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Problematic internet use: an exploration of associations between cognition and COMT rs4818, rs4680 haplotypes

Published online by Cambridge University Press:  04 June 2019

Konstantinos Ioannidis Open the ORCID record for Konstantinos Ioannidis [Opens in a new window] ,
Sarah A. Redden ,
Stephanie Valle ,
Samuel R. Chamberlain Open the ORCID record for Samuel R. Chamberlain [Opens in a new window]  and
Jon E. Grant Open the ORCID record for Jon E. Grant [Opens in a new window]
Konstantinos Ioannidis
Affiliation:
Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom Cambridge and Peterborough NHS Foundation Trust, Cambridge, United Kingdom
Sarah A. Redden
Affiliation:
Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois, USA
Stephanie Valle
Affiliation:
Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois, USA
Samuel R. Chamberlain
Affiliation:
Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom Cambridge and Peterborough NHS Foundation Trust, Cambridge, United Kingdom
Jon E. Grant*
Affiliation:
Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois, USA
*
*Address correspondence to: Jon E. Grant, Department of Psychiatry & Behavioral Neuroscience, University of Chicago, Pritzker School of Medicine, 5841 S. Maryland Avenue, MC 3077, Chicago, IL 60637, USA. (Email: [email protected])
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Abstract

Objective

Problematic internet users suffer from impairment in a variety of cognitive domains. Research suggests that COMT haplotypes exert differential effects on cognition. We sought to investigate differences in the genetic profiles of problematic internet users and whether those could shed light on potential cognitive differences.

Methods

We recruited 206 non-treatment seeking participants with heightened impulsive traits and obtained cross-sectional demographic, clinical, and cognitive data as well as the genetic haplotypes of COMT rs4680 and rs4818. We identified 24 participants who presented with problematic internet use (PIU) and compared PIU and non-PIU participants using one-way analysis of variance (ANOVA) and chi square as appropriate.

Results

PIU was associated with worse performance on decision making, rapid visual processing, and spatial working memory tasks. Genetic variants were associated with altered cognitive performance, but rates of PIU did not statistically differ for particular haplotypes of COMT.

Conclusion

This study indicates that PIU is characterized by deficits in decision making and working memory domains; it also provides evidence for elevated impulsive responses and impaired target detection on a sustained attention task, which is a novel area worth exploring further in future work. The effects observed in the genetic influences on cognition of PIU subjects imply that the genetic heritable components of PIU may not lie within the genetic loci influencing COMT function and cognitive performance; or that the genetic component in PIU involves many genetic polymorphisms each conferring only a small effect.

Keywords

Problematic internet useinternet addictionCOMTcognitiongenetics
Type
Original Research
Information
CNS Spectrums , Volume 25 , Issue 3 , June 2020 , pp. 409 - 418
Copyright
© Cambridge University Press 2019

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References

References:

Fineberg, N, Demetrovics, Z, Stein, D, et al. Manifesto for a European research network into problematic usage of the internet. Eur Neuropsychopharmacol. 2018; 28(11): 1232–1246. doi: 10.1016/J.EURONEURO.2018.08.004.Google Scholar
Kuss, DJ, Lopez-Fernandez, O.Internet addiction and problematic internet use: a systematic review of clinical research. World J Psychiatry. 2016; 6(1): 143–176. doi: 10.5498/wjp.v6.i1.143.Google Scholar
Király, O, Griffiths, MD, Demetrovics, Z.Internet gaming disorder and the DSM-5: conceptualization, debates, and controversies. Curr Addict Reports. 2015; 2(3): 254–262. doi: 10.1007/s40429-015-0066-7.Google Scholar
Carli, V, Durkee, T, Wasserman, D, et al.The association between pathological internet use and comorbid psychopathology: a systematic review. Psychopathology. 2013; 46(1): 1–13. doi: 10.1159/000337971.Google Scholar
Ko, C-H, Yen, J-Y, Yen, C-F, et al. The association between internet addiction and psychiatric disorder: a review of the literature. Eur Psychiatry. 2012; 27(1): 1–8. doi: 10.1016/j.eurpsy.2010.04.011.Google Scholar
Chamberlain, SR, Ioannidis, K, Leppink, EW, et al. ADHD symptoms in non-treatment seeking young adults: relationship with other forms of impulsivity. CNS Spectr. 2016; 22(1): 1–9. doi: 10.1017/S1092852915000875.Google Scholar
Chamberlain, SR, Ioannidis, K, Grant, JE.The impact of comorbid impulsive/compulsive disorders on problematic internet use. J Behav Addict. 2018; 7(2): 269–275. doi: 10.1556/2006.7.2018.30.Google Scholar
Ioannidis, K, Chamberlain, SR, Treder, MS, et al. Problematic internet use (PIU): associations with the impulsive-compulsive spectrum. An application of machine learning in psychiatry. J Psych. 2016; 83: 94–102. doi: 10.1016/j.jpsychires.2016.08.010.Google Scholar
Ioannidis, K, Treder, MS, Chamberlain, SR, et al.Problematic internet use as an age-related multifaceted problem: evidence from a two-site survey. Addict Behav. 2018; 81: 157–166. doi: 10.1016/J.ADDBEH.2018.02.017.Google Scholar
Ioannidis, K, Hook, R, Goudriaan, AE, et al. Cognitive deficits in problematic internet use: a meta-analysis of 40 studies. Br J Psychiatry. 2019; 20: 1–8. doi: 10.1192/bjp.2019.3.Google Scholar
Deryakulu, D, Ursavaş ÖF. Genetic and environmental influences on problematic internet use: a twin study. Comput Human Behav. 2014; 39:331–338. doi: 10.1016/J.CHB.2014.07.038.Google Scholar
Li, M, Chen, J, Li, N, et al. A twin study of problematic internet use: its heritability and genetic association with effortful control. Twin Res Hum Genet. 2014; 17(4):279–287. doi: 10.1017/thg.2014.32.Google Scholar
Vink, JM, Van Beijsterveldt, TCEM, Huppertz, C, et al. Heritability of compulsive internet use in adolescents. Addict Biol. 2016; 21(2): 460–468. doi: 10.1111/adb.12218.Google Scholar
Hahn, E, Reuter, M, Spinath, FM, et al. Internet addiction and its facets: the role of genetics and the relation to self-directedness. Addict Behav. 2017; 65: 137–146. doi: 10.1016/j.addbeh.2016.10.018.Google Scholar
Prescott, CA, Kendler, KS.Genetic and environmental contributions to alcohol abuse and dependence in a population-based sample of male twins. Am J Psychiatry. 1999; 156(1): 34–40. doi: 10.1176/ajp.156.1.34.Google Scholar
Lee, YS, Han, DH, Yang, KC, et al.Depression like characteristics of 5HTTLPR polymorphism and temperament in excessive internet users. J Affect Disord. 2008; 109(1–2): 165–169. doi: 10.1016/j.jad.2007.10.020.Google Scholar
Jeong, J-E, Rhee, J-K, Kim, T-M, et al.The association between the nicotinic acetylcholine receptor α4 subunit gene (CHRNA4) rs1044396 and internet gaming disorder in Korean male adults. PLoS One. 2017; 12(12): e0188358. doi: 10.1371/journal.pone.0188358.Google Scholar
Montag, C, Kirsch, P, Sauer, C, et al. The role of the CHRNA4 gene in internet addiction. J Addict Med. 2012; 6(3): 191–195. doi: 10.1097/ADM.0b013e31825ba7e7.Google Scholar
Kim, J-Y, Jeong, J-E, Rhee, J-K, et al.Targeted exome sequencing for the identification of a protective variant against internet gaming disorder at rs2229910 of neurotrophic tyrosine kinase receptor, type 3 (NTRK3): a pilot study. J Behav Addict. 2016; 5(4): 631–638. doi: 10.1556/2006.5.2016.077.Google Scholar
Volkow, ND, Fowler, JS, Wang, G-J, et al. Dopamine in drug abuse and addiction. Arch Neurol. 2007; 64(11): 1575. doi: 10.1001/archneur.64.11.1575.Google Scholar
Robbins, TW, Everitt, BJ, Nutt, DJ.Introduction. The neurobiology of drug addiction: new vistas. Philos Trans R Soc Lond B Biol Sci. 2008; 363(1507): 3109–3111. doi: 10.1098/rstb.2008.0108.Google Scholar
Hou, H, Jia, S, Hu, S, et al.Reduced striatal dopamine transporters in people with Internet addiction disorder. J Biomed Biotechnol. 2012; 2012: 854524. doi: 10.1155/2012/854524.Google Scholar
Kim, SH, Baik, S-H, Park, CS, et al. Reduced striatal dopamine D2 receptors in people with Internet addiction. Neuroreport. 2011; 22(8): 407–411. doi: 10.1097/WNR.0b013e328346e16e.Google Scholar
Han, DH, Lee, YS, Yang, KC, et al. Dopamine genes and reward dependence in adolescents with excessive internet video game play. J Addict Med. 2007; 1(3): 133–138. doi: 10.1097/ADM.0b013e31811f465f.Google Scholar
Grant, JE, Leppink, EW, Redden, SA, et al. COMT genotype, gambling activity, and cognition. J Psychiatr Res. 2015; 68: 371–376. doi: 10.1016/j.jpsychires.2015.04.029.Google Scholar
Chen, J, Lipska, BK, Halim, N, et al.Functional analysis of genetic variation in catechol-O-methyltransferase (COMT): effects on mRNA, protein, and enzyme activity in postmortem human brain. Am J Hum Genet. 2004; 75(5): 807–821. doi: 10.1086/425589.Google Scholar
Roussos, P, Giakoumaki, SG, Pavlakis, S, et al. Planning, decision-making and the COMT rs4818 polymorphism in healthy males. Neuropsychologia. 2008; 46(2): 757–763. doi: 10.1016/j.neuropsychologia.2007.10.009.Google Scholar
Young, KS.Internet addiction: the emergence of a new clinical disorder. Publ CyberPsychology Behav. 1998; 1(3): 237–244. doi: 10.1089/cpb.1998.1.237.Google Scholar
Dong, G, Zhou, H, Zhao, X.Male Internet addicts show impaired executive control ability: evidence from a color-word Stroop task. Neurosci Lett. 2011; 499(2): 114–118. doi: 10.1016/j.neulet.2011.05.047.Google Scholar
Li, Q, Nan, W, Taxer, J, et al. Problematic internet users show impaired inhibitory control and risk taking with losses: evidence from stop signal and mixed gambles tasks. Front Psychol. 2016; 7: 1–9. doi: 10.3389/fpsyg.2016.00370.Google Scholar
Chamberlain, SR, Redden, SA, Leppink, E, et al. Problematic internet use in gamblers: impact on clinical and cognitive measures. CNS Spectr. 2017; 22(6): 1–9. doi: 10.1017/S1092852917000037.Google Scholar
Sheehan, DV, Lecrubier, Y, Sheehan, KH, et al.The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry. 1998; 59(Suppl 20):22–57; http://www.ncbi.nlm.nih.gov/pubmed/9881538. Accessed July 2, 2017.Google Scholar
Grant, JE, Levine, L, Kim, D, et al. Impulse control disorders in adult psychiatric inpatients. Am J Psychiatry. 2005; 162(11): 2184–2188. doi: 10.1176/appi.ajp.162.11.2184.Google Scholar
Patton, JH, Stanford, MS, Barratt, ES.Factor structure of the Barratt impulsiveness scale. J Clin Psychol. 1995; 51(6): 768–774; http://www.ncbi.nlm.nih.gov/pubmed/8778124. Accessed September 17, 2016.Google Scholar
Burns, GL, Keortge, SG, Formea, GM, et al. Revision of the Padua Inventory of obsessive compulsive disorder symptoms: distinctions between worry, obsessions, and compulsions. Behav Res Ther. 1996; 34(2): 163–173; http://www.ncbi.nlm.nih.gov/pubmed/8741724. Accessed January 7, 2017.Google Scholar
Frisch, MB, Cornell, J, Villanueva, M, et al. Clinical validation of the quality of life inventory. a measure of life satisfaction for use in treatment planning and outcome assessment. Psychol Assess. 1992; 4(1): 92–101. doi: 10.1037/1040-3590.4.1.92.Google Scholar
Kim, Y-J, Lim, JA, Lee, JY, et al.Impulsivity and compulsivity in internet gaming disorder: a comparison with obsessive-compulsive disorder and alcohol use disorder. J Behav Addict. 2017; 6(4): 1–9. doi: 10.1556/2006.6.2017.069.Google Scholar
Aron, AR, Robbins, TW, Poldrack, RA.Inhibition and the right inferior frontal cortex. Trends Cogn Sci. 2004; 8(4): 170–177. doi: 10.1016/j.tics.2004.02.010.Google Scholar
Liu, RT, Choi, JY, Boland, EM, et al. Childhood abuse and stress generation: the mediational effect of depressogenic cognitive styles. Psychiatry Res. 2013; 206(2–3): 217–222. doi: 10.1016/j.psychres.2012.12.001.Google Scholar
Choi, S-W, Kim, H, Kim, G-Y, et al.Similarities and differences among internet gaming disorder, gambling disorder and alcohol use disorder: a focus on impulsivity and compulsivity. J Behav Addict. 2014; 3(4): 246–253. doi: 10.1556/JBA.3.2014.4.6.Google Scholar
Lim, J-A, Lee, J-Y, Jung, HY, et al.Changes of quality of life and cognitive function in individuals with internet gaming disorder. Medicine (Baltimore). 2016; 95(50): e5695. doi: 10.1097/MD.0000000000005695.Google Scholar
Zhou, Z, Zhou, H, Zhu, H.Working memory, executive function and impulsivity in internet-addictive disorders: a comparison with pathological gambling. Acta Neuropsychiatr. 2016; 28(2): 92–100. doi: 10.1017/neu.2015.54.Google Scholar
Zhou, Z, Zhu, H, Li, C, et al. Internet addictive individuals share impulsivity and executive dysfunction with alcohol-dependent patients. Front Behav Neurosci. 2014; 8: 288. doi: 10.3389/fnbeh.2014.00288.Google Scholar
Lawrence, AJ, Luty, J, Bogdan, NA, et al. Impulsivity and response inhibition in alcohol dependence and problem gambling. Psychopharmacology (Berl). 2009; 207(1): 163–172. doi: 10.1007/s00213-009-1645-x.Google Scholar
Pawlikowski, M, Brand, M.Excessive internet gaming and decision making: do excessive World of Warcraft players have problems in decision making under risky conditions? Psychiatry Res. 2011;188 (3): 428–433. doi: 10.1016/j.psychres.2011.05.017.Google Scholar
Qi, X, Du, X, Yang, Y, et al.Decreased modulation by the risk level on the brain activation during decision making in adolescents with internet gaming disorder. Front Behav Neurosci. 2015; 9: 1–8. doi: 10.3389/fnbeh.2015.00296.Google Scholar
Lorenz, RC, Krüger, J-K, Neumann, B, et al.Cue reactivity and its inhibition in pathological computer game players. Addict Biol. 2013; 18(1): 134–146. doi: 10.1111/j.1369-1600.2012.00491.x.Google Scholar
Nikolaidou, M, Fraser, DS, Hinvest, N.Physiological markers of biased decision-making in problematic internet users. J Behav Addict. 2016; 5(3): 510–517. doi: 10.1556/2006.5.2016.052.Google Scholar
Gau, SS-F, Huang, W-L.Rapid visual information processing as a cognitive endophenotype of attention deficit hyperactivity disorder. Psychol Med. 2014; 44(2): 435–446. doi: 10.1017/S0033291713000640.Google Scholar
Owen, AM, Downes, JJ, Sahakian, BJ, et al. Planning and spatial working memory following frontal lobe lesions in man. Neuropsychologia. 1990; 28(10): 1021–1034.Google Scholar
Lotta, T, Vidgren, J, Tilgmann, C, et al.Kinetics of human soluble and membrane-bound catechol O-methyltransferase: a revised mechanism and description of the thermolabile variant of the enzyme. Biochemistry. 1995; 34(13): 4202–4210.Google Scholar
Farrell, SM, Tunbridge, EM, Braeutigam, S, et al. COMT Val(158)Met genotype determines the direction of cognitive effects produced by catechol-O-methyltransferase inhibition. Biol Psychiatry. 2012; 71(6): 538–544. doi: 10.1016/j.biopsych.2011.12.023.Google Scholar
van den Bos, R, Homberg, J, Gijsbers, E, et al. The effect of COMT Val158 Met genotype on decision-making and preliminary findings on its interaction with the 5-HTTLPR in healthy females. Neuropharmacology. 2009; 56(2): 493–498. doi: 10.1016/j.neuropharm.2008.10.002.Google Scholar
Soeiro-De-Souza, M, Stanford, M, Bio, D, et al. Association of the COMT Met158 allele with trait impulsivity in healthy young adults. Mol Med Rep. 2013; 7(4): 1067–1072. doi: 10.3892/mmr.2013.1336.Google Scholar
Schacht, JP.COMT val158met moderation of dopaminergic drug effects on cognitive function: a critical review. Pharmacogenomics J. 2016; 16(5): 430–438. doi: 10.1038/tpj.2016.43.Google Scholar
Robbins, TW, Arnsten, AFT. The neuropsychopharmacology of fronto-executive function: monoaminergic modulation. Annu Rev Neurosci. 2009; 32(1): 267–287. doi: 10.1146/annurev.neuro.051508.135535.Google Scholar
Nackley, AG, Shabalina, SA, Tchivileva, IE, et al.Human catechol-O-methyltransferase haplotypes modulate protein expression by altering mRNA secondary structure. Science. 2006; 314(5807): 1930–1933. doi: 10.1126/science.1131262.Google Scholar
Roussos, P, Giakoumaki, SG, Bitsios, P.Tolcapone effects on gating, working memory, and mood interact with the synonymous catechol-O-methyltransferase rs4818C/G polymorphism. Biol Psychiatry. 2009;66(11): 997–1004. doi: 10.1016/j.biopsych.2009.07.008.Google Scholar
Graffelman, J. Exploring Diallelic Genetic Markers: The HardyWeinberg Package. Journal of Statistical Software. 2015; 64(3): 1–23.Google Scholar
Venables, WN, Ripley, BD. Modern Applied Statistics with S. Fourth edition. New York: Springer; 2002.Google Scholar
Faul, F, Erdfelder, E, Lang, A-G, et al. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007; 39: 175–191.Google Scholar
Laconi, S, Rodgers, RF, Chabrol, H.The measurement of internet addiction: a critical review of existing scales and their psychometric properties. Comput Human Behav. 2014; 41: 190–202. doi: 10.1016/J.CHB.2014.09.026.Google Scholar
Ho, RC, Zhang, MWB, Tsang, TY, et al.The association between internet addiction and psychiatric co-morbidity: a meta-analysis. BMC Psychiatry. 2014; 14: 183. doi: 10.1186/1471-244X-14-183.Google Scholar