Association between hippocampal volume and P300 event related potential in psychosis: support for the Kraepelinian divide

Evaluation of Event-Related Potentials in Somatic Diseases - Systematic Review

Many somatic illnesses (e.g. hypertension, diabetes, pulmonary and cardiac diseases, hepatitis C, kidney and heart failure, HIV infection, Sjogren's disease) may impact central nervous system functions resulting in emotional, sensory, cognitive or even personality impairments. Event-related potential (ERP) methodology allows for monitoring neurocognitive processes and thus can provide a valuable window into these cognitive processes that are influenced, or brought about, by somatic disorders. The current review aims to present published studies on the relationships between somatic illness and brain function as assessed with ERP methodology, with the goal to discuss where this field of study is right now and suggest future directions.

The reduced left hippocampal volume related to the delayed P300 latency in amnestic mild cognitive impairment

BACKGROUND

Amnestic mild cognitive impairment (aMCI) is characterized by delayed P300 latency and reduced grey matter (GM) volume, respectively. The relationship between the features in aMCI is unclear. This study was to investigate the relationship between the altered P300 latency and the GM volume in aMCI.

METHODS

Thirty-four aMCI and 34 well-matched normal controls (NC) were studied using electroencephalogram during a visual oddball task and scanned with MRI. Both tests were finished in the same day.

RESULTS

As compared with the NC group, the aMCI group exhibited delayed P300 latency in parietal cortex and reduced GM volumes in bilateral temporal pole and left hippocampus/parahippocampal gyrus. A remarkable negative correlation was found between delayed P300 latency and reduced left hippocampal volume only in the aMCI group. Interestingly, the mediating analysis found P300 latency significantly mediated the association between right supramarginal gyrus volume and information processing speed indicated by Stroop Color and Word Test A scores.

CONCLUSIONS

The association between delayed P300 latency and reduced left hippocampal volume in aMCI subjects suggests that reduced left hippocampal volume may be the potential structural basis of delayed P300 latency.

The P300 event-related potential in bipolar disorder: A systematic review and meta-analysis

BACKGROUND

Neurophysiology including P300, that is a typical index of event-related potential, may be potential biomarkers for bipolar disorder (BD) and it can be useful towards elucidating the pathophysiology of BD. However, previous findings from P300 studies were inconsistent due to the heterogeneity of research methods, which make it difficult to understand the neurobiological significance of them. The aim of this study is to conduct a meta-analysis on P300 in patients with BD.

METHOD

A literature search was conducted using PubMed to identify studies that compared P300 event-related potential between patients with BD and healthy controls (HCs). We analyzed P300 indices such as amplitude and latency of P3a and P3b in auditory or visual paradigms. Further, moderator analyses were conducted to investigate the influence of patient characteristics (i.e. history of psychosis, diagnostic subcategories [BD-I/BD-II], and phase of illness [euthymic, manic, or depressive]) on P300 indices.

RESULT

Out of 124 initial records, we included 30 articles (BD: N = 1331; HCs: N = 1818). Patients with BD showed reduced P3a and P3b amplitude in both paradigms and delayed P3b latency in auditory paradigms compared to HCs. There was no influence on the history of psychosis, diagnostic subcategories, or phase of illness on P300 indices.

LIMITATION

The difference in medication use was difficult to control and it may affect the results.

CONCLUSION

This meta-analysis provides evidence for P300 abnormalities in patients with BD compared to HCs. Our results suggest that P300 may be trait markers rather than state markers in this illness.

A Meta-analytic Review of Auditory Event-Related Potential Components as Endophenotypes for Schizophrenia: Perspectives From First-Degree Relatives

INTRODUCTION

As endophenotypes bridge the gap between genetics and phenotypic disease expression, identifying reliable markers is important for fostering understanding of pathophysiology. The present aim was to conduct current meta-analyses of 3 key auditory event-related potential (ERP) components that have been held as potential endophenotypes for schizophrenia: P50, P300 amplitude and latency, and mismatch negativity (MMN), reflective of sensory gating, attention and classification speed, and perceptual discrimination ability, respectively. In order to assess endophenotype viability, these components were examined in unaffected relatives of patients with schizophrenia and healthy controls.

METHODS

Effect sizes (ES) were examined between relatives and controls for P50 suppression (10 studies, n = 360 relatives, 473 controls), P300 amplitude (20 studies, n = 868 relatives, 961 controls), P300 latency (17 studies, n = 674 relatives, 792 controls), and MMN (11 studies, n = 377 relatives, 552 controls).

RESULTS

Reliable differences in P50 suppression (ES = 0.86, P < .001), P300 amplitude (ES = -0.52, P < .001), and P300 latency (ES = 0.44, P < .05) were found between unaffected relatives and controls. A trend was found between relatives and controls for MMN (ES = 0.21, P = 0.06), and the use of extraneous channels was found to be a significant moderator (P = 0.01). When MMN was analyzed using frontocentral channel Fz, a significant difference was found (ES = 0.26, P < 0.01).

DISCUSSION

The results indicate that P50 suppression, P300 amplitude and P300 latency, and MMN may serve as viable endophenotypes for schizophrenia.

Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness

It is becoming increasingly clear that combining multi-modal brain imaging data is able to provide more information for individual subjects by exploiting the rich multimodal information that exists. However, the number of studies that do true multimodal fusion (i.e. capitalizing on joint information among modalities) is still remarkably small given the known benefits. In part, this is because multi-modal studies require broader expertise in collecting, analyzing, and interpreting the results than do unimodal studies. In this paper, we start by introducing the basic reasons why multimodal data fusion is important and what it can do, and importantly how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies. We also discuss the challenges that need to be confronted for such approaches to be more widely applied by the community. We then provide a review of the diverse studies that have used multimodal data fusion (primarily focused on psychosis) as well as provide an introduction to some of the existing analytic approaches. Finally, we discuss some up-and-coming approaches to multi-modal fusion including deep learning and multimodal classification which show considerable promise. Our conclusion is that multimodal data fusion is rapidly growing, but it is still underutilized. The complexity of the human brain coupled with the incomplete measurement provided by existing imaging technology makes multimodal fusion essential in order to mitigate against misdirection and hopefully provide a key to finding the missing link(s) in complex mental illness.

Impaired prefrontal synaptic gain in people with psychosis and their relatives during the mismatch negativity

The mismatch negativity (MMN) evoked potential, a preattentive brain response to a discriminable change in auditory stimulation, is significantly reduced in psychosis. Glutamatergic theories of psychosis propose that hypofunction of NMDA receptors (on pyramidal cells and inhibitory interneurons) causes a loss of synaptic gain control. We measured changes in neuronal effective connectivity underlying the MMN using dynamic causal modeling (DCM), where the gain (excitability) of superficial pyramidal cells is explicitly parameterised. EEG data were obtained during a MMN task—for 24 patients with psychosis, 25 of their first‐degree unaffected relatives, and 35 controls—and DCM was used to estimate the excitability (modeled as self‐inhibition) of (source‐specific) superficial pyramidal populations. The MMN sources, based on previous research, included primary and secondary auditory cortices, and the right inferior frontal gyrus. Both patients with psychosis and unaffected relatives (to a lesser degree) showed increased excitability in right inferior frontal gyrus across task conditions, compared to controls. Furthermore, in the same region, both patients and their relatives showed a reversal of the normal response to deviant stimuli; that is, a decrease in excitability in comparison to standard conditions. Our results suggest that psychosis and genetic risk for the illness are associated with both context‐dependent (condition‐specific) and context‐independent abnormalities of the excitability of superficial pyramidal cell populations in the MMN paradigm. These abnormalities could relate to NMDA receptor hypofunction on both pyramidal cells and inhibitory interneurons, and appear to be linked to the genetic aetiology of the illness, thereby constituting potential endophenotypes for psychosis. Hum Brain Mapp 37:351–365, 2016. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Genetic Sources of Subcomponents of Event-Related Potential in the Dimension of Psychosis Analyzed From the B-SNIP Study

OBJECTIVE

Biological risk factors underlying psychosis are poorly understood. Biological underpinnings of the dimension of psychosis can be derived using genetic associations with intermediate phenotypes such as subcomponents of auditory event-related potentials (ERPs). Various ERP subcomponent abnormalities in schizophrenia and psychotic bipolar disorder are heritable and are expressed in unaffected relatives, although studies investigating genetic contributions to ERP abnormalities are limited. The authors used a novel parallel independent component analysis (para-ICA) to determine which empirically derived gene clusters are associated with data-driven ERP subcomponents, assuming a complex etiology underlying psychosis.

METHOD

The authors examined the multivariate polygenic association of ERP subcomponents from 64-channel auditory oddball data in 144 individuals with schizophrenia, 210 psychotic bipolar disorder probands, and 95 healthy individuals from the multisite Bipolar-Schizophrenia Network on Intermediate Phenotypes study. Data were reduced by principal components analysis to two target and one standard ERP waveforms. Multivariate association of compressed ERP waveforms with a set of 20,329 single-nucleotide polymorphisms (SNPs) (reduced from a 1-million-SNP array) was examined using para-ICA. Genes associated with SNPs were further examined using pathway analysis tools.

RESULTS

Para-ICA identified four ERP components that were significantly correlated with three genetic components. Enrichment analysis revealed complement immune response pathway and multiple processes that significantly mediate ERP abnormalities in psychosis, including synaptic cell adhesion, axon guidance, and neurogenesis.

CONCLUSIONS

This study identified three genetic components comprising multiple genes mediating ERP subcomponent abnormalities in schizophrenia and psychotic bipolar disorder. The data suggest a possible polygenic structure comprising genes influencing key neurodevelopmental processes, neural circuitry, and brain function mediating biological pathways plausibly associated with psychosis.

Resting EEG in psychosis and at-risk populations--a possible endophenotype?

BACKGROUND

Finding reliable endophenotypes for psychosis could lead to an improved understanding of aetiology, and provide useful alternative phenotypes for genetic association studies. Resting quantitative electroencephalography (QEEG) activity has been shown to be heritable and reliable over time. However, QEEG research in patients with psychosis has shown inconsistent and even contradictory findings, and studies of at-risk populations are scarce. Hence, this study aimed to investigate whether resting QEEG activity represents a candidate endophenotype for psychosis.

METHOD

QEEG activity at rest was compared in four frequency bands (delta, theta, alpha, and beta), between chronic patients with psychosis (N=48), first episode patients (N=46), at-risk populations ("at risk mental state", N=33; healthy relatives of patients, N=45), and healthy controls (N=107).

RESULTS

Results showed that chronic patients had significantly increased resting QEEG amplitudes in delta and theta frequencies compared to healthy controls. However, first episode patients and at-risk populations did not differ from controls in these frequency bands. There were no group differences in alpha or beta frequency bands.

CONCLUSION

Since no abnormalities were found in first episode patients, ARMS, or healthy relatives, resting QEEG activity in the frequency bands examined is unlikely to be related to genetic predisposition to psychosis. Rather than endophenotypes, the low frequency abnormalities observed in chronic patients are probably related to illness progression and/or to the long-term effects of treatments.

Immunology of major depression

High levels of several proinflammatory components of the immune system, such as interleukin-6, C-reactive protein, tumor necrosis factor (TNF)-α, or neopterin in patients suffering from major depression (MD) point to the involvement of an inflammatory process in the pathophysiology of MD. The direct and indirect effects of cytokines on neurotransmitter storage and release - mediated by microglia cells and astrocytes - are discussed. The tryptophan/kynurenine metabolism is one of the indirect mechanisms because the enzyme indoleamine 2,3-dioxygenase - a key enzyme of this metabolism in the central nervous system - is driven by pro- and anti-inflammatory cytokines and degrades serotonin. Moreover, neuroactive kynurenines such as kynurenic acid and quinolinic acid act on the glutamatergic neurotransmission as N-methyl-D-aspartate antagonists and agonists, respectively. Alterations of the serotonergic, noradrenergic and glutamatergic neurotransmission have been shown with low-level neuroinflammation and may be involved in symptom generation. Epidemiological and clinical studies show a role for inflammation as a risk factor for MD. A large-scale epidemiological study in MD clearly demonstrates that severe infections and autoimmune disorders are lifetime risk factors for MD. The vulnerability-stress-inflammation model matches with this view as stress may increase proinflammatory cytokines and even contribute to a lasting proinflammatory state. Further support comes from the therapeutic benefit of anti-inflammatory medications such as the cyclo-oxygenase-2 inhibitors, TNF-α antagonists and others, and the anti-inflammatory and immunomodulatory intrinsic effects of antidepressants.

White matter metabolism differentiates schizophrenia and bipolar disorder: a preliminary PET study

Fluorodeoxyglucose-F18 positron emission tomography studies (FDG-PET) have shown similar corticolimbic metabolic dysregulation in bipolar disorder and schizophrenia, with hypoactive prefrontal cortex coupled with hyperactive anterior limbic areas. However, it is not clear whether white matter metabolism connecting these regions is differently affected in the two disorders. Twenty-six patients with schizophrenia (mean age ± S.D.=30.23 ± 9.7 year-old; 19 males; mean weight ± S.D.=71 ± 3 kg) and 26 patients with bipolar disorder (mean age ± S.D.=48.73 ± 13 year-old; 18 males; mean weight ± S.D.=75 ± 15 kg) underwent an FDG-PET scan. Normalized datasets the two groups of patients were compared on a voxel-by-voxel basis using a two-sample t statistic test as implemented in SPM8, and adding age as covariate. Group differences were assessed applying a threshold of p<0.0005. White matter metabolic rates significantly differed between schizophrenia and bipolar disorder, whereas no differences were shown for cortical activity. This is the first FDG-PET, to our best knowledge, directly comparing subjects with schizophrenia to those with bipolar disorder. It reports decreased activity in the center of large fronto-temporal and cerebellar white matter tracts in patients with schizophrenia in respect to those with bipolar disorder. This feature may characterize and differentiate the regional brain metabolism of the two illnesses.

Multi-components of evoked-brain potentials in deficit and nondeficit schizophrenia

INTRODUCTION

The present study aims to detect the specific and common impairment index relative to evoked brain potentials (EBPS ) in deficit schizophrenia (DS) and nondeficit schizophrenia (NDS), and investigates the relationship between EBPs and clinical variables.

METHODS

The study used EBPs in 21 patients with DS, 38 patients with NDS, and 50 healthy controls (HCs) to investigate P300 waves, mismatch negative (MMN), sensory gating (SG) P50 and contingent negative variation (CNV). A comparison of three groups and the relationship between EBPs and clinical variables were performed using general linear model analyses and partial correlation, respectively.

RESULTS

Compared with HCs, both groups of patients showed delayed N1 , N2 , and P3a latency, and reduced N1 and N2 amplitude. The MMN showed delayed latency. The P50 ratios and the inhibited ratios were impaired, whereas SG loss ratios increased. CNV amplitude was reduced. Compared with HCs, NDS showed delayed latency of S2'-C in CNV, whereas DS showed shortened latency. Only NDS, when compared with HCs, showed delayed latency of P3b , Also, only DS, when compared with HCs, showed delayed latency of point A in CNV. Latency of point A in CNV of DS, correlated with a poorer Global Assessment of Functioning Scale (6 weeks) and was independent of clinical characteristics.

DISCUSSION

Schizophrenia represents a clinical syndrome with shared impairments in brain function, whereas DS is a relatively homogeneous subgroup of schizophrenia with unique pathophysiological changes.

More pronounced deficits in facial emotion recognition for schizophrenia than bipolar disorder

Schizophrenia and bipolar disorder are typically separated in diagnostic systems. Behavioral, cognitive, and brain abnormalities associated with each disorder nonetheless overlap. We evaluated the diagnostic specificity of facial emotion recognition deficits in schizophrenia and bipolar disorder to determine whether select aspects of emotion recognition differed for the two disorders. The investigation used an experimental task that included the same facial images in an emotion recognition condition and an age recognition condition (to control for processes associated with general face recognition) in 27 schizophrenia patients, 16 bipolar I patients, and 30 controls. Schizophrenia and bipolar patients exhibited both shared and distinct aspects of facial emotion recognition deficits. Schizophrenia patients had deficits in recognizing angry facial expressions compared to healthy controls and bipolar patients. Compared to control participants, both schizophrenia and bipolar patients were more likely to mislabel facial expressions of anger as fear. Given that schizophrenia patients exhibited a deficit in emotion recognition for angry faces, which did not appear due to generalized perceptual and cognitive dysfunction, improving recognition of threat-related expression may be an important intervention target to improve social functioning in schizophrenia.