Publications by authors named "C E Bearden"
Objectives: Most bipolar disorder (BD) patients initially present with depressive symptoms, resulting in a delayed diagnosis of BD and poor clinical outcomes. This study aims to identify features predictive of the conversion from Major Depressive Disorder (MDD) to BD by leveraging electronic health record (EHR) data from the Clínica San Juan de Dios Manizales in Colombia.
Methods: We employed a multivariable Cox regression model to identify important predictors of conversion from MDD to BD.
Background: Attention Deficit Hyperactivity Disorder (ADHD) affects a significant proportion of the population and is associated with numerous adverse outcomes including lower educational attainment, occupational challenges, increased substance use, and various mental health issues including psychosis. This study examined the demographic, clinical, cognitive, social cognitive, and functional differences between youth at clinical high-risk (CHR) for psychosis with and without comorbid ADHD.
Method: Data were drawn from the North American Prodrome Longitudinal Studies (NAPLS2 and NAPLS3), which included 764 and 710 CHR individuals, respectively.
Mismatch negativity (MMN) event-related potential (ERP) component reduction, indexing N-methyl-D-aspartate receptor (NMDAR)-dependent auditory echoic memory and short-term plasticity, is a well-established biomarker of schizophrenia that is sensitive to psychosis risk among individuals at clinical high-risk (CHR-P). Based on the NMDAR-hypofunction model of schizophrenia, NMDAR-dependent plasticity is predicted to contribute to aberrant neurodevelopmental processes involved in the pathogenesis of schizophrenia during late adolescence or young adulthood, including gray matter loss. Moreover, stress and inflammation disrupt plasticity.
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- - The PUMAS project aims to address the lack of representation of African and Latin American populations in psychiatric genetics studies by analyzing genetic data from individuals with serious mental illness (SMI), including disorders like schizophrenia and bipolar disorder, using data from 89,320 participants across four different cohorts.
- - The research involves harmonizing data from various clinical assessments to create standardized measures of mental health symptoms, which allows for more accurate genetic analyses across different diagnoses and symptoms.
- - The findings show that schizophrenia and severe bipolar disorder are the most common diagnoses among participants, and a set of 19 key symptoms has been identified, which may be useful for cross-diagnosis genetic studies.
Background And Hypothesis: Studying individuals at Clinical High Risk (CHR) for psychosis provides an opportunity to examine protective factors that predict resilient outcomes. Here, we present a model for the study of protective factors in CHR participants at the very highest risk for psychotic conversion based on the Psychosis Risk Calculator.
Study Design: CHR participants (N = 572) from NAPLS3 were assessed on the Risk Calculator.