Genome Scan Identified Chromosomal Regions Linked to Cannabis and Alcohol Dependence
A genome-wide scan of families with high addiction rates found overlapping chromosomal regions linked to both alcohol and cannabis dependence, particularly on chromosomes 2 and 10.
Quick Facts
What This Study Found
Using large multi-generational families from the COGA study, researchers scanned the genome for regions linked to substance dependence using 1,717 genetic markers.
For alcohol dependence, significant linkage signals appeared on chromosomes 1, 2, and 10 (highest LOD score 3.7 on chromosome 10). For cannabis dependence, a notable signal appeared on chromosome 14 (LOD 1.9). For any illicit drug dependence, signals appeared on chromosomes 10 and 13.
When alcohol and drug dependence scores were combined, the strongest signals were on chromosomes 2 (LOD 3.2) and 10 (LOD 2.4 and 2.6 at different locations). The overlap on chromosome 10 for both alcohol-specific and broader substance dependence phenotypes suggested this region may harbor genes influencing general addiction vulnerability rather than substance-specific risk.
Key Numbers
Alcohol dependence: LOD 3.7 on chr 10 (60 cM), 3.4 on chr 2 (234 cM). Cannabis dependence: LOD 1.9 on chr 14 (95 cM). Any drug dependence: LOD 2.4 on chr 13 (64 cM). Combined: LOD 3.2 on chr 2, LOD 2.6 on chr 10.
How They Did This
Quantitative genome-wide linkage analysis using 1,717 SNP markers in large families from the Collaborative Study on the Genetics of Alcoholism (COGA). DSM-IV criteria counts for alcohol dependence, cannabis dependence, and any illicit drug dependence were analyzed individually and in combination.
Why This Research Matters
Identifying chromosomal regions linked to substance dependence is a step toward finding specific genes that influence addiction risk. The overlap between alcohol and drug dependence signals supports the idea that some genetic factors create a general vulnerability to addiction rather than risk for specific substances.
The Bigger Picture
This study contributed to the understanding that addiction has a significant genetic component and that some genetic risk factors are shared across substances. It helped guide subsequent gene-finding efforts that have identified specific addiction-related genes in these chromosomal regions.
What This Study Doesn't Tell Us
Linkage analysis identifies broad chromosomal regions containing many genes, not specific causal variants. The COGA families were selected for high alcoholism rates, which may limit generalizability. LOD scores for cannabis dependence specifically did not reach genome-wide significance.
Questions This Raises
- ?Which specific genes within these chromosomal regions drive addiction risk?
- ?Do the genes identified affect general reward processing, stress response, or other addiction-relevant pathways?
Trust & Context
- Key Stat:
- Chromosomes 2 and 10 showed overlapping linkage signals for alcohol and drug dependence
- Evidence Grade:
- This is a well-powered genome-wide linkage study using well-characterized families, providing moderate evidence for genetic regions of interest, though individual findings require replication.
- Study Age:
- Published in 2008. Genome-wide association studies (GWAS) with much larger samples have since identified specific genetic variants for substance use disorders.
- Original Title:
- Linkage scan for quantitative traits identifies new regions of interest for substance dependence in the Collaborative Study on the Genetics of Alcoholism (COGA) sample.
- Published In:
- Drug and alcohol dependence, 93(1-2), 12-20 (2008)
- Authors:
- Agrawal, Arpana(39), Hinrichs, Anthony L, Dunn, Gerald, Bertelsen, Sarah, Dick, Danielle M, Saccone, Scott F, Saccone, Nancy L, Grucza, Richard A, Wang, Jen C, Cloninger, C Robert, Edenberg, Howard J, Foroud, Tatiana, Hesselbrock, Victor, Kramer, John, Bucholz, Kathleen K, Kuperman, Samuel, Nurnberger, John I, Porjesz, Bernice, Schuckit, Marc A, Goate, Alison M, Bierut, Laura J
- Database ID:
- RTHC-00296
Evidence Hierarchy
Follows a group of people over time to track how outcomes develop.
What do these levels mean? →Frequently Asked Questions
Does this mean addiction is genetic?
The study found chromosomal regions associated with addiction risk, supporting a genetic component. However, genetics is only one factor. Environmental influences, life experiences, and personal choices also play major roles.
What is a LOD score?
A LOD (logarithm of odds) score measures the strength of evidence for genetic linkage. Scores above 3.0 are generally considered significant evidence that a chromosomal region contains a gene influencing the trait.
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Cite This Study
https://rethinkthc.com/research/RTHC-00296APA
Agrawal, Arpana; Hinrichs, Anthony L; Dunn, Gerald; Bertelsen, Sarah; Dick, Danielle M; Saccone, Scott F; Saccone, Nancy L; Grucza, Richard A; Wang, Jen C; Cloninger, C Robert; Edenberg, Howard J; Foroud, Tatiana; Hesselbrock, Victor; Kramer, John; Bucholz, Kathleen K; Kuperman, Samuel; Nurnberger, John I; Porjesz, Bernice; Schuckit, Marc A; Goate, Alison M; Bierut, Laura J. (2008). Linkage scan for quantitative traits identifies new regions of interest for substance dependence in the Collaborative Study on the Genetics of Alcoholism (COGA) sample.. Drug and alcohol dependence, 93(1-2), 12-20.
MLA
Agrawal, Arpana, et al. "Linkage scan for quantitative traits identifies new regions of interest for substance dependence in the Collaborative Study on the Genetics of Alcoholism (COGA) sample.." Drug and alcohol dependence, 2008.
RethinkTHC
RethinkTHC Research Database. "Linkage scan for quantitative traits identifies new regions ..." RTHC-00296. Retrieved from https://rethinkthc.com/research/agrawal-2008-linkage-scan-for-quantitative
Access the Original Study
Study data sourced from PubMed, a service of the U.S. National Library of Medicine, National Institutes of Health.
This study breakdown was produced by the RethinkTHC research team. We analyze and report published research findings without making health recommendations. All interpretations are based solely on the published abstract and study data.