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Interaction Effects of the COMT and DRD4 Genes with Anxiety-Related Traits on Selective Attention

Published online by Cambridge University Press:  08 July 2014

Margarita Alfimova ,
Galina Korovaitseva ,
Tatiana Lezheiko  and
Vera Golimbet
Margarita Alfimova*
Affiliation:
The Mental Health Research Centre of the Russian Academy of Medical Sciences (Russia)
Galina Korovaitseva
Affiliation:
The Mental Health Research Centre of the Russian Academy of Medical Sciences (Russia)
Tatiana Lezheiko
Affiliation:
The Mental Health Research Centre of the Russian Academy of Medical Sciences (Russia)
Vera Golimbet
Affiliation:
The Mental Health Research Centre of the Russian Academy of Medical Sciences (Russia)
*
*Correspondence concerning this article should be addressed to Margarita V. Alfimova. Principal Investigator. Department of Clinical Genetics. Mental Health Research Centre RAMS. MHRC RAMS. Zagorodnoe sh.2, k.2. 117152. Moscow (Russia). Phone: +7–4991320062, +7–9169195348. E-mail: [email protected]
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Abstract

The study investigated whether the DRD4 and COMT genes can modify relations between trait anxiety and selective attention. Two hundreds and sixty-six subjects performed a visual search task in which they had to find words looking through a sheet with rows of letters. After finishing the first sheet the subject was presented the second one, this time with an instruction to perform the task as quickly and accurate as possible. To study top-down attention, the number of correctly identified words (accuracy) and the time for completion of each trial were analyzed. To study bottom-up attention, the letters ‘o’ and ‘n’ were written in green, whilst the others were in black, and subjects were asked whether they had noticed that 2–3 minutes after the task completion. Genotypes for the COMT Val158Met and DRD4 VNTR-48 polymorphisms and TCI Harm Avoidance and MMPI Depression scales’ scores were obtained as well. High anxious individuals showed a more pronounced increase in accuracy in the second trial and more profound processing of irrelevant stimuli (colored letters). There was a significant interaction effect of DRD4 and Harm avoidance on the accuracy dynamics F(1, 210), = 7.65, p = .006, η2 = .04. Among DRD4 long allele carriers, high anxious subjects significantly improved accuracy (p = .013) and tended to slow speed, while those with lower Harm avoidance demonstrated the opposite trend. These effects were more robust in less educated individuals. It was concluded that the DRD4 polymorphism may modify the influence of trait anxiety on the speed-accuracy tradeoff.

Keywords

anxietyharm avoidanceattentionCOMTDRD4
Type
Research Article
Information
The Spanish Journal of Psychology , Volume 17 , 2014 , E44
Copyright
Copyright © Universidad Complutense de Madrid and Colegio Oficial de Psicólogos de Madrid 2014 

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References

Alfimova, M. V., Abramova, L. I., Barhatova, A. I., Yumatova, P. E., Lyachenko, G. L., & Golimbet, V. E. (2009). Facial affect recognition deficit as a marker of genetic vulnerability to schizophrenia. The Spanish Journal of Psychology, 12, 46–55.CrossRefGoogle ScholarPubMed
Ansari, T. L., & Derakshan, N. (2011). The neural correlates of cognitive effort in anxiety: Effects on processing efficiency. Biological Psychology, 86, 337–348. http://dx.doi.org/10.1016/j.biopsycho.2010.12.013 CrossRefGoogle ScholarPubMed
Baekken, P. M., Skorpen, F., Stordal, E., Zwart, J. A., & Hagen, K. (2008). Depression and anxiety in relation to catechol-O-methyltransferase Val158Met genotype in the general population: the Nord-Trondelag Health Study (HUNT). BMC Psychiatry, 8, 48. http://dx.doi.org/10.1186/1471-244X-8-48 Google Scholar
Barnett, J. H., Scoriels, L., & Munafo, M. R. (2008). Meta-analysis of the cognitive effects of the catechol-O-methyltransferase gene Val158/108Met polymorphism. Biological Psychiatry, 64, 137–144. http://dx.doi.org/10.1016/j.biopsych.2008.01.005 CrossRefGoogle ScholarPubMed
Basten, U., Stelzel, C., & Fiebach, C. J. (2011). Trait anxiety modulates the neural efficiency of inhibitory control. Journal of Cognitive Neuroscience, 23, 3132–3145. http://dx.doi.org/10.1162/jocn_a_00003 Google Scholar
Belsky, J., Jonassaint, C., Pluess, M., Stanton, M., Brummett, B., & Williams, R. (2009). Vulnerability genes or plasticity genes? Vulnerability genes or plasticity genes? Molecular Psychiatry, 14, 746–754. http://dx.doi.org/10.1038/mp.2009.44 Google Scholar
Berezin, F. B., Miroshnikov, M. P., & Rozhanec, R. V. (1976). Minnesota Multiphasic Personality Inventory in clinical medicine and psychohygiene. Moscow, Russia: Medicine.Google Scholar
Bijleveld, E., Custers, R., & Aarts, H. (2010). Unconscious reward cues increase invested effort, but do not change speed–accuracy tradeoffs. Cognition, 115, 330–335. http://dx.doi.org/10.1016/j.cognition.2009.12.012 CrossRefGoogle Scholar
Bishop, S. J. (2009). Trait anxiety and impoverished prefrontal control of attention. Nature Neuroscience, 12, 92–98. http://dx.doi.org/10.1038/nn.2242 Google Scholar
Blanchette, I., & Richards, A. (2010). The influence of affect on higher level cognition: A review of research on interpretation, judgment, decision making and reasoning. Cognition & Emotion, 24, 561–595. http://dx.doi.org/10.1080/02699930903132496 Google Scholar
Blasi, G., Mattay, V. S., Bertolino, A., Elvevag, B., Callicott, J. H., Das, S., … Weinberger, D. R. (2005). Effect of catechol-O-methyltransferase Val158Met genotype on attentional control. Journal of Neuroscience, 25, 5038–5045. http://dx.doi.org/10.1523/JNEUROSCI.0476-05.2005 CrossRefGoogle ScholarPubMed
Cloninger, C. R., Przybeck, T. R., Svrakic, D. M., & Wetzel, R. D. (1994). The Temperament and Character Inventory (TCI): A guide to its development and use. St. Louis, MO: Center for Psychobiology of Personality.Google Scholar
Congdon, M. A. E., Lesch, K. P., & Canli, T. (2008). Analysis of DRD4 and DAT polymorphisms and behavioral inhibition in healthy adults: Implications for impulsivity. American Journal of Medical Genetics. Part B: Neuropsychiatric Genetics, 147B, 27–32. http://dx.doi.org/10.1002/ajmg.b.30557 Google Scholar
Coombes, S. A., Higgins, T., Gamble, K. M., Cauraugh, J. H., & Janelle, C. M. (2009). Attentional control theory: Anxiety, emotion, and motor planning. Journal of Anxiety Disorders, 23, 1072–1079. http://dx.doi.org/10.1016/j.janxdis.2009.07.009 Google Scholar
Dennis, N. A., Need, A. C., LaBar, K. S., Waters-Metenier, S., Cirulli, E. T., Kragel, J., … Cabeza, R. (2010). COMT Val 108/158 Met genotype affects neural but not cognitive processing in healthy individuals. Cerebral Cortex, 20, 672–683. http://dx.doi.org/10.1093/cercor/bhp132 Google Scholar
Derakshan, N., & Eysenck, M. W. (2010). Introduction to the special issue: Emotional states, attention, and working memory. Cognition & Emotion, 24, 189–199. http://dx.doi.org/10.1080/02699930903412120 Google Scholar
Ebstein, R. P. (2006). The molecular genetic architecture of human personality: Beyond self-report questionnaires. Molecular Psychiatry, 11, 427–445. http://dx.doi.org/10.1038/sj.mp.4001814 Google Scholar
Egan, M. F., Goldberg, T. E., Kolachana, B. S., Callicott, J. H., Mazzanti, C. M., Straub, R. E., … Weinberger, D. R. (2001). Effect of COMT Val108/158met genotype on frontal lobe function and risk for schizophrenia. The Proceedings of the National Academy of Sciences of the United States of America, 98, 6917–6922. http://dx.doi.org/10.1073/pnas.111134598 Google Scholar
Eisenberger, N. I., Lieberman, M. D., & Satpute, A. B. (2005). Personality from a controlled processing perspective: An fMRI study of neuroticism, extraversion, and self-consciousness. Cognitive, Affective, & Behavioral Neuroscience, 5, 169–181. http://dx.doi.org/10.3758/CABN.5.2.169 Google Scholar
Eley, T. C., Tahir, E., Angleitner, A., Harriss, K., McClay, J., Plomin, R., … Craig, I. (2003). Association analysis of MAOA and COMT with neuroticism assessed by peers. American Journal of Medical Genetics. Part B: Neuropsychiatric Genetics, 120B, 90–96. http://dx.doi.org/10.1002/ajmg.b.20046 Google Scholar
Enoch, M. A., Xu, K., Ferro, E., Harris, C. R., & Goldman, D. (2003). Genetic origins of anxiety in women: A role for a functional catechol-O-methyltransferase polymorphism. Psychiatric Genetics, 13, 33–41. http://dx.doi.org/10.1097/00041444-200303000-00006 Google Scholar
Eysenck, M. W., & Calvo, M. G. (1992). Anxiety and performance: The processing efficiency theory. Cognition & Emotion, 6, 409–434. http://dx.doi.org/10.1080/02699939208409696 CrossRefGoogle Scholar
Eysenck, M. W., Derakshan, N., Santos, R., & Calvo, M. G. (2007). Anxiety and cognitive performance: Attentional control theory. Emotion, 7, 336–353. http://dx.doi.org/10.1037/1528-3542.7.2.336 Google Scholar
Fales, C. L., Barch, D. M., Burgess, G. C., Schaefer, A., Mennin, D. S., & Braver, T. S. (2008). Anxiety and cognitive efficiency: Differential modulation of transient and sustained neural activity during a working memory task. Cognitive, Affective & Behavioral Neuroscience, 8, 239–253. http://dx.doi.org/10.3758/CABN.8.3.239 Google Scholar
Flehmig, H. C., Steinborn, M. B., Westhoff, K., & Langner, R. (2010). Neuroticism and speed-accuracy tradeoff in self-paced speeded mental addition and comparison. Journal of Individual Differences, 31, 130–137. http://dx.doi.org/10.1027/1614-0001/a000021 Google Scholar
Gable, P., & Harmon-Jones, E. (2010). The motivational dimensional model of affect: Implications for breadth of attention, memory, and cognitive categorization. Cognition & Emotion, 24, 322–337. http://dx.doi.org/10.1080/02699930903378305 Google Scholar
Gold, J. I., & Shadlen, M. N. (2002). Banburismus and the brain: Decoding the relationship between sensory stimuli, decisions, and reward. Neuron, 36, 299–308. http://dx.doi.org/10.1016/S0896-6273(02)00971-6 Google Scholar
Goldman, D., Oroszi, G., & Ducci, F. M. (2005). The genetics of addictions: Uncovering the genes. Nature Review Genetics, 6, 521–532. http://dx.doi.org/10.1038/nrg1635 CrossRefGoogle ScholarPubMed
Greenwood, P. M., Lin, M.-K., Sundararajan, R., Fryxell, K. J., & Parasuraman, R. (2009). Synergistic effects of genetic variation in nicotinic and muscarinic receptors on visual attention but not working memory. The Proceedings of the National Academy of Sciences of the United States of America, 106, 3633–3638. www.pnas.org/cgi/doi/10.1073/pnas.0807891106 Google Scholar
Kebir, O., Tabbane, K., Sengupta, S., & Joober, R. (2009). Candidate genes and neuropsychological phenotypes in children with ADHD: Review of association studies. Journal of Psychiatry and Neuroscience, 34, 88–101.Google Scholar
Kieling, C., Roman, T., Doyle, A. E., Hutz, M. H., & Rohde, L. A. (2006). Association between DRD4 gene and performance of children with ADHD in a test of sustained attention. Biological Psychiatry, 60, 1163–1165. http://dx.doi.org/10.1016/j.biopsych.2006.04.027 Google Scholar
Kramer, U. M., Rojo, N., Schule, R., Cunillera, T., Schols, L., Marco-Pallares, J., … Munte, T. F. (2009). ADHD candidate gene (DRD4 exon III) affects inhibitory control in a healthy sample. BMC Neuroscience, 10, 150. http://dx.doi.org/10.1186/1471-2202-10-150 Google Scholar
Lachman, H. M., Papolos, D. F., Saito, T., Yu, Y. M., Szumlanski, C. L., & Weinshilboum, R. M. (1996). Human catechol-O-methyltransferase pharmacogenetics: Description of a functional polymorphism and its potential application to neuropsychiatric disorders. Pharmacogenetics, 6, 243–250. http://dx.doi.org/10.1097/00008571-199606000-00007 CrossRefGoogle ScholarPubMed
Langley, K., Marshall, L., Van den Bree, M., Thomas, H., Owen, M., O'Donovan, M., & Thapar, A. (2004). Association of the dopamine D4 receptor gene 7-repeat allele with neuropsychological test performance of children with ADHD. American Journal of Psychiatry, 161, 133–138. http://dx.doi.org/10.1176/appi.ajp.161.1.133 Google Scholar
Li, D., Sham, P. C., Owen, M. J., & He, L. (2006). Meta-analysis shows significant association between dopamine system genes and attention deficit hyperactivity disorder (ADHD). Human Molecular Genetics, 15, 2276–2284. http://dx.doi.org/10.1093/hmg/ddl152 Google Scholar
Munafò, M. R., Yalcin, B., Willis-Owe, S. A., & Flint, J. (2008). Association of the dopamine D4 receptor (DRD4) gene and approach-related personality traits: Meta-analysis and new data. Biological Psychiatry, 63, 197–206. http://dx.doi.org/10.1016/j.biopsych.2007.04.006 Google Scholar
Pacheco-Unguetti, A. P., Acosta, A., Callejas, A., & Lupianez, J. (2010). Attention and anxiety: Different attentional functioning under state and trait anxiety. Psychological Science, 21, 298–304. http://dx.doi.org/10.1177/0956797609359624 Google Scholar
Parasuraman, R., Greenwood, P. M., Kumar, R., & Fossella, J. (2005). Beyond heritability: Neurotransmitter genes differentially modulate visuospatial attention and working memory. Psychological Science, 16, 200–207. http://dx.doi.org/10.1111/j.0956-7976.2005.00804.x Google Scholar
Parasuraman, R., & Jiang, Y. (2012). Individual differences in cognition, affect, and performance: Behavioral, neuroimaging, and molecular genetic approaches. NeuroImage, 59, 70–82. http://dx.doi.org/10.1016/j.neuroimage.2011.04.040 Google Scholar
Petronis, A., Van Tol, H. H., Lichter, J. B., Livak, K. J., & Kennedy, J. L. (1993). The D4 dopamine receptor gene maps on 11p proximal to HRAS. Genomics, 18, 161–163. http://dx.doi.org/10.1006/geno.1993.1445 CrossRefGoogle ScholarPubMed
Posner, M. I., & Rothbart, M. K. (2009). Toward a physical basis of attention and self regulation. Physics of Life Reviews, 6, 103–120. http://dx.doi.org/10.1016/j.plrev.2009.02.001 Google Scholar
Rende, R. (2012). Behavioral resilience in the post-genomic era: Emerging models linking genes with environment. Frontiers in Human Neuroscience, 6, 50. http://dx.doi.org/10.3389/fnhum.2012.00050 Google Scholar
Richards, A., French, C. C., Keogh, E., & Carter, C. (2000). Test anxiety, inferential reasoning and working memory load. Anxiety, Stress, and Coping, 13, 87–109. http://dx.doi.org/10.1080/10615800008248335 Google Scholar
Sadeh, N., & Bredemeier, K. (2011). Individual differences at high perceptual load: The relation between trait anxiety and selective attention. Cognition & Emotion, 25, 747–755. http://dx.doi.org/10.1080/02699931.2010.500566 Google Scholar
Schmidt, L. A., Fox, N. A., Perez-Edgar, K., & Hamer, D. H. (2009). Linking gene, brain, and behavior: DRD4, frontal asymmetry, and temperament. Psychological Science, 20, 831–837. http://dx.doi.org/10.1111/j.1467-9280.2009.02374.x Google Scholar
Stern, Y. (2002). What is cognitive reserve? Theory and research application of the reserve concept. Journal of the International Neuropsychological Society, 8, 448–460. http://dx.doi.org/10.1017/S1355617702813248 CrossRefGoogle ScholarPubMed
Szekely, A., Balota, D. A., Duchek, J. M., Nemoda, Z., Vereczkei, A., & Sasvari-Szekely, M. (2011). Genetic factors of reaction time performance: DRD4 7-repeat allele associated with slower responses. Genes, Brain and Behavior, 10, 129–136. http://dx.doi.org/10.1111/j.1601-183X.2010.00645.x Google Scholar
Tunbridge, E. M., Harrison, P. J., &Weinberger, D. R. (2006). Catechol-o-methyltransferase, cognition, and psychosis: Val158Met and beyond. Biological Psychiatry, 60, 141–151. http://dx.doi.org/10.1016/j.biopsych.2005.10.024 Google Scholar
Wray, N. R., James, M. R., Dumenil, T., Handoko, H. Y., Lind, P. A., Montgomery, G. W., & Martin, N. G. (2008). Association study of candidate variants of COMT with neuroticism, anxiety and depression. American Journal of Medical Genetics. Part B: Neuropsychiatric Genetics, 147B, 1314–1318. http://dx.doi.org/10.1002/ajmg.b.30744 Google Scholar
Yeh, T. K., Chang, C. Y., Hu, C. Y., Yeh, T. C., & Lin, M. Y. (2009). Association of catechol-O-methyltransferase (COMT) polymorphism and academic achievement in a Chinese cohort. Brain & Cognition, 71, 300–305. http://dx.doi.org/10.1016/j.bandc.2009.07.011 Google Scholar