Evidence map›Paper›PMID 36446900›Full record

ReviewNature reviews. Neuroscience2023

The Genetically Informed Neurobiology of Addiction (GINA) model.

Ryan Bogdan, Alexander S Hatoum, Emma C Johnson, Arpana Agrawal

Open access · greenAbstract readReview
In one paragraph

Review in Nature reviews. Neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 3 pooled it
4.5field-weighted citation impact, top 4% 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

32 citing papers in PubMed, 3 syntheses or guidelines pooled it, 51 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Classification of Alcohol Use Disorder With Explainable AI.Alcohol, clinical & experimental research · 2026
    Article
  5. Article
  6. Adapter protein 2-modulatedActa pharmacologica Sinica · 2026
    Article
  7. Article
  8. Article
  9. The Brain Age Gap as a Predictor of Alcohol Initiation in Adolescence.bioRxiv : the preprint server for biology · 2026
    Article
  10. Article
  11. Review
  12. Article
  13. Youth Correlates of Genetic Liability to Substance Use Disorders.medRxiv : the preprint server for health sciences · 2025
    Article
  14. The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article
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

4 authors at 1 institution in 1 country.

Ryan BogdanDepartment of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA. rbogdan@wustl.edu.ORCID 0000-0002-1430-1045
Alexander S HatoumDepartment of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.ORCID 0000-0002-8002-7267
Emma C JohnsonDepartment of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.ORCID 0000-0003-0394-777X
Arpana AgrawalDepartment of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA. arpana@wustl.edu.ORCID 0000-0002-0313-793X
Washington University in St. Louis · US

Funding

23/24 Healthy Brain and Child Development National ConsortiumU01DA055367 · NIDA · WASHINGTON UNIVERSITY · PI RYAN H BOGDAN, CYNTHIA Elise ROGERS · 2021 to 2026
$10.8M
BIOMEDICAL RESEARCH TRAINING IN DRUG ABUSET32DA007261 · NIDA · WASHINGTON UNIVERSITY · PI ARPANA AGRAWAL, Jose A Moron-Concepcion · 1991 to 2026
$8.8M
7/7 Psychiatric Genomics Consortium: Advancing Discovery and ImpactR01DA054869 · NIDA · WASHINGTON UNIVERSITY · PI AGRAWAL, ARPANA, EDENBERG, HOWARD J · 2021 to 2025
$3.3M
Neurobehavioral pathways of polygenic and polyenvironmental effects on the onset and maintenance of substance involvementR01DA054750 · NIDA · WASHINGTON UNIVERSITY · PI AGRAWAL, ARPANA, BOGDAN, RYAN H · 2021 to 2025
$2.0M
DELINEATING THE ROLE OF GENETIC INFLUENCES ON CANNABIS INVOLVEMENTK02DA032573 · NIDA · WASHINGTON UNIVERSITY · PI AGRAWAL, ARPANA · 2012 to 2021
$1.1M
Mass Multivariate Derivation and Validation of AUD Biotypes using Developmental Imaging and Genomic ApproachesK01AA030083 · NIAAA · WASHINGTON UNIVERSITY · PI Alexander S Hatoum · 2022 to 2026
$897k
Identifying genetic sources of comorbidity between cannabis and schizophrenia using genome-wide and integrative omics dataK01DA051759 · NIDA · WASHINGTON UNIVERSITY · PI JOHNSON, EMMA COVEY · 2021 to 2025
$816k
Modeling poly-genomic risk in the relationship between brain structure and alcohol involvement from adolescence through adulthoodR21AA027827 · NIAAA · WASHINGTON UNIVERSITY · PI BOGDAN, RYAN H · 2019 to 2020
$413k
NIAAA NIH HHS K01 AA030083NIAAA NIH HHS R21 AA027827NIDA NIH HHS K01 DA051759NIDA NIH HHS K02 DA032573NIDA NIH HHS R01 DA054750NIDA NIH HHS R01 DA054869NIDA NIH HHS T32 DA007261NIDA NIH HHS U01 DA055367
6 · The paper itself

Abstract

Addictions are heritable and unfold dynamically across the lifespan. One prominent neurobiological theory proposes that substance-induced changes in neural circuitry promote the progression of addiction. Genome-wide association studies have begun to characterize the polygenic architecture undergirding addiction liability and revealed that genetic loci associated with risk can be divided into those associated with a general broad-spectrum liability to addiction and those associated with drug-specific addiction risk. In this Perspective, we integrate these genomic findings with our current understanding of the neurobiology of addiction to propose a new Genetically Informed Neurobiology of Addiction (GINA) model.

Indexed as

Behavior, AddictiveSubstance-Related DisordersGenome-Wide Association StudyHumansNeurobiology

Identifiers

PMID36446900
PMCPMC10041646
OpenAlexW4310217092

What Socratic 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 Socratic graph.