Evidence map›Paper›PMID 32344559›Full record

ArticleMetabolites2020

Distinguishing NASH Histological Severity Using a Multiplatform Metabolomics Approach.

George N Ioannou, G A Nagana Gowda, Danijel Djukovic, Daniel Raftery

Open access · goldAbstract read
In one paragraph

Article in Metabolites, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
3.8field-weighted citation impact, top 6% 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

26 citing papers in PubMed, 37 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

George N IoannouDivision of Gastroenterology, Veterans Affairs Puget Sound Healthcare System and University of Washington, Seattle, WA 98108, USA.
G A Nagana GowdaNorthwest Metabolomics Research Center, Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98109, USA.ORCID 0000-0002-0544-7464
Danijel DjukovicNorthwest Metabolomics Research Center, Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98109, USA.
Daniel RafteryNorthwest Metabolomics Research Center, Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98109, USA.ORCID 0000-0003-2467-8118
University of Washington · US

Funding

Translational Bioimaging Core Shared ResourceP30CA015704 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Marian Esvelt · 1985 to 2026
$296.4M
Vector and Transgenic Mouse CoreP30DK017047 · NIDDK · UNIVERSITY OF WASHINGTON · PI Sakeneh Zraika · 1986 to 2026
$41.4M
PILOT STUDY--CLINICAL NUTRITION RESEARCHP30DK035816 · NIDDK · UNIVERSITY OF WASHINGTON · PI Ellen A Schur · 1986 to 2026
$30.4M
Cholesterol lights the fire of NASHI01BX002910 · VA · VA PUGET SOUND HEALTHCARE SYSTEM · PI IOANNOU, GEORGE · 2017 to 2021
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BLRD VA I01 BX002910NCI NIH HHS P30 CA015704NIDDK NIH HHS P30 DK035816NIH HHS P30CA015704NIH HHS P30DK017047NIH HHS P30DK035816University of Washington Startup Funding MMCDRR
6 · The paper itself

Abstract

Nonalcoholic fatty liver disease (NAFLD) is categorized based on histological severity into nonalcoholic fatty liver (NAFL) or nonalcoholic steatohepatitis (NASH). We used a multiplatform metabolomics approach to identify metabolite markers and metabolic pathways that distinguish NAFL from early NASH and advanced NASH. We analyzed fasting serum samples from 57 prospectively-recruited patients with histologically-proven NAFLD, including 12 with NAFL, 31 with early NASH and 14 with advanced NASH. Metabolite profiling was performed using a combination of liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) spectroscopy analyzed with multivariate statistical and pathway analysis tools. We targeted 237 metabolites of which 158 were quantified. Multivariate analysis uncovered metabolite profile clusters for patients with NAFL, early NASH, and advanced NASH. Also, multiple individual metabolites were associated with histological severity, most notably spermidine which was more than 2-fold lower in advanced fibrosis vs. early fibrosis, in advanced NASH vs. NAFL and in advanced NASH vs. early NASH, suggesting that spermidine exercises a protective effect against development of fibrosing NASH. Furthermore, the results also showed metabolic pathway perturbations between early-NASH and advanced-NASH. In conclusion, using a combination of two reliable analytical platforms (LC-MS and NMR spectroscopy) we identified individual metabolites, metabolite clusters and metabolic pathways that were significantly different between NAFL, early-NASH, and advanced-NASH. These differences provide mechanistic insights as well as potentially important metabolic biomarker candidates that may noninvasively distinguish patients with NAFL, early-NASH, and advanced-NASH. The associations of spermidine levels with less advanced histology merit further assessment of the potential protective effects of spermidine in NAFLD.

Indexed as

liquid chromatography-mass spectrometrymetabolic pathwaynonalcoholic fatty livernonalcoholic steatohepatitisnuclear magnetic resonance spectroscopy

Identifiers

PMID32344559
PMCPMC7240949
OpenAlexW3020200374

What OpenQuestion holds

Textmetadata
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.