John Lauriello

The expert consensus guideline series

Abstract Over the past decade, many new epilepsy treatments have been approved in the United States, promising better quality of life for many with epilepsy. However, clinicians must now choose among a growing number of treatment options and possible combinations. Randomized clinical trials (RCTs) form the basis for evidence-based decision making about best treatment options, but they rarely compare active therapies, making decisions difficult. When medical literature is lacking, expert opinion is helpful, but may contain potential biases. The expert consensus method is a new approach for statistically analyzing pooled opinion to minimize biases inherent in other systems of summarizing expert opinion. We used this method to analyze expert opinion on treatment of three epilepsy syndromes (idiopathic generalized epilepsy, symptomatic localization-related epilepsy, and symptomatic generalized epilepsy) and status epilepticus. For all three syndromes, the experts recommended the same general treatment strategy. As a first step, they recommend monotherapy. If this fails, a second monotherapy should be tried. Following this, the experts are split between additional trials of monotherapy and a combination of two therapies. If this fails, most agree the next step should be additional trials of two therapies, with less agreement as to the next best step after this. One exception to these recommendations is that the experts recommend an evaluation for epilepsy surgery after the third failed step for symptomatic localization-related epilepsies. The results of the expert survey were used to develop user-friendly treatment guidelines concerning overall treatment strategies and choice of specific medications for different syndromes and for status epilepticus.

Working memory and DLPFC inefficiency in schizophrenia: The FBIRN study

BACKGROUND The Functional Imaging Biomedical Informatics Network is a consortium developing methods for multisite functional imaging studies. Both prefrontal hyper- or hypoactivity in chronic schizophrenia have been found in previous studies of working memory. METHODS In this functional magnetic resonance imaging (fMRI) study of working memory, 128 subjects with chronic schizophrenia and 128 age- and gender-matched controls were recruited from 10 universities around the United States. Subjects performed the Sternberg Item Recognition Paradigm1,2 with memory loads of 1, 3, or 5 items. A region of interest analysis examined the mean BOLD signal change in an atlas-based demarcation of the dorsolateral prefrontal cortex (DLPFC), in both groups, during both the encoding and retrieval phases of the experiment over the various memory loads. RESULTS Subjects with schizophrenia performed slightly but significantly worse than the healthy volunteers and showed a greater decrease in accuracy and increase in reaction time with increasing memory load. The mean BOLD signal in the DLPFC was significantly greater in the schizophrenic group than the healthy group, particularly in the intermediate load condition. A secondary analysis matched subjects for mean accuracy and found the same BOLD signal hyperresponse in schizophrenics. CONCLUSIONS The increase in BOLD signal change from minimal to moderate memory loads was greater in the schizophrenic subjects than in controls. This effect remained when age, gender, run, hemisphere, and performance were considered, consistent with inefficient DLPFC function during working memory. These findings from a large multisite sample support the concept not of hyper- or hypofrontality in schizophrenia, but rather DLPFC inefficiency that may be manifested in either direction depending on task demands. This redirects the focus of research from direction of difference to neural mechanisms of inefficiency.

Dysregulation of Working Memory and Default- Mode Networks in Schizophrenia Using Independent Component Analysis, an fBIRN and MCIC Study

Deficits in working memory (WM) are a consistent neurocognitive marker for schizophrenia. Previous studies have suggested that WM is the product of coordinated activity in distributed functionally connected brain regions. Independent component analysis (ICA) is a data‐driven approach that can identify temporally coherent networks that underlie fMRI activity. We applied ICA to an fMRI dataset for 115 patients with chronic schizophrenia and 130 healthy controls by performing the Sternberg Item Recognition Paradigm. Here, we describe the first results using ICA to identify differences in the function of WM networks in schizophrenia compared to controls. ICA revealed six networks that showed significant differences between patients with schizophrenia and healthy controls. Four of these networks were negatively task‐correlated and showed deactivation across the posterior cingulate, precuneus, medial prefrontal cortex, anterior cingulate, inferior parietal lobules, and parahippocampus. These networks comprise brain regions known as the default‐mode network (DMN), a well‐characterized set of regions shown to be active during internal modes of cognition and implicated in schizophrenia. Two networks were positively task‐correlated, with one network engaging WM regions such as bilateral DLPFC and inferior parietal lobules while the other network engaged primarily the cerebellum. Our results suggest that DLPFC dysfunction in schizophrenia might be lateralized to the left and intrinsically tied to other regions such as the inferior parietal lobule and cingulate gyrus. Furthermore, we found that DMN dysfunction in schizophrenia exists across multiple subnetworks of the DMN and that these subnetworks are individually relevant to the pathophysiology of schizophrenia. In summary, this large multsite study identified multiple temporally coherent networks, which are aberrant in schizophrenia versus healthy controls and suggests that both task‐correlated and task‐anticorrelated networks may serve as potential biomarkers. Hum Brain Mapp, 2009.

A Genome-Wide Association Study of Schizophrenia Using Brain Activation as a Quantitative Phenotype

BACKGROUND Genome-wide association studies (GWASs) are increasingly used to identify risk genes for complex illnesses including schizophrenia. These studies may require thousands of subjects to obtain sufficient power. We present an alternative strategy with increased statistical power over a case-control study that uses brain imaging as a quantitative trait (QT) in the context of a GWAS in schizophrenia. METHODS Sixty-four subjects with chronic schizophrenia and 74 matched controls were recruited from the Functional Biomedical Informatics Research Network (FBIRN) consortium. Subjects were genotyped using the Illumina HumanHap300 BeadArray and were scanned while performing a Sternberg Item Recognition Paradigm in which they learned and then recognized target sets of digits in an functional magnetic resonance imaging protocol. The QT was the mean blood oxygen level-dependent signal in the dorsolateral prefrontal cortex during the probe condition for a memory load of 3 items. RESULTS Three genes or chromosomal regions were identified by having 2 single-nucleotide polymorphisms (SNPs) each significant at P < 10(-6) for the interaction between the imaging QT and the diagnosis (ROBO1-ROBO2, TNIK, and CTXN3-SLC12A2). Three other genes had a significant SNP at <10(-6) (POU3F2, TRAF, and GPC1). Together, these 6 genes/regions identified pathways involved in neurodevelopment and response to stress. CONCLUSION Combining imaging and genetic data from a GWAS identified genes related to forebrain development and stress response, already implicated in schizophrenic dysfunction, as affecting prefrontal efficiency. Although the identified genes require confirmation in an independent sample, our approach is a screening method over the whole genome to identify novel SNPs related to risk for schizophrenia.

Test-retest and between-site reliability in a multicenter fMRI study.

In the present report, estimates of test–retest and between‐site reliability of fMRI assessments were produced in the context of a multicenter fMRI reliability study (FBIRN Phase 1, www.nbirn.net). Five subjects were scanned on 10 MRI scanners on two occasions. The fMRI task was a simple block design sensorimotor task. The impulse response functions to the stimulation block were derived using an FIR‐deconvolution analysis with FMRISTAT. Six functionally‐derived ROIs covering the visual, auditory and motor cortices, created from a prior analysis, were used. Two dependent variables were compared: percent signal change and contrast‐to‐noise‐ratio. Reliability was assessed with intraclass correlation coefficients derived from a variance components analysis. Test–retest reliability was high, but initially, between‐site reliability was low, indicating a strong contribution from site and site‐by‐subject variance. However, a number of factors that can markedly improve between‐site reliability were uncovered, including increasing the size of the ROIs, adjusting for smoothness differences, and inclusion of additional runs. By employing multiple steps, between‐site reliability for 3T scanners was increased by 123%. Dropping one site at a time and assessing reliability can be a useful method of assessing the sensitivity of the results to particular sites. These findings should provide guidance toothers on the best practices for future multicenter studies. Hum Brain Mapp, 2008.

A Controlled Study of Imagery Rehearsal for Chronic Nightmares in Sexual Assault Survivors With PTSD: A Preliminary Report

Imagery-rehearsal therapy for chronic nightmares was assessed in a randomized, controlled study of sexual assault survivors with posttraumatic stress disorder (PTSD). Nightmares, sleep quality, and PTSD were assessed at baseline for 169 women, who were randomized into two groups: treatment (n = 87) and wait-list control (n = 82). Treatment consisted of two 3-hr sessions and one 1-hr session conducted over 5 weeks. Of 169 participants, 91 women (Treatment, n = 43, Control, n = 48) completed a 3-month follow-up and 78 did not. At follow-up, nightmare frequency and PTSD severity decreased and sleep quality improved in the treatment group with small to minimal changes in the control group. Treatment effects were moderate to high (Cohens d ranged from 0.57 to 1.26). Notwithstanding the large dropout rate, imagery-rehearsal therapy is an effective treatment for chronic nightmares in sexual assault survivors with PTSD and is associated with improvement in sleep quality and decreases in PTSD severity.

Selective Cognitive Impairments Associated with NMDA Receptor Blockade in Humans

Hypofunction of the N-methyl-D-aspartate receptor (NMDAR) may be involved in the pathophysiology of schizophrenia. NMDAR antagonists like ketamine induce schizophrenia-like features in humans. In rodent studies, NMDAR antagonism impairs learning by disrupting long-term potentiation (LTP) in the hippocampus. This study investigated the effects of ketamine on spatial learning (acquisition) vs retrieval in a virtual Morris water task in humans. Verbal fluency, working memory, and learning and memory of verbal information were also assessed. Healthy human subjects participated in this double-blinded, placebo-controlled study. On two separate occasions, ketamine/placebo was administered and cognitive tasks were assessed in association with behavioral ratings. Ketamine impaired learning of spatial and verbal information but retrieval of information learned prior to drug administration was preserved. Schizophrenia-like symptoms were significantly related to spatial and verbal learning performance. Ketamine did not significantly impair attention, verbal fluency, or verbal working memory task performance. Spatial working memory was slightly impaired. In conclusion, these results provide evidence for ketamines differential impairment of verbal and spatial learning vs retrieval. By using the Morris water task, which is hippocampal-dependent, this study helps bridge the gap between nonhuman animal and human NMDAR antagonism research. Impaired cognition is a core feature of schizophrenia. A better understanding of NMDA antagonism, its physiological and cognitive consequences, may provide improved models of psychosis and cognitive therapeutics.

Auditory Oddball Deficits in Schizophrenia: An Independent Component Analysis of the fMRI Multisite Function BIRN Study

Deficits in the connectivity between brain regions have been suggested to play a major role in the pathophysiology of schizophrenia. A functional magnetic resonance imaging (fMRI) analysis of schizophrenia was implemented using independent component analysis (ICA) to identify multiple temporally cohesive, spatially distributed regions of brain activity that represent functionally connected networks. We hypothesized that functional connectivity differences would be seen in auditory networks comprised of regions such as superior temporal gyrus as well as executive networks that consisted of frontal-parietal areas. Eight networks were found to be implicated in schizophrenia during the auditory oddball paradigm. These included a bilateral temporal network containing the superior and middle temporal gyrus; a default-mode network comprised of the posterior cingulate, precuneus, and middle frontal gyrus; and multiple dorsal lateral prefrontal cortex networks that constituted various levels of between-group differences. Highly task-related sensory networks were also found. These results indicate that patients with schizophrenia show functional connectivity differences in networks related to auditory processing, executive control, and baseline functional activity. Overall, these findings support the idea that the cognitive deficits associated with schizophrenia are widespread and that a functional connectivity approach can help elucidate the neural correlates of this disorder.

1H-MRS at 4 Tesla in minimally treated early schizophrenia

We investigated glutamate-related neuronal dysfunction in the anterior cingulate (AC) early in schizophrenia before and after antipsychotic treatment. A total of 14 minimally treated schizophrenia patients and 10 healthy subjects were studied with single-voxel proton magnetic resonance spectroscopy (1H-MRS) of the AC, frontal white matter and thalamus at 4 T. Concentrations of N-acetylaspartate (NAA), glutamate (Glu), glutamine (Gln) and Gln/Glu ratios were determined and corrected for the partial tissue volume. Patients were treated with antipsychotic medication following a specific algorithm and 1H-MRS was repeated after 1, 6 and 12 months. There were group × region interactions for baseline NAA (P=0.074) and Gln/Glu (P=0.028): schizophrenia subjects had lower NAA (P=0.045) and higher Gln/Glu (P=0.006) in the AC before treatment. In addition, AC Gln/Glu was inversely related to AC NAA in the schizophrenia (P=0.0009) but not in the control group (P=0.92). Following antipsychotic treatment, there were no further changes in NAA, Gln/Glu or any of the other metabolites in any of the regions studied. We conclude that early in the illness, schizophrenia patients already show abnormalities in glutamatergic metabolism and reductions in NAA consistent with glutamate-related excitotoxicity.

Voxel-based Morphometric Multisite Collaborative Study on Schizophrenia

Regional gray matter (GM) abnormalities are well known to exist in patients with chronic schizophrenia. Voxel-based morphometry (VBM) has been previously used on structural magnetic resonance images (MRI) data to characterize these abnormalities. Two multisite schizophrenia studies, the Functional Biomedical Informatics Research Network and the Mind Clinical Imaging Consortium, which include 9 data collection sites, are evaluating the efficacy of pooling structural imaging data across imaging centers. Such a pooling of data could yield the increased statistical power needed to elucidate effects that may not be seen with smaller samples. VBM analyses were performed to evaluate the consistency of patient versus control gray matter concentration (GMC) differences across the study sites, as well as the effects of combining multisite data. Integration of data from both studies yielded a large sample of 503 subjects, including 266 controls and 237 patients diagnosed with schizophrenia, schizoaffective or schizophreniform disorder. The data were analyzed using the combined sample, as well as analyzing each of the 2 multisite studies separately. A consistent pattern of reduced relative GMC in schizophrenia patients compared with controls was found across all study sites. Imaging center-specific effects were evaluated using a region of interest analysis. Overall, the findings support the use of VBM in combined multisite studies. This analysis of schizophrenics and controls from around the United States provides continued supporting evidence for GM deficits in the temporal lobes, anterior cingulate, and frontal regions in patients with schizophrenia spectrum disorders.