Smoking is a major preventable cause of morbidity and mortality in the United States and is moderately heritable. Genome wide association studies (GWAS) has allowed the discovery of hundreds of common variants associated with smoking. Although low frequency variants are expected to influence tobacco use, these rare variants are yet to be identified possibly due in part to high statistical power required to test rare variants. Most of the GWAS for smoking have been conducted in individuals with European ancestry and similar associations have not been studied in non-European populations. As a part of the Trans-Omics for Precision Medicine Whole Genome Sequencing Program (TOPMed), we seek to identify rare variants associated with four measures of smoking behaviors in a multi-ethnic sample. Among the four phenotypes, two relate to the initiation of smoking, capturing the age at which they started smoking regularly and whether an individual has ever become a regular smoker in their life. The remaining two relate to smoking cessation which contrasts current and former smokers. Finally, the number of cigarettes smoked per day reflects the heaviness of tobacco use among smokers. 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 are conducting single variant association tests for age of initiation, smoking initiation, smoking cessation, and cigarettes smoked per day with 154,176,919 variants with minor allele count >=1 using whole genome sequences from 7,067 individuals. The preliminary results for age of initiation showed no significant associations, suggesting that additional samples will be required to raise the statistical power 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 larger samples, up to the full sample of 45,000 for one or more phenotypes. Stronger power to detect effects will be achieved as the remainder of our sample is analyzed and as the data available to us continues to grow with the release of new data freezes through TOPMed.

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.

Genome-wide array-based analyses of tobacco use have identified many associated common variants, but the vast majority of the heritability remains unexplained. Rare variants likely contribute to risk for smoking and other addictive behaviors, and cost-effective whole genome sequencing is now making genome-wide analyses of rare variants possible. The present study reports rare variant association results for tobacco use from TOPMed, which has at present called genotypes from 9,536 30x whole genome sequences in 8 distinct studies with smoking phenotypes. We conducted a genome-wide association study (GWAS) of all discovered variants with minor allele count > 10 for four phenotypes: regular vs never smoker (n=9,536;n variants=34,115,958), current vs former smoker (n=4,601;n variants=27,243,212), age of initiation of regular smoking (n=4,467;n variants=27,141,662) and cigarettes smoked per day (n=4,590;n variants=27,547,744). The GWAS yielded no significant results after Bonferroni correction per phenotype, although there was a signal suggested for the known variant rs16969968 in CHRNA5 (p=7.718e-05). Rare variant burden tests of highly deleterious variants also yielded no significant results. Finally, we used the TOPMed sequences to fine map 182 recently discovered smoking-related loci--defined as 1MB regions around top associated variants--from array-based GWAS meta-analyses across all four smoking phenotypes (N ranging from 256,658 to 991,257 depending on the phenotype). Of the 182 most significantly associated common variants within these 182 loci, two were significant after Bonferroni correction for 182 tests (rs56113850 in CYP2A6, p=7.3e-5 and rs112878080 in CHRNA3, p=2.6e-5), and 121 of the 182 variants showed the same direction of effect in TOPMed and GSCAN (p=5.1e-6). Forward selection fine mapping tests in TOPMed within the 182 loci discovered one additional conditionally independent variant in an intron of ASXL1 (rs148986225, MAF=0.003, p=1.7e-7) associated with cigarettes smoked per day after Bonferroni correction per phenotype. We expect to present updated results on a much larger data freeze approaching 50,000 total individuals, greatly increasing power and precision of all analyses.