Evidence map›Paper›PMID 36572854›Full record

ArticleClinical proteomics2022

Novel plasma protein biomarkers from critically ill sepsis patients.

Logan R Van Nynatten, Marat Slessarev, Claudio M Martin, Aleks Leligdowicz, Michael R Miller, Maitray A Patel, Mark Daley, Eric K Patterson, Gediminas Cepinskas, Douglas D Fraser

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Article in Clinical proteomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

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

  1. Pooled it
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  7. Proteomic profiling and pathway analyses reveal molecular signatures and immune networks in pediatric sepsis.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 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

10 authors.

Logan R Van NynattenMedicine, Western University, London, ON, Canada.
Marat SlessarevMedicine, Western University, London, ON, Canada.
Claudio M MartinMedicine, Western University, London, ON, Canada.
Aleks LeligdowiczMedicine, Western University, London, ON, Canada.
Michael R MillerLawson Health Research Institute, London, ON, Canada.
Maitray A PatelComputer Science, Western University, London, ON, N6A 3K7, Canada.
Mark DaleyLawson Health Research Institute, London, ON, Canada.
Eric K PattersonLawson Health Research Institute, London, ON, Canada.
Gediminas CepinskasLawson Health Research Institute, London, ON, Canada.
Douglas D FraserLawson Health Research Institute, London, ON, Canada. douglas.fraser@lhsc.on.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite the high morbidity and mortality associated with sepsis, the relationship between the plasma proteome and clinical outcome is poorly understood. In this study, we used targeted plasma proteomics to identify novel biomarkers of sepsis in critically ill patients.

methodsBlood was obtained from 15 critically ill patients with suspected/confirmed sepsis (Sepsis-3.0 criteria) on intensive care unit (ICU) Day-1 and Day-3, as well as age- and sex-matched 15 healthy control subjects. A total of 1161 plasma proteins were measured with proximal extension assays. Promising sepsis biomarkers were narrowed with machine learning and then correlated with relevant clinical and laboratory variables.

resultsThe median age for critically ill sepsis patients was 56 (IQR 51-61) years. The median MODS and SOFA values were 7 (IQR 5.0-8.0) and 7 (IQR 5.0-9.0) on ICU Day-1, and 4 (IQR 3.5-7.0) and 6 (IQR 3.5-7.0) on ICU Day-3, respectively. Targeted proteomics, together with feature selection, identified the leading proteins that distinguished sepsis patients from healthy control subjects with ≥ 90% classification accuracy; 25 proteins on ICU Day-1 and 26 proteins on ICU Day-3 (6 proteins overlapped both ICU days; PRTN3, UPAR, GDF8, NTRK3, WFDC2 and CXCL13). Only 7 of the leading proteins changed significantly between ICU Day-1 and Day-3 (IL10, CCL23, TGFα1, ST2, VSIG4, CNTN5, and ITGAV; P < 0.01). Significant correlations were observed between a variety of patient clinical/laboratory variables and the expression of 15 proteins on ICU Day-1 and 14 proteins on ICU Day-3 (P < 0.05).

conclusionsTargeted proteomics with feature selection identified proteins altered in critically ill sepsis patients relative to healthy control subjects. Correlations between protein expression and clinical/laboratory variables were identified, each providing pathophysiological insight. Our exploratory data provide a rationale for further hypothesis-driven sepsis research.

Indexed as

BiomarkersCritical careICUProteomicsSepsis

Identifiers

PMID36572854
PMCPMC9792322

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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 OpenQuestion graph.