Automatic auditory processing features in distinct subtypes of patients at clinical high risk for psychosis: Forecasting remission with mismatch negativity

Altered theta band and theta/beta ratio in mismatch negativity associate with treatment effect in schizophrenia with auditory hallucinations

Evidence suggests that attenuated mismatch negative (MMN) waves have a close link to auditory verbal hallucinations (AVH) and their clinical outcomes, especially impaired neural oscillations such as θ, β representing attentional control. In current study, thirty patients with schizophrenia and AVH (SZ) and twenty-nine healthy controls (HC) underwent multi-feature MMN paradigm measurements including frequency and duration deviant stimuli (fMMN and dMMN). Clinical symptoms and MMN paradigm were followed up among SZ group after 8-week treatment. Results demonstrated that hallucinating patients exhibited attenuated dMMN amplitudes across Fz (p = 0.010), F1 (p = 0.020) and F2 (p = 0.014) electrodes, which were trendily recovered after treatment. Meanwhile, θ band and TBR at frontal fMMN and right temporal dMMN were significantly reduced in SZs. After treatment, SZs showed reduced scores of Hoffman's Auditory Hallucinations Rating Scale (AHRS), with a remarkable recovery in right temporal TBR of dMMN (p = 0.042) and a trending change in frontal TBR of fMMN (p = 0.090). The β band was decreased in dMMN (p = 0.035) by time. Additionally, P3 scores of Positive and Negative Syndrome Scale (PANSS) were negatively correlated with θ band of fMMN at baseline. Baseline scores of AHRS negatively predicted changes of dMMN amplitude after treatment, and changes of β band in left temporal dMMN predicted the reduction in scores of PANSS negative scale. These findings supported that deficits in θ oscillation and TBR during auditory attention process were crucial to clinical progression of schizophrenia with AVH.

Investigating the disconnection between cytokine and symptom clusters in clinical high risk populations: Towards a comprehensive cross-dimensional analysis

OBJECTIVE

Clustering individuals at the Clinical High-Risk(CHR) stage of psychosis often relies on single dimensions, and the independence or overlap of clustering results across different dimensions lacks sufficient evidence. Additionally, it remains unclear whether combining different dimensions-such as biological markers(e.g., cytokines) and symptomatic dimensions-can enhance predictive efficacy.

METHODS

This study included 370 individuals with CHR and conducted a three-year follow-up, 50 CHR individuals transitioned to psychosis. The participants underwent thorough symptom assessments, encompassing both clinical symptoms and cognitive impairments. Baseline measurements of eight cytokines were obtained. Latent Class Analysis(LCA) was employed to construct clusters based on both symptom profiles and cytokine levels separately. Survival analysis was utilized to explore differences in conversion rates among different clusters.

RESULTS

The LCA determined the selection of the four-cluster solution for symptoms, cytokines, and the integrated clusters. Symptom-Cluster-2 exhibited the most severe clinical symptoms and cognitive impairments, while Symptom-Cluster-4 displayed the mildest clinical symptoms and cognitive impairments. Cytokine-Cluster-1 was characterized by the highest levels of inflammatory cytokines, excluding vascular endothelial growth factor, whereas Symptom-Cluster-4 exhibited the lowest levels of cytokines. The clusters identified based on symptoms and cytokines showed substantial inconsistency. Survival analysis comparing conversion rates across four clusters revealed no significant difference in symptom(χ2 = 6.731, p = 0.081) and cytokine(χ2 = 7.139, p = 0.068) clusters but was significant in integrated clusters(χ2 = 9.234, p = 0.026).

CONCLUSION

The study emphasizes the distinct perspectives on psychosis risk offered by symptom and cytokine dimensions, advocating for the integration of these dimensions in a cross-modal approach to enhance predictive accuracy.

What Do Mismatch Negativity (MMN) Responses Tell Us About Tinnitus?

Due to the heterogeneous causes, symptoms and associated comorbidities with tinnitus, there remains an unmet need for a clear biomarker of tinnitus presence. Previous research has suggested a "final pathway" of tinnitus presence, which occurs regardless of the specific mechanisms that resulted in alterations of auditory predictions and, eventually, tinnitus perception. Predictive inference mechanisms have been proposed as the possible basis for this final unifying pathway. A commonly used measure of prediction violation is mismatch negativity (MMN), an electrical potential generated in response to most stimuli that violate an established regularity. This narrative review discusses 16 studies comparing MMN between tinnitus and non-tinnitus groups. Methods varied considerably, including type of deviant, type of paradigm and carrier frequency. A minority of studies matched groups for age, sex and hearing, with few measuring hyperacusis. Frequency deviants were the most widely studied; at frequencies remote from tinnitus, MMN was consistently smaller in tinnitus groups, though hyperacusis or altered distress or attention could not be ruled out as explanatory factors. Few studies have used tinnitus-related frequencies; these showed larger MMN to upward frequency deviants above the tinnitus frequency, and larger MMN to upward intensity deviants at or close to the tinnitus frequency. However, the latter appears a correlate of hyperacusis rather than tinnitus, and tinnitus groups without hyperacusis instead show larger MMN to downward intensity deviants than controls. Other factors that affect MMN amplitudes included age, attention, and the specific characteristics of the range of stimuli across a particular experiment paradigm. As such, MMN cannot presently be considered a specific biomarker of tinnitus, but showed potential to objectively characterise a number of auditory processing traits relevant to tinnitus and hyperacusis.

Dissociable Default Mode Network Connectivity Patterns Underlie Distinct Symptoms in Psychosis Risk

The Clinical High Risk (CHR) stage of psychosis is characterized by subthreshold symptoms of schizophrenia including negative symptoms, dysphoric mood, and functional deterioration. Hyperconnectivity of the default-mode network (DMN) has been observed in early schizophrenia, but the extent to which hyperconnectivity is present in CHR, and the extent to which such hyperconnectivity may underlie transdiagnostic symptoms, is not clear. As part of the Shanghai At-Risk for Psychosis (SHARP) program, resting-state fMRI data were collected from 251 young adults (158 CHR and 93 controls, M = 18.72, SD = 4.68, 129 male). We examined functional connectivity of the DMN by performing a whole-brain seed-to-voxel analysis with the MPFC as the seed. Symptom severity across a number of dimensions, including negative symptoms, positive symptoms, and affective symptoms were assessed. Compared to controls, CHRs exhibited significantly greater functional connectivity (p < 0.001 uncorrected) between the MPFC and 1) other DMN nodes including the posterior cingulate cortex (PCC), and 2) auditory cortices (superior and middle temporal gyri, STG/MTG). Furthermore, these two patterns of hyperconnectivity were differentially associated with distinct symptom clusters. Within CHR, MPFC-PCC connectivity was significantly correlated with anxiety (r= 0.23, p=0.006), while MPFC-STG/MTG connectivity was significantly correlated with negative symptom severity (r=0.26, p=0.001). Secondary analyses using item-level symptom scores confirmed a similar dissociation. These results demonstrate that two dissociable patterns of DMN hyperconnectivity found in the CHR stage may underlie distinct dimensions of symptomatology.

Neurophysiological Models in Individuals at Clinical High Risk for Psychosis: Using Translational EEG Paradigms to Forecast Psychosis Risk and Resilience

Over the last several decades, there have been major research efforts to improve the identification of youth and young adults at clinical high-risk for psychosis (CHR-P). Among individuals identified as CHR-P based on clinical criteria, approximately 20% progress to full-blown psychosis over 2-3 years and 30% achieve remission. In more recent years, neurophysiological measures with established sensitivity to schizophrenia have gained traction in the study of CHR-P and its range of clinical outcomes, with the goal of identifying specific biomarkers that precede psychosis onset that 7 chapter, we review studies examining several translational electroencephalography (EEG) and event-related potential (ERP) measures, which have known sensitivity to schizophrenia and reflect abnormal sensory, perceptual, and cognitive processing of task stimuli, as predictors of future clinical outcomes in CHR-P individuals. We discuss the promise of these EEG/ERP biomarkers of psychosis risk, including their potential to provide (a) translational bridges between human studies and animal models focused on drug development for early psychosis, (b) target engagement measures for clinical trials, and (c) prognostic indicators that could enhance personalized treatment planning.

Intact Mismatch Negativity Responses in Clinical High Risk for Psychosis and First-Episode Psychosis: Evidence From Source-Reconstructed Event-Related Fields and Time-Frequency Data

BACKGROUND

This study examined whether mismatch negativity (MMN) responses are impaired in participants at clinical high risk for psychosis (CHR-P) and patients with first-episode psychosis (FEP) and whether MMN deficits predict clinical outcomes in CHR-Ps.

METHODS

Magnetoencephalography data were collected during a duration-deviant MMN paradigm for a group of 116 CHR-P participants, 33 FEP patients (15 antipsychotic-naïve), clinical high risk negative group (n = 38) with substance abuse and affective disorder, and 49 healthy control participants. Analysis of group differences of source-reconstructed event-related fields as well as time-frequency and intertrial phase coherence focused on the bilateral Heschl's gyri and bilateral superior temporal gyri.

RESULTS

Significant magnetic MMN responses were found across participants in the bilateral Heschl's gyri and bilateral superior temporal gyri. However, MMN amplitude as well as time-frequency and intertrial phase coherence responses were intact in CHR-P participants and FEP patients compared with healthy control participants. Furthermore, MMN deficits were not related to persistent attenuated psychotic symptoms or transitions to psychosis in CHR-P participants.

CONCLUSIONS

Our data suggest that magnetic MMN responses in magnetoencephalography data are not impaired in early-stage psychosis and may not predict clinical outcomes in CHR-P participants.

Comprehensive review of multidimensional biomarkers in the ShangHai At Risk for Psychosis (SHARP) program for early psychosis identification

Psychosis is recognized as one of the largest contributors to nonfatal health loss, and early identification can largely improve routine clinical activity by predicting the psychotic course and guiding treatment. Clinicians have used the clinical high-risk for psychosis (CHR) paradigm to better understand the risk factors that contribute to the onset of psychotic disorders. Clinical factors have been widely applied to calculate the individualized risks for conversion to psychosis 1-2 years later. However, there is still a dearth of valid biomarkers to predict psychosis. Biomarkers, in the context of this paper, refer to measurable biological indicators that can provide valuable information about the early identification of individuals at risk for psychosis. The aim of this paper is to critically review studies assessing CHR and suggest possible biomarkers for application of prediction. We summarized the studies on biomarkers derived from the findings of the ShangHai at Risk for Psychosis (SHARP) program, including those that are considered to have the most potential. This comprehensive review was conducted based on expert opinions within the SHARP research team, and the selection of studies and results presented in this paper reflects the collective expertise of the team in the field of early psychosis identification. The three dimensions with potential candidates include neuroimaging dimension of brain structure and function, electrophysiological dimension of event-related potentials (ERPs), and immune dimension of inflammatory cytokines and complement proteins, which proved to be useful in supporting the prediction of psychosis from the CHR state. We suggest that these three dimensions could be useful as risk biomarkers for treatment optimization. In the future, when available for the integration of multiple dimensions, clinicians may be able to obtain a comprehensive report with detailed information of psychosis risk and specific indications about preferred prevention.

Markers of muscarinic deficit for individualized treatment in schizophrenia

Recent clinical studies have shown that agonists at muscarinic acetylcholine receptors effectively reduce schizophrenia symptoms. It is thus conceivable that, for the first time, a second substance class of procholinergic antipsychotics could become established alongside the usual antidopaminergic antipsychotics. In addition, various basic science studies suggest that there may be a subgroup of schizophrenia in which hypofunction of muscarinic acetylcholine receptors is of etiological importance. This could represent a major opportunity for individualized treatment of schizophrenia if markers can be identified that predict response to procholinergic vs. antidopaminergic interventions. In this perspective, non-response to antidopaminergic antipsychotics, specific symptom patterns like visual hallucinations and strong disorganization, the presence of antimuscarinic antibodies, ERP markers such as mismatch negativity, and radiotracers are presented as possible in vivo markers of muscarinic deficit and thus potentially of response to procholinergic therapeutics. Finally, open questions and further research steps are outlined.