Evidence map›Paper›PMID 41334935›Full record

ArticleProteomics2025

Mass Spectrometry-Based Quantification of Proteins and Post-Translational Modifications in Dried Blood: Longitudinal Sampling of Patients With Sepsis in Tanzania.

Matthew W Foster, Timothy J McMahon, James S Ngocho, Asia H Kipengele, Marlene Violette, Youwei Chen, Deng B Madut, Robert S Plumb, A Lan Wong, Lingye Chen and 8 more

Abstract read
In one paragraph

Article in Proteomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors.

Matthew W FosterDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.ORCID https://orcid.org/0000-0003-0212-2346
Timothy J McMahonDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
James S NgochoSchool of Medicine, Institute of Public Health, KCMC University, Moshi, Tanzania.
Asia H KipengeleKilimanjaro Clinical Research Institute, Kilimanjaro Christian Medical Centre, Moshi, Tanzania.
Marlene VioletteDuke Proteomics and Metabolomics Core Facility, Duke University School of Medicine, Durham, North Carolina, USA.ORCID https://orcid.org/0000-0001-9351-3996
Youwei ChenDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Deng B MadutDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Robert S PlumbWaters Corporation, Milford, Massachusetts, USA.
A Lan WongDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Lingye ChenDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Grace M LeeDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Philoteus A SakasakaKilimanjaro Clinical Research Institute, Kilimanjaro Christian Medical Centre, Moshi, Tanzania.
Blandina T MmbagaSchool of Medicine, Institute of Public Health, KCMC University, Moshi, Tanzania.
John A CrumpDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Micah T McClainDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Christopher W WoodsDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Venance P MaroKilimanjaro Clinical Research Institute, Kilimanjaro Christian Medical Centre, Moshi, Tanzania.
Matthew P RubachDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.

Funding

Sepsis Characterization in KilimanjaroR01AI155733 · NIAID · DUKE UNIVERSITY · PI RUBACH, MATTHEW P · 2020 to 2024
$3.4M
Multiomic, mass spectrometry-based analysis of dried blood for deep phenotyping of sepsisR33GM146142 · NIGMS · DUKE UNIVERSITY · PI FOSTER, MATTHEW WOLF, MCMAHON, TIMOTHY J · 2024 to 2025
$1.4M
Multiomic, mass spectrometry-based analysis of dried blood for deep phenotyping of sepsisR21GM146142 · NIGMS · DUKE UNIVERSITY · PI FOSTER, MATTHEW WOLF, MCMAHON, TIMOTHY J · 2022 to 2023
$439k
NIAID NIH HHS R01 AI155733NIGMS NIH HHS R21 GM146142NIGMS NIH HHS R33 GM146142NIH HHS R21-GM146142;R33-GM146142;R01-AI155733
6 · The paper itself

Abstract

The proteomic analysis of blood is routine for disease phenotyping and biomarker development. Blood is commonly separated into soluble and cellular fractions. However, this can introduce pre-analytical variability, and analysis of a single component (which is common) may ignore important pathophysiology. We have recently developed methods for the facile processing of dried blood for mass spectrometry-based quantification of the proteome, N-glycoproteome, and phosphoproteome. Here, we applied this approach to 38 patients in Tanzania who presented to the hospital with sepsis. Blood was collected on Mitra devices at presentation and 1, 3, and 28-42 days post-enrollment. Processing of 96 total samples was performed in plate-based formats and completed within 2 days. Approximately 2000 protein groups and 8000 post-translational modifications were quantified in 3 LC-MS/MS runs at ∼1.5 h per sample. Analysis of differential abundance revealed blood proteome signatures of acute phase response and neutrophilic inflammation that partially resolved at the 28-42 day timepoint. Numerous analytes correlated with clinical laboratory values for c-reactive protein and white blood cell counts, as well as the Universal Vital Assessment illness severity score. These datasets serve as proof-of-concept for large-scale MS-based (sub)phenotyping of disease using dried blood and are available via the ProteomeXchange consortium (PXD060377). SUMMARY: For the first time, we report the integrated quantitative analysis of proteins, N-glycopeptides, and phosphopeptides from dried blood specimens in a disease context. Sample collection on Mitra devices is easily incorporated into existing biobanking protocols and provides a convenient solution for sample storage and preparation for downstream mass spectrometry analysis. Signatures of sepsis are reflected in each of the analyzed proteomes and decline between presentation to the hospital and 1 month post. In addition to well-described markers, these analyses identify mediators of inflammation and innate immune signaling that would be missed in the more common analysis of cell-free plasma.

Indexed as

data‐independent acquisitionmicroflow liquid chromatographyN‐glycosylationOrbitrap AstralUVA scorevolumetric absorptive microsampling

Identifiers

PMID41334935
PMCPMC12925604

What OpenQuestion holds

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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 OpenQuestion graph.