Shashwath A. Meda

Short-term Effects of Antipsychotic Treatment on Cerebral Function in Drug-Naive First-Episode Schizophrenia Revealed by “Resting State” Functional Magnetic Resonance Imaging

CONTEXT Most of what we know about antipsychotic drug effects is at the receptor level, distal from the neural system effects that mediate their clinical efficacy. Studying cerebral function in antipsychotic-naive patients with schizophrenia before and after pharmacotherapy can enhance understanding of the therapeutic mechanisms of these clinically effective treatments. OBJECTIVE To examine alterations of regional and neural network function in antipsychotic-naive patients with first-episode schizophrenia before and after treatment with second-generation antipsychotic medication. DESIGN Case-control study. SETTING Huaxi MR Research Center and Mental Health Centre of the West China Hospital. PARTICIPANTS Thirty-four antipsychotic-naive patients with first-episode schizophrenia were scanned using gradient-echo echo-planar imaging while in a resting state. After 6 weeks of antipsychotic treatment, patients were rescanned. Thirty-four matched healthy control subjects were studied at baseline for comparison purposes. MAIN OUTCOME MEASURES The amplitude of low-frequency fluctuations (ALFF) of blood oxygen level-dependent signals, believed to reflect spontaneous neural activity, was used to characterize regional cerebral function. Functional connectivity across brain regions was evaluated using a seed voxel correlation approach and an independent component analysis. Changes in these measures after treatment were examined to characterize effects of antipsychotic drugs on regional function and functional integration. RESULTS After short-term treatment with second-generation antipsychotic medications, patients showed increased ALFF, particularly in the bilateral prefrontal and parietal cortex, left superior temporal cortex, and right caudate nucleus. Increased regional ALFF was associated with a reduction of clinical symptoms, and a widespread attenuation in functional connectivity was observed that was correlated with increased regional ALFF. CONCLUSIONS We demonstrate for the first time, to our knowledge, that widespread increased regional synchronous neural activity occurs after antipsychotic therapy, accompanied by decreased integration of function across widely distributed neural networks. These findings contribute to the understanding of the complex systems-level effects of antipsychotic drugs.

Differences in resting-state functional magnetic resonance imaging functional network connectivity between schizophrenia and psychotic bipolar probands and their unaffected first-degree relatives.

BACKGROUND Schizophrenia and bipolar disorder share overlapping symptoms and genetic etiology. Functional brain dysconnectivity is seen in both disorders. METHODS We compared 70 schizophrenia and 64 psychotic bipolar probands, their respective unaffected first-degree relatives (n = 70, and n = 52), and 118 healthy subjects, all group age-, gender-, and ethnicity-matched. We used functional network connectivity analysis to measure differential connectivity among 16 functional magnetic resonance imaging resting state networks. First, we examined connectivity differences between probands and control subjects. Next, we probed these dysfunctional connections in relatives for potential endophenotypes. Network connectivity was then correlated with Positive and Negative Syndrome Scale (PANSS) scores to reveal clinical relationships. RESULTS Three different network pairs were differentially connected in probands (false-discovery rate corrected q < .05) involving five individual resting-state networks: (A) fronto/occipital, (B) anterior default mode/prefrontal, (C) meso/paralimbic, (D) fronto-temporal/paralimbic, and (E) sensory-motor. One abnormal pair was unique to schizophrenia, (C-E), one unique to bipolar, (C-D), and one (A-B) was shared. Two of these three combinations (A-B, C-E) were also abnormal in bipolar relatives but none was normal in schizophrenia relatives (nonsignificant trend for C-E). The paralimbic circuit (C-D), which uniquely distinguished bipolar probands, contained multiple mood-relevant regions. Network relationship C-D correlated significantly with PANSS negative scores in bipolar probands, and A-B with PANSS positive and general scores in schizophrenia. CONCLUSIONS Schizophrenia and psychotic bipolar probands share several abnormal resting state network connections, but there are also unique neural network underpinnings between disorders. We identified specific connections that might also be candidate psychosis endophenotypes.

Investigating the behavioral and self-report constructs of impulsivity domains using principal component analysis.

Impulsivity, often defined as a human behavior characterized by the inclination of an individual to act on urge rather than thought, with diminished regard to consequences, encompasses a range of maladaptive behaviors, which are in turn affected by distinct neural systems. Congruent with the above definition, behavioral studies have consistently shown that the underlying construct of impulsivity is multidimensional in nature. However, research to date has been inconclusive regarding the different domains or constructs that constitute this behavior. In addition there is also no clear consensus as to whether self-report and laboratory based measures of impulsivity measure the same or different domains. This study aimed to: (i) characterize the underlying multidimensional construct of impulsivity using a sample with varying degrees of putative impulsivity related to substance misuse, including subjects who were at-risk of substance use or addicted (ARA), and (ii) assess relationships between self-report and laboratory measures of impulsivity, using a principal component-based factor analysis. In addition, our supplementary goal was to evaluate the structural constructs of impulsivity within each group separately (healthy and ARA). We used five self-report measures (Behavioral Inhibition System/Behavioral Activation System, Barratt Impulsivity Scale-11, Padua Inventory, Zuckerman Sensation Seeking Scale, and Sensitivity to Punishment and Sensitivity to Reward Questionnaire) and two computer-based laboratory tasks (Balloon Analog Risk Task and the Experiential Discounting Task) to measure the aspects of impulsivity in a total of 176 adult subjects. Subjects included healthy controls (n = 89), nonalcoholic subjects with family histories of alcoholism (family history positive; n = 36) and both former (n = 20) and current (n = 31) cocaine users. Subjects with a family history of alcoholism and cocaine abusers were grouped together as ‘at-risk/addicted’ (ARA) to evaluate our supplementary goal. Our overall results revealed the multidimensional nature of the impulsivity construct as captured optimally through a five-factor solution that accounted for nearly 70% of the total variance. The five factors/components were imputed as follows ‘Self-Reported Behavioral Activation’, ‘Self-Reported Compulsivity and Reward/Punishment’, ‘Self-Reported Impulsivity’, ‘Behavioral Temporal Discounting’, and ‘Behavioral Risk-Taking’. We also found that contrary to previously published reports, there was significant overlap between certain laboratory and self-report measures, indicating that they might be measuring the same impulsivity domain. In addition, our supplemental analysis also suggested that the impulsivity constructs were largely, but not entirely the same within the healthy and ARA groups.

Is Aberrant Functional Connectivity A Psychosis Endophenotype? A Resting State Functional Magnetic Resonance Imaging Study

BACKGROUND Schizophrenia and bipolar disorder share overlapping symptoms and risk genes. Shared aberrant functional connectivity is hypothesized in both disorders and in relatives. METHODS We investigated resting state functional magnetic resonance imaging in 70 schizophrenia and 64 psychotic bipolar probands, their respective first-degree relatives (n = 70 and 52), and 118 healthy subjects. We used independent component analysis to identify components representing various resting state networks and assessed spatial aspects of functional connectivity within all networks. We first investigated group differences using five-level, one-way analysis of covariance (ANCOVA), followed by post hoc t tests within regions displaying ANCOVA group differences and correlation of such functional connectivity measures with symptom ratings to examine clinical relationships. RESULTS Seven networks revealed abnormalities (five-level one-way ANCOVA, family-wise error correction p < .05): A) fronto-occipital, B) midbrain/cerebellum, C) frontal/thalamic/basal ganglia, D) meso/paralimbic, E) posterior default mode network, F) fronto-temporal/paralimbic and G) sensorimotor networks. Abnormalities in networks B and F were unique to schizophrenia probands. Furthermore, abnormalities in networks D and E were common to both patient groups. Finally, networks A, C, and G showed abnormalities shared by probands and their relative groups. Negative correlation with Positive and Negative Syndrome Scale negative and positive scores were found in regions within network C and F respectively, and positive correlation with Positive and Negative Syndrome Scale negative scores was found in regions in network D among schizophrenia probands only. CONCLUSIONS Schizophrenia, psychotic bipolar probands, and their relatives share both unique and overlapping within-network brain connectivity abnormalities, revealing potential psychosis endophenotypes.

Individuals Family History Positive for Alcoholism Show Functional Magnetic Resonance Imaging Differences in Reward Sensitivity That Are Related to Impulsivity Factors

BACKGROUND Substance-abusing individuals tend to display abnormal reward processing and a vulnerability to being impulsive. Detoxified alcoholics show differences in regional brain activation during a monetary incentive delay task. However, there is limited information on whether this uncharacteristic behavior represents a biological predisposition toward alcohol abuse, a consequence of chronic alcohol use, or both. METHODS We investigated proposed neural correlates of substance disorder risk by examining reward system activity during a monetary incentive delay task with separate reward prospect, reward anticipation, and reward outcome phases in 30 individuals with and 19 without family histories of alcoholism. All subjects were healthy, lacked DSM-IV past or current alcohol or substance abuse histories, and were free of illegal substances as verified by a urine toxicology screening at the time of scanning. Additionally, we explored specific correlations between task-related nucleus accumbens (NAcc) activation and distinct factor analysis-derived domains of behavioral impulsivity. RESULTS During reward anticipation, functional magnetic resonance imaging data confirmed blunted NAcc activation in family history positive subjects. In addition, we found atypical activation in additional reward-associated brain regions during additional task phases. We further found a significant negative correlation between NAcc activation during reward anticipation and an impulsivity construct. CONCLUSIONS Overall, results demonstrate that sensitivity of the reward circuit, including NAcc, is functionally different in alcoholism family history positive individuals in multiple regards.

Evidence for Anomalous Network Connectivity during Working Memory Encoding in Schizophrenia: An ICA Based Analysis

Background Numerous neuroimaging studies report abnormal regional brain activity during working memory performance in schizophrenia, but few have examined brain network integration as determined by “functional connectivity” analyses. Methodology/Principal Findings We used independent component analysis (ICA) to identify and characterize dysfunctional spatiotemporal networks in schizophrenia engaged during the different stages (encoding and recognition) of a Sternberg working memory fMRI paradigm. 37 chronic schizophrenia and 54 healthy age/gender-matched participants performed a modified Sternberg Item Recognition fMRI task. Time series images preprocessed with SPM2 were analyzed using ICA. Schizophrenia patients showed relatively less engagement of several distinct “normal” encoding-related working memory networks compared to controls. These encoding networks comprised 1) left posterior parietal-left dorsal/ventrolateral prefrontal cortex, cingulate, basal ganglia, 2) right posterior parietal, right dorsolateral prefrontal cortex and 3) default mode network. In addition, the left fronto-parietal network demonstrated a load-dependent functional response during encoding. Network engagement that differed between groups during recognition comprised the posterior cingulate, cuneus and hippocampus/parahippocampus. As expected, working memory task accuracy differed between groups (p<0.0001) and was associated with degree of network engagement. Functional connectivity within all three encoding-associated functional networks correlated significantly with task accuracy, which further underscores the relevance of abnormal network integration to well-described schizophrenia working memory impairment. No network was significantly associated with task accuracy during the recognition phase. Conclusions/Significance This study extends the results of numerous previous schizophrenia studies that identified isolated dysfunctional brain regions by providing evidence of disrupted schizophrenia functional connectivity using ICA within widely-distributed neural networks engaged for working memory cognition.

A Large Scale (N=400) Investigation of Gray Matter Differences in Schizophrenia Using Optimized Voxel-based Morphometry

BACKGROUND Many studies have employed voxel-based morphometry (VBM) of MRI images as an automated method of investigating cortical gray matter differences in schizophrenia. However, results from these studies vary widely, likely due to different methodological or statistical approaches. OBJECTIVE To use VBM to investigate gray matter differences in schizophrenia in a sample significantly larger than any published to date, and to increase statistical power sufficiently to reveal differences missed in smaller analyses. METHODS Magnetic resonance whole brain images were acquired from four geographic sites, all using the same model 1.5T scanner and software version, and combined to form a sample of 200 patients with both first episode and chronic schizophrenia and 200 healthy controls, matched for age, gender and scanner location. Gray matter concentration was assessed and compared using optimized VBM. RESULTS Compared to healthy controls, schizophrenia patients showed significantly less gray matter concentration in multiple cortical and subcortical regions, some previously unreported. Overall, we found lower concentrations of gray matter in regions identified in prior studies, most of which reported only subsets of the affected areas. CONCLUSIONS Gray matter differences in schizophrenia are most comprehensively elucidated using a large, diverse and representative sample.

Multivariate analysis reveals genetic associations of the resting default mode network in psychotic bipolar disorder and schizophrenia

Significance Connectivity within the brain’s resting-state default mode network (DMN) has been shown to be compromised in multiple genetically complex/heritable neuropsychiatric disorders. Uncovering the source of such alterations will help in developing targeted treatments for these disorders. To our knowledge, this study is the first attempt to do so by using a multivariate data-driven fusion approach. We report five major DMN subnodes, all of which were found to be hypo-connected in probands with psychotic illnesses. Further, we found an overrepresentation of genes in major relevant pathways such as NMDA potentiation, PKA/immune response signalling, synaptogenesis, and axon guidance that influenced altered DMN connectivity in psychoses. The study thus identifies several putative genes and pathways related to an important biological marker known to be compromised in psychosis. The brain’s default mode network (DMN) is highly heritable and is compromised in a variety of psychiatric disorders. However, genetic control over the DMN in schizophrenia (SZ) and psychotic bipolar disorder (PBP) is largely unknown. Study subjects (n = 1,305) underwent a resting-state functional MRI scan and were analyzed by a two-stage approach. The initial analysis used independent component analysis (ICA) in 324 healthy controls, 296 SZ probands, 300 PBP probands, 179 unaffected first-degree relatives of SZ probands (SZREL), and 206 unaffected first-degree relatives of PBP probands to identify DMNs and to test their biomarker and/or endophenotype status. A subset of controls and probands (n = 549) then was subjected to a parallel ICA (para-ICA) to identify imaging–genetic relationships. ICA identified three DMNs. Hypo-connectivity was observed in both patient groups in all DMNs. Similar patterns observed in SZREL were restricted to only one network. DMN connectivity also correlated with several symptom measures. Para-ICA identified five sub-DMNs that were significantly associated with five different genetic networks. Several top-ranking SNPs across these networks belonged to previously identified, well-known psychosis/mood disorder genes. Global enrichment analyses revealed processes including NMDA-related long-term potentiation, PKA, immune response signaling, axon guidance, and synaptogenesis that significantly influenced DMN modulation in psychoses. In summary, we observed both unique and shared impairments in functional connectivity across the SZ and PBP cohorts; these impairments were selectively familial only for SZREL. Genes regulating specific neurodevelopment/transmission processes primarily mediated DMN disconnectivity. The study thus identifies biological pathways related to a widely researched quantitative trait that might suggest novel, targeted drug treatments for these diseases.

Gray Matter Volume as an Intermediate Phenotype for Psychosis: Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP)

OBJECTIVE The study examined gray matter volume across psychosis diagnoses organized by dimensional and DSM-IV categories from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) sample. METHOD In total, 351 probands with psychosis (146 with schizophrenia, 90 with schizoaffective disorder, and 115 with psychotic bipolar I disorder), 369 of their first-degree relatives (134 were relatives of individuals with schizophrenia, 106 of individuals with schizoaffective disorder, and 129 of individuals with psychotic bipolar I disorder), and 200 healthy comparison subjects were assessed. Gray matter volumes from 3-T T1-weighted images were analyzed using the VBM8 toolbox for SPM8, and outcomes were determined at a false discovery rate-corrected threshold of p<0.005. RESULTS Across the psychosis dimension, probands (N=351) and relatives with psychosis spectrum disorders (N=34) showed substantial overlapping gray matter reductions throughout the neocortex, whereas relatives without psychosis spectrum (N=332) had normal gray matter volumes relative to comparison subjects. Across DSM-IV diagnoses, schizophrenia and schizoaffective probands showed overlapping gray matter reductions in numerous cortical and subcortical regions, whereas psychotic bipolar probands showed limited gray matter reductions localized to the frontotemporal cortex relative to comparison subjects. All relative groups had gray matter volumes that did not differ from comparison subjects. CONCLUSIONS Across the dimensional psychosis categories, these findings indicate extensive neocortical gray matter reductions in psychosis probands and relatives with psychosis spectrum disorders, possibly reflecting lifetime psychosis burden, but normal gray matter in nonpsychotic relatives. Traditional DSM-IV psychosis grouping revealed partially divergent gray matter phenotypes for probands with schizophrenia or schizoaffective disorder (extensive neocortical or subcortical gray matter reductions) relative to those with psychotic bipolar disorder (smaller reductions were limited to frontotemporal regions). The dimensional conceptualization of psychosis appears useful in defining more homogenous disease categories that may help identify underlying psychosis biomarkers and develop a biologically driven diagnostic system and targeted treatments.

Abnormal prefrontal activity subserving attentional control of emotion in remitted depressed patients during a working memory task with emotional distracters.

BACKGROUND Patients with major depressive disorder (MDD) show deficits in processing of facial emotions that persist beyond recovery and cessation of treatment. Abnormalities in neural areas supporting attentional control and emotion processing in remitted depressed (rMDD) patients suggests that there may be enduring, trait-like abnormalities in key neural circuits at the interface of cognition and emotion, but this issue has not been studied systematically. METHOD Nineteen euthymic, medication-free rMDD patients (mean age 33.6 years; mean duration of illness 34 months) and 20 age- and gender-matched healthy controls (HC; mean age 35.8 years) performed the Emotional Face N-Back (EFNBACK) task, a working memory task with emotional distracter stimuli. We used blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) to measure neural activity in the dorsolateral (DLPFC) and ventrolateral prefrontal cortex (VLPFC), orbitofrontal cortex (OFC), ventral striatum and amygdala, using a region of interest (ROI) approach in SPM2. RESULTS rMDD patients exhibited significantly greater activity relative to HC in the left DLPFC [Brodmann area (BA) 9/46] in response to negative emotional distracters during high working memory load. By contrast, rMDD patients exhibited significantly lower activity in the right DLPFC and left VLPFC compared to HC in response to positive emotional distracters during high working memory load. These effects occurred during accurate task performance. CONCLUSIONS Remitted depressed patients may continue to exhibit attentional biases toward negative emotional information, reflected by greater recruitment of prefrontal regions implicated in attentional control in the context of negative emotional information.