge, Cambridge, UK.
Wanseon LeeWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Andrew J KwokCentre for Human Genetics, University of Oxford, Oxford, UK.
Kiki Cano-GamezWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK; Centre for Human Genetics, University of Oxford, Oxford, UK.
Yuxin MiCentre for Human Genetics, University of Oxford, Oxford, UK.
Cyndi G GeogheganCentre for Human Genetics, University of Oxford, Oxford, UK.
Ping ZhangCentre for Human Genetics, University of Oxford, Oxford, UK; Chinese Academy of Medical Science Oxford Institute, University of Oxford, Oxford, UK.
GAinS Investigators
Stuart McKechnieOxford University Hospitals NHS Foundation Trust, Oxford, UK.
Nicole SoranzoWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Charles J HindsCentre for Translational Medicine & Therapeutics, William Harvey Research Institute, Faculty of Medicine & Dentistry, Queen Mary University of London, London, UK.
Julian C KnightCentre for Human Genetics, University of Oxford, Oxford, UK; Chinese Academy of Medical Science Oxford Institute, University of Oxford, Oxford, UK. Electronic address: julian@well.ox.ac.uk.
Emma E DavenportWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK. Electronic address: ed5@sanger.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sepsis is a clinical syndrome of life-threatening organ dysfunction caused by a dysregulated response to infection, for which disease heterogeneity is a major obstacle to developing targeted treatments. We have previously identified gene-expression-based patient subgroups (sepsis response signatures [SRS]) informative for outcome and underlying pathophysiology. Here, we aimed to investigate the role of genetic variation in determining the host transcriptomic response and to delineate regulatory networks underlying SRS. Using genotyping and RNA-sequencing data on 638 adult sepsis patients, we report 16,049 independent expression (eQTLs) and 32 co-expression module (modQTLs) quantitative trait loci in this disease context. We identified significant interactions between SRS and genotype for 1,578 SNP-gene pairs and combined transcription factor (TF) binding site information (SNP2TFBS) and predicted regulon activity (DoRothEA) to identify candidate upstream regulators. Overall, these approaches identified putative mechanistic links between host genetic variation, cell subtypes, and the individual transcriptomic response to infection.

Indexed as

Gene Regulatory NetworksPolymorphism, Single NucleotideQuantitative Trait LociSepsisAdultFemaleGenotypeHumansMaleMiddle AgedTranscription FactorsTranscriptomeTranscription Factorsco-expressioneQTLgenomicsinfectionsepsistranscriptomics

Identifiers

PMID38897207
PMCPMC11293594

What Socratic 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 Socratic graph.