International Journal of Neuropsychopharmacology (2018) 21(8): 725–733 doi:10.1093/ijnp/pyy035 Advance Access Publication: May 9, 2018 Regular Research Article regular research article Corticostriatal Connectivity in Antisocial Personality Disorder by MAO-A Genotype and Its Relationship to Aggressive Behavior Nathan J. Kolla, Katharine Dunlop, Jeffrey H. Meyer, Jonathan Downar Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada (Drs Kolla, Meyer, and Downar); Centre for Addiction and Mental Health (CAMH) Research Imaging Centre, Toronto, Ontario, Canada (Drs Kolla and Meyer); Violence Prevention Neurobiological Research Unit, CAMH, Toronto, Ontario, Canada (Dr Kolla); Krembil Neuroscience Centre, Toronto Western Hospital, Toronto, Ontario, Canada (Ms Dunlop and Dr Downar); Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada (Ms Dunlop). Correspondence: Nathan Kolla, MD, PhD, Centre for Addiction and Mental Health, 250 College Street, Room 626, Toronto, Ontario, Canada, M5T 1R8 (firstname.lastname@example.org). ABSTRACT Background: The influence of genetic variation on resting-state neural networks represents a burgeoning line of inquiry in psychiatric research. Monoamine oxidase A, an X-linked gene, is one example of a molecular target linked to brain activity in psychiatric illness. Monoamine oxidase A genetic variants, including the high and low variable nucleotide tandem repeat polymorphisms, have been shown to differentially affect brain functional connectivity in healthy humans. However, it is currently unknown whether these same polymorphisms influence resting-state brain activity in clinical conditions. Given its high burden on society and strong connection to violent behavior, antisocial personality disorder is a logical condition to study, since in vivo markers of monoamine oxidase A brain enzyme are reduced in key affect- modulating regions, and striatal levels of monoamine oxidase A show a relation with the functional connectivity of this same region. Methods: We utilized monoamine oxidase A genotyping and seed-to-voxel-based functional connectivity to investigate the relationship between genotype and corticostriatal connectivity in 21 male participants with severe antisocial personality disorder and 19 male healthy controls. Results: Dorsal striatal connectivity to the frontal pole and anterior cingulate gyrus differentiated antisocial personality disorder subjects and healthy controls by monoamine oxidase A genotype. Furthermore, the linear relationship of proactive aggression to superior ventral striatal-angular gyrus functional connectivity differed by monoamine oxidase A genotype in the antisocial personality disorder groups. Conclusions: These results suggest that monoamine oxidase A genotype may affect corticostriatal connectivity in antisocial personality disorder and that these functional connections may also underlie use of proactive aggression in a genotype- specific manner. Keywords: antisocial personality disorder, monoamine oxidase A, resting-state functional magnetic resonance imaging Received: July 17, 2017; Revised: February 28, 2018; Accepted: May 1, 2018 © The Author(s) 2018. Published by Oxford University Press on behalf of CINP. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, 725 provided the original work is properly cited. For commercial re-use, please contact email@example.com Downloaded from https://academic.oup.com/ijnp/article-abstract/21/8/725/4994274 by Ed 'DeepDyve' Gillespie user on 07 August 2018 726 | International Journal of Neuropsychopharmacology, 2018 Significance Statement Antisocial personality disorder (ASPD) is a serious psychiatric condition that presents with high aggression and violence. Monoamine oxidase A (MAO-A) is a gene comprising different variants that show a relation to brain activity in healthy humans. However, it has not been demonstrated whether these variants are also associated with brain activation patterns in ASPD. Therefore, we used resting-state functional magnetic resonance imaging to study brain activity in healthy control participants and subjects with ASPD. We found that the high-activity MAO-A variant was related to stronger brain connections in ASPD between the dorsal caudate, a brain region involved in decision making, and frontal brain areas. Functional connectivity from the superior ventral striatum to the angular gyrus also revealed an interaction between ASPD and proactive or premeditated aggres- sion. Our results suggest that brain connections in ASPD and violence may be under control by the MAO-A gene. Introduction Antisocial personality disorder (ASPD) is a chronic psychiatric MAO-A genotypic effects, in combination with in vivo brain condition characterized by aggressive behavior that frequently markers, may influence FC. Clinically, differential FC in ASPD leads to criminal offending (Barratt et al, 1997). Longitudinal with MAOA-L or MAOA-H could indicate biological subtypes, studies show that ASPD-afflicted males experience severe life- reflected by propensity for aggression, violent recidivism, and long interpersonal problems (Paris, 2003). Furthermore, some manifestation of substance misuse (Kolla and Vinette, 2017). estimates suggest that 7% of the general population (Swanson Since no study has ever examined whether MAO-A polymor - et al, 1994) and nearly 50% of incarcerated individuals (Fazel and phisms differentially affect FC in ASPD, we investigated the Danesh, 2002) meet criteria for ASPD. This evidence provides a FC of previously employed VS seeds (Kolla et al, 2016) and a compelling rationale to intensify research efforts. dorsal caudate seed from the same striatal parcellation. Our Increasingly, studies have identified genetic polymorphisms aim was to determine whether resting-state FC differed by in psychiatric populations that may influence brain endopheno- MAO-A genotype in ASPD and healthy controls. Based on the types, including neural circuitry. For example, monoamine oxi- rs-fMRI results in healthy individuals (Clemens et al, 2015), dase A (MAO-A) is one gene vigorously pursued as a psychiatric we hypothesized that differences would emerge in corticos- endophenotype, as it functions to degrade monoamine neuro- triatal resting-state FC by diagnosis (control and ASPD), geno- transmitters (Youdim et al, 2006). MAO-A is particularly impli- type (high- and low-activity MAO-A), and in the interaction of cated in impulsive, aggressive phenotypes, as positron emission group× genotype. tomography (PET) studies demonstrate lower brain MAO-A lev- els in ASPD and aggressive individuals (Kolla et al, 2015). A com- mon variable nucleotide tandem repeat (VNTR) polymorphism Methods in the MAO-A promoter region affects transcriptional activity in cell lines. Alleles with 3.5 or 4 copies of the VNTR are transcribed Subjects more efficiently (high activity: MAOA-H) than alleles with 2 or 3 VNTR repeats (low activity: MAOA-L) (Sabol et al, 1998). Twenty-one males with ASPD and 19 sex-matched healthy con- Resting-state fMRI (rs-fMRI) is a functional neuroimaging trols completed the study. A total of 163 individuals who con- technique that measures spontaneous neural activity in the tacted the study authors to be part of the experimental group absence of a task stimulus. To our knowledge, a single rs-fMRI were excluded based on our inclusion and exclusion criteria. study investigated its relation to MAO-A VNTR genetic polymor - Sixty-nine participants who contacted the study authors to phisms (Clemens et al, 2015). Comprised of healthy individuals, form part of the healthy control group were also excluded based the study reported similarly low aggression levels in the MAOA-L on our inclusion and exclusion criteria. All subjects provided and MAOA-H groups. Using independent components analysis, informed, written consent, and the Research Ethics Board at the authors found regional distinctions of executive and sali- the Centre for Addiction and Mental Health, Toronto, Ontario, ence resting-state network nodes: low right middle frontal gyrus approved all study components. All subjects were clinically activity in MAOA-L carriers and high dorsal anterior cingulate assessed by a forensic psychiatrist (N.J.K.) using the Structured cortex activity among MAOA-H participants. Furthermore, alter - Clinical Interview for DSM-IV Axis II, Personality Disorders nate resting-state modalities have not yet been applied to dis- (SCID-II) (First et al, 1997) and SCID-I (First et al, 2002). Official tinguish MAO-A genotypes. Seed-based correlational analysis is documentation confirmed that all ASPD subjects had a criminal one such technique that correlates time series data from a pri- record and no healthy controls had a record of criminal offend- ori seed regions and whole-brain time courses. This data-driven, ing. A subset of 20 healthy (Kolla et al, 2017) and 18 ASPD partici- simple, and easily interpretable analysis is ideal for demarcating pants (Kolla et al, 2015) had previously participated in imaging functional connectivity (FC) (van den Heuvel and Hulshoff Pol, studies in our laboratory. Exclusion criteria included history of 2010). major depressive disorder, bipolar disorder, or a schizophrenia We previously reported that seed-based FC of ventral stri- spectrum illness. Current nonalcohol drug abuse or depend- atal (VS) seed regions in ASPD correlated with VS MAO-A ence additionally excluded participation. Use of psychotropic level using PET (Kolla et al, 2016). However, MAO-A VNTR medication was also exclusionary as was cigarette smoking. genotypes show no relationship with in vivo levels of brain Nonsmoking status was verified by breathalyzer testing for car - MAO-A, at least in healthy males (Fowler et al, 2007). Yet, the bon monoxide (MicroSmokerlyzer, Bedfont Scientific Ltd.) on fMRI-genetic study of healthy humans cited above suggests assessment and scanning days. All subjects’ urine toxicology that there may exist distinct profiles of functional brain activ- samples were uniformly negative for drugs of abuse on the day ity based on MAO-A genotype. These findings indicate that of scanning and all assessment days. Downloaded from https://academic.oup.com/ijnp/article-abstract/21/8/725/4994274 by Ed 'DeepDyve' Gillespie user on 07 August 2018 Kolla et al. | 727 mixed-effects general linear model to identify group effects. Seed Selection and Rationale For each ROI, we compared any difference between the four We selected three brain regions of interest (ROIs): superior VS groups using 2× 2 between-subjects ANOVA, which was based (VSs), inferior VS (VSi), and the dorsal striatum/caudate (Di on MAO-A genotype and diagnosis, covarying for IQ. The result- Martino et al, 2008). We previously selected these VS seeds, ant group-level analyses were thresholded at P < .001 (cluster- demonstrating that the striatal resting state connectivity was corrected using the false discovery rate [FDR], with a height related to brain MAO-A level (Kolla et al, 2016). Furthermore, threshold of P < .01). The resulting clusters were then displayed the neural circuitry of impulsive behaviors has been associ- on the MNI brain. To determine any significant statistical dif- ated with the VS (Basar et al, 2010), and VS circuitry is associ- ferences between groups, posthoc parameter estimates for the ated with emotional processing, reward pathways, and cognitive mean effect size for each resulting cluster were extracted, and a control (Haber, 2016). The dorsal caudate (DC) seed was created t test for each combination of groups was performed. The cutoff from the same striatal parcellation (Di Martino et al, 2008) and P value for each test was .0033 (.01/3 ROIs). was selected based on its role in the abnormal reward process- ing and impaired evaluation of contingency changes reported Genetics Analysis in antisocial individuals (Glenn and Yang, 2012). To correct for the comparison of 3 seed regions, we applied a Bonferroni cor - Standard PCR procedures that used primers as previously rection to all posthoc analyses on extracted cluster parameters. reported (Deckert et al, 1999) were employed to amplify the All ROIs were spheres centered on the coordinates outlined by MAO-A VNTR locus. Minor changes were implemented, includ- Di Martino and colleagues, with a radius of 4 mm and masked by ing the labeling of the forward primer with 5’ HEX modifier, the subject’s T1 gray matter segmentation. which permitted electrophoresis and visualization on a capil- lary sequencer. Briefly, 125 ng of total genomic DNA was added to the following components: 1x PcR Amplification Buffer, Image Acquisition 1.5 mM MgSO , and 1x PcR Enhancer Solution that accompa- 4 x Each participant underwent a T1-weighted anatomical scan nied the Invitrogen PcR Enhancer Kit, 0.2 mM of each dNTP, (TE = 3.0 milliseconds, TR = 6.7 milliseconds, flip angle = 8°, slice 0.0975 ug of each primer, and 0.5 U Taq polymerase. This com- thickness = 0.9 mm, 200 slices, FOV = 240 mm, matrix = 256 × 256, bination produced a total reaction volume of 20 μL. The cycling voxel size = 0.9 mm × 0.9 mm × 0.9 mm; 3.0-T GE Discovery MR750 conditions mirrored those as previously reported (Deckert et al, scanner, GE Medical Systems) for the ROI analysis. To obtain 1999), except for an additional denaturation step of 5 minures resting-state activity patterns, participants completed a 6-min- at 95°C. The ABI 3130 Genetic Analyzer system and GeneMapper ute fMRI scan (TE= 30 milliseconds, TR= 2000 milliseconds, flip software (ThermoFisher Scientific) electrophoresed and helped angle = 60°, slice thickness = 5.0 mm, 31 axial slices, FOV = 220 mm) visualize 1 µL of the amplified product. Subjects with 2, 3, or 5 performed in the resting state with their eyes closed. copies of the MAO-A VNTR were designated as MAOA-L carri- ers, while individuals with 3.5 or 4 copies were assigned the Data Preprocessing MAOA-H genotype. The first five volumes of each subject’s resting-state fMRI scan Clinical Measures were removed prior to data preprocessing to allow for signal equilibrium. Data preprocessing was performed using SPM12 Intelligence (http://www.fil.ion.ucl.ac.uk/spm/doc/) and the CONN FC tool- Participants were administered the Wechsler Test of Adult box (Whitfield-Gabrieli and Nieto-Castanon, 2012), implemented Reading (Wechsler, 1981) to provide an estimate of full-scale IQ. in Matlab v184.108.40.206613 (https://www.mathworks.com/products/ matlab/). Preprocessing steps included the following: slice-time Buss-Perry Aggression Questionnaire correction (interleaved), motion correction (e.g., realignment and The Buss-Perry Aggression Questionnaire (Buss and Perry, 1992) scrubbing), linear affine registration of the functional image to conceptualizes human aggression as a 4-factor model, including the anatomical T1 image, nonlinear registration of the functional physical aggression, verbal aggression, anger, and hostility. The and anatomical images to the MNI standard brain, and spatial 29-item Aggression Questionnaire has been validated in aggres- smoothing with a 6-mm full-width half-maximum. Anatomical sive populations (Gallagher and Ashford, 2016). T1 images were additionally segmented into gray matter, white matter, and CSF for the removal of physiological noise. Hare Psychopathy Checklist-Revised Physiological noise and noise from other sources were A trained forensic psychiatrist (N.J.K.) conducted interviews removed via linear regression. To remove physiological noise, with participants and obtained criminal records to score the aCompCor (Behzadi et al, 2007) was performed using segmented Hare Psychopathy Checklist-Revised (PCL-R) (Hare, 2003). The white matter and CSF images. The first 5 principal components PCL-R includes 20 items comprising 4 facets that measure inter - of each tissue segment were removed in addition to the 12 personal, affective, lifestyle instability, and antisocial behavior. motion parameters, their first derivative, and the linear motion Each PCL-R item is rated from 0 to 2 based on the presence or trend. Functional data were then bandpass filtered at 0.008 to absence of the trait (0 = no; 1 = possible; 2= yes) to generate a final 0.09 Hz. score between 0 and 40. Barratt Impulsiveness Scale-11 Resting-State fMRI Statistical Analysis The Barratt Impulsiveness Scale -11 (Patton et al, 1995) is a self- Whole-brain seed-to-voxel-based FC was performed for each report instrument that indexes motor impulsiveness, attentional ROI for each subject. Each ROI resulted in a bivariate correlation impulsiveness, and nonplanning impulsiveness subscales. The map for each subject; these maps were then Fisher-transformed Barratt Impulsiveness Scale-11 displays strong psychometric to normalized z-scores and were entered into a second-level, properties in offender populations (Patton et al, 1995). Downloaded from https://academic.oup.com/ijnp/article-abstract/21/8/725/4994274 by Ed 'DeepDyve' Gillespie user on 07 August 2018 728 | International Journal of Neuropsychopharmacology, 2018 Reactive-Proactive Aggression Questionnaire— for each variable except nonplanning impulsiveness, where no The Reactive-Proactive Aggression Questionnaire (Raine et al, difference between ASPD MAOA-H and healthy control MAOA-L 2006) is a self-report measure that assesses both verbal and groups was discerned (P = .13). The only variable that distin- physical forms of aggressive behavior. Eleven items index guished the 2 ASPD groups was proactive aggression: MAOA-L reactive forms of aggression, while the other 12 items meas- carriers with ASPD endorsed greater proactive aggression than ure proactive aggression. The Reactive-Proactive Aggression ASPD MAOA-H carriers (P = .043) and both healthy control groups Questionnaire has been used in adult ASPD populations (Kolla (healthy control MAOA-L: P < .001; healthy control MAOA-H: et al, 2013). P < .001). fMRI Results RESULTS Main Effect of Diagnosis Demographic and Clinical Variables The 2 × 2 between-subjects ANOVA revealed no significant differ- ence in the FC of any ROIs between the ASPD group and controls. ASPD subjects (n= 21) and controls (n= 19) were similar in age (ASPD = 36.2 ± 8.7 years; controls = 34.2 ± 7.7 years,t = 0.78, Main Effect of MAO-A Genotype P = .44) and proportion of individuals by MAO-A genotype The 2 × 2 between-subjects ANOVA revealed no significant differ- (L/H: ASPD = 11/ 10; controls = 9/10, χ = 0.1, P = .75). However, ence in the FC of any ROIs between the high- and low-activity the groups showed differences in IQ (ASPD= 106.0 ± 10.6; con- MAO-A genotypes. trols = 112.3 ± 8.2,t = -2.1, P = .043). As a result, IQ was covaried in the functional analyses. The two ASPD groups and two healthy groups were strati- Interaction Between Genotype and Diagnosis fied by genotype, and comparisons were performed using 1-way Dorsal Caudate ANOVA for variables relating to aggression, anger, impulsivity, The 2 × 2 ANOVA revealed a significant interaction effect of and psychopathic traits. Because the analyses produced 16 sep- MAO-A genotype and diagnosis in FC from the dorsal caudate arate ANOVAs, a Bonferroni correction was applied for mul- (Figure 1A). This interaction was found in one significant clus- tiple testing, which resulted in a significant threshold P value of ter: bilateral anterior cingulate cortex (ACC) and right frontal .0031 (0.05/16 tests). For each significant ANOVA, posthoc tests pole (312 voxels, T= 3.59, cluster P-FDR = .000077; Figure 1B). using Tukey’s HSD were then calculated to analyze differences Subsequent posthoc analyses indicated that the ASPD MAOA-H between the 4 groups (ASPD MAOA-L; ASPD MAOA-H; healthy group displayed greater mean FC to the frontal pole and ACC control MAOA-L; and healthy control MAOA-H). As depicted in relative to ASPD subjects with MAOA-L (Figure 1B; ASPD Table 1 and the tables included as supplementary results, the MAOA-H MPE = 0.26 ± 0.04 SE, ASPD MAOA-L MPE = 0.02 ± 0.03 ANOVAs for all variables were significant with the exception SE, t(19) = 26.00 P = .0001), and healthy control MAOA-H sub- of Barratt Attentional Impulsiveness. Posthoc tests revealed jects (Figure 1B; healthy control MAOA-H MPE = -0.03 ± 0.04 that both ASPD groups differed from the healthy participants SE, P = .00024). The healthy control MAOA-L group displayed greater mean FC to the frontal pole and ACC relative to the Table 1. Comparisons between the Four Groups on Clinical Variables healthy control MAOA-H group (Figure 1B; healthy control MAOA-L MPE = 0.17 ± 0.05 SE, P = .0037) and ASPD MAOA-L group ANOVA Posthoc (Figure 1B; P = .037). Given that our Bonferroni-corrected cluster- Measure F-Test P Value Tests* P threshold was .01/3 ROIs= .0033, the differences observed in the healthy control MAOA-L group do not survive multiple com- Buss Perry Aggression Scale parisons correction. Physical aggression 22.4 <.0001 Verbal aggression 16.1 <.0001 Anger 28.1 <.0001 VSi and VSs Hostility 8.8 <.0001 No clusters met the threshold of cluster P < .001 FDR-corrected Total 28.4 <.0001 with a height threshold of P < .01. Hare Psychopathy Checklist-Revised Interpersonal (facet 1) 21.0 <.0001 Exploratory Analyses Affective (facet 2) 41.3 <.0001 Impulsive (facet 3) 34.0 <.0001 Since proactive aggression was the only continuous variable Antisocial (facet 4) 48.4 <.0001 that differed between ASPD MAOA-L and MAOA-H groups, we Total PCL-R score 65.5 <.0001 modeled a 2-group (ASPD MAOA-L and ASPD MAOA-H) with Barratt Impulsiveness Scale-11 continuous covariate interaction with the FC of the three ROIs, Motor impulsiveness 10.8 <.0001 covarying for IQ. Statistical significance was defined according to Attentional impulsiveness 4.8 .007 a voxel-level, cluster-defined height threshold of P < .005, where Nonplanning 10.7 <.0001 clusters were retained that met an FDR-cluster level correction impulsiveness of P < .01/3 ROIs = .0033. While there were no significant clusters Reactive-Proactive Aggression Questionnaire associated with the dorsal caudate ROI before or after correcting Reactive aggression 20.9 <.0001 Proactive aggression 14.6 <.0001 1 > 2 (P = .043) for multiple comparisons, there were significant clusters related Total aggression 21.7 <.0001 to the VSi and VSs seeds. First, VSs FC to the right angular gyrus displayed a significant ASPD × proactive aggression interaction in ASPD subjects, even after correction for multiple compari- *Only those tests where differences emerged between (1) ASPD sons (396 voxels, cluster-P FDR = .00071; Figure 2Ai). Extracting MAOA-L and (2) ASPD MAOA-H groups or (3) healthy control MAOA-L the mean parameter estimate representing VSs-angular gyrus and (4) healthy control MAOA-H groups are specified. Downloaded from https://academic.oup.com/ijnp/article-abstract/21/8/725/4994274 by Ed 'DeepDyve' Gillespie user on 07 August 2018 Kolla et al. | 729 Figure 1. Dorsal striatal functional connectivity that showed a genotype × dia gnosis interaction. (A) Significant clusters of functional connectivity (FC) to the dorsal caudate (DC) that differed between groups. (B) Posthoc mean parameter estimates of DC FC to the anterior cingulate cortex (ACC) and frontal pole (FP). **P value < .0033, corrected. FC revealed a trend correlation between VSs-angular gyrus con- so that higher frontostriatal FC was associated with greater nectivity and proactive aggression in the ASPD MAOA-L group MAO-A density (Kolla et al, 2016). Frontostriatal connectivity (r = 0.62, P = .054) and no correlation in the ASPD MAOA-H group was also positively correlated with NEO-PI-R impulsivity in our (r = -0.056, P = .89; Figure 2Aii). Similarly, VSi FC to the left and previous study. Our current result replicates our previous find- right precuneus displayed a significant interaction in ASPD ing that increased medio-frontostriatal connectivity may reflect subjects; however, both clusters did not meet significance fol- differential MAO-A density. Further work is needed to confirm lowing multiple comparisons correction (right precuneus clus- its relationship to impulsivity and ASPD, especially as we were ter: 274 voxels, cluster-P FDR = .0043; left precuneus cluster = 257 unable to replicate an association between MAO-A genotype, voxels, cluster-P FDR = .0043) (Figure 2Bi). Mean parameter esti- frontostriatal connectivity, and impulsivity. As the extant lit- mates of VSi-precuneus connectivity showed a negative correl- erature is silent on how MAO-A polymorphisms may impact FC ation between FC and proactive aggression in ASPD MAOA-L underlying pathological behaviors, we must extrapolate from participants (left VSi-precuneus FC: r = -0.71, P = .022; right VSi- the results of healthy control MAO-A fMRI studies. These studies precuneus FC: r = -0.62, P = .056) and no association in the ASPD incorporate behavioral paradigms typically employed to study MAOA-H group (left VSi-precuneus: r = 0.30, P = .43; right VSi- high-aggression populations. For example, one task-based fMRI precuneus: r = 0.40, P = .29) (Figure 2Bii). study reported that MAOA-H carriers exhibited increased acti- vation of the dorsal ACC during response inhibition compared with their MAOA-L counterparts (Meyer-Lindenberg et al, 2006). Discussion OFC activity was similarly elevated among MAOA-H participants To our knowledge, this study is the first to examine the asso- vs MAOA-L carriers when individuals were exposed to emotion- ciation of MAO-A polymorphisms with resting-state FC in a ally arousing stimuli. Another research group reported a rela- sample with clinical level severity of symptoms. We chose to tive deactivation of the left middle frontal gyrus in MAOA-L investigate genotype-based brain activity in medication-free, subjects vs MAOA-H carriers upon hearing the word “no” (Alia- nonsmoking, and non-substance-using ASPD participants to Klein et al, 2007). Given these previous task-based findings and eliminate potential confounds. Furthermore, previous find- our own results, we suggest that increased caudate FC at rest ings correlated in vivo MAO-A levels and FC in this population to the frontal pole and ACC could relate to the neural basis of (Kolla et al, 2016). Inconsistent with our hypothesis, we did pathological behavior and aggression in ASPD offenders with not find any differences in frontostriatal connectivity between the MAOA-H genotype. ASPD subjects and healthy controls or between MAO-A geno- We also found an inverse relationship between MAO-A geno- types regardless of diagnosis. However, we did detect a dorsal type and frontostriatal connectivity in the healthy control groups caudate-frontostriatal interaction by genotype and diagnosis. relative to the antisocial groups. Only ASPD MAOA-H FC signifi- A subsequent exploratory analysis revealed that ventral striatal cantly differed between control MAOA-H and ASPD MAOA-L FC was associated with different linear relationships with pro- groups after correcting for multiple comparisons. We speculate active aggression in MAOA-H and MAOA-L ASPD groups. These that these differences displayed by the ASPD MAOA-H group findings expand upon a litany of prior genetic research linking may be genotype specific. In healthy humans, frontostriatal FC MAO-A VNTR genotypes to aggression (Kolla and Vinette, 2017) from dorsal prefrontal regions such as the ACC is associated with and helps establish that MAO-A polymorphisms are differen- response selection (Walton et al, 2007), decision-making (Walton tially associated with resting-state FC in ASPD. et al, 2007), and habit-learning (Packard and Knowlton, 2002), Our principal finding is that ASPD MAOA-H subjects exhibited while ventral frontostriatal connectivity, including the paracin- increased caudate FC to the right frontal pole and ACC relative gulate gyrus and frontal pole, is related to rewar prd- ocessing to ASPD MAOA-L carriers and MAOA-H healthy controls. Notably, (Knutson et al, 2001). These studies suggest that frontostriatal we recently reported that medio-frontostriatal FC was posi- connectivity differences between ASPD and healthy groups may tively correlated with MAO-A V , a measure of MAO-A density, reflect the combined effect of MAO-A genotype and pathological Downloaded from https://academic.oup.com/ijnp/article-abstract/21/8/725/4994274 by Ed 'DeepDyve' Gillespie user on 07 August 2018 730 | International Journal of Neuropsychopharmacology, 2018 Figure 2. Ventral striatum (VS) functional connectivity in antisocial personality disorder (ASPD) participants that showed a monoamine oxidase A (MAO-A) geno- type× proactive aggression score interaction. (Ai) Significant functional connectivity (FC) to the superior VS (VSs). (Aii) Scatter plot of VSs FC and proactive aggression in MAOA-L and MAOA-H ASPD groups. (Bi) FC to the inferior VS (VSi); note that this cluster did not survive after correcting for multiple comparisons. (Bii) Scatter plot of VSi-left precuneus FC and proactive aggression in MAOA-L and MAOA-H ASPD groups. Again, this relationship did not survive after correcting for multiple comparisons. mechanisms of ASPD on reward-based decision-making pro- MAO-A genotype and proactive aggression in offender popula- cesses. Interestingly, increased resting-state caudate FC has tions may, therefore, depend on manifestation of psychopathic been reported in externalizing disorders (Tomasi and Volkow, traits. In any event, future research with larger samples that 2012) and is consonant with our findings in ASPD MAOA-H sub- takes into account salient environmental influences is needed jects. Since enhanced corticostriatal connectivity is present in to parse the relationship between MAO-A genotypes and aggres- our ASPD MAOA-H subjects, we attribute the relative increase sion subtypes. Our exploratory analysis revealed that proactive of FC in the ASPD MAOA-H group vs healthy MAOA-H carriers to aggression in the ASPD MAOA-L group was positively associated the effect of ASPD diagnosis. with ventral striatal FC to the angular gyrus and negatively asso- ASPD MAOA-L carriers endorsed significantly higher levels ciated with FC to the precuneus. We are unaware of any other of proactive aggression relative to our other groups, and the lin- research examining the association of resting-state FC with ear relationship of proactive aggression to ventral striatal FC dif-proactive aggression. Both the angular gyrus and precuneus are fered by MAO-A genotype in the ASPD groups. Before correction, nodes of the default mode network (Vaidya and Gordon, 2013), ventral striatal FC to the angular gyrus and precuneus displayed and it is worthwhile noting the inverse relationship between near significant correlations with proactive aggression only in ventral striatal connectivity to these regions and proactive the ASPD MAOA-L carriers and not in ASPD MAOA-H carriers; aggression scores in the MAOA-L ASPD group. Previous studies only VSs-angular gyrus FC differed significantly postcorrection. have shown that poorer inhibitory control in healthy controls Proactive aggression refers to the deliberate, purposeful behav- (Davis et al, 2013), borderline personality disorder (Wolf et al, ior that is enacted to achieve a desired goal, whereas reactive 2011), and incarcerated juvenile offenders (Shannon et al, 2011) aggression encapsulates angry or impulsive actions that occur is associated with altered between and within network default following provocative stimuli (Crick and Dodge, 1996). Some mode connectivity. More specifically, the presence of external- studies (Caspi et al, 2002), but not all (Kolla et al, 2014), report izing symptoms like aggression in childhood attention deficit- a connection between the MAOA-L allele and higher proactive hyperactivity disorder is also associated with altered default aggression. In the latter study, violent offenders had substan- mode network and subcortical resting-state FC (Cao et al, 2009; tially lower PCL-R scores, whereas in the current investiga- Chabernaud et al, 2012). Angular gyrus volume has also been tion, PCL-R scores were much higher. The relationship between associated with externalizing behaviors in children, such that Downloaded from https://academic.oup.com/ijnp/article-abstract/21/8/725/4994274 by Ed 'DeepDyve' Gillespie user on 07 August 2018 Kolla et al. | 731 greater externalizing behavior was associated with smaller also note that a seminal paper reported using 8-minute resting- cortical volumes (Caldwell et al, 2015). More generally, angular state scans with a slice thickness of 4 mm (Greicius et al, 2009). gyrus function has been implicated in moral cognition and deci- Future studies should endeavor to optimize scanning param- sion-making (Miczek et al, 2007). Given the strong genetic liabil- eters to conform to current gold standards. ity underlying pathological use of proactive aggression (Tuvblad In summary, we identified differences in corticostriatal et al, 2009), a multitude of genes, perhaps including MAO-A, resting-state FC in ASPD participants by MAO-A VNTR polymor - likely contributes to regulation of functional neural networks phism. We found that DC connectivity to the frontal pole and that ultimately control expression of this multifaceted and dys- ACC was significantly greater in ASPD MAOA-H subjects com- functional behavior. pared with ASPD participants carrying the MAOA-L polymor - Several limitations of the present investigation must be phism and healthy groups. We additionally discovered that the acknowledged. First, the sample size was relatively small for ASPD MAOA-L group displayed higher levels of proactive aggres- typical imaging-genetic studies. Still, our sample size is com- sion relative to ASPD MAOA-H participants and healthy controls. parable with the only other investigation (Clemens et al, 2015) This increase showed a robust correlation with corticostriatal to have examined connections between MAO-A VNTR polymor - connectivity between the precuneus and angular gyrus; such phisms and resting-state FC. In the aforementioned study, the nodes of the default mode network have been implicated in sample was composed exclusively of healthy subjects, whereas the genesis of externalizing behavior like aggression and moral the present study examined healthy controls in addition to judgment. Subtyping externalizing disorders using biological ASPD. Given the smaller sample size, we do, however, empha- measures, including genetic and neuroimaging markers, holds size the importance of interpreting these results with caution. promise for improving our understanding of illness nosology A second limitation is that we restricted our analysis to 3-seed and endophenotypes. Research indicating that somatic treat- regions in the dorsal and ventral striatum. These regions were ments may depend on MAO-A genotype (Domschke et al, 2008) selected, because they had been implicated in previous neu- speaks to the translational potential of the present work, espe- roimaging studies of antisocial populations (Glenn and Yang, cially as emerging neuromodulation techniques have been 2012). Furthermore, prior work had also demonstrated func- shown to alter corticostriatal FC (Dunlop et al, 2016). As we con- tional links between the VS and in vivo markers of MAO-A in tinue to learn more about the neural underpinnings of ASPD, a ASPD (Kolla et al, 2016). It would be advantageous for future better understanding of how these biological systems interact to studies to consider examining whether other regional FC, such instigate violence and aggression will become critical for devel- as the amygdala (Hyde et al, 2014) and ventromedial prefrontal oping novel treatments. cortex (Narayan et al, 2007), also show a relation to MAO-A genetic variants; evidence suggests that these structures may Supplementary Material also be under MAO-A genetic control (Buckholtz and Meyer- Lindenberg, 2008; Cerasa et al, 2011). A third limitation is that Supplementary data are available at International Journal of we only sampled males. One rationale is that ASPD is approxi- Neuropsychopharmacology online. mately five to seven times more common in males than females (Hamdi and Iacono, 2014). However, one can include females in Acknowledgments a study and genotype for MAO-A alleles. It is just not as straight- forward as it is for males, because females can be homozy- This work was supported by the Canadian Institutes of Health gous or heterozygous for the MAO-A VNTR locus, and there is Research and the American Psychiatric Association. debate as to whether X-inactivation occurs at this site (Carrel and Willard, 2005). A fourth limitation is that our carbon mon- Statement of Interest oxide breathalyzer was only sensitive to detecting carbon mon- oxide (e.g., smoking) in the past 24 hours. Although unlikely, it is Dr Downar received a travel stipend from Lundbeck and from possible that some smokers were able to refrain from smoking ANT Neuro and in-kind equipment support for an investi- for 24 hours prior to testing and thus were incorrectly classi- gator-initiated study from Tonika/Magventure. Dr Meyer has fied as nonsmokers. Fifth, use of alcohol was determined solely received operating grant funds for other studies from Eli-Lilly, by self-report. We asked subjects to refrain from drinking the GlaxoSmithKline, Bristol Myers Squibb, Lundbeck, Janssen, and day before and the day of scanning. When asked, all confirmed SK Life Sciences in the past 5 years. Dr Meyer has consulted for that they had not consumed alcohol. However, we did not have several of these companies as well as Takeda, Sepracor, Trius, a biological assay to test for alcohol consumption, and it is pos- Mylan, and Teva. These organizations had no further role in the sible that some participants misrepresented themselves. Sixth, study design; in the collection, analysis, and interpretation of we cannot declare with certainty that participants did not fall data; in the writing of the report; and in the decision to submit asleep during the scans. Our resting-state instructions asked the paper for publication. All other authors report no financial participants to refrain from sleeping during the scan. 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International Journal of Neuropsychopharmacology – Oxford University Press
Published: Aug 1, 2018
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