EEG microstates as biomarker for psychosis in ultra-high-risk patients

Abstract Resting-state EEG microstates are brief (50–100 ms) periods, in which the spatial configuration of scalp global field power remains quasi-stable before rapidly shifting to another configuration. Changes in microstate parameters have been described in patients with psychotic disorders. These changes have also been observed in individuals with a clinical or genetic high risk, suggesting potential usefulness of EEG microstates as a biomarker for psychotic disorders. The present study aimed to investigate the potential of EEG microstates as biomarkers for psychotic disorders and future transition to psychosis in patients at ultra-high-risk (UHR). We used 19-channel clinical EEG recordings and orthogonal contrasts to compare temporal parameters of four normative microstate classes (A–D) between patients with first-episode psychosis (FEP; n = 29), UHR patients with (UHR-T; n = 20) and without (UHR-NT; n = 34) later transition to psychosis, and healthy controls (HC; n = 25). Microstate A was increased in patients (FEP & UHR-T & UHR-NT) compared to HC, suggesting an unspecific state biomarker of general psychopathology. Microstate B displayed a decrease in FEP compared to both UHR patient groups, and thus may represent a state biomarker specific to psychotic illness progression. Microstate D was significantly decreased in UHR-T compared to UHR-NT, suggesting its potential as a selective biomarker of future transition in UHR patients.

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S150. EMOTIONAL BEHAVIOUR IN HIGH-RISK AND FIRST-EPISODE PSYCHOSIS

Schizophrenia Bulletin ◽

10.1093/schbul/sbaa031.216 ◽

2020 ◽

Vol 46 (Supplement_1) ◽

pp. S93-S93

Author(s):

Irina Falkenberg ◽

Huai-Hsuan Tseng ◽

Gemma Modinos ◽

Barbara Wild ◽

Philip McGuire ◽

...

Keyword(s):

High Risk ◽

Emotion Recognition ◽

Psychotic Disorders ◽

First Episode Psychosis ◽

First Episode ◽

Healthy Controls ◽

Emotional Faces ◽

Facial Movements ◽

Episode Psychosis ◽

Ultra High Risk

Abstract Background Studies indicate that people with schizophrenia and first-episode psychosis experience deficits in their ability to accurately detect and display emotions through facial expressions, and that functioning and symptoms are associated with these deficits. This study aims to examine how emotion recognition and facial emotion expression are related to functioning and symptoms in a sample of individuals at ultra-high risk, first-episode psychosis and healthy controls. Methods During fMRI, we combined the presentation of emotional faces with the instruction to react with facial movements predetermined and assigned. 18 patients with first-episode psychosis (FEP), 18 individuals at ultra high risk of psychosis (UHR) and 22 healthy controls (HCs) were examined while viewing happy, sad, or neutral faces and were instructed to simultaneously move the corners of their mouths either (a). upwards or (b). downwards, or (c). to refrain from movement. The subjects’ facial movements were recorded with an MR-compatible video camera. Results Neurofunctional and behavioral response to emotional faces were measured. Analyses have only recently commenced and are ongoing. Full results of the clinical and functional impact of behavioral and neuroimaging results will be presented at the meeting. Discussion Increased knowledge about abnormalities in emotion recognition and behaviour as well as their neural correlates and their impact on clinical measures and functional outcome can inform the development of novel treatment approaches to improve social skills early in the course of schizophrenia and psychotic disorders.

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Dysregulation of complement and coagulation pathways: emerging mechanisms in the development of psychosis

Molecular Psychiatry ◽

10.1038/s41380-021-01197-9 ◽

2021 ◽

Author(s):

Meike Heurich ◽

Melanie Föcking ◽

David Mongan ◽

Gerard Cagney ◽

David R. Cotter

Keyword(s):

High Risk ◽

Psychotic Disorder ◽

Psychotic Disorders ◽

Clinical Symptoms ◽

First Episode Psychosis ◽

Specific Protein ◽

First Episode ◽

Clinical High Risk ◽

Blood Proteins ◽

Episode Psychosis

AbstractEarly identification and treatment significantly improve clinical outcomes of psychotic disorders. Recent studies identified protein components of the complement and coagulation systems as key pathways implicated in psychosis. These specific protein alterations are integral to the inflammatory response and can begin years before the onset of clinical symptoms of psychotic disorder. Critically, they have recently been shown to predict the transition from clinical high risk to first-episode psychosis, enabling stratification of individuals who are most likely to transition to psychotic disorder from those who are not. This reinforces the concept that the psychosis spectrum is likely a central nervous system manifestation of systemic changes and highlights the need to investigate plasma proteins as diagnostic or prognostic biomarkers and pathophysiological mediators. In this review, we integrate evidence of alterations in proteins belonging to the complement and coagulation protein systems, including the coagulation, anticoagulation, and fibrinolytic pathways and their dysregulation in psychosis, into a consolidated mechanism that could be integral to the progression and manifestation of psychosis. We consolidate the findings of altered blood proteins relevant for progression to psychotic disorders, using data from longitudinal studies of the general population in addition to clinical high-risk (CHR) individuals transitioning to psychotic disorder. These are compared to markers identified from first-episode psychosis and schizophrenia as well as other psychosis spectrum disorders. We propose the novel hypothesis that altered complement and coagulation plasma levels enhance their pathways’ activating capacities, while low levels observed in key regulatory components contribute to excessive activation observed in patients. This hypothesis will require future testing through a range of experimental paradigms, and if upheld, complement and coagulation pathways or specific proteins could be useful diagnostic or prognostic tools and targets for early intervention and preventive strategies.

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Circulating lipids associate with future weight gain in individuals with an at-risk mental state and in first-episode psychosis

10.1101/2020.01.30.20019711 ◽

2020 ◽

Author(s):

Santosh Lamichhane ◽

Alex M. Dickens ◽

Partho Sen ◽

Heikki Laurikainen ◽

Jaana Suvisaari ◽

...

Keyword(s):

At Risk ◽

Weight Gain ◽

High Risk ◽

Psychotic Disorders ◽

First Episode Psychosis ◽

Molecular Signature ◽

First Episode ◽

Baseline Serum ◽

Average Life Span ◽

Episode Psychosis

AbstractPatients with schizophrenia have a lower than average life span, largely due to the increased prevalence of cardiometabolic co-morbidities. Identification of individuals with psychotic disorders with a high risk of rapid weight gain, and the associated development of metabolic complications, is an unmet need as regards public health. Here, we applied mass spectrometry-based lipidomics in a prospective study comprising 48 controls (CTR), 44 first-episode psychosis (FEP) patients and 22 individuals at clinical-high-risk (CHR) for psychosis, from two study centers (Turku/Finland and London/UK). Baseline serum samples were analyzed by lipidomics, while body mass index (BMI) was assessed at baseline and after 12 months. We found that baseline triacylglycerols with low double bond counts and carbon numbers were positively associated with the change in BMI at follow-up. In addition, a molecular signature comprised of two triacylglycerols (TG(48:0) and TG(45:0)), was predictive of weight gain in individuals with a psychotic disorder, with an area under the receiver operating characteristic curve (AUROC) of 0.74 (95% CI: 0.60–0.85). When independently tested in the CHR group, this molecular signature predicted said weight change with AUROC = 0.73 (95% CI: 0.61–0.83). We conclude that molecular lipids may serve as a predictor of weight gain in psychotic disorders in at-risk individuals, and may thus provide a useful marker for identifying individuals who are most prone to developing cardiometabolic co-morbidities.

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Basic symptoms and gray matter volumes of patients at clinical high risk for psychosis

Psychological Medicine ◽

10.1017/s0033291720001282 ◽

2020 ◽

pp. 1-9 ◽

Cited By ~ 1

Author(s):

Daniela Hubl ◽

Chantal Michel ◽

Frauke Schultze-Lutter ◽

Martinus Hauf ◽

Benno G. Schimmelmann ◽

...

Keyword(s):

High Risk ◽

Gray Matter ◽

First Episode ◽

Clinical High Risk ◽

Significant Group ◽

Basic Symptoms ◽

Conversion Rates ◽

Episode Psychosis ◽

Ultra High Risk ◽

Gray Matter Volumes

Abstract Background Clinical high-risk (CHR) for psychosis is indicated by ultra-high risk (UHR) and basic symptom (BS) criteria; however, conversion rates are highest when both UHR and BS criteria are fulfilled (UHR&BS). While BSs are considered the most immediate expression of neurobiological aberrations underlying the development of psychosis, research on neurobiological correlates of BS is scarce. Methods We investigated gray matter volumes (GMV) of 20 regions of interest (ROI) previously associated with UHR criteria in 90 patients from the Bern early detection service: clinical controls (CC), first-episode psychosis (FEP), UHR, BS and UHR&BS. We expected lowest GMV in FEP and UHR&BS, and highest volume in CC with UHR and BS in-between. Results Significantly, lower GMV was detected in FEP and UHR&BS patients relative to CC with no other significant between-group differences. When ROIs were analyzed separately, seven showed a significant group effect (FDR corrected), with five (inferior parietal, medial orbitofrontal, lateral occipital, middle temporal, precuneus) showing significantly lower GM volume in the FEP and/or UHR&BS groups than in the CC group (Bonferroni corrected). In the CHR group, only COGDIS scores correlated negatively with cortical volumes. Conclusions This is the first study to demonstrate that patients who fulfill both UHR and BS criteria – a population that has been associated with higher conversion rates – exhibit more severe GMV reductions relative to those who satisfy BS or UHR criteria alone. This result was mediated by the BS in the UHR&BS group, as only the severity of BS was linked to GMV reductions.

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Facial affect recognition in individuals at clinical high risk for psychosis

The British Journal of Psychiatry ◽

10.1192/bjp.bp.107.039784 ◽

2008 ◽

Vol 192 (1) ◽

pp. 67-68 ◽

Cited By ~ 121

Author(s):

Jean Addington ◽

David Penn ◽

Scott W. Woods ◽

Donald Addington ◽

Diana O. Perkins

Keyword(s):

High Risk ◽

Facial Affect ◽

First Episode ◽

Affect Recognition ◽

Facial Affect Recognition ◽

Clinical High Risk ◽

Identification Task ◽

Episode Psychosis ◽

Patient Groups ◽

Better Than

SummaryFacial affect discrimination and identification were assessed in 86 clinical high-risk individuals and compared with 50 individuals with first-episode psychosis, 53 with multiepisode schizophrenia and 55 non-psychiatric controls. On the identification task the non-psychiatric controls performed significantly better than all other groups, and on discrimination significantly better than both patient groups. Deficits in facial affect recognition appear to be present before the onset of psychosis and may be a vulnerability marker.

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Aripiprazole for Drug-Naive or Antipsychotic-Short-Exposure Subjects With Ultra-High Risk State and First-Episode Psychosis

Journal of Clinical Psychopharmacology ◽

10.1097/jcp.0b013e31827cb017 ◽

2013 ◽

Vol 33 (1) ◽

pp. 18-23 ◽

Cited By ~ 11

Author(s):

Chen-Chung Liu ◽

Yi-Ling Chien ◽

Ming H. Hsieh ◽

Tzung-Jeng Hwang ◽

Hai-Gwo Hwu ◽

...

Keyword(s):

High Risk ◽

First Episode Psychosis ◽

Short Exposure ◽

First Episode ◽

Episode Psychosis ◽

Ultra High Risk ◽

Drug Naïve

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Prediction of transition from ultra-high risk to first-episode psychosis using a probabilistic model combining history, clinical assessment and fatty-acid biomarkers

Translational Psychiatry ◽

10.1038/tp.2016.170 ◽

2016 ◽

Vol 6 (9) ◽

pp. e897-e897 ◽

Cited By ~ 38

Author(s):

S R Clark ◽

B T Baune ◽

K O Schubert ◽

S Lavoie ◽

S Smesny ◽

...

Keyword(s):

Fatty Acid ◽

High Risk ◽

Clinical Assessment ◽

Probabilistic Model ◽

First Episode Psychosis ◽

First Episode ◽

Model Combining ◽

Episode Psychosis ◽

Ultra High Risk ◽

Fatty Acid Biomarkers

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Association Between Circulating Lipids and Future Weight Gain in Individuals With an At-Risk Mental State and in First-Episode Psychosis

Schizophrenia Bulletin ◽

10.1093/schbul/sbaa087 ◽

2020 ◽

Cited By ~ 1

Author(s):

Santosh Lamichhane ◽

Alex M Dickens ◽

Partho Sen ◽

Heikki Laurikainen ◽

Faith Borgan ◽

...

Keyword(s):

At Risk ◽

Weight Gain ◽

High Risk ◽

Psychotic Disorders ◽

First Episode Psychosis ◽

Molecular Signature ◽

First Episode ◽

Baseline Serum ◽

Average Life Span ◽

Episode Psychosis

Abstract Patients with schizophrenia have a lower than average life span, largely due to the increased prevalence of cardiometabolic comorbidities. There is an unmet public health need to identify individuals with psychotic disorders who have a high risk of rapid weight gain and who are at risk of developing metabolic complications. Here, we applied mass spectrometry-based lipidomics in a prospective study comprising 48 healthy controls (CTR), 44 first-episode psychosis (FEP) patients, and 22 individuals at clinical high risk (CHR) for psychosis, from 2 study centers (Turku, Finland and London, UK). Baseline serum samples were analyzed using lipidomics, and body mass index (BMI) was assessed at baseline and after 12 months. We found that baseline triacylglycerols (TGs) with low double-bond counts and carbon numbers were positively associated with the change in BMI at follow-up. In addition, a molecular signature comprised of 2 TGs (TG[48:0] and TG[45:0]) was predictive of weight gain in individuals with a psychotic disorder, with an area under the receiver operating characteristic curve (AUROC) of 0.74 (95% CI: 0.60–0.85). When independently tested in the CHR group, this molecular signature predicted said weight change with AUROC = 0.73 (95% CI: 0.61–0.83). We conclude that molecular lipids may serve as a predictor of weight gain in psychotic disorders in at-risk individuals and may thus provide a useful marker for identifying individuals who are most prone to developing cardiometabolic comorbidities.

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Using genetic, cognitive and multi-modal neuroimaging data to identify ultra-high-risk and first-episode psychosis at the individual level

Psychological Medicine ◽

10.1017/s003329171300024x ◽

2013 ◽

Vol 43 (12) ◽

pp. 2547-2562 ◽

Cited By ~ 65

Author(s):

W. Pettersson-Yeo ◽

S. Benetti ◽

A. F. Marquand ◽

F. Dell‘Acqua ◽

S. C. R. Williams ◽

...

Keyword(s):

High Risk ◽

First Episode Psychosis ◽

First Episode ◽

Support Vector ◽

Single Subject ◽

Individual Level ◽

Episode Psychosis ◽

Ultra High Risk ◽

The Individual ◽

Cognitive Data

BackgroundGroup-level results suggest that relative to healthy controls (HCs), ultra-high-risk (UHR) and first-episode psychosis (FEP) subjects show alterations in neuroanatomy, neurofunction and cognition that may be mediated genetically. It is unclear, however, whether these groups can be differentiated at single-subject level, for instance using the machine learning analysis support vector machine (SVM). Here, we used a multimodal approach to examine the ability of structural magnetic resonance imaging (sMRI), functional MRI (fMRI), diffusion tensor neuroimaging (DTI), genetic and cognitive data to differentiate between UHR, FEP and HC subjects at the single-subject level using SVM.MethodThree age- and gender-matched SVM paired comparison groups were created comprising 19, 19 and 15 subject pairs for FEPversusHC, UHRversusHC and FEPversusUHR, respectively. Genetic, sMRI, DTI, fMRI and cognitive data were obtained for each participant and the ability of each to discriminate subjects at the individual level in conjunction with SVM was tested.ResultsSuccessful classification accuracies (p < 0.05) comprised FEPversusHC (genotype, 67.86%; DTI, 65.79%; fMRI, 65.79% and 68.42%; cognitive data, 73.69%), UHRversusHC (sMRI, 68.42%; DTI, 65.79%), and FEPversusUHR (sMRI, 76.67%; fMRI, 73.33%; cognitive data, 66.67%).ConclusionsThe results suggest that FEP subjects are identifiable at the individual level using a range of biological and cognitive measures. Comparatively, only sMRI and DTI allowed discrimination of UHR from HC subjects. For the first time FEP and UHR subjects have been shown to be directly differentiable at the single-subject level using cognitive, sMRI and fMRI data. Preliminarily, the results support clinical development of SVM to help inform identification of FEP and UHR subjects, though future work is needed to provide enhanced levels of accuracy.

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