Evidence map›Paper›PMID 29049138›Full record

ArticleShock (Augusta, Ga.)2018

Graph Theoretical Analysis of Genome-Scale Data: Examination of Gene Activation Occurring in the Setting of Community-Acquired Pneumonia.

Octavia M Peck Palmer, Gary Rogers, Sachin Yende, Derek C Angus, Gilles Clermont, Michael A Langston

Open access · greenAbstract read
In one paragraph

Article in Shock (Augusta, Ga.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 36% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
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

6 authors at 2 institutions in 1 country.

Octavia M Peck PalmerDepartment of Pathology, University of Pittsburgh, Pittsburgh, Pennsylvania.
Gary RogersDepartment of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, Tennessee.
Sachin YendeDepartment of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
Derek C AngusDepartment of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
Gilles ClermontDepartment of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
Michael A LangstonDepartment of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, Tennessee.
University of Pittsburgh · USUniversity of Tennessee at Knoxville · US

Funding

Data Structures, Algorithms and Tools for Ontological DiscoveryR01AA018776 · NIAAA · JACKSON LABORATORY · PI CHESLER, ELISSA J · 2010 to 2019
$3.9M
Modeling the acute inflammatory responseR01GM067240 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CLERMONT, GILLES · 2002 to 2005
$1.3M
Model-Based Decisions in SepsisR01GM105728 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CLERMONT, GILLES · 2014 to 2017
$1.1M
NIAAA NIH HHS R01 AA018776NIGMS NIH HHS R01 GM067240NIGMS NIH HHS R01 GM105728
6 · The paper itself

Abstract

introductionWe have previously reported evidence that Black individuals appear to have a significantly higher incidence of infection-related hospitalizations compared with White individuals. It is possible that the host immune response is responsible for this vital difference. In support of such a hypothesis, the aim of this study was to determine whether Black and White individuals exhibit differential whole blood gene network activation.

methodsWe examined whole blood network activation in a subset of patients (n = 22 pairs, propensity score matched (1:1) Black and White patients) with community-acquired pneumonia (CAP) from the Genetic and Inflammatory Markers of Sepsis study. We employed day one whole blood transcriptomic data generated from this cohort and constructed co-expression graphs for each racial group. Pearson correlation coefficients were used to weight edges. Spectral thresholding was applied to ascribe significance. Innovative graph theoretical methods were then invoked to detect densely connected gene networks and provide differential structural analysis.

resultsPropensity matching was employed to reduce potential bias due to confounding variables. Although Black and White patients had similar socio- and clinical demographics, we identified novel differences in molecular network activation-dense subgraphs known as paracliques that displayed complete gene connection for both White (three paracliques) and Black patients (one paraclique). Specifically, the genes that comprised the paracliques in the White patients include circadian loop, cell adhesion, mobility, proliferation, tumor suppression, NFκB, and chemokine signaling. However, the genes that comprised the paracliques in the Black patients include DNA and messenger RNA processes, and apoptosis signaling. We investigated the distribution of Black paracliques across White paracliques. Black patients had five paracliques (with almost complete connection) comprised of genes that are critical for host immune response widely distributed across 22 parcliques in the White population. Anchoring the analysis on two critical inflammatory mediators, interleukin (IL)-6 and IL-10 identified further differential network activation among the White and Black patient populations.

conclusionsThese results demonstrate that, at the molecular level, Black and White individuals may experience different activation patterns with CAP. Further validation of the gene networks we have identified may help pinpoint genetic factors that increase host susceptibility to community-acquired pneumonia, and may lay the groundwork for personalized management of CAP.

Indexed as

Black or African AmericanCommunity-Acquired InfectionsHumansInflammationPneumoniaRNA, MessengerSepsisTranscriptional ActivationWhite PeopleRNA, Messenger

Identifiers

PMID29049138
PMCPMC6074040
OpenAlexW2766352033

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.