Human Genetics of Addiction: New Insights and Future Directions.

paper Cited Public

Authors: Hancock, Dana B; Markunas, Christina A; Bierut, Laura J; Johnson, Eric O
Year: 2018
Journal: Current psychiatry reports
PMID: 29504045
DOI: 10.1007/s11920-018-0873-3
PMCID: PMC5983372

#	Section	Preview
20	GWAS for illicit drugs combined	Next, GWAS of people who inject drugs vs. controls, revealed an African American-specific…
21	Potential for future GWAS to broaden the known genetic etiology unique to and shared among addiction phenotypes	Prior GWAS have utilized varied addiction phenotypes and biomarkers as well as study designs. A…
22	Potential for future GWAS to broaden the known genetic etiology unique to and shared among addiction phenotypes	associated with specific substances, for example [105, 109]. Other studies have not adjusted for…
23	Potential for future GWAS to broaden the known genetic etiology unique to and shared among addiction phenotypes	We fully expect that future GWAS using larger sample sizes from expanded meta-analyses and…
24	Potential for future GWAS to broaden the known genetic etiology unique to and shared among addiction phenotypes	alcohol, and substance use disorder phenotypes [123–125]. Early examples of genetic variants that…
25	Ongoing sequential integration of multiple ‘omics data	Establishing robust statistical evidence for a GWAS-identified variant marks the starting point in…
26	Ongoing sequential integration of multiple ‘omics data	Integration of GWAS with other ‘omics data types (such as, DNA methylation or RNA expression)…
27	Ongoing sequential integration of multiple ‘omics data	A reversal in the direction of sequential integration is an alternative, but not as widely utilized,…
28	Ongoing sequential integration of multiple ‘omics data	In taking integration to the next level, PrediXcan [134] is a promising new gene-based method that…
29	Importance of brain tissue specificity for multi ‘omics analyses	These sequential integration examples highlight a challenge for the field of addiction, and…
30	Importance of brain tissue specificity for multi ‘omics analyses	eQTL [136, 137, 135] variants mapped in blood vs. brain. Thus, when analyzing gene regulatory…
31	Upcoming concurrent integration of multi ‘omics data	Where once a single ‘omics type was used, studies that capture multiple ‘omics data types in the…
32	Upcoming concurrent integration of multi ‘omics data	New methods are being developed that will allow researchers to analyze data concurrently, as applied…
33	Conclusions	GWAS analyses have identified several genetic loci with statistically robust and reproducible…
34	Conclusions	variants with one another and with prominent environmental exposures, which will likely require very…
35	Conclusions	New genetic discoveries are also likely to arise from leveraging novel analytic approaches such as…

Name	Type
1000 Genomes African ancestry reference panels local	cohort
241 African Americans local	cohort
383 opioid-dependent African Americans local	cohort
abstinence	phenotype
acetaldehyde	drug
acetic acid	drug
addiction	phenotype
addiction biomarkers local	phenotype
addiction phenotype local	phenotype
addiction phenotypes	phenotype
addiction to any illicit drug local	phenotype
ADH1B	gene
ADH cluster	gene
Adult U.S. smokers local	cohort
African American	cohort
African American ancestry participants local	cohort
airflow obstruction	phenotype
alcohol	phenotype
Alcohol biomarkers local	phenotype
alcohol drinking problems local	phenotype
alcohol flush reaction	phenotype
alcohol-related phenotypes	phenotype
alcohol sensitivity	phenotype
Alcohol Use Disorder	phenotype
ALDH2	gene
allocortex	anatomy
amphetamine	drug
Amphetamine GWAS local	cohort
Asian	cohort
assessed controls local	cohort
AUTS2	gene
basal ganglia	anatomy
Bdnf	gene
Biomarkers of excessive alcohol intake local	phenotype
bipolar disorder	phenotype
blood	drug
blood pressure	phenotype
brain	anatomy
Brain eQTL Almanac local	cohort
cancer	phenotype
cannabis use	phenotype
cerebellum	anatomy
cessation treatment local	drug
CHRNA2	gene
Chrna3	gene
Chrna4	gene
CHRNA5	gene
Chrna6	gene
Chrnb3	gene
Chrnb4	gene
cigarettes	phenotype
cis-eQTL SNP local	variant
cocaine	phenotype
Cocaine GWAS local	cohort
common variants	cohort
control population	cohort
COPD	phenotype
copy number variants	variant
coronary heart disease	phenotype
cotinine biomarker local	phenotype
CREBBP	gene
current smoking	phenotype
CYP2A6	gene
CYP2B6	gene
diverse ancestry groups local	cohort
DNA methylation	drug
Dnmt3b	gene
drug dependence	phenotype
drug-seeking behavior	phenotype
emphysema	phenotype
environmental exposures	drug
eQTLGen Consortium	cohort
European ancestry	cohort
European population	cohort
ever smoking	phenotype
extended amygdala	anatomy
Finnish participants local	cohort
former smokers	phenotype
frontal cortex	anatomy
functional missense SNPs local	variant
GCKR	gene
general substance dependence local	phenotype
general substance dependence liability local	phenotype
genetically correlated outcomes local	phenotype
genetic variants	cohort
GTEx	cohort
GWAS-identified variants local	variant
habenula	anatomy
healthy cohorts local	cohort
heavy drinking	phenotype
heavy smoking	phenotype
Hispanic	phenotype
illicit drugs	phenotype
illicit drug use	phenotype
indel	variant
insula	anatomy
intralobular white matter	anatomy
Japanese population	cohort
KAT2B	gene
kidney function	phenotype
Klb	gene
large GWAS meta-analysis (N=32,330 European ancestry) local	cohort
Large-scale biobanks local	cohort
Liver cirrhosis	phenotype
LOC151121 local	gene
lung cancer	phenotype
lung function	phenotype
meQTL local	variant
Methadone	drug
methadone dosing local	phenotype
methamphetamine	drug
Methamphetamine GWAS local	cohort
misuse	phenotype
morphine	drug
morphine dosing local	phenotype
Multiple ancestries cohort local	cohort
Multiple ancestries combined local	cohort
never smokers	phenotype
nicotine	drug
nicotine dependence	phenotype
nicotine metabolite ratio	phenotype
nicotine withdrawal	phenotype
noncoding SNP local	variant
nsSNP	variant
nucleus accumbens	anatomy
opioid	drug
opioid dependence	phenotype
opioid phenotypes local	phenotype
OPRM1	cohort
other drugs	drug
people who inject drugs local	phenotype
peripheral arterial disease	phenotype
PFC	anatomy
pharmacologic treatment local	drug
postmortem human PFC local	anatomy
prefrontal cortex	anatomy
progression from misuse to later stages of addiction local	phenotype
psychiatric disorders	phenotype
RCF1	gene
recent GWAS meta-analysis (N=14,754 European Americans and African Americans) local	cohort
reward system	anatomy
RNA expression local	drug
rs1051730	variant
rs11636753 local	variant
rs117804171 local	variant
rs11940694	variant
rs1229984	variant
rs1229984-T local	variant
rs1344706	variant
rs16969968	variant
rs1799971	variant
rs2273500 local	variant
rs2952561 local	variant
rs2952621 local	variant
rs3778150	variant
rs588765	variant
rs6265	variant
rs671	variant
rs671-A local	variant
rs6943555	variant
rs73568641	variant
rs880395 local	variant
rs910083 local	variant
rs9829896	variant
schizophrenia	phenotype
Self-reported phenotypes local	phenotype
SERPINC1	gene
SGOL1	gene
smoking	phenotype
smoking biomarkers local	phenotype
smoking phenotypes	phenotype
SNP	cohort
stimulants	drug
substance	phenotype
substance use	phenotype
susceptibility to addiction local	phenotype
TF	gene
UGT2A3 local	gene
UGT2B10 local	gene
UK Biobank	cohort
U.S. population (2015) local	cohort
variant	cohort
ventral tegmental area	anatomy
ZNF804A	gene

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In this knowledge base

Title	Year	PMID
Multi-trait genome-wide association study of opioid addiction: OPRM1 and beyond.	2022	36207451
Is the Fagerström test for nicotine dependence invariant across secular trends in smoking? A question for cross-birth cohort analysis of nicotine dependence.	2018	29438887

External

Title	Authors	Journal	Year	Link
Addiction Susceptibility: Genetic Factors, Personality Traits, and Epigenetic Interactions with the Gut Microbiome.	Borrego-Ruiz A et al.	—	2025	→
Association of <i>DRD2</i> and <i>BDNF</i> Genetic Polymorphisms with Exercise Addiction.	da Silva IM et al.	—	2025	→
Indoor Tanning Addiction: Biological Mechanisms and Association with Other Disorders.	LaMonte OC et al.	—	2025	→
Neuroimaging correlates of psychological resilience: an Open Science systematic review and meta-analysis.	Kuehn A et al.	—	2025	→
An emerging multi-omic understanding of the genetics of opioid addiction.	Johnson EO et al.	—	2024	→
Deep sequencing of candidate genes identified 14 variants associated with smoking abstinence in an ethnically diverse sample.	Cinciripini PM et al.	—	2024	→
Enhanced Novel Object Recognition and Spatial Memory in Rats Selectively Bred for High Nicotine Preference.	Bekci E et al.	—	2024	→
Genes associated with cortical thickness alterations in behavioral addiction.	Xie H et al.	—	2024	→
Genetic control of DNA methylation is largely shared across European and East Asian populations.	Hatton AA et al.	—	2024	→
Integrating genetic and clinical data to predict lung cancer in patients with chronic obstructive pulmonary disease.	Gu Z et al.	—	2024	→
Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes.	Toikumo S et al.	—	2024	→
Opioid trail: Tracking contributions to opioid use disorder from host genetics to the gut microbiome.	Duffy EP et al.	—	2024	→
Reducing maladaptive behavior in neuropsychiatric disorders using network modification.	Timme NM	—	2024	→
Sex- and Substance-Specific Associations of Circadian-Related Genes with Addiction in the UK Biobank Cohort Implicate Neuroplasticity Pathways.	Khan A et al.	—	2024	→
SNP-based and haplotype-based genome-wide association on drug dependence in Han Chinese.	Xu H et al.	—	2024	→
An in-depth association analysis of genetic variants within nicotine-related loci: Meeting in middle of GWAS and genetic fine-mapping.	Mo C et al.	—	2023	→
Conflicting theories on addiction aetiology and the strengths and limitations of substance use disorder disease modelling.	Greener MR et al.	—	2023	→
Dissecting the epigenomic differences between smoking and nicotine dependence in a veteran cohort.	Nagamatsu ST et al.	—	2023	→
Evaluating 17 methods incorporating biological function with GWAS summary statistics to accelerate discovery demonstrates a tradeoff between high sensitivity and high positive predictive value.	Moore A et al.	—	2023	→
Evolutionary modeling suggests that addictions may be driven by competition-induced microbiome dysbiosis.	Lewin-Epstein O et al.	—	2023	→
Invited Expert Opinion- Bioinformatic and Limitation Directives to Help Adopt Genetic Addiction Risk Screening and Identify Preaddictive Reward Dysregulation: Required Analytic Evidence to Induce Dopamine Homeostatsis.	Blum K et al.	—	2023	→
Low Dopamine D2 Receptor Expression Drives Gene Networks Related to GABA, cAMP, Growth and Neuroinflammation in Striatal Indirect Pathway Neurons.	Guerri L et al.	—	2023	→
The pleiotropic contribution of genes in dopaminergic and serotonergic pathways to addiction and related behavioral traits.	Antón-Galindo E et al.	—	2023	→
Why do we climb mountains? An exploration of features of behavioural addiction in mountaineering and the association with stress-related psychiatric disorders.	Habelt L et al.	—	2023	→
Association of Predicted Expression and Multimodel Association Analysis of Substance Abuse Traits.	Bost DM et al.	—	2022	→
A Systematic Review of Genetic Polymorphisms Associated with Bipolar Disorder Comorbid to Substance Abuse.	de Marco A et al.	—	2022	→
Back-translating GWAS findings to animal models reveals a role for Hgfac and Slc39a8 in alcohol and nicotine consumption.	Banna FKE et al.	—	2022	→
Cocaine-Induced Locomotor Activation Differs Across Inbred Mouse Substrains.	Gaines CH et al.	—	2022	→
Convergence of case-specific epigenetic alterations identify a confluence of genetic vulnerabilities tied to opioid overdose.	Corradin O et al.	—	2022	→
Frequency of the Dopamine Receptor D3 (rs6280) vs. Opioid Receptor µ1 (rs1799971) Polymorphic Risk Alleles in Patients with Opioid Use Disorder: A Preponderance of Dopaminergic Mechanisms?	Gondré-Lewis MC et al.	—	2022	→
Multi-trait genome-wide association study of opioid addiction: OPRM1 and beyond.	Gaddis N et al.	—	2022	→
Relentless Stigma: A Qualitative Analysis of a Substance Use Recovery Needs Assessment.	Medina S et al.	—	2022	→
Smoking As an Outcome Moderator In the Treatment of Alcohol Use Disorders.	van Amsterdam J et al.	—	2022	→
The Impaired Nurse.	Salani D et al.	—	2022	→
The Promise of Polygenic Risk Prediction in Smoking Cessation: Evidence From Two Treatment Trials.	Bray M et al.	—	2022	→
Bibliometric Insights in Genetic Factors of Substance-Related Disorders: Intellectual Developments, Turning Points, and Emerging Trends.	Wang K et al.	—	2021	→
Ferroptosis-Related Genes in Neurodevelopment and Central Nervous System.	Kim SW et al.	—	2021	→
From single flies to many genes: Using <i>Drosophila</i> to explore the genetics of psychostimulant consumption.	Titos I et al.	—	2021	→
Genetic impacts on DNA methylation: research findings and future perspectives.	Villicaña S et al.	—	2021	→
Genetics of substance use disorders: a review.	Deak JD et al.	—	2021	→
Genome-wide DNA methylation differences in nucleus accumbens of smokers vs. nonsmokers.	Markunas CA et al.	—	2021	→
Heritable variation in locomotion, reward sensitivity and impulsive behaviors in a genetically diverse inbred mouse panel.	Bailey LS et al.	—	2021	→
Integration of evidence across human and model organism studies: A meeting report.	Palmer RHC et al.	—	2021	→
Intracranial self-stimulation and concomitant behaviors following systemic methamphetamine administration in Hnrnph1 mutant mice.	Borrelli KN et al.	—	2021	→
Pharmacokinetic and pharmacodynamic analyses of cocaine and its metabolites in behaviorally divergent inbred mouse strains.	Zhu J et al.	—	2021	→
Smoking among inpatients in treatment for substance use disorders: prevalence and effect on mental health and quality of life.	Lien L et al.	—	2021	→
Studying the Utility of Using Genetics to Predict Smoking-Related Outcomes in a Population-Based Study and a Selected Cohort.	Bray MJ et al.	—	2021	→
The Gut Microbiome and Substance Use Disorder.	Russell JT et al.	—	2021	→
Understanding the genetics and neurobiological pathways behind addiction (Review).	Popescu A et al.	—	2021	→
Whole-Exome Sequencing to Identify Potential Genetic Risk in Substance Use Disorders: A Pilot Feasibility Study.	AshaRani PV et al.	—	2021	→
Dissecting the genetic overlap of smoking behaviors, lung cancer, and chronic obstructive pulmonary disease: A focus on nicotinic receptors and nicotine metabolizing enzyme.	Bray MJ et al.	—	2020	→
Effect of short-term prescription opioids on DNA methylation of the OPRM1 promoter.	Sandoval-Sierra JV et al.	—	2020	→
Expanding the genetic architecture of nicotine dependence and its shared genetics with multiple traits.	Quach BC et al.	—	2020	→
Expanding the Genetic Architecture of Nicotine Dependence and its Shared Genetics with Multiple Traits: Findings from the Nicotine Dependence GenOmics (iNDiGO) Consortium	Quach BC et al.	—	2020	—
Genome-wide association study of smoking trajectory and meta-analysis of smoking status in 842,000 individuals.	Xu K et al.	—	2020	→
Genome-Wide DNA Methylation Analysis in Male Methamphetamine Users With Different Addiction Qualities.	Liu L et al.	—	2020	→
Heterogeneity and Polygenicity in Psychiatric Disorders: A Genome-Wide Perspective.	Wendt FR et al.	—	2020	→
Identifying Early Risk Factors for Addiction Later in Life: A Review of Prospective Longitudinal Studies.	Morales AM et al.	—	2020	→
Implementation and Evaluation of a Text Message-Based Addiction Counseling Program (Text4Hope-Addiction Support): Protocol for a Questionnaire Study.	Agyapong VIO et al.	—	2020	→
Prospects for finding the mechanisms of sex differences in addiction with human and model organism genetic analysis.	Datta U et al.	—	2020	→
Recent Efforts to Dissect the Genetic Basis of Alcohol Use and Abuse.	Sanchez-Roige S et al.	—	2020	→
Dorsal Striatal Circuits for Habits, Compulsions and Addictions.	Lipton DM et al.	—	2019	→
Electronic Health Records Are the Next Frontier for the Genetics of Substance Use Disorders.	Sanchez-Roige S et al.	—	2019	→
Genetics of alcohol use disorder: a review.	Deak JD et al.	—	2019	→
Insights from intoxicated Drosophila.	Petruccelli E et al.	—	2019	→
<i>OPRM1</i> A118G Polymorphisms and Its Role in Opioid Addiction: Implication on Severity and Treatment Approaches.	Taqi MM et al.	—	2019	→
Networking in Biology: The Hybrid Rat Diversity Panel.	Tabakoff B et al.	—	2019	→
[Prediction of binge drinking in young adults: a cohort study over nine years].	Morgenstern M et al.	—	2019	→
The Neuroscience of Drug Reward and Addiction.	Volkow ND et al.	—	2019	→
Three-dimensional chromosome architecture and drug addiction.	Chitaman JM et al.	—	2019	→
Tobacco Genomics: Complexity and Translational Challenges.	Bergen AW et al.	—	2019	→
Is the Fagerström test for nicotine dependence invariant across secular trends in smoking? A question for cross-birth cohort analysis of nicotine dependence.	Glasheen C et al.	—	2018	→
Understanding the implications of the biobehavioral basis of nicotine addiction and its impact on the efficacy of treatment.	Bozinoff N et al.	—	2018	→