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The pathophysiological role of neural autoantibodies in acute psychotic disorders is receiving increased attention. However, there is still an ongoing debate, whether predominantly psychotic manifestations of autoimmune encephalitides exist that may remain undetected and, thus, untreated. Furthermore, it is discussed if such conditions can be diagnosed based on serum antibody results or if a reliable diagnosis requires additional cerebrospinal fluids (CSF) results. In this study, we screened pairs of serum and CSF samples from antipsychotic-naïve individuals with first-episode schizophrenic psychosis (FEP, n = 103), clinical high risk for psychosis (CHR, n = 47), and healthy volunteers (HV, n = 40) for eight different antibodies against various antigens that have been shown to be associated with autoimmune encephalitides: N-methyl-D-aspartate receptor (NMDAR, NR1 subunits only), glutamic acid decarboxylase (GAD65), leucine-rich glioma inactivated protein 1 (LGI1), contactin-associated protein-like 2 protein (CASPR2), α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) subunit 1, AMPAR subunit 2, γ-aminobutyric acid-B receptors (GABABR), and glycine receptors. All patients were within the norm with regards to a careful neurological examination, a magnetic resonance imaging (MRI) of the brain, an electroencephalogram (EEG), and routine blood pathology. All CSF samples were autoantibody-negative. In three serum samples of individuals with FEP, we detected low-titer CASPR2 immunoglobulin (Ig) G antibodies (≤1:160, n = 2) and non-IgG antibodies against NMDAR (n = 1) (overall serum-autoantibody prevalence in FEP: 2.91%). However, the IgG titers were below the laboratory cut-off defined for positivity, and non-IgG antibodies are of no clinical relevance. This suggests that there were no cases of autoimmune encephalitis in our cohort. Our results highlight the importance and the high specificity of CSF analysis to reliably detect autoantibodies. They confirm the hypothesis that pure psychotic manifestations of antibody-associated autoimmune encephalitides without any additional neuropsychiatric findings are very rare. However, special attention must be paid to those presenting with atypical mental illnesses with additional neurological symptoms, evidence of clinically-significant cognitive involvement, profound sleep-wake perturbations, seizures, electroencephalographic, or magnetic resonance imaging pathologies to be able to identify cases with autoimmune-mediated psychiatric syndromes.
The pathophysiology of schizophrenia is still poorly understood. Investigating the neurophysiological correlates of cognitive dysfunction with functional neuroimaging techniques such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is widely considered to be a possible solution for this problem. Working memory impairment is one of the most prominent cognitive impairments found in schizophrenia. Working memory can be divided into a number of component processes, encoding, maintenance and retrieval. They appear to be differentially affected in schizophrenia, but little is known about the neurophysiological disturbances which contribute to deficits in these component processes. The aim of this dissertation was to elucidate the neurophysiological underpinnings of the component processes of working memory and their disturbance in schizophrenia. In the first study the the neurophysiological substrates of visual working memory capacity limitations were investigated during encoding, maintenance and retrieval in 12 healthy subjects using event-related fMRI. Subjects had to encode up to four abstract visual shapes and maintain them in working memory for 12 seconds. Afterwards a test stimulus was presented, which matched one of the previously shown shapes in fifty percent of the trials. A bilateral inverted U-shape pattern of BOLD activity with increasing memory load in areas closely linked with selective attention, i.e. the frontal eye fields and areas around the intraparietal sulcus, was observed already during encoding. The increase of the number of stored items from memory load three to memory load four in these regions was negatively correlated with the increase of BOLD activity from memory load three to memory load four. These results point to a crucial role of attentional processes for the limited capacity of working memory. In the second study, the contribution of early perceptual processing deficits during encoding and retrieval to working memory dysfunction was investigated in 17 patients with schizophrenia and 17 healthy control subjects using EEG and event-related fMRI. A slightly modified version of the working memory task used in the fist study was employed. Participants only had to encode and maintain up to three items. In patients the amplitude of the P1 event-related potential was significantly reduced already during encoding in all memory load conditions. Similarly, BOLD activity in early visual areas known to generate the P1 was significantly reduced in patients. In controls, a stronger P1 amplitude increase with increasing memory load predicted better performance. These findings indicate that in addition to later memory related processing stages early visual processing is disturbed in schizophrenia and contributes to working memory dysfunction by impairing the encoding of information. In the third study, which was based on the same data set as the second study, cortical activity and functional connectivity in 17 patients with schizophrenia and 17 to healthy control subjects during the working memory encoding, maintenance and retrieval was investigated using event-related fMRI. Patients had reduced working memory capacity. During encoding activation in the left ventrolateral prefrontal cortex and extrastriate visual cortex was reduced in patients but positively correlated with working memory capacity in controls. During early maintenance patients switched from hyper- to hypoactivation with increasing memory load in a fronto-parietal network which included left dorsolateral prefrontal cortex. During retrieval right ventrolateral prefrontal hyperactivation was correlated with encoding-related hypoactivation of left ventrolateral prefrontal cortex in patients. Cortical dysfunction in patients during encoding and retrieval was accompanied by abnormal functional connectivity between fronto-parietal and visual areas. These findings indicate a primary encoding deficit in patients caused by a dysfunction of prefrontal and visual areas. The findings of these studies suggest that isolating the component processes of working memory leads to more specific markers of cortical dysfunction in schizophrenia, which had been obscured in previous studies. This approach may help to identify more reliable biomarkers and endophenotypes of schizophrenia.
The graph theoretical analysis of structural magnetic resonance imaging (MRI) data has received a great deal of interest in recent years to characterize the organizational principles of brain networks and their alterations in psychiatric disorders, such as schizophrenia. However, the characterization of networks in clinical populations can be challenging, since the comparison of connectivity between groups is influenced by several factors, such as the overall number of connections and the structural abnormalities of the seed regions. To overcome these limitations, the current study employed the whole-brain analysis of connectional fingerprints in diffusion tensor imaging data obtained at 3 T of chronic schizophrenia patients (n = 16) and healthy, age-matched control participants (n = 17). Probabilistic tractography was performed to quantify the connectivity of 110 brain areas. The connectional fingerprint of a brain area represents the set of relative connection probabilities to all its target areas and is, hence, less affected by overall white and gray matter changes than absolute connectivity measures. After detecting brain regions with abnormal connectional fingerprints through similarity measures, we tested each of its relative connection probability between groups. We found altered connectional fingerprints in schizophrenia patients consistent with a dysconnectivity syndrome. While the medial frontal gyrus showed only reduced connectivity, the connectional fingerprints of the inferior frontal gyrus and the putamen mainly contained relatively increased connection probabilities to areas in the frontal, limbic, and subcortical areas. These findings are in line with previous studies that reported abnormalities in striatal–frontal circuits in the pathophysiology of schizophrenia, highlighting the potential utility of connectional fingerprints for the analysis of anatomical networks in the disorder.
Hypofunction of the N-methyl-D-aspartate receptor (NMDAR) has been implicated as a possible mechanism underlying cognitive deficits and aberrant neuronal dynamics in schizophrenia. To test this hypothesis, we first administered a sub-anaesthetic dose of S-ketamine (0.006 mg/kg/min) or saline in a single-blind crossover design in 14 participants while magnetoencephalographic data were recorded during a visual task. In addition, magnetoencephalographic data were obtained in a sample of unmedicated first-episode psychosis patients (n = 10) and in patients with chronic schizophrenia (n = 16) to allow for comparisons of neuronal dynamics in clinical populations versus NMDAR hypofunctioning. Magnetoencephalographic data were analysed at source-level in the 1–90 Hz frequency range in occipital and thalamic regions of interest. In addition, directed functional connectivity analysis was performed using Granger causality and feedback and feedforward activity was investigated using a directed asymmetry index. Psychopathology was assessed with the Positive and Negative Syndrome Scale. Acute ketamine administration in healthy volunteers led to similar effects on cognition and psychopathology as observed in first-episode and chronic schizophrenia patients. However, the effects of ketamine on high-frequency oscillations and their connectivity profile were not consistent with these observations. Ketamine increased amplitude and frequency of gamma-power (63–80 Hz) in occipital regions and upregulated low frequency (5–28 Hz) activity. Moreover, ketamine disrupted feedforward and feedback signalling at high and low frequencies leading to hypo- and hyper-connectivity in thalamo-cortical networks. In contrast, first-episode and chronic schizophrenia patients showed a different pattern of magnetoencephalographic activity, characterized by decreased task-induced high-gamma band oscillations and predominantly increased feedforward/feedback-mediated Granger causality connectivity. Accordingly, the current data have implications for theories of cognitive dysfunctions and circuit impairments in the disorder, suggesting that acute NMDAR hypofunction does not recreate alterations in neural oscillations during visual processing observed in schizophrenia.
Current theories of schizophrenia suggest that the pathophysiology of the disorder may be the result of a deficit in the coordination of neural activity within and between areas of the brain, which may lead to impairments in basic cognitive functions such as contextual disambiguation and dynamic grouping (Phillips and Silverstein, 2003). This notion has been supported by recent studies showing that patients with schizophrenia are characterized by reduced synchronous, oscillatory activity in the gamma-frequency band during sensory processing (Spencer et al. 2003, Green et al. 2003, Wynn et al. 2005). However, it is currently unclear to what extent high-frequency gamma-band oscillations (> 60 Hz) contribute to impaired neural synchronization as research has so far focussed on gamma-band oscillations between 30 and 60 Hz. In addition, it is not known whether deficits in high-frequency oscillations are already present at the onset of the disorder and to what extent reductions may be related to the confounding influence of antipsychotic medication. Finally, the neural generators underlying impairments in synchronous oscillatory activity in schizophrenia have not been investigated yet. To address these questions, we recorded MEG activity during a visual closure task (Mooney faces task) in medicated chronic schizophrenia patients, drug-naive first-episode schizophrenia patients and healthy controls. MEG data were analysed for spectral power between 25 and 150 Hz, and beamforming techniques were used to localize the sources of oscillatory gamma-band activity. In healthy controls, we observed that the processing of Mooney faces was associated with sustained high-frequency gamma-band activity (> 60 Hz). A time-resolved analysis of the neural generators underlying perceptual closure revealed a network of distributed sources in occipito-temporal, parietal and frontal regions, which were differentially activated during specific time intervals. In chronic schizophrenia patients, we found a pronounced reduction of high-frequency gamma-band oscillatory activity that was accompanied by an impairment in perceptual organization and involved reduced source power in various brain regions associated with perceptual closure. First-episode patients were also characterized by a deficit in high-frequency gamma-band activity and reductions of source power in multiple areas; these impairments, however, were less pronounced than in chronic patients. Regarding behavioral performance, first-episode patients were not impaired in their ability to detect Mooney faces, but exhibited a loss in specificity of face detection. In conclusion, our results suggest that schizophrenia is associated with a widespread reduction in high-frequency oscillations that indicate local network abnormalities. These dysfunctions are independent of medication status and already present at illness onset, suggesting a possible progressive deficit during the course of the disorder.
Current theories of the pathophysiology of schizophrenia have focused on abnormal temporal coordination of neural activity. Oscillations in the gamma-band range (>25 Hz) are of particular interest as they establish synchronization with great precision in local cortical networks. However, the contribution of high gamma (>60 Hz) oscillations toward the pathophysiology is less established. To address this issue, we recorded magnetoencephalographic (MEG) data from 16 medicated patients with chronic schizophrenia and 16 controls during the perception of Mooney faces. MEG data were analysed in the 25–150 Hz frequency range. Patients showed elevated reaction times and reduced detection rates during the perception of upright Mooney faces while responses to inverted stimuli were intact. Impaired processing of Mooney faces in schizophrenia patients was accompanied by a pronounced reduction in spectral power between 60–120 Hz (effect size: d = 1.26) which was correlated with disorganized symptoms (r = −0.72). Our findings demonstrate that deficits in high gamma-band oscillations as measured by MEG are a sensitive marker for aberrant cortical functioning in schizophrenia, suggesting an important aspect of the pathophysiology of the disorder.
Pattern recognition approaches to the analysis of neuroimaging data have brought new applications such as the classification of patients and healthy controls within reach. In our view, the reliance on expensive neuroimaging techniques which are not well tolerated by many patient groups and the inability of most current biomarker algorithms to accommodate information about prior class frequencies (such as a disorder's prevalence in the general population) are key factors limiting practical application. To overcome both limitations, we propose a probabilistic pattern recognition approach based on cheap and easy-to-use multi-channel near-infrared spectroscopy (fNIRS) measurements. We show the validity of our method by applying it to data from healthy controls (n = 14) enabling differentiation between the conditions of a visual checkerboard task. Second, we show that high-accuracy single subject classification of patients with schizophrenia (n = 40) and healthy controls (n = 40) is possible based on temporal patterns of fNIRS data measured during a working memory task. For classification, we integrate spatial and temporal information at each channel to estimate overall classification accuracy. This yields an overall accuracy of 76% which is comparable to the highest ever achieved in biomarker-based classification of patients with schizophrenia. In summary, the proposed algorithm in combination with fNIRS measurements enables the analysis of sub-second, multivariate temporal patterns of BOLD responses and high-accuracy predictions based on low-cost, easy-to-use fNIRS patterns. In addition, our approach can easily compensate for variable class priors, which is highly advantageous in making predictions in a wide range of clinical neuroimaging applications. Hum Brain Mapp, 2013. © 2012 Wiley Periodicals, Inc.
Current theories of schizophrenia (ScZ) posit that the symptoms and cognitive dysfunctions arise from a dysconnection syndrome. However, studies that have examined this hypothesis with physiological data at realistic time scales are so far scarce. The current study employed a state-of-the-art approach using Magnetoencephalography (MEG) to test alterations in large-scale phase synchronization in a sample of n = 16 chronic ScZ patients, 10 males and n = 19 healthy participants, 10 males, during a perceptual closure task. We identified large-scale networks from source reconstructed MEG data using data-driven analyses of neuronal synchronization. Oscillation amplitudes and interareal phase-synchronization in the 3–120 Hz frequency range were estimated for 400 cortical parcels and correlated with clinical symptoms and neuropsychological scores. ScZ patients were characterized by a reduction in γ-band (30–120 Hz) oscillation amplitudes that was accompanied by a pronounced deficit in large-scale synchronization at γ-band frequencies. Synchronization was reduced within visual regions as well as between visual and frontal cortex and the reduction of synchronization correlated with elevated clinical disorganization. Accordingly, these data highlight that ScZ is associated with a profound disruption of transient synchronization, providing critical support for the notion that core aspect of the pathophysiology arises from an impairment in coordination of distributed neural activity.
Considering the microbiome in stress-related and neurodevelopmental trajectories to schizophrenia
(2020)
Early life adversity and prenatal stress are consistently associated with an increased risk for schizophrenia, although the exact pathogenic mechanisms linking the exposures with the disease remain elusive. Our previous view of the HPA stress axis as an elegant but simple negative feedback loop, orchestrating adaptation to stressors among the hypothalamus, pituitary, and adrenal glands, needs to be updated. Research in the last two decades shows that important bidirectional signaling between the HPA axis and intestinal mucosa modulates brain function and neurochemistry, including effects on glucocorticoid hormones and brain-derived neurotrophic factor (BDNF). The intestinal microbiome in earliest life, which is seeded by the vaginal microbiome during delivery, programs the development of the HPA axis in a critical developmental window, determining stress sensitivity and HPA function as well as immune system development. The crosstalk between the HPA and the Microbiome Gut Brain Axis (MGBA) is particularly high in the hippocampus, the most consistently disrupted neural region in persons with schizophrenia. Animal models suggest that the MGBA remains influential on behavior and physiology across developmental stages, including the perinatal window, early childhood, adolescence, and young adulthood. Understanding the role of the microbiome on critical risk related stressors may enhance or transform of understanding of the origins of schizophrenia and offer new approaches to increase resilience against stress effects for preventing and treating schizophrenia.
An increasing body of evidences from preclinical as well as epidemiological and clinical studies suggest a potential beneficial role of dietary intake of omega-3 fatty acids for cognitive functioning. In this narrative review, we will summarize and discuss recent findings from epidemiological, interventional and experimental studies linking dietary consumption of omega-3 fatty acids to cognitive function in healthy adults. Furthermore, affective disorders and schizophrenia (SZ) are characterized by cognitive dysfunction encompassing several domains. Cognitive dysfunction is closely related to impaired functioning and quality of life across these conditions. Therefore, the current review focues on the potential influence of omega-3 fatty acids on cognition in SZ and affective disorders. In sum, current data predominantly from mechanistic models and animal studies suggest that adjunctive omega-3 fatty acid supplementation could lead to improved cognitive functioning in SZ and affective disorders. However, besides its translational promise, evidence for clinical benefits in humans has been mixed. Notwithstanding evidences indicate that adjunctive omega-3 fatty acids may have benefit for affective symptoms in both unipolar and bipolar depression, to date no randomized controlled trial had evaluated omega-3 as cognitive enhancer for mood disorders, while a single published controlled trial suggested no therapeutic benefit for cognitive improvement in SZ. Considering the pleiotropic mechanisms of action of omega-3 fatty acids, the design of well-designed controlled trials of omega-3 supplementation as a novel, domain-specific, target for cognitive impairment in SZ and affective disorders is warranted.