N100 Repetition Suppression Indexes Neuroplastic Defects in Clinical High Risk and Psychotic Youth

Novel N100 area reliably captures aberrant sensory processing and is associated with neurocognition in early psychosis

BACKGROUND

Despite findings from translational and genetic studies in the event-related potential (ERP) literature, the validity and reliability of P50 suppression as a schizophrenia spectrum endophenotype has been questioned. Here, we aimed to examine sensory registration and gating measures derived from P50 and N100 amplitude, as well as N100 area-a novel approach proposed herein-in early psychosis versus health.

METHODS

Individuals at clinical high risk for psychosis (CHR; n = 77), first-episode psychosis (FE; n = 52), and healthy controls (HC; n = 65) were assessed in a paired-click auditory ERP paradigm. Eight CHR converted to psychosis (CHRC) and 39 did not (CHR-NC) by 24 months, while 30 CHR were lost to follow-. Group differences, test-retest reliability, and associations with neurocognitive function were assessed in nine ERP measures.

RESULTS

Significant differences were observed in N100 S1 amplitude, S1 area, and area difference between HC and FE, as well as in N100 S1 area between HC and CHR, among the total population. Furthermore, significant differences were found in N100 S1 area between HC and CHR-NC (Cliff's delta, Δ = 0.32), as well as in N100 area difference between HC and CHR-C (Δ = 0.55). Both N100 S1 area and area difference demonstrated moderate to acceptable reliability (intraclass correlation coefficients: 0.61-0.78). Processing speed negatively correlated with both N100 S1 area and area difference, while executive function negatively correlated with N100 S1 area alone in CHR and FE.

CONCLUSION

Among the ERP measures studied, N100 area measures may serve as a reliable biomarker of aberrant sensory processing and neurocognition in early psychosis.

Heterogeneity of clinical symptomatology in pediatric patients at clinical high risk for psychosis

OBJECTIVE

Widespread use of diagnostic tools like the Structured Interview for Prodromal Symptoms (SIPS) has highlighted that youth at Clinical High Risk for Psychosis (CHR-P) present with heterogeneous symptomatology. This pilot study aims to highlight the range of clinical characteristics of CHR-P youth, investigate the role of the non-positive (negative, disorganization, and general) symptoms in risk assessment, and determine if specific profiles are associated with severe symptomatology.

METHODS

38 participants aged 7-18 were administered the SIPS and designated as CHR-P. Descriptive statistics and mean difference t-tests were used to describe the range in prevalence and severity of SIPS symptoms and to identify symptoms associated with greater overall symptomatology.

RESULTS

Participants who had a greater number of positive symptoms also had significantly more negative, disorganization, and general symptoms. A number of SIPS symptoms were associated with greater number of positive symptoms.

CONCLUSION

CHR-P youth represent a heterogeneous group, presenting with a wide range in clinical presentation as reflected in both the number of SIPS symptoms and their severity. Though the severity and duration of positive SIPS symptoms determines the CHR-P classification, high ratings on several of the other SIPS negative, disorganization, and general items may be useful indicators of elevated symptomatology.

Annual Research Review: Prevention of psychosis in adolescents - systematic review and meta-analysis of advances in detection, prognosis and intervention

BACKGROUND

The clinical high-risk state for psychosis (CHR-P) paradigm has facilitated the implementation of psychosis prevention into clinical practice; however, advancements in adolescent CHR-P populations are less established.

METHODS

We performed a PRISMA/MOOSE-compliant systematic review of the Web of Science database, from inception until 7 October 2019, to identify original studies conducted in CHR-P children and adolescents (mean age <18 years). Findings were systematically appraised around core themes: detection, prognosis and intervention. We performed meta-analyses (employing Q statistics and I ² test) regarding the proportion of CHR-P subgroups, the prevalence of baseline comorbid mental disorders, the risk of psychosis onset and the type of interventions received at baseline. Quality assessment and publication bias were also analysed.

RESULTS

Eighty-seven articles were included (n = 4,667 CHR-P individuals). Quality of studies ranged from 3.5 to 8 (median 5.5) on a modified Newcastle-Ottawa scale. Detection: Individuals were aged 15.6 ± 1.2 years (51.5% males), mostly (83%) presenting with attenuated positive psychotic symptoms. CHR-P psychometric accuracy improved when caregivers served as additional informants. Comorbid mood (46.4%) and anxiety (31.4%) disorders were highly prevalent. Functioning and cognition were impaired. Neurobiological studies were inconclusive.

PROGNOSIS

Risk for psychosis was 10.4% (95%CI: 5.8%-18.1%) at 6 months, 20% (95%CI: 15%-26%) at 12 months, 23% (95%CI: 18%-29%) at 24 months and 23.3% (95%CI: 17.3%-30.7%) at ≥36 months.

INTERVENTIONS

There was not enough evidence to recommend one specific treatment (including cognitive behavioural therapy) over the others (including control conditions) to prevent the transition to psychosis in this population. Randomised controlled trials suggested that family interventions, cognitive remediation and fish oil supplementation may improve cognition, symptoms and functioning. At baseline, 30% of CHR-P adolescents were prescribed antipsychotics and 60% received psychotherapy.

CONCLUSIONS

It is possible to detect and formulate a group-level prognosis in adolescents at risk for psychosis. Future interventional research is required.

Machine Learning-Based Electroencephalographic Phenotypes of Schizophrenia and Major Depressive Disorder

Background: Psychiatric diagnosis is formulated by symptomatic classification; disease-specific neurophysiological phenotyping could help with its fundamental treatment. Here, we investigated brain phenotyping in patients with schizophrenia (SZ) and major depressive disorder (MDD) by using electroencephalography (EEG) and conducted machine-learning-based classification of the two diseases by using EEG components. Materials and Methods: We enrolled healthy controls (HCs) (n = 30) and patients with SZ (n = 34) and MDD (n = 33). An auditory P300 (AP300) task was performed, and the N1 and P3 components were extracted. Two-group classification was conducted using linear discriminant analysis (LDA) and support vector machine (SVM) classifiers. Positive and negative symptoms and depression and/or anxiety symptoms were evaluated. Results: Considering both the results of statistical comparisons and machine learning-based classifications, patients and HCs showed significant differences in AP300, with SZ and MDD showing lower N1 and P3 than HCs. In the sum of amplitudes and cortical sources, the findings for LDA with classification accuracy (SZ vs. HCs: 71.31%, MDD vs. HCs: 74.55%), sensitivity (SZ vs. HCs: 77.67%, MDD vs. HCs: 79.00%), and specificity (SZ vs. HCs: 64.00%, MDD vs. HCs: 69.67%) supported these results. The SVM classifier showed reasonable scores between SZ and HCs and/or MDD and HCs. The comparison between SZ and MDD showed low classification accuracy (59.71%), sensitivity (65.08%), and specificity (54.83%). Conclusions: Patients with SZ and MDD showed deficiencies in N1 and P3 components in the sum of amplitudes and cortical sources, indicating attentional dysfunction in both early and late sensory/cognitive gating input. The LDA and SVM classifiers in the AP300 are useful to distinguish patients with SZ and HCs and/or MDD and HCs.

P300 amplitude attenuation in high risk and early onset psychosis youth

Little research has investigated the use of electrophysiological biomarkers in childhood and adolescence to distinguish early onset psychosis and the clinical high risk state. The P300 evoked potential is a robust neurophysiological marker of schizophrenia that is dampened in patients with schizophrenia and, less consistently, in those with affective psychoses and those at clinical high risk for psychosis (CHR). How it may differ between patients with psychotic disorders (PS) and CHR is less studied, especially in youth. The current study compared P300 activity among children and adolescents, aged 5-18 years, at CHR (n = 43), with PS (n = 28), and healthy controls (HC; n = 24). Participants engaged in an auditory event-related potential (ERP) task to elicit a P300 response and completed clinical interviews to verify symptoms and diagnoses. Linear regression analyses revealed a decrease in P300 amplitude with increased severity of psychotic symptoms. PS participants showed a diminished P300 response compared to those at CHR and HC, particularly among adolescents aged 13-18. This response was most evident at centroparietal and parietal locations in the right hemisphere. The findings suggest that high risk and psychotic symptomatology is linked to attenuated parietal P300 activity in youth as young as 13 years. Further exploration of the P300 as a biomarker for psychosis in very young patients could inform tailored, appropriate interventions at early stages of disease progression. Future research should evaluate whether specific phenotypic and genotypic characteristics are differentially associated with neurophysiological biomarkers and whether P300 attenuation in CHR youth can predict later symptom severity.

Neurobiological approaches to the study of clinical and genetic high risk for developing psychosis

Research on neurobiological impairments in clinical and genetic high risk for developing psychosis individuals (CHR) has identified several brain abnormalities that impact both brain structure and function. The current review will discuss research examining brain abnormalities in clinical and genetic high risk for psychosis using magnetic resonance imaging (MRI) focusing on structural brain abnormalities, diffusion tensor imaging (DTI) focusing on the integrity of white matter tracks, functional MRI focusing on functional brain abnormalities, and EEG and event related potential (ERP) methodologies focusing on indices of cognitive dysfunction in CHR. Studies conducted across these different methodologies sought to identify brain regions and brain processes that would distinguish between those high risk individuals who converted to psychosis versus those who did not. In addition, in some of the studies, the distinction was made between individuals who converted to psychosis, those who did not, and those individuals who remained clinically symptomatic while not converting to psychosis. The brain regions most often identified as abnormal in this subject group were the brain areas often found abnormal in schizophrenia, including frontal and temporal regions. Similarly, several cognitive processes often found to be abnormal in schizophrenia have been also found impaired in CHR.

Emotion Processing by ERP Combined with Development and Plasticity

Emotions important for survival and social interaction have received wide and deep investigations. The application of the fMRI technique into emotion processing has obtained overwhelming achievements with respect to the localization of emotion processes. The ERP method, which possesses highly temporal resolution compared to fMRI, can be employed to investigate the time course of emotion processing. The emotional modulation of the ERP component has been verified across numerous researches. Emotions, described as dynamically developing along with the growing age, have the possibility to be enhanced through learning (or training) or to be damaged due to disturbances in growth, which is underlain by the neural plasticity of emotion-relevant nervous systems. And mood disorders with typical symptoms of emotion discordance probably have been caused by the dysfunctional neural plasticity.