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The maintenance of normal body weight is disrupted in patients with anorexia nervosa (AN) for prolonged periods of time. Prior to the onset of AN, premorbid body mass index (BMI) spans the entire range from underweight to obese. After recovery, patients have reduced rates of overweight and obesity. As such, loci involved in body weight regulation may also be relevant for AN and vice versa. Our primary analysis comprised a cross-trait analysis of the 1000 single-nucleotide polymorphisms (SNPs) with the lowest P-values in a genome-wide association meta-analysis (GWAMA) of AN (GCAN) for evidence of association in the largest published GWAMA for BMI (GIANT). Subsequently we performed sex-stratified analyses for these 1000 SNPs. Functional ex vivo studies on four genes ensued. Lastly, a look-up of GWAMA-derived BMI-related loci was performed in the AN GWAMA. We detected significant associations (P-values

Individuals with anorexia nervosa (AN) restrict eating and become emaciated. They tend to have an aversion to foods rich in fat. Because epoxide hydrolase 2 (EPHX2) was identified as a novel AN susceptibility gene, and because its protein product, soluble epoxide hydrolase (sEH), converts bioactive epoxides of polyunsaturated fatty acid (PUFA) to the corresponding diols, lipidomic and metabolomic targets of EPHX2 were assessed to evaluate the biological functions of EPHX2 and their role in AN. Epoxide substrates of sEH and associated oxylipins were measured in ill AN, recovered AN and gender- and race-matched controls. PUFA and oxylipin markers were tested as potential biomarkers for AN. Oxylipin ratios were calculated as proxy markers of in vivo sEH activity. Several free- and total PUFAs were associated with AN diagnosis and with AN recovery. AN displayed elevated n-3 PUFAs and may differ from controls in PUFA elongation and desaturation processes. Cytochrome P450 pathway oxylipins from arachidonic acid, linoleic acid, alpha-linolenic acid and docosahexaenoic acid PUFAs are associated with AN diagnosis. The diol:epoxide ratios suggest the sEH activity is higher in AN compared with controls. Multivariate analysis illustrates normalization of lipidomic profiles in recovered ANs. EPHX2 influences AN risk through in vivo interaction with dietary PUFAs. PUFA composition and concentrations as well as sEH activity may contribute to the pathogenesis and prognosis of AN. Our data support the involvement of EPHX2-associated lipidomic and oxylipin dysregulations in AN, and reveal their potential as biomarkers to assess responsiveness to future intervention or treatment.

Anorexia nervosa (AN) and related eating disorders are complex, multifactorial neuropsychiatric conditions with likely rare and common genetic and environmental determinants. To identify genetic variants associated with AN, we pursued a series of sequencing and genotyping studies focusing on the coding regions and upstream sequence of 152 candidate genes in a total of 1205 AN cases and 1948 controls. We identified individual variant associations in the Estrogen Receptor-ß (ESR2) gene, as well as a set of rare and common variants in the Epoxide Hydrolase 2 (EPHX2) gene, in an initial sequencing study of 261 early-onset severe AN cases and 73 controls (P=0.0004). The association of EPHX2 variants was further delineated in: (1) a pooling-based replication study involving an additional 500 AN patients and 500 controls (replication set P=0.00000016); (2) single-locus studies in a cohort of 386 previously genotyped broadly defined AN cases and 295 female population controls from the Bogalusa Heart Study (BHS) and a cohort of 58 individuals with self-reported eating disturbances and 851 controls (combined smallest single locus P

We conducted gender-stratified analyses on a systems-based candidate gene study of 53 regions involved in nicotinic response and the brain-reward pathway in two randomized clinical trials of smoking cessation treatments (placebo, bupropion, transdermal and

The identification and exploration of genetic loci that influence smoking behaviors have been conducted primarily in populations of the European ancestry. Here we report results of the first genome-wide association study meta-analysis of smoking behavior in African Americans in the Study of Tobacco in Minority Populations Genetics Consortium (n = 32,389). We identified one non-coding single-nucleotide polymorphism (SNP; rs2036527[A]) on chromosome 15q25.1 associated with smoking quantity (cigarettes per day), which exceeded genome-wide significance (β = 0.040, s.e. = 0.007, P = 1.84 × 10(-8)). This variant is present in the 5'-distal enhancer region of the CHRNA5 gene and defines the primary index signal reported in studies of the European ancestry. No other SNP reached genome-wide significance for smoking initiation (SI, ever vs never smoking), age of SI, or smoking cessation (SC, former vs current smoking). Informative associations that approached genome-wide significance included three modestly correlated variants, at 15q25.1 within PSMA4, CHRNA5 and CHRNA3 for smoking quantity, which are associated with a second signal previously reported in studies in European ancestry populations, and a signal represented by three SNPs in the SPOCK2 gene on chr10q22.1. The association at 15q25.1 confirms this region as an important susceptibility locus for smoking quantity in men and women of African ancestry. Larger studies will be needed to validate the suggestive loci that did not reach genome-wide significance and further elucidate the contribution of genetic variation to disparities in cigarette consumption, SC and smoking-attributable disease between African Americans and European Americans.

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., (© 2024. The Author(s).)

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.

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury 1-4 . These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries 5 . Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction., (© 2022. The Author(s).)

Background: There is a need to match characteristics of tobacco users with cessation treatments and risks of tobacco attributable diseases such as lung cancer. The rate in which the body metabolizes nicotine has proven an important predictor of these outcomes. Nicotine metabolism is primarily catalyzed by the enzyme cytochrone P450 (CYP2A6) and CYP2A6 activity can be measured as the ratio of two nicotine metabolites: trans-3'-hydroxycotinine to cotinine (NMR). Measurements of these metabolites are only possible in current tobacco users and vary by biofluid source, timing of collection, and protocols; unfortunately, this has limited their use in clinical practice. The NMR depends highly on genetic variation near CYP2A6 on chromosome 19 as well as ancestry, environmental, and other genetic factors. Thus, we aimed to develop prediction models of nicotine metabolism using genotypes and basic individual characteristics (age, gender, height, and weight)., Results: We identified four multiethnic studies with nicotine metabolites and DNA samples. We constructed a 263 marker panel from filtering genome-wide association scans of the NMR in each study. We then applied seven machine learning techniques to train models of nicotine metabolism on the largest and most ancestrally diverse dataset (N=2239). The models were then validated using the other three studies (total N=1415). Using cross-validation, we found the correlations between the observed and predicted NMR ranged from 0.69 to 0.97 depending on the model. When predictions were averaged in an ensemble model, the correlation was 0.81. The ensemble model generalizes well in the validation studies across ancestries, despite differences in the measurements of NMR between studies, with correlations of: 0.52 for African ancestry, 0.61 for Asian ancestry, and 0.46 for European ancestry. The most influential predictors of NMR identified in more than two models were rs56113850, rs11878604, and 21 other genetic variants near CYP2A6 as well as age and ancestry., Conclusions: We have developed an ensemble of seven models for predicting the NMR across ancestries from genotypes and age, gender and BMI. These models were validated using three datasets and associate with nicotine dosages. The knowledge of how an individual metabolizes nicotine could be used to help select the optimal path to reducing or quitting tobacco use, as well as, evaluating risks of tobacco use., (© 2022. The Author(s).)

Introduction: Limited evidence for incident frailty risks associated with prescription analgesics and sedatives in older (≥ 65 years) community-living adults prompted a more comprehensive investigation., Methods: We used data from older Health and Retirement Study respondents and three frailty models (frailty index, functional domain, frailty phenotype with 8803, 10,470, and 6850 non-frail individuals, respectively) and estimated sub-hazard ratios of regular prescription drug use (co-use, analgesic use, and sedative use), by frailty model. We addressed confounding with covariate adjustment and propensity score matching approaches., Results: The baseline prevalence of analgesic and sedative co-use, analgesic use, and sedative use among non-frail respondents was 1.8%, 12.8%, and 4.7% for the frailty index model, 4.2%, 16.2%, and 5.3% for the functional domain model, and 4.3%, 15.4%, and 6.1% for the frailty phenotype model, respectively. Cumulative frailty incidence over 10 years was 39.3%, 36.1%, and 14.2% for frailty index, functional domain, and frailty phenotype models, respectively; covariate-adjusted sub-hazard ratio estimates were 2.00 (1.63-2.45), 1.83 (1.57-2.13), and 1.68 (1.21-2.33) for co-use; 1.72 (1.56-1.89), 1.38 (1.27-1.51), and 1.51 (1.27-1.79) for analgesic use; and 1.46 (1.24-1.72), 1.25 (1.07-1.46), and 1.31 (0.97-1.76) for sedative use. Frailty risk ranking (co-use > analgesic use > sedative use) persisted across all model sensitivity analyses., Discussion: Consistently significant frailty risk estimates of regular prescription analgesic and sedative co-use and of prescription analgesic use support existing clinical, public health, and regulatory guidance on opioid and benzodiazepine co-prescription, on opioid prescription, and on NSAID prescription. Frailty phenotype measurement administration limited power to detect significant frailty risks. Research into specific pharmaceutical exposures and comparison of results across cohorts will be required to contribute to the deprescribing evidence base., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The opioid crisis in the United States poses a major threat to public health due to psychiatric and infectious disease comorbidities and death due to opioid use disorder (OUD). OUD is characterized by patterns of opioid misuse leading to persistent heavy use and overdose. The standard of care for treatment of OUD is medication-assisted treatment, in combination with behavioral therapy. Medications for opioid use disorder have been shown to improve OUD outcomes, including reduction and prevention of overdose. However, understanding the effectiveness of such medications has been limited due to non-adherence to assigned dose levels by study patients. To overcome this challenge, herein we develop a model that views dose history as a time-varying covariate. Proceeding in this fashion allows the model to estimate dose effect while accounting for lapses in adherence. The proposed model is used to conduct a secondary analysis of data collected from six efficacy and safety trials of buprenorphine maintenance treatment. This analysis provides further insight into the time-dependent treatment effects of buprenorphine and how different dose adherence patterns relate to risk of opioid use.

The impact of agonist dose and of physician, staff and patient engagement on treatment have not been evaluated together in an analysis of treatment for opioid use disorder. Our hypotheses were that greater agonist dose and therapeutic engagement would be associated with reduced illicit opiate use in a time-dependent manner. Publicly-available treatment data from six buprenorphine efficacy and safety trials from the Federally-supported Clinical Trials Network were used to derive treatment variables. Three novel predictors were constructed to capture the time weighted effects of buprenorphine dosage (mg buprenorphine per day), dosing protocol (whether physician could adjust dose), and clinic visits (whether patient attended clinic). We used time-in-trial as a predictor to account for the therapeutic benefits of treatment persistence. The outcome was illicit opiate use defined by self-report or urinalysis. Trial participants (N = 3022 patients with opioid dependence, mean age 36 years, 33% female, 14% Black, 16% Hispanic) were analyzed using a generalized linear mixed model. Treatment variables dose, Odds Ratio (OR) = 0.63 (95% Confidence Interval (95%CI) 0.59−0.67), dosing protocol, OR = 0.70 (95%CI 0.65−0.76), time-in-trial, OR = 0.75 (95%CI 0.71−0.80) and clinic visits, OR = 0.81 (95%CI 0.76−0.87) were significant (p-values < 0.001) protective factors. Treatment implications support higher doses of buprenorphine and greater engagement of patients with providers and clinic staff.

Background: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders., Methods: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors., Results: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged., Conclusions: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders., (Copyright © 2021 Society of Biological Psychiatry. All rights reserved.)

This review has been withdrawn because it has been found to be in breach of the Cochrane Commercial Sponsorship policy clause 2:  'Individuals who are currently employed or where employed any time in the last three years by a company that has a real or potential financial interest in the outcome of the review (including but not limited to drug companies or medical device manufacturers); or who hold or have applied for a patent related to the review are prohibited from being Cochrane Review authors. In most cases, current or previous employment would be characterized by the affiliation statement made by the author at the title registration, protocol, or review stage of the review'., (Copyright © 2021 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.)

Introduction: The nicotine metabolite ratio and nicotine equivalents are measures of metabolism rate and intake. Genome-wide prediction of these nicotine biomarkers in multiethnic samples will enable tobacco-related biomarker, behavioral, and exposure research in studies without measured biomarkers., Aims and Methods: We screened genetic variants genome-wide using marginal scans and applied statistical learning algorithms on top-ranked genetic variants, age, ethnicity and sex, and, in additional modeling, cigarettes per day (CPD), (in additional modeling) to build prediction models for the urinary nicotine metabolite ratio (uNMR) and creatinine-standardized total nicotine equivalents (TNE) in 2239 current cigarette smokers in five ethnic groups. We predicted these nicotine biomarkers using model ensembles and evaluated external validity using dependence measures in 1864 treatment-seeking smokers in two ethnic groups., Results: The genomic regions with the most selected and included variants for measured biomarkers were chr19q13.2 (uNMR, without and with CPD) and chr15q25.1 and chr10q25.3 (TNE, without and with CPD). We observed ensemble correlations between measured and predicted biomarker values for the uNMR and TNE without (with CPD) of 0.67 (0.68) and 0.65 (0.72) in the training sample. We observed inconsistency in penalized regression models of TNE (with CPD) with fewer variants at chr15q25.1 selected and included. In treatment-seeking smokers, predicted uNMR (without CPD) was significantly associated with CPD and predicted TNE (without CPD) with CPD, time-to-first-cigarette, and Fagerström total score., Conclusions: Nicotine metabolites, genome-wide data, and statistical learning approaches developed novel robust predictive models for urinary nicotine biomarkers in multiple ethnic groups. Predicted biomarker associations helped define genetically influenced components of nicotine dependence., Implications: We demonstrate development of robust models and multiethnic prediction of the uNMR and TNE using statistical and machine learning approaches. Variants included in trained models for nicotine biomarkers include top-ranked variants in multiethnic genome-wide studies of smoking behavior, nicotine metabolites, and related disease. Association of the two predicted nicotine biomarkers with Fagerström Test for Nicotine Dependence items supports models of nicotine biomarkers as predictors of physical dependence and nicotine exposure. Predicted nicotine biomarkers may facilitate tobacco-related disease and treatment research in samples with genomic data and limited nicotine metabolite or tobacco exposure data., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.)

Background: Genetics and biology may influence the age of onset of anorexia nervosa (AN). The aims of this study were to determine whether common genetic variation contributes to age of onset of AN and to investigate the genetic associations between age of onset of AN and age at menarche., Methods: A secondary analysis of the Psychiatric Genomics Consortium genome-wide association study (GWAS) of AN was performed, which included 9335 cases and 31,981 screened controls, all from European ancestries. We conducted GWASs of age of onset, early-onset AN (<13 years), and typical-onset AN, and genetic correlation, genetic risk score, and Mendelian randomization analyses., Results: Two loci were genome-wide significant in the typical-onset AN GWAS. Heritability estimates (single nucleotide polymorphism- h 2 ) were 0.01-0.04 for age of onset, 0.16-0.25 for early-onset AN, and 0.17-0.25 for typical-onset AN. Early- and typical-onset AN showed distinct genetic correlation patterns with putative risk factors for AN. Specifically, early-onset AN was significantly genetically correlated with younger age at menarche, and typical-onset AN was significantly negatively genetically correlated with anthropometric traits. Genetic risk scores for age of onset and early-onset AN estimated from independent GWASs significantly predicted age of onset. Mendelian randomization analysis suggested a causal link between younger age at menarche and early-onset AN., Conclusions: Our results provide evidence consistent with a common variant genetic basis for age of onset and implicate biological pathways regulating menarche and reproduction., (© 2021 The Authors.)

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [r g ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (r g = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (r g = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (r g = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (r gs = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors., (© 2020 Society for the Study of Addiction.)

The Transatlantic Slave Trade transported more than 9 million Africans to the Americas between the early 16th and the mid-19th centuries. We performed a genome-wide analysis using 6,267 individuals from 25 populations to infer how different African groups contributed to North-, South-American, and Caribbean populations, in the context of geographic and geopolitical factors, and compared genetic data with demographic history records of the Transatlantic Slave Trade. We observed that West-Central Africa and Western Africa-associated ancestry clusters are more prevalent in northern latitudes of the Americas, whereas the South/East Africa-associated ancestry cluster is more prevalent in southern latitudes of the Americas. This pattern results from geographic and geopolitical factors leading to population differentiation. However, there is a substantial decrease in the between-population differentiation of the African gene pool within the Americas, when compared with the regions of origin from Africa, underscoring the importance of historical factors favoring admixture between individuals with different African origins in the New World. This between-population homogenization in the Americas is consistent with the excess of West-Central Africa ancestry (the most prevalent in the Americas) in the United States and Southeast-Brazil, with respect to historical-demography expectations. We also inferred that in most of the Americas, intercontinental admixture intensification occurred between 1750 and 1850, which correlates strongly with the peak of arrivals from Africa. This study contributes with a population genetics perspective to the ongoing social, cultural, and political debate regarding ancestry, admixture, and the mestizaje process in the Americas., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objectives: We aimed to estimate incident frailty risks of prescription drugs for pain and for sleep in older US adults., Design: Longitudinal cohort., Setting: Health and Retirement Study., Participants: Community-living respondents aged 65 years and older, excluding individuals who received recent treatment for cancer (N = 14 208). Our longitudinal analysis sample included respondents who were not frail at baseline and had at least one follow-up wave with complete information on both prescription drug use and frailty, or date of death (N = 7201)., Measurements: Prescription drug use for pain and sleep, sociodemographics, other drug and substance use, and Burden frailty model components. Multivariable drug use stratified hazard models with death as a competing risk evaluated frailty risks associated with co-use and single use of prescription drugs for pain and for sleep., Results: Proportions endorsing prescription drug use were 22.1% for pain only, 6.8% for sleep only, and 7.7% for both indications. Burden frailty model prevalence was 41.0% and varied significantly by drug use. Among non-frail individuals at baseline, proportions endorsing prescription drug use were 14.9%, 5.6%, and 2.2% for the three indications. Prescription drug use was associated with increased risk of frailty (co-use adjusted subhazard ratio [sHR] = 1.95; 95% confidence interval [CI] = 1.6-2.4; pain only adjusted sHR = 1.58; CI = 1.4-1.8; sleep-only adjusted sHR = 1.35; CI = 1.1-1.6; no use = reference group). Cumulative incidence of frailty over 8 years for the four groups was 60.6%, 50.9%, 45.8%, and 34.1%. Sensitivity analyses controlling for chronic diseases associated with persistent pain resulted in minor risk reductions., Conclusion: Prescription pain and sleep drug use is significantly associated with increased incidence of frailty. Research to estimate effects of pain and sleep indications and of drug class-specific dosage and duration on incident frailty is indicated before advocating deprescribing based on these findings. J Am Geriatr Soc 67:2474-2481, 2019., (© 2019 The American Geriatrics Society.)

Introduction: Pharmacogenomic studies have used genetic variants to identify smokers likely to respond to pharmacological treatments for smoking cessation., Methods: We performed a systematic review and meta-analysis of primary and secondary analyses of trials of smoking cessation pharmacotherapies. Eligible were trials with data on a priori selected single nucleotide polymorphisms, replicated non-single nucleotide polymorphisms, and/or the nicotine metabolite ratio. We estimated the genotype × treatment interaction as the ratio of risk ratios (RRR) for treatment effects across genotype groups., Results: We identified 18 trials (N = 9017 participants), including 40 active (bupropion, nicotine replacement therapy [NRT], varenicline, or combination therapies) versus placebo comparisons and 16 active versus active comparisons. There was statistical evidence of heterogeneity across rs16969968 genotypes in CHRNA5 with regard to both 6-month abstinence and end-of-treatment abstinence in non-Hispanic black smokers and end-of-treatment abstinence in non-Hispanic white smokers. There was also heterogeneity across rs1051730 genotypes in CHRNA3 with regard to end-of-treatment abstinence in non-Hispanic white smokers. There was no clear statistical evidence for other genotype-by-treatment combinations. Compared with placebo, NRT was more effective among non-Hispanic black smokers with rs16969968-GG with regard to both 6-month abstinence (RRR for GG vs. GA or AA, 3.51; 95% confidence interval [CI] = 1.19 to 10.30) and end-of-treatment abstinence (RRR for GG vs. GA or AA, 5.84; 95% CI = 1.89 to 18.10). Among non-Hispanic white smokers, NRT effectiveness relative to placebo was comparable across rs1051730 and rs169969960 genotypes., Conclusions: We did not identify widespread differential effects of smoking cessation pharmacotherapies based on genotype. The quality of the evidence is generally moderate., Implications: Although we identified some evidence of genotype × treatment interactions, the vast majority of analyses did not provide evidence of differential treatment response by genotype. Where we find some evidence, these results should be considered preliminary and interpreted with caution because of the small number of contributing trials per genotype comparison, the wide confidence intervals, and the moderate quality of evidence. Prospective trials and individual-patient data meta-analyses accounting for heterogeneity of treatment effects through modeling are needed to assess the clinical utility of genetically informed biomarkers to guide pharmacotherapy choice for smoking cessation., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Populations in sub-Saharan Africa have historically been exposed to intense selection from chronic infection with falciparum malaria. Interestingly, populations with the highest malaria intensity can be identified by the increased occurrence of endemic Burkitt Lymphoma (eBL), a pediatric cancer that affects populations with intense malaria exposure, in the so called "eBL belt" in sub-Saharan Africa. However, the effects of intense malaria exposure and sub-Saharan populations' genetic histories remain poorly explored. To determine if historical migrations and intense malaria exposure have shaped the genetic composition of the eBL belt populations, we genotyped ~4.3 million SNPs in 1,708 individuals from Ghana and Northern Uganda, located on opposite sides of eBL belt and with ≥ 7 months/year of intense malaria exposure and published evidence of high incidence of BL. Among 35 Ghanaian tribes, we showed a predominantly West-Central African ancestry and genomic footprints of gene flow from Gambian and East African populations. In Uganda, the North West population showed a predominantly Nilotic ancestry, and the North Central population was a mixture of Nilotic and Southern Bantu ancestry, while the Southwest Ugandan population showed a predominant Southern Bantu ancestry. Our results support the hypothesis of diverse ancestral origins of the Ugandan, Kenyan and Tanzanian Great Lakes African populations, reflecting a confluence of Nilotic, Cushitic and Bantu migrations in the last 3000 years. Natural selection analyses suggest, for the first time, a strong positive selection signal in the ATP2B4 gene (rs10900588) in Northern Ugandan populations. These findings provide important baseline genomic data to facilitate disease association studies, including of eBL, in eBL belt populations., Competing Interests: The authors have declared that no competing interests exist.

Objective: This study examined a hypothesized pathway by which interoceptive dysfunction accounted for associations between personality features (harm avoidance, self-directedness, and perfectionism) and anorexia nervosa (AN) severity (indicated by drive for thinness, eating disorder-related preoccupations and rituals, and body mass index)., Method: The study sample (n = 270, mean age = 28.47, 95.2% female, 98% White/Caucasian) consisted of probands and biological relatives who met DSM-IV criteria for lifetime diagnoses of AN (omitting criterion D, amenorrhea) drawn from the Price Foundation Anorexia Nervosa Affected Relative Pairs Study (AN-ARP). Participants completed measures assessing personality, interoceptive dysfunction, and eating pathology., Results: Associations between personality features of low self-directedness and high perfectionism and indicators of AN severity (drive for thinness and eating disorder-related preoccupations and rituals) were significant, as were the hypothesized indirect pathways through interoceptive dysfunction. Neither harm avoidance nor body mass index was significantly related to other study variables, and the proposed indirect pathways involving these variables were not significant., Discussion: Findings suggest that certain personality features may relate to AN severity, in part, through their associations with interoceptive dysfunction. Future research should examine prospective associations and the value of interventions targeting interoceptive dysfunction for interrupting the link between personality and AN severity., (© 2019 Wiley Periodicals, Inc.)

Introduction: Genome-wide association studies consistently show that single nucleotide polymorphisms (SNPs) in the complement receptor 1 (CR1) gene modestly but significantly alter Alzheimer's disease (AD) risk. Follow-up research has assumed that CR1 is expressed in the human brain despite a paucity of evidence for its function there. Alternatively, erythrocytes contain >80% of the body's CR1, where, in primates, it is known to bind circulating pathogens., Methods: Multidisciplinary methods were employed., Results: Conventional Western blots and quantitative polymerase chain reaction failed to detect CR1 in the human brain. Brain immunohistochemistry revealed only vascular CR1. By contrast, erythrocyte CR1 immunoreactivity was readily observed and was significantly deficient in AD, as was CR1-mediated erythrocyte capture of circulating amyloid β peptide. CR1 SNPs associated with decreased erythrocyte CR1 increased AD risk, whereas a CR1 SNP associated with increased erythrocyte CR1 decreased AD risk., Discussion: SNP effects on erythrocyte CR1 likely underlie the association of CR1 polymorphisms with AD risk., (Copyright © 2018 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)

Background: Genetic factors contribute to anorexia nervosa (AN); and the first genome-wide significant locus has been identified. We describe methods and procedures for the Anorexia Nervosa Genetics Initiative (ANGI), an international collaboration designed to rapidly recruit 13,000 individuals with AN and ancestrally matched controls. We present sample characteristics and the utility of an online eating disorder diagnostic questionnaire suitable for large-scale genetic and population research., Methods: ANGI recruited from the United States (US), Australia/New Zealand (ANZ), Sweden (SE), and Denmark (DK). Recruitment was via national registers (SE, DK); treatment centers (US, ANZ, SE, DK); and social and traditional media (US, ANZ, SE). All cases had a lifetime AN diagnosis based on DSM-IV or ICD-10 criteria (excluding amenorrhea). Recruited controls had no lifetime history of disordered eating behaviors. To assess the positive and negative predictive validity of the online eating disorder questionnaire (ED100K-v1), 109 women also completed the Structured Clinical Interview for DSM-IV (SCID), Module H., Results: Blood samples and clinical information were collected from 13,363 individuals with lifetime AN and from controls. Online diagnostic phenotyping was effective and efficient; the validity of the questionnaire was acceptable., Conclusions: Our multi-pronged recruitment approach was highly effective for rapid recruitment and can be used as a model for efforts by other groups. High online presence of individuals with AN rendered the Internet/social media a remarkably effective recruitment tool in some countries. ANGI has substantially augmented Psychiatric Genomics Consortium AN sample collection. ANGI is a registered clinical trial: clinicaltrials.govNCT01916538; https://clinicaltrials.gov/ct2/show/NCT01916538?cond=Anorexia+Nervosa&draw=1&rank=3., (Copyright © 2018. Published by Elsevier Inc.)

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology., (Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Implications: This article outlines a framework for the consistent integration of biological data/samples into smoking cessation pharmacotherapy trials, aligned with the objectives of the recently unveiled Precision Medicine Initiative. Our goal is to encourage and provide support for treatment researchers to consider biosample collection and genotyping their existing samples as well as integrating genetic analyses into their study design in order to realize precision medicine in treatment of nicotine dependence.

Introduction: Human genetic research has succeeded in definitively identifying multiple genetic variants associated with risk for nicotine dependence and heavy smoking. To build on these advances, and to aid in reducing the prevalence of smoking and its consequent health harms, the next frontier is to identify genetic predictors of successful smoking cessation and also of the efficacy of smoking cessation treatments ("pharmacogenomics"). More broadly, additional biomarkers that can be quantified from biosamples also promise to aid "Precision Medicine" and the personalization of treatment, both pharmacological and behavioral., Aims and Methods: To motivate ongoing and future efforts, here we review several compelling genetic and biomarker findings related to smoking cessation and treatment., Results: These Key results involve genetic variants in the nicotinic receptor subunit gene CHRNA5, variants in the nicotine metabolism gene CYP2A6, and the nicotine metabolite ratio. We also summarize reports of epigenetic changes related to smoking behavior., Conclusions: The results to date demonstrate the value and utility of data generated from biosamples in clinical treatment trial settings. This article cross-references a companion paper in this issue that provides practical guidance on how to incorporate biosample collection into a planned clinical trial and discusses avenues for harmonizing data and fostering consortium-based, collaborative research on the pharmacogenomics of smoking cessation., Implications: Evidence is emerging that certain genotypes and biomarkers are associated with smoking cessation success and efficacy of smoking cessation treatments. We review key findings that open potential avenues for personalizing smoking cessation treatment according to an individual's genetic or metabolic profile. These results provide important incentive for smoking cessation researchers to collect biosamples and perform genotyping in research studies and clinical trials.

There are limited biomarkers for substance use disorders (SUDs). Traditional statistical approaches are identifying simple biomarkers in large samples, but clinical use cases are still being established. High-throughput clinical, imaging, and 'omic' technologies are generating data from SUD studies and may lead to more sophisticated and clinically useful models. However, analytic strategies suited for high-dimensional data are not regularly used. We review strategies for identifying biomarkers and biosignatures from high-dimensional data types. Focusing on penalized regression and Bayesian approaches, we address how to leverage evidence from existing studies and knowledge bases, using nicotine metabolism as an example. We posit that big data and machine learning approaches will considerably advance SUD biomarker discovery. However, translation to clinical practice, will require integrated scientific efforts., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Background: Plasmodium falciparum (Pf) malaria infection is suspected to cause endemic Burkitt Lymphoma (eBL), but the evidence remains unsettled. An inverse relationship between sickle cell trait (SCT) and eBL, which supports that between malaria and eBL, has been reported before, but in small studies with low power. We investigated this hypothesis in children in a population-based study in northern Uganda using Mendelian Randomization., Methods: Malaria-related polymorphisms (SCT, IL10, IL1A, CD36, SEMA3C, and IFNAR1) were genotyped in 202 eBL cases and 624 controls enrolled during 2010-2015. We modeled associations between genotypes and eBL or malaria using logistic regression., Findings: SCT was associated with decreased risk of eBL (adjusted odds ratio [OR] 0·37, 95% CI 0·21-0·66; p=0·0003). Decreased risk of eBL was associated with IL10 rs1800896-CT (OR 0·73, 95% CI 0·50-1·07) and -CC genotypes (OR 0·53, 95% CI 0·29-0·95, p trend =0·019); IL1A rs2856838-AG (OR 0·56, 95% CI 0·39-0·81) and -AA genotype (OR 0·50, 95% CI 0·28-1·01, p trend =0·0016); and SEMA3C rs4461841-CT or -CC genotypes (OR 0·57, 95% CI 0·35-0·93, p=0·0193). SCT and IL10 rs1800896, IL1A rs2856838, but not SEMA3C rs4461841, polymorphisms were associated with decreased risk of malaria in the controls., Interpretation: Our results support a causal effect of malaria infection on eBL., (Published by Elsevier B.V.)

Background: Smoking cessation therapies are not effective for all smokers, and researchers are interested in identifying those subgroups of individuals (e.g. based on genotype) who respond best to specific treatments., Objectives: To assess whether quit rates vary by genetically informed biomarkers within pharmacotherapy treatment arms and as compared with placebo. To assess the effects of pharmacotherapies for smoking cessation in subgroups of smokers defined by genotype for identified genome-wide significant polymorphisms., Search Methods: We searched the Cochrane Tobacco Addiction Group specialised register, clinical trial registries, and genetics databases for trials of pharmacotherapies for smoking cessation from inception until 16 August 2016., Selection Criteria: We included randomised controlled trials (RCTs) that recruited adult smokers and reported pharmacogenomic analyses from trials of smoking cessation pharmacotherapies versus controls. Eligible trials included those with data on a priori genome-wide significant (P < 5 × 10 -8 ) single-nucleotide polymorphisms (SNPs), replicated non-SNPs, and/or the nicotine metabolite ratio (NMR), hereafter collectively described as biomarkers., Data Collection and Analysis: We used standard methodological procedures expected by Cochrane. The primary outcome was smoking abstinence at six months after treatment. The secondary outcome was abstinence at end of treatment (EOT). We conducted two types of meta-analyses- one in which we assessed smoking cessation of active treatment versus placebo within genotype groups, and another in which we compared smoking cessation across genotype groups within treatment arms. We carried out analyses separately in non-Hispanic whites (NHWs) and non-Hispanic blacks (NHBs). We assessed heterogeneity between genotype groups using T², I², and Cochrane Q statistics., Main Results: Analyses included 18 trials including 9017 participants, of whom 6924 were NHW and 2093 NHB participants. Data were available for the following biomarkers: nine SNPs (rs1051730 (CHRNA3); rs16969968, rs588765, and rs2036527 (CHRNA5); rs3733829 and rs7937 (in EGLN2, near CYP2A6); rs1329650 and rs1028936 (LOC100188947); and rs215605 (PDE1C)), two variable number tandem repeats (VNTRs; DRD4 and SLC6A4), and the NMR. Included data produced a total of 40 active versus placebo comparisons, 16 active versus active comparisons, and 64 between-genotype comparisons within treatment arms.For those meta-analyses showing statistically significant heterogeneity between genotype groups, we found the quality of evidence (GRADE) to be generally moderate. We downgraded quality most often because of imprecision or risk of bias due to potential selection bias in genotyping trial participants. Comparisons of relative treatment effects by genotypeFor six-month abstinence, we found statistically significant heterogeneity between genotypes (rs16969968) for nicotine replacement therapy (NRT) versus placebo at six months for NHB participants (P = 0.03; n = 2 trials), but not for other biomarkers or treatment comparisons. Six-month abstinence was increased in the active NRT group as compared to placebo among participants with a GG genotype (risk ratio (RR) 1.47, 95% confidence interval (CI) 1.07 to 2.03), but not in the combined group of participants with a GA or AA genotype (RR 0.43, 95% CI 0.15 to 1.26; ratio of risk ratios (RRR) GG vs GA or AA of 3.51, 95% CI 1.19 to 10.3). Comparisons of treatment effects between genotype groups within pharmacotherapy randomisation armsFor those receiving active NRT, treatment was more effective in achieving six-month abstinence among individuals with a slow NMR than among those with a normal NMR among NHW and NHB combined participants (normal NMR vs slow NMR: RR 0.54, 95% CI 0.37 to 0.78; n = 2 trials). We found no such differences in treatment effects between genotypes at six months for any of the other biomarkers among individuals who received pharmacotherapy or placebo., Authors' Conclusions: We did not identify widespread differential treatment effects of pharmacotherapy based on genotype. Some genotype groups within certain ethnic groups may benefit more from NRT or may benefit less from the combination of bupropion with NRT. The reader should interpret these results with caution because none of the statistically significant meta-analyses included more than two trials per genotype comparison, many confidence intervals were wide, and the quality of this evidence (GRADE) was generally moderate. Although we found evidence of superior NRT efficacy for NMR slow versus normal metabolisers, because of the lack of heterogeneity between NMR groups, we cannot conclude that NRT is more effective for slow metabolisers. Access to additional data from multiple trials is needed, particularly for comparisons of different pharmacotherapies.

Background: Falciparum malaria is an important risk factor for African Burkitt lymphoma (BL), but few studies have evaluated malaria patterns in healthy BL-age children in populations where both diseases are endemic. To obtain accurate current data, patterns of asymptomatic malaria were investigated in northern Uganda, where BL is endemic., Methods: Between 2011 and 2015, 1150 apparently healthy children under 15 years old were sampled from 100 villages in northern Uganda using a stratified, multi-stage, cluster survey design. Falciparum malaria prevalence (pfPR) was assessed by questionnaire, rapid diagnostic test (RDT) and thick film microscopy (TFM). Weighted pfPR and unadjusted and adjusted associations of prevalence with covariates were calculated using logistic models and survey methods., Results: Based on 1143 children successfully tested, weighted pfPR was 54.8% by RDT and 43.4% by TFM. RDT sensitivity and specificity were 97.5 and 77.8%, respectively, as compared to TFM, because RDT detect malaria antigens, which persist in peripheral blood after clinical malaria, thus results based on RDT are reported. Weighted pfPR increased from 40% in children aged under 2 years to 61.8% in children aged 6-8 years (odds ratio 2.42, 95% confidence interval (CI) 1.26-4.65), then fell slightly to 49% in those aged 12-15 years. Geometric mean parasite density was 1805.5 parasites/µL (95% CI 1344.6-2424.3) among TFM-positive participants, and it was higher in children aged <5 years at 5092.9/µL (95% CI 2892.7-8966.8) and lower in those aged ≥10 years at 983.8/µL (95% CI 472.7-2047.4; P = 0.001). Weighted pfPR was lower in children residing in sub-regions employing indoor residual spraying (IRS) than in those residing in non-IRS sub-regions (32.8 versus 65.7%; OR 0.26, 95% CI 0.14, 0.46). However, pfPR varied both within IRS (3.2-55.3%) and non-IRS sub-regions (29.8-75.8%; Pheterogeneity <0.001). pfPR was inversely correlated with a child's mother's income (P = 0.011) and positively correlated with being enrolled in the wet season (P = 0.076), but sex was irrelevant., Conclusions: The study observed high but geographically and demographically heterogenous patterns of asymptomatic malaria prevalence among children living in northern Uganda. These results provide important baseline data that will enable precise evaluation of associations between malaria and BL.

Introduction: Metabolic enzyme variation and other patient and environmental characteristics influence smoking behaviors, treatment success, and risk of related disease. Population-specific variation in metabolic genes contributes to challenges in developing and optimizing pharmacogenetic interventions. We applied a custom genome-wide genotyping array for addiction research (Smokescreen), to three laboratory-based studies of nicotine metabolism with oral or venous administration of labeled nicotine and cotinine, to model nicotine metabolism in multiple populations. The trans-3'-hydroxycotinine/cotinine ratio, the nicotine metabolite ratio (NMR), was the nicotine metabolism measure analyzed., Methods: Three hundred twelve individuals of self-identified European, African, and Asian American ancestry were genotyped and included in ancestry-specific genome-wide association scans (GWAS) and a meta-GWAS analysis of the NMR. We modeled natural-log transformed NMR with covariates: principal components of genetic ancestry, age, sex, body mass index, and smoking status., Results: African and Asian American NMRs were statistically significantly (P values ≤ 5E-5) lower than European American NMRs. Meta-GWAS analysis identified 36 genome-wide significant variants over a 43 kilobase pair region at CYP2A6 with minimum P = 2.46E-18 at rs12459249, proximal to CYP2A6. Additional minima were located in intron 4 (rs56113850, P = 6.61E-18) and in the CYP2A6-CYP2A7 intergenic region (rs34226463, P = 1.45E-12). Most (34/36) genome-wide significant variants suggested reduced CYP2A6 activity; functional mechanisms were identified and tested in knowledge-bases. Conditional analysis resulted in intergenic variants of possible interest (P values < 5E-5)., Conclusions: This meta-GWAS of the NMR identifies CYP2A6 variants, replicates the top-ranked single nucleotide polymorphism from a recent Finnish meta-GWAS of the NMR, identifies functional mechanisms, and provides pan-continental population biomarkers for nicotine metabolism., Implications: This multiple ancestry meta-GWAS of the laboratory study-based NMR provides novel evidence and replication for genome-wide association of CYP2A6 single nucleotide and insertion-deletion polymorphisms. We identify three regions of genome-wide significance: proximal, intronic, and distal to CYP2A6. We replicate the top-ranking single nucleotide polymorphism from a recent GWAS of the NMR in Finnish smokers, identify a functional mechanism for this intronic variant from in silico analyses of RNA-seq data that is consistent with CYP2A6 expression measured in postmortem lung and liver, and provide additional support for the intergenic region between CYP2A6 and CYP2A7., (© The Author 2016. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.)

The mu1 opioid receptor gene, OPRM1, has long been a high-priority candidate for human genetic studies of addiction. Because of its potential functional significance, the non-synonymous variant rs1799971 (A118G, Asn40Asp) in OPRM1 has been extensively studied, yet its role in addiction has remained unclear, with conflicting association findings. To resolve the question of what effect, if any, rs1799971 has on substance dependence risk, we conducted collaborative meta-analyses of 25 datasets with over 28,000 European-ancestry subjects. We investigated non-specific risk for "general" substance dependence, comparing cases dependent on any substance to controls who were non-dependent on all assessed substances. We also examined five specific substance dependence diagnoses: DSM-IV alcohol, opioid, cannabis, and cocaine dependence, and nicotine dependence defined by the proxy of heavy/light smoking (cigarettes-per-day >20 vs. ≤ 10). The G allele showed a modest protective effect on general substance dependence (OR = 0.90, 95% C.I. [0.83-0.97], p value = 0.0095, N = 16,908). We observed similar effects for each individual substance, although these were not statistically significant, likely because of reduced sample sizes. We conclude that rs1799971 contributes to mechanisms of addiction liability that are shared across different addictive substances. This project highlights the benefits of examining addictive behaviors collectively and the power of collaborative data sharing and meta-analyses.

Background: Addictive disorders are a class of chronic, relapsing mental disorders that are responsible for increased risk of mental and medical disorders and represent the largest, potentially modifiable cause of death. Tobacco dependence is associated with increased risk of disease and premature death. While tobacco control efforts and therapeutic interventions have made good progress in reducing smoking prevalence, challenges remain in optimizing their effectiveness based on patient characteristics, including genetic variation. In order to maximize collaborative efforts to advance addiction research, we have developed a genotyping array called Smokescreen. This custom array builds upon previous work in the analyses of human genetic variation, the genetics of addiction, drug metabolism, and response to therapy, with an emphasis on smoking and nicotine addiction., Results: The Smokescreen genotyping array includes 646,247 markers in 23 categories. The array design covers genome-wide common variation (65.67, 82.37, and 90.72% in African (YRI), East Asian (ASN), and European (EUR) respectively); most of the variation with a minor allele frequency ≥ 0.01 in 1014 addiction genes (85.16, 89.51, and 90.49% for YRI, ASN, and EUR respectively); and nearly all variation from the 1000 Genomes Project Phase 1, NHLBI GO Exome Sequencing Project and HapMap databases in the regions related to smoking behavior and nicotine metabolism: CHRNA5-CHRNA3-CHRNB4 and CYP2A6-CYP2B6. Of the 636 pilot DNA samples derived from blood or cell line biospecimens that were genotyped on the array, 622 (97.80%) passed quality control. In passing samples, 90.08% of markers passed quality control. The genotype reproducibility in 25 replicate pairs was 99.94%. For 137 samples that overlapped with HapMap2 release 24, the genotype concordance was 99.76%. In a genome-wide association analysis of the nicotine metabolite ratio in 315 individuals participating in nicotine metabolism laboratory studies, we identified genome-wide significant variants in the CYP2A6 region (min p = 9.10E-15)., Conclusions: We developed a comprehensive genotyping array for addiction research and demonstrated its analytic validity and utility through pilot genotyping of HapMap and study samples. This array allows researchers to perform genome-wide, candidate gene, and pathway-based association analyses of addiction, tobacco-use, treatment response, comorbidities, and associated diseases in a standardized, high-throughput platform.

Background: Genome-wide association studies have identified polymorphisms linked to both smoking exposure and risk of lung cancer. The degree to which lung cancer risk is driven by increased smoking, genetics, or gene-environment interactions is not well understood., Methods: We analyzed associations between 28 single nucleotide polymorphisms (SNPs) previously associated with smoking quantity and lung cancer in 7156 African-American females in the Women's Health Initiative (WHI), then analyzed main effects of top nominally significant SNPs and interactions between SNPs, cigarettes per day (CPD) and pack-years for lung cancer in an independent, multi-center case-control study of African-American females and males (1078 lung cancer cases and 822 controls)., Findings: Nine nominally significant SNPs for CPD in WHI were associated with incident lung cancer (corrected p-values from 0.027 to 6.09 × 10(-5)). CPD was found to be a nominally significant effect modifier between SNP and lung cancer for six SNPs, including CHRNA5 rs2036527[A](betaSNP*CPD = - 0.017, p = 0.0061, corrected p = 0.054), which was associated with CPD in a previous genome-wide meta-analysis of African-Americans., Interpretation: These results suggest that chromosome 15q25.1 variants are robustly associated with CPD and lung cancer in African-Americans and that the allelic dose effect of these polymorphisms on lung cancer risk is most pronounced in lighter smokers.