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Orbitofrontal cortex volume links polygenic risk for smoking with tobacco use in healthy adolescents

Published online by Cambridge University Press:  03 September 2020

Jin Li
Affiliation:
Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China
Bing Liu
Affiliation:
Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China University of Chinese Academy of Sciences, 19 Yuquan Road, Beijing, 100049, China
Tobias Banaschewski
Affiliation:
Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
Arun L.W. Bokde
Affiliation:
Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
Erin Burke Quinlan
Affiliation:
Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, London, UK
Sylvane Desrivières
Affiliation:
Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, London, UK
Herta Flor
Affiliation:
Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany Department of Psychology, School of Social Sciences, University of Mannheim, 68131 Mannheim, Germany
Vincent Frouin
Affiliation:
NeuroSpin, CEA, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
Hugh Garavan
Affiliation:
Departments of Psychiatry and Psychology, University of Vermont, 05405 Burlington, Vermont, USA
Penny Gowland
Affiliation:
Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
Andreas Heinz
Affiliation:
Department of Psychiatry and Psychotherapy CCM, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
Bernd Ittermann
Affiliation:
Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
Jean-Luc Martinot
Affiliation:
Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 ‘Neuroimaging & Psychiatry’, University Paris-Saclay, University Paris Descartes – Sorbonne Paris Cité; and Maison de Solenn, Paris, France
Eric Artiges
Affiliation:
Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 ‘Neuroimaging & Psychiatry’, University Paris-Saclay, University Paris Descartes – Sorbonne Paris Cité; and Psychiatry Department 91G16, Orsay Hospital, Orsay, France
Frauke Nees
Affiliation:
Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
Dimitri Papadopoulos Orfanos
Affiliation:
NeuroSpin, CEA, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
Tomáš Paus
Affiliation:
Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada Departments of Psychology and Psychiatry, University of Toronto, Toronto, Ontario, M6A 2E1, Canada
Luise Poustka
Affiliation:
Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075, Göttingen, Germany
Sarah Hohmann
Affiliation:
Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
Juliane H. Fröhner
Affiliation:
Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
Michael N. Smolka
Affiliation:
Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
Henrik Walter
Affiliation:
Department of Psychiatry and Psychotherapy CCM, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
Robert Whelan
Affiliation:
School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
Gunter Schumann*
Affiliation:
Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, London, UK PONS Research Group, Department of Psychiatry and Psychotherapy, Campus Charite Mitte, Humboldt University, Berlin, Germany Leibniz Institute for Neurobiology, Magdeburg, Germany Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, P.R. China
Tianzi Jiang*
Affiliation:
Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China University of Chinese Academy of Sciences, 19 Yuquan Road, Beijing, 100049, China The Queensland Brain Institute, University of Queensland, Brisbane, QLD 4072, Australia
*
Authors for correspondence: Gunter Schumann, E-mail: [email protected]; Tianzi Jiang, E-mail: [email protected]
Authors for correspondence: Gunter Schumann, E-mail: [email protected]; Tianzi Jiang, E-mail: [email protected]

Abstract

Background

Tobacco smoking remains one of the leading causes of preventable illness and death and is heritable with complex underpinnings. Converging evidence suggests a contribution of the polygenic risk for smoking to the use of tobacco and other substances. Yet, the underlying brain mechanisms between the genetic risk and tobacco smoking remain poorly understood.

Methods

Genomic, neuroimaging, and self-report data were acquired from a large cohort of adolescents from the IMAGEN study (a European multicenter study). Polygenic risk scores (PGRS) for smoking were calculated based on a genome-wide association study meta-analysis conducted by the Tobacco and Genetics Consortium. We examined the interrelationships among the genetic risk for smoking initiation, brain structure, and the number of occasions of tobacco use.

Results

A higher smoking PGRS was significantly associated with both an increased number of occasions of tobacco use and smaller cortical volume of the right orbitofrontal cortex (OFC). Furthermore, reduced cortical volume within this cluster correlated with greater tobacco use. A subsequent path analysis suggested that the cortical volume within this cluster partially mediated the association between the genetic risk for smoking and the number of occasions of tobacco use.

Conclusions

Our data provide the first evidence for the involvement of the OFC in the relationship between smoking PGRS and tobacco use. Future studies of the molecular mechanisms underlying tobacco smoking should consider the mediation effect of the related neural structure.

Type
Original Article
Copyright
Copyright © The Author(s) 2020. Published by Cambridge University Press

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Footnotes

*

A list of authors and affiliations for the IMAGEN Consortium appears in the Supplementary note.

References

Belsky, D. W., Moffitt, T. E., Baker, T. B., Biddle, A. K., Evans, J. P., Harrington, H., … Caspi, A. (2013). Polygenic risk and the developmental progression to heavy, persistent smoking and nicotine dependence: Evidence from a 4-decade longitudinal study. JAMA Psychiatry, 70(5), 534542. doi: 10.1001/jamapsychiatry.2013.736.CrossRefGoogle ScholarPubMed
Benjamini, Y, & Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal statistical society: series B (Methodological), 57(1), 289300.Google Scholar
Binnie, V., McHugh, S., Macpherson, L., Borland, B., Moir, K., & Malik, K. (2004). The validation of self-reported smoking status by analysing cotinine levels in stimulated and unstimulated saliva, serum and urine. Oral Diseases, 10(5), 287293. doi: 10.1111/j.1601-0825.2004.01018.x.CrossRefGoogle ScholarPubMed
Blokland, G. A., de Zubicaray, G. I., McMahon, K. L., & Wright, M. J. (2012). Genetic and environmental influences on neuroimaging phenotypes: A meta-analytical perspective on twin imaging studies. Twin Research and Human Genetics, 15(3), 351371. doi: 10.1017/thg.2012.11.CrossRefGoogle ScholarPubMed
Boes, A. D., Bechara, A., Tranel, D., Anderson, S. W., Richman, L., & Nopoulos, P. (2009). Right ventromedial prefrontal cortex: A neuroanatomical correlate of impulse control in boys. Social Cognitive and Affective Neuroscience, 4(1), 19. doi: 10.1093/scan/nsn035.CrossRefGoogle ScholarPubMed
Brody, A. L., Mandelkern, M. A., Jarvik, M. E., Lee, G. S., Smith, E. C., Huang, J. C., … London, E. D. (2004). Differences between smokers and nonsmokers in regional gray matter volumes and densities. Biological Psychiatry, 55(1), 7784.CrossRefGoogle ScholarPubMed
Bruijnzeel, A. W., Alexander, J. C., Perez, P. D., Bauzo-Rodriguez, R., Hall, G., Klausner, R., … Febo, M. (2014). Acute nicotine administration increases BOLD fMRI signal in brain regions involved in reward signaling and compulsive drug intake in rats. International Journal of Neuropsychopharmacology, 18(2), 113. doi: 10.1093/ijnp/pyu011.Google ScholarPubMed
Carassiti, D., Altmann, D. R., Petrova, N., Pakkenberg, B., Scaravilli, F., & Schmierer, K. (2018). Neuronal loss, demyelination and volume change in the multiple sclerosis neocortex. Neuropathology and Applied Neurobiology, 44(4), 377390. doi: 10.1111/nan.12405.CrossRefGoogle ScholarPubMed
Centers for Disease Control and Prevention. (1996). Projected smoking-related deaths among youth – United States. MMWR: Morbidity and Mortality Weekly Report, 45(44), 971974.Google Scholar
Crunelle, C. L., Kaag, A. M., van Wingen, G., van den Munkhof, H. E., Homberg, J. R., Reneman, L., & van den Brink, W. (2014). Reduced frontal brain volume in non-treatment-seeking cocaine-dependent individuals: Exploring the role of impulsivity, depression, and smoking. Frontiers in Human Neuroscience, 8, 7. doi: 10.3389/fnhum.2014.00007.CrossRefGoogle Scholar
Dale, A. M., Fischl, B., & Sereno, M. I. (1999). Cortical surface-based analysis. I. Segmentation and surface reconstruction. NeuroImage, 9(2), 179194. doi: 10.1006/nimg.1998.0395.CrossRefGoogle ScholarPubMed
Dima, D., & Breen, G. (2015). Polygenic risk scores in imaging genetics: Usefulness and applications. Journal of Psychopharmacology, 29(8), 867871. doi: 10.1177/0269881115584470.CrossRefGoogle ScholarPubMed
Durazzo, T. C., Insel, P. S., & Weiner, M. W., & Alzheimer Disease Neuroimaging Initiative. (2012). Greater regional brain atrophy rate in healthy elderly subjects with a history of cigarette smoking. Alzheimer's & Dementia, 8(6), 513519. doi:10.1016/j.jalz.2011.10.006.CrossRefGoogle ScholarPubMed
Durazzo, T. C., Meyerhoff, D. J., & Nixon, S. J. (2013). Interactive effects of chronic cigarette smoking and age on hippocampal volumes. Drug and Alcohol Dependence, 133(2), 704711. doi: 10.1016/j.drugalcdep.2013.08.020.CrossRefGoogle ScholarPubMed
Eliopoulos, C., Klein, J., & Koren, G. (1996). Validation of self-reported smoking by analysis of hair for nicotine and cotinine. Therapeutic Drug Monitoring, 18(5), 532536. doi: 10.1097/00007691-199610000-00002.CrossRefGoogle ScholarPubMed
Ernst, M., Bolla, K., Mouratidis, M., Contoreggi, C., Matochik, J. A., Kurian, V., … London, E. D. (2002). Decision-making in a risk-taking task: A PET study. Neuropsychopharmacology, 26(5), 682691. doi: 10.1016/S0893-133X(01)00414-6.CrossRefGoogle Scholar
Fischl, B., & Dale, A. M. (2000). Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proceedings of the National Academy of Sciences of the United States of America, 97(20), 1105011055. doi: 10.1073/pnas.200033797.CrossRefGoogle ScholarPubMed
Flory, J. D., & Manuck, S. B. (2009). Impulsiveness and cigarette smoking. Psychosomatic Medicine, 71(4), 431437. doi: 10.1097/PSY.0b013e3181988c2d.CrossRefGoogle ScholarPubMed
Friedel, J. E., DeHart, W. B., Madden, G. J., & Odum, A. L. (2014). Impulsivity and cigarette smoking: Discounting of monetary and consumable outcomes in current and non-smokers. Psychopharmacology, 231(23), 45174526. doi: 10.1007/s00213-014-3597-z.CrossRefGoogle ScholarPubMed
Gallinat, J., Meisenzahl, E., Jacobsen, L. K., Kalus, P., Bierbrauer, J., Kienast, T., … Staedtgen, M. (2006). Smoking and structural brain deficits: A volumetric MR investigation. European Journal of Neuroscience, 24(6), 17441750. doi: 10.1111/j.1460-9568.2006.05050.x.CrossRefGoogle ScholarPubMed
Genovese, C. R., Lazar, N. A., & Nichols, T. (2002). Thresholding of statistical maps in functional neuroimaging using the false discovery rate. NeuroImage, 15(4), 870878. doi: 10.1006/nimg.2001.1037.CrossRefGoogle ScholarPubMed
Hayashi, T., Ko, J. H., Strafella, A. P., & Dagher, A. (2013). Dorsolateral prefrontal and orbitofrontal cortex interactions during self-control of cigarette craving. Proceedings of the National Academy of Sciences of the United States of America, 110(11), 44224427. doi: 10.1073/pnas.1212185110.CrossRefGoogle ScholarPubMed
Hayes, A. F. (2012). PROCESS: A versatile computational tool for observed variable mediation, moderation, and conditional process modeling: University of Kansas, KS.Google Scholar
International Schizophrenia Consortium, Purcell, S. M., Wray, N. R., Stone, J. L., Visscher, P. M., O'Donovan, M. C., … Sklar, P. (2009). Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature, 460(7256), 748752. doi: 10.1038/nature08185.CrossRefGoogle ScholarPubMed
Joshi, A. A., Lepore, N., Joshi, S. H., Lee, A. D., Barysheva, M., Stein, J. L., … Thompson, P. M. (2011). The contribution of genes to cortical thickness and volume. Neuroreport, 22(3), 101105. doi: 10.1097/WNR.0b013e3283424c84.CrossRefGoogle ScholarPubMed
Lancaster, T. M., Linden, D. E., Tansey, K. E., Banaschewski, T., Bokde, A. L., Bromberg, U., … Imagen Consortium. (2016). Polygenic risk of psychosis and ventral striatal activation during reward processing in healthy adolescents. JAMA Psychiatry, 73(8), 852861. doi:10.1001/jamapsychiatry.2016.1135.CrossRefGoogle ScholarPubMed
Li, M. D., Cheng, R., Ma, J. Z., & Swan, G. E. (2003). A meta-analysis of estimated genetic and environmental effects on smoking behavior in male and female adult twins. Addiction, 98(1), 2331. doi: 10.1046/j.1360-0443.2003.00295.x.CrossRefGoogle ScholarPubMed
Li, J., Zhang, X., Li, A., Liu, S., Qin, W., Yu, C., … Jiang, T. (2018). Polygenic risk for Alzheimer's disease influences precuneal volume in two independent general populations. Neurobiology of Aging, 64, 116122. doi: 10.1016/j.neurobiolaging.2017.12.022.CrossRefGoogle ScholarPubMed
Liu, S.J., Lan, Y., Wu, L., & Yan, W.S. (2019). Profiles of Impulsivity in Problematic Internet Users and Cigarette Smokers. Frontiers in Psychology, 10, 772. doi:10.3389/fpsyg.2019.00772.CrossRefGoogle ScholarPubMed
Liu, J. Z., Tozzi, F., Waterworth, D. M., Pillai, S. G., Muglia, P., Middleton, L., … Marchini, J. (2010). Meta-analysis and imputation refines the association of 15q25 with smoking quantity. Nature Genetics, 42(5), 436440. doi: 10.1038/ng.572.CrossRefGoogle ScholarPubMed
Liu, B., Zhang, X., Cui, Y., Qin, W., Tao, Y., Li, J., … Jiang, T. (2017). Polygenic risk for schizophrenia influences cortical gyrification in 2 independent general populations. Schizophrenia Bulletin, 43(3), 673680. doi: 10.1093/schbul/sbw051.Google ScholarPubMed
Lotfipour, S., Ferguson, E., Leonard, G., Perron, M., Pike, B., Richer, L., … Paus, T. (2009). Orbitofrontal cortex and drug use during adolescence role of prenatal exposure to maternal smoking and BDNF genotype. Archives of General Psychiatry, 66(11), 12441252. doi: 10.1001/archgenpsychiatry.2009.124.CrossRefGoogle ScholarPubMed
Lubke, G. H., Hottenga, J. J., Walters, R., Laurin, C., de Geus, E. J., Willemsen, G., … Boomsma, D. I. (2012). Estimating the genetic variance of major depressive disorder due to all single nucleotide polymorphisms. Biological Psychiatry, 72(8), 707709. doi: 10.1016/j.biopsych.2012.03.011.CrossRefGoogle ScholarPubMed
Matsuo, K., Nicoletti, M., Nemoto, K., Hatch, J. P., Peluso, M. A., Nery, F. G., & Soares, J. C. (2009). A voxel-based morphometry study of frontal gray matter correlates of impulsivity. Human Brain Mapping, 30(4), 11881195. doi: 10.1002/hbm.20588.CrossRefGoogle ScholarPubMed
Meyers, J. L., Cerda, M., Galea, S., Keyes, K. M., Aiello, A. E., Uddin, M., … Koenen, K. C. (2013). Interaction between polygenic risk for cigarette use and environmental exposures in the Detroit Neighborhood Health Study. Translational Psychiatry, 3, e290. doi: 10.1038/tp.2013.63.CrossRefGoogle ScholarPubMed
Mills, K. L., Goddings, A. L., Herting, M. M., Meuwese, R., Blakemore, S. J., Crone, E. A., … Tamnes, C. K. (2016). Structural brain development between childhood and adulthood: Convergence across four longitudinal samples. NeuroImage, 141, 273281. doi: 10.1016/j.neuroimage.2016.07.044.CrossRefGoogle ScholarPubMed
Musci, R. J., Fairman, B., Masyn, K. E., Uhl, G., Maher, B., Sisto, D. Y., … Ialongo, N. S. (2018). Polygenic score x intervention moderation: An application of discrete-time survival analysis to model the timing of first marijuana use among urban youth. Prevention Science, 19(1), 614. doi: 10.1007/s11121-016-0729-1.CrossRefGoogle ScholarPubMed
Nejati, V., Salehinejad, M. A., & Nitsche, M. A. (2018). Interaction of the left dorsolateral prefrontal cortex (l-DLPFC) and right orbitofrontal cortex (OFC) in hot and cold executive functions: Evidence from transcranial direct current stimulation (tDCS). Neuroscience, 369, 109123. doi: 10.1016/j.neuroscience.2017.10.042.CrossRefGoogle Scholar
Perry, D. C., Davila-Garcia, M. I., Stockmeier, C. A., & Kellar, K. J. (1999). Increased nicotinic receptors in brains from smokers: Membrane binding and autoradiography studies. Journal of Pharmacology and Experimental Therapeutics, 289(3), 15451552.Google ScholarPubMed
Popescu, V., Klaver, R., Voorn, P., Galis-de Graaf, Y., Knol, D. L., Twisk, J. W., … Geurts, J. J. (2015). What drives MRI-measured cortical atrophy in multiple sclerosis? Multiple Sclerosis, 21(10), 12801290. doi: 10.1177/1352458514562440.CrossRefGoogle ScholarPubMed
Potts, G. F., Bloom, E. L., Evans, D. E., & Drobes, D. J. (2014). Neural reward and punishment sensitivity in cigarette smokers. Drug and Alcohol Dependence, 144, 245253. doi: 10.1016/j.drugalcdep.2014.09.773.CrossRefGoogle ScholarPubMed
Prom-Wormley, E., Maes, H. H., Schmitt, J. E., Panizzon, M. S., Xian, H., Eyler, L. T., … Neale, M. C. (2015). Genetic and environmental contributions to the relationships between brain structure and average lifetime cigarette use. Behavior Genetics, 45(2), 157170. doi: 10.1007/s10519-014-9704-4.CrossRefGoogle Scholar
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A., Bender, D., … Sham, P. C. (2007). PLINK: A tool set for whole-genome association and population-based linkage analyses. American Journal of Human Genetics, 81(3), 559575. doi: 10.1086/519795.CrossRefGoogle ScholarPubMed
Ruderfer, D. M., Fanous, A. H., Ripke, S., McQuillin, A., Amdur, R. L., … Kendler, K. S. (2014). Polygenic dissection of diagnosis and clinical dimensions of bipolar disorder and schizophrenia. Molecular Psychiatry, 19(9), 10171024. doi: 10.1038/mp.2013.138.CrossRefGoogle Scholar
Ruff, C. C., & Fehr, E. (2014). The neurobiology of rewards and values in social decision making. Nature Reviews Neuroscience, 15(8), 549562. doi: 10.1038/nrn3776.CrossRefGoogle ScholarPubMed
Schilling, C., Kuhn, S., Paus, T., Romanowski, A., Banaschewski, T., Barbot, A., … Imagen consortium. (2013). Cortical thickness of superior frontal cortex predicts impulsiveness and perceptual reasoning in adolescence. Molecular Psychiatry, 18(5), 624630. doi:10.1038/mp.2012.56.CrossRefGoogle ScholarPubMed
Schumann, G., Loth, E., Banaschewski, T., Barbot, A., Barker, G., Buchel, C., … Imagen consortium. (2010). The IMAGEN study: Reinforcement-related behaviour in normal brain function and psychopathology. Molecular Psychiatry, 15(12), 11281139. doi:10.1038/mp.2010.4.CrossRefGoogle ScholarPubMed
Studer, B., Manes, F., Humphreys, G., Robbins, T. W., & Clark, L. (2015). Risk-sensitive decision-making in patients with posterior parietal and ventromedial prefrontal cortex injury. Cerebral Cortex, 25(1), 19. doi: 10.1093/cercor/bht197.CrossRefGoogle ScholarPubMed
Sutherland, M. T., Riedel, M. C., Flannery, J. S., Yanes, J. A., Fox, P. T., Stein, E. A., & Laird, A. R. (2016). Chronic cigarette smoking is linked with structural alterations in brain regions showing acute nicotinic drug-induced functional modulations. Behavioral and Brain Functions, 12(1), 16. doi: 10.1186/s12993-016-0100-5.CrossRefGoogle ScholarPubMed
Thorgeirsson, T. E., Gudbjartsson, D. F., Surakka, I., Vink, J. M., Amin, N., Geller, F., … Stefansson, K. (2010). Sequence variants at CHRNB3-CHRNA6 and CYP2A6 affect smoking behavior. Nature Genetics, 42(5), 448453. doi: 10.1038/ng.573.CrossRefGoogle ScholarPubMed
Tobacco Genetics Consortium. (2010). Genome-wide meta-analyses identify multiple loci associated with smoking behavior. Nature Genetics, 42(5), 441447. doi: 10.1038/ng.571.CrossRefGoogle Scholar
Toro, R., Leonard, G., Lerner, J. V., Lerner, R. M., Perron, M., Pike, G. B., … Paus, T. (2008). Prenatal exposure to maternal cigarette smoking and the adolescent cerebral cortex. Neuropsychopharmacology, 33(5), 10191027. doi: 10.1038/sj.npp.1301484.CrossRefGoogle ScholarPubMed
Uhl, G. R., Walther, D., Musci, R., Fisher, C., Anthony, J. C., Storr, C. L., … Rose, J. E. (2014). Smoking quit success genotype score predicts quit success and distinct patterns of developmental involvement with common addictive substances. Molecular Psychiatry, 19(1), 5054. doi: 10.1038/mp.2012.155.CrossRefGoogle ScholarPubMed
US Department of Health and Human Services. (2014) The health consequences of smoking-50 years of progress: A report of the surgeon general. Atlanta, GA: US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health.Google Scholar
Vassos, E., Di Forti, M., Coleman, J., Iyegbe, C., Prata, D., Euesden, J., … Breen, G. (2017). An examination of polygenic score risk prediction in individuals with first-episode psychosis. Biological Psychiatry, 81(6), 470477. doi: 10.1016/j.biopsych.2016.06.028.CrossRefGoogle ScholarPubMed
Vink, J. M., Hottenga, J. J., de Geus, E. J., Willemsen, G., Neale, M. C., Furberg, H., & Boomsma, D. I. (2014). Polygenic risk scores for smoking: Predictors for alcohol and cannabis use? Addiction, 109(7), 11411151. doi: 10.1111/add.12491.CrossRefGoogle ScholarPubMed
Vink, J. M., Willemsen, G., & Boomsma, D. I. (2005). Heritability of smoking initiation and nicotine dependence. Behavior Genetics, 35(4), 397406. doi: 10.1007/s10519-004-1327-8.CrossRefGoogle ScholarPubMed
Wittchen, H. U., Behrendt, S., Hofler, M., Perkonigg, A., Lieb, R., Buhringer, G., & Beesdo, K. (2008). What are the high risk periods for incident substance use and transitions to abuse and dependence? Implications for early intervention and prevention. International Journal of Methods in Psychiatric Research, 17(Suppl. 1), S16S29. doi: 10.1002/mpr.254.CrossRefGoogle ScholarPubMed
World Health Organization. (2011). WHO report on the global tobacco epidemic, 2011: warning about the dangers of tobacco: World Health Organization.Google Scholar
Xu, J., Li, Q., Qin, W., Jun Li, M., Zhuo, C., Liu, H., … Yu, C. (2018). Neurobiological substrates underlying the effect of genomic risk for depression on the conversion of amnestic mild cognitive impairment. Brain, 141(12), 34573471. doi: 10.1093/brain/awy277.CrossRefGoogle ScholarPubMed
Zhong, J., Shi, H., Shen, Y., Dai, Z., Zhu, Y., Ma, H., & Sheng, L. (2016). Voxelwise meta-analysis of gray matter anomalies in chronic cigarette smokers. Behavioural Brain Research, 311, 3945. doi: 10.1016/j.bbr.2016.05.016.CrossRefGoogle ScholarPubMed
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