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The relationship between the Met allele of the BDNF Val66Met polymorphism and impairments in decision making under ambiguity in patients with obsessive-compulsive disorder
2011; Wiley; Volume: 10; Issue: 5 Linguagem: Inglês
10.1111/j.1601-183x.2011.00687.x
ISSN1601-1848
AutoresF.F. Rocha, Leandro Fernandes Malloy‐Diniz, Naira Vassalo Lage, Humberto Corrêa,
Tópico(s)Eating Disorders and Behaviors
ResumoGenes, Brain and BehaviorVolume 10, Issue 5 p. 523-529 Free Access The relationship between the Met allele of the BDNF Val66Met polymorphism and impairments in decision making under ambiguity in patients with obsessive–compulsive disorder F. F. da Rocha, Corresponding Author F. F. da Rocha Medicine Molecular ProgramDr F. F. da Rocha, Rua Sapucaia 83, Cond. Retiro das Pedras, CEP:35460000, Brumadinho, Minas Gerais, Brasil. E-mail: fil_bh@yahoo.com.brSearch for more papers by this authorL. Malloy-Diniz, L. Malloy-Diniz Department of Psychology Neuroscience ProgramSearch for more papers by this authorN. V. Lage, N. V. Lage Medicine Molecular ProgramSearch for more papers by this authorH. Corrêa, H. Corrêa Medicine Molecular Program Neuroscience Program Department of Mental Health, Faculty of Medicine, Universidade Federal de Minas Gerais–UFMG, Belo Horizonte, BrazilSearch for more papers by this author F. F. da Rocha, Corresponding Author F. F. da Rocha Medicine Molecular ProgramDr F. F. da Rocha, Rua Sapucaia 83, Cond. Retiro das Pedras, CEP:35460000, Brumadinho, Minas Gerais, Brasil. E-mail: fil_bh@yahoo.com.brSearch for more papers by this authorL. Malloy-Diniz, L. Malloy-Diniz Department of Psychology Neuroscience ProgramSearch for more papers by this authorN. V. Lage, N. V. Lage Medicine Molecular ProgramSearch for more papers by this authorH. Corrêa, H. Corrêa Medicine Molecular Program Neuroscience Program Department of Mental Health, Faculty of Medicine, Universidade Federal de Minas Gerais–UFMG, Belo Horizonte, BrazilSearch for more papers by this author First published: 14 March 2011 https://doi.org/10.1111/j.1601-183X.2011.00687.xCitations: 26AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract Brain-derived neurotrophic factor (BDNF) gene has an important link to neurotransmitter systems, including serotonin, and seems to play a major role in emotional decision making. Impairment of decision making is an important feature of psychiatric disorders such as obsessive–compulsive disorder (OCD). We explore the link between decision making and the BDNF Val66Met polymorphism, which results in a reduction of BDNF activity, in a sample of Caucasian OCD patients. We used the Iowa Gambling Task (IGT) to measure decision making in 122 OCD patients. All patients were assessed using the Yale–Brown Obsessive–Compulsive Scale, the Beck Depression Inventory, the Beck Anxiety Inventory and the Raven Progressive Matrices. Patients also performed the Continuous Performance Task (CPT-II) and the Trail Making Test (TMT). We grouped Met-allele carriers because these act in a dominant way. Met-allele carries exhibited low performance on both halves of the IGT (first half –F = −2.51, df = 120, P = 0.01; second half –F = −2.32, df = 120, P = 0.02). However, logistic regression analyses showed that the influence of the Met allele seemed to be restricted to the first half of the IGT [first half –β = 0.55, df = 1, P < 0.01, odds ratio (OR) = 5.62; second half –β = 0.32, df = 1, P = 0.15, OR = 2.30]. No differences were observed in tests used to evaluate executive functions associated with the dorsolateral prefrontal cortices (TMT and CPT-II, df = 120, P > 0.05 for both). Met-allele impairment may only be related to decisions made under ambiguous conditions. The null results involving TMT and CPT-II are possibly related to the dysfunction of the orbitofrontal cortices that is associated with OCD. Obsessive–compulsive disorder (OCD) is a heritable psychiatric disorder characterized by intrusive, troubling thoughts that are perceived as the product of one's own mind and/or repetitive, compulsive behaviors or mental rituals (da Rocha et al. 2008b). Current research approaches include biological models based on direct and indirect investigations of brain circuits involved in the expression of obsessive–compulsive symptoms (Kwon et al. 2009). Neuroimaging techniques suggest that the frontosubcortical circuit, including the orbitofrontal cortex (OFC), basal ganglia and amygdala, is a core circuit involved in the expression of OCD (Cavallaro et al. 2003; Chamberlain et al. 2008; Kwon et al. 2009). Moreover, the integrity of this circuit is believed to be specifically related to the proper performance of executive functions and a variety of neuropsychological studies have observed cognitive dysfunctions among OCD patients (Chamberlain et al. 2008; Ho et al. 2006; Kwon et al. 2009; Li et al. 2010; Menzies et al. 2008; Nielen et al. 2002; Olley et al. 2007; da Rocha et al. 2008a,b; Schlösser et al. 2010; Starcke et al. 2009, 2010). Considering the heterogeneity of clinical manifestations of executive functions, some authors emphasize the division between the 'cold' and 'hot' components of executive functions. The former component of executive function is related to the dorsolateral prefrontal network and encompasses mechanistic cognitive abilities (i.e. planning, problem-solving, working memory and abstract reasoning). The latter component is related to the orbitofrontal prefrontal network and involves functions such as interpersonal and social behavior, real-life decision making and emotional regulation during social interaction (Chan et al. 2008; Geurts et al. 2006). Decision making is the ability to process the necessary environmental information to make advantageous decisions (da Rocha et al. 2008b). Neurological studies have shown that both the ability to make helpful real-life decisions, which involves emotional arousal, choosing between actions that may lead to uncertain outcomes, and the ability to calibrate between rewards and punishments depend on the integrity of the OFC and its interconnected circuits, especially the mesolimbic circuitry (Li et al. 2010; Nielen et al. 2002; da Rocha et al. 2008b; Starcke et al. 2009, 2010). Many studies have used the Iowa Gambling Task (IGT), an experimental neuropsychological task designed to study the integration of emotion and cognition in decision-making processes, to show impairments in psychiatric disorders such as alcohol abuse, OCD, borderline personality disorder and suicidal behaviors (Malloy-Diniz et al. 2007, 2008, 2009; Nielen et al. 2002, da Rocha et al. 2008b). Although obsessive–compulsive symptoms may involve deficiencies in the decision-making process, it is important to understand the role of decision making in OCD (Nielen et al. 2002; Starcke et al. 2009, 2010). The brain-derived neurotrophic factor (BDNF) gene seems to be a potential candidate biomarker for emotional decision making (Gasic et al. 2009; Kang et al. 2010). It has an important effect on the proliferation of neurotransmitter systems, including serotonin. Brain-derived neurotrophic factor is associated both with OCD and with the physiological development of central serotoninergic neurons in early adulthood (Bath & Lee 2006; da Rocha et al. 2010; Roth & Sweatt in press). Additionally, BDNF also plays a major role in neuronal survival, neurogenesis and synaptic plasticity and has been implicated in various higher cognitive processes, including decision making, learning and memory (Bath & Lee 2006; Kang et al. 2010; Tramontina et al. 2009; Yamada et al. 2002). A widely investigated polymorphism of the BDNF gene is BDNF Val66Met, which reduces BDNF activity. Previous studies have associated the Met allele to harm avoidance, depression, schizophrenia, bipolar disorder, OCD and poor performance on tests of executive functioning, although findings are inconsistent (Bath & Lee 2006; Deltheil et al. 2008; Kang et al. 2010; da Rocha et al. 2010; Rybakowski 2008; Tramontina et al. 2009; Yamada et al. 2002). We sought to investigate whether the decision-making process in OCD patients is influenced by the BDNF Val66Met polymorphism. We hypothesized that the BDNF Val66Met polymorphism will be associated with dysfunctions of the frontosubcortical circuit and thus will be related to decision-making processes in OCD patients. Methods Participants and clinical assessments We assessed 122 patients (65 men and 57 women) who ranged in age from 18 to 65 years old. All patients self-identified as Brazilian-Caucasian. Diagnosis was made by a trained psychiatrist who administered a semi-structured interview (MINI-PLUS) (Sheehan et al. 1998), a structured interview that follows Diagnostic and Statistical Manual of Mental Disorders, 4th edition criteria, and conducted a complete review of medical records and an interview with at least one close relative. Patients who did not show hoarding behaviors were selected using a well-validated screening instrument: the Dimensional Yale–Brown Obsessive–Compulsive Scale (DY–BOCS) (Rosario-Campos et al. 2006). All patients were also assessed with the Y–BOCS (Goodman et al. 1989a,b), the Beck Depression Inventory (BDI) (Beck et al. 1961) and the Beck Anxiety Inventory (BAI) (Beck et al. 1988). We excluded participants with a current major depressive disorder, substance-related disorder, psychotic disorder or a lifetime history of traumatic brain injury or vascular brain disorder. Patients in a current manic or hypomanic episode were also excluded. Because hoarding symptoms may be phenomenologically and neurobiologically distinct from other common OCD symptom dimensions, individuals who also presented as hoarders were excluded (Grisham et al. 2010). None of our patients was characterized as a prominent hoarder and only a minority of patients (n = 6) showed mild hoarding symptoms. Patients were clinically medicated as follows: 71 (58.19%) were prescribed selective serotonin reuptake inhibitors, 20 (16.39%) were prescribed clomipramine, 6 (4.91%) were prescribed clomipramine + risperidone, 10 (8.19%) were prescribed a selective serotonin reuptake inhibitor + risperidone and 14 (11.47%) were not prescribed medication. All patients who were medicated had been taking the same dose of psychotropic medications for at least 12 weeks. The study was completed in accordance with the guidelines of the Helsinki Declaration and approved by the Local Ethics Committee. The subjects were provided with a complete description of the study before written informed consent was obtained. Genotyping Participants donated venous blood for DNA extraction. Blood samples were collected and DNA was obtained using the high salt method. Genotyping was performed using a made-to-order TaqMan genotyping assay (Applied Biosystems, Foster City, CA, USA) and a Mx3005P QPCR System (Stratagene, La Jolla, CA, USA) in the allelic discrimination mode. Investigators who performed the genotyping were blind to the subjects' clinical status. There was a duplicate run to check genotyping accuracy (error rate <2%). Neuropsychological assessment Subjects completed the computerized version of the IGT, which has been adapted according to the original design. The task ends when the subject has chosen 100 cards, although the subject does not know when the game will end. A virtual reward of $100 was given for selecting a card from either deck A or deck B, and a $50 reward was given for cards selected from decks C and D. However, at some points, a form of punishment unpredictably followed the selection of a card in any of the four decks. Unbeknownst to the subjects, for every 10 cards chosen from decks A or B, subjects earned $1000 but lost $1250 in unpredictable punishments. For every 10 cards chosen from decks C or D, subjects earned $500 but lost $250 in punishments. We obtained two IGT subscores by subtracting the total number of picks from the disadvantageous decks from the total number of picks from the advantageous decks [(C + D) − (A + B)] for the first 50 trials (1–50; first-half IGT score) and also for the second 50 trials (51–100; second-half IGT score). The first-half IGT score reflects guessing or 'decision making under ambiguity', as the subjects were forced to make choices in conditions of maximal uncertainty and to learn to avoid the disadvantageous card decks by using feedback from previous trials. This period is also known as the ambiguity phase. The second-half IGT score represents 'decision making under risk', when the subjects had obtained more feedback from their choices but were still forced to decide under uncertain conditions (Malloy-Diniz et al. 2008). This period is also known as the risk phase. Decision making in the IGT relies on multiple cognitive processes including the ability to respond flexibly to changing contingencies, inhibit a dominant response, identify the solution to a novel problem and monitor prior responses and their outcomes. Because cognitive impairments may intervene with the decision-making process, we used additional tasks to evaluate this influence on the IGT: the Trail Making Test (TMT) and the Continuous Performance Task (CPT-II). The potential contribution of intelligence, as measured by the Raven Progressive Matrices test, was also examined (Malloy-Diniz et al. 2009; Raven et al. 1948; Reitan & Wolfson 1985, da Rocha et al. 2008b). The CPT-II provides measures of sustained attention and motor impulsiveness. In this task, the subject is instructed to press a spacebar when any letter other than the letter X appears on screen. An omission error occurs when the subject fails to press the spacebar when a letter other than X appears. Omission errors reflect a failure to react to a target stimulus. A commission error occurs when the subject presses the spacebar when the letter X appears on the screen. Commission errors reflect a failure to inhibit a prepotent motor response. We used omission and commission errors as dependent measures to evaluate the attentional and motor impulsivity, respectively (Malloy-Diniz et al. 2007). The TMT is a pencil and paper task that requires individuals to connect a series of circles in order. Part A of the TMT (Trail A) contains only numbered circles, whereas Part B (Trail B) includes both numbered and lettered circles and requires the participants to alternate between numbers and letters while connecting the circles in the correct order. Both parts require visual scanning ability, motor speed and dexterity, and correlate well with other tests of speeded processing. Part B is also considered a measure of cognitive flexibility, alternating attention and the ability to inhibit a dominant incorrect response. The TMT is considered to be reliable, valid and sensitive to neurological impairment and brain damage. The difference in completion times for Part B and Part A (Trail B - Trail A) is thought to represent executive deficits and to eliminate the influence of visual and motor abilities on performance (Rybakowski 2008). Statistical analysis On the basis of the evidence from previous functional studies and considering the dominant effect of the Met allele, groups of patients having Val/Met and Met/Met genotypes were merged for analytical purposes (da Rocha et al. 2010). Differences in dichotomous variables were calculated by the Chi squared test. The differences between groups on continuous variables were tested with the Student's t test. Correlations between IGT performance and six potential covariates (age at onset, depressive and anxiety symptoms, CPT-II performance, TMT performance and severity of OCD measured by Y–BOCS) were analyzed using the Pearson correlation test. Two multiple logistic regression models with genotype group as the dependent variable and the factors that were statistically significant in a univariate analysis as independent variables were performed to control for possible confounding factors. SPSS 15.0 for Windows (SPSS Inc., Chicago, IL, USA) was used for all statistical analyses. Results were considered significant when P≤ 0.05. Results Forty (32.78%) participants carried the Met allele. The remainder of the sample (n = 82; 67.22%) did not carry. The clinical, demographic and neuropsychological variables of the sample are summarized in Table 1. Table 1. Clinical, demographic and neuropsychological variables between OCD patients: Met-allele carriers vs. non-Met-allele carriers Demographic and clinical features Met/Met + Val/Met (n = 40) Val/Val (n = 82) χ 2 or F test df P-value Mean age ± SD years 28.40 ± 14.12 29.33 ± 13.22 0.02 120.0 0.97 Male gender (%) 52.50% (n = 21) 53.65% (n = 44) −0.12 1 0.90 Years of formal education ± SD 10.56 ± 4.87 10.26 ± 4.90 0.31 120.0 0.75 Intelligence 42.48 ± 6.75 42.12 ± 7.88 0.24 120.0 0.80 Mean age at onset ± SD (years) 17.04 ± 12.51 23.43 ± 8.98 −2.88 120.0 <0.01 Mean Y–BOCS score ± SD Obsessions 13.21 ± 2.76 12.08 ± 3.89 1.84 120.0 0.06 Compulsions 12.00 ± 4.87 12.69 ± 4.12 −0.81 120.0 0.41 Total 25.85 ± 7.91 25.32 ± 8.19 0.33 120.0 0.73 Mean BAI score ± SD 20.75 ± 10.32 21.01 ± 8.85 −0.14 120.0 0.88 Mean BDI score ± SD 13.77 ± 5.04 9.56 ± 6.43 3.63 120.0 <0.01 Absence of axis I comorbidity (%) 12.50% (n = 5) 22.22% (n = 18) −1.25 – 0.21 IGT IGT – net score −5.98 ± 10.34 −0.89 ± 9.64 −2.67 120.0 <0.01 IGT – [(C + D) − (A = B)] for first 50 cards −3.16 ± 6.84 −0.27 ± 5.48 −2.51 120.0 0.01 IGT – [(C + D) − (A = B)] for second 50 cards −3.69 ± 6.66 −0.78 ± 6.40 −2.32 120.0 0.02 TMT (Trails B - A) 58.15 ± 63.98 63.76 ± 80.45 −0.38 120.0 0.70 CPT-II Omission errors 11.15 ± 9.76 8.19 ± 10.45 1.50 120.0 0.13 Commission errors 11.66 ± 8.37 9.98 ± 7.34 1.13 120.0 0.25 No significant differences were found between the groups in terms of education level, gender, intelligence, age, symptoms of anxiety and seriousness of obsessive–compulsive symptoms. The non-Met carriers had lower depressive symptom scores and later ages of onset of obsessive–compulsive symptoms. Non-Met carriers performed significantly better on both parts of the IGT and had better total net scores on the IGT (Table 1 and Fig. 1). No differences were observed in the performance of the IGT-II or the TMT. Figure 1Open in figure viewerPowerPoint IGT performance among genotype groups: Met-allele carries vs. non-Met-allele carries.*P < 0.01; error bars = SD. Pearson analyses showed several clinical associations between the Y–BOCS, BAI, BDI and the age at onset for both groups (Tables 2 and 3). Table 2. Correlations between clinical and neuropsychological features in non-Met-carrier OCD patients 1 2 3 4 5 6 7 8 9 10 Commission error x 0.14 0.09 0.11 0.10 0.02 −0.18 −0.21 0.31 0.18 Omission error — x 0.17 −0.14 −0.08 −0.05 0.15 0.54** −0.23 0.15 TMT — — x −0.21 −0.12 −0.14 −0.21 −0.10 0.36** 0.19 IGT – net score — — — x 0.30** 0.62** 0.10 −0.14 0.20 −0.44** IGT – first half — — — — x 0.35* 0.07 −0.09 0.14 −0.29* IGT – second half — — — — — x 0.14 −0.13 0.10 0.19 Age at onset — — — — — — x −0.24* −0.27* −0.25* BAI — — — — — — — x 0.23* 0.29* BDI — — — — — — — — x 0.30* Y–BOCS — — — — — — — — — x **P < 0.05; **P < 0.01. All tests have df = 80. Table 3. Correlations between clinical and neuropsychological features in Met-carrier OCD patients 1 2 3 4 5 6 7 8 9 10 Commission error x 0.18 0.15 0.17 0.04 0.05 −0.19 −0.19 0.30 0.15 Omission error — x 0.13 −0.18 −0.10 −0.07 0.14 0.59** −0.21 0.19 TMT — — x −0.19 −0.15 −0.17 −0.19 −0.13 0.40** 0.21 IGT – net score — — — x 0.67** 0.59** 0.18 −0.12 −0.32* −0.42** IGT – first half — — — — x 0.67** 0.20 −0.19 0.08 0.03 IGT – second half — — — — — x 0.19 −0.11 0.11 0.21 Age at onset — — — — — — x −0.28* −0.25* −0.29* BAI — — — — — — — x 0.24* 0.25* BDI — — — — — — — — x 0.29* Y–BOCS — — — — — — — — — x * P < 0.05; **P < 0.01. All tests have df = 38. Analysis of associations between clinical features and cognitive performance revealed negative correlations between the Y–BOCS score and the IGT net score for both groups (r = −0.42 for Met carriers, r = −0.44 for non-Met carriers, P < 0.01). Negative correlations were also found between the Y–BOCS score and the first 50 blocks score (IGT) for the non-Met carriers (r = −0.29, P < 0.05). The BDI score was found to be negatively correlated with the IGT net score for the Met carriers (r = −0.32, P < 0.05). For both the groups, anxiety symptoms were correlated with omission errors (CPT-II) (r = 0.59 for Met carriers, r = 0.54 for non-Met carriers, P < 0.01) and depressive symptoms were related with the performance on the TMT (r = 0.40 for Met carriers, r = 0.36 for non-Met carriers, p < 0.01). In addition, correlations between neuropsychological performances were evaluated and were not found to be significant. However, the two halves of the IGT were found to be significantly related. The IGT net score was positively associated with scores on both the first and the second halves of the IGT for both groups. Scores on the second half of the IGT were positively correlated to scores on the first half of the IGT for both groups (r = 0.67 for Met-allele carriers, P < 0.01; r = 0.35, P < 0.05 for non-Met carriers). Two logistic regression analyses were performed to evaluate the influence of the variables on the IGT net score for both the genotype groups (Table 4). For Met carriers, the variables included revealed an R2 = 0.48 (SE = 9.65), df = 1 and an F value of 8.97 (P = 0.03). For non-Met carriers, results were as follows: R2 = 0.73 (SE = 11.91), df = 1 and F = 18.26 (P < 0.01). As shown in Table 4, we observed that lower scores on the second half of the IGT for Met-allele carriers were not significant, which suggests that performance on this task is secondary to a lower first-half performance. Table 4. Logistic regression analyses of IGT performance (net score) by BDNF Val66Met genotype groups of OCD patients Predictor variable β P-value Odds ratio Non-Met-carrier OCD patients IGT—first half 0.78 <0.01 9.49 IGT—second half 0.52 <0.01 6.03 Age at OCD onset 0.01 0.85 0.13 BDI score −0.21 0.44 1.53 Y–BOCS score −0.27 0.41 1.48 Met-carrier OCD patients IGT – first half 0.55 <0.01 5.62 IGT – second half 0.35 0.15 2.30 Age at OCD onset 0.09 0.76 0.22 BDI score −0.29 0.39 1.83 Y–BOCS score −0.15 0.54 1.99 All tests have df = 1. Discussion Our study showed that OCD patients who carry the Met allele exhibited lower performances on the first and second halves of the IGT than patients who did not carry the Met allele, which suggests that these patients have impaired decision-making ability when faced with both ambiguity and risk. However, after statistical analysis, the influence of the Met allele seems to be restricted to the first half of the IGT and thus may only be related to decision under conditions of ambiguity. To make an advantageous decision, we have to use multiple cognitive and affective processes including recall of previous experiences of reward or punishment associated with behavioral choices, temporary holding of this information in working memory and planning for a future optimal outcome. Decision making under conditions of ambiguity and risk may involve partially independent brain circuits. Although decision making under conditions of ambiguity is related to a 'limbic' loop of affective processing, decision making under conditions of risk may involve a 'cognitive' loop (Ha et al. 2009; Li et al. 2010; da Rocha et al. 2008b; Starcke et al. 2009, 2010; Stoltenberg & Vandever 2010). Our findings are consistent with affective processing studies in which individuals with the Met allele exhibit dysfunctions in amygdala activation to fearful or ambiguous stimuli, which disrupt amygdala–cingulate coupling after experiencing an emotional stimuli (Harrison et al. 2009; Roth & Sweatt in press). These findings are essential for understanding adequate performances of decision making under conditions of ambiguity, as the amygdala is suggested to be a critical structure involved in the processing of primary inducers and emotional arousal that is associated with the anticipation of rewards and punishments (Bath & Lee 2006; Harrison et al. 2009; Roth & Sweatt in press; Yamada et al. 2002). Interestingly, studies have showed decreased amygdale activation in OCD patients, thus corroborating the hypothesis of a dysfunction of the 'limbic' loop. Indeed, this structure is believed to be highly relevant to the pathophysiology of OCD given its prominent role in fear conditioning (Britton et al. 2010; Cannistraro et al. 2004). These hypotheses are in agreement with the somatic marker hypothesis (SMH), which was developed to address the problems of decision making in patients with lesions of the ventromedial prefrontal cortex who had compromised emotions. According to this hypothesis, somatic markers are special feelings that are not consciously experienced that are generated by emotions. These markers have been connected by learning to predict future outcomes in specific scenarios. For example, when a negative somatic marker is repeatedly associated with a particular future outcome, the resulting combination functions as an alarm bell which warns that the decision must be modified for a positive outcome to occur. Iowa Gambling Task has been a useful tool for investigating the SMH. Impaired emotional responses that are possibly related to the amygdala dysfunction in Met carriers corroborate the SMH, as somatic markers are essential to the process of making advantageous decisions before individuals are consciously aware of which decisions are advantageous. Nonetheless, performance on the IGT has been associated with obsessive–compulsive traits rather than with SMH in psychiatric subjects (Liao et al. 2009). Therefore, future studies are needed to address the nature of the relationships among the Met allele, obsessive traits and the somatic marker hypotheses. Met-allele patients performed poorly on the second half of IGT as compared with non-Met-allele patients. However, this result was also associated with their performance on the first half of the task. Decision making under conditions of risk is associated with specific executive functions (i.e. set shifting) and the processing of feedback from previous trials within the task (van den Bos et al. 2009; Ha et al. 2009; Li et al. 2010; da Rocha et al. 2008a,b). As the first half of the task appears to be impaired by the presence of the Met allele, performance on the second half may have been worse among these patients because the feedback from the first 50 cards was thought to guide the decision-making process for the second half of the task. The complexity of the cognitive loop associated with decision making under conditions of risk may be influenced by other features or polymorphisms, as shown by some studies that evaluated the influence of gene interactions on decision-making processes (Starcke et al. 2009, 2010; Stoltenberg & Vandever 2010). In a previous study, we observed that the decision-making process was influenced by a polymorphism of the serotonin transporter, the 5-HTTLPR. Patients carrying the 5-HTTLPR LaLa genotype showed significant improvements on the task, especially during the second half, which suggests that genetic modulation of serotonin affects decision making under conditions of risk (da Rocha et al. 2008b). Future studies should further analyze the role of gene–gene interactions in decision-making processes. Studies have also shown an association between the Met allele and decreased volumes of the dorsolateral prefrontal cortex, an area associated with planning and higher order cognitive functioning, as well as decreased volume of subcortical regions such as the caudate nucleus (Bath & Lee 2006; Deltheil et al. 2008; Kang et al. 2010). Consistent with other studies, executive dysfunction associated with these regions has been related to the Met allele (Bath & Lee 2006; Kang et al. 2010; Tramontina et al. 2009; Yamada et al. 2002). However, no genotype differences were observed for performance on the CPT-II or the Tail Making Test, which are tasks that are related to the dorsolateral prefrontal cortex (Bath & Lee 2006; Harrison et al. 2009; Kang et al. 2010; Tramontina et al. 2009). Considering that dysfunction of the OFC is involved in OCD, we hypothesize that the presence of the Met allele may lead to impairments of cognitive functions that are related to the OFC (i.e. IGT) but that it is not sufficient to influence the performance on tasks associated with the dorsolateral prefrontal cortices. Furthermore, we hypothesize that the complexity of these executive functions is influenced by other polymorphisms and that epigenetics should be necessary to lead to other neuropsychological findings. Caution should be taken in generalizing the results of this study, as there are some methodological limitations. Although there is a high comorbidity of DSM-IV axis I and II disorders in OCD, not all possible comorbidities were considered exclusion criteria. Most patients in our sample were receiving psychotropic medication at the time of the study, but no steps were taken in this study to reduce the possible influence of medication, and it was not possible to assess possible influences. Although several studies evaluate associations between dopamine and serotonin, only a few investigations have studied the possible effects of psychotropic medication on decision making. Of these studies, most focus on the serotonergic pathway. Briefly, results of these studies suggest that abrupt elevations of serotonin impair decision making. This data were observed after sin
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