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.
View Article and Find Full Text PDFRev Colomb Psiquiatr (Engl Ed)
July 2022
Introduction: Lithium treatment of bipolar disorder (BD) has been associated with less cognitive impairment and fewer changes in structural brain anatomy compared to other treatments. However, the studies are heterogeneous and few assess whether these effects are related. The objective of this study was to evaluate and relate cognitive performance and structural neuroanatomy in patients treated with and without lithium.
View Article and Find Full Text PDFAims: 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.
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.
View Article and Find Full Text PDFRev Colomb Psiquiatr (Engl Ed)
January 2021
Introduction: Lithium treatment of bipolar disorder (BD) has been associated with less cognitive impairment and fewer changes in structural brain anatomy compared to other treatments. However, the studies are heterogeneous and few assess whether these effects are related. The objective of this study was to evaluate and relate cognitive performance and structural neuroanatomy in patients treated with and without lithium.
View Article and Find Full Text PDFHum Brain Mapp
January 2022
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.
View Article and Find Full Text PDFBackground: 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.
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.
View Article and Find Full Text PDFBiol Psychiatry Cogn Neurosci Neuroimaging
January 2019
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.
View Article and Find Full Text PDFBipolar 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.
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