Evidence map›Paper›PMID 38164795›Full record

ArticleGenes, brain, and behavior2024

Discovery and validation of genes driving drug-intake and related behavioral traits in mice.

Tyler A Roy, Jason A Bubier, Price E Dickson, Troy D Wilcox, Juliet Ndukum, James W Clark, Stacey J Sukoff Rizzo, John C Crabbe, James M Denegre, Karen L Svenson and 6 more

Open access · hybridAbstract read
In one paragraph

Article in Genes, brain, and behavior, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 40% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 4 institutions in 1 country.

Tyler A RoyCenter for Addiction Biology, The Jackson Laboratory, Bar Harbor, Maine, USA.
Jason A BubierCenter for Addiction Biology, The Jackson Laboratory, Bar Harbor, Maine, USA.ORCID https://orcid.org/0000-0001-5013-1234
Price E DicksonJoan C Edwards School of Medicine, Marshall University, Huntington, West Virginia, USA.
Troy D WilcoxCenter for Addiction Biology, The Jackson Laboratory, Bar Harbor, Maine, USA.
Juliet NdukumCenter for Addiction Biology, The Jackson Laboratory, Bar Harbor, Maine, USA.
James W ClarkCenter for Addiction Biology, The Jackson Laboratory, Bar Harbor, Maine, USA.
Stacey J Sukoff RizzoCenter for Addiction Biology, The Jackson Laboratory, Bar Harbor, Maine, USA.
John C CrabbeVA Portland Health Care System, Oregon Health & Science University, Portland, Oregon, USA.
James M DenegreCenter for Addiction Biology, The Jackson Laboratory, Bar Harbor, Maine, USA.
Karen L SvensonCenter for Addiction Biology, The Jackson Laboratory, Bar Harbor, Maine, USA.
Robert E BraunCenter for Addiction Biology, The Jackson Laboratory, Bar Harbor, Maine, USA.
Vivek KumarCenter for Addiction Biology, The Jackson Laboratory, Bar Harbor, Maine, USA.ORCID https://orcid.org/0000-0001-6643-7465
Stephen A MurrayCenter for Addiction Biology, The Jackson Laboratory, Bar Harbor, Maine, USA.
Jacqueline K WhiteCenter for Addiction Biology, The Jackson Laboratory, Bar Harbor, Maine, USA.
Vivek M PhilipCenter for Addiction Biology, The Jackson Laboratory, Bar Harbor, Maine, USA.
Elissa J CheslerCenter for Addiction Biology, The Jackson Laboratory, Bar Harbor, Maine, USA.
Jackson Laboratory · USMarshall University · USOregon Health & Science University · USUniversity of Pittsburgh · US

Funding

Shared Resource ManagementP30CA034196 · NCI · JACKSON LABORATORY · PI Anna Karolina Palucka · 1985 to 2026
$61.9M
The Jackson Laboratory Knockout Mouse Production and Phenotyping Project (JAX KOMP2)UM1OD023222 · OD · JACKSON LABORATORY · PI ROBERT E BRAUN, Stephen A Murray · 2016 to 2026
$47.2M
Project 5: Circadian RhythmsP50DA039841 · NIDA · JACKSON LABORATORY · PI LAURA G REINHOLDT · 2016 to 2026
$26.2M
Genetic Control of Addiction by Host and MicrobiomeU01DA043809 · NIDA · JACKSON LABORATORY · PI BUBIER, JASON A, ZHOU, YANJIAO · 2018 to 2022
$4.0M
Genetic Variation in Opioid Induced Respiratory Depression in MiceR01DA048890 · NIDA · JACKSON LABORATORY · PI BUBIER, JASON A · 2020 to 2024
$3.4M
Discovery and Characterization of Genetic Mechanisms Driving Stress-induced Addiction VulnerabilityK99DA043573 · NIDA · JACKSON LABORATORY · PI DICKSON, PRICE EVANS · 2018 to 2019
$289k
NCI NIH HHS P30 CA034196NIDA NIH HHS K99 DA043573NIDA NIH HHS P50 DA039841NIDA NIH HHS R01 DA048890NIDA NIH HHS U01 DA043809NIH HHS DA039841NIH HHS K99 DA043573NIH HHS P30 CA034196NIH HHS R01 DA048890NIH HHS U01 DA043809NIH HHS UM1 OD023222NIH HHS UM OD 023222
6 · The paper itself

Abstract

Substance use disorders are heritable disorders characterized by compulsive drug use, the biological mechanisms for which remain largely unknown. Genetic correlations reveal that predisposing drug-naïve phenotypes, including anxiety, depression, novelty preference and sensation seeking, are predictive of drug-use phenotypes, thereby implicating shared genetic mechanisms. High-throughput behavioral screening in knockout (KO) mice allows efficient discovery of the function of genes. We used this strategy in two rounds of candidate prioritization in which we identified 33 drug-use candidate genes based upon predisposing drug-naïve phenotypes and ultimately validated the perturbation of 22 genes as causal drivers of substance intake. We selected 19/221 KO strains (8.5%) that had a difference from control on at least one drug-naïve predictive behavioral phenotype and determined that 15/19 (~80%) affected the consumption or preference for alcohol, methamphetamine or both. No mutant exhibited a difference in nicotine consumption or preference which was possibly confounded with saccharin. In the second round of prioritization, we employed a multivariate approach to identify outliers and performed validation using methamphetamine two-bottle choice and ethanol drinking-in-the-dark protocols. We identified 15/401 KO strains (3.7%, which included one gene from the first cohort) that differed most from controls for the predisposing phenotypes. 8 of 15 gene deletions (53%) affected intake or preference for alcohol, methamphetamine or both. Using multivariate and bioinformatic analyses, we observed multiple relations between predisposing behaviors and drug intake, revealing many distinct biobehavioral processes underlying these relationships. The set of mouse models identified in this study can be used to characterize these addiction-related processes further.

Indexed as

addictionaddiction predicativealcoholgenetic screenknock-outKOMPmethamphetaminemouse mutantsneurogeneticsnicotinephenotyping

Identifiers

PMID38164795
PMCPMC10780947
OpenAlexW4390508013

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.