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Quantitative Susceptibility Mapping MRI in Deep-Brain Nuclei in First-Episode Psychosis
(2023)
Marisleydis García Saborit
;
Alejandro Jara
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Néstor Muñoz
;
Carlos Milovic
;
Angeles Tepper
<jats:title>Abstract</jats:title> <jats:sec> <jats:title>Background</jats:title> <jats:p>Psychosis is related to neurochemical changes in deep-brain nuclei, particularly suggesting dopamine dysfunctions. We used an magnetic resonance imaging-based technique called quantitative susceptibility mapping (QSM) to study these regions in psychosis. QSM quantifies magnetic susceptibility in the brain, which is associated with iron concentrations. Since iron is a cofactor in dopamine pathways and co-localizes with inhibitory neurons, differences in QSM could reflect changes in these processes.</jats:p> </jats:sec> <jats:sec> <jats:title>Methods</jats:title> <jats:p>We scanned 83 patients with first-episode psychosis and 64 healthy subjects. We reassessed 22 patients and 21 control subjects after 3 months. Mean susceptibility was measured in 6 deep-brain nuclei. Using linear mixed models, we analyzed the effect of case-control differences, region, age, gender, volume, framewise displacement (FD), treatment duration, dose, laterality, session, and psychotic symptoms on QSM.</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>Patients showed a significant susceptibility reduction in the putamen and globus pallidus externa (GPe). Patients also showed a significant R2* reduction in GPe. Age, gender, FD, session, group, and region are significant predictor variables for QSM. Dose, treatment duration, and volume were not predictor variables of QSM.</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusions</jats:title> <jats:p>Reduction in QSM and R2* suggests a decreased iron concentration in the GPe of patients. Susceptibility reduction in putamen cannot be associated with iron changes. Since changes observed in putamen and GPe were not associated with symptoms, dose, and treatment duration, we hypothesize that susceptibility may be a trait marker rather than a state marker, but this must be verified with long-term studies.</jats:p> </jats:sec>
Scopus© Citations 1 1
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Abnormal nodal and global network organization in resting state functional MRI from subjects with the 22q11 deletion syndrome
(2021)
Teuntje A. D. Pelgrim
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Matthijs G. Bossong
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Analía Cuiza
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Luz María Alliende
;
Carlos Mena
<jats:title>Abstract</jats:title><jats:p>The 22q11 deletion syndrome is a genetic disorder associated with a high risk of developing psychosis, and is therefore considered a neurodevelopmental model for studying the pathogenesis of schizophrenia. Studies have shown that localized abnormal functional brain connectivity is present in 22q11 deletion syndrome like in schizophrenia. However, it is less clear whether these abnormal cortical interactions lead to global or regional network disorganization as seen in schizophrenia. We analyzed from a graph-theory perspective fMRI data from 40 22q11 deletion syndrome patients and 67 healthy controls, and reconstructed functional networks from 105 brain regions. Between-group differences were examined by evaluating edge-wise strength and graph theoretical metrics of local (weighted degree, nodal efficiency, nodal local efficiency) and global topological properties (modularity, local and global efficiency). Connectivity strength was globally reduced in patients, driven by a large network comprising 147 reduced connections. The 22q11 deletion syndrome network presented with abnormal local topological properties, with decreased local efficiency and reductions in weighted degree particularly in hub nodes. We found evidence for abnormal integration but intact segregation of the 22q11 deletion syndrome network. Results suggest that 22q11 deletion syndrome patients present with similar aberrant local network organization as seen in schizophrenia, and this network configuration might represent a vulnerability factor to psychosis.</jats:p>
Scopus© Citations 2 1
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Dysconnectivity in Schizophrenia Revisited: Abnormal Temporal Organization of Dynamic Functional Connectivity in Patients With a First Episode of Psychosis
(2022)
Juan P Ramirez-Mahaluf
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Ángeles Tepper
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Luz Maria Alliende
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Carlos Mena
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Carmen Paz Castañeda
<jats:title>Abstract</jats:title> <jats:sec> <jats:title>Background and Hypothesis</jats:title> <jats:p>Abnormal functional connectivity between brain regions is a consistent finding in schizophrenia, including functional magnetic resonance imaging (fMRI) studies. Recent studies have highlighted that connectivity changes in time in healthy subjects. We here examined the temporal changes in functional connectivity in patients with a first episode of psychosis (FEP). Specifically, we analyzed the temporal order in which whole-brain organization states were visited.</jats:p> </jats:sec> <jats:sec> <jats:title>Study Design</jats:title> <jats:p>Two case-control studies, including in each sample a subgroup scanned a second time after treatment. Chilean sample included 79 patients with a FEP and 83 healthy controls. Mexican sample included 21 antipsychotic-naïve FEP patients and 15 healthy controls. Characteristics of the temporal trajectories between whole-brain functional connectivity meta-states were examined via resting-state functional MRI using elements of network science. We compared the cohorts of cases and controls and explored their differences as well as potential associations with symptoms, cognition, and antipsychotic medication doses.</jats:p> </jats:sec> <jats:sec> <jats:title>Study Results</jats:title> <jats:p>We found that the temporal sequence in which patients’ brain dynamics visited the different states was more redundant and segregated. Patients were less flexible than controls in changing their network in time from different configurations, and explored the whole landscape of possible states in a less efficient way. These changes were related to the dose of antipsychotics the patients were receiving. We replicated the relationship with antipsychotic medication in the antipsychotic-naïve FEP sample scanned before and after treatment.</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusions</jats:title> <jats:p>We conclude that psychosis is related to a temporal disorganization of the brain’s dynamic functional connectivity, and this is associated with antipsychotic medication use.</jats:p> </jats:sec>
Scopus© Citations 17 1
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Functional Dysconnectivity in Ventral Striatocortical Systems in 22q11.2 Deletion Syndrome
(2021)
Ángeles Tepper
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Analía Cuiza
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Luz María Alliende
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Carlos Mena
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Juan Pablo Ramirez-Mahaluf
<jats:title>Abstract</jats:title> <jats:p>22q11.2 deletion syndrome (22q11.2DS) is a genetic neurodevelopmental disorder that represents one of the greatest known risk factors for psychosis. Previous studies in psychotic subjects without the deletion have identified a dopaminergic dysfunction in striatal regions, and dysconnectivity of striatocortical systems, as an important mechanism in the emergence of psychosis. Here, we used resting-state functional MRI to examine striatocortical functional connectivity in 22q11.2DS patients. We used a 2 × 2 factorial design including 125 subjects (55 healthy controls, 28 22q11.2DS patients without a history of psychosis, 10 22q11.2DS patients with a history of psychosis, and 32 subjects with a history of psychosis without the deletion), allowing us to identify network effects related to the deletion and to the presence of psychosis. In line with previous results from psychotic patients without 22q11.2DS, we found that there was a dorsal to ventral gradient of hypo- to hyperstriatocortical connectivity related to psychosis across both patient groups. The 22q11.2DS was additionally associated with abnormal functional connectivity in ventral striatocortical networks, with no significant differences identified in the dorsal system. Abnormalities in the ventral striatocortical system observed in these individuals with high genetic risk to psychosis may thus reflect a marker of illness risk.</jats:p>
1Scopus© Citations 6
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Gender, age and geographical representation over the past 50 years of schizophrenia research
(2022)
Luz María Alliende
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Leticia S. Czepielewski
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David Aceituno
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Carmen Paz Castañeda
;
Camila Diaz
15Scopus© Citations 5

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