Evidence map›Paper›PMID 29404805›Full record

ReviewJournal of inherited metabolic disease2018

Inborn errors of metabolism and the human interactome: a systems medicine approach.

Mathias Woidy, Ania C Muntau, Søren W Gersting

Abstract readReview
In one paragraph

Review in Journal of inherited metabolic disease, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Network Analysis Reveals Proteins Associated with Aortic Dilatation in Mucopolysaccharidoses.Interdisciplinary sciences, computational life sciences · 2021
    Article
  8. IRS-2/Akt/GSK-3Oxidative medicine and cellular longevity · 2021
    Article
  9. 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

3 authors.

Mathias WoidyUniversity Children's Hospital, University Medical Center Hamburg Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany.
Ania C MuntauUniversity Children's Hospital, University Medical Center Hamburg Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany.
Søren W GerstingDepartment of Molecular Pediatrics, Dr. von Hauner Children's Hospital, Ludwig-Maximilians-University Munich, Lindwurmstrasse 4, 80336, Munich, Germany. soeren.gersting@med.lmu.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The group of inborn errors of metabolism (IEM) displays a marked heterogeneity and IEM can affect virtually all functions and organs of the human organism; however, IEM share that their associated proteins function in metabolism. Most proteins carry out cellular functions by interacting with other proteins, and thus are organized in biological networks. Therefore, diseases are rarely the consequence of single gene mutations but of the perturbations caused in the related cellular network. Systematic approaches that integrate multi-omics and database information into biological networks have successfully expanded our knowledge of complex disorders but network-based strategies have been rarely applied to study IEM. We analyzed IEM on a proteome scale and found that IEM-associated proteins are organized as a network of linked modules within the human interactome of protein interactions, the IEM interactome. Certain IEM disease groups formed self-contained disease modules, which were highly interlinked. On the other hand, we observed disease modules consisting of proteins from many different disease groups in the IEM interactome. Moreover, we explored the overlap between IEM and non-IEM disease genes and applied network medicine approaches to investigate shared biological pathways, clinical signs and symptoms, and links to drug targets. The provided resources may help to elucidate the molecular mechanisms underlying new IEM, to uncover the significance of disease-associated mutations, to identify new biomarkers, and to develop novel therapeutic strategies.

Indexed as

Systems AnalysisGene Regulatory NetworksGenomicsHumansInfant, NewbornMetabolism, Inborn ErrorsMetabolomicsProtein Interaction MapsDisease moduleInborn errors of metabolismInteractomeNetwork medicineProtein-protein interaction

Identifiers

PMID29404805
PMCPMC5959957

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Registered trials

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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.