ReviewFrontiers in neuroscience2015
An animal model of differential genetic risk for methamphetamine intake.
Review in Frontiers in neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.
- Association Between Brain-Derived Neurotrophic Factor Val66Met Polymorphism and Methamphetamine Use Disorder: A Meta-Analysis.Frontiers in psychiatry · 2020Pooled it
- NQO1 and NQO2 Gene Polymorphisms Related to Methamphetamine-Associated Psychosis in the Makassar Population, Indonesia.Noro psikiyatri arsivi · 2026Article
- Absence of TAAR1 function increases methamphetamine-induced excitability of dorsal raphe serotonin neurons and drives binge-level methamphetamine intake.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2025Article
- Robust aversive effects of trace amine-associated receptor 1 activation in mice.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2023Article
- Midazolam, methamphetamine, morphine and nicotine intake in high-drinking-in-the-dark mice.Addiction biology · 2022Article
- Dopamine dysfunction in stimulant use disorders: mechanistic comparisons and implications for treatment.Molecular psychiatry · 2022Review
- A breeding strategy to identify modifiers of high genetic risk for methamphetamine intake.Genes, brain, and behavior · 2021Article
- The motivational valence of methamphetamine relates inversely to subsequent methamphetamine self-administration in female C57BL/6J mice.Behavioural brain research · 2021Article
- Confirmation of a CausalFrontiers in psychiatry · 2021Article
- Differential genetic risk for methamphetamine intake confers differential sensitivity to the temperature-altering effects of other addictive drugs.Genes, brain, and behavior · 2020Article
- Depression-like symptoms of withdrawal in a genetic mouse model of binge methamphetamine intake.Genes, brain, and behavior · 2019Article
- Verification of a genetic locus for methamphetamine intake and the impact of morphine.Mammalian genome : official journal of the International Mammalian Genome Society · 2018Article
- Methamphetamine Addiction Vulnerability: The Glutamate, the Bad, and the Ugly.Biological psychiatry · 2017Article
- Parallel Effects of Methamphetamine on Anxiety and CCL3 in Humans and a Genetic Mouse Model of High Methamphetamine Intake.Neuropsychobiology · 2017Article
- A Spontaneous Mutation inFrontiers in pharmacology · 2017Article
- A Mouse Model for Binge-Level Methamphetamine Use.Frontiers in neuroscience · 2016Article
- Methamphetamine Consumption Inhibits Pair Bonding and Hypothalamic Oxytocin in Prairie Voles.PloS one · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
The question of whether genetic factors contribute to risk for methamphetamine (MA) use and dependence has not been intensively investigated. Compared to human populations, genetic animal models offer the advantages of control over genetic family history and drug exposure. Using selective breeding, we created lines of mice that differ in genetic risk for voluntary MA intake and identified the chromosomal addresses of contributory genes. A quantitative trait locus was identified on chromosome 10 that accounts for more than 50% of the genetic variance in MA intake in the selected mouse lines. In addition, behavioral and physiological screening identified differences corresponding with risk for MA intake that have generated hypotheses that are testable in humans. Heightened sensitivity to aversive and certain physiological effects of MA, such as MA-induced reduction in body temperature, are hallmarks of mice bred for low MA intake. Furthermore, unlike MA-avoiding mice, MA-preferring mice are sensitive to rewarding and reinforcing MA effects, and to MA-induced increases in brain extracellular dopamine levels. Gene expression analyses implicate the importance of a network enriched in transcription factor genes, some of which regulate the mu opioid receptor gene, Oprm1, in risk for MA use. Neuroimmune factors appear to play a role in differential response to MA between the mice bred for high and low intake. In addition, chromosome 10 candidate gene studies provide strong support for a trace amine-associated receptor 1 gene, Taar1, polymorphism in risk for MA intake. MA is a trace amine-associated receptor 1 (TAAR1) agonist, and a non-functional Taar1 allele segregates with high MA consumption. Thus, reduced TAAR1 function has the potential to increase risk for MA use. Overall, existing findings support the MA drinking lines as a powerful model for identifying genetic factors involved in determining risk for harmful MA use. Future directions include the development of a binge model of MA intake, examining the effect of withdrawal from chronic MA on MA intake, and studying potential Taar1 gene × gene and gene × environment interactions. These and other studies are intended to improve our genetic model with regard to its translational value to human addiction.
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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.