ReviewPharmacology & therapeutics2013
Implications of genome wide association studies for addiction: are our a priori assumptions all wrong?
Review in Pharmacology & therapeutics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled 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.
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
34 citing papers in PubMed, 1 synthesis or guideline pooled it, 76 citations in OpenAlex.
- Association of the OPRM1 Variant rs1799971 (A118G) with Non-Specific Liability to Substance Dependence in a Collaborative de novo Meta-Analysis of European-Ancestry Cohorts.Behavior genetics · 2016Pooled it
- Bidirectional genetic and phenotypic links between smoking and striatal iron content involving dopaminergic and inflammatory pathways.Addiction (Abingdon, England) · 2026Article
- Establishing Best Practices for Clinical GWAS: Tackling Imputation and Data Quality Challenges.International journal of molecular sciences · 2025Review
- Effects of positive mGlu5 modulation on DJournal of psychopharmacology (Oxford, England) · 2025Article
- The association of genetic polymorphisms within the dopaminergic system with nicotine dependence: A narrative review.Heliyon · 2024Review
- Neuroepigenetic Editing.Methods in molecular biology (Clifton, N.J.) · 2024Review
- Is There a Natural, Non-addictive, and Non-anti-reward, Safe, Gene-based Solution to Treat Reward Deficiency Syndrome? KB220 Variants vs GLP-1 Analogs.Journal of addiction psychiatry · 2024Article
- Molecular genetics of cocaine use disorders in humans.Molecular psychiatry · 2022Review
- FACTORS CONTRIBUTING TO THE ESCALATION OF ALCOHOL CONSUMPTION.Neuroscience and biobehavioral reviews · 2022Review
- Genetic basis of variation in cocaine and methamphetamine consumption in outbred populations ofProceedings of the National Academy of Sciences of the United States of America · 2021Article
- Identification of the Risk Genes Associated With Vulnerability to Addiction: Major Findings From Transgenic Animals.Frontiers in neuroscience · 2021Review
- Endocannabinoid Gene × Gene Interaction Association to Alcohol Use Disorder in Two Adolescent Cohorts.Frontiers in psychiatry · 2021Article
- Implementation and Evaluation of a Text Message-Based Addiction Counseling Program (Text4Hope-Addiction Support): Protocol for a Questionnaire Study.JMIR research protocols · 2020Article
- Endogenous Opioids at the Intersection of Opioid Addiction, Pain, and Depression: The Search for a Precision Medicine Approach.Annual review of neuroscience · 2020Review
- Prospects for finding the mechanisms of sex differences in addiction with human and model organism genetic analysis.Genes, brain, and behavior · 2020Review
- Genetics of cocaine and methamphetamine consumption and preference in Drosophila melanogaster.PLoS genetics · 2019Article
- Insurance Companies Fighting the Peer Review Empire without any Validity: the Case for Addiction and Pain Modalities in the face of an American Drug Epidemic.SEJ surgery and pain · 2018Article
- MiR-9, miR-153 and miR-124 are down-regulated by acute exposure to cocaine in a dopaminergic cell model and may contribute to cocaine dependence.Translational psychiatry · 2018Article
- The Role of Cell Adhesion Molecule Genes Regulating Neuroplasticity in Addiction.Neural plasticity · 2018Review
- Neuroepigenetic Editing.Methods in molecular biology (Clifton, N.J.) · 2018Review
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Substantial genetic contributions to addiction vulnerability are supported by data from twin studies, linkage studies, candidate gene association studies and, more recently, Genome Wide Association Studies (GWAS). Parallel to this work, animal studies have attempted to identify the genes that may contribute to responses to addictive drugs and addiction liability, initially focusing upon genes for the targets of the major drugs of abuse. These studies identified genes/proteins that affect responses to drugs of abuse; however, this does not necessarily mean that variation in these genes contributes to the genetic component of addiction liability. One of the major problems with initial linkage and candidate gene studies was an a priori focus on the genes thought to be involved in addiction based upon the known contributions of those proteins to drug actions, making the identification of novel genes unlikely. The GWAS approach is systematic and agnostic to such a priori assumptions. From the numerous GWAS now completed several conclusions may be drawn: (1) addiction is highly polygenic; each allelic variant contributing in a small, additive fashion to addiction vulnerability; (2) unexpected, compared to our a priori assumptions, classes of genes are most important in explaining addiction vulnerability; (3) although substantial genetic heterogeneity exists, there is substantial convergence of GWAS signals on particular genes. This review traces the history of this research; from initial transgenic mouse models based upon candidate gene and linkage studies, through the progression of GWAS for addiction and nicotine cessation, to the current human and transgenic mouse studies post-GWAS.
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Registered trials
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.