Evidence map›Paper›PMID 41353157›Full record

ArticleJournal of neuroinflammation2025

Early peripheral blood gene expression predicts 90-day outcomes following subarachnoid hemorrhage.

Bodie Knepp, Garreck H Lenz, Frank R Sharp, Fernando Rodriguez, Huimahn Alex Choi, Aaron M Gusdon, Glen Jickling, Lara L Zimmermann, Ryan Martin, Jeffrey Vitt and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of neuroinflammation, 2025. 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

18 authors.

Bodie KneppDepartment of Neurology, School of Medicine, University of California at Davis, Sacramento, CA, USA. baknepp@health.ucdavis.edu.
Garreck H LenzDepartment of Neurology, School of Medicine, University of California at Davis, Sacramento, CA, USA.
Frank R SharpDepartment of Neurology, School of Medicine, University of California at Davis, Sacramento, CA, USA.
Fernando RodriguezDepartment of Neurology, School of Medicine, University of California at Davis, Sacramento, CA, USA.
Huimahn Alex ChoiDepartment of Neurosurgery, UT Health Houston McGovern Medical School, Houston, TX, USA.
Aaron M GusdonDepartment of Neurosurgery, UT Health Houston McGovern Medical School, Houston, TX, USA.
Glen JicklingDivision of Neurology in Department of Medicine, University of Alberta, Alberta, Canada.
Lara L ZimmermannDepartment of Neurology, School of Medicine, University of California at Davis, Sacramento, CA, USA.
Ryan MartinDepartment of Neurology, School of Medicine, University of California at Davis, Sacramento, CA, USA.
Jeffrey VittDepartment of Neurology, School of Medicine, University of California at Davis, Sacramento, CA, USA.
Ben WaldauDepartment of Neurosurgery, School of Medicine, University of California at Davis, Sacramento, CA, USA.
Brandon J CordDepartment of Neurosurgery, School of Medicine, University of California at Davis, Sacramento, CA, USA.
Alan YeeDepartment of Neurology, School of Medicine, University of California at Davis, Sacramento, CA, USA.
Kwan NgDepartment of Neurology, School of Medicine, University of California at Davis, Sacramento, CA, USA.
Nerissa U KoDepartment of Neurology, University of California at San Francisco, San Francisco, CA, USA.
Heather HullDepartment of Neurology, School of Medicine, University of California at Davis, Sacramento, CA, USA.
Bradley P AnderDepartment of Neurology, School of Medicine, University of California at Davis, Sacramento, CA, USA.
Boryana StamovaDepartment of Neurology, School of Medicine, University of California at Davis, Sacramento, CA, USA. bsstamova@health.ucdavis.edu.

Funding

Biomarker Signatures for Delayed Cerebral Ischemia and Outcome Following Subarachnoid HemorrhageR61NS119345 · NINDS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Bradley Pearce Ander, FRANK R SHARP · 2022 to 2023
$1.3M
Whole Transcriptome Studies of Blood to Predict Stroke OutcomeR01NS127976 · UNIVERSITY OF CALIFORNIA AT DAVIS · 2025 to 2025
$642k
Biomarker Signatures for Delayed Cerebral Ischemia and Outcome Following Subarachnoid HemorrhageR33NS119345 · UNIVERSITY OF CALIFORNIA AT DAVIS · 2025 to 2025
$543k
NINDS NIH HHS R01 NS127976NINDS NIH HHS R33 NS119345NINDS NIH HHS R61 NS119345
6 · The paper itself

Abstract

backgroundPrevious clinical, radiological and machine learning studies have predicted 90-day outcomes following subarachnoid hemorrhage (SAH). The present study was designed to determine whether early changes in mRNA expression of immune, clotting and other genes expressed in peripheral blood can predict patient outcomes at 90 days after SAH and possibly provide insights into the molecular factors that promote good versus poor outcomes.

methodsPeripheral blood was drawn after SAH and from vascular risk factor controls (VRFC) and RNAseq performed to measure mRNA expression. A mixed effects regression model identified potential predictors and machine learning algorithms derived the best predictors of 90-day SAH outcome as measured by modified Rankin Score (mRS) for a derivation cohort (23 Poor and 37 Good SAH Outcome patients, 48 VRFC). The model trained on the derivation cohort was then used to predict 90-day SAH outcome in an independent validation cohort (15 Poor and 23 Good SAH Outcome). Enrichment analyses for cell-type specific genes, canonical pathways, and biological processes were performed for the predictor genes.

resultsThe mixed effects regression on the derivation cohort yielded 94 genes from which 20 were selected through feature reduction. Machine learning algorithms were optimized to generate a model that predicted SAH 90-day outcome with AUC = 0.85, sensitivity = 87%, and specificity = 84% on cross-validation. Application of this model to the independent validation cohort yielded AUC = 0.84, sensitivity = 93%, and specificity = 74%. The 20 predictors were significantly enriched in genes from neutrophils and erythroblasts and in nine pathways including the Unfolded Protein Response, Neutrophil Degranulation, and Neutrophil Extracellular Trap Signaling.

conclusionsThis discovery study demonstrates that a small panel of 20 genes expressed in peripheral blood after SAH has the potential for predicting 90-day outcomes following SAH. It also shows that neutrophils may be important drivers of SAH outcomes and could represent therapeutic targets.

Indexed as

Gene ExpressionSubarachnoid HemorrhageAdultAgedCohort StudiesFemaleHumansMachine LearningMaleMiddle AgedPredictive Value of TestsPrognosisBiomarkersGenesHumanMachine-learningNeutrophilsOutcomeRNA-SeqSubarachnoid hemorrhage

Identifiers

PMID41353157
PMCPMC12690849

What Socratic holds

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LicenceCC BY
Read underepoch 390

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.