Evidence map›Paper›PMID 36295894›Full record

ArticleMetabolites2022

Cluster Analysis Statistical Spectroscopy for the Identification of Metabolites in

Silke S Heinzmann, Melanie Waldenberger, Annette Peters, Philippe Schmitt-Kopplin

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Evolution ofGut microbes · 2023
    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

4 authors.

Silke S HeinzmannResearch Unit Analytical BioGeoChemistry, Helmholtz Munich, 85764 Neuherberg, Germany.ORCID 0000-0003-0257-8837
Melanie WaldenbergerResearch Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Munich, 85764 Neuherberg, Germany.ORCID 0000-0003-0583-5093
Annette PetersGerman Center for Diabetes Research (DZD), 85764 Neuherberg, Germany.ORCID 0000-0001-6645-0985
Philippe Schmitt-KopplinResearch Unit Analytical BioGeoChemistry, Helmholtz Munich, 85764 Neuherberg, Germany.ORCID 0000-0003-0824-2664

Funding

Deutsche Forschungsgemeinschaft FOR5042European Union no. 603288
6 · The paper itself

Abstract

Metabolite identification in non-targeted NMR-based metabolomics remains a challenge. While many peaks of frequently occurring metabolites are assigned, there is a high number of unknowns in high-resolution NMR spectra, hampering biological conclusions for biomarker analysis. Here, we use a cluster analysis approach to guide peak assignment via statistical correlations, which gives important information on possible structural and/or biological correlations from the NMR spectrum. Unknown peaks that cluster in close proximity to known peaks form hypotheses for their metabolite identities, thus, facilitating metabolite annotation. Subsequently, metabolite identification based on a database search, 2D NMR analysis and standard spiking is performed, whereas without a hypothesis, a full structural elucidation approach would be required. The approach allows a higher identification yield in NMR spectra, especially once pathway-related subclusters are identified.

Indexed as

metabolite identificationmetabolomicsNMR spectroscopyurine

Identifiers

PMID36295894
PMCPMC9607017

What OpenQuestion holds

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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.