Multiethnic Prediction of Nicotine Biomarkers and Association With Nicotine Dependence

Deep sequencing of candidate genes identified 14 variants associated with smoking abstinence in an ethnically diverse sample

Despite the large public health toll of smoking, genetic studies of smoking cessation have been limited with few discoveries of risk or protective loci. We investigated common and rare variant associations with success in quitting smoking using a cohort from 8 randomized controlled trials involving 2231 participants and a total of 10,020 common and 24,147 rare variants. We identified 14 novel markers including 6 mapping to genes previously related to psychiatric and substance use disorders, 4 of which were protective (CYP2B6 (rs1175607105), HTR3B (rs1413172952; rs1204720503), rs80210037 on chr15), and 2 of which were associated with reduced cessation (PARP15 (rs2173763), SCL18A2 (rs363222)). The others mapped to areas associated with cancer including FOXP1 (rs1288980) and ZEB1 (rs7349). Network analysis identified significant canonical pathways for the serotonin receptor signaling pathway, nicotine and bupropion metabolism, and several related to tumor suppression. Two novel markers (rs6749438; rs6718083) on chr2 are flanked by genes associated with regulation of bodyweight. The identification of novel loci in this study can provide new targets of pharmacotherapy and inform efforts to develop personalized treatments based on genetic profiles.

Biochemical and genetic biomarkers associated with nicotine dependence in Mexican smokers

Cigarette smoking remains an important health concern and is still a leading cause of preventable mortality. Nicotine is the substance responsible for sustained tobacco use and dependence. Identification of biomarkers underlying nicotine dependence behavior is important to identify people at risk for this dependence. In the present study, we identified biochemical and genetic biomarkers of nicotine dependence detected by the Fagerström Test for Nicotine Dependence (FTDN) in Mexican smokers. The nicotine metabolites nicotine-N'-oxide, trans-3'-hydroxycotinine-glucuronide (3HC-O-Gluc), and nicotine-N-Gluc (Gluc) were useful to differentiate nicotine-dependent from non-dependent subjects (p < .0001) with an area under the curve (AUC) of 0.7818. Genetic variants in CYP2A6, FMO3, and UGT2B7 (rs2431413, rs28363545, and rs7439326, respectively) were associated with nicotine dependence (p = .03, p = .01, p = .01, respectively). Variations in the enzymatic activity of CYP2A6 were associated with altered nicotine-N'-oxide and 3HC-O-Gluc levels. Decreased urinary levels of 3HC-O-Gluc and increased nicotine-N'-oxide were associated with a decrease in the functional activity of CYP2A6. A strong positive correlation was observed between the ratio of urinary 3HC/cotinine, a measure of CYP2A6 activity, and the levels of 3HC-O-Gluc (p < .0001, r = .6835), while a strong negative correlation was observed with nicotine-N'-oxide (p < .0001, r = .6522) in nicotine-dependent subjects. No correlations were observed in non-nicotine-dependent subjects. These data suggest that particular urinary nicotine metabolites and genetic variants involved in nicotine metabolism are useful to identify subjects with nicotine dependence in the Mexican population.

Genomic medicine to reduce tobacco and related disorders: Translation to precision prevention and treatment

Genomic medicine can enhance prevention and treatment. First, we propose that advances in genomics have the potential to enhance assessment of disease risk, improve prognostic predictions, and guide treatment development and application. Clinical implementation of polygenic risk scores (PRSs) has emerged as an area of active research. The pathway from genomic discovery to implementation is an iterative process. Second, we provide examples on how genomic medicine has the potential to solve problems in prevention and treatment using two examples: Lung cancer screening and evidence-based tobacco treatment are both under-utilized and great opportunities for genomic interventions. Third, we discuss the translational process for developing genomic interventions from evidence to implementation by presenting a model to evaluate genomic evidence for clinical implementation, mechanisms of genomic interventions, and patient desire for genomic interventions. Fourth, we present potential challenges in genomic interventions including a great need for evidence in all diverse populations, little evidence on treatment algorithms, challenges in accommodating a dynamic evidence base, and implementation challenges in real world clinical settings. Finally, we conclude that research to identify genomic markers that are associated with smoking cessation success and the efficacy of smoking cessation treatments is needed to empower people of all diverse ancestry. Importantly, genomic data can be used to help identify patients with elevated risk for nicotine addiction, difficulty quitting smoking, favorable response to specific pharmacotherapy, and tobacco-related health problems.

The Use of Biomarkers to Guide Precision Treatment for Tobacco Use

This review summarizes the evidence to date on the development of biomarkers for personalizing the pharmacological treatment of combustible tobacco use. First, the latest evidence on FDA-approved medications is considered, demonstrating that, while these medications offer real benefits, they do not contribute to smoking cessation in approximately two-thirds of cases. Second, the case for using biomarkers to guide tobacco treatment is made based on the potential to increase medication effectiveness and uptake and reduce side effects. Next, the FDA framework of biomarker development is presented along with the state of science on biomarkers for tobacco treatment, including a review of the nicotine metabolite ratio, electroencephalographic event-related potentials, and other biomarkers utilized for risk feedback. We conclude with a discussion of the challenges and opportunities for the translation of biomarkers to guide tobacco treatment and propose priorities for future research.

Genetic variation in CSF2 (5q31.1) is associated with longitudinal susceptibility to pediatric malaria, severe malarial anemia, and all-cause mortality in a high-burden malaria and HIV region of Kenya

Plasmodium falciparum infections remain among the leading causes of morbidity and mortality in holoendemic transmission areas. Located within region 5q31.1, the colony-stimulating factor 2 gene (CSF2) encodes granulocyte–macrophage colony-stimulating factor (GM-CSF), a hematopoietic growth factor that mediates host immune responses. Since the effect of CSF2 variation on malaria pathogenesis remains unreported, we investigated the impact of two genetic variants in the 5q31.1 gene region flanking CSF2:g-7032 G > A (rs168681:G > A) and CSF2:g.64544T > C (rs246835:T > C) on the rate and timing of malaria and severe malarial anemia (SMA, Hb < 5.0 g/dL) episodes over 36 months of follow-up. Children (n = 1654, aged 2–70 months) were recruited from a holoendemic P. falciparum transmission area of western Kenya. Decreased incidence rate ratio (IRR) for malaria was conferred by inheritance of the CSF2:g.64544 TC genotype (P = 0.0277) and CSF2 AC/GC diplotype (P = 0.0015). Increased IRR for malaria was observed in carriers of the CSF2 AT/GC diplotype (P = 0.0237), while the inheritance of the CSF2 AT haplotype increased the IRR for SMA (P = 0.0166). A model estimating the longitudinal risk of malaria showed decreased hazard rates among CSF2 AC haplotype carriers (P = 0.0045). Investigation of all-cause mortality revealed that inheritance of the GA genotype at CSF2:g-7032 increased the risk of mortality (P = 0.0315). Higher risk of SMA and all-cause mortality were observed in younger children (P < 0.0001 and P = 0.0015), HIV-1(+) individuals (P < 0.0001 and P < 0.0001), and carriers of HbSS (P = 0.0342 and P = 0.0019). Results from this holoendemic P. falciparum area show that variation in gene region 5q31.1 influences susceptibility to malaria, SMA, and mortality, as does age, HIV-1 status, and inheritance of HbSS.