Evidence map›Paper›PMID 31031010›Full record

ArticleCell2019

Disentangling Genetic and Environmental Effects on the Proteotypes of Individuals.

Natalie Romanov, Michael Kuhn, Ruedi Aebersold, Alessandro Ori, Martin Beck, Peer Bork

Open access · hybridAbstract read
In one paragraph

Article in Cell, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 2 pooled it
5.4field-weighted citation impact, top 3% 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

31 citing papers in PubMed, 2 syntheses or guidelines pooled it, 61 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

6 authors at 5 institutions in 2 countries.

Natalie RomanovStructural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
Michael KuhnStructural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
Ruedi AebersoldDepartment of Biology, Institute of Molecular Systems Biology, ETH Zurich, Switzerland; Faculty of Science, University of Zurich, Zurich, Switzerland.
Alessandro OriLeibniz Institute on Aging - Fritz Lipmann Institute, Jena, Germany.
Martin BeckStructural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany; Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany. Electronic address: martin.beck@embl.de.
Peer BorkStructural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany; Max Delbrück Center for Molecular Medicine, Berlin, Germany. Electronic address: bork@embl.de.
European Molecular Biology Laboratory · DEEuropean Molecular Biology Laboratory · DELeibniz Institute on Aging - Fritz Lipmann Institute (FLI) · DEMax Delbrück Center · DEUniversity of Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Proteotypes, like genotypes, have been found to vary between individuals in several studies, but consistent molecular functional traits across studies remain to be quantified. In a meta-analysis of 11 proteomics datasets from humans and mice, we use co-variation of proteins in known functional modules across datasets and individuals to obtain a consensus landscape of proteotype variation. We find that individuals differ considerably in both protein complex abundances and stoichiometry. We disentangle genetic and environmental factors impacting these metrics, with genetic sex and specific diets together explaining 13.5% and 11.6% of the observed variation of complex abundance and stoichiometry, respectively. Sex-specific differences, for example, include various proteins and complexes, where the respective genes are not located on sex-specific chromosomes. Diet-specific differences, added to the individual genetic backgrounds, might become a starting point for personalized proteotype modulation toward desired features.

Indexed as

Databases, ProteinGene-Environment InteractionGenotypeSex CharacteristicsA549 CellsAnimalsFemaleHEK293 CellsHeLa CellsHep G2 CellsHumansJurkat CellsK562 CellsMaleMCF-7 CellsMice

Identifiers

PMID31031010
PMCPMC6988111
OpenAlexW2941892501

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.