Abstract Introduction Nicotine acts as an agonist at presynaptic nicotinic acetylcholine receptors and to facilitate synaptic release of several neurotransmitters including dopamine and glutamate. The thalamus has the highest density of nicotinic acetylcholine receptors in the brain, which may make this area more vulnerable to the addictive effects of nicotine. However, the volume of thalamus abnormalities and the association with smoking behaviors in young smokers remains unknown. Methods Thirty-six young male smokers and 36 age-, gender- and education-matched nonsmokers participated in the current study. The nicotine dependence severity and cumulative effect were assessed with the Fagerström test for nicotine dependence (FTND) and pack-years. We used subcortical volume analyses method in FreeSurfer to investigate the thalamus volume differences between young smokers and nonsmokers. Correlation analysis was used to investigate the relationship between thalamus volume and smoking behaviors (pack-years and FTND) in young smokers. Results and Conclusions Relative to nonsmokers, the young smokers showed reduced volume of bilateral thalamus. In addition, the left thalamus volume was correlated with FTND in young smokers. It is hoped that our findings can shed new insights into the neurobiology of young smokers. Implications In this article, we investigated the changes of thalamus volume in young male smokers compared with nonsmokers. Reduced left thalamus volume was correlated with FTND in young smokers, which may reflect nicotine severity in young male smokers. Introduction As the leading preventable cause of disease and death,1 smoking was associated with the high risk of several serious diseases, such as cardiovascular diseases2 and chronic obstructive pulmonary diseases.3 Interestingly, approximately 80% of adult smokers have progressed to nicotine dependence by 18 years of age, and people who do not start smoking as teenagers are unlikely ever to do so.4 Developmental plasticity renders the brain of adolescents and young adults vulnerable to the effects of nicotine and smoking.5 During this special development period, the brain of adolescents continues to develop structurally and functionally,6 which has been implicated as a cause of maladaptive decision making associated with immature cognitive control.7 Nicotine exposure during adolescence has been linked to subsequent deficits in brain circuits of attention and memory.8 As the largest consumer of cigarette, China has 350 million smokers including 14 million young smokers (www.chinacdc.cn). The Chinese Center for Disease Control and Prevention announced the latest national survey of youth smoking in May 2014, which reported that the smoking rate of junior high school students was 10.6% for males and 1.8% for females in China (http://www.chinacdc.cn/). Based on global smoking patterns, 88% of adult smokers begin smoking by the age of 18 and 99% by the age of 26.9,10 Young smokers are more likely to become life-long smokers and are more susceptible to nicotine addiction than adults.11 Nicotine exposure during prenatal or adolescent period may disrupt brain development to manifest as disturbances in cognitive functioning and behavioral changes.12–14 In the period from late adolescence to young adult, important changes in brain maturation occur, which may be especially sensitive to environmental perturbations and to nicotine exposure through cigarettes.15 However, very little is known about alterations in brain structure that may occur in young smokers, especially for the volume of thalamus and its association with smoking behaviors. Therefore, it is of great significance to investigate the underlying neural mechanisms of young smokers. Nicotine plays a critical role in the highly addictive properties of tobacco use.16 Acting as an agonist at presynaptic nicotinic acetylcholine receptors (nAChRs), nicotine facilitates synaptic release of several neurotransmitters including dopamine and glutamate.17 It is noteworthy that the thalamus has the highest density of nAChRs in the brain, which may make this area more vulnerable to the addictive effects of nicotine.17,18 The gray matter density and volume of thalamus abnormalities of smokers were discussed in previous voxel-based morphometry (VBM) studies.19–21 Nevertheless, the study by Brody et al.22 showed no differences of gray matter in the thalamus between smokers and nonsmokers. VBM studies were sensitive to a combination of changes in gray matter thickness, intensity, cortical surface area, and cortical folding, and may suffer from several limitations, like the degree of smoothing, registration techniques, and choice of normalization templates.23–25 Measurements of cortical thickness and subcortical volumetric segmentation are other methods of detecting GM structural changes in the FreeSurfer (http://surfer.nmr.mgh.harvard.edu).26 However, few studies used subcortical volumetric segmentation method to investigate the volume changes of the thalamus in young smokers. Therefore, we investigated the thalamus volume differences between young adult smokers and nonsmokers by subcortical volumetric segmentation method in the current study, which has proved to be more sensitive to the changes of thalamus than VBM.27–31 Moreover, we assessed the relationship between structural changes in the thalamus and the characteristic of young smokers. Pack-years may reflect the cumulative effect of smoking and Fagerström test for nicotine dependence (FTND) may reflect the severity of smoking. We hypothesized that abnormal thalamus volume would be detected in young smokers and these changes would be associated with smoking behavior. Materials and methods The study was approved by the Ethical Committee of Xi’an Jiaotong University and was conducted in accordance with the Declaration of Helsinki. All subjects and their legal guardians gave written informed consent prior to participation in the study. Participants Thirty-six male, right-handed subjects and 36 age- and education-matched male nonsmokers were recruited from the local university. All young smokers were screened according to the DSM-V criteria for current nicotine dependence as described in our previous studies.28,31–34 The participants did not smoke other products besides cigarettes (eg, e-cigarettes, cigars). Nicotine dependence severity was assessed with FTND.35 All smokers consumed more than 10 cigarettes per day in the last 6 months with expired air carbon monoxide (CO)>6 parts per million (ppm). Additionally, none of smokers had attempted to quit smoking or undergo smoking abstinence for longer than 3 months in the past year. The nonsmokers had smoked less than 5 cigarettes in their lifetime with expired CO≤3 ppm. Exclusion criteria for both groups were as follows: (1) any physical illness such as a brain tumor, obstructive lung disease, hepatitis, or epilepsy as assessed according to clinical evaluations and medical records; (2) any current medications that may affect cognitive functioning; (3) alcohol or drug abuse;(4) existence of a neurological disease; (5) claustrophobia; and (6) any participants with psychiatric disorder as assessed by the structured clinical interview for DSM-V. To remove the possible effect of other addiction, the exclusion criteria for both groups included any drug abuse, and tobacco and alcohol intake. Detailed demographic data are shown in Table 1. Table 1. Clinical Details of Young Smokers and Nonsmokers Clinical details Smokers (n = 36) Nonsmokers (n = 36) P-value Age (years) 20.8 ± 1.8 20.1 ± 1.2 0.22 Age range (years) 16–24 16–23 Education (years) 13.5 ± 1.3 13.3 ± 0.6 0.21 Age at start of smoking 15.1 ± 2.6 – – Cigarettes smoked per day 15.4 ± 4.5 – – Pack-years 3.5 ± 2.3 – – FTND 5.0 ± 1.9 – – Clinical details Smokers (n = 36) Nonsmokers (n = 36) P-value Age (years) 20.8 ± 1.8 20.1 ± 1.2 0.22 Age range (years) 16–24 16–23 Education (years) 13.5 ± 1.3 13.3 ± 0.6 0.21 Age at start of smoking 15.1 ± 2.6 – – Cigarettes smoked per day 15.4 ± 4.5 – – Pack-years 3.5 ± 2.3 – – FTND 5.0 ± 1.9 – – Data are means ± standard deviations. Pack-years = Years of smoking × Cigarettes smoked per day/20; FTND = Fagerström test for nicotine dependence. View Large Data Acquisition All MRI images were acquired using a 3-T MRI system (EXCITE, General Electric, Milwaukee, WI) at the First Affiliated Hospital of the Medical College, Xi’an Jiaotong University, China. A standard birdcage head coil was used, along with restraining foam pads, to minimize head motion and to diminish scanner noise. High-resolution 3D T1-weighted images were acquired for subcortical volume measurements with the following parameters: repetition time = 8.5 ms; echo time = 3.4 ms; flip angle = 12°; field of view = 240 × 240 mm2; data matrix = 240 × 240; slices = 140; and voxel size = 1 × 1 × 1 mm3. To prevent the potential effect of brain damage on results, for each subject, two neurologists examined the T1-weighted 3D images for structural lesions in the brain and no subject was excluded. Data Analysis Subcortical volumetric segmentation of the whole brain was performed with the FreeSurfer software package (Version 5.1.0, http://surfer.nmr.mgh.harvard.edu), which had been used widely in our previous studies.27,29–31,36 In more detail, the preprocessing was as follows: (1) removal of nonbrain tissue; (2) automated Talairach transformation; (3) segmentation of the subcortical white matter and deep gray matter volumetric structures; (4) intensity normalization; (5) tessellation of the gray matter/white matter boundary; (6) automated topology correction; (7) surface deformation; and (8) registration of the subjects’ brains to a common spherical atlas. The results implemented in the Freesurfer analysis were checked by a neurologist and manual adjustments were carried out if necessary. The thalamus was extracted according to Harvard subcortical structural atlas (http://www.cma.mgh.harvard.edu/). After the preprocessing, the volumes of bilateral thalamus and intracranial volume (ICV) were extracted and imported into SPSS 20.0 software for statistical analyses (SPSS Statistics, IBM, Armonk, NY). For each structure, a general linear model was fit with volume as the dependent variable, diagnosis (young smokers and nonsmokers) as the categorical predictors, and ICV as covariates. To correct for multiple comparisons, the Bonferroni correction was used. All tests were two-tailed, and the level of significance was p < 0.025 (0.05/2). Pearson correlation was applied between the absolute volumes of bilateral thalamus and smoking variables (pack-years and FTND). To correct for multiple comparisons of correlation analysis, the Bonferroni correction was also used (p < 0.0125 (0.05/4)). Results No significant ICV difference (p > 0.05) between the young smokers (1149060 ± 209249 mm3) and nonsmokers (1106206 ± 149594 mm3) was shown. Relative to nonsmokers, young smokers showed reduced volume in the left thalamus (F = 17.277, p < 0.001, Bonferroni correction), after controlling ICV as the covariate. Similarly, decreased volumes of the right thalamus (F = 14.617, p < 0.001) in young smokers were also observed when compared with nonsmokers (Figure 1). Correlation between smoking and body weight has been documented, for example, in the short term, nicotine increases energy expenditure and smokers tend to have lower body weight than nonsmokers and gray matter volume of thalamus is also associated with body weight status.37,38 To exclude the possible effect of BMI on our results, we analyzed the thalamus volume differences controlling the BMI as covariates and found reduced volume of left thalamus (F = 16.4, p < 0.001, Bonferroni correction) and right thalamus (F = 14.1, p < 0.001, Bonferroni correction) in young male smokers. Moreover, correlation analysis results showed that the volume of left thalamus was negatively correlated with FTND in smokers (r = -0.4285, p = 0.0091) (Figure 2). The volume of left thalamus was also negatively correlated with pack-years in smokers (r = -0.4031, p = 0.0148). With regard to the right hemisphere, the volume of right thalamus was negatively correlated with pack-years (r = -0.3604, p = 0.0309) and FTND ( = -0.3482, p = 0.0374) in smokers, although the results did not survive the Bonferroni correction. Figure 1. View largeDownload slide Relative to nonsmokers, young smokers showed reduced volume in left thalamus (F = 17.277, p < 0.001, Bonferroni correction), after controlling intracranial volume (ICV) as the covariates. Similarly, decreased volumes of right thalamus (F = 14.617, p < 0.001) in young smokers were also observed when compared with nonsmokers. Figure 1. View largeDownload slide Relative to nonsmokers, young smokers showed reduced volume in left thalamus (F = 17.277, p < 0.001, Bonferroni correction), after controlling intracranial volume (ICV) as the covariates. Similarly, decreased volumes of right thalamus (F = 14.617, p < 0.001) in young smokers were also observed when compared with nonsmokers. Figure 2. View largeDownload slide Correlation analysis results showed that (a) the volume of left thalamus was also negatively correlated with pack-years in smokers (r = −0.4031, p = 0.0148). (b) The volume of left thalamus was negatively correlated with FTND in smokers (r = −0.4285, p = 0.0091). (c) The volume of right thalamus was negatively correlated with pack-years (r = −0.3604, p = 0.0309). (d) The volume of right thalamus was negatively correlated with FTND (r = −0.3482, p = 0.0374) in smokers. Although the results did not survive the Bonferroni correction. Figure 2. View largeDownload slide Correlation analysis results showed that (a) the volume of left thalamus was also negatively correlated with pack-years in smokers (r = −0.4031, p = 0.0148). (b) The volume of left thalamus was negatively correlated with FTND in smokers (r = −0.4285, p = 0.0091). (c) The volume of right thalamus was negatively correlated with pack-years (r = −0.3604, p = 0.0309). (d) The volume of right thalamus was negatively correlated with FTND (r = −0.3482, p = 0.0374) in smokers. Although the results did not survive the Bonferroni correction. Discussion Just as the adverse effects of smoking on general health are well known, there is a growing consensus that a long history of nicotine smoking is associated with alterations in neural tissue integrity throughout the frontal–striatal–thalamic circuits involved in cognitive control and reward processing.19,22,28,31,39 Recently, we detected the structural and functional abnormalities within the frontostriatal circuits in young smokers.28,31,33 For instance, reduced cortical thickness of the prefrontal cortex and increased caudate volume were observed in young adult smokers.28 The resting state functional connectivity between dorsolateral prefrontal cortex and striatum (caudate) was disrupted and correlated with the cognitive control deficits in young smokers.31 In contrast, few studies focused on the implication of the volume of thalamus with smoking behaviors in young smokers. In the current study, we contributed toward filling this gap by revealing the reduced volume of bilateral thalamus in young smokers compared with nonsmokers (Figure 1). Moreover, the volume of left thalamus was correlated with the FTND in young smokers, which suggested that reduced thalamus volume may be related to nicotine severity in young smokers (Figure 2). Although the structural deficits of thalamus in smokers had been revealed in previous VBM studies,19,20 there were some inconsistent results, that is, no differences of gray matter in the thalamus between smokers and nonsmokers.22 This may be due to the sample size, different age range of participants, and the choice of VBM. Therefore, in current study, we enrolled a relatively homogenous sample of young smokers and employed a more sensitive parameter (subcortical volume) to assess the thalamus volume changes. Our results demonstrated that the bilateral thalamus showed reduced volume in young smokers (Figure 1). As the highly addictive property of tobacco use,16 nicotine facilitates synaptic release of several neurotransmitters by acting as an agonist at nAChRs.17 The thalamus has the highest density of nAChRs, which may render this area more vulnerable to the addictive effects of nicotine.17,18 Previous studies had investigated functional changes in the thalamus and the association with the neurobiology of substance addiction including cigarette smoking.40,41 Nicotine can induce abnormal activation of the thalamus in smokers,18,42 which may suggest that nicotine is capable of influencing the function of thalamus. Evidence suggests that cigarette smoking plays a critical role in inducing changes in the thalamus. Thus, it is rational that the volume of thalamus would be different between the young smokers and nonsmokers. In current study, we also found that the volume of left thalamus was correlated with the FTND in young smokers (Figure 2). As the key nodes of frontal–striatal–thalamic circuits involved in cognitive control and reward processing43, the thalamus played several roles in smoking behaviors. There was a positive correlation between the increase of cerebral blood flow in the thalamus during abstinence and the abstinence-induced craving,41 and an inverse correlation between abstinence-induced global withdrawal symptoms and reductions in cerebral blood flow in the thalamus.44 Reactivity to smoking-related cues may be an important factor that precipitates relapse in smokers, which had been investigated in several fMRI studies.45 Smoking cues reliably evoke larger responses of thalamus in smokers.45 Recently, stronger resting state functional connectivity between thalamus and anterior cingulate cortex was associated with the increased risky decision making and severity of nicotine dependence in young smokers.46 Our results suggested that the volume of left thalamus can reflect the severity of nicotine dependence of young smokers. Evidently, more comprehensive experiment design is necessary to reveal the accurate role of the reduced volume of thalamus in young smokers. The cross-sectional design made it difficult to clarify any causal relationships. We could not be certain about whether the reduced volume of thalamus was a consequence of nicotine addiction or a cause of nicotine addiction. We cannot deny the possibility that the abnormalities in the thalamus may have existed even before they have begun smoking and potentially be a predisposing factor or marker of vulnerability to nicotine dependence. We only controlled the acute alcohol use and did not control the regular use. Moderate alcohol use can impact thalamic volume and that moderate alcohol use does not necessarily imply alcohol abuse. Given that smokers have higher rates of drinking, it seems reasonable to assume that the smoking group probably also drinks at higher levels/rates than the non-smoking group. The possible effect of alcohol use on the volume of thalamus in smokers should be investigated in the future. Previous study had demonstrated that adolescents with prenatal exposure to tobacco showed a trend toward smaller volumes in thalamus than their peers who were not exposed to prenatal tobacco.47 Moreover, adolescents with smaller volume of thalamus showed higher levels of impulsivity, a factor known to contribute to smoking initiation.19 Conclusion We validated the reduced volume of thalamus and its association with smoking behaviors in young smokers, that is the left thalamus volume may reflect the nicotine severity in young smokers. It is hoped that our findings can shed new insights into the neurobiology of young smokers. Funding This paper is supported by the National Natural Science Foundation of China under Grant nos. 81571751, 81571753, 81301281, 61502376, 81401478, 81401488, 81470816, 61431013, 81471737, 81271546, and 81271549; the Natural Science Basic Research Plan in Shaanxi Province of China under Grant no. 2014JQ4118; the Fundamental Research Funds for the Central Universities under the Grant nos. JBG151207, JB161201, JB151204, and JB121405; the Natural Science Foundation of Inner Mongolia under Grant no. 2014BS0610; the Innovation Fund Project of Inner Mongolia University of Science and Technology Grant Nos. 2015QNGG03 and 2014QDL002; and General Financial Grant of the China Post-doctoral Science Foundation under Grant no. 2014M552416. Declaration of Interests None. References 1. Bauer UE, Briss PA, Goodman RA, Bowman BA. Prevention of chronic disease in the 21st century: elimination of the leading preventable causes of premature death and disability in the USA. 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Nicotine and Tobacco Research – Oxford University Press
Published: Apr 1, 2018
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