Predicting Diagnostic Conversion From Major Depressive Disorder to Bipolar Disorder: An EHR Based Study From Colombia.

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.

White matter microstructure in obesity and bipolar disorders: an ENIGMA bipolar disorder working group study in 2186 individuals.

Although specific risk factors for brain alterations in bipolar disorders (BD) are currently unknown, obesity impacts the brain and is highly prevalent in BD. Gray matter correlates of obesity in BD have been well documented, but we know much less about brain white matter abnormalities in people who have both obesity and BD. We obtained body mass index (BMI) and diffusion tensor imaging derived fractional anisotropy (FA) from 22 white matter tracts in 899 individuals with BD, and 1287 control individuals from 20 cohorts in the ENIGMA-BD working group.

Geospatial investigations in Colombia reveal variations in the distribution of mood and psychotic disorders.

Background: Geographical variations in mood and psychotic disorders have been found in upper-income countries. We looked for geographic variation in these disorders in Colombia, a middle-income country. We analyzed electronic health records from the Clínica San Juan de Dios Manizales (CSJDM), which provides comprehensive mental healthcare for the one million inhabitants of Caldas.

Predicting diagnostic conversion from major depressive disorder to bipolar disorder: an EHR based study from Colombia.

Bipolar Disorder (BD) is a severe and chronic disorder characterized by recurrent episodes of depression, mania, and/or hypomania. Most BD patients initially present with depressive symptoms, resulting in a delayed diagnosis of BD and poor clinical outcomes. This study leverages electronic health record (EHR) data from the Clínica San Juan de Dios Manizales in Colombia to identify features predictive of the transition from Major Depressive Disorder (MDD) to BD.

Ancestry component as a major predictor of lithium response in the treatment of bipolar disorder.

Background: Bipolar Disorder (BD) represents the seventh major cause of disability life-years-adjusted. Lithium remains as a first-line treatment, but clinical improvement occurs only in 30 % of treated patients. Studies suggest that genetics plays a major role in shaping the individual response of BD patients to lithium.

Mega-analysis of association between obesity and cortical morphology in bipolar disorders: ENIGMA study in 2832 participants.

Background: Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact.

Diagnosis of bipolar disorders and body mass index predict clustering based on similarities in cortical thickness-ENIGMA study in 2436 individuals.

Aims: Rates of obesity have reached epidemic proportions, especially among people with psychiatric disorders. While the effects of obesity on the brain are of major interest in medicine, they remain markedly under-researched in psychiatry.

Methods: We obtained body mass index (BMI) and magnetic resonance imaging-derived regional cortical thickness, surface area from 836 bipolar disorders (BD) and 1600 control individuals from 14 sites within the ENIGMA-BD Working Group.

Association between body mass index and subcortical brain volumes in bipolar disorders-ENIGMA study in 2735 individuals.

Individuals with bipolar disorders (BD) frequently suffer from obesity, which is often associated with neurostructural alterations. Yet, the effects of obesity on brain structure in BD are under-researched. We obtained MRI-derived brain subcortical volumes and body mass index (BMI) from 1134 BD and 1601 control individuals from 17 independent research sites within the ENIGMA-BD Working Group.

In vivo hippocampal subfield volumes in bipolar disorder-A mega-analysis from The Enhancing Neuro Imaging Genetics through Meta-Analysis Bipolar Disorder Working Group.

The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta-Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1-weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer.

Structural brain abnormalities in schizophrenia in adverse environments: examining the effect of poverty and violence in six Latin American cities.

Background: Social and environmental factors such as poverty or violence modulate the risk and course of schizophrenia. However, how they affect the brain in patients with psychosis remains unclear.

Aims: We studied how environmental factors are related to brain structure in patients with schizophrenia and controls in Latin America, where these factors are large and unequally distributed.

What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group.

MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD.

Distinct and shared contributions of diagnosis and symptom domains to cognitive performance in severe mental illness in the Paisa population: a case-control study.

Background: Severe mental illness diagnoses have overlapping symptomatology and shared genetic risk, motivating cross-diagnostic investigations of disease-relevant quantitative measures. We analysed relationships between neurocognitive performance, symptom domains, and diagnoses in a large sample of people with severe mental illness not ascertained for a specific diagnosis (cases), and people without mental illness (controls) from a single, homogeneous population.

Methods: In this case-control study, cases with severe mental illness were ascertained through electronic medical records at Clínica San Juan de Dios de Manizales (Manizales, Caldas, Colombia) and the Hospital Universitario San Vicente Fundación (Medellín, Antioquía, Colombia).

10Kin1day: A Bottom-Up Neuroimaging Initiative.

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.

Imaging Social and Environmental Factors as Modulators of Brain Dysfunction: Time to Focus on Developing Non-Western Societies.

Social and environmental factors are known risk factors and modulators of mental health disorders. We here conducted a nonsystematic review of the neuroimaging literature studying the effects of poverty, urbanicity, and community violence, highlighting the opportunities of studying non-Western developing societies such as those in Latin America. Social and environmental factors in these communities are widespread and have a large magnitude, as well as an unequal distribution, providing a good opportunity for their characterization.

Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group.

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use.

Inflammatory Markers in the Staging of Bipolar Disorder: A Systematic Review of the Literature.

Background: Previous studies suggest that inflammatory molecules play an important role in the pathophysiology of Bipolar Disorder (BD). The evidence suggests that BD may present a progressive course. Therefore there are theories that postulate the relationship between progression and stages of the disease with distinct peripheral biomarkers.

Evaluation and Socio-occupational Intervention in Bipolar and Schizophrenic Patients within a Multimodal Intervention Program- PRISMA.

Background: Functional improvement in bipolar and schizophrenic patients is one of the main aims of treatment. Nevertheless, there is no evidence about the effect of socio-occupational intervention within a multimodal intervention (MI) programme.

Objective: To describe the socio-occupational profile and to evaluate the functional effect of a MI in bipolar I and schizophrenic patients.

[Impact of a Multimodal Intervention on the Psychological Profile of Schizophrenic and Bipolar I Patients: A Study of PRISMA Program].

Background: Bipolar Disorder (BD) and schizophrenia are included in the group of severe mental illness and are main causes of disability and morbidity in the local population due to the bio-psycho-social implications in patients. In the last 20 years or so, adjunctive psychological interventions been studied with the purpose of decreasing recurrences, stabilising the course of the disease, and improving the functionality in these patients.

Objective: To analyse the psychological effect of a multimodal intervention (MI) vs a traditional intervention (TI) program in BD I and schizophrenic patients.