Evidence map›Paper›PMID 31467298›Full record

ArticleScientific reports2019

Gene Expression Predicts Histological Severity and Reveals Distinct Molecular Profiles of Nonalcoholic Fatty Liver Disease.

Stephen A Hoang, Abdul Oseini, Ryan E Feaver, Banumathi K Cole, Amon Asgharpour, Robert Vincent, Mohammad Siddiqui, Mark J Lawson, Nathan C Day, Justin M Taylor and 5 more

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 120 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
120citing papers in PubMed, 4 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

120 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
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  10. Gene-Based Clustering Identifies QSOX1 and IL1RAP as Biomarkers of Metabolic Dysfunction-Associated Steatotic Liver Disease.Liver international : official journal of the International Association for the Study of the Liver · 2026
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60 more citing papers are in PubMed but not listed here.

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

15 authors.

Stephen A HoangHemoShear Therapeutics, LLC, Charlottesville, Virginia, USA. hoang@hemoshear.com.
Abdul OseiniDivision of Gastroenterology, Hepatology and Nutrition, Department of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, VA, USA.
Ryan E FeaverHemoShear Therapeutics, LLC, Charlottesville, Virginia, USA.
Banumathi K ColeHemoShear Therapeutics, LLC, Charlottesville, Virginia, USA.
Amon AsgharpourDivision of Surgical Pathology, Department of Pathology, Virginia Commonwealth University School of Medicine, Richmond, VA, USA.
Robert VincentDivision of Gastroenterology, Hepatology and Nutrition, Department of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, VA, USA.
Mohammad SiddiquiDivision of Gastroenterology, Hepatology and Nutrition, Department of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, VA, USA.ORCID http://orcid.org/0000-0001-7392-7489
Mark J LawsonHemoShear Therapeutics, LLC, Charlottesville, Virginia, USA.
Nathan C DayHemoShear Therapeutics, LLC, Charlottesville, Virginia, USA.ORCID http://orcid.org/0000-0002-6714-8611
Justin M TaylorHemoShear Therapeutics, LLC, Charlottesville, Virginia, USA.ORCID http://orcid.org/0000-0003-4590-0777
Brian R WamhoffHemoShear Therapeutics, LLC, Charlottesville, Virginia, USA.
Faridoddin MirshahiDivision of Gastroenterology, Hepatology and Nutrition, Department of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, VA, USA.
Melissa J ContosDivision of Gastroenterology, Hepatology and Nutrition, Department of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, VA, USA.
Michael IdowuDivision of Gastroenterology, Hepatology and Nutrition, Department of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, VA, USA.
Arun J SanyalDivision of Gastroenterology, Hepatology and Nutrition, Department of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, VA, USA. arun.sanyal@vcuhealth.org.

Funding

Training Grant in Digestive Diseases and Liver DiseasesT32DK007150 · NIDDK · VIRGINIA COMMONWEALTH UNIVERSITY · PI SANYAL, ARUN J · 1986 to 2017
$4.2M
LIPIDOMICS BASED DIAGNOSTICS FOR NONALCOHOLIC STEATOHEPATITISR01DK105961 · NIDDK · VIRGINIA COMMONWEALTH UNIVERSITY · PI DENNIS, EDWARD A, SANYAL, ARUN J · 2015 to 2018
$2.8M
NIDDK NIH HHS R01 DK105961NIDDK NIH HHS T32 DK007150
6 · The paper itself

Abstract

The heterogeneity of biological processes driving the severity of nonalcoholic fatty liver disease (NAFLD) as reflected in the transcriptome and the relationship between the pathways involved are not well established. Well-defined associations between gene expression profiles and disease progression would benefit efforts to develop novel therapies and to understand disease heterogeneity. We analyzed hepatic gene expression in controls and a cohort with the full histological spectrum of NAFLD. Protein-protein interaction and gene set variation analysis revealed distinct sets of coordinately regulated genes and pathways whose expression progressively change over the course of the disease. The progressive nature of these changes enabled us to develop a framework for calculating a disease progression score for individual genes. We show that, in aggregate, these scores correlate strongly with histological measures of disease progression and can thus themselves serve as a proxy for severity. Furthermore, we demonstrate that the expression levels of a small number of genes (~20) can be used to infer disease severity. Finally, we show that patient subgroups can be distinguished by the relative distribution of gene-level scores in specific gene sets. While future work is required to identify the specific disease characteristics that correspond to patient clusters identified on this basis, this work provides a general framework for the use of high-content molecular profiling to identify NAFLD patient subgroups.

Indexed as

Cohort StudiesDisease ProgressionGene Expression ProfilingHistologyHumansLiverNon-alcoholic Fatty Liver DiseaseProteinsTranscriptomeProteins

Identifiers

PMID31467298
PMCPMC6715650

What OpenQuestion holds

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LicenceCC BY
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.