Nejvíce citovaný článek - PubMed ID 32356562
Call to action regarding the vascular-bipolar link: A report from the Vascular Task Force of the International Society for Bipolar Disorders
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. In a mega-analysis, we investigated the associations between BMI, diagnosis or medication and FA. Lower FA was associated with both BD and BMI in six white matter tracts, including the corpus callosum and thalamic radiation. Higher BMI or BD were uniquely associated with lower FA in three and six white matter tracts, respectively. People not receiving lithium treatment had a greater negative association between FA and BMI than people treated with lithium in the posterior thalamic radiation and sagittal stratum. In three tracts BMI accounted for 10.5 to 17% of the negative association between the number of medication classes other than lithium and FA. Both overweight/obesity and BD demonstrated lower FA in some of the same regions. People prescribed lithium had a weaker association between BMI and FA than people not on lithium. In contrast, greater weight contributed to the negative associations between medications and FA. Obesity may add to brain alterations in BD and may play a role in effects of medications on the brain.
- MeSH
- anizotropie MeSH
- bílá hmota * patologie diagnostické zobrazování metabolismus MeSH
- bipolární porucha * patologie metabolismus MeSH
- dospělí MeSH
- index tělesné hmotnosti MeSH
- lidé středního věku MeSH
- lidé MeSH
- mozek patologie MeSH
- obezita * patologie metabolismus komplikace MeSH
- šedá hmota MeSH
- zobrazování difuzních tenzorů metody MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
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. METHODS: We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations. RESULTS: BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI. CONCLUSIONS: We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.
- Klíčová slova
- Body mass index, antipsychotics, bipolar disorders, cortical thickness, heterogeneity, lithium, obesity, surface area,
- MeSH
- bipolární porucha * patologie diagnostické zobrazování MeSH
- dospělí MeSH
- index tělesné hmotnosti * MeSH
- lidé středního věku MeSH
- lidé MeSH
- magnetická rezonanční tomografie * MeSH
- mozková kůra * diagnostické zobrazování patologie MeSH
- obezita * patologie MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- metaanalýza MeSH
Bipolar disorder is heterogeneous in phenomenology, illness trajectory, and response to treatment. Despite evidence for the efficacy of multimodal-ity interventions, the majority of persons affected by this disorder do not achieve and sustain full syndromal recovery. It is eagerly anticipated that combining datasets across various information sources (e.g., hierarchical "multi-omic" measures, electronic health records), analyzed using advanced computational methods (e.g., machine learning), will inform future diagnosis and treatment selection. In the interim, identifying clinically meaningful subgroups of persons with the disorder having differential response to specific treatments at point-of-care is an empirical priority. This paper endeavours to synthesize salient domains in the clinical characterization of the adult patient with bipolar disorder, with the overarching aim to improve health outcomes by informing patient management and treatment considerations. Extant data indicate that characterizing select domains in bipolar disorder provides actionable information and guides shared decision making. For example, it is robustly established that the presence of mixed features - especially during depressive episodes - and of physical and psychiatric comorbidities informs illness trajectory, response to treatment, and suicide risk. In addition, early environmental exposures (e.g., sexual and physical abuse, emotional neglect) are highly associated with more complicated illness presentations, inviting the need for developmentally-oriented and integrated treatment approaches. There have been significant advances in validating subtypes of bipolar disorder (e.g., bipolar I vs. II disorder), particularly in regard to pharmacological interventions. As with other severe mental disorders, social functioning, interpersonal/family relationships and internalized stigma are domains highly relevant to relapse risk, health outcomes, and quality of life. The elevated standardized mortality ratio for completed suicide and suicidal behaviour in bipolar disorder invites the need for characterization of this domain in all patients. The framework of this paper is to describe all the above salient domains, providing a synthesis of extant literature and recommendations for decision support tools and clinical metrics that can be implemented at point-of-care.
- Klíčová slova
- Bipolar disorder, bipolar I disorder, bipolar II disorder, clinical characterization, cognition, comorbidity, depression, mania, mixed features, personalization, phenotyping, rapid cycling, resilience, social determinants, stigma, stressors, subtypes, trauma,
- Publikační typ
- časopisecké články MeSH
Schizophrenia is frequently associated with obesity, which is linked with neurostructural alterations. Yet, we do not understand how the brain correlates of obesity map onto the brain changes in schizophrenia. We obtained MRI-derived brain cortical and subcortical measures and body mass index (BMI) from 1260 individuals with schizophrenia and 1761 controls from 12 independent research sites within the ENIGMA-Schizophrenia Working Group. We jointly modeled the statistical effects of schizophrenia and BMI using mixed effects. BMI was additively associated with structure of many of the same brain regions as schizophrenia, but the cortical and subcortical alterations in schizophrenia were more widespread and pronounced. Both BMI and schizophrenia were primarily associated with changes in cortical thickness, with fewer correlates in surface area. While, BMI was negatively associated with cortical thickness, the significant associations between BMI and surface area or subcortical volumes were positive. Lastly, the brain correlates of obesity were replicated among large studies and closely resembled neurostructural changes in major depressive disorders. We confirmed widespread associations between BMI and brain structure in individuals with schizophrenia. People with both obesity and schizophrenia showed more pronounced brain alterations than people with only one of these conditions. Obesity appears to be a relevant factor which could account for heterogeneity of brain imaging findings and for differences in brain imaging outcomes among people with schizophrenia.
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. We identified regionally specific profiles of cortical thickness using K-means clustering and studied clinical characteristics associated with individual cortical profiles. RESULTS: We detected two clusters based on similarities among participants in cortical thickness. The lower thickness cluster (46.8% of the sample) showed thinner cortex, especially in the frontal and temporal lobes and was associated with diagnosis of BD, higher BMI, and older age. BD individuals in the low thickness cluster were more likely to have the diagnosis of bipolar disorder I and less likely to be treated with lithium. In contrast, clustering based on similarities in the cortical surface area was unrelated to BD or BMI and only tracked age and sex. CONCLUSIONS: We provide evidence that both BD and obesity are associated with similar alterations in cortical thickness, but not surface area. The fact that obesity increased the chance of having low cortical thickness could explain differences in cortical measures among people with BD. The thinner cortex in individuals with higher BMI, which was additive and similar to the BD-associated alterations, may suggest that treating obesity could lower the extent of cortical thinning in BD.
- Klíčová slova
- bipolar disorders, body mass index, cortical thickness, heterogeneity, obesity, surface area,
- MeSH
- bipolární porucha * diagnóza MeSH
- index tělesné hmotnosti MeSH
- lidé MeSH
- magnetická rezonanční tomografie MeSH
- obezita komplikace diagnostické zobrazování MeSH
- shluková analýza MeSH
- spánkový lalok patologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
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. We jointly modeled the effects of BD and BMI on subcortical volumes using mixed-effects modeling and tested for mediation of group differences by obesity using nonparametric bootstrapping. All models controlled for age, sex, hemisphere, total intracranial volume, and data collection site. Relative to controls, individuals with BD had significantly higher BMI, larger lateral ventricular volume, and smaller volumes of amygdala, hippocampus, pallidum, caudate, and thalamus. BMI was positively associated with ventricular and amygdala and negatively with pallidal volumes. When analyzed jointly, both BD and BMI remained associated with volumes of lateral ventricles and amygdala. Adjusting for BMI decreased the BD vs control differences in ventricular volume. Specifically, 18.41% of the association between BD and ventricular volume was mediated by BMI (Z = 2.73, p = 0.006). BMI was associated with similar regional brain volumes as BD, including lateral ventricles, amygdala, and pallidum. Higher BMI may in part account for larger ventricles, one of the most replicated findings in BD. Comorbidity with obesity could explain why neurostructural alterations are more pronounced in some individuals with BD. Future prospective brain imaging studies should investigate whether obesity could be a modifiable risk factor for neuroprogression.
BACKGROUND: Obesity is highly prevalent in schizophrenia, with implications for psychiatric prognosis, possibly through links between obesity and brain structure. In this longitudinal study in first episode of psychosis (FEP), we used machine learning and structural magnetic resonance imaging (MRI) to study the impact of psychotic illness and obesity on brain ageing/neuroprogression shortly after illness onset. METHODS: We acquired 2 prospective MRI scans on average 1.61 years apart in 183 FEP and 155 control individuals. We used a machine learning model trained on an independent sample of 504 controls to estimate the individual brain ages of study participants and calculated BrainAGE by subtracting chronological from the estimated brain age. RESULTS: Individuals with FEP had a higher initial BrainAGE than controls (3.39 ± 6.36 vs 1.72 ± 5.56 years; β = 1.68, t(336) = 2.59, P = .01), but similar annual rates of brain ageing over time (1.28 ± 2.40 vs 1.07±1.74 estimated years/actual year; t(333) = 0.93, P = .18). Across both cohorts, greater baseline body mass index (BMI) predicted faster brain ageing (β = 0.08, t(333) = 2.59, P = .01). For each additional BMI point, the brain aged by an additional month per year. Worsening of functioning over time (Global Assessment of Functioning; β = -0.04, t(164) = -2.48, P = .01) and increases especially in negative symptoms on the Positive and Negative Syndrome Scale (β = 0.11, t(175) = 3.11, P = .002) were associated with faster brain ageing in FEP. CONCLUSIONS: Brain alterations in psychosis are manifest already during the first episode and over time get worse in those with worsening clinical outcomes or higher baseline BMI. As baseline BMI predicted faster brain ageing, obesity may represent a modifiable risk factor in FEP that is linked with psychiatric outcomes via effects on brain structure.
- Klíčová slova
- antipsychotics, brain age, first-episode psychosis, longitudinal study, machine learning, obesity,
- MeSH
- dospělí MeSH
- index tělesné hmotnosti MeSH
- lidé MeSH
- longitudinální studie MeSH
- magnetická rezonanční tomografie MeSH
- mladiství MeSH
- mladý dospělý MeSH
- obezita komplikace diagnostické zobrazování patologie patofyziologie MeSH
- předčasné stárnutí diagnostické zobrazování etiologie patologie patofyziologie MeSH
- progrese nemoci * MeSH
- psychotické poruchy diagnostické zobrazování patologie patofyziologie MeSH
- rizikové faktory MeSH
- strojové učení * MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mladiství MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
