Smoking is a moderately heritable behavior that is one of the leading preventable causes of death in the United States. Genome wide association studies have discovered hundreds of common variants associated with tobacco use in individuals of European ancestry, but similar associations have not been studied in non-European populations. Low frequency variants are expected to affect smoking risk, but any such rare variants are yet to be identified, likely due in part to low statistical power of existing studies.

As a part of the Trans-Omics for Precision Medicine Whole Genome Sequencing Program (TOPMed), we seek to identify novel associations between rare variants and four measures of smoking behavior in a multi-ethnic sample. Two of these phenotypes relate to the initiation of smoking, capturing whether an individual has ever smoked regularly in their life and the age at which they began smoking regularly. We also measured smoking cessation through a comparison of current and former smokers. Finally, the heaviness of tobacco use among smokers is measured with the number of cigarettes smoked per day.

At the time of writing, the TOPMed project has called genotypes from 65,000 individuals with 30x whole genome sequences. A subset of 45,000 individuals from this data freeze have one or more smoking phenotypes. We will present results for all four of our smoking phenotypes, including single variant tests on up to 582,000,000 variants and gene based tests on rare nonsynonymous and loss of function variants. To date, we have conducted single variant association tests for cigarettes smoked per day with 154,176,919 variants with minor allele count > 10 using whole genome sequences from 10,444 individuals. This preliminary meta-analysis showed no significant associations between any variants and cigarettes smoked per day, suggesting that additional samples will be required to make discoveries for this and other complex substance use phenotypes. We will present updated results from single variant tests and gene based tests on much larger samples, up to the full sample of 45,000 with one or more smoking phenotypes. Our power to detect effects will increase as the remainder of our sample is analyzed and as the data available to us through TOPMed continues to grow with the release of new data freezes.