Evidence map›Paper›PMID 34666007›Full record

ArticleCell systems2022

Multiomic profiling of the liver across diets and age in a diverse mouse population.

Evan G Williams, Niklas Pfister, Suheeta Roy, Cyril Statzer, Jack Haverty, Jesse Ingels, Casey Bohl, Moaraj Hasan, Jelena Čuklina, Peter Bühlmann and 5 more

Open access · greenAbstract read
In one paragraph

Article in Cell systems, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
4.2field-weighted citation impact, top 5% 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

34 citing papers in PubMed, 50 citations in OpenAlex.

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  9. The DREAM complex links somatic mutation, lifespan, and disease.bioRxiv : the preprint server for biology · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors at 4 institutions in 4 countries.

Evan G WilliamsLuxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg. Electronic address: evan.williams@uni.lu.
Niklas PfisterDepartment of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark.
Suheeta RoyDepartment of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA.
Cyril StatzerDepartment of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland.
Jack HavertyLuxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
Jesse IngelsDepartment of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA.
Casey BohlDepartment of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA.
Moaraj HasanDepartment of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zurich, Switzerland.
Jelena ČuklinaDepartment of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zurich, Switzerland.
Peter BühlmannDepartment of Mathematics, Seminar for Statistics, ETH Zürich, Zurich, Switzerland.
Nicola ZamboniDepartment of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zurich, Switzerland.
Lu LuDepartment of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA.
Collin Y EwaldDepartment of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland.
Robert W WilliamsDepartment of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA.
Ruedi AebersoldDepartment of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zurich, Switzerland; Faculty of Science, University of Zürich, Zurich, Switzerland.
ETH Zurich · CHUniversity of Tennessee Health Science Center · USUniversity of Luxembourg · LUUniversity of Copenhagen · DK

Funding

Translational Systems Genetics of Mitochondria, Metabolism, and AgingR01AG043930 · NIA · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI WILLIAMS, ROBERT W. · 2013 to 2017
$2.5M
Identifying Biomolecular Networks Driving Metabolic Trait VariationF32GM119190 · NIGMS · SWISS FEDERAL INST OF TECH (ETH ZURICH) · PI WILLIAMS, EVAN GRAEHL · 2016 to 2018
$174k
European Research Council 670821NIA NIH HHS R01 AG043930NIGMS NIH HHS F32 GM119190
6 · The paper itself

Abstract

We profiled the liver transcriptome, proteome, and metabolome in 347 individuals from 58 isogenic strains of the BXD mouse population across age (7 to 24 months) and diet (low or high fat) to link molecular variations to metabolic traits. Several hundred genes are affected by diet and/or age at the transcript and protein levels. Orthologs of two aging-associated genes, St7 and Ctsd, were knocked down in C. elegans, reducing longevity in wild-type and mutant long-lived strains. The multiomics data were analyzed as segregating gene networks according to each independent variable, providing causal insight into dietary and aging effects. Candidates were cross-examined in an independent diversity outbred mouse liver dataset segregating for similar diets, with ∼80%-90% of diet-related candidate genes found in common across datasets. Together, we have developed a large multiomics resource for multivariate analysis of complex traits and demonstrate a methodology for moving from observational associations to causal connections.

Indexed as

Caenorhabditis elegansLiverAnimalsDietGene Regulatory NetworksMiceTranscriptomeagingcausal inferencegene-by-environment interactiongenetic reference populationGxElivermultiomicsmultivariate analysisnetwork biologyproteomicstime course

Identifiers

PMID34666007
PMCPMC8776606
OpenAlexW3207108812

What OpenQuestion holds

Textmetadata
LicenceTDM
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.