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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- 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.
- 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.
- Lateral hypothalamic activity indicates hunger and satiety states in humans(2017) TALAKOUB, Omid; PAIVA, Raquel R.; MILOSEVIC, Matija; HOEXTER, Marcelo Q.; FRANCO, Ruth; ALHO, Eduardo; NAVARRO, Jessie; PEREIRA JR., Jose F.; POPOVIC, Milos R.; SAVAGE, Cary; LOPES, Antonio C.; ALVARENGA, Pedro; DAMIANI, Durval; TEIXEIRA, Manoel J.; MIGUEL, Euripides C.; FONOFF, Erich T.; BATISTUZZO, Marcelo C.; HAMANI, ClementLateral hypothalamic area (LHA) local field potentials (LFPs) were recorded in a Prader-Willi patient undergoing deep brain stimulation (DBS) for obesity. During hunger, exposure to food-related cues induced an increase in beta/low-gamma activity. In contrast, recordings during satiety were marked by prominent alpha rhythms. Based on these findings, we have delivered alpha-frequency DBS prior to and during food intake. Despite reporting an early sensation of fullness, the patient continued to crave food. This suggests that the pattern of activity in LHA may indicate hunger/satiety states in humans but attest to the complexity of conducting neuromodulation studies in obesity.
- Toward identifying reproducible brain signatures of obsessive-compulsive profiles: rationale and methods for a new global initiative(2020) SIMPSON, Helen Blair; HEUVEL, Odile A. van den; MIGUEL, Euripedes C.; REDDY, Y. C. Janardhan; STEIN, Dan J.; LEWIS-FERNANDEZ, Roberto; SHAVITT, Roseli Gedanke; LOCHNER, Christine; POUWELS, Petra J. W.; NARAYANAWAMY, Janardhanan C.; VENKATASUBRAMANIAN, Ganesan; HEZEL, Dianne M.; VRIEND, Chris; BATISTUZZO, Marcelo C.; HOEXTER, Marcelo Q.; JOODE, Niels T. de; COSTA, Daniel Lucas; MATHIS, Maria Alice de; SHESHACHALA, Karthik; NARAYAN, Madhuri; BALKOM, Anton J. L. M. van; BATELAAN, Neeltje M.; VENKATARAM, Shivakumar; CHERIAN, Anish; MARINCOWITZ, Clara; PANNEKOEK, Nienke; STOVEZKY, Yael R.; MARE, Karen; LIU, Feng; OTADUY, Maria Concepcion Garcia; PASTORELLO, Bruno; RAO, Rashmi; KATECHIS, Martha; METER, Page Van; WALL, MelanieBackground Obsessive-compulsive disorder (OCD) has a lifetime prevalence of 2-3% and is a leading cause of global disability. Brain circuit abnormalities in individuals with OCD have been identified, but important knowledge gaps remain. The goal of the new global initiative described in this paper is to identify robust and reproducible brain signatures of measurable behaviors and clinical symptoms that are common in individuals with OCD. A global approach was chosen to accelerate discovery, to increase rigor and transparency, and to ensure generalizability of results. Methods We will study 250 medication-free adults with OCD, 100 unaffected adult siblings of individuals with OCD, and 250 healthy control subjects at five expert research sites across five countries (Brazil, India, Netherlands, South Africa, and the U.S.). All participants will receive clinical evaluation, neurocognitive assessment, and magnetic resonance imaging (MRI). The imaging will examine multiple brain circuits hypothesized to underlie OCD behaviors, focusing on morphometry (T1-weighted MRI), structural connectivity (Diffusion Tensor Imaging), and functional connectivity (resting-state fMRI). In addition to analyzing each imaging modality separately, we will also use multi-modal fusion with machine learning statistical methods in an attempt to derive imaging signatures that distinguish individuals with OCD from unaffected siblings and healthy controls (Aim #1). Then we will examine how these imaging signatures link to behavioral performance on neurocognitive tasks that probe these same circuits as well as to clinical profiles (Aim #2). Finally, we will explore how specific environmental features (childhood trauma, socioeconomic status, and religiosity) moderate these brain-behavior associations. Discussion Using harmonized methods for data collection and analysis, we will conduct the largest neurocognitive and multimodal-imaging study in medication-free subjects with OCD to date. By recruiting a large, ethno-culturally diverse sample, we will test whether there are robust biosignatures of core OCD features that transcend countries and cultures. If so, future studies can use these brain signatures to reveal trans-diagnostic disease dimensions, chart when these signatures arise during development, and identify treatments that target these circuit abnormalities directly. The long-term goal of this research is to change not only how we conceptualize OCD but also how we diagnose and treat it.
- 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
- Differential prefrontal gray matter correlates of treatment response to fluoxetine or cognitive-behavioral therapy in obsessive-compulsive disorder(2013) HOEXTER, Marcelo Q.; DOUGHERTY, Darin D.; SHAVITT, Roseli G.; D'ALCANTE, Carina C.; DURAN, Fabio L. S.; LOPES, Antonio C.; DINIZ, Juliana B.; BATISTUZZO, Marcelo C.; EVANS, Karleyton C.; BRESSAN, Rodrigo A.; BUSATTO, Geraldo F.; MIGUEL, Euripedes C.Nearly one-third of patients with obsessive-compulsive disorder (OCD) fail to respond to adequate therapeutic approaches such as serotonin reuptake inhibitors and/or cognitive-behavioral therapy (CBT). This study investigated structural magnetic resonance imaging (MRI) correlates as potential pre-treatment brain markers to predict treatment response in treatment-naive OCD patients randomized between trials of fluoxetine or CBI Treatment-naive OCD patients underwent structural MRI scans before randomization to a 12-week clinical trial of either fluoxetine or group-based CBT. Voxel-based morphometry was used to identify correlations between pretreatment regional gray matter volume and changes in symptom severity on the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS). Brain regional correlations of treatment response differed between treatment groups. Notably, symptom improvement in the fluoxetine treatment group (n=14) was significantly correlated with smaller pretreatment gray matter volume within the right middle lateral orbitofrontal cortex (OFC), whereas symptom improvement in the CBT treatment group (n=15) was significantly correlated with larger pretreatment gray matter volume within the right medial prefrontal cortex (mPFC). No significant a priori regional correlations of treatment response were identified as common between the two treatment groups when considering the entire sample (n=29). These findings suggest that pretreatment gray matter volumes of distinct brain regions within the lateral OFC and mPFC were differentially correlated to treatment response to fluoxetine versus CBT in OCD patients. This study further implicates the mPFC in the fear/anxiety extinction process and stresses the importance of lateral portions of the OFC in mediating fluoxetine's effectiveness in OCD. Clinical registration information: http://clinicaltrials.gov-NCT00680602.
- Cross-National Harmonization of Neurocognitive Assessment Across Five Sites in a Global Study(2023) BATISTUZZO, Marcelo C.; SHESHACHALA, Karthik; ALSCHULER, Daniel M.; HEZEL, Dianne M.; LEWIS-FERNANDEZ, Roberto; JOODE, Niels T. de; VRIEND, Chris; LEMPERT, Karolina M.; NARAYAN, Madhuri; MARINCOWITZ, Clara; LOCHNER, Christine; STEIN, Dan J.; NARAYANASWAMY, Janardhanan C.; HEUVEL, Odile A. van den; SIMPSON, Helen Blair; WALL, MelanieObjective: Cross-national work on neurocognitive testing has been characterized by inconsistent findings, suggesting the need for improved harmonization. Here, we describe a prospective harmonization approach in an ongoing global collaborative study. Method: Visuospatial N-Back, Tower of London (ToL), Stop Signal task (SST), Risk Aversion (RA), and Intertemporal Choice (ITC) tasks were administered to 221 individuals from Brazil, India, the Netherlands, South Africa, and the USA. Prospective harmonization methods were employed to ensure procedural similarity of task implementation and processing of derived task measures across sites. Generalized linear models tested for between-site differences controlling for sex, age, education, and socioeconomic status (SES). Associations with these covariates were also examined and tested for differences by site with site-by-covariate interactions. Results: The Netherlands site performed more accurately on N-Back and ToL than the other sites, except for the USA site on the N-Back. The Netherlands and the USA sites performed faster than the other three sites during the go events in the SST. Finally, the Netherlands site also exhibited a higher tolerance for delay discounting than other sites on the ITC, and the India site showed more risk aversion than other sites on the RA task. However, effect size differences across sites on the five tasks were generally small (i.e., partial eta-squared < 0.05) after dropping the Netherlands (on ToL, N-Back, ITC, and SST tasks) and India (on the RA task). Across tasks, regardless of site, the N-Back (sex, age, education, and SES), ToL (sex, age, and SES), SST (age), and ITC (SES) showed associations with covariates. Conclusions: Four out of the five sites showed only small between-site differences for each task. Nevertheless, despite our extensive prospective harmonization steps, task score performance deviated from the other sites in the Netherlands site (on four tasks) and the India site (on one task). Because the procedural methods were standardized across sites, and our analyses were adjusted for covariates, the differences found in cognitive performance may indicate selection sampling bias due to unmeasured confounders. Future studies should follow similar cross-site prospective harmonization procedures when assessing neurocognition and consider measuring other possible confounding variables for additional statistical control.
- Disentangling the Role of Amygdala Activation in Obsessive-Compulsive Disorder(2018) HOEXTER, Marcelo Q.; BATISTUZZO, Marcelo C.