Trait, staging, and state markers of psychosis based on functional alteration of salience-related networks in the high-risk, first episode, and chronic stages

Objective: Salience is a critical mechanism for survival in animals, the alteration of which is postulated to play key role in psychosis, including the hippocampus-midbrain-striatal and anterior cingulate cortex (ACC)-insular (salience network: SN) systems. However, how these two systems contribute to the psychosis traits, staging, and state is unknown. Methods: Eight scanners at seven sites recruited 29 ultra-high-risk (UHR) individuals and 25 matched healthy controls (HC), 81 first-episode psychosis (FEP) patients and 109 HC, and 99 chronic psychosis (ChrP) patients and 145 HC. Resting-state functional MRI data which were intensively denoised and site effect-removed revealed the two systems as comprising five networks: the medial temporal lobe network (MTLN), midbrain-thalamic and striatal parts of the basal ganglia network (BGN-MbThal and BGN-Str), and ACC and insular parts of the SN (SN-ACC and SN-Ins). Group difference and correlation with positive symptom of network measures were performed in each psychosis stage. Results: Connectivity within the BGN-MbThal was reduced in FEP compared to HC (p<0.05, family-wise-error [FWE] corrected). Connectivity within the SN-ACC was reduced in UHR (p<0.05, FWE) and in FEP and ChrP at liberal thresholds, with effect size of UHR>FEP>ChrP. FEP showed increased brain-state instability among the five networks, and positive correlation between positive symptom and connectivity within and between the MTLN. The correlation was stronger in unmedicated than medicated, and in affective than non-affective psychosis patients (all p<0.05, FWE). Conclusions: Two salience-related systems were associated with psychosis traits, staging, and state. Refining these findings will lead to the development of clinically usable biomarkers.

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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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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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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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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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