SBIR-STTR Award

Tobacco-attributable disease remains the largest potentially modifiable cause of mortality. Strategies to reduce smoking prevalence include developing more effective smoking cessation treatments. Nicotine metabolism is a predictor of smoking behaviors, including response to treatment. The goal of this Phase I project is to establish the technical and scientific feasibility of developing the "Smokescreen(r) Translational Analysis Platform (TL)", a service that will predict an individual's nicotine metabolism from Smokescreen(r) Genotyping Array (GTA) data (with content focused for pharmacogenetic analysis) in individuals from multiple world populations. Germline variants in the CYP2A6 gene play a major role in nicotine metabolism activity and are difficult to genotype due to the region's complex alleles and sequence similarity with other genes. We will assess the genotyping and imputation accuracy of the Smokescreen(r) GTA for CYP2A6 variants, using samples from public genomic projects and from three laboratory studies of nicotine metabolism. This assessment will support the technical validity of using Smokescreen(r) GTA CYP2A6 genotypes in predictive models. We will then use existing Smokescreen(r) GTA genotype data from three laboratory studies of nicotine metabolism to compute CYP2A6 haplotypes and predict metabolism in individuals of African, Asian, and European ancestry; the results will be evaluated in relation to observed nicotine metabolism. In addition, we will define new nicotine metabolism pathway prediction models using the latest Bayesian variable selection methodologies that incorporate external functional, clinical, and pathway knowledge. These results will be packaged into prototype reports for the Smokescreen(r) TL service and presented to translational and clinical researchers for feedback. Accomplishments, opportunities and challenges will be summarized for the Smokescreen(r) TL service. Computable models of nicotine metabolism integrated into a unified genetic platform will provide opportunities for future validation in laboratory studies of diverse populations and can be used retrospectively or prospectively in clinical trials of smoking behaviors, including response to smoking cessation therapies. With additional research using clinical trials of smoking cessation therapies, this platform will ultimately provide model estimates and prognostic information for translational research and for use in smoking cessation therapy assignment.

Public Health Relevance Statement:


Public Health Relevance:
Quitting tobacco-smoking remains a challenge for a significant portion of the U.S. population. This project aims to create a service to help scientist identify factors related to how nicotine is processed in the body and use these factors to improve rates of quitting, reduce side effects, and assess risk of related diseases.

NIH Spending Category:
Bioengineering; Drug Abuse (NIDA only); Genetics; Human Genome; Prevention; Smoking and Health; Substance Abuse; Tobacco

Project Terms:
addiction; Adverse effects; African; Algorithms; Alleles; Asians; base; Benchmarking; Biological Markers; Clinical; Clinical Pathways; Clinical Treatment; Clinical Trials; Complex; Congresses; Copy Number Polymorphism; Custom; Data; Disease; DNA; Ensure; Ethnic Origin; European; Feedback; Future; Genes; Genetic; genetic profiling; Genetic Variation; genome-wide; Genomics; Genotype; Goals; Haplotypes; improved; Individual; Investments; Knowledge; knowledge base; Laboratory Study; Malignant neoplasm of lung; Measurement; Measures; Metabolism; Methodology; Modeling; mortality; National Institute of Drug Abuse; Nicotine; non-genetic; novel; Other Genetics; Pathway interactions; Patients; Pharmaceutical Preparations; Pharmacogenetics; Phase; Play; Population; Population Heterogeneity; predicting response; prediction algorithm; predictive modeling; Process; prognostic; prototype; public health relevance; Questionnaires; Reporting; Research; Research Personnel; response; Risk; Role; Sampling; Scientist; Services; Smoking Behavior; smoking cessation; smoking prevalence; Structure; Subgroup; Technology; Tobacco; tobacco control; Tobacco smoking; Translational Research; treatment response; Validation; Variant; Withholding Treatment

Tobacco-attributable disease remains the largest potentially modi?able cause of mortality. Strategies to reduce smoking prevalence include developing more effective smoking cessation treatments. Nicotine metabolism and dependence are predictors of smoking behaviors, including response to smoking cessation treatments. The goal of this Phase II project is to develop prediction models of nicotine metabolism, nicotine dependence and smoking cessation from clinical and genomic data. An optimized set of models will be implemented in the “Smokescreen®Translational (TL) Analysis Platform”, and applied to clinical cohorts of treatment-seeking smokers. We have previously designed Smokescreen®GTA, a genome-wide array that deeply captures variation in over 1,000 addiction genes, including the most important loci for nicotine metabolism and nicotine dependence. We have identi?ed multiple metabolic and regulatory genes, that with relatively few markers, can predict an individual's nicotine metabolic activity. We will use existing cohorts and a clinical treatment trial of smokers to discover and test integrated models with the goal of providing estimates of nicotine metabolism, nicotine dependence and cessation probability. These models will incorporate ancestry, clinical, genomic and social vari- ables to maximize prediction of smoking cessation. We will develop a compact laboratory assay for genotyping DNA samples with speci?c markers and software to analyze clinical and genomic data. Smokescreen®TL will be validated in smokers in clinical care. The results will be delivered in ?exible reporting formats. Ultimately, Smokescreen®TL will be available for use by health care providers interested in helping treatment seeking smokers quit.

Public Health Relevance Statement:
Project Narrative Quitting tobacco-smoking remains a challenge for a signi?cant portion of the U.S. population. This project will create a predictive test to personalize smoking cessation treatment.

NIH Spending Category:
Alcoholism, Alcohol Use and Health; Behavioral and Social Science; Brain Disorders; Cancer; Cancer Genomics; Genetics; Human Genome; Lung; Lung Cancer; Patient Safety; Precision Medicine; Prevention; Substance Abuse; Tobacco; Tobacco Smoke and Health; Women's Health

Project Terms:
addiction; African American; Biological Assay; Biological Markers; biosignature; Cancer Patient; cancer risk; Cardiovascular Diseases; cigarette smoking; Clinical; clinical care; Clinical Data; Clinical Treatment; Code; cohort; Cohort Studies; Communities; Computer software; Cotinine; CYP2A7 gene; Dependence; design; Development; Disease; DNA; Drug Kinetics; Enrollment; European; flexibility; Genes; Genetic Transcription; genome wide association study; genome-wide; genomic biomarker; genomic data; Genomic Segment; Genomics; Genotype; Glucuronides; Goals; health care service organization; Health Personnel; Healthcare; hydroxycotinine; Individual; interest; Japanese Population; Joints; Laboratories; Laboratory Study; Latino; Lung diseases; Malignant Neoplasms; Measures; Metabolic; Metabolic Diseases; Metabolism; Modeling; mortality; National Heart, Lung, and Blood Institute; National Institute of Drug Abuse; Native Hawaiian; Nicotine; nicotine cessation; Nicotine Dependence; novel; Outcome; Oxides; Participant; Pathway interactions; personalized medicine; Pharmacodynamics; Pharmacogenomics; Pharmacology; Phase; Population; predicting response; predictive modeling; predictive test; Probability; Randomized Clinical Trials; Regulator Genes; Reporting; response; Sample Size; Sampling; Scientific Advances and Accomplishments; Series; Smoker; smoking abstinence; Smoking Behavior; smoking cessation; Smoking Cessation Intervention; smoking prevalence; social; Statistical Models; statistics; Technology; Testing; therapy outcome; Tobacco; tobacco control; Tobacco smoking behavior; Tobacco use; Translating; treatment trial; United States National Institutes of Health; Variant