240 research outputs found
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A novel biomarker of cardiometabolic pathology in schizophrenia?
BackgroundPersons with schizophrenia and schizoaffective disorder (PwS) have high rates of cardiometabolic pathology that contributes to premature mortality. Adiponectin is a metabolic hormone affecting insulin sensitivity and inflammation, and is active in the brain. High-molecular weight (HMW) adiponectin is considered a more sensitive marker of metabolic dysfunction than total adiponectin, but has been poorly studied in schizophrenia.MethodsThis was a cross-sectional study of 100 PwS, age range 26-68 years (46 women), and 93 age- and sex-comparable non-psychiatric comparison (NC) subjects. Assessments included measures of psychopathology, physical health, cognitive function, and circulating biomarkers of metabolic dysfunction (HMW adiponectin, lipids, insulin resistance) and inflammation (high-sensitivity C-reactive protein or hs-CRP, Tumor Necrosis Factor-α, Interleukin-6, and Interleukin-10).ResultsHMW adiponectin levels were lower in PwS compared to NCs. Lower HMW adiponectin levels were associated with higher body mass index (BMI), higher Framingham risk for coronary heart disease, higher number of metabolic syndrome criteria, greater insulin resistance, lower HDL cholesterol, and higher hs-CRP in both groups. Only in PwS, lower HMW adiponectin correlated with younger age. In the best-fit regression models of HMW adiponectin, lower levels were associated with lower HDL cholesterol and minority race/ethnicity in both groups; but with younger age, non-smoking, higher insulin resistance, and a diagnosis of schizoaffective disorder only among PwS, and with male sex, better cognitive functioning, and higher hs-CRP levels in NCs only.DiscussionHMW adiponectin may be a promising biomarker of cardiometabolic health, especially among PwS. Adiponectin is a potential target for lifestyle and pharmacological interventions. Research on the possible role of HMW adiponectin in modifying cardiometabolic pathology in schizophrenia is needed
Genetic network properties of the human cortex based on regional thickness and surface area measures
We examined network properties of genetic covariance between average cortical thickness (CT) and surface area (SA) within genetically-identified cortical parcellations that we previously derived from human cortical genetic maps using vertex-wise fuzzy clustering analysis with high spatial resolution. There were 24 hierarchical parcellations based on vertex-wise CT and 24 based on vertex-wise SA expansion/contraction; in both cases the 12 parcellations per hemisphere were largely symmetrical. We utilized three techniquesâbiometrical genetic modeling, cluster analysis, and graph theoryâto examine genetic relationships and network properties within and between the 48 parcellation measures. Biometrical modeling indicated significant shared genetic covariance between size of several of the genetic parcellations. Cluster analysis suggested small distinct groupings of genetic covariance; networks highlighted several significant negative and positive genetic correlations between bilateral parcellations. Graph theoretical analysis suggested that small world, but not rich club, network properties may characterize the genetic relationships between these regional size measures. These findings suggest that cortical genetic parcellations exhibit short characteristic path lengths across a broad network of connections. This property may be protective against network failure. In contrast, previous research with structural data has observed strong rich club properties with tightly interconnected hub networks. Future studies of these genetic networks might provide powerful phenotypes for genetic studies of normal and pathological brain development, aging, and function
Genetic Influences on Cortical Regionalization in the Human Brain
SummaryAnimal data demonstrate that the development of distinct cortical areas is influenced by genes that exhibit highly regionalized expression patterns. In this paper, we show genetic patterning of cortical surface area derived from MRI data from 406 adult human twins. We mapped genetic correlations of areal expansion between selected seed regions and all other cortical locations, with the selection of seed points based on results from animal studies. âMarching seedsâ and a data-driven, hypothesis-free, fuzzy-clustering approach provided convergent validation. The results reveal strong anterior-to-posterior graded, bilaterally symmetric patterns of regionalization, largely consistent with patterns previously reported in nonhuman mammalian models. Broad similarities in genetic patterning between rodents and humans might suggest a conservation of cortical patterning mechanisms, whereas dissimilarities might reflect the functionalities most essential to each species
Large-scale associations between the leukocyte transcriptome and BOLD responses to speech differ in autism early language outcome subtypes.
Heterogeneity in early language development in autism spectrum disorder (ASD) is clinically important and may reflect neurobiologically distinct subtypes. Here, we identified a large-scale association between multiple coordinated blood leukocyte gene coexpression modules and the multivariate functional neuroimaging (fMRI) response to speech. Gene coexpression modules associated with the multivariate fMRI response to speech were different for all pairwise comparisons between typically developing toddlers and toddlers with ASD and poor versus good early language outcome. Associated coexpression modules were enriched in genes that are broadly expressed in the brain and many other tissues. These coexpression modules were also enriched in ASD-associated, prenatal, human-specific, and language-relevant genes. This work highlights distinctive neurobiology in ASD subtypes with different early language outcomes that is present well before such outcomes are known. Associations between neuroimaging measures and gene expression levels in blood leukocytes may offer a unique in vivo window into identifying brain-relevant molecular mechanisms in ASD
Positive mental health in schizophrenia and healthy comparison groups: relationships with overall health and biomarkers
ObjectivePositive psychological factors (PPFs) have been reported to have a significant impact on health in the general population. However, little is known about the relationship of these factors with mental and physical health in schizophrenia.MethodOne hundred and thirty-five outpatients with schizophrenia and 127 healthy comparison subjects (HCs), aged 26-65 years, were evaluated with scales of resilience, optimism, happiness, and perceived stress. Measures of mental and physical health were also obtained. Regression analyses examined associations of a PPF composite with health variables.ResultsRelative to the HCs, the schizophrenia group had lower levels of PPFs. However, there was considerable heterogeneity, with over one-third of schizophrenia participants having values within the 'normative' range. The PPF composite was positively related to mental and physical health variables and with biomarkers of inflammation and insulin resistance. The relationship between PPFs and mental health was particularly strong for individuals with schizophrenia.ConclusionA sizable minority of adults with chronic schizophrenia have levels of resilience, optimism, happiness, and perceived stress similar to HCs. Psychosocial interventions to enhance PPFs should be tested in patients with serious mental illnesses, with the goal of improving their mental health (beyond controlling symptoms of psychosis) and their physical health
Essential data dimensions for prospective international data collection in older age bipolar disorder (OABD):Recommendations from the GAGE-BD group
Background: By 2030, over 50% of individuals living with bipolar disorder (BD) are expected to be aged â„50 years. However, older age bipolar disorder (OABD) remains understudied. There are limited large-scale prospectively collected data organized in key dimensions capable of addressing several fundamental questions about BD affecting this subgroup of patients.Methods: We developed initial recommendations for the essential dimensions for OABD data collection, based on (1) a systematic review of measures used in OABD studies, (2) a Delphi consensus of international OABD experts, (3) experience with harmonizing OABD data in the Global Aging & Geriatric Experiments in Bipolar Disorder Database (GAGE-BD, n ℠4500 participants), and (4) critical feedback from 34 global experts in geriatric mental health.Results: We identified 15 key dimensions and variables within each that are relevant for the investigation of OABD: (1) demographics, (2) core symptoms of depression and (3) mania, (4) cognition screening and subjective cognitive function, (5) elements for BD diagnosis, (6) descriptors of course of illness, (7) treatment, (8) suicidality, (9) current medication, (10) psychiatric comorbidity, (11) psychotic symptoms, (12) general medical comorbidities, (13) functioning, (14) family history, and (15) other. We also recommend particular instruments for capturing some of the dimensions and variables.Conclusion: The essential data dimensions we present should be of use to guide future international data collection in OABD and clinical practice. In the longer term, we aim to establish a prospective consortium using this core set of dimensions and associated variables to answer research questions relevant to OABD.</p
Essential data dimensions for prospective international data collection in older age bipolar disorder (OABD):Recommendations from the GAGE-BD group
Background: By 2030, over 50% of individuals living with bipolar disorder (BD) are expected to be aged â„50 years. However, older age bipolar disorder (OABD) remains understudied. There are limited large-scale prospectively collected data organized in key dimensions capable of addressing several fundamental questions about BD affecting this subgroup of patients.Methods: We developed initial recommendations for the essential dimensions for OABD data collection, based on (1) a systematic review of measures used in OABD studies, (2) a Delphi consensus of international OABD experts, (3) experience with harmonizing OABD data in the Global Aging & Geriatric Experiments in Bipolar Disorder Database (GAGE-BD, n ℠4500 participants), and (4) critical feedback from 34 global experts in geriatric mental health.Results: We identified 15 key dimensions and variables within each that are relevant for the investigation of OABD: (1) demographics, (2) core symptoms of depression and (3) mania, (4) cognition screening and subjective cognitive function, (5) elements for BD diagnosis, (6) descriptors of course of illness, (7) treatment, (8) suicidality, (9) current medication, (10) psychiatric comorbidity, (11) psychotic symptoms, (12) general medical comorbidities, (13) functioning, (14) family history, and (15) other. We also recommend particular instruments for capturing some of the dimensions and variables.Conclusion: The essential data dimensions we present should be of use to guide future international data collection in OABD and clinical practice. In the longer term, we aim to establish a prospective consortium using this core set of dimensions and associated variables to answer research questions relevant to OABD.</p
Brain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium
Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18-72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18-73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; Iâ=â57.53%) compared to controls, after adjusting for age, sex and site (Cohen's dâ=â0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions
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ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.
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
The International Consortium Investigating Neurocognition in Bipolar Disorder (ICONICĂą BD)
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148257/1/bdi12748.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148257/2/bdi12748_am.pd
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