First genome-wide search for cannabis dependence genes found suggestive signals but no definitive hits | Research

The takeaway

The first genome-wide association study of cannabis dependence tested nearly 1 million genetic variants in 708 cases versus 2,346 controls, finding suggestive signals on chromosome 17 but none reaching genome-wide significance.

Read this if you are interested in the search for specific genes that influence cannabis dependence risk.

Nearly 1 million genetic variants tested; none reached genome-wide significance

What the researchers found

Researchers conducted the first genome-wide association study (GWAS) specifically targeting DSM-IV cannabis dependence. They compared 708 cannabis-dependent individuals to 2,346 cannabis-exposed but non-dependent controls.

None of the 948,142 single nucleotide polymorphisms (SNPs) tested reached the strict threshold for genome-wide significance (P < 10^-8). The strongest signals were two SNPs on chromosome 17 (rs1019238 and rs1431318) in the ANKFN1 gene, with P values at 10^-7.

Despite the null headline finding, the study represented an important first step because twin studies consistently showed 50-70% heritability for cannabis dependence, meaning specific genetic variants must exist even if this study was underpowered to detect them.

Why it matters

While the null result was initially disappointing, it demonstrated that cannabis dependence is likely influenced by many genes of small individual effect, requiring much larger samples to detect, rather than a few genes of large effect.

The numbers in context

708 cases, 2,346 controls. 948,142 SNPs tested. Lowest P values at 10^-7 (chromosome 17, ANKFN1 gene). None reached genome-wide significance (10^-8).

How the study worked

Genome-wide association study (GWAS) using logistic regression in PLINK. 708 DSM-IV cannabis-dependent cases versus 2,346 cannabis-exposed non-dependent controls. 948,142 SNPs tested for association with dependence.

What this study cannot tell us

Likely underpowered given the expected small effect sizes of individual genetic variants. Single-ancestry sample may miss variants important in other populations. Cannabis dependence is genetically complex, requiring much larger samples.

How to read the evidence

First GWAS of cannabis dependence with moderate sample size but likely underpowered for the expected small genetic effect sizes.

When this study was published

Published in 2011. Larger GWAS studies have since identified genome-wide significant associations for cannabis use traits.

The bigger picture

This was a foundational study for cannabis genetics, establishing the GWAS approach and sample size requirements that would guide future, larger studies seeking to identify specific dependence-related genes.

Questions still open

Would larger GWAS identify genome-wide significant hits? What is the function of ANKFN1 and could it relate to dependence biology?

Common questions

Have scientists found genes for cannabis addiction?

This first genome-wide search found suggestive signals but no definitive genes. Cannabis dependence appears influenced by many genes of small effect, requiring very large studies to detect. Later, larger studies have identified some genome-wide significant signals.

Why did this study not find definitive results despite known heritability?

Twin studies show 50-70% heritability, but this genetic influence is spread across many genes, each contributing a tiny amount. Detecting these small effects requires tens of thousands of participants, far more than the 3,054 in this study.

Read the original research

A genome-wide association study of DSM-IV cannabis dependence.

Addiction biology, 16(3), 514-8

View on PubMed ↗Publisher’s paper ↗

Citation

Agrawal, Arpana; Lynskey, Michael T; Hinrichs, Anthony; Grucza, Richard; Saccone, Scott F; Krueger, Robert; Neuman, Rosalind; Howells, William; Fisher, Sherri; Fox, Louis; Cloninger, Robert; Dick, Danielle M; Doheny, Kimberly F; Edenberg, Howard J; Goate, Alison M; Hesselbrock, Victor; Johnson, Eric; Kramer, John; Kuperman, Samuel; Nurnberger, John I; Pugh, Elizabeth; Schuckit, Marc; Tischfield, Jay; Rice, John P; Bucholz, Kathleen K; Bierut, Laura J. (2011). A genome-wide association study of DSM-IV cannabis dependence.. Addiction biology, 16(3), 514-8. https://doi.org/10.1111/j.1369-1600.2010.00255.x