Drug and Alcohol DependenceGeneticsPeer-reviewed journal article
Causal relationships between substance use and insomnia
Joëlle A. PasmaniD, Dirk J. A. SmitiD, Lilian Kingma, Jacqueline M. VinkiD, Jorien L. TreuriD, Karin J. H. VerweijiD
Abstract
BackgroundPoor sleep quality and insomnia have been associated with the use of tobacco, alcohol, and cannabis, but it is unclear if there is a causal link. In this Mendelian Randomization (MR) study we examine if insomnia causes substance use and/or if substance use causes insomnia. MethodsMR uses summary effect estimates from a genome-wide association study (GWAS) to create a genetic instrumental variable for a proposed exposure variable and then identifies that same genetic instrument in an outcome GWAS. With data of GWAS of insomnia, smoking (initiation, heaviness, cessation), alcohol use (drinks per week, dependence), and cannabis initiation, bi-directional causal effects were tested. Multiple sensitivity analyses were applied to assess the robustness of the findings. ResultsThere was strong evidence for positive causal effects of insomnia on all substance use phenotypes (smoking traits, alcohol dependence, cannabis initiation), except alcohol per week. The effects on alcohol dependence and cannabis initiation were attenuated after filtering out pleiotropic SNPs. In the other direction, there was strong evidence that smoking initiation increased chances of insomnia (smoking heaviness and cessation could not be tested as exposures). We found no evidence that alcohol use per week, alcohol dependence, or cannabis initiation causally affect insomnia. ConclusionsThere were unidirectional effects of insomnia on alcohol dependence and cannabis initiation, and bidirectional effects between insomnia and smoking measures. Bidirectional effects between smoking and insomnia might give rise to a vicious circle. Future research should investigate if interventions aimed at insomnia are beneficial for substance use treatment.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 62
- FWCI
- 9.18
- Field percentile
- top 2%
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