Population modeling with machine learning can enhance measures of mental health

Background: Biological aging is revealed by physical measures, e.g., DNA probes or brain scans. In contrast, individual differences in mental function are explained by psychological constructs, e.g., intelligence or neuroticism. These constructs are typically assessed by tailored neuropsychological tests that build on expert judgement and require careful interpretation. Could machine learning on large samples from the general population be used to build proxy measures of these constructs that do not require human intervention? Results: Here, we built proxy measures by applying machine learning on multimodal MR images and rich sociodemographic information from the largest biomedical cohort to date: the UK Biobank. Objective model comparisons revealed that all proxies captured the target constructs and were as useful, and sometimes more useful, than the original measures for characterizing real-world health behavior (sleep, exercise, tobacco, alcohol consumption). We observed this complementarity of proxy measures and original measures at capturing multiple health-related constructs when modeling from, both, brain signals and sociodemographic data. Conclusion: Population modeling with machine learning can derive measures of mental health from heterogeneous inputs including brain signals and questionnaire data. This may complement or even substitute for psychometric assessments in clinical populations

Glial Cell Line-Derived Neurotrophic Factor and Developing Mammalian Motoneurons: Regulation of Programmed Cell Death Among Motoneuron Subtypes

Because of discrepancies in previous reports regarding the role of glial cell line-derived neurotrophic factor (GDNF) in motoneuron (MN) development and survival, we have reexamined MNs in GDNF-deficient mice and in mice exposed to increased GDNF afte

Disruption of Conscious Access in Psychosis Is Associated with Altered Structural Brain Connectivity

According to global neuronal workspace (GNW) theory, conscious access relies on long-distance cerebral connectivity to allow a global neuronal ignition coding for conscious content. In patients with schizophrenia and bipolar disorder, both alterations in cerebral connectivity and an increased threshold for conscious perception have been reported. The implications of abnormal structural connectivity for disrupted conscious access and the relationship between these two deficits and psychopathology remain unclear. The aim of this study was to determine the extent to which structural connectivity is correlated with consciousness threshold, particularly in psychosis. We used a visual masking paradigm to measure consciousness threshold, and diffusion MRI tractography to assess structural connectivity in 97 humans of either sex with varying degrees of psychosis: healthy control subjects (n = 46), schizophrenia patients (n = 25), and bipolar disorder patients with (n = 17) and without (n = 9) a history of psychosis. Patients with psychosis (schizophrenia and bipolar disorder with psychotic features) had an elevated masking threshold compared with control subjects and bipolar disorder patients without psychotic features. Masking threshold correlated negatively with the mean general fractional anisotropy of white matter tracts exclusively within the GNW network (inferior frontal-occipital fasciculus, cingulum, and corpus callosum). Mediation analysis demonstrated that alterations in long-distance connectivity were associated with an increased masking threshold, which in turn was linked to psychotic symptoms. Our findings support the hypothesis that long-distance structural connectivity within the GNW plays a crucial role in conscious access, and that conscious access may mediate the association between impaired structural connectivity and psychosis

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

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

Pigment epithelium-derived factor protects retinal ganglion cells

BACKGROUND: Retinal ganglion cells (RGCs) are responsible for the transmission of visual signals to the brain. Progressive death of RGCs occurs in glaucoma and several other retinal diseases, which can lead to visual impairment and blindness. Pigment epithelium-derived factor (PEDF) is a potent antiangiogenic, neurotrophic and neuroprotective protein that can protect neurons from a variety of pathologic insults. We tested the effects of PEDF on the survival of cultured adult rat RGCs in the presence of glaucoma-like insults, including cytotoxicity induced by glutamate or withdrawal of trophic factors. RESULTS: Cultured adult rat RGCs exposed to glutamate for 3 days showed signs of cytotoxicity and death. The toxic effect of glutamate was concentration-dependent (EC(50 )= 31 μM). In the presence of 100 μM glutamate, RGC number decreased to 55 ± 4% of control (mean ± SEM, n = 76; P < 0.001). The glutamate effect was completely eliminated by MK801, an NMDA receptor antagonist. Trophic factor withdrawal also caused a similar loss of RGCs (54 ± 4%, n = 60, P < 0.001). PEDF protected against both insults with EC(50 )values of 13.6 ng/mL (glutamate) and 3.4 ng/mL (trophic factor withdrawal), respectively. At 100 ng/mL, PEDF completely protected the cells from both insults. Inhibitors of the nuclear factor κB (NFκB) and extracellular signal-regulated kinases 1/2 (ERK1/2) significantly reduced the protective effects of PEDF. CONCLUSION: We demonstrated that PEDF potently and efficaciously protected adult rat RGCs from glutamate- and trophic factor withdrawal-mediated cytotoxicity, via the activation of the NFκB and ERK1/2 pathways. The neuroprotective effect of PEDF represents a novel approach for potential treatment of retinopathies, such as glaucoma

Abnormal left and right amygdala-orbitofrontal cortical functional connectivity to emotional faces:state versus trait vulnerability markers of depression in bipolar disorder

Background - Amygdala-orbitofrontal cortical (OFC) functional connectivity (FC) to emotional stimuli and relationships with white matter remain little examined in bipolar disorder individuals (BD). Methods - Thirty-one BD (type I; n = 17 remitted; n = 14 depressed) and 24 age- and gender-ratio-matched healthy individuals (HC) viewed neutral, mild, and intense happy or sad emotional faces in two experiments. The FC was computed as linear and nonlinear dependence measures between amygdala and OFC time series. Effects of group, laterality, and emotion intensity upon amygdala-OFC FC and amygdala-OFC FC white matter fractional anisotropy (FA) relationships were examined. Results - The BD versus HC showed significantly greater right amygdala-OFC FC (p = .001) in the sad experiment and significantly reduced bilateral amygdala-OFC FC (p = .007) in the happy experiment. Depressed but not remitted female BD versus female HC showed significantly greater left amygdala-OFC FC (p = .001) to all faces in the sad experiment and reduced bilateral amygdala-OFC FC to intense happy faces (p = .01). There was a significant nonlinear relationship (p = .001) between left amygdala-OFC FC to sad faces and FA in HC. In BD, antidepressants were associated with significantly reduced left amygdala-OFC FC to mild sad faces (p = .001). Conclusions - In BD, abnormally elevated right amygdala-OFC FC to sad stimuli might represent a trait vulnerability for depression, whereas abnormally elevated left amygdala-OFC FC to sad stimuli and abnormally reduced amygdala-OFC FC to intense happy stimuli might represent a depression state marker. Abnormal FC measures might normalize with antidepressant medications in BD. Nonlinear amygdala-OFC FC–FA relationships in BD and HC require further study

AAV-mediated human PEDF inhibits tumor growth and metastasis in murine colorectal peritoneal carcinomatosis model

<p>Abstract</p> <p>Background</p> <p>Angiogenesis plays an important role in tumor growth and metastasis, therefore antiangiogenic therapy was widely investigated as a promising approach for cancer therapy. Recently, pigment epithelium-derived factor (PEDF) has been shown to be the most potent inhibitor of angiogenesis. Adeno-associated virus (AAV) vectors have been intensively studied due to their wide tropisms, nonpathogenicity, and long-term transgene expression <it>in vivo</it>. The objective of this work was to evaluate the ability of AAV-mediated human PEDF (hPEDF) as a potent tumor suppressor and a potential candidate for cancer gene therapy.</p> <p>Methods</p> <p>Recombinant AAV₂encoding hPEDF (rAAV₂-hPEDF) was constructed and produced, and then was assigned for <it>in vitro </it>and <it>in vivo </it>experiments. Conditioned medium from cells infected with rAAV₂-hPEDF was used for cell proliferation and tube formation tests of human umbilical vein endothelial cells (HUVECs). Subsequently, colorectal peritoneal carcinomatosis (CRPC) mouse model was established and treated with rAAV₂-hPEDF. Therapeutic efficacy of rAAV₂-hPEDF were investigated, including tumor growth and metastasis, survival time, microvessel density (MVD) and apoptosis index of tumor tissues, and hPEDF levels in serum and ascites.</p> <p>Results</p> <p>rAAV₂-hPEDF was successfully constructed, and transmission electron microscope (TEM) showed that rAAV₂-hPEDF particles were non-enveloped icosahedral shape with a diameter of approximately 20 nm. rAAV₂-hPEDF-infected cells expressed hPEDF protein, and the conditioned medium from infected cells inhibited proliferation and tube-formation of HUVECs <it>in vitro</it>. Furthermore, in CRPC mouse model, rAAV₂-hPEDF significantly suppressed tumor growth and metastasis, and prolonged survival time of treated mice. Immunofluorescence studies indicated that rAAV₂-hPEDF could inhibit angiogenesis and induce apoptosis in tumor tissues. Besides, hPEDF levels in serum and ascites of rAAV₂-hPEDF-treated mice were significant higher than those in rAAV₂-null or normal saline (NS) groups.</p> <p>Conclusions</p> <p>Thus, our results suggest that rAAV₂-hPEDF may be a potential candidate as an antiangiogenic therapy agent.</p

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

First published: 29 July 2020MRI-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.Christopher R. K. Ching .... Bernhard T. Baune ... et al

ENIGMA-Sleep:Challenges, opportunities, and the road map

Neuroimaging and genetics studies have advanced our understanding of the neurobiology of sleep and its disorders. However, individual studies usually have limitations to identifying consistent and reproducible effects, including modest sample sizes, heterogeneous clinical characteristics and varied methodologies. These issues call for a large-scale multi-centre effort in sleep research, in order to increase the number of samples, and harmonize the methods of data collection, preprocessing and analysis using pre-registered well-established protocols. The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium provides a powerful collaborative framework for combining datasets across individual sites. Recently, we have launched the ENIGMA-Sleep working group with the collaboration of several institutes from 15 countries to perform large-scale worldwide neuroimaging and genetics studies for better understanding the neurobiology of impaired sleep quality in population-based healthy individuals, the neural consequences of sleep deprivation, pathophysiology of sleep disorders, as well as neural correlates of sleep disturbances across various neuropsychiatric disorders. In this introductory review, we describe the details of our currently available datasets and our ongoing projects in the ENIGMA-Sleep group, and discuss both the potential challenges and opportunities of a collaborative initiative in sleep medicine