Evidence map›Paper›PMID 34015823›Full record

ArticleBriefings in bioinformatics2021

COVID-19 biomarkers and their overlap with comorbidities in a disease biomarker data model.

Nikhita Gogate, Daniel Lyman, Amanda Bell, Edmund Cauley, Keith A Crandall, Ashia Joseph, Robel Kahsay, Darren A Natale, Lynn M Schriml, Sabyasach Sen and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.4field-weighted citation impact, top 16% of its field
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

11 citing papers in PubMed, 24 citations in OpenAlex.

  1. Admission biomarkers and COVID-19 mortality: A retrospective study during Vietnam's pandemic peak.Journal of critical care medicine (Universitatea de Medicina si Farmacie din Targu-Mures) · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 1 country.

Nikhita GogateGeorge Washington University School of Medicine and Health Sciences, Washington, DC 20037, USA.
Daniel LymanGeorge Washington University School of Medicine and Health Sciences, Department of Biochemistry and Molecular Medicine, Washington, DC 20037, USA.
Amanda BellGeorge Washington University School of Medicine and Health Sciences, Washington, DC 20037, USA.
Edmund CauleyGeorge Washington University School of Medicine and Health Sciences, Washington, DC 20037, USA.
Keith A CrandallComputational Biology Institute at The George Washington University, Washington, DC 20037, USA.
Ashia JosephGeorge Washington University, Washington, DC 20037, USA.
Robel KahsayGeorge Washington University School of Medicine and Health Sciences, Department of Biochemistry and Molecular Medicine, Washington, DC 20037, USA.
Darren A NataleGeorgetown University Medical Center, Washington, DC 20037, USA.
Lynn M SchrimlUniversity of Maryland, School of Medicine in Baltimore, MD, USA.
Sabyasach SenGeorge Washington University School of Medicine and Health Sciences, Washington, DC 20037, USA.
Raja MazumderDepartment of Biochemistry and Molecular Medicine, The George Washington University Medical Center, Washington, DC 20037, USA.
George Washington University · USGeorgetown University Medical Center · USUniversity of Maryland, Baltimore · US

Funding

The Disease Ontology Project: mechanistic profiles of human disease for biomedical and clinical researchU41HG008735 · NHGRI · UNIVERSITY OF MARYLAND BALTIMORE · PI SCHRIML, LYNN MARIE · 2017 to 2021
$3.4M
Integration of comprehensive cancer mutation and expression-associated data for biomarker evaluation and discoveryU01CA215010 · NCI · GEORGE WASHINGTON UNIVERSITY · PI CRICHTON, DANIEL, MAZUMDER, RAJA · 2017 to 2019
$1.3M
National Science Foundation DEB-2028280NCI NIH HHS U01 CA215010NCI NIH HHS U01CA215010NHGRI NIH HHS U41 HG008735
6 · The paper itself

Abstract

In response to the COVID-19 outbreak, scientists and medical researchers are capturing a wide range of host responses, symptoms and lingering postrecovery problems within the human population. These variable clinical manifestations suggest differences in influential factors, such as innate and adaptive host immunity, existing or underlying health conditions, comorbidities, genetics and other factors-compounding the complexity of COVID-19 pathobiology and potential biomarkers associated with the disease, as they become available. The heterogeneous data pose challenges for efficient extrapolation of information into clinical applications. We have curated 145 COVID-19 biomarkers by developing a novel cross-cutting disease biomarker data model that allows integration and evaluation of biomarkers in patients with comorbidities. Most biomarkers are related to the immune (SAA, TNF-∝ and IP-10) or coagulation (D-dimer, antithrombin and VWF) cascades, suggesting complex vascular pathobiology of the disease. Furthermore, we observe commonality with established cancer biomarkers (ACE2, IL-6, IL-4 and IL-2) as well as biomarkers for metabolic syndrome and diabetes (CRP, NLR and LDL). We explore these trends as we put forth a COVID-19 biomarker resource (https://data.oncomx.org/covid19) that will help researchers and diagnosticians alike.

Indexed as

cancerCOVID-19COVID-19 biomarkersmetabolic syndromevascular disease

Identifiers

PMID34015823
PMCPMC8195003
OpenAlexW3160776171

What OpenQuestion holds

Textmetadata
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.