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Abstract Background & aim Smoking is a major risk factor for multiple gastrointestinal cancers, and adversely affects peptic ulcer disease, gastroesophageal reflux, pancreatitis and Crohn’s disease. Despite key recommendations for diagnosing and treating tobacco use disorder in healthcare settings, the degree to which this is implemented in Gastroenterology (GI) clinics is unknown. We aimed to assess our providers’ practices, identify barriers for implementing evidence-based smoking cessation treatments, and address these barriers by implementing a novel low-burden point of care Electronic health record-enabled evidence-based tobacco treatment (ELEVATE), in GI clinics. Methods An online survey was distributed to clinic gastroenterologists. ELEVATE module training was implemented in 1/2021. Data were evaluated during pre (7/2020-12/2020) and post (1/2021-12/2021) implementation periods to evaluate the reach and effectiveness of ELEVATE. Generalized estimating equations (GEE) were used to generate rate ratios (RR) to evaluate the intervention. Results 91% (20/22) of GI physicians responded to our survey, and only 20% often assisted patients who smoke with counseling. Lack of a systematic program to offer help to patients was reported by 80% of providers as an extremely/very important barrier limiting their smoking cessation practices. The proportion of current patients who smoke receiving cessation treatment increased from pre-ELEVATE to post-ELEVATE (14.36–27.47%, RR = 1.90, 95% CI 1.60–2.26, p

Abstract Background The Cancer Center Cessation Initiative (C3I) is a National Cancer Institute (NCI) Cancer Moonshot Program that supports NCI-designated cancer centers developing tobacco treatment programs for oncology patients who smoke. C3I-funded centers implement evidence-based programs that offer various smoking cessation treatment components (e.g., counseling, Quitline referrals, access to medications). While evaluation of implementation outcomes in C3I is guided by evaluation of reach and effectiveness (via RE-AIM), little is known about technical efficiency—i.e., how inputs (e.g., program costs, staff time) influence implementation outcomes (e.g., reach, effectiveness). This study demonstrates the application of data envelopment analysis (DEA) as an implementation science tool to evaluate technical efficiency of C3I programs and advance prioritization of implementation resources. Methods DEA is a linear programming technique widely used in economics and engineering for assessing relative performance of production units. Using data from 16 C3I-funded centers reported in 2020, we applied input-oriented DEA to model technical efficiency (i.e., proportion of observed outcomes to benchmarked outcomes for given input levels). The primary models used the constant returns-to-scale specification and featured cost-per-participant, total full-time equivalent (FTE) effort, and tobacco treatment specialist effort as model inputs and reach and effectiveness (quit rates) as outcomes. Results In the DEA model featuring cost-per-participant (input) and reach/effectiveness (outcomes), average constant returns-to-scale technical efficiency was 25.66 (SD = 24.56). When stratified by program characteristics, technical efficiency was higher among programs in cohort 1 (M = 29.15, SD = 28.65, n = 11) vs. cohort 2 (M = 17.99, SD = 10.16, n = 5), with point-of-care (M = 33.90, SD = 28.63, n = 9) vs. no point-of-care services (M = 15.59, SD = 14.31, n = 7), larger (M = 33.63, SD = 30.38, n = 8) vs. smaller center size (M = 17.70, SD = 15.00, n = 8), and higher (M = 29.65, SD = 30.99, n = 8) vs. lower smoking prevalence (M = 21.67, SD = 17.21, n = 8). Conclusion Most C3I programs assessed were technically inefficient relative to the most efficient center benchmark and may be improved by optimizing the use of inputs (e.g., cost-per-participant) relative to program outcomes (e.g., reach, effectiveness). This study demonstrates the appropriateness and feasibility of using DEA to evaluate the relative performance of evidence-based programs.

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.

Abstract Background The Cancer Center Cessation Initiative (C3I) was launched in 2017 as a part of the NCI Cancer Moonshot program to assist NCI-designated cancer centers in developing tobacco treatment programs for oncology patients. Participating centers have implemented varied evidence-based programs that fit their institutional resources and needs, offering a wide range of services including in-person and telephone-based counseling, point of care, interactive voice response systems, referral to the quitline, text- and web-based services, and medications. Methods We used a mixed methods comparative case study design to evaluate system-level implementation costs across 15 C3I-funded cancer centers that reported for at least one 6-month period between July 2018 and June 2020. We analyzed operating costs by resource category (e.g., personnel, medications) concurrently with transcripts from semi-structured key-informant interviews conducted during site visits. Personnel salary costs were estimated using Bureau of Labor Statistics wage data adjusted for area and occupation, and non-wage benefits. Qualitative findings provided additional information on intangible resources and contextual factors related to implementation costs. Results Median total monthly operating costs across funded centers were $11,045 (range: $5129–$20,751). The largest median operating cost category was personnel ($10,307; range: $4122–$19,794), with the highest personnel costs attributable to the provision of in-person program services. Monthly (non-zero) cost ranges for other categories were medications ($17–$573), materials ($6–$435), training ($96–$516), technology ($171–$2759), and equipment ($10–$620). Median cost-per-participant was $466 (range: $70–$2093) and cost-per-quit was $2688 (range: $330–$9628), with sites offering different combinations of program components, ranging from individually-delivered in-person counseling only to one program that offered all components. Site interviews provided context for understanding variations in program components and their cost implications. Conclusions Among most centers that have progressed in tobacco treatment program implementation, cost-per-quit was modest relative to other prevention interventions. Although select centers have achieved similar average costs by offering program components of various levels of intensity, they have varied widely in program reach and effectiveness. Evaluating implementation costs of such programs alongside reach and effectiveness is necessary to provide decision makers in oncology settings with the important additional information needed to optimize resource allocation when establishing tobacco treatment programs.

PurposeThe objective of this study is to identify how predisposing characteristics, enabling factors, and health needs are jointly and individually associated with epidemiological patterns of outpatient healthcare utilization for patients who already interact and engage with a large healthcare system.MethodsWe retrospectively analyzed electronic medical record data from 1,423,166 outpatient clinic visits from 474,674 patients in a large healthcare system from June 2018-March 2019. We evaluated patients who exclusively visited rural clinics versus patients who exclusively visited urban clinics using Chi-square tests and the generalized estimating equation Poisson regression methodology. The outcome was healthcare use defined by the number of outpatient visits to clinics within the healthcare system and independent variables included age, gender, race, ethnicity, smoking status, health status, and rural or urban clinic location. Supplementary analyses were conducted observing healthcare use patterns within rural and urban clinics separately and within primary care and specialty clinics separately.FindingsPatients in rural clinics vs. urban clinics had worse health status [χ2 = 935.1, df = 3, pConclusionsWithin the large healthcare system, patients in rural clinics had lower outpatient healthcare utilization compared to their urban counterparts despite having potentially elevated health needs reflected by a higher number of unique health diagnoses documented in their electronic health records after adjusting for multiple factors. This work can inform future studies exploring the roots and ramifications of rural-urban healthcare utilization differences and rural healthcare disparities.

Main objectiveThere is limited information on how patient outcomes have changed during the COVID-19 pandemic. This study characterizes changes in mortality, intubation, and ICU admission rates during the first 20 months of the pandemic.Study design and methodsUniversity of Wisconsin researchers collected and harmonized electronic health record data from 1.1 million COVID-19 patients across 21 United States health systems from February 2020 through September 2021. The analysis comprised data from 104,590 adult hospitalized COVID-19 patients. Inclusion criteria for the analysis were: (1) age 18 years or older; (2) COVID-19 ICD-10 diagnosis during hospitalization and/or a positive COVID-19 PCR test in a 14-day window (+/- 7 days of hospital admission); and (3) health system contact prior to COVID-19 hospitalization. Outcomes assessed were: (1) mortality (primary), (2) endotracheal intubation, and (3) ICU admission.Results and significanceThe 104,590 hospitalized participants had a mean age of 61.7 years and were 50.4% female, 24% Black, and 56.8% White. Overall risk-standardized mortality (adjusted for age, sex, race, ethnicity, body mass index, insurance status and medical comorbidities) declined from 16% of hospitalized COVID-19 patients (95% CI: 16% to 17%) early in the pandemic (February-April 2020) to 9% (CI: 9% to 10%) later (July-September 2021). Among subpopulations, males (vs. females), those on Medicare (vs. those on commercial insurance), the severely obese (vs. normal weight), and those aged 60 and older (vs. younger individuals) had especially high mortality rates both early and late in the pandemic. ICU admission and intubation rates also declined across these 20 months.ConclusionsMortality, intubation, and ICU admission rates improved markedly over the first 20 months of the pandemic among adult hospitalized COVID-19 patients although gains varied by subpopulation. These data provide important information on the course of COVID-19 and identify hospitalized patient groups at heightened risk for negative outcomes.Trial registrationClinicalTrials.gov Identifier: NCT04506528 (https://clinicaltrials.gov/ct2/show/NCT04506528).

Tobacco cessation after cancer diagnosis leads to better patient outcomes. However, tobacco treatment services are frequently unavailable in cancer care settings, and multilevel implementation challenges can impede uptake of new programs. The National Cancer Institute (NCI) dedicated Cancer Moonshot funding through the Cancer Center Cessation Initiative (C3I) for NCI-Designated Cancer Centers to implement or enhance the implementation of tobacco treatment services. We examined a pragmatic application of the RE-AIM framework (reach, effectiveness, adoption, implementation, and maintenance) to evaluate tobacco treatment programs implemented within Cancer Centers funded through C3I. Using three C3I-funded Centers as examples, we describe how each RE-AIM construct was operationalized to evaluate the implementation of a wide range of cessation services (e.g., tobacco use screening, counseling, Quitline referral, pharmacotherapy) in this heterogeneous group of cancer care settings. We discuss the practical challenges encountered in assessing RE-AIM constructs in real world situations, including using the electronic health record (EHR) to aid in assessment. Reach and effectiveness evaluation required that Centers define the setting(s) where cessation services were implemented (to determine the “denominator”), enumerate the patient population, report current patient tobacco use, patient engagement in tobacco treatment, and 6-month cessation outcomes. To reduce site heterogeneity, increase data accuracy, and reduce burden, reach was frequently captured via standardized EHR enhancements that improved the identification of current smokers and tobacco treatment referrals. Effectiveness was determined by cessation outcomes (30-day point prevalence abstinence at 6-months post-engagement) assessed through a variety of data collection approaches. Adoption was measured by the characteristics and proportion of targeted cancer care settings and clinicians engaged in cessation service delivery. Implementation was assessed by examining the delivery of tobacco screening assessments and intervention components across sites, and provider-level implementation consistency. Maintenance assessments identified whether tobacco treatment services continued in the setting after implementation and documented the sustainability plan and organizational commitment to continued delivery. In sum, this paper demonstrates a pragmatic approach to using RE-AIM as an evaluation framework that yields relevant outcomes on common implementation metrics across widely differing tobacco treatment approaches and settings.

Background: Recent meta-analyses show that individuals with high risk variants in CHRNA5 on chromosome 15q25 are likely to develop lung cancer earlier than those with low-risk genotypes. The same high-risk genetic variants also predict nicotine dependence and delayed smoking cessation. It is unclear whether smoking cessation confers the same benefits in terms of lung cancer risk reduction for those who possess CHRNA5 risk variants versus those who do not. Methods: Meta-analyses examined the association between smoking cessation and lung cancer risk in 15 studies of individuals with European ancestry who possessed varying rs16969968 genotypes (N = 12,690 ever smokers, including 6988 cases of lung cancer and 5702 controls) in the International Lung Cancer Consortium. Results: Smoking cessation (former vs. current smokers) was associated with a lower likelihood of lung cancer (OR = 0.48, 95%CI = 0.30–0.75, p = 0.0015). Among lung cancer patients, smoking cessation was associated with a 7-year delay in median age of lung cancer diagnosis (HR = 0.68, 95%CI = 0.61–0.77, p = 4.9 ∗ 10–10). The CHRNA5 rs16969968 risk genotype (AA) was associated with increased risk and earlier diagnosis for lung cancer, but the beneficial effects of smoking cessation were very similar in those with and without the risk genotype. Conclusion: We demonstrate that quitting smoking is highly beneficial in reducing lung cancer risks for smokers regardless of their CHRNA5 rs16969968 genetic risk status. Smokers with high-risk CHRNA5 genotypes, on average, can largely eliminate their elevated genetic risk for lung cancer by quitting smoking- cutting their risk of lung cancer in half and delaying its onset by 7 years for those who develop it. These results: 1) underscore the potential value of smoking cessation for all smokers, 2) suggest that CHRNA5 rs16969968 genotype affects lung cancer diagnosis through its effects on smoking, and 3) have potential value for framing preventive interventions for those who smoke.

Imputation, the process of inferring genotypes for untyped variants, is used to identify and refine genetic association findings. Inaccuracies in imputed data can distort the observed association between variants and a disease. Many statistics are used to assess accuracy; some compare imputed to genotyped data and others are calculated without reference to true genotypes. Prior work has shown that the Imputation Quality Score (IQS), which is based on Cohen's kappa statistic and compares imputed genotype probabilities to true genotypes, appropriately adjusts for chance agreement; however, it is not commonly used. To identify differences in accuracy assessment, we compared IQS with concordance rate, squared correlation, and accuracy measures built into imputation programs. Genotypes from the 1000 Genomes reference populations (AFR N = 246 and EUR N = 379) were masked to match the typed single nucleotide polymorphism (SNP) coverage of several SNP arrays and were imputed with BEAGLE 3.3.2 and IMPUTE2 in regions associated with smoking behaviors. Additional masking and imputation was conducted for sequenced subjects from the Collaborative Genetic Study of Nicotine Dependence and the Genetic Study of Nicotine Dependence in African Americans (N = 1,481 African Americans and N = 1,480 European Americans). Our results offer further evidence that concordance rate inflates accuracy estimates, particularly for rare and low frequency variants. For common variants, squared correlation, BEAGLE R2, IMPUTE2 INFO, and IQS produce similar assessments of imputation accuracy. However, for rare and low frequency variants, compared to IQS, the other statistics tend to be more liberal in their assessment of accuracy. IQS is important to consider when evaluating imputation accuracy, particularly for rare and low frequency variants.

The American College of Medical Genetics and Genomics (ACMG) recommends that clinical sequencing laboratories return secondary findings in 56 genes associated with medically actionable conditions. Our goal was to apply a systematic, stringent approach consistent with clinical standards to estimate the prevalence of pathogenic variants associated with such conditions using a diverse sequencing reference sample. Candidate variants in the 56 ACMG genes were selected from Phase 1 of the 1000 Genomes dataset, which contains sequencing information on 1,092 unrelated individuals from across the world. These variants were filtered using the Human Gene Mutation Database (HGMD) Professional version and defined parameters, appraised through literature review, and examined by a clinical laboratory specialist and expert physician. Over 70,000 genetic variants were extracted from the 56 genes, and filtering identified 237 variants annotated as disease causing by HGMD Professional. Literature review and expert evaluation determined that 7 of these variants were pathogenic or likely pathogenic. Furthermore, 5 additional truncating variants not listed as disease causing in HGMD Professional were identified as likely pathogenic. These 12 secondary findings are associated with diseases that could inform medical follow-up, including cancer predisposition syndromes, cardiac conditions, and familial hypercholesterolemia. The majority of the identified medically actionable findings were in individuals from the European (5/379) and Americas (4/181) ancestry groups, with fewer findings in Asian (2/286) and African (1/246) ancestry groups. Our results suggest that medically relevant secondary findings can be identified in approximately 1% (12/1092) of individuals in a diverse reference sample. As clinical sequencing laboratories continue to implement the ACMG recommendations, our results highlight that at least a small number of potentially important secondary findings can be selected for return. Our results also confirm that understudied populations will not reap proportionate benefits of genomic medicine, highlighting the need for continued research efforts on genetic diseases in these populations.

The Cytochrome P450 2B6 (CYP2B6) enzyme makes a small contribution to hepatic nicotine metabolism relative to CYP2A6, but CYP2B6 is the primary enzyme responsible for metabolism of the smoking cessation drug bupropion. Using CYP2A6 genotype as a covariate, we find that a non-coding polymorphism in CYP2B6 previously associated with smoking cessation (rs8109525) is also significantly associated with nicotine metabolism. The association is independent of the well-studied non-synonymous variants rs3211371, rs3745274, and rs2279343 (CYP2B6*5 and *6). Expression studies demonstrate that rs8109525 is also associated with differences in CYP2B6 mRNA expression in liver biopsy samples. Splicing assays demonstrate that specific splice forms of CYP2B6 are associated with haplotypes defined by variants including rs3745274 and rs8109525. These results indicate differences in mRNA expression and splicing as potential molecular mechanisms by which non-coding variation in CYP2B6 may affect enzymatic activity leading to differences in metabolism and smoking cessation.

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. [ABSTRACT FROM AUTHOR]

Introduction: Genetic variants associated with nicotine dependence have previously been identified, primarily in European-ancestry populations. No genome-wide association studies (GWAS) have been reported for smoking behaviors in Hispanics/Latinos in the United States and Latin America, who are of mixed ancestry with European, African, and American Indigenous components.Methods: We examined genetic associations with smoking behaviors in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) (N = 12 741 with smoking data, 5119 ever-smokers), using ~2.3 million genotyped variants imputed to the 1000 Genomes Project phase 3. Mixed logistic regression models accounted for population structure, sampling, relatedness, sex, and age.Results: The known region of CHRNA5, which encodes the α5 cholinergic nicotinic receptor subunit, was associated with heavy smoking at genome-wide significance (p ≤ 5 × 10-8) in a comparison of 1929 ever-smokers reporting cigarettes per day (CPD) > 10 versus 3156 reporting CPD ≤ 10. The functional variant rs16969968 in CHRNA5 had a p value of 2.20 × 10-7 and odds ratio (OR) of 1.32 for the minor allele (A); its minor allele frequency was 0.22 overall and similar across Hispanic/Latino background groups (Central American = 0.17; South American = 0.19; Mexican = 0.18; Puerto Rican = 0.22; Cuban = 0.29; Dominican = 0.19). CHRNA4 on chromosome 20 attained p < 10-4, supporting prior findings in non-Hispanics. For nondaily smoking, which is prevalent in Hispanic/Latino smokers, compared to daily smoking, loci on chromosomes 2 and 4 achieved genome-wide significance; replication attempts were limited by small Hispanic/Latino sample sizes.Conclusions: Associations of nicotinic receptor gene variants with smoking, first reported in non-Hispanic European-ancestry populations, generalized to Hispanics/Latinos despite different patterns of smoking behavior.Implications: We conducted the first large-scale genome-wide association study (GWAS) of smoking behavior in a US Hispanic/Latino cohort, and the first GWAS of daily/nondaily smoking in any population. Results show that the region of the nicotinic receptor subunit gene CHRNA5, which in non-Hispanic European-ancestry smokers has been associated with heavy smoking as well as cessation and treatment efficacy, is also significantly associated with heavy smoking in this Hispanic/Latino cohort. The results are an important addition to understanding the impact of genetic variants in understudied Hispanic/Latino smokers. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The incorporation of genomic information into routine care settings is a burgeoning area for investigation in behavioral medicine. The past decade has witnessed rapid advancements in knowledge of genetic biomarkers associated with smoking behaviors and tobacco-related morbidity and mortality, providing the basis for promising genomic applications in clinical and community settings. We assessed the current state of readiness for implementing genomic applications involving variation in the α5 nicotinic cholinergic receptor subunit gene CHRNA5 and smoking outcomes (behaviors and related diseases) using a process that could be translatable to a wide range of genomic applications in behavioral medicine. We reviewed the scientific literature involving CHRNA5 genetic variation and smoking cessation, and then summarized and synthesized a chain of evidence according to analytic validity, clinical validity, clinical utility, and ethical, legal, and social implications (ACCE), a well-established set of criteria used to evaluate genomic applications. Our review identified at least three specific genomic applications for which implementation may be considered, including the use of CHRNA5 genetic test results for informing disease risk, optimizing smoking cessation treatment, and motivating smoking behavior change. For these genomic applications, we rated analytic validity as convincing, clinical validity as adequate, and clinical utility and ethical, legal, and social implications as inadequate. For clinical genomic applications involving CHRNA5 variation and smoking outcomes, research efforts now need to focus on establishing clinical utility. This approach is compatible with pre-implementation research, which is also needed to accelerate translation, improve innovation design, and understand and refine system processes involved in implementation. This study informs the readiness to incorporate smoking-related genomic applications in real-world settings and facilitates cross-disciplinary collaboration to accelerate the integration of evidence-based genomics in behavioral medicine. [ABSTRACT FROM AUTHOR]

Background: Recent meta-analyses show strong evidence of associations among genetic variants in CHRNA5 on chromosome 15q25, smoking quantity, and lung cancer. This meta-analysis tests whether the CHRNA5 variant rs16969968 predicts age of smoking cessation and age of lung cancer diagnosis. Methods: Meta-analyses examined associations between rs16969968, age of quitting smoking, and age of lung cancer diagnosis in 24 studies of European ancestry (n = 29 072). In each dataset, we used Cox regression models to evaluate the association between rs16969968 and the two primary phenotypes (age of smoking cessation among ever smokers and age of lung cancer diagnosis among lung cancer case patients) and the secondary phenotype of smoking duration. Heterogeneity across studies was assessed with the Cochran Q test. All statistical tests were two-sided. Results: The rs16969968 allele (A) was associated with a lower likelihood of smoking cessation (hazard ratio [HR] = 0.95, 95% confidence interval [CI] = 0.91 to 0.98, P = .0042), and the AA genotype was associated with a four-year delay in median age of quitting compared with the GG genotype. Among smokers with lung cancer diagnoses, the rs16969968 genotype (AA) was associated with a four-year earlier median age of diagnosis compared with the low-risk genotype (GG) (HR = 1.08, 95% CI = 1.04 to 1.12, P = 1.1*10-5). Conclusion: These data support the clinical significance of the CHRNA5 variant rs16969968. It predicts delayed smoking cessation and an earlier age of lung cancer diagnosis in this meta-analysis. Given the existing evidence that this CHRNA5 variant predicts favorable response to cessation pharmacotherapy, these findings underscore the potential clinical and public health importance of rs16969968 in CHRNA5 in relation to smoking cessation success and lung cancer risk. [ABSTRACT FROM AUTHOR]

Rationale: The CHRNA5-CHRNA3-CHRNB4 locus is associated with self-reported smoking behavior and also harbors the strongest genetic associations with chronic obstructive pulmonary disease (COPD) and lung cancer. Because the associations with lung disease remain after adjustment for self-reported smoking behaviors, it has been asserted that CHRNA5-CHRNA3-CHRNB4 variants increase COPD and lung cancer susceptibility independently of their effects on smoking.Objectives: To compare the genetic associations of exhaled carbon monoxide (CO), a biomarker of current cigarette exposure, with self-reported smoking behaviors.Methods: A total of 1,521 European American and 247 African American current smokers recruited into smoking cessation studies were assessed for CO at intake before smoking cessation. DNA samples were genotyped using the Illumina Omni2.5 microarray. Genetic associations with CO and smoking behaviors (cigarettes smoked per day, Fagerstrom test for nicotine dependence) were studied.Measurements and Main Results: Variants in the CHRNA5-CHRNA3-CHRNB4 locus, including rs16969968, a nonsynonymous variant in CHRNA5, are genomewide association study-significantly associated with CO (β = 2.66; 95% confidence interval [CI], 1.74-3.58; P = 1.65 × 10(-8)), and this association remains strong after adjusting for smoking behavior (β = 2.18; 95% CI, 1.32-3.04; P = 7.47 × 10(-7)). The correlation between CO and cigarettes per day is statistically significantly lower (z = 3.43; P = 6.07 × 10(-4)) in African Americans (r = 0.14; 95% CI, 0.02-0.26; P = 0.003) than in European-Americans (r = 0.36; 95% CI, 0.31-0.40; P = 0.0001).Conclusions: Exhaled CO, a biomarker that is simple to measure, captures aspects of cigarette smoke exposure in current smokers beyond the number of cigarettes smoked per day. Behavioral measures of smoking are therefore insufficient indices of cigarette smoke exposure, suggesting that genetic associations with COPD or lung cancer that persist after adjusting for self-reported smoking behavior may still reflect genetic effects on smoking exposure. [ABSTRACT FROM AUTHOR]

Cigarette smoking is highly addictive, and modern genetic research has identified robust genetic influences on nicotine dependence. An important step in translating these genetic findings is to identify the genetic factors affecting smoking cessation in order to enhance current smoking cessation treatments. We review the significance of variants in the nicotinic receptor gene cluster (CHRNA5―CHRNA3―CHRNB4) in the prediction of smoking quantity, smoking cessation, and response to cessation medication in multiple studies of smoking cessation. Three common haplotypes (low-risk, intermediate-risk, and high-risk) in the CHRNA5―CHRNA3―CHRNB4 region are defined by rs16969968 and rs680244. The genetic variants in the CHRNA5―CHRNA3―CHRNB4 region that predict nicotine dependence also predicted a later age of smoking cessation in a community-based sample. In a smoking cessation trial, these variants predicted abstinence at the end of treatment in individuals receiving placebo medication, but not among individuals receiving active medication. Pharmacological treatments moderate the genetic risk in affecting cessation success. These pharmacogenetic interactions have been reproduced by a recent meta-analysis of smoking cessation trials. The number needed to treat was four for smokers with the high-risk haplotype, seven for smokers with the intermediate-risk haplotype, and > 1000 for smokers with the low-risk haplotype. The wide variation in number needed to treat between smokers with different haplotypes supports the notion that personalized smoking cessation intervention based upon genotype could meaningfully increase the efficiency of such treatment. In summary, variants in the CHRNA5―CHRNA3―CHRNB4 region identify individuals at increased risk of cessation failure, and this increased risk can be ameliorated by cessation pharmacotherapy. [ABSTRACT FROM AUTHOR]

Objective: Smoking is highly intractable, and the genetic influences on cessation are unclear. Identifying the genetic factors affecting smoking cessation could elucidate the nature of tobacco dependence, enhance risk assessment, and support development of treatment algorithms. This study tested whether variants in the nicotinic receptor gene cluster CHRNA5-CHRNA3-CHRNB4 predict age at smoking cessation and relapse after an attempt to quit smoking. Method: In a community-based, cross-sectional study (N=5,216) and a randomized comparative effectiveness smoking cessation trial (N=1,073), the authors used Cox proportional hazard models and logistic regression to model the relationships of smoking cessation (self-reported quit age in the community study and point-prevalence abstinence at the end of treatment in the clinical trial) to three common haplotypes in the CHRNA5-CHRNA3-CHRNB4 region defined by rs16969968 and rs680244. Results: The genetic variants in the CHRNA5-CHRNA3-CHRNB4 region that predict nicotine dependence also predicted a later age at smoking cessation in the community sample. In the smoking cessation trial, haplotype predicted abstinence at end of treatment in individuals receiving placebo but not among individuals receiving active medication. Haplotype interacted with treatment in affecting cessation success. Conclusions: Smokers with the high-risk haplotype were three times as likely to respond to pharmacologic cessation treatments as were smokers with the low-risk haplotype. The high-risk haplotype increased the risk of cessation failure, and this increased risk was ameliorated by cessation pharmacotherapy. By identifying a high-risk genetic group with heightened response to smoking cessation pharmacotherapy, this work may support the development of personalized cessation treatments. [ABSTRACT FROM AUTHOR]

Nicotine dependence is moderately heritable, but identified genetic associations explain only modest portions of this heritability. We analyzed 3369 SNPs from 349 candidate genes and investigated whether incorporation of SNP-by-environment interaction into association analyses might bolster gene discovery efforts and prediction of nicotine dependence. Specifically, we incorporated the interaction between allele count and age at onset of regular smoking (AOS) into association analyses of nicotine dependence. Subjects were from the Collaborative Genetic Study of Nicotine Dependence and included 797 cases ascertained for Fagerström nicotine dependence and 811 non-nicotine-dependent smokers as controls, all of European descent. Compared with main effect models, SNP × AOS interaction models resulted in higher numbers of nominally significant tests, increased predictive utility at individual SNPs and higher predictive utility in a multi-locus model. Some SNPs previously documented in main effect analyses exhibited improved fits in the joint analysis, including rs16969968 from CHRNA5 and rs2314379 from MAP3K4. CHRNA5 exhibited larger effects in later-onset smokers, in contrast with a previous report that suggested the opposite interaction ( Weiss et al. 2008 ). However, a number of SNPs that did not emerge in main effect analyses were among the strongest findings in the interaction analyses. These include SNPs located in GRIN2B ( P = 1.5 × 10−5), which encodes a subunit of the N-methyl-D-aspartate receptor channel, a key molecule in mediating age-dependent synaptic plasticity. Incorporation of logically chosen interaction parameters, such as AOS, into genetic models of substance use disorders may increase the degree of explained phenotypic variation and constitutes a promising avenue for gene discovery. [ABSTRACT FROM AUTHOR]

Background: Theories regarding how spontaneous panic and agoraphobia relate are based mostly on cross-sectional and/or clinic data.Aims: To determine how spontaneous panic and agoraphobia relate longitudinally, and to estimate the incidence rate of and other possible risk factors for first-onset agoraphobia, using a general population cohort.Method: A sample of 1920 adults in east Baltimore were assessed in 1981-1982 and the mid-1990s with the Diagnostic Interview Schedule (DIS). Psychiatrist diagnoses were made in a subset of the sample at follow-up (n = 816).Results: Forty-one new cases of DIS/DSM-III-R agoraphobia were identified (about 2 per 1000 person-years at risk). As expected, baseline DIS/DSM-III panic disorder predicted first incidence of agoraphobia (OR = 12, 95% CI 3.2-45), as did younger age, female gender and other age, female gender and other phobias. Importantly, baseline agoraphobia without spontaneous panic attacks also predicted first incidence of panic disorder (OR=3.9, 95% CI1.8-8.4). Longitudinal relationships between panic disorder and psychiatrist-confirmed agoraphobia were strong (panic before agoraphobia OR=20, 95% CI 2.3-180; agoraphobia before panic OR=16, 95% CI 3.2-78).Conclusions: The implied one-way causal relationship between spontaneous panic attacks and agoraphobia in DSM-IV appears incorrect. [ABSTRACT FROM AUTHOR]

Examines the validity and utility of major depressive disorder, depressive syndrome, dysthymia and a comorbid depression condition by examining subject transition between categories and the symptoms, course and risk factors of each. Association between stressful life and depressive syndrome; Gender specificity of comorbid depression condition.

Investigates the cognitive decline over 11.5 years in adult household residents of Baltimore, Maryland. Relationship between education and cognitive decline; Performance of residents on the Mini-Mental State test; Occurrence of cognitive decline in all age groups.

Deals with a study which examined the relationship between perceived cognitive competence in children and the risk of subsequent alcohol-related problems. Methods; Results; Discussion.

The “Genetics and pharmacogenetics of substance use disorder” session was chaired by Dr Pao-Luh Tao and had three speakers. The speakers and topics were as follows. Dr Li-Shiun Chen discussed “Genomics and personalized medicine for smoking cessation treatments”. Dr Chih-Ken Chen presented a talk on the “Genetics of methamphetamine abuse and methamphetamine psychosis”. Dr Yu-Li Liu described a “Pharmacogenomics study in a Taiwan methadone maintenance cohort”. [ABSTRACT FROM AUTHOR]