Evidence map›Paper›PMID 41057643›Full record

SynthesisMolecular psychiatry2026

Genome-wide meta-analyses of cross substance use disorders in diverse populations.

Dongbing Lai, Michael Zhang, Nick Green, Marco Abreu, Tae-Hwi Schwantes-An, Clarissa C Parker, Shanshan Zhang, Fulai Jin, Anna Sun, Pengyue Zhang and 3 more

Abstract readMeta-Analysis
In one paragraph

Synthesis in Molecular psychiatry, 2026. 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
–field-weighted citation impact
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.

  1. Article
  2. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Dongbing LaiDepartment of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA. dlai@iu.edu.ORCID http://orcid.org/0000-0001-7803-580X
Michael ZhangDepartment of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
Nick GreenDepartment of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.ORCID http://orcid.org/0000-0002-1457-879X
Marco AbreuDepartment of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
Tae-Hwi Schwantes-AnDepartment of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.ORCID http://orcid.org/0000-0001-6387-0095
Clarissa C ParkerDepartment of Psychology and Program in Neuroscience, Middlebury College, Middlebury, VT, 05753, USA.
Shanshan ZhangDepartment of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA.
Fulai JinDepartment of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH, 44106, USA.ORCID http://orcid.org/0000-0003-0025-4337
Anna SunDepartment of Biostatistics and Heath Data Science, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
Pengyue ZhangDepartment of Biostatistics and Heath Data Science, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
Howard J EdenbergDepartment of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.ORCID http://orcid.org/0000-0003-0344-9690
Yunlong LiuDepartment of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.ORCID http://orcid.org/0000-0002-2699-626X
Tatiana ForoudDepartment of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.ORCID http://orcid.org/0000-0002-5549-2212

Funding

Robust mapping of chromatin loops from sparse or single cell Hi-C data with DeepLoopR01HG009658 · NHGRI · CASE WESTERN RESERVE UNIVERSITY · PI Fulai Jin · 2017 to 2026
$5.1M
STAG2 mutations and 3D genome organization in glioblastoma multiformeR01CA267872 · NCI · GEORGETOWN UNIVERSITY · PI Fulai Jin, TODD A WALDMAN · 2022 to 2026
$2.7M
Mapping heritable chromatin loop variants with allele-specific Hi-C analysisR01HG012384 · NHGRI · CASE WESTERN RESERVE UNIVERSITY · PI Alan D Attie, Fulai Jin · 2023 to 2026
$2.6M
Translational genetic analysis in human and mouse GWAS to identify the genomic architecture of alcohol sensitivity and toleranceR01AA031176 · NIAAA · INDIANA UNIVERSITY INDIANAPOLIS · PI Dongbing Lai, Yunlong Liu · 2024 to 2026
$1.6M
NCI NIH HHS R01 CA267872NHGRI NIH HHS R01 HG009658NHGRI NIH HHS R01 HG012384NIAAA NIH HHS R01 AA031176U.S. Department of Health & Human Services | National Institutes of Health (NIH) AA031176U.S. Department of Health & Human Services | NIH | National Institute on Drug Abuse (NIDA) DA054869
6 · The paper itself

Abstract

Substance use disorders (SUDs, including alcohol, cannabis, opioids, and tobacco) represent significant public health challenges. The estimated heritability of SUDs is ~50% and many individuals experience multiple SUDs concurrently. Studies have demonstrated the existence of genes shared across multiple SUDs, and identifying these SUD-shared genes is critical to developing novel prevention and treatment strategies. Here, we conducted the largest cross SUD meta-analysis to date to identify SUD-shared genes using samples genetically similar to 1000 Genomes Project European (1kg-EUR-like), African (1kg-AFR-like), and American mixed (1kg-AMR-like) populations. We defined variants that had the same direction of effects across different SUDs (i.e., concordant variants) as SUD-shared. In total, we identified 220 loci, including 40 novel loci that were not reported as SUD-associated in previous genome-wide association studies. Through gene-based analyses, gene mapping, and gene prioritization, we identified 785 SUD-shared genes. These genes are highly expressed in the amygdala, cortex, hippocampus, hypothalamus, and thalamus; and are primarily highly expressed in neuronal cells, suggesting that more brain regions may be involved in SUDs than previously reported. Concordant variants explained 56-96% of the SNP-heritability of each SUD in the 1kg-EUR-like sample. Furthermore, the top 10% of individuals in the 1kg-EUR-like and 1kg-AMR-like samples with the highest polygenic scores had odds ratios ranging from 1.95-2.87 to develop SUDs, and these polygenic scores could potentially be used to identify high-risk individuals. Lastly, using a real-world dataset, we identified seven SUD-shared genes targeting drugs that may be repurposed for treating SUDs, particularly in those suffering from comorbid SUDs.

Indexed as

Substance-Related DisordersBlack or African AmericanGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPolymorphism, Single NucleotideWhiteWhite People

Identifiers

PMID41057643
PMCPMC12916498

What Socratic holds

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Registered trials

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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 Socratic graph.