Heritability, SNP- and Gene-Based Analyses of Cannabis Use Initiation and Age at Onset.
- Authors
- MinicΔ, Camelia C; Dolan, Conor V; Hottenga, Jouke-Jan; Pool, RenΓ©; Genome of the Netherlands Consortium; Fedko, Iryna O; Mbarek, Hamdi; Huppertz, Charlotte; Bartels, Meike; Boomsma, Dorret I; Vink, Jacqueline M
- Year
- 2015
- Journal
- Behavior genetics
- PMID
- 25987507
- DOI
- 10.1007/s10519-015-9723-9
- PMCID
- PMC4561059
Prior searches for genetic variants (GVs) implicated in initiation of cannabis use have been limited to common single nucleotide polymorphisms (SNPs) typed in HapMap samples. Denser SNPs are now available with the completion of the 1000 Genomes and the Genome of the Netherlands projects. More densely distributed SNPs are expected to track the causal variants better. Therefore we extend the search for variants implicated in early stages of cannabis use to previously untagged common and low-frequency variants. We run heritability, SNP and gene-based analyses of initiation and age at onset. This is the first genome-wide study of age at onset to date. Using GCTA and a sample of distantly related individuals from the Netherlands Twin Register, we estimated that the currently measured (and tagged) SNPs collectively explain 25 % of the variance in initiation (SE = 0.088; P = 0.0016). Chromosomes 4 and 18, previously linked with cannabis use and other addiction phenotypes, account for the largest amount of variance in initiation (6.8 %, SE = 0.025, P = 0.002 and 3.6 %, SE = 0.01, P = 0.012, respectively). No individual SNP- or gene-based test reached genomewide significance in the initiation or age at onset analyses. Our study detected association signal in the currently measured SNPs. A comparison with prior SNP-heritability estimates suggests that at least part of the signal is likely coming from previously untyped common and low frequency variants. Our results do not rule out the contribution of rare variants of larger effect-a plausible source of the difference between the twin-based heritability estimate and that from GCTA. The causal variants are likely of very small effect (i.e., <1 % explained variance) and are uniformly distributed over the genome in proportion to chromosomes' length. Similar to other complex traits and diseases, detecting such small effects is to be expected in sufficiently large samples.
Percent of variance in initiation of cannabis use explained per chromosome relative to chromosome length. The chromosome number is shown in circles
| # | Section | Preview |
|---|---|---|
| 40 | Discussion | Our study detected association signal in the measured SNPs. A comparison with prior SNP-heritability⦠|
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| Cannabis Pharmacogenomics: A Path to Personalized Medicine. | Babayeva M et al. | β | 2023 | β |
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| Transcriptome-wide association study by different approaches reveals candidate causal genes for cannabis use disorder. | Gao J et al. | β | 2023 | β |
| Common and distinguishing genetic factors for substance use behavior and disorder: an integrated analysis of genomic and transcriptomic studies from both human and animal studies. | Chang XW et al. | β | 2022 | β |
| The genetic aetiology of cannabis use: from twin models to genome-wide association studies and beyond. | Verweij KJH et al. | β | 2022 | β |
| Genetic basis of cannabis use: a systematic review. | Hillmer A et al. | β | 2021 | β |
| Genomic and Personalized Medicine Approaches for Substance Use Disorders (SUDs) Looking at Genome-Wide Association Studies. | Cozzoli D et al. | β | 2021 | β |
| Exploring the relationship between polygenic risk for cannabis use, peer cannabis use and the longitudinal course of cannabis involvement. | Johnson EC et al. | β | 2019 | β |
| Genome-wide association study implicates CHRNA2 in cannabis use disorder. | Demontis D et al. | β | 2019 | β |
| The Impact of Genes on Adolescent Substance Use: A Developmental Perspective. | Trucco EM et al. | β | 2019 | β |
| Genome-wide association meta-analysis of age at first cannabis use. | MinicΔ CC et al. | β | 2018 | β |
| Genome-wide association study identifies a novel locus for cannabis dependence. | Agrawal A et al. | β | 2018 | β |
| GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal influence of schizophrenia. | Pasman JA et al. | β | 2018 | β |
| Human Genetics of Addiction: New Insights and Future Directions. | Hancock DB et al. | β | 2018 | β |
| Evidence for the Risks and Consequences of Adolescent Cannabis Exposure. | Levine A et al. | β | 2017 | β |
| <i>S100A10</i> identified in a genome-wide gene Γ cannabis dependence interaction analysis of risky sexual behaviours. | Polimanti R et al. | β | 2017 | β |
| The genetic epidemiology of substance use disorder: A review. | Prom-Wormley EC et al. | β | 2017 | β |
| Genetic and Environmental Factors Associated with Cannabis Involvement. | Bogdan R et al. | β | 2016 | β |
| Genetic variation in FAAH is associated with cannabis use disorders in a young adult sample of Mexican Americans. | Melroy-Greif WE et al. | β | 2016 | β |
| Genome-wide association study of lifetime cannabis use based on a large meta-analytic sample of 32 330 subjects from the International Cannabis Consortium. | Stringer S et al. | β | 2016 | β |