Search

Low-dose testosterone has been shown to improve depression symptom severity, fatigue, and sexual function in small studies in women not formally diagnosed with major depressive disorder. The authors sought to determine whether adjunctive low-dose transdermal testosterone improves depression symptom severity, fatigue, and sexual function in women with antidepressant-resistant major depression. A functional MRI (fMRI) substudy examined effects on activity in the anterior cingulate cortex (ACC), a brain region important in mood regulation.The authors conducted an 8-week randomized double-blind placebo-controlled trial of adjunctive testosterone cream in 101 women, ages 21-70, with antidepressant-resistant major depression. The primary outcome measure was depression symptom severity as assessed by the Montgomery-Åsberg Depression Rating Scale (MADRS). Secondary endpoints included fatigue, sexual function, and safety measures. The primary outcome of the fMRI substudy (N=20) was change in ACC activity.The participants' mean age was 47 years (SD=14) and their mean baseline MADRS score was 26.6 (SD=5.9). Eighty-seven (86%) participants completed 8 weeks of treatment. MADRS scores decreased in both study arms from baseline to week 8 (testosterone arm: from 26.8 [SD=6.3] to 15.3 [SD=9.6]; placebo arm: from 26.3 [SD=5.4] to 14.4 [SD=9.3]), with no significant difference between groups. Improvement in fatigue and sexual function did not differ between groups, nor did side effects. fMRI results showed a relationship between ACC activation and androgen levels before treatment but no difference in ACC activation with testosterone compared with placebo.Adjunctive transdermal testosterone, although well tolerated, was not more effective than placebo in improving symptoms of depression, fatigue, or sexual dysfunction. Imaging in a subset of participants demonstrated that testosterone did not result in greater activation of the ACC.

BACKGROUND Neurovascular abnormalities are relevant to the pathophysiology of bipolar disorder (BD), which can be assessed using cerebral blood flow (CBF) imaging. CBF alterations have been identified in BD, but studies to date have been small and inconclusive. We aimed to determine cortical gray matter CBF (GM-CBF) differences between BD and healthy controls (HC) and to identify relationships between CBF and clinical or cognitive measures. METHODS Cortical GM-CBF maps were generated using Pseudo-Continuous Arterial Spin Labeling (pCASL) for 109 participants (BD, n = 61; HC, n = 48). We used SnPM13 to perform non-parametric voxel-wise two-sample t-tests comparing CBF between groups. We performed multiple linear regression to relate GM-CBF with clinical and cognitive measures. Analysis was adjusted for multiple comparisons with 10,000 permutations. Significance was set at a voxel level threshold of P

The brain is the seat of body weight homeostasis. However, our inability to control the increasing prevalence of obesity highlights a need to look beyond canonical feeding pathways to broaden our understanding of body weight control1–3. Here we used a reverse-translational approach to identify and anatomically, molecularly and functionally characterize a neural ensemble that promotes satiation. Unbiased, task-based functional magnetic resonance imaging revealed marked differences in cerebellar responses to food in people with a genetic disorder characterized by insatiable appetite. Transcriptomic analyses in mice revealed molecularly and topographically -distinct neurons in the anterior deep cerebellar nuclei (aDCN) that are activated by feeding or nutrient infusion in the gut. Selective activation of aDCN neurons substantially decreased food intake by reducing meal size without compensatory changes to metabolic rate. We found that aDCN activity terminates food intake by increasing striatal dopamine levels and attenuating the phasic dopamine response to subsequent food consumption. Our study defines a conserved satiation centre that may represent a novel therapeutic target for the management of excessive eating, and underscores the utility of a ‘bedside-to-bench’ approach for the identification of neural circuits that influence behaviour. Activity in anterior deep cerebellar nuclei reduces food consumption in mice without reducing metabolic rate, potentially identifying a therapeutic target for disorders involving excessive eating.

The early stage of psychosis (ESP) is a critical period where effective intervention has the most favorable impact on outcomes. Thalamic connectivity abnormalities have been consistently found in psychosis, and are associated with clinical symptoms and cognitive deficits. However, most studies consider ESP patients as a homogeneous population and fail to take the duration of illness into account. In this study, we aimed to capture the progression of thalamic connectivity changes over the first five years of psychosis. Resting-state functional MRI scans were collected from 156 ESP patients (44 with longitudinal data) and 82 healthy controls (24 with longitudinal data). We first performed a case-control analysis comparing thalamic connectivity with 13 networks in the cortex and cerebellum. Next, we modelled the shape (flat, linear, curvilinear) of thalamic connectivity trajectories by comparing flexible non-linear versus linear models. We then tested the significance of the duration of illness and diagnosis in trajectories that changed over time. Connectivity changed over the ESP period between the thalamus and default mode network (DMN) and fronto-parietal network (FPN) nodes in both the cortex and cerebellum. Three models followed a curvilinear trajectory (early increase followed by a subsequent decrease), while thalamo-cerebellar FPN connectivity followed a linear trajectory of steady reductions over time, indicating different rates of change. Finally, diagnosis significantly predicted thalamic connectivity. Thalamo-cortical and thalamo-cerebellar connectivity change in a dynamic fashion during the ESP period. A better understanding of these changes may provide insights into the compensatory and progressive changes in functional connectivity in the early stages of illness.

OBJECTIVE: The interpretability of results in psychiatric neuroimaging is significantly limited by an overreliance on correlational relationships. Purely correlational studies cannot alone determine if behavior-imaging relationships are causal to illness, functionally compensatory processes, or purely epiphenomena. Here we take a two-step approach to identifying and then empirically testing a brain network model of schizophrenia symptoms. Negative symptoms (e.g. anhedonia, amotivation, and expressive deficits) are refractory to current medications and are one of the foremost causes of disability in this illness. METHOD: We used two-stage method: In the first cohort (n=44), we used a data-driven resting state functional connectivity analysis to identify a network whose connectivity corresponds to negative symptom severity. Then in a second cohort (n=11) we modulated this network connectivity with 5 days of twice daily transcranial magnetic stimulation to the cerebellar midline (vermis VIIb). RESULTS: A breakdown of connectivity in a specific dorsolateral prefrontal cortex to cerebellum network directly corresponds to negative symptom severity. Restoration of network connectivity with TMS corresponds to amelioration of negative symptoms, showing a strong relationship of functional connectivity change to negative symptom change (r=0.809,p=0003). CONCLUSION: Our results demonstrate that a connectivity breakdown between the cerebellum and right dorsolateral prefrontal cortex is associated with negative symptom severity and that correction of this breakdown ameliorates negative symptom severity. Our results support a novel network hypothesis for medication refractory negative symptoms and indicates network manipulation may establish causal relationships between network markers and clinical phenomena.

Background Neuroimaging of psychiatric disease is challenged by the difficulty of establishing the causal role of neuroimaging abnormalities. Lesions that cause mania present a unique opportunity to understand how brain network disruption may cause mania in both lesions and in bipolar disorder. Methods A literature search revealed 23 case reports with imaged lesions that caused mania in patients without history of bipolar disorder. We traced these lesions and examined resting-state functional Magnetic Resonance Imaging (rsfMRI) connectivity to these lesions and control lesions to find networks that would be disrupted specifically by mania-causing lesions. The results were then used as regions-of-interest to examine rsfMRI connectivity in patients with bipolar disorder (n = 16) who underwent imaging longitudinally across states of both mania and euthymia alongside a cohort of healthy participants scanned longitudinally. We then sought to replicate these results in independent cohorts of manic (n = 26) and euthymic (n = 21) participants with bipolar disorder. Results Mania-inducing lesions overlap significantly in network connectivity. Mania-causing lesions selectively disrupt networks that include orbitofrontal cortex, dorsolateral prefrontal cortex, and temporal lobes. In bipolar disorder, the manic state was reflected in strong, significant, and specific disruption in network communication between these regions and regions implicated in bipolar pathophysiology: the amygdala and ventro-lateral prefrontal cortex. Limitations There was heterogeneity in the clinical characterization of mania causing lesions. Conclusions Lesions causing mania demonstrate shared and specific network disruptions. These disruptions are also observed in bipolar mania and suggest a convergence of multiple disorders on shared circuit dysfunction to cause mania.

Instead of matching neuroimaging to static clinical targets, it is currently possible to use dynamic biobehavioral markers of cognition, functioning, behavior, and symptoms captured through a person’s smartphone. This paper reviews the published literature linking neuroimaging and smartphone data to understand the feasibility, methods, and potential of using smartphone sensing (often called digital phenotyping) as a target for neuroimaging. On June 30, 2020, a literature search was conducted on PubMed and PsycINFO for studies utilizing neuroimaging and smartphones tools. We excluded EEG focused studies, conference proceedings and abstracts. A snowball approach was applied to further locate papers. We utilized the NIMH’s Research Domain Criteria (RDoC) framework to organize results. 262 publications uncovered by the search were screened, and 14 papers were included in the final analysis. All studies differed in terms of the type of data collected from smartphones, type of neuroimaging used, areas of the brain measured, and population studied. The average duration before or after neuroimaging and smartphone assessments was 39 days. While it was not possible to directly compare studies, a majority of the included reports were classified under the Negative Valence Systems category in the RDoC framework. All studies reported statistically significant relationships between the information collected via the digital tool and the brain scans, and support feasibility of this method. The current literature connecting smartphone data and neuroimaging is nascent but holds the potential to better understand the ability of digital tools to inform brain structure and/or function. Although the protocols and studies from this search were heterogenous, results suggest feasibility and practicality of this work.

Psychiatric neuroimaging has had limited impact on the clinical care of psychiatric disorders. Despite decades of discoveries of abnormalities in brain circuits, neuroimaging findings have not translated into clinical application. Some have proposed the solution to this problem is larger samples and increasing amounts of imaging data per individual. We believe that these proposals are unlikely to close the translational gap between the bench and the bedside because they continue to rely on purely observational correlations between biology and phenotype. Because these studies never test the causality of these correlations, these approaches are unlikely to lead to a clinically-actionable result. We propose that observed imaging findings should be probed directly to determine if they are causally linked to clinical phenotypes and therefore targets for therapeutic engagement. In this Disruptive Innovation, we provide an example of how perturbing circuit-phenotype relationships can identify and validate circuit targets for both clinical intervention as well as generating models of pathophysiology. This approach can be readily implemented, as these technologies are mature and widely available, and there exist empirically-derived targets that can be tested. All that is needed is to change our mindset to test the validity of identified brain signals rather than generating ever more of them.

BackgroundThe ability to manage emotions is an important social-cognitive domain impaired in schizophrenia and linked to functional outcome. The goal of our study was to examine the impact of cognitive enhancement therapy (CET) on the ability to manage emotions and brain functional connectivity in early-course schizophrenia.MethodsParticipants were randomly assigned to CET (n = 55) or an enriched supportive therapy (EST) control group (n = 45). The resting-state functional magnetic resonance imaging scans and measures of emotion management performances were collected at baseline, 9, and 18 months follow-up. The final sample consisted of 37 CET and 25 EST participants, including 19 CET and 12 EST participants with imaging data. Linear mixed-effects models investigated the impact of treatment on emotion management and functional connectivity from the amygdala to ventrolateral and dorsolateral prefrontal cortex (dlPFC).ResultsThe CET group showed significant improvement over time in emotion management compared to EST. Neither functional connectivity changes nor main group differences were observed following treatment. However, a significant between-group interaction showed that improved emotion management ability was associated with increased functional connectivity between the left amygdala and the left dlPFC in the CET group exclusively.ConclusionOur results replicate the previous work demonstrating that CET is effective at improving some aspects of social cognition in schizophrenia. We found evidence that improvement in emotion management may be associated with a change in amygdala-dlPFC connectivity. This fronto-limbic circuit may provide a mechanistic link between the biology of emotion management processes that can be enhanced in individuals with schizophrenia.

Background: Psychotic disorders are characterized by impairment in social cognitive processing, which is associated with poorer community functioning. However, the neural mechanisms of social impairment in psychosis remain unclear. Social impairment is a hallmark of other psychiatric illnesses as well, including autism spectrum disorders (ASD), and the nature and degree of social cognitive impairments across psychotic disorders and ASD are similar, suggesting that mechanisms that are known to underpin social impairments in ASD may also play a role in the impairments seen in psychosis. Specifically, in both humans and animal models of ASD, a cerebellar-parietal network has been identified that is directly related to social cognition and social functioning. In this study we examined social cognition and resting-state brain connectivity in people with psychosis and in neurotypical adults. We hypothesized that social cognition would be most strongly associated with cerebellar-parietal connectivity, even when using a whole-brain data driven approach. Methods: We examined associations between brain connectivity and social cognition in a trans-diagnostic sample of people with psychosis (n = 81) and neurotypical controls (n = 45). Social cognition was assessed using the social cognition domain score of the MATRICS Consensus Cognitive Battery. We used a multivariate pattern analysis to correlate social cognition with resting-state functional connectivity at the individual voxel level. Results: This approach identified a circuit between right cerebellar Crus I, II and left parietal cortex as the strongest correlate of social cognitive performance. This connectivity-cognition result was observed in both people with psychotic disorders and in neurotypical adults. Conclusions: Using a data-driven whole brain approach we identified a cerebellar-parietal circuit that was robustly associated with social cognitive ability, consistent with findings from people with ASD and animal models. These findings suggest that this circuit may be marker of social cognitive impairment trans-diagnostically and support cerebellar-parietal connectivity as a potential therapeutic target for enhancing social cognition.

Resting-state fMRI (rsfMRI) demonstrates that the brain is organized into distributed networks. Numerous studies have examined links between psychiatric symptomatology and network functional connectivity. Traditional rsfMRI analyses assume that the spatial organization of networks is invariant between individuals. This dogma has recently been overturned by the demonstration that networks show significant variation between individuals. We tested the hypothesis that previously observed relationships between schizophrenia-negative symptom severity and network connectivity are actually due to individual differences in network spatial organization. Forty-four participants diagnosed with schizophrenia underwent rsfMRI scans and clinical assessments. A multivariate pattern analysis determined how whole-brain functional connectivity correlates with negative symptom severity at the individual voxel level. Brain connectivity to a region of the right dorsolateral prefrontal cortex correlates with negative symptom severity. This finding results from individual differences in the topographic distribution of 2 networks: the default mode network (DMN) and the task-positive network (TPN). Both networks demonstrate strong (r = ~0.49) and significant (P < .001) relationships between topography and symptom severity. For individuals with low symptom severity, this critical region is part of the DMN. In highly symptomatic individuals, this region is part of the TPN. Previously overlooked individual variation in brain organization is tightly linked to differences in schizophrenia symptom severity. Recognizing critical links between network topography and pathological symptomology may identify key circuits that underlie cognitive and behavioral phenotypes. Individual variation in network topography likely guides different responses to clinical interventions that rely on anatomical targeting (eg, transcranial magnetic stimulation [TMS]).

Objective: Nonresponse to selective serotonin reuptake inhibitor and serotonin norepinephrine reuptake inhibitor treatment is common in patients with major depressive disorder (MDD), particularly in women, occurring in about 70% of patients despite adequate dosing. Well-tolerated augmentation strategies are needed, particularly ones that do not cause or exacerbate symptoms such as fatigue and sexual dysfunction. Low-dose testosterone has been shown to improve depression symptom severity, fatigue and sexual function in small studies of women not formally diagnosed with MDD. We sought to determine whether adjunctive low-dose transdermal testosterone improves depression symptom severity, fatigue, and sexual function in women with treatment-resistant MDD. A functional MRI (fMRI) substudy examined effects of testosterone on activity in the anterior cingulate cortex (ACC), a brain region important in mood regulation. Methods: Randomized, double-blind, placebo-controlled, 8-week trial of adjunctive testosterone cream (AndroFeme® 1, Lawley Pharmaceuticals, Australia) in 101 women, ages 21–70, with treatment-resistant MDD. Testosterone was titrated to achieve blood levels near the upper normal reference limit. Primary outcome measure was depression severity by Montgomery-Asberg Depression Rating Scale (MADRS). Secondary endpoints included fatigue, sexual function, and safety measures. fMRI substudy (n=20) primary outcome was change in ACC activity. Results: Mean age was 47±14 (SD) years and mean baseline MADRS score was 26.6±5.9. Eighty-seven (86%) participants completed 8 weeks of treatment. MADRS depression scores decreased in both arms [testosterone: 26.8±6.3 to 15.3±9.6; placebo: 26.3±5.4 to 14.4±9.3 (baseline to 8 weeks, respectively)], with no difference between groups (p=0.91). Fatigue and sexual function improved without differences between groups. There were no group differences in side effects. fMRI results demonstrated a relationship between ACC activation and androgen levels pretreatment but no difference in ACC activation with treatment. Conclusions: This rigorously designed, double-blinded clinical trial did not find significant group differences between adjunctive low dose transdermal testosterone and placebo for antidepressant augmentation in women with treatment-resistant MDD and had a high placebo response rate. Low-dose testosterone was well tolerated but failed to differentially impact overall depressive symptom severity, fatigue, or sexual dysfunction. Testosterone did not result in greater activity in a brain region (ACC) implicated in MDD etiopathology compared to placebo. Thus, the addition of low-dose testosterone to ineffective antidepressant treatment should not be recommended for women with MDD. Further studies using strategies designed to reduce placebo effects may be warranted.

Neuroimaging studies of psychotic disorders have demonstrated abnormalities in structural and functional connectivity involving widespread brain networks. However, these group-level observations have failed to yield any biomarkers that can provide confirmatory evidence of a patient's current symptoms, predict future symptoms, or predict a treatment response. Lack of precision in both neuroanatomical and clinical boundaries have likely contributed to the inability of even well-powered studies to resolve these key relationships. Here, we employed a novel approach to defining individual-specific functional connectivity in 158 patients diagnosed with schizophrenia (n = 49), schizoaffective disorder (n = 37), or bipolar disorder with psychosis (n = 72), and identified neuroimaging features that track psychotic symptoms in a dimension- or disorder-specific fashion. Using individually specified functional connectivity, we were able to estimate positive, negative, and manic symptoms that showed correlations ranging from r = 0.35 to r = 0.51 with the observed symptom scores. Comparing optimized estimation models among schizophrenia spectrum patients, positive and negative symptoms were associated with largely non-overlapping sets of cortical connections. Comparing between schizophrenia spectrum and bipolar disorder patients, the models for positive symptoms were largely non-overlapping between the two disorder classes. Finally, models derived using conventional region definition strategies performed at chance levels for most symptom domains. Individual-specific functional connectivity analyses revealed important new distinctions among cortical circuits responsible for the positive and negative symptoms, as well as key new information about how circuits underlying symptom expressions may vary depending on the underlying etiology and illness syndrome from which they manifest.

Purpose Rosenblat and McIntyre (Acta Psychiatr Scand. 2015;132: 180-191) propose that immune disorders are important mediators between bipolar disorders and medical comorbidities. Rosenblat et al (Bipolar Disord. 2016;18:89-101) present a meta-analysis showing that adjunctive anti-inflammatory agents could evoke moderate antidepressant responses in bipolar disorders. We propose using the anti-inflammatory drug colchicine to improve the long-term safety and efficacy of lithium treatment for bipolar disorders. Methods This report is based on searches of the PubMed and Web of Science databases. Results Bipolar disorders are associated with significant medical comorbidities such as hypertension, overweight/obesity, diabetes mellitus, metabolic syndrome, and arteriosclerosis, accompanied by enhanced release of pro-inflammatory markers during changes in mood state. During lithium therapy, granulocyte-colony stimulating factor, CD34+ hematopoietic stem/progenitor cells, and neutrophil elastase enter the circulation with activated neutrophils to promote the extravascular migration of activated neutrophils and enhance tissue inflammation. Concurrent treatment with lithium and low-dose colchicine could facilitate the responsiveness of bipolar patients to lithium by reducing leukocyte tissue emigration, the release of neutrophil elastase, and the release of leukocyte pro-inflammatory cytokines such as IL-1β that are regulated by the NLRP3 inflammasome assembly complex. Conclusions Concurrent therapy with lithium and low-dose colchicine could reduce complications involving leukocyte-mediated inflammatory states in bipolar patients and promote patient acceptance and responsiveness to lithium therapy.

Background Using resting-state functional magnetic resonance imaging (rsfMRI), we previously compared cohorts of bipolar I subjects in a manic state to those in a euthymic state to identify mood state-specific patterns of cortico-amygdala connectivity. Our results suggested that mania is reflected in the disruption of emotion regulation circuits. We sought to replicate this finding in a group of subjects with bipolar disorder imaged longitudinally across states of mania and euthymia Methods We divided our subjects into three groups: 26 subjects imaged in a manic state, 21 subjects imaged in a euthymic state, and 10 subjects imaged longitudinally across both mood states. We measured differences in amygdala connectivity between the mania and euthymia cohorts. We then used these regions of altered connectivity to examine connectivity in the longitudinal bipolar group using a within-subjects design. Results Our findings in the mania vs euthymia cohort comparison were replicated in the longitudinal analysis. Bipolar mania was differentiated from euthymia by decreased connectivity between the amygdala and pre-genual anterior cingulate cortex. Mania was also characterized by increased connectivity between amygdala and the supplemental motor area, a region normally anti-correlated to the amygdala in emotion regulation tasks. Limitations Stringent controls for movement effects limited the number of subjects in the longitudinal sample. Conclusions In this first report of rsfMRI conducted longitudinally across mood states, we find that previously observed between-group differences in amygdala connectivity are also found longitudinally within subjects. These results suggest resting state cortico-amygdala connectivity is a biomarker of mood state in bipolar disorder.

Background The adaptability of the human brain to the constantly changing environment is reduced in patients with psychotic disorders, leading to impaired cognitive functions. Brain signal complexity, which may reflect adaptability, can be readily quantified via resting-state functional magnetic resonance imaging (fMRI) signals. We hypothesized that resting-state brain signal complexity is altered in psychotic disorders, and is correlated with cognitive impairment. Methods We assessed 156 healthy controls (HC) and 330 probands, including 125 patients with psychotic bipolar disorder (BP), 107 patients with schizophrenia (SZ), 98 patients with schizoaffective disorder (SAD) and 230 of their unaffected first-degree relatives (76 BPR, 79 SADR, and 75 SZR) from four sites of the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium. Using multi-scale entropy analysis, we determined whether patients and/or relatives had pathologic differences in complexity of resting-state fMRI signals toward regularity (reduced entropy in all time scales), or toward uncorrelated randomness (increased entropy in fine time scales that decays as the time scale increases) and how these complexity differences might be associated with cognitive impairment. Results Compared to HC subjects, proband groups showed either decreased complexity toward regularity or toward randomness. SZ probands showed decreased complexity toward regular signal in hypothalamus, and BP probands in left inferior occipital, right precentral and left superior parietal regions, whereas no brain region with decreased complexity toward regularity was found in SAD probands. All proband groups showed significantly increased brain signal randomness in dorsal and ventral prefrontal cortex (PFC), and unaffected relatives showed no complexity differences in PFC regions. SZ had the largest area of involvement in both dorsal and ventral PFC. BP and SAD probands shared increased brain signal randomness in ventral medial PFC, BP and SZ probands shared increased brain signal randomness in ventral lateral PFC, whereas SAD and SZ probands shared increased brain signal randomness in dorsal medial PFC. Only SZ showed increased brain signal randomness in dorsal lateral PFC. The increased brain signal randomness in dorsal or ventral PFC was weakly associated with reduced cognitive performance in psychotic probands. Conclusion These observations support the loss of brain complexity hypothesis in psychotic probands. Furthermore, we found significant differences as well as overlaps of pathologic brain signal complexity between psychotic probands by DSM diagnoses, thus suggesting a biological approach to categorizing psychosis based on functional neuroimaging data.

// Chao Zhang 1,2,* , Chunzhang Yang 3,* , Michael J. Feldman 4 , Herui Wang 4 , Ying Pang 2 , Dominic M. Maggio 4 , Dongwang Zhu 4 , Cody L. Nesvick 4 , Pauline Dmitriev 4 , Petra Bullova 2,5 , Prashant Chittiboina 4 , Roscoe O. Brady 4 , Karel Pacak 2 and Zhengping Zhuang 4 1 Department of Orthopedics, Xinqiao Hospital, The Third Military Medical University, Chongqing, China 2 Program in Reproductive and Adult Endocrinology, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland, USA 3 Neuro-Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA 4 Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA 5 Department of Molecular Medicine, Institute of Virology, Slovak Academy of Sciences, Bratislava, Slovakia * These authors have contributed equally to this work Correspondence to: Karel Pacak, email: // Zhengping Zhuang, email: // Keywords : HDACi, Hsp90, SAHA, HIF, hypoxia Received : December 14, 2016 Accepted : April 10, 2017 Published : May 23, 2017 Abstract Histone deacetylase inhibitors (HDACis) are a potent class of tumor-suppressive agents traditionally believed to exert their effects through loosening tightly-wound chromatin resulting in de-inhibition of various tumor suppressive genes. Recent literature however has shown altered intratumoral hypoxia signaling with HDACi administration not attributable to changes in chromatin structure. We sought to determine the precise mechanism of HDACi-mediated hypoxia signaling attenuation using vorinostat (SAHA), an FDA-approved class I/IIb/IV HDACi. Through an in-vitro and in-vivo approach utilizing cell lines for hepatocellular carcinoma (HCC), osteosarcoma (OS), and glioblastoma (GBM), we demonstrate that SAHA potently inhibits HIF-a nuclear translocation via direct acetylation of its associated chaperone, heat shock protein 90 (Hsp90). In the presence of SAHA we found elevated levels of acetyl-Hsp90, decreased interaction between acetyl-Hsp90 and HIF-a, decreased nuclear/cytoplasmic HIF-α expression, absent HIF-α association with its nuclear karyopharyin Importin, and markedly decreased HIF-a transcriptional activity. These changes were associated with downregulation of downstream hypoxia molecules such as endothelin 1, erythropoietin, glucose transporter 1, and vascular endothelial growth factor. Findings were replicated in an in-vivo Hep3B HRE-Luc expressing xenograft, and were associated with significant decreases in xenograft tumor size. Altogether, this study highlights a novel mechanism of action of an important class of chemotherapeutic.

Subtypes of schizophrenia, constructed using clinical phenomenology to resolve illness heterogeneity, have faced criticism due to overlapping symptomatology and longitudinal instability; they were therefore dropped from the Diagnostic Statistical Manual-5. Cognitive and imaging findings comparing paranoid (P-SZ) and non-paranoid (disorganized, residual and undifferentiated; NP-SZ) schizophrenia have been limited due to small sample sizes. We assessed P-SZ and NP-SZ using symptomatology, cognition and brain structure and predicted that there would be few neurobiological differences. P-SZ (n = 237), NP-SZ (n = 127) and controls (n = 430) were included from a multi-site study. In a subset of this sample, structural imaging measures (P-SZ, n = 133; NP-SZ, n = 67; controls, n = 310) were calculated using Freesurfer 6.0. Group contrasts were run using analysis of covariance, controlling for age, sex, race and site, p-values were corrected using False Discovery Rate (FDR) and were repeated excluding the residual subtype. Compared to NP-SZ (with and without the residual subtype), P-SZ displayed fewer negative symptoms, faster speed of processing, larger bilateral hippocampus, right amygdala and their subfield volumes. Additionally, NP-SZ (with residual subtype) displayed fewer depressive symptoms and higher left transverse temporal cortical thickness (CT) but NP-SZ without residual subtype showed lower GAF scores and worse digit sequencing compared to P-SZ. No differences in positive symptoms and functioning (global or social) were detected. Subtle but significant differences were seen in cognition, symptoms, CT and subcortical volumes between P-SZ and NP-SZ. While the magnitude of these differences is not large enough to justify them as distinct categories, the paranoid- nonparanoid distinction in schizophrenia merits further investigation.

Significance Historically, most research on the biological origins of psychiatric illness has focused on individual diagnostic categories, studied in isolation. Mounting evidence indicates that nominally distinct psychiatric diagnoses are not separated by clear neurobiological boundaries. Here, we derive functional connectomic signatures in over 1,000 individuals, including patients presenting with different categories of impairment (psychosis), clinical diagnoses, and severity of illness as reflected in treatment seeking. Our analyses reveal features of connectome functioning that are commonly disrupted across distinct forms of pathology, scaling with clinical severity. Conversely, other aspects of network connectivity were preferentially disrupted in patients with psychotic illness. These data have important implications for the establishment of functional connectome fingerprints of severe mental disease., Converging evidence indicates that groups of patients with nominally distinct psychiatric diagnoses are not separated by sharp or discontinuous neurobiological boundaries. In healthy populations, individual differences in behavior are reflected in variability across the collective set of functional brain connections (functional connectome). These data suggest that the spectra of transdiagnostic symptom profiles observed in psychiatric patients may map onto detectable patterns of network function. To examine the manner through which neurobiological variation might underlie clinical presentation, we obtained fMRI data from over 1,000 individuals, including 210 diagnosed with a primary psychotic disorder or affective psychosis (bipolar disorder with psychosis and schizophrenia or schizoaffective disorder), 192 presenting with a primary affective disorder without psychosis (unipolar depression, bipolar disorder without psychosis), and 608 demographically matched healthy comparison participants recruited through a large-scale study of brain imaging and genetics. Here, we examine variation in functional connectomes across psychiatric diagnoses, finding striking evidence for disease connectomic “fingerprints” that are commonly disrupted across distinct forms of pathology and appear to scale as a function of illness severity. The presence of affective and psychotic illnesses was associated with graded disruptions in frontoparietal network connectivity (encompassing aspects of dorsolateral prefrontal, dorsomedial prefrontal, lateral parietal, and posterior temporal cortices). Conversely, other properties of network connectivity, including default network integrity, were preferentially disrupted in patients with psychotic illness, but not patients without psychotic symptoms. This work allows us to establish key biological and clinical features of the functional connectomes of severe mental disease.

Fabry disease is a glycosphingolipid storage disorder that is caused by a genetic deficiency of the enzyme alpha-galactosidase A (AGA, EC 3.2.1.22). It is a multisystem disease that affects the vascular, cardiac, renal, and nervous systems. One of the hallmarks of this disorder is neuropathic pain and sympathetic and parasympathetic nervous dysfunction. The exact mechanism by which changes in AGA activity result in change in neuronal function is not clear, partly due to of a lack of relevant model systems. In this study, we report the development of an in vitro model system to study neuronal dysfunction in Fabry disease by using short-hairpin RNA to create a stable knock-down of AGA in the human cholinergic neuronal cell line, LA-N-2. We show that gene-silenced cells show specifically reduced AGA activity and store globotriaosylceramide. In gene-silenced cells, release of the neurotransmitter acetylcholine is significantly reduced, demonstrating that this model may be used to study specific neuronal functions such as neurotransmitter release in Fabry disease.

Niemann-Pick disease type A (NPA)-induced pluripotent stem cells from patient dermal fibroblasts were differentiated into neural stem cells. By using the differentiated NPA neuronal cells as a cell-based disease model system, α-tocopherol, δ-tocopherol, and hydroxypropyl-β-cyclodextrin significantly reduced sphingomyelin accumulation in these NPA neuronal cells. This cell-based NPA model can be used for further study of disease pathophysiology and for high-throughput screening of compound libraries to identify lead compounds for drug development., Niemann-Pick disease type A (NPA) is a lysosomal storage disease caused by mutations in the SMPD1 gene that encodes acid sphingomyelinase (ASM). Deficiency in ASM function results in lysosomal accumulation of sphingomyelin and neurodegeneration. Currently, there is no effective treatment for NPA. To accelerate drug discovery for treatment of NPA, we generated induced pluripotent stem cells from two patient dermal fibroblast lines and differentiated them into neural stem cells. The NPA neural stem cells exhibit a disease phenotype of lysosomal sphingomyelin accumulation and enlarged lysosomes. By using this disease model, we also evaluated three compounds that reportedly reduced lysosomal lipid accumulation in Niemann-Pick disease type C as well as enzyme replacement therapy with ASM. We found that α-tocopherol, δ-tocopherol, hydroxypropyl-β-cyclodextrin, and ASM reduced sphingomyelin accumulation and enlarged lysosomes in NPA neural stem cells. Therefore, the NPA neural stem cells possess the characteristic NPA disease phenotype that can be ameliorated by tocopherols, cyclodextrin, and ASM. Our results demonstrate the efficacies of cyclodextrin and tocopherols in the NPA cell-based model. Our data also indicate that the NPA neural stem cells can be used as a new cell-based disease model for further study of disease pathophysiology and for high-throughput screening to identify new lead compounds for drug development. Significance Currently, there is no effective treatment for Niemann-Pick disease type A (NPA). To accelerate drug discovery for treatment of NPA, NPA-induced pluripotent stem cells were generated from patient dermal fibroblasts and differentiated into neural stem cells. By using the differentiated NPA neuronal cells as a cell-based disease model system, α-tocopherol, δ-tocopherol, and hydroxypropyl-β-cyclodextrin significantly reduced sphingomyelin accumulation in these NPA neuronal cells. Therefore, this cell-based NPA model can be used for further study of disease pathophysiology and for high-throughput screening of compound libraries to identify lead compounds for drug development.

Converging evidence indicates that groups of patients with nominally distinct psychiatric diagnoses are not separated by sharp or discontinuous neurobiological boundaries. In healthy populations, individual differences in behavior are reflected in variability across the collective set of functional brain connections (functional connectome). These data suggest that the spectra of transdiagnostic symptom profiles observed in psychiatric patients may map onto detectable patterns of network function. To examine the manner through which neurobiological variation might underlie clinical presentation we obtained functional magnetic resonance imaging (fMRI) data from over 1,000 individuals, including 210 diagnosed with a primary psychotic disorder or affective psychosis (bipolar disorder with psychosis and schizophrenia or schizoaffective disorder), 192 presenting with a primary affective disorder without psychosis (unipolar depression, bipolar disorder without psychosis), and 608 demographically and data-quality matched healthy comparison participants recruited through a large-scale study of brain imaging and genetics. Here, we examine variation in functional connectomes across psychiatric diagnoses, finding striking evidence for disease connectomic “fingerprints” that are commonly disrupted across distinct forms of pathology and appear to scale as a function of illness severity. Conversely, other properties of network connectivity were preferentially disrupted in patients with psychotic illness, but not patients without psychotic symptoms. This work allows us to establish key biological and clinical features of the functional connectomes of severe mental disease.SIGNIFICANCE STATEMENTHistorically, most research on the biological origins of psychiatric illness has focused on individual diagnostic categories, studied in isolation. Mounting evidence suggests nominally distinct psychiatric diagnoses are not separated by clear neurobiological boundaries. Here, we derive functional connectomic signatures in over 1,000 individuals including patients presenting with specific categories of impairment (psychosis), clinical diagnoses, or severity of illness as reflected in treatment seeking. Our analyses revealed features of connectome functioning that are commonly disrupted across distinct forms of pathology, scaling with clinical severity. Conversely, other aspects of network connectivity were preferentially disrupted in patients with psychotic illness, but not patients without psychotic symptoms. These data have important implications for the establishment of functional connectome fingerprints of severe mental disease.

BackgroundNeuroimaging of psychiatric disease is challenged by the difficulty of establishing the causal role of neuroimaging abnormalities. Lesions that cause mania present a unique opportunity to understand how brain network disruption may cause mania in both lesions and in bipolar disorder.MethodsA literature search revealed 23 case reports with imaged lesions that caused mania in patients without history of bipolar disorder. We traced these lesions and examined resting-state functional Magnetic Resonance Imaging (rsfMRI) connectivity to these lesions and control lesions to find networks that would be disrupted specifically by mania-causing lesions. The results were then used as regions-of-interest to examine rsfMRI connectivity in patients with bipolar disorder (n=16) who underwent imaging longitudinally across states of both mania and euthymia alongside a cohort of healthy participants scanned longitudinally. We then sought to replicate these results in independent cohorts of manic (n=26) and euthymic (n=21) participants with bipolar disorder.ResultsMania-inducing lesions overlap significantly in network connectivity. Mania-causing lesions selectively disrupt networks that include orbitofrontal cortex, dorsolateral prefrontal cortex, and temporal lobes. In bipolar disorder, the manic state was reflected in strong, significant, and specific disruption in network communication between these regions and regions implicated in bipolar pathophysiology: the amygdala and ventro-lateral prefrontal cortex.LimitationsThe was heterogeneity in the clinical characterization of mania causing lesions.ConclusionsLesions causing mania demonstrate shared and specific network disruptions. These disruptions are also observed in bipolar mania and suggest a convergence of multiple disorders on shared circuit dysfunction to cause mania.

Background Social cognitive ability is a significant determinant of functional outcome, and deficits in social cognition are a disabling symptom of psychotic disorders. The neurobiological underpinnings of social cognition are not well understood, hampering our ability to ameliorate these deficits. Objective Using ‘resting state’ functional magnetic resonance imaging (rsfMRI) and a trans-diagnostic, data-driven analytic strategy, we sought to identify the brain network basis of emotional intelligence, a key domain of social cognition. Methods The study included 60 participants with a diagnosis of schizophrenia or schizoaffective disorder and 45 healthy controls. All participants underwent a rsfMRI scan. Emotional Intelligence was measured using the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT). A connectome-wide analysis examined how each individual brain voxel's connectivity correlated with emotional intelligence using multivariate distance matrix regression (MDMR). Results We identified a region in the left superior parietal lobule (SPL) where individual network topology is linked to emotional intelligence. Specifically, in high scoring individuals, this region is a node of the Default Mode Network and in low scoring individuals, it is a node of the Dorsal Attention Network. This relationship was observed in both schizophrenia and healthy comparison participants. Conclusion Prior studies have demonstrated individual variance in the topology of canonical resting state networks but the cognitive or behavioral relevance of these differences has largely been undetermined. We observe that the left SPL, a region of high individual variance at the cytoarchitectonic level, also demonstrates individual variance in its association with large scale resting-state networks and that network topology is linked to emotional intelligence.

BackgroundSocial cognitive ability is a significant determinant of functional outcome and deficits in social cognition are a disabling symptom of psychotic disorders. The neurobiological underpinnings of social cognition are not well understood, hampering our ability to ameliorate these deficits.ObjectiveUsing ‘resting-state’ fMRI (functional magnetic resonance imaging) and a trans-diagnostic, data-driven analytic strategy, we sought to identify the brain network basis of emotional intelligence, a key domain of social cognition.MethodsStudy participants included 60 participants with a diagnosis of schizophrenia or schizoaffective disorder and 46 healthy comparison participants. All participants underwent a resting-state fMRI scan. Emotional Intelligence was measured using the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT). A connectome-wide analysis of brain connectivity examined how each individual brain voxel’s connectivity correlated with emotional intelligence using multivariate distance matrix regression (MDMR).ResultsWe identified a region in the left superior parietal lobule (SPL) where individual network topology predicted emotional intelligence. Specifically, the association of this region with the Default Mode Network predicted higher emotional intelligence and association with the Dorsal Attention Network predicted lower emotional intelligence. This correlation was observed in both schizophrenia and healthy comparison participants.ConclusionPrevious studies have demonstrated individual variance in brain network topology but the cognitive or behavioral relevance of these differences was undetermined. We observe that the left SPL, a region of high individual variance at the cytoarchitectonic level, also demonstrates individual variance in its association with large scale brain networks and that network topology predicts emotional intelligence.

Mucopolysaccharidosis type I (MPS I) is a progressive lysosomal storage disorder with systemic and central nervous system (CNS) involvement due to deficiency of α-l-iduronidase (IDUA). We previously identified a receptor-binding peptide from apolipoprotein E (e) that facilitated a widespread delivery of IDUAe fusion protein into CNS. In this study, we evaluated the long-term CNS biodistribution, dose-correlation, and therapeutic benefits of IDUAe after systemic, sustained delivery via hematopoietic stem cell (HSC)-mediated gene therapy with expression restricted to erythroid/megakaryocyte lineages. Compared to the highest dosage group treated by nontargeted control IDUAc (165 U/ml), physiological levels of IDUAe in the circulation (12 U/ml) led to better CNS benefits in MPS I mice as demonstrated in glycosaminoglycan accumulation, histopathology analysis, and neurological behavior. Long-term brain metabolic correction and normalization of exploratory behavior deficits in MPS I mice were observed by peripheral enzyme therapy with physiological levels of IDUAe derived from clinically attainable levels of HSC transduction efficiency (0.1). Importantly, these levels of IDUAe proved to be more beneficial on correction of cerebrum pathology and behavioral deficits in MPS I mice than wild-type HSCs fully engrafted in MPS I chimeras. These results provide compelling evidence for CNS efficacy of IDUAe and its prospective translation to clinical application.

Objective Neuroimaging techniques have begun to elucidate the neurophysiology of bipolar disorder (BPD). Several features of BPD have hindered understanding of how mood-state changes are reflected in changes in brain physiology. Longitudinal studies have advantages in isolating state-related changes and in studying the instability, inherent in these disorders, that gives rise to pathological mood states. Methods To assess the state of the art in longitudinal neuroimaging studies in BPD, we conducted a literature review, searching MEDLINE for articles that included the key words bipolar disorder and magnetic resonance spectroscopy (MRS), magnetic resonance imaging (MRI), or emission tomography. The search was limited to studies with multiple subjects at two distinct and defined mood states. This search yielded eight MRS studies, four functional MRI studies, and three positron emission tomography studies. Results Although longitudinally designed studies allow for the isolation of biomarkers of mood state (including euthymia), the current literature is hampered by a lack of replication between studies. Conclusions The current body of longitudinal BPD imaging studies is heterogeneous and incomplete, and does not lend itself to the construction of an explanatory model of mood-state transitions. Drawing on extant studies, we propose a hypothetical framework for future experiments combining multimodal imaging with a longitudinal study design.

BACKGROUND: Negative symptoms and cognitive deficits are a substantial cause of disability in schizophrenia, and are often resistant to conventional methods of treatment necessitating newer therapies. Theta Burst Stimulation or TBS, a novel form of Transcranial Magnetic Stimulation (TMS) has more potent and long-lasting effects than conventional rTMS (repetitive TMS). TBS when delivered to novel brain targets (e.g., the cerebellar vermis) has shown promising results in open-label trials. METHODS: A double blind randomised controlled trial (Trial Registration.No-REF/2016/09/012196) was conducted where we randomized 60 schizophrenia patients with persistent negative symptoms, to receive intermittent TBS (iTBS; n=30) or sham TBS (n=30). In iTBS a burst of three pulses is administered at 50 Hz, repeated at a frequency of 5 Hz and delivered in 2 s trains followed by an 8 s interval. They received 600-pulses of neuronavigation-guided cerebellar vermis TBS (area VIIB) twice daily, four hours apart for five days, with an intensity of 80% of active motor threshold. Patients underwent assessments of positive and negative symptoms, depression, extrapyramidal symptoms and cognition at baseline, sixth-day and six-weeks after the intervention. Resting state functional magnetic resonance imaging was performed at baseline and on the sixth-day after intervention. RESULTS: Mixed-models repeated measures analysis showed significant time effect for negative symptoms (Scale for Assessment of Negative Symptoms total score; F= 37.433, P

Background This study aimed to identify how the activity of large-scale brain networks differs between mood states in bipolar disorder. The authors measured spontaneous brain activity in subjects with bipolar disorder in mania and euthymia and compared these states to a healthy comparison population. Methods 23 subjects with bipolar disorder type I in a manic episode, 24 euthymic bipolar I subjects, and 23 matched healthy comparison (HC) subjects underwent resting state fMRI scans. Using an existing parcellation of the whole brain, we measured functional connectivity between brain regions and identified significant differences between groups. Results In unbiased whole-brain analyses, functional connectivity between parietal, occipital, and frontal nodes within the dorsal attention network (DAN) were significantly greater in mania than euthymia or HC subjects. In the default mode network (DMN), connectivity between dorsal frontal nodes and the rest of the DMN differentiated both mood state and diagnosis. Limitations The bipolar groups were separate cohorts rather than subjects imaged longitudinally across mood states. Conclusions Bipolar mood states are associated with highly significant alterations in connectivity in two large-scale brain networks. These same networks also differentiate bipolar mania and euthymia from a HC population. State related changes in DAN and DMN connectivity suggest a circuit based pathology underlying cognitive dysfunction as well as activity/reactivity in bipolar mania. Altered activities in neural networks may be biomarkers of bipolar disorder diagnosis and mood state that are accessible to neuromodulation and are promising novel targets for scientific investigation and possible clinical intervention.

Background Existing models of the pathophysiology of bipolar disorder posit disruption in neural circuits of emotion regulation and reward processing. However, few fMRI studies have compared regional brain activity and connectivity in different mood states in bipolar disorder to determine if manic symptomatology is reflected in specific circuit abnormalities. The purpose of this study was to test the hypothesis that bipolar mania is associated with altered connectivity between cortical regions thought to regulate subcortical structures such as the amygdala and striatum. Methods 28 subjects with bipolar disorder in a manic state, 24 different bipolar subjects in a euthymic state, and 23 matched healthy comparison subjects underwent resting state fMRI scans. Several cortical and sub-cortical structures implicated in the pathogenesis of bipolar disorder were selected for study. We conducted a whole-brain analysis of functional connectivity of these regions. Results Bipolar mania was differentiated from euthymia by decreased functional connectivity between the amygdala and anterior cingulate cortex (ACC). Mania was also characterized by increased connectivity between amygdala and dorsal frontal cortical structures that are normally anti-correlated in emotion regulation tasks. Limitations Both groups of bipolar subjects were prescribed medications. The study was not longitudinal in design. Conclusions Compared to bipolar subjects in a euthymic state, subjects in the manic state demonstrate disrupted functional connectivity between brain regions involved in the regulation of emotion and the amygdala. This disruption of activity in neural circuits involved in emotion may underlie the emotional dysregulation inherent to a bipolar manic episode.

Cocaine-associated toxicity is the result of effects on the cardiovascular and central nervous systems. Since the primary route of cocaine inactivation is enzymatic degradation by butyrylcholinesterase (BChE), we sought to determine if the administration of purified human enzyme would ameliorate the lethal effects of cocaine. While the cardiovascular, autonomic or central nervous systems were unaffected by BChE, the enzyme reduced the adverse effects of cocaine including hypertension, hyperactivity and convulsions. BChE decreased both the brain and blood levels of cocaine and shifted the metabolites towards the production of the inactive product ecgonine methyl ester and away from the physiologically active metabolites, norcocaine and benzoylecgonine. We conclude that BChE would appear to be an ideal antidote in the treatment of cocaine intoxication and has potential therapeutic application.

The extraordinary benefit of enzyme replacement therapy (ERT) on the systemic manifestations of Gaucher disease was demonstrated in 1991. Since that time, investigators have devoted substantial effort to improve the delivery of enzymes to the brain because many hereditary metabolic disorders are characterized by extensive central nervous system involvement. Because the required supplemental enzyme is too large to cross the blood-brain barrier (BBB), ERT for central nervous system involvement was out of the question at that time. Several innovative strategies that have been reported to overcome this impediment are discussed. Recent investigations have provided additional insight concerning the pathogenesis of enzyme deficiency disorders. For many years it was presumed that alterations of the amino acid sequence of enzymes such as glucocerebrosidase reduced the catalytic activity of the enzyme. It has recently been shown that the decrease of glucocerebrosidase activity was the result of a quantitative loss of the amount of this enzyme. Significant increases of its activity were obtained with small molecule inhibitors of histone deacetylase that cross the BBB. The effect of such materials on neuronopathic Gaucher disease and other CNS metabolic disorders is discussed.

Astrocytes are the most abundant cell of the CNS and demonstrate contact inhibition in which a nonproliferative, nonmotile cellular state is achieved once stable intercellular contacts are formed between mature cells. Cellular injury disrupts these intercellular contacts, causing a loss of contact inhibition and the rapid initiation of healing. Dysregulation of the molecular pathways involved in this process is thought to lead to an aggressive cellular state associated with neoplasia. We investigated whether a comparable correlation exists between the response of astrocytes to injury and the malignant phenotype of astrocytomas. We discovered that the loss of contact inhibition plays a critical role in the initiation and regulation of reactive astrocytes in the healing of wounds. In particular, injury of the astrocytes interrupts and destabilizes the cadherin-catenin complexes at the cell membrane leading to nuclear translocation of β-catenin and characteristic changes associated with the activation of astrocytes. Similar signaling pathways are found to be active—but dysregulated—in astrocytomas. Inhibition of β-catenin signaling diminished both the response of astrocytes to injury and induction of the malignant phenotype of astrocytomas. The findings shed light on a unique mechanism associated with the pathogenesis of astrocytomas and provide a model for the loss of contact inhibition that may broadly apply to understanding the mechanisms of tissue repair and tumorigenesis in the brain.