Evidence map›Paper›PMID 23916847›Full record

ArticleGastroenterology2013

Relationship between methylome and transcriptome in patients with nonalcoholic fatty liver disease.

Susan K Murphy, Hyuna Yang, Cynthia A Moylan, Herbert Pang, Andrew Dellinger, Manal F Abdelmalek, Melanie E Garrett, Allison Ashley-Koch, Ayako Suzuki, Hans L Tillmann and 2 more

Open access · bronzeAbstract readComparative Study
In one paragraph

Article in Gastroenterology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 242 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
242citing papers in PubMed, 2 pooled it
15.1field-weighted citation impact, top 1% 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

242 citing papers in PubMed, 2 syntheses or guidelines pooled it, 391 citations in OpenAlex.

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  17. Role of cellular senescence in hepatic diseases (Review).International journal of molecular medicine · 2025
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182 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 1 country.

Susan K MurphyDepartment of Obstetrics and Gynecology, Duke University, Durham, North Carolina.
Hyuna Yang
Cynthia A Moylan
Herbert Pang
Andrew Dellinger
Manal F Abdelmalek
Melanie E Garrett
Allison Ashley-Koch
Ayako Suzuki
Hans L Tillmann
Michael A Hauser
Anna Mae Diehl
Duke University · USDuke University Hospital · USCenter for Human Genetics · US

Funding

DUKE TRAINING GRANT IN DIGESTIVE DISEASES AND NUTRITIONT32DK007568 · NIDDK · DUKE UNIVERSITY · PI Katherine Garman, Rodger A. Liddle · 1988 to 2026
$5.6M
Characterizing Alcohol's Effects on Repair of Liver InjuryRC2AA019399 · NIAAA · DUKE UNIVERSITY · PI DIEHL, ANNA MAE ELIZABETH · 2009 to 2010
$2.0M
NIAAA NIH HHS 5RC2-AA019399NIAAA NIH HHS RC2 AA019399NIDDK NIH HHS T32 DK007568
6 · The paper itself

Abstract

BACKGROUND &

aimsCirrhosis and liver cancer are potential outcomes of advanced nonalcoholic fatty liver disease (NAFLD). It is not clear what factors determine whether patients will develop advanced or mild NAFLD, limiting noninvasive diagnosis and treatment before clinical sequelae emerge. We investigated whether DNA methylation profiles can distinguish patients with mild disease from those with advanced NAFLD, and how these patterns are functionally related to hepatic gene expression.

methodsWe collected frozen liver biopsies and clinical data from patients with biopsy-proven NAFLD (56 in the discovery cohort and 34 in the replication cohort). Samples were divided into groups based on histologic severity of fibrosis: F0-1 (mild) and F3-4 (advanced). DNA methylation profiles were determined and coupled with gene expression data from the same biopsies; differential methylation was validated in subsets of the discovery and replication cohorts. We then analyzed interactions between the methylome and transcriptome.

resultsClinical features did not differ between patients known to have mild or advanced fibrosis based on biopsy analysis. There were 69,247 differentially methylated CpG sites (76% hypomethylated, 24% hypermethylated) in patients with advanced vs mild NAFLD (P < .05). Methylation at fibroblast growth factor receptor 2, methionine adenosyl methyltransferase 1A, and caspase 1 was validated by bisulfite pyrosequencing and the findings were reproduced in the replication cohort. Methylation correlated with gene transcript levels for 7% of differentially methylated CpG sites, indicating that differential methylation contributes to differences in expression. In samples with advanced NAFLD, many tissue repair genes were hypomethylated and overexpressed, and genes in certain metabolic pathways, including 1-carbon metabolism, were hypermethylated and underexpressed.

conclusionsFunctionally relevant differences in methylation can distinguish patients with advanced vs mild NAFLD. Altered methylation of genes that regulate processes such as steatohepatitis, fibrosis, and carcinogenesis indicate the role of DNA methylation in progression of NAFLD.

Indexed as

Disease ProgressionSeverity of Illness IndexAdultBiopsyCaspase 1Cohort StudiesCpG IslandsDiagnosis, DifferentialDNA MethylationFatty LiverFemaleGene Expression RegulationHumansLiverMaleMethionine AdenosyltransferaseCaspase 1FGFR2 protein, humanMAT1A protein, humanMethionine AdenosyltransferaseReceptor, Fibroblast Growth Factor, Type 2adenosyl homocysteineAHCYaldehyde dehydrogenase 1 family, member L1ALDH1L1BMIbody mass indexCASP1caspase 1CGICpG islandsdifferentially methylatedDMDNA MethylationFGFR2fibroblast growth factor receptor 2gene expressionGene Expression(GEx)MAT1Amethionine adenosyl methyltransferase 1Amethylenetetrahydrofolate dehydrogenase 2MicroarraysMTHFDNAFLDNASHnonalcoholic fatty liver diseasenonalcoholic steatohepatitistranscription start siteTSSuntranslated regionUTR

Identifiers

PMID23916847
PMCPMC3805742
OpenAlexW2150020322

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.