Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals.

paper Cited Public

Authors: Zhou, Hang; Kember, Rachel L; Deak, Joseph D; Xu, Heng; Toikumo, Sylvanus; Yuan, Kai; Lind, Penelope A; Farajzadeh, Leila; Wang, Lu; Hatoum, Alexander S; Johnson, Jessica; Lee, Hyunjoon; Mallard, Travis T; Xu, Jiayi; Johnston, Keira J A; Johnson, Emma C; Nielsen, Trine Tollerup; Galimberti, Marco; Dao, Cecilia; Levey, Daniel F; Overstreet, Cassie; Byrne, Enda M; Gillespie, Nathan A; Gordon, Scott; Hickie, Ian B; Whitfield, John B; Xu, Ke; Zhao, Hongyu; Huckins, Laura M; Davis, Lea K; Sanchez-Roige, Sandra; Madden, Pamela A F; Heath, Andrew C; Medland, Sarah E; Martin, Nicholas G; Ge, Tian; Smoller, Jordan W; Hougaard, David M; Børglum, Anders D; Demontis, Ditte; Krystal, John H; Gaziano, J Michael; Edenberg, Howard J; Agrawal, Arpana; Million Veteran Program; Justice, Amy C; Stein, Murray B; Kranzler, Henry R; Gelernter, Joel
Year: 2023
Journal: Nature medicine
PMID: 38062264
DOI: 10.1038/s41591-023-02653-5
PMCID: PMC10719093

Fig. 1

Genetic architecture of PAU.a, Sample sizes in different ancestral groups. b, Relationship between sample size and number of independent variants identified. Kranzler et al., 2019: cross-ancestry meta-analysis for AUD; Zhou et al., 2020: PAU in EUR. c, Lookup for cross-ancestry replication in AFR for the 85 independent variants in the EUR meta-analysis. Of the 85 variants, 76 could be analyzed in AFR (Methods). A sign test was performed for the number of variants with same direction of effect (64/76, binomial test P = 1.0 × 10−9). Twenty-three variants were nominally significant (P < 0.05) in AFR and six were significant after multiple correction (P < 0.05/76 = 6.58 × 10−4). d, Observed-scale and liability-scale SNP-based heritability (h2) in multiple ancestries. For PAU in EUR, N = 903,147 and for AUD, N = 753,249 (EUR), N = 122,571 (AFR) and N = 38,962 (LA). The error bar is the 95% confidence interval. e, Cross-ancestry genetic-effect correlation (ρge) and genetic-impact correlation (ρgi) among EUR (N = 903,147), AFR (N = 122,571) and LA (N = 38,962) ancestries. The error bar is the 95% confidence interval. f, Genome-wide association results for PAU in the cross-ancestry meta-analysis (N = 1,079,947 and Neffective = 646,371). Effective sample size-weighted meta-analyses were performed using METAL. Red line is significance threshold of 5 × 10−8.

LLM interpretation

This figure presents the genetic architecture of Problematic Alcohol Use (PAU) across multiple ancestries. It includes a pie chart of sample distribution (a), a line plot showing the relationship between sample size and identified variants (b), a horizontal bar chart detailing variant replication in AFR populations (c), and dot plots with 95% confidence intervals for SNP-based heritability (d) and genetic correlations (e). Panel (f) is a Manhattan plot showing genome-wide association results, highlighting a highly significant peak at *ADH1B* ($P = 2.22 \times 10^{-283}$) above the red significance threshold of $5 \times 10^{-8}$.

Fig. 2

Fine mapping for PAU.a, Fine mapping of causal variants in 85 regions in EUR. b, Ninety-two regions in a cross-ancestry analysis were fine mapped and a direct comparison was done for these regions in EUR. c, Comparison for the highest PIPs from cross-ancestry and EUR-only fine mapping in the 92 regions. Red dots are the regions fine mapped across EUR, AFR and LA; blue dots are the regions fine mapped across EUR and AFR; green dots are the regions fine mapped across EUR and LA; and black dots are the regions only fine mapped in EUR. FM, fine mapping.

LLM interpretation

This figure presents fine-mapping results for PAU across different ancestries. Panels **a** and **b** are horizontal stacked bar charts showing the distribution of credible set lengths (ranging from 1 to >20) for 85 EUR regions and a comparison of 92 regions between cross-ancestry and EUR-only analyses. Panel **c** is a scatter plot comparing the best posterior inclusion probabilities (PIPs) between cross-ancestry and EUR-only fine mapping, with color-coded dots indicating the specific ancestry combinations used (EUR, AFR, and LA).

Fig. 3

Genetic correlations between AUD and traits in AFR.Total PCL is the total index of recent symptom severity by the post-traumatic stress disorder checklist for DSM-IV. Genetic correlations were estimated using LDSC. Traits with P < 3.85 × 10−3 are genetically correlated with AUD (N = 122,571) after Bonferroni correction. The error bar is the 95% confidence interval.

LLM interpretation

This figure is a forest plot showing the genetic correlations between Alcohol Use Disorder (AUD) and various traits in an African population. The x-axis represents the genetic correlation coefficient, with blue squares indicating the point estimate and horizontal lines representing the 95% confidence intervals. Positive genetic correlations are observed for maximum habitual alcohol intake, OUD, and smoking trajectory, all of which have p-values below the Bonferroni-corrected threshold ($P < 3.85 \times 10^{-3}$).

#	Section	Preview
0	Main	Excessive alcohol use and alcohol use disorder (AUD) are leading causes of death and morbidity…
1	Main	Genetic and environmental factors contribute to AUD risk, with an observed heritability (h2) of…
2	Main	A key finding from recent studies is that both AUD and AUDIT–P differ phenotypically and…
3	Main	Notwithstanding prior discovery of multiple genome-wide significant (GWS) loci for PAU, there are…
4	Main	In this Article, to improve our understanding of the biology of PAU in multiple populations, we…
5	Results — Ancestrally diverse data collection	To extend our understanding of the genetics of PAU—a phenotype comprising AUD and alcohol-related…
6	Results — Ancestrally diverse data collection	previous study9, we utilized data on International Classification of Diseases (ICD)-diagnosed AUD…
7	Results — Ancestrally diverse data collection	excluding two Australian cohorts.Cohorts are described in the Methods. UKB–EUR1: genetically…
8	Results — Genome-wide association results for PAU	We performed GWAS and within-ancestry meta-analyses for PAU in five ancestral groups and then…
9	Results — Genome-wide association results for PAU	With the smaller sample numbers, the non-EUR GWAS yielded fewer variants associated with PAU than…
10	Results — Genome-wide association results for PAU	Of the 85 lead variants identified in the EUR GWAS, 76 were either directly analyzed or had proxy…
11	Results — Genome-wide association results for PAU	The SNP-based heritability (h2) for PAU and AUD (excluding AUDIT–P from UKB) in EUR, AFR and LA…
12	Results — Genome-wide association results for PAU	We performed a secondary, sex-stratified (sex was concordant between self-reported and genetically…
13	Results — Genome-wide association results for PAU	High genetic correlations were observed across the EUR, AFR and LA ancestries (Fig. 1e and…
14	Results — Genome-wide association results for PAU	In the cross-ancestry meta-analysis of all available datasets, we identified 100 independent…
15	Results — Within- and cross-ancestry causal variant fine mapping	We performed within-ancestry fine mapping for the 85 clumped regions with independent lead variants…
16	Results — Within- and cross-ancestry causal variant fine mapping	We performed cross-ancestry fine mapping to identify credible sets with 99% PIP for causal variants…
17	Results — Within- and cross-ancestry causal variant fine mapping	To compare within- and cross-ancestry fine mapping, we performed within-ancestry fine mapping for…
18	Results — Gene-based association analysis	We used Multivariate Analysis of Genomic Annotation (MAGMA)32 to perform gene-based association…
19	Results — TWAS	We used S-PrediXcan33 to identify predicted gene expression associations with PAU in 13 brain…

Name	Type
1000 Genomes Project	cohort
1000 Genomes Project phase 3 EUR LD reference local	cohort
acamprosate	drug
AD8 local	phenotype
ADH1B	gene
ADH1C	gene
ADH5	gene
ADH gene cluster	gene
adult midbrain dopaminergic local	anatomy
Affymetrix Axiom biobank array local	drug
AFR	cohort
AFR ancestries local	cohort
AFR ancestry	cohort
African American	cohort
AFR meta-analysis local	cohort
AGDS	cohort
alcohol	phenotype
alcohol dependence	phenotype
Alcohol-induced blackouts local	phenotype
alcohol-related problems	phenotype
Alcohol Use	phenotype
Alcohol Use Disorder	phenotype
alcohol use disorders	phenotype
alcohol withdrawal	phenotype
alcohol withdrawal-related anxiety local	phenotype
ALDH2 region local	gene
All of Us Research Program	cohort
Alzheimer's disease	phenotype
amlodipine	drug
AMT local	gene
amygdala	anatomy
attention deficit hyperactivity disorder	phenotype
AUD	phenotype
AUD/AD local	phenotype
AUDIT-P	phenotype
AUD PRS local	cohort
AUD PRS	drug
Australian Genetics of Bipolar Disorder Study local	cohort
autism spectrum disorder	phenotype
Bdnf	gene
biobanks	cohort
BioMe biobank local	cohort
BioVU	cohort
bipolar disorder	phenotype
brain	anatomy
brain-linked gene local	gene
brain tissue	anatomy
BRAP	phenotype
BRD3 local	gene
Brisbane Longitudinal Twin Study	cohort
CACNA1C	gene
cannabis use	phenotype
cannabis use disorder	phenotype
caudate nucleus	anatomy
causal variant	cohort
cerebellar hemisphere	anatomy
cerebellum	anatomy
CEU	cohort
CHB	cohort
CHD9	gene
CLMN local	gene
clomethiazole local	drug
Clomethiazole local	drug
cocaine	phenotype
conditionally independent variants local	variant
Core+Exome family chip local	drug
cortical neurons	anatomy
cross-ancestry meta-analysis local	cohort
Cross-ancestry meta-analysis local	cohort
CTA-223H9.9 local	gene
Denmark birth cohort 1981-2008 local	cohort
disulfiram	drug
dorsolateral prefrontal cortex	anatomy
DPYD	gene
DRD2	gene
DSM-5 AUD	phenotype
DSM-5 AUD criterion count local	phenotype
DSM-IV alcohol dependence	phenotype
DYPD	gene
EA	cohort
Eagle2	drug
EAs	cohort
EAS ancestry local	cohort
East Asian	cohort
East Asian cohorts local	cohort
educational attainment	phenotype
EUR	cohort
EUR lead SNP local	variant
EUR meta-analysis local	cohort
European ancestry	cohort
Europeans	cohort
EVI2A local	gene
EVI2B local	gene
excessive alcohol consumption	phenotype
externalizing behavior	phenotype
fetal brain	anatomy
FinnGen	cohort
frequency of alcohol use	phenotype
FTO	gene
gabapentin	drug
Gabra4	gene
GBP local	cohort
GBP study local	cohort
GCKR	gene
Global Biobank Meta-analysis Initiative local	cohort
Global Screening Array v1 local	drug
Global Screening Array v2	drug
glycemic traits	phenotype
GSA local	drug
GTEx79 local	cohort
Han Chinese–Cyto local	cohort
Han Chinese–GSA local	cohort
Han Chinese–Illumina Cyto12 array local	cohort
Han Chinese–Illumina Global Screening Array local	cohort
Haplotype Reference Consortium	cohort
HapMap3	cohort
HapMap3 dataset local	cohort
height	phenotype
hg19	drug
Hispanic	phenotype
hypothalamus	anatomy
ICD-10	phenotype
ICD-9 local	phenotype
Illumina 2.5M chip local	drug
Illumina Global Screening Array local	drug
Illumina GSA v.2 local	drug
Illumina HapMap-derived chip 317K local	drug
Illumina HapMap-derived chip 370K local	drug
Illumina HapMap-derived chip 610K local	drug
Illumina HapMap-derived chip 660K local	drug
Illumina MEGEX array local	drug
Illumina Omni local	drug
Illumina PsychArray local	drug
iPSC-derived astrocyte local	anatomy
iPSC-derived neuron local	anatomy
iPSYCH	cohort
iPSYCH1 local	cohort
iPSYCH2 local	cohort
iPSYCH cohort	cohort
iPSYCH study local	cohort
Klb	gene
L1000 local	drug
LA	cohort
LA ancestry local	cohort
LA samples from MVP local	cohort
lead SNP	cohort
lead variants	variant
major depressive disorder	phenotype
Mapt	gene
Mass General Brigham Biobank	cohort
Maximum Habitual Alcohol Intake	phenotype
MEGA	drug
melperone local	drug
methamphetamine	drug
methamphetamine dependence	phenotype
Michigan Imputation Server	drug
Million Veteran Program	cohort
Minimac4 local	drug
Mount Sinai (BioMe) local	cohort
MsCAVIAR local	drug
MTCH2	gene
multi-ancestry GWAS local	cohort
Multiple cohorts local	cohort
MVP	cohort
MVP AUD local	cohort
MVPAUD local	cohort
MVP EAS local	cohort
MVP release 4 local	cohort
naltrexone	drug
National Survey on Drug Use and Health	cohort
NCAM1	gene
Nineteen and Up study local	cohort
Nondependent use local	phenotype
non-EUR	cohort
non-EUR ancestry local	cohort
non-EUR groups local	cohort
non-EUR GWAS local	cohort
non-European ancestry	cohort
nonpsychiatric traits local	phenotype
nucleus accumbens	anatomy
OmniExpress local	drug
opioid	drug
opioid dependence	phenotype
OPRM1	cohort
OUD	phenotype
PAU	phenotype
PAU PRS local	cohort
PAU PRS	phenotype
PAU PRS local	variant
PAU risk local	phenotype
Pde4b	gene
Penn Medicine Biobank	cohort
PGC	cohort
PGC AD	cohort
PGC study local	cohort
phecode	phenotype
PheWAS local	phenotype
physical traits local	phenotype
Plink	drug
PLINK v1.9 local	drug
PMBB	cohort
PredictDB	cohort
problematic alcohol use	phenotype
proxy SNPs	variant
PRSAFR local	drug
PRSEUR local	drug
PRSfinal local	drug
PRSLA local	drug
PRSsingle local	drug
PsychArray local	drug
PsycheMERGE local	cohort
PsycheMERGE Network local	cohort
psychiatric disorders	phenotype
Psychiatric Genomics Consortium	cohort
psychiatric traits	phenotype
psychosocial traits local	phenotype
putamen	anatomy
QIMR	cohort
QIMR AGDS local	cohort
QIMR Berghofer local	cohort
QIMR Berghofer Australian Genetics of Depression Study local	cohort
QIMR Berghofer cohorts local	cohort
QIMR Berghofer study local	cohort
QIMR GBP local	cohort
QIMR TWINS local	cohort
rare variant	cohort
ricopili pipeline	drug
risk allele	cohort
rs10032906 local	variant
rs113464470 local	variant
rs12048727 local	variant
rs1229984	variant
rs12354219 local	variant
rs1260326	variant
rs12677811 local	variant
rs13107325	variant
rs142346138 local	variant
rs1799971	variant
rs181007867 local	variant
rs199537352 local	variant
rs2066702	variant
rs2098112 local	variant
rs2699453 local	variant
rs2942194 local	variant
rs3782886	variant
rs472140 local	variant
rs6265	variant
rs72772203 local	variant
rs7531138 local	variant
rs75967634	variant
SAIGE	drug
SAS	cohort
SAS ancestry local	cohort
SAS meta-analysis local	cohort
schizophrenia	phenotype
SLC25A37 local	gene
SLC25A48 local	gene
SLC39A8	gene
SLC4A8 local	gene
smartpca61 local	drug
smoking phenotypes	phenotype
smoking trajectory local	phenotype
Smoking trajectory local	phenotype
S-MultiXcan	drug
SNP	cohort
socioeconomic status	phenotype
South Asian	cohort
spironolactone local	drug
Spironolactone local	drug
S-PrediXcan	drug
substance use	phenotype
Substance use traits local	phenotype
SUD	phenotype
Thai METH local	cohort
Thai METH–GSA local	cohort
Thai METH–MEGA local	cohort
TLK2 local	gene
tobacco dependence	phenotype
tobacco use	phenotype
topiramate	drug
TOPMed Imputation Server	drug
TOPMed-r2 reference panel local	drug
trichostatin-a local	drug
Trichostatin-a local	drug
triflupromazine local	drug
TRIM54 local	gene
Twin cohort	cohort
UKB	cohort
UKB-EUR1 local	cohort
UKB–EUR1 local	cohort
UKB-EUR2 local	cohort
UKB–EUR2 local	cohort
UK Biobank	cohort
UKB–SAS local	cohort
United States	cohort
variant	cohort
Yale-Penn	cohort
Yale–Penn	cohort
Yale–Penn 3 local	cohort
Yale–Penn 3 individuals local	cohort
Yale–Penn AFR subsample local	cohort
Yale–Penn EUR subsample local	cohort
Yale–Penn study local	cohort
YP3 local	cohort
YPEL3 local	gene
YRI	cohort
ZNF184	gene

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In this knowledge base

Title	Year	PMID
Integrated single-cell multiomic profiling of caudate nucleus suggests key mechanisms in alcohol use disorder.	2025	41083468
The Impact of Polygenic Risk, Parental Separation, and Parental Relationship Discord on Heavy Episodic Drinking Across Adolescence and Young Adulthood in a High-Risk Sample.	2025	41367971

External

Title	Authors	Journal	Year	Link
Advancing substance use disorder biology by studying underlying gene x environment interactions.	Sidamon-Eristoff AE et al.	—	2026	→
A large-scale DNA methylation study of alcohol use identified robust associations and cell-type specific insights.	Clark SL et al.	—	2026	→
Alcohol use and risk of dementia in diverse populations: evidence from cohort, case-control and Mendelian randomisation approaches.	Topiwala A et al.	—	2026	→
Alcohol use disorder-associated gene FNDC4 alters glutamatergic and GABAergic neurogenesis in neural organoids.	Zhu X et al.	—	2026	→
Are polygenic scores for psychiatric and substance use outcomes "ready" for clinical application? Current state and next steps.	Dick DM et al.	—	2026	→
Central amygdala single-nucleus atlas reveals chromatin and gene transcription dynamics in human alcohol use disorder.	Lee CY et al.	—	2026	→
Genetic overlap of chronic pain, musculoskeletal-specific pain, substance use disorders and substance use consumption: Common addiction and substance-specific effects.	Rader L et al.	—	2026	→
Genome-wide association studies of lifetime and frequency of cannabis use in 131,895 individuals.	Thorpe HHA et al.	—	2026	→
Genome-wide meta-analyses of cross substance use disorders in diverse populations.	Lai D et al.	—	2026	→
<i>BDNF</i> gene polymorphisms and substance use disorders: a systematic review.	Peregud D et al.	—	2026	→
Multivariate genetic analyses of 2.2 million individuals reveal broad and substance-specific pathways of addiction risk.	Poore HE et al.	—	2026	→
Optimizing Control Definitions in Opioid Use Disorder Genetic Research Using Electronic Health Records	Niarchou M et al.	—	2026	→
Polygenic risk scores reveal genetic underpinnings of comorbidity between substance use disorders and ADHD.	Horstman LI et al.	—	2026	→
Robust human genetic evidence supporting causal effects of FGF21 on reducing alcohol consuming behaviours.	Cronjé HT et al.	—	2026	→
Sex differences in the genetic and causal relationships between depression, smoking, and alcohol use: the role of socioeconomic status.	Hu J et al.	—	2026	→
Trajectories of genetic risk across dimensions of alcohol use behaviors.	Savage JE et al.	—	2026	→
Transdiagnostic and Disorder-Level Genome-Wide Association Studies Enhance Precision of Substance Use and Psychiatric Genetic Risk Profiles in African and European Ancestries.	Khan Y et al.	—	2026	→
Alcohol use disorder and body mass index show genetic pleiotropy and shared neural associations.	Malone SG et al.	—	2025	→
Artificial Intelligence-driven and technological innovations in the diagnosis and management of substance use disorders.	Tassinari DL et al.	—	2025	→
Association Between GABRG2 and Self-Rating of the Effects of Alcohol in a French Young Adult Sample.	Moe JS et al.	—	2025	→
Associations of childhood adversity and substance use disorder polygenic scores with disorder severity and diagnostic criteria.	SooHoo JF et al.	—	2025	→
Beneath the Phenotypic Surface: Pleiotropy Shapes the Co-Occurrence of Alcohol Use Disorder and Psychopathology.	Mallard TT et al.	—	2025	→
Clinical, Genomic, and Neurophysiological Correlates of Lifetime Suicide Attempts among Individuals with an Alcohol Use Disorder.	Barr PB et al.	—	2025	→
Crosstalk between alcohol use disorder and obesity: two sides of the same coin?	Leggio L et al.	—	2025	→
Delineating trajectories of alcohol consumption and alcohol problems from adolescence to young adulthood: An integrated assessment of genetic, familial, and psychosocial factors.	Cheng HG et al.	—	2025	→
Development of the Comprehensive Addiction Risk Evaluation System: Initial Participant Response to an Online Personalized Feedback Program Integrating Genomic, Behavioral, and Environmental Risk Information.	Dick DM et al.	—	2025	→
Differences and similarities between the genetic architecture of lifetime substance use across different substances.	Bright U et al.	—	2025	→
Drinking motives and alcohol sensitivity mediate multidimensional genetic influences on alcohol use behaviors.	Savage JE et al.	—	2025	→
Externalizing as a common genetic influence for a broad spectrum of substance use and behavioral conditions: A developmental perspective from the Avon Longitudinal Study of Parents and Children.	Deng WQ et al.	—	2025	→
Gene expression differences associated with alcohol use disorder in human brain.	Willis C et al.	—	2025	→
Genetically modeled GLP1R and GIPR agonism reduce binge drinking and alcohol-associated phenotypes: a multi-ancestry drug-target Mendelian randomization study.	Reitz J et al.	—	2025	→
Genetic correlations of alcohol consumption and alcohol use disorder with sex hormone levels in females and males.	Waller TC et al.	—	2025	→
Genetic risk for alcohol use disorder in relation to individual symptom criteria: Do polygenic indices provide unique information for understanding severity and heterogeneity?	Sarles YM et al.	—	2025	→
Genome-Wide Association Studies of Delay Discounting and Impulsive Personality Traits in Children From the Adolescent Behavior and Cognitive Development Study.	Deng WQ et al.	—	2025	→
Genomic approaches to explore susceptibility and pathogenesis of alcohol use disorder and alcohol-associated liver disease.	Norden-Krichmar TM et al.	—	2025	→
Genomic structural equation study reveals links between anorexia nervosa and delay discounting and lack of perseverance but not other facets of impulsivity.	Bianchi SB et al.	—	2025	→
Genotype-by-sex interaction analyses for alcohol use disorder across biobanks.	Zhou H et al.	—	2025	→
Gut Microbiome-Liver-Brain axis in Alcohol Use Disorder. The role of gut dysbiosis and stress in alcohol-related cognitive impairment progression: possible therapeutic approaches.	Pich EM et al.	—	2025	→
Identification of potential therapeutic targets for problematic alcohol use using multi-omics data.	Lee DJ et al.	—	2025	→
Identification of risk variants and cross-disorder pleiotropy through multi-ancestry genome-wide analysis of alcohol use disorder.	Icick R et al.	—	2025	→
Impulsivity facets and substance use involvement: insights from genomic structural equation modeling.	Vilar-Ribó L et al.	—	2025	→
Integrated single-cell multiomic profiling of caudate nucleus suggests key mechanisms in alcohol use disorder.	Green NC et al.	—	2025	→
Integrating HiTOP and RDoC frameworks Part I: Genetic architecture of externalizing and internalizing psychopathology.	Davis CN et al.	—	2025	→
Investigating the Contribution of Coding Variants in Alcohol Use Disorder Using Whole-Exome Sequencing Across Ancestries.	Wang L et al.	—	2025	→
Large-scale transcriptomic analyses of major depressive disorder reveal convergent dysregulation of synaptic pathways in excitatory neurons.	Goes FS et al.	—	2025	→
Leveraging Genomic Data to Examine the Causal Impact of Alcohol, Tobacco, Cannabis, and Opioid Use on Biological and Cognitive Ageing.	Balbona JV et al.	—	2025	→
Leveraging pleiotropy for the improved treatment of psychiatric disorders.	Woodward DJ et al.	—	2025	→
Measures of General Intelligence and Risk for Alcohol Use Disorder.	Capusan AJ et al.	—	2025	→
Moderation of treatment outcomes by polygenic risk for alcohol-related traits in placebo-controlled trials of topiramate.	Kranzler HR et al.	—	2025	→
Multi-ancestral genome-wide association study of clinically defined nicotine dependence reveals strong genetic correlations with other substance use disorders and health-related traits.	Johnson EC et al.	—	2025	→
Multiancestry brain pQTL fine-mapping and integration with genome-wide association studies of 21 neurologic and psychiatric conditions.	Wingo AP et al.	—	2025	→
Multi-ancestry investigation of the genomics of erectile dysfunction.	Bright U et al.	—	2025	→
Multi-ancestry sequencing-based genome-wide association study of C-reactive protein in 513,273 genomes.	Li H et al.	—	2025	→
Next-generation biomarkers for alcohol consumption and alcohol use disorder diagnosis, prognosis, and treatment: A critical review.	Clark SL et al.	—	2025	→
Open Targets Platform: facilitating therapeutic hypotheses building in drug discovery.	Buniello A et al.	—	2025	→
Polygenic risk and childhood adversity as moderators of drug and alcohol withdrawal symptoms.	Han A et al.	—	2025	→
Post-traumatic stress and genetic interactions affect tobacco and alcohol use after trauma: findings from a multi-ancestry cohort.	Garrison-Desany HM et al.	—	2025	→
Predicting treatment-seeking status for alcohol use disorder using polygenic scores and machine learning in a deeply-phenotyped sample.	Jinwala Z et al.	—	2025	→
Predictive performance for alcohol use disorder of polygenic scores based on the general addiction risk factor and problematic alcohol use.	Pérez-Gutiérrez AM et al.	—	2025	→
Psychiatric genetics in the diverse landscape of Latin American populations.	Bruxel EM et al.	—	2025	→
Recent advances in understanding how compulsivity is related to behavioural addictions over their timecourse.	Solly JE et al.	—	2025	→
Shared Genetic Architecture and Neurobiological Pathways of Problematic Alcohol Use and Anxiety Disorders	Shi M et al.	—	2025	—
The effects of polygenic risks for alcohol misuse on negative emotion processing in young adult binge drinkers.	Chen Y et al.	—	2025	→
The Impact of Polygenic Risk, Parental Separation, and Parental Relationship Discord on Heavy Episodic Drinking Across Adolescence and Young Adulthood in a High-Risk Sample.	Kuo SI et al.	—	2025	→
The Promise of Genetics in Alcohol Use Disorders and the Problems of Phenotype, Polygenetic Architecture, Ancestry, and Comorbidity.	Ehlers CL et al.	—	2025	→
The Psychiatric Genomics Consortium: discoveries and directions.	Agrawal A et al.	—	2025	→
The Role of SLC39A8.p.(Ala391Thr) in Schizophrenia Symptom Severity and Cognitive Ability: Cross-Sectional Studies of Schizophrenia and the General UK Population.	Smart SE et al.	—	2025	→
Uncovering genetic mechanisms associated with harmful use of alcohol in admixed Latin Americans.	Amaral EHB et al.	—	2025	→
Understanding the alcohol harm paradox: A multivariable mendelian randomization approach.	Sawyer G et al.	—	2025	→
Understanding the Comorbidities Among Psychiatric Disorders, Chronic Low Back Pain, and Spinal Degenerative Disease Using Observational and Genetically Informed Analyses.	Qiu D et al.	—	2025	→
Unveiling causal relationship between white matter tracts and psychiatric disorders.	Yu Y et al.	—	2025	→
Whole-exome sequencing study of opioid dependence offers novel insights into the contributions of exome variants.	Wang L et al.	—	2025	→
Whole Genome Sequencing of Pedigrees With High Density of Substance Use and Psychiatric Disorders: A Meeting Report.	Hill SY et al.	—	2025	→
A genome-wide investigation into the underlying genetic architecture of personality traits and overlap with psychopathology.	Gupta P et al.	—	2024	→
Association of genetically predicted problem alcohol use with risk of atrial fibrillation: a Mendelian randomization study.	Ji Y et al.	—	2024	→
Considerations for the application of polygenic scores to clinical care of individuals with substance use disorders.	Kember RL et al.	—	2024	→
Divergent gene expression patterns in alcohol and opioid use disorders lead to consistent alterations in functional networks within the dorsolateral prefrontal cortex.	MacDonald M et al.	—	2024	→
Examining the association between the FTO gene and neuroticism reveals indirect effects on subjective well-being and problematic alcohol use.	Cai W et al.	—	2024	→
Genetic contribution to the comorbidity between attention-deficit/hyperactivity disorder and substance use disorders.	Koller D et al.	—	2024	→
Genetic Heterogeneity Across Dimensions of Alcohol Use Behaviors.	Savage JE et al.	—	2024	→
Genetic influences and causal pathways shared between cannabis use disorder and other substance use traits.	Galimberti M et al.	—	2024	→
Genome-wide association study of the common retinal disorder epiretinal membrane: Significant risk loci in each of three American populations.	Gelernter J et al.	—	2024	→
How to survive enormous amounts of alcohol.	Spanagel R	—	2024	→
Human genetics and epigenetics of alcohol use disorder.	Zhou H et al.	—	2024	→
Identification and validation of a novel gene <i>ARVCF</i> associated with alcohol dependence among Chinese population.	Shi X et al.	—	2024	→
Identification of novel genetic loci and candidate genes for progressive ethanol consumption in diversity outbred mice.	Mignogna KM et al.	—	2024	→
Long-term impact of digital media on brain development in children.	Nivins S et al.	—	2024	→
Neuronal-specific methylome and hydroxymethylome analysis reveal significant loci associated with alcohol use disorder.	Andrade-Brito DE et al.	—	2024	→
Pleiotropy and genetically inferred causality linking multisite chronic pain to substance use disorders.	Koller D et al.	—	2024	→
Rare and common variants associated with alcohol consumption identify a conserved molecular network.	Leger BS et al.	—	2024	→
Western diets and chronic diseases.	Adolph TE et al.	—	2024	→
What Are the Genetic Building Blocks of Alcohol-Related Behaviors?	Gelernter J et al.	—	2024	→
Alcohol Consumption and Alcohol Use Disorder: Exposing an Increasingly Shared Genetic Architecture.	White JD et al.	—	2023	→
Examining interactions between polygenic scores and interpersonal trauma exposure on alcohol consumption and use disorder in an ancestrally diverse college cohort.	Sheerin CM et al.	—	2023	→
Polygenic risk score for problematic alcohol use predicts heavy drinking and alcohol use disorder symptoms in young adulthood after accounting for adolescent alcohol use and parental alcohol use disorder.	Wang FL et al.	—	2023	→