Evidence map›Paper›PMID 35323654›Full record

ArticleMetabolites2022

High-Throughput UHPLC-MS to Screen Metabolites in Feces for Gut Metabolic Health.

Andressa de Zawadzki, Maja Thiele, Tommi Suvitaival, Asger Wretlind, Min Kim, Mina Ali, Annette F Bjerre, Karin Stahr, Ismo Mattila, Torben Hansen and 2 more

Abstract read
In one paragraph

Article in Metabolites, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. Trial
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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

12 authors.

Andressa de ZawadzkiSteno Diabetes Center Copenhagen, 2730 Herlev, Denmark.ORCID 0000-0002-7442-3474
Maja ThieleDepartment of Gastroenterology and Hepatology, Odense University Hospital, 5000 Odense, Denmark.ORCID 0000-0003-1854-1924
Tommi SuvitaivalSteno Diabetes Center Copenhagen, 2730 Herlev, Denmark.
Asger WretlindSteno Diabetes Center Copenhagen, 2730 Herlev, Denmark.
Min KimSteno Diabetes Center Copenhagen, 2730 Herlev, Denmark.
Mina AliSteno Diabetes Center Copenhagen, 2730 Herlev, Denmark.
Annette F BjerreSteno Diabetes Center Copenhagen, 2730 Herlev, Denmark.
Karin StahrSteno Diabetes Center Copenhagen, 2730 Herlev, Denmark.
Ismo MattilaSteno Diabetes Center Copenhagen, 2730 Herlev, Denmark.ORCID 0000-0001-9597-7831
Torben HansenNovo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, 1165 Copenhagen, Denmark.
Aleksander KragDepartment of Gastroenterology and Hepatology, Odense University Hospital, 5000 Odense, Denmark.ORCID 0000-0002-9598-4932
Cristina Legido-QuigleySteno Diabetes Center Copenhagen, 2730 Herlev, Denmark.

Funding

European Union's Horizon 2020 research and innovation programme 668031Novo Nordisk Foundation NNF15OC0016692
6 · The paper itself

Abstract

Feces are the product of our diets and have been linked to diseases of the gut, including Chron's disease and metabolic diseases such as diabetes. For screening metabolites in heterogeneous samples such as feces, it is necessary to use fast and reproducible analytical methods that maximize metabolite detection. As sample preparation is crucial to obtain high quality data in MS-based clinical metabolomics, we developed a novel, efficient and robust method for preparing fecal samples for analysis with a focus in reducing aliquoting and detecting both polar and non-polar metabolites. Fecal samples (n = 475) from patients with alcohol-related liver disease and healthy controls were prepared according to the proposed method and analyzed in an UHPLC-QQQ targeted platform in order to obtain a quantitative profile of compounds that impact liver-gut axis metabolism. MS analyses of the prepared fecal samples have shown reproducibility and coverage of n = 28 metabolites, mostly comprising bile acids and amino acids. We report metabolite-wise relative standard deviation (RSD) in quality control samples, inter-day repeatability, LOD (limit of detection), LOQ (limit of quantification), range of linearity and method recovery. The average concentrations for 135 healthy participants are reported here for clinical applications. Our high-throughput method provides a novel tool for investigating gut-liver axis metabolism in liver-related diseases using a noninvasive collected sample.

Indexed as

bile acidsfecal metabolomicsgut-liver axissample preparationtargeted metabolomics

Identifiers

PMID35323654
PMCPMC8950041

What Socratic 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 Socratic graph.