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1.
Hum Brain Mapp ; 2020 Oct 19.
Artigo em Inglês | MEDLINE | ID: mdl-33073925

RESUMO

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. We used linear mixed-effects models and mega-analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = -0.20), cornu ammonis (CA)1 (d = -0.18), CA2/3 (d = -0.11), CA4 (d = -0.19), molecular layer (d = -0.21), granule cell layer of dentate gyrus (d = -0.21), hippocampal tail (d = -0.10), subiculum (d = -0.15), presubiculum (d = -0.18), and hippocampal amygdala transition area (d = -0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non-users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD.

2.
Psychol Med ; : 1-9, 2020 Sep 14.
Artigo em Inglês | MEDLINE | ID: mdl-32921338

RESUMO

BACKGROUND: Eighty percent of all patients suffering from major depressive disorder (MDD) relapse at least once in their lifetime. Thus, understanding the neurobiological underpinnings of the course of MDD is of utmost importance. A detrimental course of illness in MDD was most consistently associated with superior longitudinal fasciculus (SLF) fiber integrity. As similar associations were, however, found between SLF fiber integrity and acute symptomatology, this study attempts to disentangle associations attributed to current depression from long-term course of illness. METHODS: A total of 531 patients suffering from acute (N = 250) or remitted (N = 281) MDD from the FOR2107-cohort were analyzed in this cross-sectional study using tract-based spatial statistics for diffusion tensor imaging. First, the effects of disease state (acute v. remitted), current symptom severity (BDI-score) and course of illness (number of hospitalizations) on fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity were analyzed separately. Second, disease state and BDI-scores were analyzed in conjunction with the number of hospitalizations to disentangle their effects. RESULTS: Disease state (pFWE < 0.042) and number of hospitalizations (pFWE< 0.032) were associated with decreased FA and increased MD and RD in the bilateral SLF. A trend was found for the BDI-score (pFWE > 0.067). When analyzed simultaneously only the effect of course of illness remained significant (pFWE < 0.040) mapping to the right SLF. CONCLUSIONS: Decreased FA and increased MD and RD values in the SLF are associated with more hospitalizations when controlling for current psychopathology. SLF fiber integrity could reflect cumulative illness burden at a neurobiological level and should be targeted in future longitudinal analyses.

3.
Artigo em Inglês | MEDLINE | ID: mdl-32801319

RESUMO

Childhood maltreatment is associated with cognitive deficits that in turn have been predictive for therapeutic outcome in psychiatric patients. However, previous studies have either investigated maltreatment associations with single cognitive domains or failed to adequately control for confounders such as depression, socioeconomic environment, and genetic predisposition. We aimed to isolate the relationship between childhood maltreatment and dysfunction in diverse cognitive domains, while estimating the contribution of potential confounders to this relationship, and to investigate gene-environment interactions. We included 547 depressive disorder and 670 healthy control participants (mean age: 34.7 years, SD = 13.2). Cognitive functioning was assessed for the domains of working memory, executive functioning, processing speed, attention, memory, and verbal intelligence using neuropsychological tests. Childhood maltreatment and parental education were assessed using self-reports, and psychiatric diagnosis was based on DSM-IV criteria. Polygenic scores for depression and for educational attainment were calculated. Multivariate analysis of cognitive domains yielded significant associations with childhood maltreatment (η²p = 0.083, P < 0.001), depression (η²p = 0.097, P < 0.001), parental education (η²p = 0.085, P < 0.001), and polygenic scores for depression (η²p = 0.021, P = 0.005) and educational attainment (η²p = 0.031, P < 0.001). Each of these associations remained significant when including all of the predictors in one model. Univariate tests revealed that maltreatment was associated with poorer performance in all cognitive domains. Thus, environmental, psychopathological, and genetic risk factors each independently affect cognition. The insights of the current study may aid in estimating the potential impact of different loci of interventions for cognitive dysfunction. Future research should investigate if customized interventions, informed by individual risk profiles and related cognitive preconditions, might enhance response to therapeutic treatments.

4.
JAMA Psychiatry ; 2020 Aug 26.
Artigo em Inglês | MEDLINE | ID: mdl-32857118

RESUMO

Importance: Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood. Objective: To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia. Design, Setting, and Participants: Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244. Main Outcomes and Measures: Interregional profiles of group difference in cortical thickness between cases and controls. Results: A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders. Conclusions and Relevance: In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.

5.
Clin Neurophysiol ; 131(9): 2181-2191, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32693192

RESUMO

OBJECTIVE: Advanced age is accompanied by a deterioration in memory performance that can profoundly influence activities of daily living. However, the neural processes responsible for age-related memory decline are not fully understood. Here, we used transcranial magnetic stimulation (TMS) in combination with electroencephalography (EEG) to assess age-related changes in neuroplasticity in the human prefrontal cortex. METHODS: TMS-evoked cortical potentials (TEPs) were recorded before and following the neuroplasticity-inducing intermittent theta burst stimulation (iTBS), applied to the left lateral prefrontal cortex in healthy young (n = 33, mean age 22 ± 3 years) and older adults (n = 33, mean age 68 ± 7 years). RESULTS: iTBS increased the amplitude of the positive TEP component at 60 ms after the TMS pulse (P60) in young, but not older adults. This age-related decline in P60 plasticity response was associated with poorer visuospatial associative (but not working) memory performance in older adults. CONCLUSIONS: These findings suggest that neuroplasticity in the human lateral prefrontal cortex is reduced in older relative to young adults, and this may be an important factor in age-related memory decline. SIGNIFICANCE: This may have important implications for the early detection of cognitive decline and dementia.

6.
Hum Brain Mapp ; 2020 Jul 29.
Artigo em Inglês | MEDLINE | ID: mdl-32725849

RESUMO

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. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness.

7.
Am J Med Genet B Neuropsychiatr Genet ; 183(6): 309-330, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32681593

RESUMO

It is imperative to understand the specific and shared etiologies of major depression and cardio-metabolic disease, as both traits are frequently comorbid and each represents a major burden to society. This study examined whether there is a genetic association between major depression and cardio-metabolic traits and if this association is stratified by age at onset for major depression. Polygenic risk scores analysis and linkage disequilibrium score regression was performed to examine whether differences in shared genetic etiology exist between depression case control status (N cases = 40,940, N controls = 67,532), earlier (N = 15,844), and later onset depression (N = 15,800) with body mass index, coronary artery disease, stroke, and type 2 diabetes in 11 data sets from the Psychiatric Genomics Consortium, Generation Scotland, and UK Biobank. All cardio-metabolic polygenic risk scores were associated with depression status. Significant genetic correlations were found between depression and body mass index, coronary artery disease, and type 2 diabetes. Higher polygenic risk for body mass index, coronary artery disease, and type 2 diabetes was associated with both early and later onset depression, while higher polygenic risk for stroke was associated with later onset depression only. Significant genetic correlations were found between body mass index and later onset depression, and between coronary artery disease and both early and late onset depression. The phenotypic associations between major depression and cardio-metabolic traits may partly reflect their overlapping genetic etiology irrespective of the age depression first presents.

8.
Hum Brain Mapp ; 2020 Jul 10.
Artigo em Inglês | MEDLINE | ID: mdl-32648625

RESUMO

Reduced sleep duration and sleep deprivation have been associated with cognitive impairment as well as decreased white matter integrity as reported by experimental studies. However, it is largely unknown whether differences in sleep duration and sleep quality might affect microstructural white matter and cognition. Therefore, the present study aims to examine the cross-sectional relationship between sleep duration, sleep quality, and cognitive performance in a naturalistic study design, by focusing on the association with white matter integrity in a large sample of healthy, young adults. To address this, 1,065 participants, taken from the publicly available sample of the Human Connectome Project, underwent diffusion tensor imaging. Moreover, broad cognitive performance measures (NIH Cognition Toolbox) and sleep duration and quality (Pittsburgh Sleep Quality Index) were assessed. The results revealed a significant positive association between sleep duration and overall cognitive performance. Shorter sleep duration significantly correlated with fractional anisotropy (FA) reductions in the left superior longitudinal fasciculus (SLF). In turn, FA in this tract was related to measures of cognitive performance and was shown to significantly mediate the association of sleep duration and cognition. For cognition only, associations shift to a negative association of sleep duration and cognition for participants sleeping more than 8 hr a day. Investigations into subjective sleep quality showed no such associations. The present study showed that real-world differences in sleep duration, but not subjective sleep quality are related to cognitive performance measures and white matter integrity in the SLF in healthy, young adults.

9.
Biol Psychiatry ; 88(9): 678-686, 2020 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-32646651

RESUMO

BACKGROUND: Neuroimaging studies have consistently reported similar brain structural abnormalities across different psychiatric disorders. Yet, the extent and regional distribution of shared morphometric abnormalities between disorders remains unknown. METHODS: Here, we conducted a cross-disorder analysis of brain structural abnormalities in 6 psychiatric disorders based on effect size estimates for cortical thickness and subcortical volume differences between healthy control subjects and psychiatric patients from 11 mega- and meta-analyses from the ENIGMA (Enhancing Neuro Imaging Genetics Through Meta Analysis) consortium. Correlational and exploratory factor analyses were used to quantify the relative overlap in brain structural effect sizes between disorders and to identify brain regions with disorder-specific abnormalities. RESULTS: Brain structural abnormalities in major depressive disorder, bipolar disorder, schizophrenia, and obsessive-compulsive disorder were highly correlated (r = .443 to r = .782), and one shared latent underlying factor explained between 42.3% and 88.7% of the brain structural variance of each disorder. The observed shared morphometric signature of these disorders showed little similarity with brain structural patterns related to physiological aging. In contrast, patterns of brain structural abnormalities independent of all other disorders were observed in both attention-deficit/hyperactivity disorder and autism spectrum disorder. Brain regions showing high proportions of independent variance were identified for each disorder to locate disorder-specific morphometric abnormalities. CONCLUSIONS: Taken together, these results offer novel insights into transdiagnostic as well as disorder-specific brain structural abnormalities across 6 major psychiatric disorders. Limitations comprise the uncertain contribution of risk factors, comorbidities, and medication effects to the observed pattern of results that should be clarified by future research.

10.
Brain Behav Immun ; 88: 242-251, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-32526448

RESUMO

BACKGROUND: A subset of patients with Major Depressive Disorder (MDD) have shown differences relative to healthy controls in blood inflammatory and immune markers. Meanwhile, MDD and comorbid obesity appear to present with distinct biological and symptom characteristics, categorised as "atypical" or "immunometabolic" depression, although the relevant underlying biological mechanisms are still uncertain. Therefore, this exploratory study aimed to better characterise the relationship between peripheral blood immune markers and symptoms of MDD, as well as the extent to which body mass index (BMI) may alter this relationship. METHODS: Linear regression analyses were performed between selected baseline characteristics including clinical scales and blood inflammatory markers in participants with MDD (n = 119) enrolled in the PREDDICT randomised controlled trial (RCT), using age, sex and BMI as covariates, and then stratified by BMI status. Specifically, the Montgomery-Åsberg Depression Rating Scale (MADRS) for symptom severity, Clinical Global Impression scale (CGI) for functional impairment, Oxford Depression Questionnaire (ODQ) for emotional blunting, and THINC integrated tool (THINC-it) for cognitive function were considered as clinical measures. RESULTS: There was a significant association between basophil count and THINC-it Codebreaker mean response time (associated with complex attention, perceptual motor, executive function, and learning and memory abilities) in overweight individuals and with THINC-it Trails total response time (associated with executive function ability) in moderately obese individuals, when controlling for age, sex, and years of education. No correlation was found between any tested blood markers and MADRS, CGI or ODQ clinical measures, regardless of BMI. DISCUSSION: Although the present study is exploratory, the results suggest that targeting of the immune system and of metabolic parameters might confer benefits, specifically in patients with high BMI and experiencing cognitive impairment associated with MDD. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR), ACTRN12617000527369p. Registered on 11 April 2017.

11.
Cell Mol Neurobiol ; 2020 May 25.
Artigo em Inglês | MEDLINE | ID: mdl-32451728

RESUMO

Physical exercise (PE) and environmental enrichment (EE) can modulate immunity. However, the differential effects of short-term PE, EE, and PE + EE on neuroimmune mechanisms during normal aging has not been elucidated. Hence, a cohort of 3-, 8-, and 13-month-old immunologically unchallenged C57BL/6 wild-type mice were randomly assigned to either Control, PE, EE, or PE + EE groups and provided with either no treatment, a running wheel, a variety of plastic and wooden objects alone or in combination with a running wheel for seven weeks, respectively. Immunohistochemistry and 8-color flow cytometry were used to determine the numbers of dentate gyrus glial cells, and the proportions of CD4+ and CD8+ T cell numbers and their subsets from cervical lymph nodes, respectively. An increase in the number of IBA1+ microglia in the dentate gyrus at 5 and 10 months was observed after EE, while PE and PE + EE increased it only at 10 months. No change in astroglia number in comparison to controls were observed in any of the treatment groups. Also, all treatments induced significant differences in the proportion of specific T cell subsets, i.e., CD4+ and CD8+ T naïve (TN), central memory (TCM), and effector memory (TEM) cells. Our results suggest that in the short-term, EE is a stronger modulator of microglial and peripheral T cell subset numbers than PE and PE + EE, and the combination of short-term PE and EE has no additive effects.

12.
Mol Psychiatry ; 2020 May 18.
Artigo em Inglês | MEDLINE | ID: mdl-32424236

RESUMO

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.

13.
Eur Neuropsychopharmacol ; 36: 10-17, 2020 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-32451266

RESUMO

While the hippocampus remains a region of high interest for neuropsychiatric research, the precise contributors to hippocampal morphometry are still not well understood. We and others previously reported a hippocampus specific effect of a tescalcin gene (TESC) regulating single nucleotide polymorphism (rs7294919) on gray matter volume. Here we aimed to replicate and extend these findings. Two complementary morphometric approaches (voxel based morphometry (VBM) and automated volumetric segmentation) were applied in a well-powered cohort from the Marburg-Münster Affective Disorder Cohort Study (MACS) including N=1137 participants (n=636 healthy controls, n=501 depressed patients). rs7294919 homozygous T-allele genotype was significantly associated with lower hippocampal gray matter density as well as with reduced hippocampal volume. Exploratory whole brain VBM analyses revealed no further associations with gray matter volume outside the hippocampus. No interaction effects of rs7294919 with depression nor with childhood trauma on hippocampal morphometry could be detected. Hippocampal subfield analyses revealed similar effects of rs7294919 in all hippocampal subfields. In sum, our results replicate a hippocampus specific effect of rs7294919 on brain structure. Due to the robust evidence for a pronounced association between the reported polymorphism and hippocampal morphometry, future research should consider investigating the potential clinical and functional relevance of the reported association.

14.
Brain Stimul ; 13(4): 1051-1058, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32388195

RESUMO

BACKGROUND: In treatment-resistant major depressive disorder (MDD), electroconvulsive therapy (ECT) is a treatment with high efficacy. While knowledge regarding changes in brain structure following ECT is growing, the effects of ECT on brain function during emotional processing are largely unknown. OBJECTIVE: We investigated the effects of ECT on the activity of the anterior cingulate cortex (ACC) and amygdala during negative emotional stimuli processing and its association with clinical response. METHODS: In this non-randomized longitudinal study, patients with MDD (n = 37) were assessed before and after treatment with ECT. Healthy controls (n = 37) were matched regarding age and gender. Functional magnetic resonance imaging (fMRI) was obtained twice, at baseline and after six weeks using a supraliminal face-matching paradigm. In order to evaluate effects of clinical response, additional post-hoc analyses were performed comparing responders to non-responders. RESULTS: After ECT, patients with MDD showed a statistically significant increase in ACC activity during processing of negative emotional stimuli (pFWE = .039). This effect was driven by responders (pFWE = .023), while non-responders showed no increase. Responders also had lower pre-treatment ACC activity compared to non-responders (pFWE = .025). No significant effects in the amygdala could be observed. CONCLUSIONS: ECT leads to brain functional changes in the ACC, a relevant region for emotional regulation during processing of negative stimuli. Furthermore, baseline ACC activity might serve as a biomarker for treatment response. Findings are in accordance with recent studies highlighting properties of pre-treatment ACC to be associated with general antidepressive treatment response.

15.
Transl Psychiatry ; 10(1): 172, 2020 05 29.
Artigo em Inglês | MEDLINE | ID: mdl-32472038

RESUMO

A key objective in the field of translational psychiatry over the past few decades has been to identify the brain correlates of major depressive disorder (MDD). Identifying measurable indicators of brain processes associated with MDD could facilitate the detection of individuals at risk, and the development of novel treatments, the monitoring of treatment effects, and predicting who might benefit most from treatments that target specific brain mechanisms. However, despite intensive neuroimaging research towards this effort, underpowered studies and a lack of reproducible findings have hindered progress. Here, we discuss the work of the ENIGMA Major Depressive Disorder (MDD) Consortium, which was established to address issues of poor replication, unreliable results, and overestimation of effect sizes in previous studies. The ENIGMA MDD Consortium currently includes data from 45 MDD study cohorts from 14 countries across six continents. The primary aim of ENIGMA MDD is to identify structural and functional brain alterations associated with MDD that can be reliably detected and replicated across cohorts worldwide. A secondary goal is to investigate how demographic, genetic, clinical, psychological, and environmental factors affect these associations. In this review, we summarize findings of the ENIGMA MDD disease working group to date and discuss future directions. We also highlight the challenges and benefits of large-scale data sharing for mental health research.

16.
Bipolar Disord ; 2020 May 01.
Artigo em Inglês | MEDLINE | ID: mdl-32356562

RESUMO

OBJECTIVES: The association of bipolar disorder with early and excessive cardiovascular disease was identified over a century ago. Nonetheless, the vascular-bipolar link remains underrecognized, particularly with regard to how this link can contribute to our understanding of pathogenesis and treatment. METHODS: An international group of experts completed a selective review of the literature, distilling core themes, identifying limitations and gaps in the literature, and highlighting future directions to bridge these gaps. RESULTS: The association between bipolar disorder and vascular disease is large in magnitude, consistent across studies, and independent of confounding variables where assessed. The vascular-bipolar link is multifactorial and is difficult to study given the latency between the onset of bipolar disorder, often in adolescence or early adulthood, and subsequent vascular disease, which usually occurs decades later. As a result, studies have often focused on risk factors for vascular disease or intermediate phenotypes, such as structural and functional vascular imaging measures. There is interest in identifying the most relevant mediators of this relationship, including lifestyle (eg, smoking, diet, exercise), medications, and systemic biological mediators (eg, inflammation). Nonetheless, there is a paucity of treatment studies that deliberately engage these mediators, and thus far no treatment studies have focused on engaging vascular imaging targets. CONCLUSIONS: Further research focused on the vascular-bipolar link holds promise for gleaning insights regarding the underlying causes of bipolar disorder, identifying novel treatment approaches, and mitigating disparities in cardiovascular outcomes for people with bipolar disorder.

17.
Neuropsychopharmacology ; 45(10): 1758-1765, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32272482

RESUMO

Transgender individuals (TIs) show brain-structural alterations that differ from their biological sex as well as their perceived gender. To substantiate evidence that the brain structure of TIs differs from male and female, we use a combined multivariate and univariate approach. Gray matter segments resulting from voxel-based morphometry preprocessing of N = 1753 cisgender (CG) healthy participants were used to train (N = 1402) and validate (20% holdout N = 351) a support-vector machine classifying the biological sex. As a second validation, we classified N = 1104 patients with depression. A third validation was performed using the matched CG sample of the transgender women (TW) application sample. Subsequently, the classifier was applied to N = 26 TW. Finally, we compared brain volumes of CG-men, women, and TW-pre/post treatment cross-sex hormone treatment (CHT) in a univariate analysis controlling for sexual orientation, age, and total brain volume. The application of our biological sex classifier to the transgender sample resulted in a significantly lower true positive rate (TPR-male = 56.0%). The TPR did not differ between CG-individuals with (TPR-male = 86.9%) and without depression (TPR-male = 88.5%). The univariate analysis of the transgender application-sample revealed that TW-pre/post treatment show brain-structural differences from CG-women and CG-men in the putamen and insula, as well as the whole-brain analysis. Our results support the hypothesis that brain structure in TW differs from brain structure of their biological sex (male) as well as their perceived gender (female). This finding substantiates evidence that TIs show specific brain-structural alterations leading to a different pattern of brain structure than CG-individuals.

19.
Transl Psychiatry ; 10(1): 100, 2020 03 20.
Artigo em Inglês | MEDLINE | ID: mdl-32198361

RESUMO

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.

20.
J Affect Disord ; 267: 42-48, 2020 Apr 15.
Artigo em Inglês | MEDLINE | ID: mdl-32063571

RESUMO

BACKGROUND: At present, no predictive markers for Major Depressive Disorder (MDD) exist. The search for such markers has been challenging due to clinical and molecular heterogeneity of MDD, the lack of statistical power in studies and suboptimal statistical tools applied to multidimensional data. Machine learning is a powerful approach to mitigate some of these limitations. METHODS: We aimed to identify the predictive markers of recurrent MDD in the elderly using peripheral whole blood from the Sydney Memory and Aging Study (SMAS) (N = 521, aged over 65) and adopting machine learning methodology on transcriptome data. Fuzzy Forests is a Random Forests-based classification algorithm that takes advantage of the co-expression network structure between genes; it allows to alleviate the problem of p >> n via reducing the dimensionality of transcriptomic feature space. RESULTS: By adopting Fuzzy Forests on transcriptome data, we found that the downregulated TFRC (transferrin receptor) can predict recurrent MDD with an accuracy of 63%. LIMITATIONS: Although we corrected our data for several important confounders, we were not able to account for the comorbidities and medication taken, which may be numerous in the elderly and might have affected the levels of gene transcription. CONCLUSIONS: We found that downregulated TFRC is predictive of recurrent MDD, which is consistent with the previous literature, indicating the role of the innate immune system in depression. This study is the first to successfully apply Fuzzy Forests methodology on psychiatric condition, opening, therefore, a methodological avenue that can lead to clinically useful predictive markers of complex traits.

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