Journal of Neurology and Neuroscience

  • ISSN: 2171-6625
  • Journal h-index: 15
  • Journal CiteScore: 2.13
  • Journal Impact Factor: 1.45
  • Average acceptance to publication time (5-7 days)
  • Average article processing time (30-45 days) Less than 5 volumes 30 days
    8 - 9 volumes 40 days
    10 and more volumes 45 days
20+ Million Readerbase
Indexed In
  • Open J Gate
  • Genamics JournalSeek
  • The Global Impact Factor (GIF)
  • China National Knowledge Infrastructure (CNKI)
  • Directory of Research Journal Indexing (DRJI)
  • OCLC- WorldCat
  • Proquest Summons
  • Scientific Journal Impact Factor (SJIF)
  • Euro Pub
  • Google Scholar
  • Secret Search Engine Labs
Share This Page
Recommended Webinars & Conferences

36th European Neurology Congress 2023

Amsterdam, Netherlands Antilles

Research Article - (2018) Volume 9, Issue 1

Lack of Association between DMT1 Polymorphism and Iron Overload in Chinese Patients with Parkinson’s Disease

Wei M1, Lou Y1, Tan YY1, Xiao Q1*, Hu YY2 and Zhan WW2

1Department of Neurology, Institute of Neurology, Ruijin Hospital affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, P.R.China

2Department of Ultrasound, Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, P.R. China

*Corresponding Author:

Xiao Q
Department of Neurology, Institute of Neurology
Ruijin Hospital affiliated to Shanghai Jiaotong University
School of Medicine, Shanghai, 200025, P.R. China
Tel: 13761095970
E-mail: [email protected]

Received date: January 12, 2018; Accepted date: February 21, 2018; Published date: February 26, 2018

Citation: Wei M, Lou Y, Tan YY, Xiao Q, Hu YY et al. (2018) Lack of Association Between DMT1 Polymorphism and Iron Overload in Chinese Patients with Parkinson’s Disease. J Neurol Neurosci Vol.9 No.1:249. doi: 10.21767/2171-6625.1000249

Visit for more related articles at Journal of Neurology and Neuroscience


Objective: Iron overload in the substantia nigra (SN) has been suggested playing a role in causing Parkinson’s disease (PD), but the underlying mechanism leading to iron accumulation is not clear. Divalent metal transporter 1 (DMT1), an endogenous transporter for ferrous iron, has been suggested being involved in iron metabolism in both animal model and PD patients. However, previous studies failed to reveal DMT1 as strong risk factor for PD patients. One reason might be that abnormal iron accumulation is not a universal pathogenesis for PD patients. This study aims to explore whether DMT1 is a risk factor for PD patients with or without iron overload.

Methods: Transcranial sonography (TCS) was used to classify PD patients into two subgroups, PD with SN hyperechogenicity (SN+) and PD without SN hyperechogenicity (SN-), to study the possible association between DMT1 gene variants and iron overload in PD patients. One mutation (1303C/A) and two single nucleotide polymorphisms (SNPs) (1254T/C and IVS4 + 44C/A) of DMT1 gene were tested in 67 PD SN+ patients and 53 PD SN- patients of Southern Han Chinese population by method of polymerase chain reactionrestriction fragment length polymorphism (PCR–RFLP).

Results: Distribution of Genotypes and allele frequencies of all these three sites didn’t show significant difference between PD SN+ and PD SN- patients. Haplotype analysis of 1254T/C and IVS4 + 44C/A didn’t reveal potential risk factor for iron overload.

Conclusion: Our results suggested that DMT1 gene variants (1303C/A, 1254T/C and IVS4 + 44C/A) are not correlated with iron accumulation in PD patients.


Parkinson’s Disease (PD); Iron overload; Divalent Metal Transporter 1 (DMT1); Single Nucleotide Polymorphism (SNP)


Parkinson’ disease (PD) is the most common movement disorder, characterized by degeneration of dopaminergic neurons in the substantia nigra (SN) of midbrain and the formation of intracytoplasmic inclusions called Lewy bodies (LBs) in the remaining dopaminergic neurons [1]. The pathogenesis of idiopathic PD has not been fully understood so far, but evidence suggests that abnormal aggregation of iron in SN perhaps have an important role in the etiology of idiopathic PD [2].

Brain iron abnormalities in SN were first observed in idiopathic PD patients about 90 years ago [3]. Subsequent studies also demonstrated an increase of total iron in SN [4-6], where dopaminergic neurons undergo selective degeneration. In 1995, Becker firstly described SN hyperechogenicity as a typical characteristic of idiopathic PD [7]. Hyperechogenicity was defined when the intensity of the ultrasound signal of the detected structure was abnormally increased compared with a reference structure, usually the surrounding white matter [8]. Related researches showed a sensitive and stable hyperechogenicity in idiopathic PD patients [9,10]. Animal studies and post mortem analyses of human brain tissue revealed that this hyperechogenicity is associated with increased iron levels of the substantia nigra [11,12].

To date, the mechanism of unusual aggregation of iron in SN is still an unsolved problem. The iron metabolism or homeostasis related genes such as, transferrin, transferrin receptor, iron responsive element binding protein 2 (IREB2), divalent metal transporter 1 (DMT1) and parkin [13] might change the expression or function of proteins involved in iron homeostasis, which might lead to iron abnormal accumulation in the brain. DMT1, also known as natural resistanceassociated macrophage protein 2 (NRAMP2), divalent cation transporter 1 (DCT1) or solute carrier family 11 member 2 (SLC11A2), is essential for dietary iron absorption and iron translocation from the endosome. Up-regulation of DMT1 in the SN of both MPTP-induced PD models and PD patients indicated that DMT1 might involve in the process of iron accumulation in SN [14,15] Previous studies failed to reveal DMT1 gene variants as strong risk factors for iron-related disease, such as PD, RLS and ALS [16-18]. But, haplotype analysis of 1254T/C and IVS4 + 44C/A showed that CC haplotype of DMT1 gene was a possible risk factor for PD in Han Chinese population [16]. Two DMT1 intronic SNPs (rs224589 and rs407135) showed positive association with RLS in patients with a history of anemia compared to RLS patients without anemia [17]. C allele of rs407135 in DMT1 was associated with shorter disease duration in sporadic ALS patients with onset in the legs [18]. Thus, these results suggested DMT1 gene variants were still candidates to explore the mechanism of abnormal iron accumulation in PD. However, abnormal iron accumulation is not a universal mechanism for all PD patients. Since hyperechogenicity is associated with increased iron levels, thus abnormal iron accumulation was more likely involved in those PD patients with SN hyperechogenicity than those PD patients without SN hyperechogenicity. In order to explore the possible association between DMT1 gene and abnormal iron accumulation, in our study, TCS was used to classify PD patients into two subgroups PD with SN hyperechogenicity (SN+) and PD without SN hyperechogenicity (SN-). One mutation (1303C/A) and two single nucleotide polymorphisms (SNPs) (1254T/C and IVS4 + 44C/A) of DMT1 was tested in these two groups.

Materials and Methods


A total of 120 idiopathic PD patients (90 male and 30 female) were recruited from the Movement Disorder Clinic at the Department of Neurology, Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine. Patients were divided into PD SN+ group (male 50, female 17, mean age: 65.3 ± 10.5 years) and PD SN-group (male 40, female 13, mean age 64.8 ± 10.9 years) according to TCS results. Two groups were matched for gender and age (Table 1), and none of them had a positive family history of PD. Patients with Parkinson’s-plus syndrome or secondary Parkinsonism was excluded. The clinical diagnosis of idiopathic PD was given by two independent movement disorder specialists according to the diagnosis criteria [19]. The study was approved by the Ethics Committee of Rujin Hospital.

Transcranial sonography

A color-coded phase array ultra-sound system (MyLab90, ESAOTE, Italy) with a 2.5 MHz phased-array transducer was used to the TCS examination for PD patients. The probe was placed consecutively at bilateral temporal bone windows, scanning supratentorial and infratentorial brain areas in axial planes. For this study, we mainly paid special attention to the mesencephalic brainstem. In general, hyper-echogenicity of the SN is stated if the SN shows a pathological signal at least on one side. An area of echogenicity [20] 0.18 cm2 was classified as normal (Figure 1a) and areas of echogenicity ≥ 0.18 cm2 was classified as hyperechogenic in either one or two sides in our research (Figure 1b). The examiners were ultrasound specialists blind to the clinical diagnosis.


Figure 1: Echogenicity examined by TCS in SN area. A. Midbrain was lined out. No obvious hyperechogenicity was detected in SN area. B. Peripheral line circled out midbrain. Inner line circled out hyperechogenicity in SN area.

Genetic analysis

Genomic DNA was extracted from peripheral blood leukocytes through standardized phenol/chloroform extraction method. Primers were designed using the Primer software. Genotyping for the DMT1 polymorphisms or mutations was conducted by polymerase chain reaction–restriction fragment length polymorphism (PCR–RFLP) method, alleles and genotypes frequencies were determined by direct sequencing. The PCR amplification was performed in a total volume of 20 μl reaction mixture, after an initial denaturation of 95 for 5 min, amplification was performed for 35 cycles at 95°C for 30s, 59°C for 30s and 72°C for 7 min and 16°C forever. After amplification, the PCR products were sequenced directly. The primers for each SNPS or mutation are listed below:

• IVS4+44C/A:

• The sense primer5

• The antisense primer5

• The product length is 351bp.

• 1254T/C and 1303C/A:

• The sense primer 5

• The antisense primer 5

• The product length is 362 bp.

Statistical analysis

All statistical analysis was performed using Statistic Package for the Social Science (SPSS) version 17.0 for Windows. Goodness-of-fit to the Hardy–Weinberg equilibrium was examined by chi-square test, and differences in genotype and allele frequencies between the SN+ and SN- groups were calculated and compared by Chi-squared or Fisher’s exact test. Exact logistic regression adjusted for age and gender was also used to analyze differences in genotype and allele distributions between two groups. Linkage disequilibrium (LD) and haplotype frequencies were analyzed by SHEsis software ( The P-value, odds ratios (OR) and 95% confidence intervals (CI) were estimated for the association between DMT1 polymorphisms and iron accumulation in PD. The statistical significance level was set at P value 0.05 for all the tests.


Clinical characteristics were shown in Table 1. SN+ PD patients and SN- PD patients were well matched in age (P=0.915), gender (P=0.772), age of onset (P=0.88), UPDRS III score (P=0.106), and Hoehn-Yahr stage (P=0.77).

 Variables SN+ PD patients SN- PD patients P value
Total sample 67 53  
Male 50 40  
Female 17 13 0.915
Age (year) 65.3 ± 10.5 64.8 ± 10.9 0.772
Age of onset (year) 59.4 ± 10.9 59.1 ± 11.3 0.88
UPDRS Ⅲ score 24.72 ± 12.9 28.72 ± 13.7 0.106
Hoehn and Yahr stage 2.09 2.13 0.77

Table 1: Demographic information (mean (standard deviation)) for young and elderly controls (HYC and HEC, respectively), and Parkinson’s (PD) and Essential tremor (ET) subjects.

Distributions of genotypes and allele frequencies of 1254T/C, IVS4+44C/A were in Hardy-Weinberg equilibrium (P>0.05). As shown in Table 2, no C→ A mutation at 1303 nucleotide was found in our study.

 Variables Genotype (n, %) P Allele (n, %) P
1303C/A CC CA AA   C A  
SN+ group 67 (100) 0 0 134 (100) 0
SN- group 53 (100) 0 0   106 (100) 0  
1254T/C TT TC CC   T C  
SN+ group 52 (77.6) 15 (22.4) 0 0.18 119 (88.8) 15 (11.2) 0.98
SN- group 43 (81.1) 8 (15.1) 2 (3.8)   94 (88.7) 12 (11.3)  
IVS4 + 44C/A CC CA AA   C A  
SN+ group 51 (76.1) 16 (23.9) 0 0.2 118 (88.1) 16 (11.9) 0.94
SN- group  42 9 (17) 2 (3.8)   93 (87.7) 13 (12.3)  

Table 2: Distribution of genotype and allele frequencies of the DMT1 gene mutations/polymorphisms in PD patients.

Genotypes and allele frequencies of 1254T/C and IVS4+44C/A didn’t show significant difference between SN+ and SN- PD groups. Haplotypes were analyzed between 1254T/C and IVS4+44C/A (D'=0.91, r2=0.77) and didn’t reveal any potential risk factor for abnormal iron accumulation as shown in Table 3.

Haplotype SN+ (%) SN- (%) χ2-test single statistics χ2-test global statistics OR [95%CI]
χ2 p χ2 p
CA 15 (11.2) 10 (9.4) 0.21 0.65 4.4 0.22 1.22 [0.52-2.83]
CC 0 (0) 2 (1.9) 2.61 0.11  --  -- --
TA 1 (0.7) 3 (2.9) 1.62 0.2  --  -- 0.25 [0.03-2.47]
TC 118 (88.1) 91 (85.8) 0.27 0.61  --  -- 1.22 [0.57-2.60]

Table 3: Distribution of haplotypes in SN+ and SN- PD patients.

Since age is an important factor in abnormal iron metabolism and accumulation, we tried to analyze our data by classifying PD patients into early onset Parkinson’s disease (EOPD, age of onset ≤ 50 years) and late onset Parkinson’s disease (LOPD, age of onset >50 years) respectively [21]. EOPD subgroup only has 15 SN+ patients and 13 SN- patients, thus distribution of genotypes and allele frequencies were analyzed in LOPD patients only. No significant difference was found between SN+ LOPD patients and SN- LOPD patients as shown in Table 4.

 Variables Genotype (n, %)   P Minor allele frequency (n, %) P
1254T/C TT TC CC   C  
SN+ LOPD 39 (75) 13 (25) 0   13 (12.5)  
SN- LOPD 33 (82.5) 6 (15) 1 (2.5) 0.23 8 (10) 0.60
IVS4 + 44C/A CC CA AA   A  
SN+ LOPD 38 (73.1) 14 (26.9) 0   14 (13.5)  
SN- LOPD 32 (80) 7 (17.5) 1 (2.5) 0.26 9 (11.3) 0.65

LOPD: Late Onset Parkinson’s Disease. SN+ LOPD: Late Onset Parkinson’s Disease With SN Hyperechogenicity SN- LOPD: Late Onset Parkinson’s Disease Without SN Hyperechogenicity

Table 4: Allele and genotype frequencies of 1254T/C, IVS4 + 44C/A in LOPD.

Exact logistic regression also showed that the results were not influenced by age, gender (P=0.845, P=0.637, respectively). Thus, our results didn’t reveal DMT1 as a risk factor for abnormal iron accumulation in PD patients.


Role of abnormal iron metabolism in PD arises from two lines of evidence. First, iron plays a key role in many crucial neuronal functions, such as oxygen transport, mitochondrial energy production, DNA synthesis and mitochondrial respiration [22]. Iron-induced oxidative stress, inflammatory stimulation, mitochondrial impairment, ubiquitin-proteasome system (UPS) dysfunction and alpha-synuclein aggregation are important factors to the nigral dopaminergic neuron degeneration [23].

Second, dysregulation of iron homoeostasis has been identified in PD. Mounting evidence shows that iron content dramatically increases in the substamtia nigra pars compacta (SNpc) rather than in other brain regions in idiopathic PD [6,24].

However, the mechanism for abnormal iron accumulation in SN is still not clearly understood so far. Dysregulation of influx proteins [25], blockade of axonal transport [26,27] and mitochondria abnormalities [25] could all contribute to abnormal iron metabolism. Related researches also proved that DMT1 involved in the process of iron accumulation in SN [14,15]. Up to now, five single nucleotide mutations or polymorphisms were identified within the DMT1 gene. Mutation 1303C→A occurs in the coding region of DMT1 and results in an amino acid change from leucine to isolecine. 1254T/C also occurs in the coding region of DMT1 but does not cause an amino acid change. The other three polymorphisms are within introns (IVS2  538G/Gdel) [28]. The previous functional and genetic studies of DMT1 make its polymorphic variants attractive candidates for the study of iron accumulation, but earlier reports failed to reveal DMT1 as strong risk factors in both PD and RLS patients. One reason for failing to find the association should be considered is that abnormal iron accumulation is not a universal pathogenetic mechanism to these diseases. Thus, it is reasonable to explore association of DMT1 and iron accumulation between PD patients with abnormal iron accumulation and PD patients without abnormal iron accumulation. Hyperechogenicity examined by TCS highly indicated iron overload [11,12]. In our study, one single nucleotide mutation (1303C/A) and two polymorphisms within DMT1 (1254T/C and IVS4+44C/A) were tested in PD SN+ patients and PD SN- patients. We did not find any significant association of DMT1 variants between patients with SN hyperechogenicity and those without SN hyperechogenicity in either genotypes or alleles frequencies of the three-tested locus. There was not any C →A mutation at 1303C/A nucleotide site detected in the present study. These results found in our study were consistent with previous study about DMT1 polymorphism and risk of Parkinson’s disease in Northern Han Chinese PD patients except that we didn’t reveal CC haplotype as a possible risk factor in haplotype analysis of 1254T/C and IVS4+44C/A sites as indicated by the above study [16]. As a matter of fact, CC haplotype is very rare in both SN+ PD paitents (0%) and SN- PD patients (1.9%) in our study, which is much lower than the above study conducted in Northern Han Chinese patients, 18.2% in PD patients and 11.4% in control. Regional difference (Southern vs Northern part of China) might be one reason for lower CC haplotype in our study. Another possible reason for failing to find correlation of DMT1 with abnormal iron accumulation might be that the sample size is not big enough in our study, but such a low CC haplotype in our study subjects largely limits its potential clinical importance.


In conclusion, our present data do not support the relationship between 1303C/A mutation or 1254T/C, IVS4+44C/A polymorphism within DMT1 and abnormal iron accumulation indicated by SN hyperechogenicity in idopathic PD patients from Southern China. How DMT1 affects the process of iron accumulation, and whether it plays a key role in pathogenesis of PD still needs further study.

Ethics Approval and Consent to Participate

The study was approved by the Ethics Committee of Rujin Hospital. The consents to participate are stored in Ethics office.

Consent for Publication

Not relevant.

Availability of Data and Materials

All the data mentioned in this article are available on published article.

Competing Interests

he authors declare they have no competing interest.


Our work was supported by funds from the National Natural Science Foundation of China (81071023) and the Natural Science Foundation of Shanghai (14ZR1425700). All founding were used for the design, collection, analysis and interpretation of data and in writing in the manuscript.

Authors' Contributions

Wei M did the genetic analysis, statistical analysis and wrote the manuscript. Hu YY and Zhan WW did the transcranial sonography. Lou Y was responsible for the patient recruitment and data integration. Tan YY and Xiao Qin were responsible for study design and manuscript revision. All authors read and approved the final manuscript.


We are grateful to all of the patients who kindly agreed to join in our study.



  1. Palfai TP, Monti PM, Ostafin B, Hutchison K (2000) Effects of nicotine deprivation on alcohol-related information processing and drinking behavior. J Abnorm Psychol 109: 96-105.
  2. Harrison EL, Hinson RE, McKee SA (2009) Experimenting and daily smokers: episodic patterns of alcohol and cigarette use. Addict Behav 34: 484-486.
  3. Howell A, Leyro T, Hogan J, Buckner J, Zvolensky M (2010) Anxiety sensitivity, distress tolerance, and discomfort intolerance in relation to coping and conformity motives for alcohol use and alcohol use problems among young adult drinkers. Addictive Behaviors 35:1144-1147.
  4. Krukowski RA, Solomon LJ, Naud S (2005) Triggers of heavier and lighter cigarette smoking in college students. J Behav Med 28: 335-345.
  5. Reed MB, Wang R, Shillington AM, Clapp JD, Lange JE (2007) The relationship between alcohol use and cigarette smoking in a sample of undergraduate college students. Addictive Behaviors 32: 449-464.
  6. Hughes JR, Kalman D (2006) Do smokers with alcohol problems has more difficulty quitting? Drug Alcohol Depend 82: 91-102.
  7. Hurt RD, Offord KP, Croghan IT, Gomez-Dahl L, Kottke TE, et al. (1996) Mortality following inpatient addictions treatment: Role of tobacco use in a community-based cohort. JAMA: Journal of the American Medical Association 275: 1097-1103.
  8. Lisha NE, Carmody TP2, Humfleet GL2, Delucchi KL2 (2014) Reciprocal effects of alcohol and nicotine in smoking cessation treatment studies.  Addict Behav 39: 637-643.
  9. Taylor B, Rehm J (2006) When risk factors combine: The interaction between alcohol and smoking for aerodigestive cancer, coronary heart disease, and traffic and fire injury. Addictive Behaviors 31: 1522-1535.
  10. Jarvis CM, Hayman LL, Braun LT, Schwertz DW, Ferrans CE, et al. (2007) Cardiovascular risk factors and metabolic syndrome in alcohol- and nicotine-dependent men and women. J CardiovascNurs 22: 429-435.
  11. Joseph AM, Willenbring ML, Nugent SM, Nelson DB (2004) A randomized trial of concurrent versus delayed smoking intervention for patients in alcohol dependence treatment. Journal of Studies on Alcohol, 65: 681-691.
  12. Kodl M, Fu SS, Joseph AM (2006) Tobacco cessation treatment for alcohol-dependent smokers: when is the best time? Alcohol Res Health 29: 203-207.
  13. Fu S, Kodl M, Willenbring M, Nelson D, Nugent S, et al. (2008) Ethnic differences in alcohol treatment outcomes and the effect of concurrent smoking cessation treatment. Drug and Alcohol Dependence 92: 61-68.
  14. Holt LJ, Litt MD, Cooney NL (2012) Prospective analysis of early lapse to drinking and smoking among individuals in concurrent alcohol and tobacco treatment. Psychology of Addictive Behaviors 26:561-572.
  15. Centers for Disease Control and Prevention (CDC) (2009) Cigarette smoking among adults and trends in smoking cessation - United States, 2008. MMWR Morb Mortal Wkly Rep 58: 1227-1232.
  16. Irving LM, Seidner AL, Burling TA, Thomas RG, Brenner GF (1994) Drug and alcohol abuse inpatients' attitudes about smoking cessation. J Subst Abuse 6: 267-278.
  17. Macnee CL, Talsma A (1995) Development and testing of the barriers to cessation scale. Nurs Res 44: 214-219.
  18. Orleans CT, Rimer BK, Cristinzio S, Keintz MK, Fleisher L (1991) A national survey of older smokers: treatment needs of a growing population. Health Psychol 10: 343-351.
  19. Kristeller JL (1994) Treatment of hard-core, high-risk smokers using FDA approved pharmaceutical agents: An oral health team perspective. Health Values 18: 25-32.
  20. Asher MK, Martin RA, Rohsenow DJ, MacKinnon S, Traficante R, et al. (2003) Perceived barriers to quitting smoking among alcohol dependent patients in treatment. Journal of Substance Abuse Treatment 24: 169-174.
  21. Martin RA, Rohsenow DJ, MacKinnon SV, Abrams DB, Monti PM (2006) Correlates of motivation to quit smoking among alcohol dependent patients in residential treatment. Drug Alcohol Depend 83: 73-78.
  22. Marlatt GA, Gordon JR (1985) Relapse prevention. New York: Guilford Press.
  23. Velicer WF, DiClemente CC, Prochaska JO, Brandenburg N (1985) Decisional balance measure for assessing and predicting smoking status. J PersSoc Psychol 48: 1279-1289.
  24. DiClemente CC, Prochaska JO (1982) Self-change and therapy change of smoking behavior: a comparison of processes of change in cessation and maintenance. Addict Behav 7: 133-142.
  25. Curry SJ, Grothaus L, McBride C (1997) Reasons for quitting: intrinsic and extrinsic motivation for smoking cessation in a population-based sample of smokers. Addict Behav 22: 727-739.
  26. Baha M, Le Faou AL (2010) Smokers' reasons for quitting in an anti-smoking social context. Public Health 124: 225-231.
  27. Curry SJ, McBride C, Grothaus LC, Louie D, Wagner EH (1995) A randomized trial of self-help materials, personalized feedback, and telephone counseling with nonvolunteer smokers. J Consult Clin Psychol 63: 1005-1014.
  28. Saunders JB, Aasland OG, Babor TF, de la Fuente JR, Grant M (1993) Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO Collaborative Project on Early Detection of Persons with Harmful Alcohol Consumption--II. Addiction 88: 791-804.
  29. First MB, Williams JB, Spitzer RL, Gibbon M (2002) Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Clinical Trials Version (SCID-CT). New York: Biometrics Research, New York State Psychiatric Institute.
  30. Brown RA, Lejuez CW, Kahler CW, Strong DR (2002) Distress tolerance and duration of past smoking cessation attempts. J Abnorm Psychol 111: 180-185.
  31. Heatherton TF, Kozlowski LT, Frecker RC, Fagerström KO (1991) The Fagerström Test for Nicotine Dependence: a revision of the Fagerström Tolerance Questionnaire. Br J Addict 86: 1119-1127.
  32. Pomerleau CS, Carton SM, Lutzke ML, Flessland KA, Pomerleau OF (1994) Reliability of the Fagerstrom Tolerance Questionnaire and the Fagerstrom Test for Nicotine Dependence. Addict Behav 19: 33-39.
  33. Fagerstrom KO, Heatherton TF, Kozlowski LT (1990) Nicotine addiction and its assessment. Ear Nose Throat J 69: 763-765.
  34. Filbey FM, Claus E, Audette AR, Niculescu M, Banich MT, et al. (2007) Exposure to the taste of alcohol elicits activation of the mesocorticolimbicneurocircuitry. Neuropsychopharmacology 33: 1391-1401.
  35. Fleming MF, Barry KL, MacDonald R (1991) The alcohol use disorders identification test (AUDIT) in a college sample. Int J Addict 26: 1173-1185.
  36. Cherpitel CJ (1995) Analysis of cut points for screening instruments for alcohol problems in the emergency room. J Stud Alcohol 56: 695-700.
  37. Macnee CL, Talsma A (1995) Predictors of progress in smoking cessation. Public Health Nurs 12: 242-248.
  38. Curry S, Wagner EH, Grothaus LC (1990) Intrinsic and extrinsic motivation for smoking cessation. J Consult Clin Psychol 58: 310-316.
  39. McBride CM, Pollak KI, Bepler G, Lyna P, Lipkus IM, et al. (2001) Reasons for quitting smoking among low-income African American smokers. Health Psychol 20: 334-340.
  40. Bonn-Miller MO, Zvolensky MJ (2009) An evaluation of the nature of marijuana use and its motives among young adult active users. Am J Addict 18: 409-416.
  41. Buckner JD, Zvolensky MJ, Schmidt NB (2012) Cannabis-related impairment and social anxiety: the roles of gender and cannabis use motives. Addict Behav 37: 1294-1297.
  42. Agrawal A, Budney AJ, Lynskey MT (2012) The co-occurring use and misuse of cannabis and tobacco: a review. Addiction 107: 1221-1233.
  43. Degenhardt L, Hall W, Lynskey M (2001) The relationship between cannabis use and other substance use in the general population. Drug Alcohol Depend 64: 319-327.
  44. Cohen J, Cohen P (1983) Applied multiple regression/correlation analysis for the behavioral sciences. Hillsdale, NJ: Lawrence Erlbaum.
  45. Cohen J, Cohen P, West SG, Aiken LS (2003) Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ US: Lawrence Erlbaum Associates Publishers.
  46. Lipkus IM, Feaganes JR, Green JD, Sedikides C (2001) The Relationship Between Attitudinal Ambivalence and Desire to Quit Smoking Among College Smokers. Journal of Applied Social Psychology, 31: 113-133.
  47. Wilson SJ, Creswell KG, Sayette MA, Fiez JA (2013) Ambivalence about smoking and cue-elicited neural activity in quitting-motivated smokers faced with an opportunity to smoke.  Addict Behav 38: 1541-1549.
  48. Festinger LA (1957) A theory of cognitive dissonance. Evanston, IL: Row, Peterson.
  49. Markowitz LJ (2000) Smoker's perceived self-exemption from health risks. Psi Chi Journal of Undergraduate Research 5: 119-124.
  50. Jamieson P, Romer D (2001)What do young people think they know about the risks of smoking? In P. Slovic (Ed.), Smoking: Risk, perception, and policy (pp. 51-63). Thousand Oaks, CA US: Sage Publications, Inc.
  51. Schane RE, Glantz SA, Ling PM (2009) Social smoking implications for public health, clinical practice, and intervention research. American Journal of Preventive Medicine 37: 124-131.
  52. DaniJA, De Biasi M (2001) Cellular mechanisms of nicotine addiction. PharmacolBiochemBehav 70: 439-446.
  53. Nestler EJ (2005) Is there a common molecular pathway for addiction? Nat Neurosci 8: 1445-1449.
  54. Ehrman RN, Robbins SJ, Bromwell MA, Lankford ME, Monterosso JR, et al. (2002) Comparing attentional bias to smoking cues in current smokers, former smokers, and non-smokers using a dot-probe task. Drug Alcohol Depend 67: 185-191.
  55. Kerst WF, Waters AJ (2014)Attentional retraining administered in the field reduces smokers’ attentional bias and craving.
  56. Wiers RW, Rinck M, Kordts R, Houben K, Strack F (2010) Retraining automatic action-tendencies to approach alcohol in hazardous drinkers. Addiction 105: 279-287.
  57. Raupach T, West R, Brown J (2013) The most "successful" method for failing to quit smoking is unassisted cessation. Nicotine Tob Res 15: 748-749.
  58. Korte KJ, Capron DW, Zvolensky M, Schmidt NB (2013) The Fagerström test for nicotine dependence: do revisions in the item scoring enhance the psychometric properties? Addict Behav 38: 1757-1763.