Evidence map›Paper›PMID 35923315›Full record

ArticlemedRxiv : the preprint server for health sciences2022

Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer and coronary disease pathways.

Lihua Wang, Dan Western, Jigyasha Timsina, Charlie Repaci, Won-Min Song, Joanne Norton, Pat Kohlfeld, John Budde, Sharlee Climer, Omar H Butt and 12 more

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2022. 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, 4 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

22 authors at 5 institutions in 1 country.

Lihua WangDepartment of Psychiatry, Washington University School of Medicine, St Louis, MO, USA.
Dan WesternDepartment of Psychiatry, Washington University School of Medicine, St Louis, MO, USA.
Jigyasha TimsinaDepartment of Psychiatry, Washington University School of Medicine, St Louis, MO, USA.
Charlie RepaciDepartment of Psychiatry, Washington University School of Medicine, St Louis, MO, USA.
Won-Min SongDepartment of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Joanne NortonDepartment of Psychiatry, Washington University School of Medicine, St Louis, MO, USA.
Pat KohlfeldDepartment of Psychiatry, Washington University School of Medicine, St Louis, MO, USA.
John BuddeDepartment of Psychiatry, Washington University School of Medicine, St Louis, MO, USA.
Sharlee ClimerDepartment of Computer Science, University of Missouri-St. Louis, St. Louis, MO, USA.
Omar H ButtDepartment of Neurology, Washington University School of Medicine, St Louis, MO, USA.
Daniel JacobsonBiosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA.
Michael GarvinBiosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA.
Alan R TempletonDepartment of Biology, Washington University School of Medicine, St Louis, MO, USA.
Shawn CampagnaDepartment of Chemistry, University of Tennessee, Knoxville, TN, USA.
Jane O'HalloranDivision of Infectious Diseases, Washington University School of Medicine, St Louis, MO, USA.
Rachel PrestiDivision of Infectious Diseases, Washington University School of Medicine, St Louis, MO, USA.
Charles W GossDivision of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA.
Philip A MuddDepartment of Emergency Medicine, Washington University School of Medicine, St Louis, MO, USA.
Beau M AncesDepartment of Neurology, Washington University School of Medicine, St Louis, MO, USA.
Bin ZhangDepartment of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Yun Ju SungDepartment of Psychiatry, Washington University School of Medicine, St Louis, MO, USA.
Carlos CruchagaDepartment of Psychiatry, Washington University School of Medicine, St Louis, MO, USA.
Washington University in St. Louis · USIcahn School of Medicine at Mount Sinai · USOak Ridge National Laboratory · USUniversity of Missouri–St. Louis · USUniversity of Tennessee at Knoxville · US

Funding

Washington University Center for Cellular ImagingP30CA091842 · NCI · WASHINGTON UNIVERSITY · PI AIMEE S JAMES · 2001 to 2026
$128.0M
WU INSTITUTE OF CLINICAL AND TRANSLATIONAL SCIENCESUL1TR002345 · NCATS · WASHINGTON UNIVERSITY · PI William G. Powderly · 2017 to 2026
$97.8M
Smartphone-Based "Burst" Cognitive AssessmentsP01AG003991 · NIA · WASHINGTON UNIVERSITY · PI JOHN MORRIS · 1985 to 2026
$69.5M
The natural history of AB accumulation in preclinical ADP01AG026276 · NIA · WASHINGTON UNIVERSITY · PI MORRIS, JOHN · 2005 to 2025
$49.5M
Research Education ComponentP30AG066444 · NIA · WASHINGTON UNIVERSITY · PI DAVID M. HOLTZMAN · 2020 to 2026
$28.7M
USING QUANTITATIVE TRAITS TO IDENTIFY NOVEL GENES FOR ALZHEIMERS DISEASE AND OTHER COMPLEX TRAITSRF1AG053303 · NIA · WASHINGTON UNIVERSITY · PI CLIMER, SHARLEE, CRUCHAGA, CARLOS · 2016 to 2020
$4.0M
GENETIC MODIFIERS OF CEREBROSPINAL FLUID TREM2 IN ALZHEIMER'S DISEASERF1AG058501 · NIA · WASHINGTON UNIVERSITY · PI CRUCHAGA, CARLOS, PICCIO, LAURA · 2018 to 2018
$3.5M
The Familial Alzheimer Sequencing (FASe) ProjectU01AG058922 · NIA · WASHINGTON UNIVERSITY · PI CRUCHAGA, CARLOS, GOATE, ALISON M · 2018 to 2022
$3.5M
Sex-specific Molecular Profiling to Understand Pathology and Identify Causal Genes and Drug Targets for Alzheimer's DiseaseRF1AG074007 · NIA · WASHINGTON UNIVERSITY · PI SUNG, YUNJU · 2021 to 2021
$2.7M
IDENTIFYING RARE VARIANTS THAT INCREASE RISK FOR ALZHEIMER'S DISEASER01AG044546 · NIA · WASHINGTON UNIVERSITY · PI CRUCHAGA, CARLOS · 2013 to 2017
$2.7M
Training OPportunities in Translational Imaging Education and Research (TOP-TIER)T32EB021955 · NIBIB · WASHINGTON UNIVERSITY · PI Hongyu An, Joseph Edward Ippolito · 2017 to 2026
$2.4M
NCATS NIH HHS UL1 TR002345NCI NIH HHS P30 CA091842NIA NIH HHS P01 AG003991NIA NIH HHS P01 AG026276NIA NIH HHS P30 AG066444NIA NIH HHS R01 AG044546NIA NIH HHS RF1 AG053303NIA NIH HHS RF1 AG058501NIA NIH HHS RF1 AG074007NIA NIH HHS U01 AG058922NIBIB NIH HHS T32 EB021955
6 · The paper itself

Abstract

Identification of the plasma proteomic changes of Coronavirus disease 2019 (COVID-19) is essential to understanding the pathophysiology of the disease and developing predictive models and novel therapeutics. We performed plasma deep proteomic profiling from 332 COVID-19 patients and 150 controls and pursued replication in an independent cohort (297 cases and 76 controls) to find potential biomarkers and causal proteins for three COVID-19 outcomes (infection, ventilation, and death). We identified and replicated 1,449 proteins associated with any of the three outcomes (841 for infection, 833 for ventilation, and 253 for death) that can be query on a web portal ( https://covid.proteomics.wustl.edu/ ). Using those proteins and machine learning approached we created and validated specific prediction models for ventilation (AUC>0.91), death (AUC>0.95) and either outcome (AUC>0.80). These proteins were also enriched in specific biological processes, including immune and cytokine signaling (FDR ≤ 3.72×10

Identifiers

PMID35923315
PMCPMC9347279
OpenAlexW4287878548

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.