VI. a Controlled Study of Nicotine Effects on Attention: Pharmacogenetic Interactions

Why do young women smoke? VI. A controlled study of nicotine effects on attention: pharmacogenetic interactions

A Rigbi1, A Yakir1, K Sarner- In prior studies we found that young, female smokers manifest poorer 1 2 1 performance than non-smokers on attention-related tasks and that these Kanyas , Y Pollak and B Lerer findings can be moderated by variation in nicotinic acetylcholine receptor 1Biological Psychiatry Laboratory, Department of (nAChR) genes. We predicted that under controlled conditions (1) nicotine Psychiatry, Hadassah-Hebrew University Medical would improve functioning on attentional tasks in smokers who previously Center, Jerusalem, Israel and 2Department of manifested relatively poor performance, and that (2) smokers who carry Psychology, Hebrew University, Jerusalem, Israel genetic variations associated with poorer attention performance would derive greater benefit from nicotine. To test these hypotheses, 31 young Correspondence: Professor B Lerer, Biological Psychiatry female smokers, who participated in our previous study, performed the Laboratory, Department of Psychiatry, Matching Familiar Figures Test (MFFT), Tower of London Test and Hadassah-Hebrew University Medical Center, Continuous Performance Task (CPT) in a double-blind, within-between Ein Karem, Jerusalem 91120, Israel. subject design, placebo or nicotine (4 mg as gum) serving as the within factor E-mail: [email protected] and genetic profile as the between factor. Repeated measures ANCOVA controlling for attention deficit symptomatology, substance abuse and nicotine dependence showed better performance under nicotine among participants with higher levels of attention deficit symptoms (MFFT errors: P ¼ 0.04; CPT commissions: P ¼ 0.01) and nicotine dependence (CPT stability of response: P ¼ 0.04) and greater consumption of caffeine (CPT stability of response: P ¼ 0.04). An interactive effect of genetic profile was demonstrated for SNP rs2337980 in CHRNA7. These findings suggest that nicotine may have stronger short-term facilitating effects on attention in women who have more attention deficit symptoms and consume more nicotine and caffeine. This effect may be modified by a specific genetic make-up. Such individuals may be at increased risk for nicotine addiction and for greater difficulties in smoking cessation. The Pharmacogenomics Journal (2011) 11, 45–52; doi:10.1038/tpj.2010.15; published online 16 March 2010

Keywords: nicotine; nicotinic acetylcholine receptor genes; attention; response-inhibition; smoking; women

Introduction

It is estimated that 29% of the world’s population aged 15 and over smoke cigarettes daily. Although smoking prevalence is four times higher among men than women the decrease observed in recent years in high-income countries1,2 Received 28 July 2009; revised 16 October 3 2009; accepted 7 February 2010; published including Israel is greater among men. In most European countries teenage girls online 16 March 2010 are as likely to smoke as boys, if not more so.4 These findings replicate previous Nicotine effects on attention A Rigbi et al 46

surveys.5–7 They indicate that in spite of growing awareness between smokers and non-smokers in Yakir et al.10 (n ¼ 108), of the health hazards, cigarette smoking remains a signifi- with priority for the 100 who had also been genotyped for cant public health problem. In high-income countries there nAchR gene variants;8 (2) continued to smoke currently; is a specific concern among young women. In 2002, the and, (3) were competent and willing to give written Biological Psychiatry Laboratory, Department of Psychiatry, informed consent. Forty-four of the potential participants Hadassah-Hebrew University Medical Center launched the were ineligible because of smoking cessation (28), preg- ‘Why Do Young Women Smoke?’ (WDYWS) project to nancy/breastfeeding (5), substance abuse (4, self-report of identify factors that predispose to smoking initiation and using any drug apart from cannabis and/or using cannabis nicotine dependence in young, Israeli women.8–12 twice a week or more) or medical/psychiatric condition;7 15 It is well established that nicotine has a small but refused to participate and 15 did not reply to the invitation; significant short-term, facilitating effect on attention.13–17 34 were recruited of whom 31 completed both arms of In pathological states characterized by cognitive deficits the study. nicotine appears to have a stronger facilitating effect on cognitive function.18–22 Moreover, smoking occurs at higher Instruments of evaluation rates than in the general population among individuals with Background measures. Questionnaires completed in the schizophrenia and Attention Deficit/Hyperactivity Disorder WDYWS project covering background information, life (ADHD)23–24 who may smoke more because nicotine helps experience and smoking behavior and the Fagerstro¨m them to cope with cognitive deficits that characterize these Tolerance Scale for Nicotine Dependence31 were re- states. In the WDYWS sample, Yakir et al.10 showed that administered to obtain information on variables subject to current and past smokers made more errors on tests of change during the 6 years since initial recruitment. attention and response-inhibition than non-smokers and suggested that a priori attention deficits lead to a greater risk Cognitive battery. We used the CogScan battery (V4.0) for developing nicotine dependence. On the basis of the role provided by AnimaScan, Ashdod, Israel.32 The tests re- of nicotinic acetylcholine receptors (nAChRs) in mediating administered were those that yielded a significant the physiological, behavioral and cognitive effects of association among smoking status, genetic profile and nicotine,25 Rigbi et al.12 examined interactive effects cognitive performance in Rigbi et al.12—the MFFT, Tower of smoking status and nAChR gene variants. A plethora of of London and Continuous Performance Task (CPT). studies have associated nAChR gene variation and nicotine dependence;26 fewer have sought association with cognitive Subjective measures of attention deficit and impulsivity. Brown function.27–30 Rigbi et al.12 demonstrated a significant effect Attention Deficit Disorder Rating Scale for Adults, the Adult of SNPs and haplotypes in several nAchR genes on tests that ADHD Rating Scale and the Barratt Impulsiveness Scale33–35 reflect attention and response-inhibition and were shown (see Supplementary Methods for detailed description and by Yakir et al.10 to differentiate young women who smoked psychometric properties of the evaluation instruments cigarettes regularly or had done so in the past from young above). women who had never smoked. In several cases there was an interaction with smoking status; in some a particular genetic Genotyping. Genotypes were available from Greenbaum variant had effects that were different in direction in the et al.8 for 24 participants. The genetic variants analyzed group of smokers (current or past) compared with young were those that remained significant in the regression women who had never smoked. models applied by Rigbi et al.,12 that is significantly The hypotheses of this study were that (1) exogenous predicted cognitive performance on the MFFT, Tower of nicotine administration would improve functioning on London and CPT within the smokers group (Table 1) (see tasks that measure attention and response-inhibition in Supplementary Methods for detailed description of young women who smoke cigarettes on a regular basis and genotyping). were found (10) to manifest relatively poor performance on these tasks, and that (2) nAChR gene variants found to Urine cotinine levels. Urine cotinine levels were assayed in modify cognitive performance among cigarette smokers (12) the laboratories of the Association for Public Health Services, would interact with nicotine to alter cognitive performance Tel-Aviv, Israel using DRI Cotinine Assay kits (Microgenics in the direction of the main and previously observed Corporation, Fremont, CA, USA). Cotinine is a nicotine interactive effects with smoking status. metabolite (half-life B16 h) produced by the liver enzyme CYP2A6, widely used as a quantitative marker for nicotine exposure.36 Materials and methods Mode of nicotine delivery Participants Cigarettes are problematic as a mode of nicotine delivery Participants were re-recruited from current smokers in the because the amount of nicotine administered cannot be WDYWS sample who had undergone cognitive testing and controlled and an effective placebo group cannot be (1) had error scores X5 on the Matching Familiar Figures created.13 Although nicotine patch contains more nicotine Test (MFFT), which yielded the most robust differences than gum and both patch and nicotine nasal spray have

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Table 1 Selected SNPs and haplotypes

Gene SNP/haplotype Alleles Cognitive test (major, minor) associated to variant

CHRN-A2a rs-2891398 T,C MFFT CHRN-A4 rs-2273502 C,T TOL CHRN-A6 rs-2217732 A,G CPT rs-1072003 C,G CPT CHRN-A7 rs-2337980 C,T MFFT rs-883473 C,T TOL CCCT TOL CTTT CPT CHRN-A10 rs-2741868 A,T CPT rs-4575304 A,G CPT CHRN-B2 rs-4845652 C,T TOL rs-12072348 A,C CPT CACCA MFFT CHRN-B3 rs-2304297 G,C CPT rs-9298629 G,T CPT ACAG CPT

Abbreviations: CPT, Continuous Performance Task; MFFT, Matching Familiar Figures Test; TOL, Tower of London. aCholinergic nicotinic receptor. better bioavailability, nicotine gum (‘Nicotinell’ (Novartis, Basel, Switzerland) containing 4 mg of nicotine) was used for this study because time to reach maximum concentration can extend up to 12 h using a patch compared with 30 min when using a gum37 and the maximum nicotine concentration with nasal spray is smaller than with gum (5–8 ng mlÀ1 compared with 10–17 ng mlÀ1).37 Placebo gum was supplied by Novartis, Petah-Tikva, Israel (see Supplementary Methods Figure 1 Study procedure. for more details on the nicotine gum).

Procedure Data analysis Participants were tested in counterbalanced placebo and Repeated measures ANCOVA (SPSS 15, SPSS, Chicago, IL, nicotine conditions (mean interval: 9±4 days) and were USA, 1989–2003) were used to test the main hypothesis randomized, double-blind, to receive nicotine or placebo in regarding the effect of experimental condition on cognitive the first session. Participants were directed to avoid alcohol functioning. Within (experimental condition)-between (ge- and/or cannabis 24 h before sessions and coffee, juices or netic variance) ANCOVA was used to test the secondary fizzy drinks 15 min before as these may reduce the absorp- hypothesis of interaction between genetic variance and tion of nicotine from the gum. Participants could smoke experimental condition on cognitive functioning. The freely before the sessions. To control for nicotine abstinence, Greenhouse–Geiser correction was applied for the within- they were asked to smoke their last cigarette no earlier than subject effects. Cronbach’s a coefficient was used for 2 h before.38 Participants who had smoked their last assessing reliability. Principal component analysis was used cigarette more than 2 h before a session could choose for data reduction. Factor loading was determined by between smoking a cigarette and quitting the session. Two absolute factor scores of 0.4 and above.39 participants chose to quit. One participant vomited after the administration of nicotine gum and was dropped from the experiment. At the beginning of each session, blood Results pressure (BP) and heart rate (HR) were recorded and urine samples were obtained (Figure 1). The participants then Background variables received a detailed explanation of how to chew the gum and Descriptive statistics for relevant background variables are possible side effects that might occur. After 30 min the gum presented in Table 2. The sample consisted of smokers was discarded. BP and HR were recorded and the participants with medium–high nicotine dependence and B11 years performed the three cognitive tests (MFFT, Tower of London mean duration of smoking, a low level of subjective ADHD and CPT) consecutively in counterbalanced manner. When symptoms and mild caffeine, cannabis and alcohol the test sessions were over, HR and BP were again recorded. consumption. There was no significant difference between

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Table 2 Background variables for the 31 participants who completed both arms of the study

Variable Mean±s.d. Median Min–max n (%)

Age 28±1.77 28 24–31 No. cigarettes per day 15±6.20 15 5–30 Years of smoking 11.30±2.55 11 8–17 FTNDa 6.52±1.78 7 3–9 No. cups of coffee per day 2.00±1.76 2 0–5 Brown ADD Scaleb 29.67±15.30 28.5 6–64 ASRS ADHD Scalec 1.35±1.30 1 0–5 BIS Impulsivity Scale 61.19±11.18 60 41–85

Cannabis consumption Ever used 11 (36.7) Never used 19 (63.3)

Alcohol consumption Once a week or more 17 (56.7) Less than once a week 13 (43.3)

Abbreviations: ADHD, Attention Deficit/Hyperactivity Disorder; ASRS, the Adult ADHD Rating Scale; BIS, Barratt Impulsiveness Scale; Brown ADD Scale, Brown Attention Deficit Disorder Rating Scale for Adults; FTND, Fagerstro¨m Tolerance Scale for Nicotine Dependence. aHigh nicotine dependence cut-off X7. bADD cut-off X45. cADHD cut-off X4. sessions for the mean time interval since last cigarette and 680.47±419.44 ng mlÀ1, respectively. Both results were smoked (nicotine: 70.47±27.88; placebo: 76.87± positive for urine cotinine based on the assay’s cut-off value 32.91 min) and mean number of sleep hours before session of 500 ng mlÀ1. No significant difference in cotinine levels (nicotine: 6.48±1.58; placebo: 6.95±1.29). Owing to the was found across conditions. high inter-correlations between the subjective attention (the Adult ADHD Rating Scale, Brown Attention Deficit Disorder Effect of nicotine on attention and impulsivity Rating Scale for Adults) and impulsivity (Barratt Impulsive- Descriptive statistics of the cognitive performance measures ness Scale) measures (X0.60, Cronbach a ¼ 0.61), principal under nicotine and placebo are shown in Table 3. Repeated component analysis was performed showing that all three measures ANCOVA was performed with condition (nicotine/ measures were highly loaded on one factor with loadings placebo) serving as the independent variable and the 40.80. This was termed ‘Attention-Impulsivity Factor’ (A-I) relevant operational measures in each of the three cognitive and was scored by transforming the Brown Attention Deficit tasks serving as dependent measures. Each analysis con- Disorder Rating Scale for Adults, the Adult ADHD Rating trolled for (1) A-I factor because of the associations Scale and Barratt Impulsiveness Scale scores into z-scores among smoking, ADHD and attention-related cognitive and summing them into one composite score.39 performance; (2) Fagerstro¨m Tolerance Scale for Nicotine Dependence (FTQ) score because nicotine gum might affect Physiological measures participants who are more addicted to nicotine differently Figure 2 (a–c) shows systolic BP, diastolic BP and HR for both compared with participants who are less addicted to it. In conditions within three time-points during the two experi- addition, univariate correlation analysis was performed mental sessions. HR linear decrement was significant within between the cognitive measures and the following back- the nicotine (Overall: F ¼ 4.17; df ¼ 2, 56; P ¼ 0.02; Contrast ground variables: hours of sleep prior session; smoking analysis: beginning of session-end of session time-points: latency prior session; urine continine level of session; age; F ¼ 8.36; df ¼ 1, 28; P ¼ 0.007) and placebo (Overall: number of cigarettes smoked per day; number of coffee cups F ¼ 15.52; df ¼ 2, 56; P 0.0001; Contrast analysis: begin- o consumed per day; cannabis consumption; and alcohol ning of session-after gum time-points: F ¼ 27.86; df ¼ 1, 28; consumption. Any variable showing a significant associa- P 0.0001; beginning-end of session time-points: F ¼ 17.66; o tion with the cognitive measures in both conditions (that is df ¼ 1, 28; P 0.0001). Systolic and diastolic BP were not o nicotine or placebo) was entered as an additional covariate significant along time-points in both conditions. Compar- (see Supplementary Table 1). Overall, there was no direct ison of time-points between conditions showed higher effect of condition; however, the following modifying diastolic BP for nicotine after chewing the gum and at the effects were found (Supplementary Table 2 for all effects): end of the experiment (t ¼ 2.46, 2.74; df ¼ 30, 27; P ¼ 0.02, 0.01, respectively) and faster HR after chewing the gum 1. On the MFFT a significant condition by A-I factor effect

(t ¼ 2.95, df ¼ 30; P ¼ 0.006). Mean urinary cotinine levels in on the number of errors was found (F(1, 28) ¼ 4.50, the nicotine and placebo conditions were 690.88±550.15 P ¼ 0.04). Inspection of the association between number

The Pharmacogenomics Journal Nicotine effects on attention A Rigbi et al 49

(F(1, 26) ¼ 7.23, P ¼ 0.01). Inspection of the association between SD of RT in each condition and coffee consumption showed a significant correlation between the coffee consumption and the difference in SD of RT between the conditions (r ¼ 0.40, P ¼ 0.02), indicating that nicotine administration decreases SD of RT (that is better performance) more the more coffee the participants consume. 3. On the CPT-Loading phase a significant condition by FTQ

score effect on SD of RT was found (F(1, 25) ¼ 4.68, P ¼ 0.04). Inspection of the association between SD of RT in each condition and the FTQ score showed a significant correlation between the FTQ and the difference in SD of RT between the conditions. However, this was limited to those participants who reported high nicotine dependence (FTQX8, r ¼ 0.64, P ¼ 0.02), indicating that nicotine administration decreases SD of RT (that is better performance) specifically for those participants reporting high nicotine dependence. 4. Moreover, on the CPT-Loading phase a significant condition by A-I factor score effect on the number of

commissions was found (F(1, 27) ¼ 6.98, P ¼ 0.01). Inspec- tion of the association between number of commissions in each condition and the A-I factor score showed a significant correlation between the A-I score and the difference in commission between the conditions (r ¼ 0.38, P ¼ 0.03), indicating that nicotine administration decreases the number of commissions more the higher the participants scored on the A-I factor (that is reported more symptoms of ADHD and impulsivity). Figure 3 (a–d) shows the nature of the modified effects of condition on cognitive performance. The modifying variables (x axis) are presented as dichotomous variables, despite of being analyzed as continuous variables, to clarify and simplify the effects found.

Figure 2 Effect of condition on HR (a), systolic (b) and diastolic BP (c) Interaction with nAChR gene variants within three time-points between experimental conditions. Comparison The hypothesis tested was that participants who carry an of time-points between conditions showed higher diastolic BP for nAChR genetic variant that was associated with worse nicotine after chewing the gum and at the end of the experiment and cognitive performance in Rigbi et al.12 would benefit more faster HR after chewing the gum. ** (a) and (c) effect is significant at from nicotine than participants who do not (Supplementary P 0.01. y axes (a–c): mean±s.e. (The color reproduction of this figure p Table 3 shows the associations between the SNPs tested and is available on the html full text version of the manuscript.) background variables). Eleven SNPs and four haplotypes were tested under this hypothesis (Table 1) by entering as factors into the main hypotheses multivariate models. of errors in each condition and the A-I factor score Figure 4 presents the significant condition by genotype showed a significant correlation between the A-I score interaction effect on MFFT errors that was found for SNP and the difference in errors between the conditions rs2337980 in CHRNA7 and is in the hypothesized direction.

(r ¼ 0.38, P ¼ 0.03), indicating that nicotine administra- Controlling for A-I factor and FTQ scores (F(1, 19) ¼ 4.35, tion decreases the number of errors more the higher the P ¼ 0.05), CC genotype carriers (n ¼ 8) made fewer errors participants scored on the A-I factor (that is reported under nicotine compared with placebo whereas CT/TT more symptoms of ADHD and impulsivity). carriers (n ¼ 16; 10,6 respectively) were more indifferent to 2. On the CPT-Boring phase a significant condition by condition. Other SNPs/haplotypes did not reach a signifi- coffee consumption effect on the standard deviation of cant interaction effect with condition or could not be reaction time for correct responses (SD of RT) was found analyzed because of small samples within genotypes.

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Table 3 Descriptive statistics of cognitive tests

Test and test measure n Nicotine Median Min–max Placebo Median Min–max mean±s.d. mean±s.d.

MFFT No. of errorsa 31 3.35±3.37 2.00 0–15 3.68±3.00 3.00 0–15 Reaction time of first response (s) 31 10.39±5.82 7.80 2.6–22.8 11.04±8.72 8.20 1.4–38.8

TOL No. of oversteps 31 4.71±8.19 1.00 0–31 3.61±4.91 2.00 0–24 Reaction time (s) 31 8.16±3.17 7.45 4.81–21.22 8.07±2.00 7.51 4.97–13.70

CPT-Boring phase Reaction time (ms) 31 371.67±67.14 359.60 273.2–545.3 370.36±65.04 350.60 279.4–507 s.d. of reaction time (ms)a 31 58.28±19.11 54.00 26.7–95 57.31±29.00 53.20 27.9–173 No. of commissions 31 0.39±0.61 0.00 0–2 0.19±0.74 0.00 0–4 No. of omissions 31 0.06±0.25 0.00 0–1 0.06±0.25 0.00 0–1

CPT-Loading phase Reaction time (ms) 31 331.75±73.49 318.20 242.5–570.6 327.71±62.66 318.20 250.3–517.6 s.d. of reaction time (ms)a 31 62.61±23.54 58.40 32.1–116.7 70.89±28.59 61.20 33.8–165.7 No. of commissionsa 31 1.90±2.42 1.00 0–9 1.71±2.03 1.00 0–9 No. of omissions 31 0.58±1.85 0.00 0–10 0.35±0.87 0.00 0–4

Abbreviations: CPT, Continuous Performance Task; MFFT, Matching Familiar Figures Test; TOL, Tower of London. aMeasures that yielded condition x covariate interaction effect.

Figure 3 Effect of nicotine on (a) MFFT errors controlled for A-I Factor; (b) CPT-Boring SD of RT controlled for coffee consumption; (c) CPT-Loading SD of RT controlled for FTQ score and; (d) CPT-Loading commissions controlled for A-I factor. ANCOVA showed greater number of MFFT errors (a) and CPT commissions (d) under placebo within participants reporting greater ADHD symptomatology and greater level of unstable performance in the CPT under placebo within participants reporting of consuming more caffeine (b) and nicotine (c). Splits are based on ANCOVA results. All effects were significant at Pp0.05. y axes (a–d): mean±s.e. (The color reproduction of this figure is available on the html full text version of the manuscript.)

The Pharmacogenomics Journal Nicotine effects on attention A Rigbi et al 51

variation, cognitive performance or level of modifying variables is very limited and associations do not withstand correction for multiple testing. Second, nicotine gum contains a smaller amount of nicotine than cigarettes;37 however, 4 mg is the maximum nicotine concentration available commercially. Moreover, placebo gum does not match perfectly in taste; however, overcoming the taste dissimilarity by adding an external flavoring agent,46 may affect the chemical/pharmacological properties of the gum and reduce participants’ compliance. Third, blood nicotine levels were not assessed. However, the physiological effects of nicotine on BP and HR indicate that the gum did cause the expected physiological effect compared with placebo. Notwithstanding these limitations, the study sheds light on the interplay between attention-related cognitive performance, genetic make-up and smoking. Subject to verifica- tion in a larger sample, the results suggest that nicotine, as a short-term facilitating agent for attention and response- Figure 4 Interaction between condition and genotype in SNP A7- inhibition, may have stronger effects in individuals who rs2337980 controlling for A-I factor in relation to MFFT errors. ANCOVA have more attention deficit symptoms and tend to consume showed that participants carrying CC genotype make more MFFT errors more CNS stimulants such as nicotine and caffeine. In under placebo compared with participants carrying CT/TT genotypes. addition, this effect can be modified by a specific genetic Interaction is significant at Pp0.05. y axis: mean±s.e. (The color reproduction of this figure is available on the html full text version of the make-up that is related to poorer performance on attention manuscript.) and response-inhibition functions. Such individuals may be at greater risk for developing nicotine addiction and for experiencing of more difficulties in smoking cessation.

Discussion Conflict of interest The results of this study show that nicotine does not have an omnibus facilitating effect on the functioning of young The authors declare no conflict of interest. female smokers on attention and response-inhibition- related tasks but improves performance of those who report Acknowledgments more attention deficit symptoms, greater nicotine dependence and greater consumption of coffee. The findings are This study was supported in part by a grant from the Professor in accordance with the consensus that the facilitating effect Milton Rosenbaum Endowment Fund for Research in the Psychiatric of nicotine on cognition is greater and more salient among Sciences (to YP). populations with attention deficits.18–22 Attention deficit symptoms, even below the clinical threshold, are signifi- References cantly associated with risk for smoking.40–42 Caffeine, 43 1 Anderson P. Global use of alcohol, drugs and tobacco. Drug Alcohol Rev another CNS stimulant, was also reported to be associated 2006; 25: 489–502. with smoking44 and to enhance attention performance, 2 World Health Organization. Report on the Global Tobacco Epidemic, although the results are less consistent than for nicotine.45 2008—the Mpower Package. World Health Organization: Geneva, The interaction found between nicotine administration Switzerland. (Available from: http://apps.who.int/bookorders/anglais/ detart1.jsp?sesslan=1&codlan=1&codcol=93&codcch=220) and genetic variation in CHRNA7 SNP rs2337980, where 3 Israel Ministry of Health. Minister of Health Report About Smoking in carriers of the CC variant benefited more from nicotine than Israel. Israel Ministry of Health: Jerusalem, Israel, 2007–2008. (Available CT/TT carriers, is as predicted by the findings of Rigbi et al.12 from: http://www.health.gov.il/download/pages/smoke18052009.pdf in which CC carriers manifested worse MFFT performance. (Hebrew)) 4 US Centers for Disease Control and Prevention. Global Youth Tobacco Compared with the number of studies relating variation in Survey. US Centers for Disease Control and Prevention (CDC): Atlanta, nAChR receptor genes to smoking behavior and nicotine GA, 2007. (Available from: http://www.cdc.gov/Tobacco/global/gyts/) dependence,26 the number of studies relating such varia- 5 Payne S. Gender in Lung Cancer and Smoking Research. World tions to attention deficit symptomatology42 or cognitive Health Organization, Department of Gender, Women, Health Family 28–30 and Community Health, 2005. (Available from: http://www.who.int/ performance is rather small and shows mixed results. gender/documents/LungCancerlast2.pdf) Thus, the genetic interplay between smoking, attention and 6 Israel Ministry of Health. Minister of Health Report About Smoking nAChR variation requires additional research. in Israel. Israel Ministry of Health: Jerusalem, Israel, 2004–2005. Our findings have several potential limitations. First, the (Available from: http://www.health.gov.il/download/forms/a2752_ ALL_310705.pdf (Hebrew)) sample was relatively small; thus, the possibility of splitting 7 Israel Ministry of Health. Minister of Health Report About Smoking it into sub-groups of interest according to specific genetic in Israel. Israel Ministry of Health: Jerusalem, Israel, 2002–2003.

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