MARCELO CAMARGO BATISTUZZO
Projetos de Pesquisa
Unidades Organizacionais
Instituto de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina
LIM/23 - Laboratório de Psicopatologia e Terapêutica Psiquiátrica, Hospital das Clínicas, Faculdade de Medicina
LIM/23 - Laboratório de Psicopatologia e Terapêutica Psiquiátrica, Hospital das Clínicas, Faculdade de Medicina
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conferenceObject Attentional Bias to Symmetry and Cleaning Features in Obsessive-Compulsive Disorder: A Pilot Study(2015) MATHIS, Maria Alice De; SALUM, Giovanni; MORAES, Ivanil; BATISTUZZO, Marcelo; MARCO, Marina De; TOLEDO, Maria Cecilia; REQUENA, Guaraci; ABEND, Rany; BAR-HAIM, Yair; MIGUEL, Euripedes; SHAVITT, Roseli- Toward a neurocircuit-based taxonomy to guide treatment of obsessive-compulsive disorder(2021) SHEPHARD, Elizabeth; STERN, Emily R.; HEUVEL, Odile A. van den; COSTA, Daniel L. C.; BATISTUZZO, Marcelo C.; GODOY, Priscilla B. G.; LOPES, Antonio C.; BRUNONI, Andre R.; HOEXTER, Marcelo Q.; SHAVITT, Roseli G.; REDDY, Y. C. Janardhan; LOCHNER, Christine; STEIN, Dan J.; SIMPSON, H. Blair; MIGUEL, Euripedes C.An important challenge in mental health research is to translate findings from cognitive neuroscience and neuroimaging research into effective treatments that target the neurobiological alterations involved in psychiatric symptoms. To address this challenge, in this review we propose a heuristic neurocircuit-based taxonomy to guide the treatment of obsessive-compulsive disorder (OCD). We do this by integrating information from several sources. First, we provide case vignettes in which patients with OCD describe their symptoms and discuss different clinical profiles in the phenotypic expression of the condition. Second, we link variations in these clinical profiles to underlying neurocircuit dysfunctions, drawing on findings from neuropsychological and neuroimaging studies in OCD. Third, we consider behavioral, pharmacological, and neuromodulatory treatments that could target those specific neurocircuit dysfunctions. Finally, we suggest methods of testing this neurocircuit-based taxonomy as well as important limitations to this approach that should be considered in future research.
conferenceObject Associations Between Medial Prefrontal Cerebral Metabolic Features and Clinical Characteristics in Obsessive-compulsive Disorder(2016) BATISTUZZO, Marcelo C.; HOEXTER, Marcelo; COSTA, Fabiana; SHAVITT, Roseli; LOPES, Antonio C.; CAPPI, Carolina; VATTIMO, Edoardo; MATHIS, Alice de; DINIZ, Juliana B.; HENNING, Anke; PASTORELLO, Bruno; MIGUEL, Euripedes C.; OTADUY, Maria C.- Using supervised machine learning on neuropsychological data to distinguish OCD patients with and without sensory phenomena from healthy controls(2021) STAMATIS, Caitlin A.; BATISTUZZO, Marcelo C.; TANAMATIS, Tais; MIGUEL, Euripedes C.; HOEXTER, Marcelo Q.; TIMPANO, Kiara R.Objectives While theoretical models link obsessive-compulsive disorder (OCD) with executive function deficits, empirical findings from the neuropsychological literature remain mixed. These inconsistencies are likely exacerbated by the challenge of high-dimensional data (i.e., many variables per subject), which is common across neuropsychological paradigms and necessitates analytical advances. More unique to OCD is the heterogeneity of symptom presentations, each of which may relate to distinct neuropsychological features. While researchers have traditionally attempted to account for this heterogeneity using a symptom-based approach, an alternative involves focusing on underlying symptom motivations. Although the most studied symptom motivation involves fear of harmful events, 60-70% of patients also experience sensory phenomena, consisting of uncomfortable sensations or perceptions that drive compulsions. Sensory phenomena have received limited attention in the neuropsychological literature, despite evidence that symptoms motivated by these experiences may relate to distinct cognitive processes. Methods Here, we used a supervised machine learning approach to characterize neuropsychological processes in OCD, accounting for sensory phenomena. Results Compared to logistic regression and other algorithms, random forest best differentiated healthy controls (n = 59; balanced accuracy = .70), patients with sensory phenomena (n = 29; balanced accuracy = .59), and patients without sensory phenomena (n = 46; balanced accuracy = .62). Decision-making best distinguished between groups based on sensory phenomena, and among the patient subsample, those without sensory phenomena uniquely displayed greater risk sensitivity compared to healthy controls (d = .07, p = .008). Conclusions Results suggest that different cognitive profiles may characterize patients motivated by distinct drives. The superior performance and generalizability of the newer algorithms highlights the utility of considering multiple analytic approaches when faced with complex data. Practitioner points Practitioners should be aware that sensory phenomena are common experiences among patients with OCD. OCD patients with sensory phenomena may be distinguished from those without based on neuropsychological processes.
bookPart Transtornos obsessivo-compulsivo na infância e adolescência(2021) FATORI, Daniel; BATISTUZZO, Marcelo Camargo; MORIKAWA, Márcia; SAWADA, Julio Renó; ASBAHR, Fernando Ramos- Intelligence quotient (IQ) in pediatric patients with obsessive-compulsive disorder(2020) BATISTUZZO, Marcelo Camargo; SOUZA, Marina de Marco e; BERNARDES, Elisa Teixeira; REQUENA, Guaraci; MIGUEL, Euripedes Constantino; SHAVITT, Roseli GedankeObjective: The aim of the present study was to examine the intellectual quotient (IQ) in a large sample of youth with obsessive-compulsive disorder (OCD) and to compare them with typically developing individuals (TDI), adding to the scarce literature focusing on the intelligence evaluation of this population. Method: The IQ of 82 children and adolescents with OCD and 82 TDI, matched by age, sex, handedness and education, was assessed by the Wechsler Abbreviated Scale of Intelligence (WASI, Brazilian-version). Statistics were performed with independent t-test, correlations and ANCOVA (controlling for motor and processing speed and comorbidities), corrected using the Benjamini-Hochberg multiple comparisons correction. Results: No between-group differences were found on the full-scale IQ (FSIQ, p-value = 0.545) or verbal IQ (VIQ; p-value = 0.423). In contrast, a significant difference was found in the performance IQ (PIQ; p-value = 0.045, Cohen's d = 0.379) and IQ discrepancy, i.e. the difference between VIQ and PIQ (p-value = 0.012, Cohen's d = 0.494). Analyses of the PIQ subtest scores revealed impaired performance in the Block Design test among OCD patients (p-value = 0.012, Cohen's d = 0.273), that remained after correcting for motor and processing speed and comorbidity status. Conclusion: In our sample of pediatric patients with OCD, the FSIQ, VIQ and PIQ were within the average range (90-110), and we did not find between-group differences in the FSIQ or VIQ, indicating that youth with OCD do not present major deficits in intellectual efficiency. Nevertheless, replicating an extensive adult literature, we found lower PIQ scores in youth patients, that were not better explained by motor and processing speed or comorbidity status.
- Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium(2020) YUN, Je-Yeon; BOEDHOE, Premika S. W.; VRIEND, Chris; JAHANSHAD, Neda; ABE, Yoshinari; AMEIS, Stephanie H.; ANTICEVIC, Alan; ARNOLD, Paul D.; BATISTUZZO, Marcelo C.; BENEDETTI, Francesco; BEUCKE, Jan C.; BOLLETTINI, Irene; BOSE, Anushree; BREM, Silvia; CALVO, Anna; CHENG, Yuqi; CHO, Kang Ik K.; CIULLO, Valentina; DALLASPEZIA, Sara; DENYS, Damiaan; FEUSNER, Jamie D.; FOUCHE, Jean-Paul; GIMENEZ, Monica; GRUNER, Patricia; HIBAR, Derrek P.; HOEXTER, Marcelo Q.; HU, Hao; HUYSER, Chaim; IKARI, Keisuke; KATHMANN, Norbert; KAUFMANN, Christian; KOCH, Kathrin; LAZARO, Luisa; LOCHNER, Christine; MARQUES, Paulo; MARSH, Rachel; MARTINEZ-ZALACAIN, Ignacio; MATAIX-COLS, David; MENCHON, Jose M.; MINUZZI, Luciano; MORGADO, Pedro; MOREIRA, Pedro; NAKAMAE, Takashi; NAKAO, Tomohiro; NARAYANASWAMY, Janardhanan C.; NURMI, Erika L.; O'NEILL, Joseph; PIACENTINI, John; PIRAS, Fabrizio; PIRAS, Federica; REDDY, Y. C. Janardhan; SATO, Joao R.; SIMPSON, H. Blair; SORENI, Noam; SORIANO-MAS, Carles; SPALLETTA, Gianfranco; STEVENS, Michael C.; SZESZKO, Philip R.; TOLIN, David F.; VENKATASUBRAMANIAN, Ganesan; WALITZA, Susanne; WANG, Zhen; WINGEN, Guido A. van; XU, Jian; XU, Xiufeng; ZHAO, Qing; THOMPSON, Paul M.; STEIN, Dan J.; HEUVEL, Odile A. van den; KWON, Jun SooBrain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect commontrajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsivedisorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scansacquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCDWorking Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to thesimilarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Globalnetworks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency),and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networkswas undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measureswere integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the networkdensity range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering(P<0.0001), lower modularity (P<0.0001), and lower small-worldness (P = 0.017). Detection of community membershipemphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed)centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicativeof altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated withOCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of thisstudy, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariancenetworks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometryin OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularlyin cingulate and orbitofrontal regions.
conferenceObject Treatment Response Prediction in Pediatric Patients With OCD Using Structural Neuroimaging Correlates: Simple Linear Regression Versus Support Vector Regression(2017) VATTIMO, Edoardo; BARROS, Vivian; BATISTUZZO, Marcelo; REQUENA, Guaraci; SATO, Joao; FATORI, Daniel; SHAVITT, Roseli; MIGUEL, Euripedes; HOEXTER, MarceloconferenceObject Early Life Adverse Experiences and Obsessive-Compulsive Disorder: A Study With Patients, Siblings and Controls(2018) COSTA, Fabiana; CAPPI, Carolina; BATISTUZZO, Marcelo; SHAVITT, Roseli; REQUENA, Guaraci; MIGUEL, Euripedes; HOEXTER, Marcelo- Distinct Subcortical Volume Alterations in Pediatric and Adult OCD: A Worldwide Meta-and Mega-Analysis (vol , pg , 2016)(2017) ABE, Yoshinari; ALONSO, Pino; AMEIS, Stephanie H.; ARNOLD, Paul D.; BARGALLO, Nuria; BATISTUZZO, Marcelo C.; BENEDETTI, Francesco; BEUCKE, Jan C.; BOEDHOE, Premika S. W.; BOLLETTINI, Irene; BOSE, Anushree; BREM, Silvia; BUSATTO, Geraldo F.; CALVO, Anna; CALVO, Rosa; CATH, Danielle C.; CHENG, Yuqi; CHO, Kang Ik K.; DALLASPEZIA, Sara; VRIES, Froukje E. de; WIT, Stella J. de; DENYS, Damiaan; FANG, Yu; FITZGERALD, Kate D.; FONTAINE, Martine; FOUCHE, Jean-Paul; GIMENEZ, Monica; GRUNER, Patricia; HANNA, Gregory L.; HIBAR, Derrek P.; HOEXTER, Marcelo Q.; HU, Hao; HUYSER, Chaim; IKARI, Keisuke; JAHANSHAD, Neda; KATHMANN, Norbert; KAUFMANN, Christian; KHADKA, Sabin; KOCH, Kathrin; KWON, Jun Soo; LAZARO, Luisa; LIU, Yanni; LOCHNER, Christine; MARSH, Rachel; MARTINEZ-ZALACAIN, Ignacio; MATAIX-COLS, David; MENCHON, Jose M.; MIGUEL, Euripedes C.; MINUZZI, Luciano; MORER, Astrid; NAKAMAE, Takashi; NAKAO, Tomohiro; NARAYANASWAMY, Janardhanan C.; PIRAS, Fabrizio; PIRAS, Federica; PITTENGER, Christopher; REDDY, Y. C. Janardhan; SATO, Joao R.; SIMPSON, H. Blair; SCHMAAL, Lianne; SORENI, Noam; SORIANO-MAS, Carles; SPALLETTA, Gianfranco; STEIN, Dan J.; STEVENS, Michael C.; SZESZKO, Philip R.; THOMPSON, Paul M.; TOLIN, David F.; VELTMAN, Dick J.; VENKATASUBRAMANIAN, Ganesan; HEUVEL, Odile A. van den; WERF, Ysbrand D. van der; WINGEN, Guido A. van; WALITZA, Susanne; WANG, Zhen; XU, Jian; XU, Xiufeng; YUN, Je-Yeon; ZHAO, Qing