Browsing by Author "Ramirez, Juan"
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Item Functional Dysconnectivity in Ventral Striatocortical Systems in 22q11.2 Deletion Syndrome(2022) Tepper, Ángeles; Cuiza, Analía; Alliende, Luz; Mena, Carlos; Ramirez, Juan; Iruretagoyena, Bárbara; Ornstein, Claudia; Fritsch, Rosemarie; Nachar, Ruben; González, Alfonso; Undurraga, Juan; Cruz, Juan; Nachar, Ruben; González, Alfonso; Undurraga, Juan; Cruz, Juan; Tejos, Cristian; Fornito, Alex; Repetto, Gabriela; Crossley, Nicolás22q11.2 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.Publication Interpretable machine learning model for characterizing magnetic susceptibility-based biomarkers in first episode psychosis(2025) Franco, Pamela; Montalba, Cristian; Caulier, Raúl; Milovic, Carlos; González, Alfonso; Ramirez, Juan; Undurraga, Juan; Salas, Rodrigo; Crossley, Nicolás; Tejos, Cristian; Uribe, SergioBackground and purpose: Several studies have shown changes in neurochemicals within the deep-brain nuclei of patients with psychosis. These alterations indicate a dysfunction in dopamine within subcortical regions affected by fluctuations in iron concentrations. Quantitative Susceptibility Mapping (QSM) is a method employed to measure iron concentration, offering a potential means to identify dopamine dysfunction in these subcortical areas. This study employed a random forest algorithm to predict susceptibility features of the First-Episode Psychosis (FEP) and the response to antipsychotics using Shapley Additionality Explanation (SHAP) values. Methods: 3D multi-echo Gradient Echo (GRE) and T1-weighted GRE were obtained in 61 healthy-volunteers (HV) and 76 FEP patients (32 % Treatment-Resistant Schizophrenia (TRS) and 68 % treatment-Responsive Schizophrenia (RS)) using a 3T Philips Ingenia MRI scanner. QSM and R2* were reconstructed and averaged in twenty-two segmented regions of interest. We used a Sequential Forward Selection as a feature selection algorithm and a Random Forest as a model to predict FEP patients and their response to antipsychotics. We further applied the SHAP framework to identify informative features and their interpretations. Finally, multiple correlation patterns from magnetic susceptibility parameters were extracted using hierarchical clustering. Results: Our approach accurately classifies HV and FEP patients with 76.48 ± 10.73 % accuracy (using four features) and TRS vs RS patients with 76.43 ± 12.57 % accuracy (using four features), using 10-fold stratified cross-validation. The SHAP analyses indicated the top four nonlinear relationships between the selected features. Hierarchical clustering revealed two groups of correlated features for each study. Conclusions: Early prediction of treatment response enables tailored strategies for FEP patients with treatment resistance, ensuring timely and effective interventions.Publication Longitudinal changes in striatocortical connectivity in first-episode psychosis associated with the emergence of treatment resistance(2025) Tepper, Angeles; Vásquez, Javiera; Díaz, Camila; Ramirez, Juan; Aguirre, Juan; Barbagelata, Daniella; Aceituno, David; Undurraga, Juan; Nachar, Ruben; Mena, Cristian; McCutcheon, Robert; McGuire, Philip; Gonzalez, Alfonso; Crossley, NicolasTreatment resistance affects up to one in four individuals with psychosis in the first few years of illness. However, there is limited information about the brain changes associated with treatment resistance, restricting our ability to develop effective prognostic biomarkers or new treatments. Using resting-state functional MRI, we examined striatocortical connectivity in 87 patients who presented a non-affective first-episode of psychosis and 118 healthy controls, with follow-up imaging on more than half of the participants in the next 6 years, totaling 361 images. Crucially, we identified 30 patients who presented treatment-resistant psychosis in this follow-up period. Thus, we examined baseline (at first episode) and longitudinal striatocortical differences within psychosis subgroups (treatment-responsive and treatment-resistant psychosis), and between patients subgroups and healthy controls. Compared to healthy controls, participants with treatment-responsive psychosis presented baseline differences in functional connectivity of ventral striatal systems, without changes over time; whereas patients with treatment-resistant psychosis showed both baseline and longitudinal differences in ventral striatal systems, compared to healthy controls. Treatment-responsive and treatment-resistant psychosis groups differed in longitudinal changes in connectivity between ventral striatal and temporal cortical regions. This is one of the circuits which has been previously related to symptom improvements in patients with first-episode of psychosis. No baseline differences were observed between the two psychosis groups. Overall, treatment-resistant psychosis is characterized by longitudinal changes in striatal systems in early psychosis, which might be used as the basis of future prognostic biomarkers.