Background and Aims: Although genome-wide association studies have identified many loci that influence smoking behaviors, much of the genetic variance remains unexplained. We characterized the genetic architecture of four smoking behaviors using single nucleotide polymorphism (SNP) heritability (h2SNP). This is an estimate of narrow-sense heritability specifically estimating the proportion of phenotypic variation due to causal variants (CVs) tagged by SNPs. Design: Partitioned h2SNP analysis of smoking behavior traits. Setting: UK Biobank. Participants: UK Biobank participants of European ancestry. The number of participants varied depending on the trait, from 54 792 to 323 068. Measurements: Smoking initiation, age of initiation, cigarettes per day (CPD; count, log-transformed, binned and dichotomized into heavy versus light) and smoking cessation with imputed genome-wide SNPs. Findings: We estimated that, in aggregate, approximately 18% of the phenotypic variance in smoking initiation was captured by imputed SNPs [h2SNP = 0.18, standard error (SE) = 0.01] and 12% [SE = 0.02] for smoking cessation, both of which were more than twice the previously reported estimates. Estimated age of initiation (h2SNP = 0.05, SE = 0.01) and binned CPD (h2SNP = 0.1, SE = 0.01) were substantially below published twin-based h2 of 50%. CPD encoding influenced estimates, with dichotomized CPD h2SNP = 0.28. There was no evidence of dominance genetic variance for any trait. Conclusion: A biobank study of smoking behavior traits suggested that the phenotypic variance explained by SNPs of smoking initiation, age of initiation, cigarettes per day and smoking cessation is modest overall.
Bibliographical noteFunding Information:
This work was supported by National Institute of Mental Health R01 MH100141‐06 [Principal Investigator (PI): M.C.K.]; National Institute on Drug Abuse R01 DA 044283, National Institute on Drug Abuse R01 DA 037904, National Human Genome Research Institute R01 HG 008983 (PI: S.I.V.), and National Institute on Drug Abuse R01 DA042090 (PI: D.B.H.); and the Institute for Behavioral Genetics. We thank John Hewitt, Jerry Stitzel, Charles Hoeffer, Laura Saba, Christian Hopfer, Naomi Wray and Peter Visscher for helpful discussion and comments. This research was conducted using the UK Biobank Resource (application number 1665). We thank the UK Biobank and the participants of the UK Biobank.
© 2021 Society for the Study of Addiction
- Dominance variance
- genetic architecture
PubMed: MeSH publication types
- Journal Article