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Ruas Resende, M. B., F. Agostinho, R. Nogueira, D. Cotovio, F. A. Silva, and R. Lousada. "Ultra-High-Risk that do not transition to psychosis. What happens?" European Psychiatry 67, S1 (April 2024): S737. http://dx.doi.org/10.1192/j.eurpsy.2024.1533.
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IntroductionSpeaking prospectively we use the concept of “at risk mental state” (ARMS) to describe the state in which a person has a heightened risk of developing a psychotic disorder. Young people who are experiencing ARMS can be more precisely defined as being at ultra-high-risk of psychosis using a specific set of criteria known as the UHR criteria.ObjectivesTo clarify the concept of ultra-high-risk individuals and to characterize the clinical and functional characteristics and general psychopathology of those individuals that do not transition to psychosis during the follow-up period.MethodsResearch on UpToDate using the terms “Ultra-High-Risk”; “psychosis”, “transition”.ResultsRecent literature has suggested that less than 30% of those who meet established criteria for being at Clinical-High-Risk of psychosis (CHR-P) go on to develop a psychotic illness. It is therefore of crucial importance and relevance to assess and clarify what happens to high-risk individuals who do not transition to psychosis, who make up the vast majority.One of the most recent studies (NAPLS-2) that encompassed 764 of CHR-P individuals who were followed for 2 years, concluded that 278 did not transition to psychosis during the follow-up period. Three clinical outcomes were recorded: 1 group had experienced a psychopathological remission (39.57%); the other kept symptomatic but not currently meeting criteria for a prodromal risk syndrome (33.45%); the third group had a prodromal progression (26.98%). The study concluded among others that although the remission group had improved social functioning at 2 years compared with the other groups, they were still functioning below the healthy control group.Another meta-analysis that included a total of 2756 CHR-P individuals with a mean duration of follow-up of 30.7 months evaluated several clinical outcomes in CHR-P that didn’t transitioned to psychosis and between CHR-P non-transitioning versus those transitioning to psychosis. It concluded that CHR-P that do not transition to psychosis have an overall improvement of symptoms (APS, negative, depressive) and functioning at follow-up compared to baseline.ConclusionsThe occurrence of a first psychotic episode is often devastating for the patient and their family, especially given its usual onset in adolescence and early adulthood. This is a critical period in the individual’s development as a person, and disorders at this stage can threaten the potential for a productive and inclusive adult life. Studies have suggested that less than 30% of individuals classified as UHR actually develop a psychotic disorder.However, little is known about the individuals belonging to this group who do not transition to psychosis. We therefore consider it is relevant to clarify the clinical and functional outcomes of this group of individuals.Disclosure of InterestNone Declared
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Richter, Anja, Evangelos Vassos, Matthew J. Kempton, Mark van der Gaag, Lieuwe de Haan, Barnaby Nelson, Anita Riecher-Rössler, et al. "S175. CLINICAL OUTCOMES IN PEOPLE AT HIGH RISK FOR PSYCHOSIS RELATED TO INTERACTIONS BETWEEN POLYGENIC RISK SCORES AND CHILDHOOD ADVERSITY." Schizophrenia Bulletin 46, Supplement_1 (April 2020): S104. http://dx.doi.org/10.1093/schbul/sbaa031.241.
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Abstract Background Genetic vulnerability to psychosis is polygenic, involving multiple genes with small individual effects (Psychiatric Genomics Consortium (PGC), 2014). The risk of psychosis is also related to environmental factors, such as childhood trauma (Lardinois et al, 2011). Although the onset of psychosis is thought to result from the interaction of genetic and environmental risk factors (Walker & Diforio, 1997), the extent to which the influence of childhood trauma depends on genetic susceptibility remains unclear. We sought to address this issue in a large prospective study of people at clinical high risk (CHR) for psychosis. These individuals present with psychotic and affective symptoms, and are at increased risk of developing both schizophreniform and affective psychoses. Methods We studied subjects of European ancestry, drawn from EU-GEI, a large multi-centre prospective study of people at CHR for psychosis. At baseline, DNA was obtained from subjects who met the CAARMS criteria for the CHR state (n=266) and healthy controls (HC; n=42). Childhood trauma was assessed using the childhood trauma questionnaire (CTQ), which comprises 5 subdomains: emotional abuse, physical abuse, sexual abuse, physical neglect, and emotional neglect. Polygenic risk scores (PRSs) for schizophrenia (SCZ), bipolar disorder (BD) and major depressive disorder (MDD) were constructed separately, using results from meta-analyses by the corresponding Disorder Working Groups of the PGC. The CHR subjects were clinically monitored for up to 5 years and clinical outcomes were assessed in terms of transition to psychosis (as defined by the CAARMS), remission from the CHR state (subject no longer meets CAARMS inclusion criteria) and level of functioning (GAF Disability Scale). Logistic regression models were used to investigate the association between each PRSs and childhood trauma as predictors of transition and remission, adjusted by population stratification using the first 10 principal components, age, sex and site. All findings are reported at p<0.017, Bonferroni-corrected for the 3 PRSs. Results Within the CHR sample, the onset of psychosis during follow up was related to interactions between the BD PRS and the total childhood trauma score (OR=0.959, 95% CI 0.930–0.988, p=0.006), and between the BD PRS and physical abuse (OR=0.787, 95% CI 0.689–0.900, p<0.001). Remission from the CHR state was related to an interaction between the SCZ PRS and childhood sexual abuse (OR: 1.110, 95% CI 1.004–1.226, p=0.041). Discussion These data indicate that clinical outcomes in CHR subjects are related to interactions between the polygenic risk for psychotic disorders and childhood adversity. The measurement of interactions between genomic and environmental risk factors may help to predict individual outcomes in people at high risk in a clinical setting.
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Omelchenko, M. "Premorbid of depressive youth at clinical high-risk for psychosis." European Psychiatry 65, S1 (June 2022): S683. http://dx.doi.org/10.1192/j.eurpsy.2022.1757.
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Introduction Early detection of psychosis is a promising area in preventive psychiatry. The use of early intervention can prevent the first episode psychosis and improve outcomes. Objectives Identification of premorbid features of depressive patients at clinical high risk for psychosis (CHR) comparing with depressive patients without CHR in order to improve early recognition of the psychotic process. Methods 219 young depressive in-patients with CHR criteria for SOPS with attenuated positive and attenuated negative symptoms and 52 young depressive in-patients without CHR were examined. Presence of obstetric complications, neurodevelopmental deviance, neurological and psychiatric signs at the premorbid stage, and the level of premorbid functioning on the PAS were examined. Results It has been established that depressive patients at CHR and without CHR had some obstetric complications (57.5% and 40.4%, respectively). Neurodevelopmental deviance in the first year of live was in 57.5% patients with CHR. At the age of 3-5 sleep disorders, ADHD and phobias were more common in patients at CHR than without it (58.8% and 32.7%, p=0.014). In pubertal, patients at CHR were more likely to show depression symptoms, obsessions, and aggression - 90.4% versus 76.9% (p=0.029). On the PAS scale, a decrease of the level of premorbid functioning has been observed in two groups of patients with and without CHR from the age of 12: from 12 to 15 years, 0.4 and 0.3 (p=0.004), from 16 to 18 years, 0.47 and 0.37 (p 0.001). Conclusions Premorbid functioning were worst in patients with CHR, which indicates the possibility of early clinical detection of psychosis. Disclosure No significant relationships.
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Fusar-Poli, Paolo. "The Clinical High-Risk State for Psychosis (CHR-P), Version II." Schizophrenia Bulletin 43, no. 1 (January 2017): 44–47. http://dx.doi.org/10.1093/schbul/sbw158.
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Cleusix, Martine, Ines Khadimallah, Elodie Toffel, Paul Klauser, Kim Q. Do, Kerstin von Plessen, Philippe Conus, and Alessandra Solida. "S69. CLINICAL HIGH RISK STATE: STRATIFICATION BASED ON CLINICAL PROFILE AND REDOX STATUS." Schizophrenia Bulletin 46, Supplement_1 (April 2020): S60. http://dx.doi.org/10.1093/schbul/sbaa031.135.
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Abstract Background The Clinical High Risk state (CHR) concept was implemented to promote the early detection of young help-seeking patients with higher risk of psychotic transition. This category is based on specific clinical criteria (EPA, 2015) and require narrow frequency/duration ratings of subclinical positive psychotic symptoms to allow its definition. Prevalence of CHR “category” appears nevertheless rare in help-seeking young people and the rate of psychotic transition of CHR state is lower than predicted by early studies. Therefore, the binary outcome of transition to psychosis proposed by the “CHR model” actually fails to be an efficient marker to stratify, in neurobiological studies, people with different psychopathological trajectories, notably those who develop psychosis from those who do not. In order to rely on a vulnerability model for schizophrenic psychosis more sensitive to psychosocial functioning and negative dimension, we study prospectively with three years of follow-up a population of help-seekers addressed for clinical suspicion of prodromal state of psychosis. We aimed here to identify subgroups of patients in a sample of subclinical psychotic states using psychological and cognitive outcomes as profiling criteria, focusing not only on transition but also on psychosocial functioning as main outcome. Methods A total of 32 help-seeking adolescents and young adults aged 14 to 35 were referred by health care providers for a specialized evaluation in case of suspicion of a prodromal psychotic state and/or detected by the French version of the Prodromal Questionnaire (PQ-16; cut-off 6/16). Their CHR status was assessed by the Structured Interview for Psychosis-Risk Syndromes (SIPS) and the Schizophrenia Proneness Instrument, Adult (SPI-A). Individuals included in the study presented either a CHR status, a subclinical CHR status or negative symptomatology. All subjects performed an additional neuropsychological battery and blood test for redox markers (Glutathione Peroxidase (GPx) and Glutathione Reductase (GR) activities) (Xin et al, 2016). Based on their clinical profile, we made a stratification of the patients using a Principal Component Analysis. Results Cognitive and psychological outcome stratification of all help-seekers revealed two subgroups (called group1 and group2) of patients with distinct profiles. Individuals in group1 (n=18) had greater levels of basic symptoms and general symptomatology. On the other hand, in group2 (n=14), individuals showed a weaker self-esteem and a lower rate of “living independently”. Cognitive scores for speed processing, attention, verbal learning and social cognition were significantly lower in group2 compared to group1. In addition, these cognitive outcomes were negatively correlated with negative symptoms only in group2. Analysis of redox markers revealed a positive correlation between GPx and GR activities in group1, a correlation disrupted in group2. Discussion Stratification of a cohort of young help-seekers with suspicion of prodromal psychosis, regardless of their CHR status, allowed us to distinguish two subgroups with different clinical profiles: group1 with higher levels of basic symptoms and general symptomatology, and group2 with weaker self-esteem, less autonomy and poorer neurocognition. In addition, analysis of redox markers revealed a redox dysregulation in patients with poorer cognitive profile. Considering the impact of neurocognitive impairment on functioning, special focus to patients of group2 is needed, mostly in clinical practice. Moreover, they might benefit of supplementation with antioxidant compounds such as NAC, which may improve cognitive deficits (Conus et al, 2018).
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Omelchenko, M. A. "Clinical High Risk Psychosis: Issues of Diagnostics and Therapy." Psychiatry 18, no. 2 (July 22, 2020): 82–91. http://dx.doi.org/10.30629/2618-6667-2020-18-2-82-91.
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The aim of the review: the analysis of modern Russian and foreign literature dedicated to the problem of determining diagnostic criteria for clinical high risk of psychosis (CHR-P) and outlining the therapeutic approaches based on the pathogenic mechanisms of their development. Material and method: the publications found by searching queries for keywords in Russian and English in the MEDLINE/PubMed and eLIBRARY databases for the time period from 2010 to 2020 were then analyzed. Conclusion: the review presents a modern definition of the CHR-P group, along with a clarification of individual diagnostic criteria, which include attenuated psychotic symptoms (APS), brief limited intermittent psychotic symptoms (BLIPS), genetic risk with deterioration of premorbid functioning, as well as basic symptoms (BS). We found heterogeneity of the CHR-P group with different levels of manifestation and outcomes and indicated the involvement of different pathogenic mechanisms in their formation. These findings determine the development of various approaches to treatment, which involve the assessment of the ratio of potential benefits and the risks of side effects. The obtained data, on the one hand, attest to the prospective viability of the therapeutic approach to the patients with CHR-P with the possibility of influencing the course of the disease, delaying its manifestation and improving long-term outcomes, and, on the other hand, the lack of universal standards of therapy at present. Tactics of treatment are determined basing on an individual approach to the patient with a comprehensive psychopathological assessment of complaints, clinical state and its dynamics.
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Lepock, Jennifer R., Romina Mizrahi, Michele Korostil, R. Michael Bagby, Elizabeth W. Pang, and Michael Kiang. "Event-Related Potentials in the Clinical High-Risk (CHR) State for Psychosis: A Systematic Review." Clinical EEG and Neuroscience 49, no. 4 (January 31, 2018): 215–25. http://dx.doi.org/10.1177/1550059418755212.
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There is emerging evidence that identification and treatment of individuals in the prodromal or clinical high-risk (CHR) state for psychosis can reduce the probability that they will develop a psychotic disorder. Event-related brain potentials (ERPs) are a noninvasive neurophysiological technique that holds promise for improving our understanding of neurocognitive processes underlying the CHR state. We aimed to systematically review the current literature on cognitive ERP studies of the CHR population, in order to summarize and synthesize the results, and their implications for our understanding of the CHR state. Across studies, amplitudes of the auditory P300 and duration mismatch negativity (MMN) ERPs appear reliably reduced in CHR individuals, suggesting that underlying impairments in detecting changes in auditory stimuli are a sensitive early marker of the psychotic disease process. There are more limited data indicating that an earlier-latency auditory ERP response, the N100, is also reduced in amplitude, and in the degree to which it is modulated by stimulus characteristics, in the CHR population. There is also evidence that a number of auditory ERP measures (including P300, MMN and N100 amplitudes, and N100 gating in response to repeated stimuli) can further refine our ability to detect which CHR individuals are most at risk for developing psychosis. Thus, further research is warranted to optimize the predictive power of algorithms incorporating these measures, which could help efforts to target psychosis prevention interventions toward those most in need.
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Poletti, Michele. "Early Intervention Services for youth at Clinical High-Risk for Psychosis: The Reggio Emilia At-Risk Mental State (ReARMS) experience." RIVISTA SPERIMENTALE DI FRENIATRIA 146, no. 3 (December 2022): 61–80. http://dx.doi.org/10.3280/rsf2022-003004.
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Between 2012-2017, 300 individuals completed the baseline assessment, 205 of them met criteria for CHR-P or First-Episode Psychosis, and 154 accepted the enrolment in the ReARMS for treatment and follow-up. Empirical contributions based on the ReARMS dataset involved the structure of assessment and intervention, the Italian validation of ad-hoc instruments of assessment, clinical features of enrolled individuals (anhedonia, aberrant salience, suicidality and metacognition) and longitudinal trajectories in terms of outcome and response to treatments. age between adolescence and young adulthood, being effective in intercepting an early and usually enduring psychopathological suffering, independently from the transition to psychosis. Rather than being rigidly focused on homotypic trajectories from CHR-P to psychosis, increasing evidence on heterotypic trajectories starting from CHR-P to multiple psychopathological outcomes suggest to update early intervention services toward increased organizational flexibility, for example in therapeutic options.
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Oliver, Dominic, Giulia Spada, Joaquim Radua, Philip McGuire, and Paolo Fusar-Poli. "M136. PSYCHOSIS POLYRISK SCORE (PPS): IMPROVING DETECTION OF INDIVIDUALS AT-RISK AND PREDICTION OF CLINICAL OUTCOMES." Schizophrenia Bulletin 46, Supplement_1 (April 2020): S187. http://dx.doi.org/10.1093/schbul/sbaa030.448.
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Abstract Background Primary prevention in Clinical High Risk for psychosis (CHR-P) can ameliorate the course of psychotic disorders. Further advancements of knowledge have been slowed by the standstill of the field, which is mostly attributed to its epidemiological weakness. This underlies the limited identification power for at-risk individuals and the relatively modest ability of CHR-P interviews to rule-in a state of risk for psychosis. One potential avenue for improving identification of individuals at risk for psychosis is a Psychosis Polyrisk Score (PPS) integrating genetic and non-genetic risk and protective factors for psychosis. The PPS hinges on recent findings that risk enrichment in CHR-P samples is accounted for by the accumulation of non-genetic factors e.g. parental and sociodemographic risk factors, perinatal risk factors, later risk factors, and antecedents. Methods A prototype of the PPS has been developed encompassing 26 non-genetic risk and protective factors, utilising Relative Risks (RR) from an umbrella review of risk and protective factors for psychosis onset in the general population. This was combined with prevalence data to ensure positive scores indicated increased psychosis risk and negative scores indicated decreased psychosis risk. To pilot this, patients referred for a CHR-P assessment (n=15) and healthy controls (n=66) were recruited and assessed with the PPS. Additionally, to investigate the range and distribution of these scores in the general population, 10,000,000 permutations were run utilising prevalence data to produce a simulated dataset. Results In the simulated general population data, scores ranged from -15 (least risk, equivalent RR = 0.03) to 39.5 (highest risk, RR = 8912.51). 50% of individuals had an RR < 1 (PPS < 0), 26.7% of individuals had an RR > 3 (PPS > 5), and 2.7% RR > 30 (PPS > 15). Patients referred for a CHR-P assessment had higher PPS scores (median=9, IQR=12.75) than healthy controls (median=-1.75, IQR=8.875). PPS scores in the simulated general population dataset (median=0, IQR=9.5) were similarly lower than patients. Discussion The PPS has potential for improving identification of individuals at risk for psychosis. Its distribution in a simulated general population is reflective of expected psychosis risk, with the vast majority of people not being at-risk and very few being at high risk. In addition to supplementing current assessments for CHR-P, this could be implemented at an earlier stage to stratify individuals based on psychosis risk and inform prognoses and clinical decision-making. This promise warrants further research to ascertain its prognostic accuracy and optimal thresholds for clinical intervention.
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Skuhareuskaya, M., and O. Skugarevsky. "Predictors of transition to psychosis in individuals at clinical high-risk for psychosis." European Psychiatry 41, S1 (April 2017): s838. http://dx.doi.org/10.1016/j.eurpsy.2017.01.1651.
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ObjectiveClinical high risk (CHR) for psychosis state is characterized by presence of potentially prodromal for schizophrenia symptoms. The aim of this study was to assess the predictors of transition to first psychotic episode.MethodsThe study included 123 CHR subjects. All the subjects were characterized by the presence of one of the group of criteria: (1) UHR criteria, (2) basic symptoms criteria and (3) negative symptoms and formal thought disorders (FTD). The presence of FTD in clinical high-risk individuals was assessed with methods of experimental pathopsychology. The mean length of follow-up was 26 months (SD 18). All subjects were males, mean age = 20.2 (SD: 2.1). We examined the subjects’ performance using the Cambridge automated neuropsychological test battery. We applied survival analyses to determine associations between a transition to psychosis and sociodemographic, clinical and neurocognitive parameters. To determine which items are the best predictors, Cox regression analyses were applied.ResultsThe psychosis developed in 39 subjects (31.7%). Global assessment of functioning, positive symptoms, blunted affect, social isolation, impaired role function, disorganizing/stigmatizing behavior, basic symptoms (thought pressure, unstable ideas of reference), neurocognitive parameters (visual memory and new learning, decision making, executive function) significantly influenced the transition to psychosis. A prediction model was developed and included unusual thought content (Wald = 12.386, P < 0.0001, HR = 2.996), perceptual abnormalities (Wald = 4.777, P = 0.029, HR = 1.43) and impaired role function (Wald = 1.425, P < 0.028, HR = 4.157).ConclusionClinical measures are important predictors for transition to psychosis in high-risk individuals.Disclosure of interestThe authors have not supplied their declaration of competing interest.
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Kotlicka-Antczak, Magdalena, Michał S. Karbownik, Konrad Stawiski, Agnieszka Pawełczyk, Natalia Żurner, Tomasz Pawełczyk, Dominik Strzelecki, and Paolo Fusar-Poli. "Short clinically-based prediction model to forecast transition to psychosis in individuals at clinical high risk state." European Psychiatry 58 (March 11, 2019): 72–79. http://dx.doi.org/10.1016/j.eurpsy.2019.02.007.
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AbstractObjective:The predictive accuracy of the Clinical High Risk criteria for Psychosis (CHR-P) regarding the future development of the disorder remains suboptimal. It is therefore necessary to incorporate refined risk estimation tools which can be applied at the individual subject level. The aim of the study was to develop an easy-to use, short refined risk estimation tool to predict the development of psychosis in a new CHR-P cohort recruited in European country with less established early detection services.Methods:A cohort of 105 CHR-P individuals was assessed with the Comprehensive Assessment of At Risk Mental States12/2006, and then followed for a median period of 36 months (25th-75th percentile:10–59 months) for transition to psychosis. A multivariate Cox regression model predicting transition was generated with preselected clinical predictors and was internally validated with 1000 bootstrap resamples.Results:Speech disorganization and unusual thought content were selected as potential predictors of conversion on the basis of published literature. The prediction model was significant (p < 0.0001) and confirmed that both speech disorganization (HR = 1.69; 95%CI: 1.39–2.05) and unusual thought content (HR = 1.51; 95%CI: 1.27–1.80) were significantly associated with transition. The prognostic accuracy of the model was adequate (Harrell’s c- index = 0.79), even after optimism correction through internal validation procedures (Harrell’s c-index = 0.78).Conclusions:The clinical prediction model developed, and internally validated, herein to predict transition from a CHR-P to psychosis may be a promising tool for use in clinical settings. It has been incorporated into an online tool available at:https://link.konsta.com.pl/psychosis. Future external replication studies are needed.
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Zhen, Mao, Qijing Bo, Qing Tian, Fang Dong, Xianbin Li, and Chuanyue Wang. "T37. PREPULSE INHIBITION IN UNAFFECTED SIBLINGS OF SCHIZOPHRENIA AND CLINICAL-HIGH RISK WITHOUT FAMILY HISTORY OF PSYCHOSIS." Schizophrenia Bulletin 46, Supplement_1 (April 2020): S245—S246. http://dx.doi.org/10.1093/schbul/sbaa029.597.
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Abstract Background It is reported that prepulse inhibition (PPI) deficiency of startle reflex in schizophrenia is associated with positive symptoms and is hereditary. In this study, the perceived spatial separation (PSS) induced-prepulse inhibition paradigm based on the priority effect effectively was used to explore PPI levels of genetically high-risk (GHR) of schizophrenia and clinical high risk (CHR) without family history of psychosis Methods We examined startle magnitude and PPI in38 CHR (No family history of psychosis), 28 GHR (Siblings or children of schizophrenia), and 44 healthy controls (HC). Modified acoustic PPI paradigm included PSS-PPI and perceived spatial co-location PPI (PSC-PPI) with inter-stimulus interval (ISI) of 60 or 120ms. The Structured Interview for Psychosis risk Syndromes (SIPS) and MATRICS Consensus Cognitive Battery (MCCB) was used to measure psychotic symptom and neuropsychological state of individuals Results Using gender, age, and smoking as covariates, Covariance analysis for modified PPI level results revealed that there were significant differences in PSSPPI60 (F = 6.25, p = 0.03) and PSSPI120 (F = 6.57, p = 0.03) paradigm between the three groups. Compared with HC, PSSPPI paradigm detected PPI defects of CHR individuals at 60ms ISI (F = 14.25, p ＜0.001) and 120ms ISI (F = 14.01, p ＜0.001). PPI deficiency was not detected in GHR individuals. PPI level in both groups were unrelated to demographics, clinical characteristics, and cognition. Using GLM analysis, the interaction between grouping and experimental paradigm had no significant effect on PPI level at 60ms (F = 1.88, P = 0.16) and 120ms (Z = 1.66, P = 0.19). Discussion It seems that mere heritability of psychosis is not enough to produce PPI defects, which may be related to the progression of psychosis
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Wei, Yanyan, Xiaochen Tang, Tingyu Zhang, Wenjun Su, Lihua Xu, Huiru Cui, Zhenying Qian, Tianhong Zhang, and Jijun Wang. "Reduced temporal activation during a verbal fluency test in clinical high risk of psychosis: a functional near-infrared spectroscopy-based study." General Psychiatry 35, no. 2 (April 2022): e100702. http://dx.doi.org/10.1136/gpsych-2021-100702.
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BackgroundClinical high risk (CHR) of psychosis is a state in which positive symptoms cause the subjects distress but do not approach a severity level that fulfils the criteria for a psychotic episode. CHR exhibits cognitive deficits; however, the underlying neurobiological mechanisms remain unclear. This study aimed to investigate whether brain activation measured by the levels of oxygenated hemoglobin (oxy-Hb) in CHR subjects could be correlated with cognitive deficits.MethodsFifty-eight CHR individuals who fulfilled the criteria for attenuated positive syndrome as specified in the Structured Interview for Prodromal Syndrome (SIPS) and the Scale of Prodromal Syndrome (SOPS) and 58 age- and sex-matched healthy participants were included in the study. All subjects completed the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) that includes tests measuring attention, verbal memory, verbal fluency, executive function, and general intelligence. Functional near-infrared spectroscopy (fNIRS) was used to measure the level of oxy-Hb in the dorsolateral prefrontal and frontotemporal cortices.ResultsWe observed significantly decreased oxy-Hb levels in channel 32 (located in the right superior temporal gyrus, rSTG)) within the CHR individuals compared with that in the healthy controls (HCs) (t=−3.44, Bonferroni-corrected p=0.002), indicating lower brain activity. A significant positive correlation was observed between task-related β values and working memory in the CHR group (r=0.35, p=0.008).ConclusionsThe brain activation of rSTG is abnormal among subjects at clinicial high risk for psychosis. This abnormality is probably associated with the neural mechanisms of deficits in the working memory during the early stage of psychosis.
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Kim, Ahra, Minji Ha, Taekwan Kim, Sunghyun Park, Silvia Kyungjin Lho, Sun-Young Moon, Minah Kim, and Jun Soo Kwon. "Triple-Network Dysconnectivity in Patients With First-Episode Psychosis and Individuals at Clinical High Risk for Psychosis." Psychiatry Investigation 19, no. 12 (December 25, 2022): 1037–45. http://dx.doi.org/10.30773/pi.2022.0091.
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Objective In the triple-network model, the salience network (SN) plays a crucial role in switching between the default-mode network (DMN) and the central executive network (CEN). Aberrant patterns of triple-network connectivity have been reported in schizophrenia patients, while findings have been less consistent for patients in the early stages of psychotic disorders. Thus, the present study examined the connectivity among the SN, DMN, and CEN in first-episode psychosis (FEP) patients and individuals at clinical high risk (CHR) for psychosis.Methods Thirty-nine patients with FEP, 78 patients with CHR for psychosis, and 110 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging. We compared the SN, DMN, and CEN connectivity patterns of the three groups. The role of the SN in networks with significant connectivity differences was examined by mediation analysis.Results FEP patients showed lower SN-DMN and SN-CEN (cluster-level F=5.83, false discovery rate [FDR] corrected-p=0.001) connectivity than HCs. There was lower SN-DMN connectivity (cluster-level F=3.06, FDR corrected-p=0.053) at a trend level in CHR subjects compared to HCs. Between HCs and FEP patients, mediation analysis showed that SN-DMN connectivity was a mediator between group and SN-CEN connectivity. Additionally, SN-CEN connectivity functioned as a mediator between group and SN-DMN connectivity.Conclusion Aberrant connectivity between the SN and DMN/CEN suggests disrupted network switching in FEP patients, although CHR subjects showed trend-level SN-DMN dysconnectivity. Our findings suggest that dysfunctional triple-network dynamics centered on the SN can appear in patients in the early stages of psychotic disorders.
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Wadell, Paula. "62.2 Evidence-Based Treatment for Clinical High-Risk State for Psychosis (CHR-P) Syndromes." Journal of the American Academy of Child & Adolescent Psychiatry 61, no. 10 (October 2022): S84. http://dx.doi.org/10.1016/j.jaac.2022.07.351.
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Menefee, Elizabeth. "62.1 Epidemiology and Diagnosis of Clinical High-Risk State for Psychosis (CHR-P) Syndromes." Journal of the American Academy of Child & Adolescent Psychiatry 61, no. 10 (October 2022): S84. http://dx.doi.org/10.1016/j.jaac.2022.07.350.
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Salazar de Pablo, Gonzalo, Scott W. Woods, Georgia Drymonitou, Héctor de Diego, and Paolo Fusar-Poli. "Prevalence of Individuals at Clinical High-Risk of Psychosis in the General Population and Clinical Samples: Systematic Review and Meta-Analysis." Brain Sciences 11, no. 11 (November 20, 2021): 1544. http://dx.doi.org/10.3390/brainsci11111544.
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(1) The consistency and magnitude of the prevalence of Clinical High-Risk for Psychosis (CHR-P) individuals are undetermined, limiting efficient detection of cases. We aimed to evaluate the prevalence of CHR-P individuals systematically assessed in the general population or clinical samples. (2) PRISMA/MOOSE-compliant (PROSPERO: CRD42020168672) meta-analysis of multiple databases until 21/01/21: a random-effects model meta-analysis, heterogeneity analysis, publication bias and quality assessment, sensitivity analysis—according to the gold-standard CHR-P and pre-screening instruments—leave-one-study-out analyses, and meta-regressions were conducted. (3) 35 studies were included, with 37,135 individuals tested and 1554 CHR-P individuals identified (median age = 19.3 years, Interquartile range (IQR) = 15.8–22.1; 52.2% females, IQR = 38.7–64.4). In the general population (k = 13, n = 26,835 individuals evaluated), the prevalence of the CHR-P state was 1.7% (95% Confidence Interval (CI) = 1.0–2.9%). In clinical samples (k = 22, n = 10,300 individuals evaluated), the prevalence of the CHR-P state was 19.2% (95% CI = 12.9–27.7%). Using a pre-screening instrument was associated with false negatives (5.6%, 95% CI = 2.2–13.3%) and a lower CHR-P prevalence (11.5%, 95% CI = 6.2–20.5%) compared to using CHR-P instruments only (28.5%, 95% CI = 23.0–34.7%, p = 0.003). (4) The prevalence of the CHR-P state is low in the general population and ten times higher in clinical samples. The prevalence of CHR-P may increase with a higher proportion of females in the general population and with a younger population in clinical samples. The CHR-P state may be unrecognized in routine clinical practice. These findings can refine detection and preventive strategies.
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Hu, Yegang, Jun Wu, YuJiao Cao, XiaoChen Tang, GuiSen Wu, Qian Guo, LiHua Xu, et al. "Abnormal neural oscillations in clinical high risk for psychosis: a magnetoencephalography method study." General Psychiatry 35, no. 2 (April 2022): e100712. http://dx.doi.org/10.1136/gpsych-2021-100712.
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BackgroundNeural oscillations directly reflect the rhythmic changes of brain activities during the resting state or while performing specific tasks. Abnormal neural oscillations have been discovered in patients with schizophrenia. However, there is limited evidence available on abnormal spontaneous neural oscillations in clinical high risk for psychosis (CHR-P). The brain signals recorded by the magnetoencephalography (MEG) technique are not to be disrupted by the skull and scalp.MethodsIn this study, we applied the MEG technique to record the resting-state neural activities in CHR-P. This was followed by a detailed MEG analysis method including three steps: (1) preprocessing, which was band-pass filtering based on the 0.5–60 Hz frequency range, removal of 50 Hz power frequency interference, and removal of electrocardiography (ECG) and electrooculography (EOG) artefacts by independent component analysis; (2) time-frequency analysis, a multitaper time-frequency transformation based on the Hanning window, and (3) source localisation, an exact low-resolution brain electromagnetic tomography. The method was verified by comparing a participant with CHR-P with a healthy control during the MEG recordings with an eyes-closed resting state.ResultsExperimental results show that the neural oscillations in CHR-P were significantly abnormal in the theta frequency band (4–7 Hz) and the delta frequency band (1–3 Hz). Also, relevant brain regions were located in the left occipital lobe and left temporo-occipital junction for the theta band and in the right dorsolateral prefrontal lobe and near orbitofrontal gyrus for the delta band.ConclusionsAbnormal neural oscillations based on specific frequency bands and corresponding brain sources may become biomarkers for high-risk groups. Further work will validate these characteristics in CHR-P cohorts.
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Worthington, Michelle, Jean Addington, Carrie Bearden, Kristin Cadenhead, Barbara Cornblatt, Daniel Mathalon, Thomas McGlashan, et al. "T116. PREDICTION OF REMISSION IN NON-CONVERTING INDIVIDUALS AT CLINICAL HIGH RISK FOR PSYCHOSIS." Schizophrenia Bulletin 46, Supplement_1 (April 2020): S274—S275. http://dx.doi.org/10.1093/schbul/sbaa029.676.
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Abstract Background The clinical high-risk period before a first episode of psychosis (CHR-P) has been widely studied in the past 30 years with the goal of understanding the development of psychosis. Despite the progress in understanding what factors are associated with conversion to psychosis from the CHR-P state, less attention has been paid to the individuals who do not transition to psychosis. It is estimated that approximately 75–80% of individuals do not go on to convert to psychosis from the CHR-P state and this group should not simply be characterized as the inverse of conversion. To date, only a handful of studies have examined the characteristics and predictors of those who do not convert to psychosis and ultimately either remit or continue to meet symptom-based CHR-P criteria. The present study took an exploratory empirical approach to determining potential factors that predict remission in non-converters. Methods Participants were drawn from the North American Prodrome Longitudinal Study (NAPLS2). Univariate Kaplan Meier survival analyses were performed on a pool of available demographic and clinical variables. Variables that were significant (p < 0.05) in the univariate analyses were then included in a multivariate Cox proportional hazard regression to predict remission. Remission was defined as all SOPS positive symptom subscale items rated as a 2 or lower at any given follow-up visit. Results A total of 359 participants from the NAPLS2 study who did not convert to psychosis and had data for at least the baseline and first follow-up visit and were included in this study. Of these participants, 174 met criteria for symptomatic remission. A total of 57 clinical variables were tested in univariate analyses and 14 of these variables met criteria for inclusion in the multivariate model. The variables included in the multivariate model were demographic variables (ethnicity, stressful life events), items from the Scale of Prodromal Symptoms (SOPS) (avolition, dysphoric mood), subtest scores from the MATRICS Cognitive Battery (speed of processing, verbal learning, verbal and non-verbal working memory, reasoning and problem solving, visual learning), one item from the Calgary Depression Scale for Schizophrenia (CDSS) (pathological guilt) and measures of functioning (GAF decline in past year, lowest GAF score in the past year). Overall, the multivariate model achieved a C-index of 0.64 (SE = 0.02) and p-value of 0.001 in predicting remission. In the multivariate model, significant covariates included stressful life events (HR = .95, p = .006), Hispanic ethnicity (HR = 1.45, p = .045), and avolition (HR = .89, p = .04). Covariates approaching significance included visual learning (HR = 1.02, p = .07), and GAF decline in the past year (HR = 1.01, p = .09). Discussion This study is the first to use a data-driven approach to systematically assess clinical and demographic predictors of symptomatic remission in individuals who do not convert to psychosis. The identified set of significant clinical variables is novel, suggesting that remission represents a unique clinical phenomenon and suggesting that further study is warranted to best understand factors contributing to resilience and recovery from the CHR-P period.
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De Micheli, Andrea, Albertine van Lawick van Pabst, Enass Yossef, Philip McGuire, and Paolo Fusar-Poli. "S154. TOBACCO SMOKING AND CLINICAL HIGH RISK: A SYSTEMATIC REVIEW AND META-ANALYSIS OF THE EVIDENCE." Schizophrenia Bulletin 46, Supplement_1 (April 2020): S94—S95. http://dx.doi.org/10.1093/schbul/sbaa031.220.
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Abstract Background There is converging evidence that youths at clinical high risk (CHR) are not only likely to develop the first episode of psychosis but also to develop poor physical outcomes. Some physical health risk factors - such as smoking - have been shown to increase the probability of a frank onset of psychosis in those at risk. A meta-analysis conducted in psychotic patients confirmed that daily tobacco use is associated with an increased risk of psychosis. A significant association between any attenuated psychotic symptoms (that characterize CHR state) and cigarette smoking has been recently shown in a study conducted in South London. Nowadays, it is not completely clear how these findings would translate to the CHR population but a better understanding of how physical health parameters could affect psychopathological outcomes could be beneficial for these vulnerable clinical populations. To shed light on the percentage of smokers in CHR populations, an updated systematic review and meta-analysis of the literature has been carried out. Our main aim was to test whether the probability of being a smoker was higher in the CHR subjects or in the control group. Methods The literature search was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. We systematically scrutinized from literature inception to 2019 the following on-line databases: Web of Science Core Collection, BIOSIS Citation Index, KCL-Korean Journal Database, MEDLINE, Russian Science Citation Index, SCiELO Citation Index. We have considered all the relevant studies reporting the smoking status in CHR subjects and in control groups. We used the odds ratio (OR) as effect size measure and data were pooled using a random effect approach. Results Preliminary data show that CHR individuals were more likely to use tobacco that matched healthy controls. Specifically, the overall OR of 2.016 (p<.001 95%CI=1.476–2.749) indicated a higher likelihood that CHR individuals would use tobacco compared to controls. Heterogeneity was not significant (I²=30.193 p=0.11). The visual inspection of funnel plots did not reveal a clear suggestion for publication bias and the Egger’s test was non-significant (p=0.10). Discussion Our systematic review and meta-analysis suggest that is crucial to investigate physical health outcomes such as tobacco use as part of clinical practice in CHR services. Unfortunately, current CHR assessment tools are entirely based on the measurement of psychopathological features and do not include an assessment of these parameters on a regular basis.
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Guo, Joyce Y., Tara A. Niendam, Andrea M. Auther, Ricardo E. Carrión, Barbara A. Cornblatt, J. Daniel Ragland, Steven Adelsheim, et al. "Predicting psychosis risk using a specific measure of cognitive control: a 12-month longitudinal study." Psychological Medicine 50, no. 13 (September 11, 2019): 2230–39. http://dx.doi.org/10.1017/s0033291719002332.
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AbstractBackgroundIdentifying risk factors of individuals in a clinical-high-risk state for psychosis are vital to prevention and early intervention efforts. Among prodromal abnormalities, cognitive functioning has shown intermediate levels of impairment in CHR relative to first-episode psychosis and healthy controls, highlighting a potential role as a risk factor for transition to psychosis and other negative clinical outcomes. The current study used the AX-CPT, a brief 15-min computerized task, to determine whether cognitive control impairments in CHR at baseline could predict clinical status at 12-month follow-up.MethodsBaseline AX-CPT data were obtained from 117 CHR individuals participating in two studies, the Early Detection, Intervention, and Prevention of Psychosis Program (EDIPPP) and the Understanding Early Psychosis Programs (EP) and used to predict clinical status at 12-month follow-up. At 12 months, 19 individuals converted to a first episode of psychosis (CHR-C), 52 remitted (CHR-R), and 46 had persistent sub-threshold symptoms (CHR-P). Binary logistic regression and multinomial logistic regression were used to test prediction models.ResultsBaseline AX-CPT performance (d-prime context) was less impaired in CHR-R compared to CHR-P and CHR-C patient groups. AX-CPT predictive validity was robust (0.723) for discriminating converters v. non-converters, and even greater (0.771) when predicting CHR three subgroups.ConclusionsThese longitudinal outcome data indicate that cognitive control deficits as measured by AX-CPT d-prime context are a strong predictor of clinical outcome in CHR individuals. The AX-CPT is brief, easily implemented and cost-effective measure that may be valuable for large-scale prediction efforts.
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Khoury, Rita, and Henry A. Nasrallah. "Inflammatory biomarkers in individuals at clinical high risk for psychosis (CHR-P): State or trait?" Schizophrenia Research 199 (September 2018): 31–38. http://dx.doi.org/10.1016/j.schres.2018.04.017.
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Andreou, Christina, and Stefan Borgwardt. "Structural and functional imaging markers for susceptibility to psychosis." Molecular Psychiatry 25, no. 11 (February 17, 2020): 2773–85. http://dx.doi.org/10.1038/s41380-020-0679-7.
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Abstract The introduction of clinical criteria for the operationalization of psychosis high risk provided a basis for early detection and treatment of vulnerable individuals. However, about two-thirds of people meeting clinical high-risk (CHR) criteria will never develop a psychotic disorder. In the effort to increase prognostic precision, structural and functional neuroimaging have received growing attention as a potentially useful resource in the prediction of psychotic transition in CHR patients. The present review summarizes current research on neuroimaging biomarkers in the CHR state, with a particular focus on their prognostic utility and limitations. Large, multimodal/multicenter studies are warranted to address issues important for clinical applicability such as generalizability and replicability, standardization of clinical definitions and neuroimaging methods, and consideration of contextual factors (e.g., age, comorbidity).
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Breitborde, Nicholas J. K., Hossam Guirgis, Walter Stearns, Kristen M. Carpenter, Ghada Lteif, Jacob G. Pine, Nichole Storey, Heather Wastler, and Aubrey M. Moe. "The Ohio State University Early Psychosis Intervention Center (EPICENTER) step-based care programme for individuals at clinical high risk for psychosis: study protocol for an observational study." BMJ Open 10, no. 1 (January 2020): e034031. http://dx.doi.org/10.1136/bmjopen-2019-034031.
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IntroductionIn October 2018, the Substance Abuse and Mental Health Services Administration funded 21 sites throughout the USA to develop, implement and evaluate specialised care programmes for individuals at clinical high risk for developing a psychotic disorder (CHR-P). Per the funding requirements, such programmes were required to provide ‘step-based care’—a model in which individuals are initially provided with low-intensity, non-psychosis-specific and more benign (ie, least side effects) interventions and only progress onto higher-intensity, psychosis-specific interventions with a greater risk of more severe side effects should they not meet a priori criteria for clinical response to such lower-intensity interventions. Here, we outline the evaluation component of the step-based care programme for individuals at CHR-P at The Ohio State University Early Psychosis Intervention Center (EPICENTER).Methods and analysesThe EPICENTER CHR-P programme provides a step-based care model comprising psychotherapy, medication management, family support/education, peer support and vocational/educational support. All participants who opt to receive care at the EPICENTER will complete a standardised assessment battery as part of usual care. This battery will be administered on enrolment and will be re-administered at 6-month intervals throughout individuals’ participation in EPICENTER clinical services. Participants will have the opportunity to allow for data from these usual care assessments to be used as part of an evaluation project for this new clinical service. The primary outcome for this evaluation project is time to remission of symptomatic and functional deficits commonly experienced by individuals at CHR-P. Participants will also have the opportunity to participate in a supplemental research project designed to further evaluate treatment outcomes and patient characteristics among individuals participating in EPICENTER clinical services.Ethics and disseminationThis project was approved by The Ohio State University Institutional Review Board. Results from this project will be disseminated through publications and presentations.Trial registration numberNCT03970005.
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Carrión, R. E., D. McLaughlin, A. M. Auther, R. Olsen, C. U. Correll, and B. A. Cornblatt. "The impact of psychosis on the course of cognition: a prospective, nested case-control study in individuals at clinical high-risk for psychosis." Psychological Medicine 45, no. 15 (July 14, 2015): 3341–54. http://dx.doi.org/10.1017/s0033291715001233.
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BackgroundAlthough cognitive deficits in patients with schizophrenia are rooted early in development, the impact of psychosis on the course of cognitive functioning remains unclear. In this study a nested case-control design was used to examine the relationship between emerging psychosis and the course of cognition in individuals ascertained as clinical high-risk (CHR) who developed psychosis during the study (CHR + T).MethodFifteen CHR + T subjects were administered a neurocognitive battery at baseline and post-psychosis onset (8.04 months, s.d. = 10.26). CHR + T subjects were matched on a case-by-case basis on age, gender, and time to retest with a group of healthy comparison subjects (CNTL, n = 15) and two groups of CHR subjects that did not transition: (1) subjects matched on medication treatment (i.e. antipsychotics and antidepressants) at both baseline and retesting (Meds-matched CHR + NT, n = 15); (2) subjects unmedicated at both assessments (Meds-free CHR + NT, n = 15).ResultsAt baseline, CHR + T subjects showed large global neurocognitive and intellectual impairments, along with specific impairments in processing speed, verbal memory, sustained attention, and executive function. These impairments persisted after psychosis onset and did not further deteriorate. In contrast, CHR + NT subjects demonstrated stable mild to no impairments in neurocognitive and intellectual performance, independent of medication treatment.ConclusionsCognition appears to be impaired prior to the emergence of psychotic symptoms, with no further deterioration associated with the onset of psychosis. Cognitive deficits represent trait risk markers, as opposed to state markers of disease status and may therefore serve as possible predictors of schizophrenia prior to the onset of the full illness.
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Modinos, Gemma, Anja Richter, Alice Egerton, Ilaria Bonoldi, Matilda Azis, Mathilde Antoniades, Matthijs Bossong, et al. "Interactions between hippocampal activity and striatal dopamine in people at clinical high risk for psychosis: relationship to adverse outcomes." Neuropsychopharmacology 46, no. 8 (May 3, 2021): 1468–74. http://dx.doi.org/10.1038/s41386-021-01019-0.
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AbstractPreclinical models propose that increased hippocampal activity drives subcortical dopaminergic dysfunction and leads to psychosis-like symptoms and behaviors. Here, we used multimodal neuroimaging to examine the relationship between hippocampal regional cerebral blood flow (rCBF) and striatal dopamine synthesis capacity in people at clinical high risk (CHR) for psychosis and investigated its association with subsequent clinical and functional outcomes. Ninety-five participants (67 CHR and 28 healthy controls) underwent arterial spin labeling MRI and 18F-DOPA PET imaging at baseline. CHR participants were followed up for a median of 15 months to determine functional outcomes with the global assessment of function (GAF) scale and clinical outcomes using the comprehensive assessment of at-risk mental states (CAARMS). CHR participants with poor functional outcomes (follow-up GAF < 65, n = 25) showed higher rCBF in the right hippocampus compared to CHRs with good functional outcomes (GAF ≥ 65, n = 25) (pfwe = 0.026). The relationship between rCBF in this right hippocampal region and striatal dopamine synthesis capacity was also significantly different between groups (pfwe = 0.035); the association was negative in CHR with poor outcomes (pfwe = 0.012), but non-significant in CHR with good outcomes. Furthermore, the correlation between right hippocampal rCBF and striatal dopamine function predicted a longitudinal increase in the severity of positive psychotic symptoms within the total CHR group (p = 0.041). There were no differences in rCBF, dopamine, or their associations in the total CHR group relative to controls. These findings indicate that altered interactions between the hippocampus and the subcortical dopamine system are implicated in the pathophysiology of adverse outcomes in the CHR state.
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Millman, Zachary B., James M. Gold, Vijay A. Mittal, and Jason Schiffman. "The Critical Need for Help-Seeking Controls in Clinical High-Risk Research." Clinical Psychological Science 7, no. 6 (September 23, 2019): 1171–89. http://dx.doi.org/10.1177/2167702619855660.
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Despite rapidly growing knowledge of the clinical high-risk (CHR) state for psychosis, the vast majority of case-control studies have relied on healthy volunteers as a reference point for drawing inferences about the CHR construct. Researchers have long recognized that results generated from this design are limited by significant interpretive concerns, yet little attention has been given to how these concerns affect the growing field of CHR research. We argue that overreliance on healthy control participants in CHR research threatens the validity of inferences concerning group differences, hinders advances in understanding the development of psychosis, and limits clinical progress. We suggest that the combined use of healthy and help-seeking (i.e., psychiatric) controls is a necessary step for the next generation of CHR research. We then evaluate methods for help-seeking control studies, identify the available CHR studies that have used such designs, discuss select findings in this literature, and offer recommendations for research.
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Franscini, M., N. Traber-Walker, F. Probst, M. Gerstenberg, and S. Walitza. "Early detection and intervention of psychosis in children and adolescents in Zurich, Switzerland: Clinical Data from 2017-2022." European Psychiatry 66, S1 (March 2023): S1075—S1076. http://dx.doi.org/10.1192/j.eurpsy.2023.2284.
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IntroductionThe construct of a clinical high-risk (CHR) state of psychosis has been established to describe potentially prodromal symptoms which typically appear during adolescence and young adulthood. This is a very sensitive developmental period and the clinical high risk (CHR) is associated with increased functional impairment. To address the specialities in the care for this patient population a specialized outpatient care unit for early intervention in psychosis at the Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital, of the University Zürich (CAPS) is established. The interdisciplinary team (psychiatrists and psychologists) supports children and adolescents with psychotic disorders or at clinical high risk for developing psychosis. The early intervention service offers specialized assessment, treatment and case management for minors with a first psychosis or CHR-state in an outpatient or inpatient setting as well as by day clinic care.ObjectivesThe evaluation main objective was to get a better understanding about this vulnerable patient group. Therefore we analysed the clinical data about CHR-state, comorbid diagnosis, treatment, medication and hospitalisation of the patients who entered the service for early intervention in psychosis.MethodsParticipants who entered the service for early intervention in psychosis were followed up in the years 2017-2021 and descriptive analysis was used to summarize the data. For the evaluation of the risk construct the participants have been classified in “no increased risk”, “CHR” or “early onset psychosis” (EOP). Additionally, ICD diagnosis, demographics and treatment (medication, psychotherapy, treatment setting) were assessed. Therapy was either psychotherapy and/or group training called DBT2P (Dialectical behavioral group training for adolescents, to prevent psychiatric disorders). Additionally, the use of a smartphone application “Robin Z”(add-on treatment tool to support the patients between the sessions) was assessed.ResultsIn the last five years we saw 300 patients (112 female, mean age 15.7) who sought the care unit for early intervention. The evaluation of the risk showed that 44 patients had no increased risk, 205 were classified with a CHR and 51 fulfilled the criteria of an early onset psychosis (18.5%). Most of the patients showed comorbid diagnosis, mainly depressive disorders (42%). The data about the treatment will be analyzed for the congress.ConclusionsDespite clinical implications, there is little data about early detection and early intervention in psychosis for children and adolescent. Therefore, the evaluation of the clinical data of the CAPS is of clinical importance and expected to add essential information in the fields of prevention and early intervention in psychosis.Disclosure of InterestNone Declared
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Ciarleglio, Adam J., Gary Brucato, Michael D. Masucci, Rebecca Altschuler, Tiziano Colibazzi, Cheryl M. Corcoran, Francesca M. Crump, et al. "A predictive model for conversion to psychosis in clinical high-risk patients." Psychological Medicine 49, no. 07 (June 28, 2018): 1128–37. http://dx.doi.org/10.1017/s003329171800171x.
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AbstractBackgroundThe authors developed a practical and clinically useful model to predict the risk of psychosis that utilizes clinical characteristics empirically demonstrated to be strong predictors of conversion to psychosis in clinical high-risk (CHR) individuals. The model is based upon the Structured Interview for Psychosis Risk Syndromes (SIPS) and accompanying clinical interview, and yields scores indicating one's risk of conversion.MethodsBaseline data, including demographic and clinical characteristics measured by the SIPS, were obtained on 199 CHR individuals seeking evaluation in the early detection and intervention for mental disorders program at the New York State Psychiatric Institute at Columbia University Medical Center. Each patient was followed for up to 2 years or until they developed a syndromal DSM-4 disorder. A LASSO logistic fitting procedure was used to construct a model for conversion specifically to a psychotic disorder.ResultsAt 2 years, 64 patients (32.2%) converted to a psychotic disorder. The top five variables with relatively large standardized effect sizes included SIPS subscales of visual perceptual abnormalities, dysphoric mood, unusual thought content, disorganized communication, and violent ideation. The concordance index (c-index) was 0.73, indicating a moderately strong ability to discriminate between converters and non-converters.ConclusionsThe prediction model performed well in classifying converters and non-converters and revealed SIPS measures that are relatively strong predictors of conversion, comparable with the risk calculator published by NAPLS (c-index = 0.71), but requiring only a structured clinical interview. Future work will seek to externally validate the model and enhance its performance with the incorporation of relevant biomarkers.
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Panikratova, Y., E. Abdullina, I. Lebedeva, M. Omelchenko, D. Tikhonov, and V. Kaleda. "Brain functional connectivity and local coherence in non-converters with clinical high risk for psychosis." European Psychiatry 66, S1 (March 2023): S612—S613. http://dx.doi.org/10.1192/j.eurpsy.2023.1277.
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IntroductionInvestigation of resilience mechanisms in patients with clinical high risk for psychosis (CHR) may inform clinical practice for the development of early intervention programs. Resilience mechanisms in CHR who did not transit to psychosis for a long period of observation may be more pronounced than in CHR converters.ObjectivesWe aimed to compare CHR who did not convert to psychosis for 7.3 ± 1.7 years, patients with first-episode psychosis (FEP), and healthy controls (HC) in terms of brain functional connectivity and local coherence.MethodsTwenty-seven CHR (mean age 27.5 ± 3.1), 24 FEP (mean age 20.6 ± 3.6), and 27 HC (mean age 27.3 ± 4) underwent resting-state fMRI (3T). All participants were males. Functional connectivity between 32 regions of interest (components of default mode, sensorimotor, visual, salience, dorsal attention, frontoparietal, language, and cerebellar networks; CONN functional network atlas www.nitrc.org/projects/conn) and whole-brain local coherence (LCOR; Deshpande et al. HBM 2009; 30(1) 13-23) were compared between 3 groups of participants (one-way ANCOVA) with post hoc analyses.ResultsCHR and HC demonstrated higher functional connectivity between the occipital cortex (visual network) and right rostral prefrontal cortex (salience network) compared to FEP. CHR also showed higher local coherence in the right calcarine and cuneal cortex than FEP (the following differences did not survive the correction for multiple comparisons: CHR>HC and HC>FEP).ConclusionsOur findings on brain functional connectivity and local coherence may be considered as the markers of resilience mechanisms in patients with CHR as these parameters were different between CHR and FEP and were similar in CHR and HC.The research was supported by RFBR grant project 20-013-00748.Disclosure of InterestNone Declared
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Haining, Kate, Gina Brunner, Ruchika Gajwani, Joachim Gross, Andrew Gumley, Stephen Lawrie, Matthias Schwannauer, Frauke Schultze-Lutter, and Peter Uhlhaas. "S64. COGNITIVE IMPAIRMENTS AND PREDICTION OF FUNCTIONAL OUTCOME IN INDIVIDUALS AT CLINICAL HIGH-RISK FOR PSYCHOSIS." Schizophrenia Bulletin 46, Supplement_1 (April 2020): S57—S58. http://dx.doi.org/10.1093/schbul/sbaa031.130.
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Abstract Background Research in individuals at clinical-high risk for psychosis (CHR-P) has focused on developing algorithms to predict transition to psychosis. However, it is becoming increasingly important to address other outcomes, such as the level of functioning of CHR-P participants. To address this important question, this study investigated the relationship between baseline cognitive performance and functional outcome between 6–12 months in a sample of CHR-P individuals using a machine-learning approach to identify features that are predictive of long-term functional impairments. Methods Data was available for 111 CHR-P individuals at 6–12 months follow-up. In addition, 47 CHR-negative (CHR-N) participants who did not meet CHR criteria and 55 healthy controls (HCs) were recruited. CHR-P status was assessed using the Comprehensive Assessment of At-Risk Mental States (CAARMS) and the Schizophrenia Proneness Instrument, Adult version (SPI-A). Cognitive assessments included the Brief Assessment of Cognition in Schizophrenia (BACS) and the Penn Computerized Neurocognitive Battery (CNB). Global, social and role functioning scales were used to measure functional status. CHR-P individuals were divided into good functional outcome (GFO, GAF ≥ 65) and poor functional outcome groups (PFO, GAF < 65). Feature selection was performed using LASSO regression with the LARS algorithm and 10-fold cross validation with GAF scores at baseline as the outcome variable. The following features were identified as predictors of GAF scores at baseline: verbal memory, verbal fluency, attention, emotion recognition, social and role functioning and SPI-A distress. This model explained 47% of the variance in baseline GAF scores. In the next step, Support Vector Machines (SVM), Linear Discriminant Analysis (LDA), Logistic Regression (LR), Gaussian Naïve Bayes (GNB), and Random Forest (RF) classifiers with 10-fold cross validation were then trained on those features with GAF category at follow-up used as the binary label column. Models were compared using a calculated score incorporating area under the curve (AUC), accuracy, and AUC consistency across runs, whereby AUC was given a higher weighting than accuracy due to class imbalance. Results CHR-P individuals had slower motor speed, reduced attention and processing speed and increased emotion recognition reaction times (RTs) compared to HCs and reduced attention and processing speed compared to CHR-Ns. At follow-up, 66% of CHR-P individuals had PFO. LDA emerged as the strongest classifier, showing a mean AUC of 0.75 (SD = 0.15), indicating acceptable classification performance for GAF category at follow-up. PFO was detected with a sensitivity of 75% and specificity of 58%, with a total mean weighted accuracy of 68%. Discussion The CHR-P state was associated with significant impairments in cognition, highlighting the importance of interventions such as cognitive remediation in this population. Our data suggest that the development of features using machine learning approaches is effective in predicting functional outcomes in CHR-P individuals. Greater levels of accuracy, sensitivity and specificity might be achieved by increasing training sets and validating the classifier with external data sets. Indeed, machine learning methods have potential given that trained classifiers can easily be shared online, thus enabling clinical professionals to make individualised predictions.
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Fusar-Poli, Paolo, Matteo Rocchetti, Alberto Sardella, Alessia Avila, Martina Brandizzi, Edgardo Caverzasi, Pierluigi Politi, Stephan Ruhrmann, and Philip McGuire. "Disorder, not just state of risk: Meta-analysis of functioning and quality of life in people at high risk of psychosis." British Journal of Psychiatry 207, no. 3 (September 2015): 198–206. http://dx.doi.org/10.1192/bjp.bp.114.157115.
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BackgroundThe nosology of the psychosis high-risk state is controversial. Traditionally conceived as an ‘at risk’ state for the development of psychotic disorders, it is also conceptualised as a clinical syndrome associated with functional impairment.AimsTo investigate meta-analytically the functional status of patients at high clinical risk for psychosis and its association with longitudinal outcomes.MethodThree meta-analyses compared level of functioning (n = 3012) and quality of life (QoL) (n = 945) between a high-risk group, a healthy control group and group with psychosis, and baseline functioning in people in the high-risk group who did or did not have a transition to psychosis at follow-up (n = 654).ResultsPeople at high risk had a large impairment in functioning (P<0.001) and worse QoL (P = 0.001) than the healthy control group, but only small to moderately better functioning (P = 0.012) and similar QoL (P = 0.958) compared with the psychosis group. Among the high-risk group, those who did not develop psychosis reported better functioning (P = 0.001) than those who did.ConclusionsOur results indicate that the high-risk state is characterised by consistent and large impairments of functioning and reduction in QoL similar to those in other coded psychiatric disorders.
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Tomyshev, A. S., I. Lebedeva, A. Dudina, P. Menshchikov, D. Kupriyanov, and M. Omelchenko. "Reduced resting-state gamma-band power correlate with unaltered glutamate + glutamine levels in patients at clinical-high risk of psychosis." European Psychiatry 67, S1 (April 2024): S615. http://dx.doi.org/10.1192/j.eurpsy.2024.1280.
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IntroductionThere is growing evidence of excitation / inhibition (E/I) balance abnormalities in schizophrenia, which might be associated with abnormal gamma frequency oscillations and glutamate concentrations. However, to the best of our knowledge, only one multimodal study have examined such associations between EEG and metabolite characteristics in patients at clinical-high risk of psychosis (CHR) so far.ObjectivesWe aimed to investigate potential associations between GLX (glutamate + glutamine) levels and resting-state gamma-band power in CHR individuals and healthy controls (HC).MethodsTwenty right-handed male patients (16-27 years, mean age 19.9 ± 2.7) fulfilling CHR criteria and 19 healthy male controls (16-27 years, mean age 21.6 ± 3.6) underwent resting-state EEG (16 leads; 10−20 system) and MR spectroscopy at 3T MRI scanner with voxels of 30×30×30mm located in left and right medial prefrontal cortex. Spectral analysis with estimation of gamma-band power (30-45 Hz) were conducted. MEGA-PRESS acquisitions were analyzed with jMRUi (ver. 5.1 Alpha), levels of GLX were calculated as a ratios to creatine + phosphocreatine (GLX/Cr). Gamma-band (30-45 Hz) spectral power and GLX/Cr were compared between groups. Correlations between EEG and metabolite data were analyzed with regression model including age and chlorpromazine equivalents as covariates.ResultsCompared to healthy controls, patients showed reduced spectral gamma-band power in 6 leads (Table). No alterations in GLX/Cr were detected. Positive correlations between altered gamma-power in all leads (except Cz) and GLX/Cr in left medial prefrontal cortex were revealed in CHR (F3: r=0.51, p=0.006; F8: r=0. 54, p=0.004; C3: r=0.37, p=0.037; Pz: r=0.51, p=0.039; P4: r=0.56, p=0.009). No correlations in HC group were found. Chlorpromazine equivalents did not correlate with GLX/Cr of gamma power in CHR group.Table.Results of between-group comparisons corrected for multiple comparisons Lead CHR Mean±SD HC Mean±SD p -value F Cohen’s d Cohen’s d CI 95%F30.97±0.621.4±0.640.00977.2-0.69-1.22 -0.16F80.84±0.611.45±1.030.00727.8-0.71-1.24 -0.19C30.97±0.551.44±0.640.00269.9-0.79-1.32 -0.27Cz1.03±0.611.42±0.520.00747.7-0.70-1.22 -0.18Pz1.17±0.71.62±0.630.00987.1-0.68-1.2 -0.16P41.04±0.661.53±0.660.00518.5-0.74-1.27 -0.22ConclusionsThe findings suggest that clinical-high risk of psychosis is associated with widespread alterations in resting-state gamma-band power. Positive correlations of such alterations with GLX/Cr and absence of such correlations in HC group are presumably indicative of disturbances in the excitation / inhibition balance in CHR individuals.This study was supported by RFBR grant 19-29-10040Disclosure of InterestNone Declared
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Ifrah, Chloe, Shaynna N. Herrera, Steven M. Silverstein, Cheryl M. Corcoran, James Gordon, Pamela D. Butler, and Vance Zemon. "The Relationship between Clinical and Psychophysical Assessments of Visual Perceptual Disturbances in Individuals at Clinical High Risk for Psychosis: A Preliminary Study." Brain Sciences 14, no. 8 (August 16, 2024): 819. http://dx.doi.org/10.3390/brainsci14080819.
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This study investigated relations between a measure of early-stage visual function and self-reported visual anomalies in individuals at clinical high risk for psychosis (CHR-P). Eleven individuals at CHR identified via the Structured Interview for Psychosis-Risk Syndromes (SIPS) were recruited from a CHR-P research program in NYC. The sample was ~36% female, ranging from 16 to 33 years old (M = 23.90, SD = 6.14). Participants completed a contrast sensitivity task on an iPad with five spatial frequencies (0.41–13 cycles/degree) and completed the self-report Audio-Visual Abnormalities Questionnaire. Higher contrast sensitivity (better performance) to low spatial frequencies was associated with higher perceptual (r = 0.616, p = 0.044) and visual disturbances (r = 0.667, p = 0.025); lower contrast sensitivity to a middle spatial frequency was also associated with higher perceptual (r = −0.604, p = 0.049) and visual disturbances (r = −0.606, p = 0.048). This relation between the questionnaire and contrast sensitivity to low spatial frequency may be indicative of a reduction in lateral inhibition and “flooding” of environmental stimuli. The association with middle spatial frequencies, which play a critical role in face processing, may result in a range of perceptual abnormalities. These findings demonstrate that self-reported perceptual anomalies occur in these individuals and are linked to performance on a measure of early visual processing.
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Zajac, Jennifer. "62.3 An Innovative Intensive Outpatient Program for Adolescents With Clinical High-Risk State for Psychosis (CHR-P) Syndromes." Journal of the American Academy of Child & Adolescent Psychiatry 61, no. 10 (October 2022): S84. http://dx.doi.org/10.1016/j.jaac.2022.07.352.
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Collin, Guusje, Alfonso Nieto-Castanon, Martha Shenton, Ofer Pasternak, Sinead Kelly, Matcheri Keshavan, Larry Seidman, et al. "S147. FUNCTIONAL BRAIN CONNECTIVITY DATA IMPROVE CLINICAL OUTCOME PREDICTION IN YOUTH AT RISK FOR PSYCHOSIS." Schizophrenia Bulletin 46, Supplement_1 (April 2020): S92. http://dx.doi.org/10.1093/schbul/sbaa031.213.
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Abstract Background Improved outcome prediction in individuals at high risk for psychosis may facilitate targeted early intervention. Studies suggest that improved outcome prediction may be achieved through the use of neurocognitive or neuroimaging data, on their own or in addition to clinical data. This study examines whether adding resting-state functional connectivity data to validated clinical predictors of psychosis improve outcome prediction in the prodromal stage. Methods This study involves 137 adolescents and young adults at Clinical High Risk (CHR) for psychosis from the Shanghai At Risk for Psychosis (SHARP) program. Based on outcome after one-year follow-up, participants were separated into three outcome categories: good outcome (symptom remission, N = 71), intermediate outcome (ongoing CHR symptoms, N = 30), and poor outcome (conversion to psychosis or treatment-refractory, N = 36). Resting-state fMRI data were acquired for each participant and processed using the Conn toolbox, including rigorous motion correction. Multinomial logistic regression analysis and leave-one-out cross-validation were used to assess the performance of three prediction models: 1) a clinical-only model using validated clinical predictors from the NAPLS-2 psychosis-risk calculator, 2) an fMRI-only model using measures of functional connectome organization and within/between-network connectivity among established resting-state networks, and 3) a combined clinical and fMRI prediction model. Model performance was assessed using the harmonic mean of the positive predictive value and sensitivity for each outcome category. This F1 measure was compared to expected chance-levels using a permutation test with 1,000 sampled permutations in order to evaluate the statistical significance of the model’s prediction. Results The clinical-only prediction model failed to achieve a significant level of outcome prediction (F1 = 0.32, F1-chance = 0.26 □ 0.06, p = .154). The fMRI-only model did predict clinical outcome to a significant degree (F1 = 0.41, F1-chance = 0.29 □ 0.06, p = .016), but the combined clinical and fMRI prediction model showed the best performance (F1 = 0.46, F1-chance = 0.29 □ 0.06, p < .001). On average, positive predictive values (reflecting the probability that an outcome label predicted by the model was correct) were 39% better than chance-level and 32% better than the clinical-only model. Analyzing the contribution of individual predictor variables showed that GAF functional decline, a family history of psychosis, and performance on the Hopkins Verbal Learning Test were the most influential clinical predictors, whereas modular connectome organization, default-mode and fronto-parietal within-network connectivity, and between-network connectivity among language, salience, dorsal attention, cerebellum, and sensorimotor networks were the leading fMRI predictors. Discussion This study’s findings suggest that functional brain abnormalities reflected by alterations in resting-state functional connectivity precede and may drive subsequent changes in clinical functioning. Moreover, the findings show that markers of functional brain connectivity may be useful for improving early identification and clinical decision-making in prodromal psychosis.
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Mongan, David, Melanie Föcking, Colm Healy, Subash Raj Susai, Gerard Cagney, Mary Cannon, Stanley Zammit, et al. "T21. DEVELOPMENT OF PROTEOMIC PREDICTION MODELS FOR OUTCOMES IN THE CLINICAL HIGH RISK STATE AND PSYCHOTIC EXPERIENCES IN ADOLESCENCE: MACHINE LEARNING ANALYSES IN TWO NESTED CASE-CONTROL STUDIES." Schizophrenia Bulletin 46, Supplement_1 (April 2020): S238—S239. http://dx.doi.org/10.1093/schbul/sbaa029.581.
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Abstract Background Individuals at clinical high risk (CHR) of psychosis have an approximately 20% probability of developing psychosis within 2 years, as well as an associated risk of non-psychotic disorders and functional impairment. People with subclinical psychotic experiences (PEs) are also at risk of future psychotic and non-psychotic disorders and decreased functioning. It is difficult to accurately predict outcomes in individuals at risk of psychosis on the basis of symptoms alone. Biomarkers for accurate prediction of outcomes could inform the clinical management of this group. Methods We conducted two nested case-control studies. We employed discovery-based proteomic methods to analyse protein expression in baseline plasma samples in EU-GEI and age 12 plasma samples in ALSPAC using liquid chromatography mass spectrometry. Differential expression of quantified proteomic markers was determined by analyses of covariance (with false discovery rate of 5%) comparing expression levels for each marker between those who did not and did not develop psychosis in Study 1 (adjusting for age, gender, body mass index and years in education), and between those who did and did not develop PEs in Study 2 (adjusting for gender, body mass index and maternal social class). Support vector machine algorithms were used to develop models for prediction of transition vs. non-transition (as determined by the Comprehensive Assessment of At Risk Mental States) and poor vs. good functional outcome at 2 years in Study 1 (General Assessment of Functioning: Disability subscale score </=60 vs. >60). Similar algorithms were used to develop a model for prediction of PEs vs. no PEs at age 18 in Study 2 (as determined by the Psychosis Like Symptoms Interview). Results In Study 1, 35 of 166 quantified proteins were significantly differentially expressed between CHR participants who did and did not develop psychosis. Functional enrichment analysis provided evidence for particular implication of the complement and coagulation cascade (false discovery rate-adjusted Fisher’s exact test p=2.23E-21). Using 65 clinical and 166 proteomic features a model demonstrated excellent performance for prediction of transition status (area under the receiver-operating curve [AUC] 0.96, positive predictive value [PPV] 83.0%, negative predictive value [NPV] 93.8%). A model based on the ten most predictive proteins accurately predicted transition status in training (AUC 0.96, PPV 87.5%, NPV 95.8%) and withheld data (AUC 0.92, PPV 88.9%, NPV 91.4%). A model using the same 65 clinical and 166 proteomic features predicted 2-year functional outcome with AUC 0.72 (PPV 67.6%, NPV 47.6%). In Study 2, 5 of 265 quantified proteins were significantly differentially expressed between participants who did and did not report PEs at age 18. A model using 265 proteomic features predicted PEs at age 18 with AUC 0.76 (PPV 69.1%, NPV 74.2%). Discussion With external validation, models incorporating proteomic data may contribute to improved prediction of clinical outcomes in individuals at risk of psychosis.
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Neuner, L. M., L. Hahn, J. Kambeitz, R. K. Salokangas, J. Hietala, A. Bertolino, S. Borgwardt, et al. "Exploring Associations between Grey Matter Volume and Clinical High-Risk for Psychosis: A Transdiagnostic Study Utilizing the NAPLS-2 Risk Calculator in the PRONIA Cohort." European Psychiatry 67, S1 (April 2024): S271—S272. http://dx.doi.org/10.1192/j.eurpsy.2024.572.
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Introduction The clinical high-risk state for psychosis (CHR) is associated with alterations in grey matter volume (GMV) in various regions such as the hippocampus (Vissink et al. BP:GOS 2022; 2(2) 147-152). Within the scope of the North American Prodrome Longitudinal Study (NAPLS-2; Cannon et al. AM J Psychiatry 2016; 173(10), 980-988), a publicly available risk calculator based on clinical variables was developed to assess the likelihood of individuals to transition to psychosis within a 2-year period.Objectives In the current study, we aim to examine the association between GMV and NAPLS-2 risk scores calculated for individuals with CHR and recent-onset depression (ROD), taking a transdiagnostic approach on the transition to psychosis.Methods The sample consisted of 315 CHR (M = 23.85, SD = ± 5.64; female: 164) and 295 ROD (M = 25.11, SD = ± 6.21; female: 144) patients from the multi-site Personalised Prognostic Tools for Early Psychosis Management (PRONIA) Study (Koutsouleris et al. JAMA Psychiatry 2018; 57(11), 1156-1172). Risk scores were calculated using the six clinical and neurocognitive variables included in the NAPLS-2 risk calculator that were significant for predicting psychosis. Further, we derived smoothed GMV maps from T1-weighted structural magnetic resonance imaging using a full width at half maximum kernel size of 8 mm. We employed a multiple regression design in SPM12 to examine associations between risk scores and GMV. On the whole-brain level, we calculated permutation-based threshold-free cluster enhancement (TFCE) contrasts using the TFCE toolbox. Additionally, we calculated t-contrasts within a region-of-interest (ROI) analysis encompassing the hippocampus. All results were thresholded at p < 0.05 with family wise error correction to address multiple comparisons.ResultsOur analysis revealed that linear GMV increases in the right middle and superior frontal gyrus (kE= 2726 voxels) were significantly associated with higher risk for psychosis transition within two years (see figure 1, highlighted in blue). In the ROI analysis, we found a significant negative linear association between GMV decreases in the left hippocampus (kE = 353 voxels) and higher risk for psychosis transition (see figure 1, highlighted in red).Image:ConclusionsGMV reductions in the hippocampus have frequently been observed in CHR and psychosis patients (Vissink et al. BP:GOS 2022; 2(2) 147-152), therefore our results further highlight the crucial role of this region in the progression of the disease. There is limited evidence on GMV increases in CHR patients. However, the GMV increase we found in the frontal pole may reflect compensatory mechanisms of the brain in the development of psychosis. In addition, we were able to provide biological validation of the NAPLS-2 risk calculator and its assessment of risk for transition to psychosis.Disclosure of InterestNone Declared
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DeVylder, J. E., S. Ben-David, S. A. Schobel, D. Kimhy, D. Malaspina, and C. M. Corcoran. "Temporal association of stress sensitivity and symptoms in individuals at clinical high risk for psychosis." Psychological Medicine 43, no. 2 (June 1, 2012): 259–68. http://dx.doi.org/10.1017/s0033291712001262.
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BackgroundIncreased sensitivity and exposure to stress are associated with psychotic symptoms in schizophrenia and its risk states, but little is known about the co-evolution of stress sensitivity and exposure with positive and other symptoms in a clinical high-risk (CHR) cohort.MethodA combined cross-sectional and longitudinal design was used to examine the associations over time of stress sensitivity and exposure (i.e. life events) with ‘prodromal’ symptoms in a cohort of 65 CHR patients assessed quarterly for up to 4 years, and at baseline in 24 healthy controls similar in age and gender.ResultsImpaired stress tolerance was greater in patients, in whom it was associated over time with positive and negative symptoms, in addition to depression, anxiety and poor function. By contrast, life events were comparable in patients and controls, and bore no association with symptoms. In this treated cohort, there was a trajectory of improvement in stress tolerance, symptoms and function over time.ConclusionsImpaired stress tolerance was associated with a wide range of ‘prodromal’ symptoms, consistent with it being a core feature of the psychosis risk state. Self-reported life events were not relevant as a correlate of clinical status. As in other treated CHR cohorts, most patients improved over time across symptom domains.
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Graham-Sullivan, Patricia C. "62.4 Prevention and Therapy Approaches to Clinical High-Risk State for Psychosis (CHR-P) in an Intensive Outpatient Program." Journal of the American Academy of Child & Adolescent Psychiatry 61, no. 10 (October 2022): S84. http://dx.doi.org/10.1016/j.jaac.2022.07.353.
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Popovic, D., C. Weyer, A. Ruef, D. Dwyer, S. L. Griffiths, P. A. Lalousis, N. Koutsouleris, and R. Upthegrove. "Neuroinflammation in Recent Onset Mental Health Disorders – Developing Multi-level Signatures of Early-stage Depression and Psychosis in Young Adults." European Psychiatry 67, S1 (April 2024): S45—S47. http://dx.doi.org/10.1192/j.eurpsy.2024.147.
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IntroductionAn early and comprehensive neurobiological characterization of severe mental disorders could elucidate mechanistic pathways, aid the development of novel therapeutics, and therefore enable timely and targeted intervention in at-risk youth and young adults. Therefore, we present an unsupervised transdiagnostic machine learning approach to investigate shared and distinct patterns of early-stage depressive and psychotic disorders on multiple clinical and neurobiological levels.ObjectivesTo derive multi-level neurobiological and clinical signatures of early-stage affective and psychotic disorders in adolescents and young adults.MethodsFrom the multicenter prospective European PRONIA cohort, we acquired data from 678 individuals (51% female) comprising young, minimally medicated in- and outpatients with clinical high-risk (CHR) states for psychosis, with recent-onset depression (ROD) or psychosis (ROP), and healthy control (HC) individuals. Within repeated nested cross-validation frameworks, we employed Sparse Partial Least Squares Analysis to detect associations between blood markers and grey matter volume (GMV), followed by support vector machine prediction of these signatures using biographical, clinical, neurocognitive, proteomic, and functional data.ResultsOur results demonstrated a psychosis staging signature separating ROP from CHR individuals via GMV patterns in the cortico-thalamo-cerebellar circuitry with a blood marker set of elevated of IL-6, TNF-α and CRP (ρ = 0.272; P = 0.002). A depression signature separated ROD from HC individuals via altered GMV in the limbic system with a blood marker set of elevated IL-1ß, IL-2, IL-4, S100B and BDNF (ρ = 0.186; P = 0.021). Only the psychosis staging signature showed a distinct proteomic enrichment regarding innate immune response, abnormal neutrophil function, cellular senescence, and anti-inflammatory drugs (Balanced Accuracy (BAC) = 87.73%; Area Under the Curve (AUC) = 0.94). Childhood trauma differentially predicted psychosis and depression signatures, while past level of functioning, personality and quality of life was predictive of both signatures (BAC = 67.19-78.00%; AUC = 0.71-0.83).Image:Image 2:Image 3:ConclusionsPsychosis and depression exhibit distinct multi-level signatures evident in early disease stages. Enhanced insight into these signatures could help delineate individual trajectories and potentially new mechanisms for pharmacological treatment.Disclosure of InterestNone Declared
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Oliver, D., M. Kotlicka-Antczak, A. Minichino, G. Spada, P. McGuire, and P. Fusar-Poli. "Meta-analytical prognostic accuracy of the Comprehensive Assessment of at Risk Mental States (CAARMS): The need for refined prediction." European Psychiatry 49 (2018): 62–68. http://dx.doi.org/10.1016/j.eurpsy.2017.10.001.
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AbstractPrimary indicated prevention is reliant on accurate tools to predict the onset of psychosis. The gold standard assessment for detecting individuals at clinical high risk (CHR-P) for psychosis in the UK and many other countries is the Comprehensive Assessment for At Risk Mental States (CAARMS). While the prognostic accuracy of CHR-P instruments has been assessed in general, this is the first study to specifically analyse that of the CAARMS. As such, the CAARMS was used as the index test, with the reference index being psychosis onset within 2 years. Six independent studies were analysed using MIDAS (STATA 14), with a total of 1876 help-seeking subjects referred to high risk services (CHR-P+: n = 892; CHR-P–: n = 984). Area under the curve (AUC), summary receiver operating characteristic curves (SROC), quality assessment, likelihood ratios, and probability modified plots were computed, along with sensitivity analyses and meta-regressions. The current meta-analysis confirmed that the 2-year prognostic accuracy of the CAARMS is only acceptable (AUC = 0.79 95% CI: 0.75–0.83) and not outstanding as previously reported. In particular, specificity was poor. Sensitivity of the CAARMS is inferior compared to the SIPS, while specificity is comparably low. However, due to the difficulties in performing these types of studies, power in this meta-analysis was low. These results indicate that refining and improving the prognostic accuracy of the CAARMS should be the mainstream area of research for the next era. Avenues of prediction improvement are critically discussed and presented to better benefit patients and improve outcomes of first episode psychosis.
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Azis, Matilda, Gregory P. Strauss, Elaine Walker, William Revelle, Richard Zinbarg, and Vijay Mittal. "Factor Analysis of Negative Symptom Items in the Structured Interview for Prodromal Syndromes." Schizophrenia Bulletin 45, no. 5 (December 8, 2018): 1042–50. http://dx.doi.org/10.1093/schbul/sby177.
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Abstract Background Negative symptoms occur early in the clinical high risk (CHR) state and indicate increased risk of conversion to psychotic disorder and poor functional outcome. However, while the negative symptom domain has shown to be parsimoniously explained by a 2-factor construct in schizophrenia, there has yet to be an established factor structure of negative symptoms in CHR. Methods 214 individuals meeting the Structured Interview for Psychosis-Risk Syndromes (SIPS) criteria for CHR were recruited through 3 active research programs in the United States. Exploratory Factor Analysis was conducted on the 6 negative symptom items of the SIPS, and factors were evaluated with respect to functional outcome and depression. Results Factor analysis indicated a 2-factor hierarchical model with 2 negative symptom dimensions reflecting volition (Occupational Functioning and Avolition) and emotion (Expression of Emotion, Experience of Emotion and Social Anhedonia). Linear Regression showed that the emotion factor was associated with poor social function, and the volition factor was associated with poor role function and depression. Conclusions Similar to factor solutions identified in adults diagnosed with psychotic disorders, results indicated that the SIPS negative symptom subscale is not a unidimensional construct. Rather, the SIPS negative subscale has 2 distinct factors that have different associations with clinical outcome and should be interpreted independently. Results have significant relevance for informing the valid assessment and conceptual interpretation of early clinical phenomenology in the psychosis prodrome.
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Dean, Derek J., Jessica A. Bernard, Katherine S. F. Damme, Randall O’Reilly, Joseph M. Orr, and Vijay A. Mittal. "Longitudinal Assessment and Functional Neuroimaging of Movement Variability Reveal Novel Insights Into Motor Dysfunction in Clinical High Risk for Psychosis." Schizophrenia Bulletin 46, no. 6 (July 14, 2020): 1567–76. http://dx.doi.org/10.1093/schbul/sbaa072.
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Abstract Motor dysfunction in youth at clinical high risk (CHR) for psychosis is thought to reflect abnormal neurodevelopment within cortical-subcortical motor circuits and may be important for understanding clinical trajectories of CHR individuals. However, to date, our perspective of brain-behavior relationships has been informed solely by cross-sectional correlational studies linking behavior in the lab to brain structure or respective resting-state network connectivity. Here, we assess movement dysfunction from 2 perspectives: study 1 investigates the longitudinal progression of handwriting variability and positive symptoms in a sample of 91 CHR and healthy controls during a 12-month follow-up and study 2 involves a multiband functional magnetic resonance imaging task exploring the relationship between power grip force stability and motor network brain activation in a subset of participants. In study 1, we found that greater handwriting variability was a stable feature of CHR participants who experienced worse symptom progression. Study 2 results showed that CHR individuals had greater variability in their grip force and greater variability was related to decreased activation in the associative cortico-striatal network compared to controls. Motor variability may be a stable marker of vulnerability for psychosis risk and possible indicator of a vulnerable cortico-striatal brain network functioning in CHR participants, although the effects of antipsychotic medication should be considered.
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Glenthøj, L. B., M. Nielsen, and M. Nordentoft. "Negative symptoms assessment in early intervention settings: Implications for early identification and treatment." European Psychiatry 64, S1 (April 2021): S36. http://dx.doi.org/10.1192/j.eurpsy.2021.124.
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Negative symptoms are a core feature of schizophrenia spectrum disorders associated with poor outcomes such as low remission rates and impairments in daily functioning and quality of life in early psychosis. The assessment of negative symptoms in early psychotic disorders is predominantly conducted by use of first-generation scales such as the PANSS and the SANS, along with the SIPS and CAARMS for the psychosis clinical high-risk (CHR) state. Following the progressed conceptualization of negative symptoms, it has, however, been recognized that these scales suffer important methodological limitations. This warrants a use of second-generation scales such as the Brief Negative Symptom Scale (BNSS) and the Clinical Assessment Interview for Negative Symptoms (CAINS) in early intervention settings in order to achieve a more accurate assessment of the negative symptom complex. Advancing the assessment of negative symptoms in early psychosis may also guide more targeted intervention approaches aimed at improving functional outcome. Albeit recognizing that negative symptoms constitute an important barrier to a good functional outcome in psychotic disorders, few studies have directly aimed at alleviating negative symptoms in early psychosis. Meta-analytical evidence does, however, exist on the efficacy of the combined treatment modalities incorporated in Early Intervention Services (e.g. intensive and assertive case management, family involvement etc.) in reducing negative symptoms in first-episode psychosis. Evidence on the effect of interventions for improving negative symptoms in the CHR state is lacking. Developing targeted, and possibly more individualized negative symptoms treatment approaches, constitute an essential future research area.DisclosureNo significant relationships.
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Jeon, Peter, Roberto Limongi, Sabrina D. Ford, Cassandra Branco, Michael Mackinley, Maya Gupta, Laura Powe, Jean Théberge, and Lena Palaniyappan. "Glutathione as a Molecular Marker of Functional Impairment in Patients with At-Risk Mental State: 7-Tesla 1H-MRS Study." Brain Sciences 11, no. 7 (July 17, 2021): 941. http://dx.doi.org/10.3390/brainsci11070941.
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A substantial number of individuals with clinical high-risk (CHR) mental state do not transition to psychosis. However, regardless of future diagnostic trajectories, many of these individuals develop poor social and occupational functional outcomes. The levels of glutathione, a crucial cortical antioxidant, may track variations in functional outcomes in early psychosis and prodromal states. Thirteen clinical high-risk and 30 healthy control volunteers were recruited for a 7-Tesla magnetic resonance spectroscopy scan with a voxel positioned within the dorsal anterior cingulate cortex (ACC). Clinical assessment scores were collected to determine if any association was observable with glutathione levels. The Bayesian Spearman’s test revealed a positive association between the Social and Occupational Functioning Assessment Scale (SOFAS) and the glutathione concentration in the clinical high-risk group but not in the healthy control group. After accounting for variations in the SOFAS scores, the CHR group had higher GSH levels than the healthy subjects. This study is the first to use 7-Tesla magnetic resonance spectroscopy to test whether ACC glutathione levels relate to social and occupational functioning in a clinically high-risk group and offers preliminary support for glutathione levels as a clinically actionable marker of prognosis in emerging adults presenting with risk features for various severe mental illnesses.
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Traber-Walker, Nina, Miriam Gerstenberg, Sibylle Metzler, Claudia Bühlmann, Yolanda Blumenthal, Susanne Walitza, and Maurizia Franscini. "O1.1. ETRo: EVALUATION OF THE TREATMENT APPROACH “ROBIN” (STANDARDIZED MANUAL AND SMARTPHONE APP) FOR ADOLESCENTS WITH CLINICAL HIGH RISK FOR DEVELOPING A PSYCHOTIC DISORDER." Schizophrenia Bulletin 46, Supplement_1 (April 2020): S1. http://dx.doi.org/10.1093/schbul/sbaa028.000.
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Abstract Background The construct of a clinical high-risk (CHR) state of psychosis has been established to describe potentially prodromal symptoms which typically appear during adolescence and young adulthood. This is a very sensitive developmental period and the clinical high risk (CHR) is associated with increased functional impairment. However, there is a lack of research on age-appropriate treatment strategies for this vulnerable age group. To fill this gap, the experts from the specialized outpatient care unit for early intervention in psychosis at the Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital, of the University Zürich (CAPS), have developed the combined treatment program “Robin” (standardized manual and smartphone App). The therapy program is targeting at risk-symptoms and aims to improve of quality of life as well as daily functioning. The smartphone application “Robin Z” is an add-on treatment tool to support the patients between the sessions. While a number of trials with smartphone applications in therapy have shown promising effects with adult patient with psychosis, there is little known about using them in the therapy with minor patients. “Robin Z” is one of the first smartphone applications addressing adolescent patients with at risk- symptoms or full-blown psychotic symptoms. Since September 2017, the efficacy of this combined treatment approach is being evaluated with the systematic clinical intervention trial ETRo (Evaluation of the treatment approach “Robin“). The study has been registered at ClinicalTrials.gov (ClinicalTrials.gov Identifier: NCT03829527) and the study protocol has been published June 2019 in the journal “Frontiers in Psychiatry”. Methods The ETRo trial is a prospective, naturalistic, follow up study with a matched control design. Participants from a former early recognition study are included for the control condition (treatment as usual). For the intervention condition (16 weekly individual sessions + a minimum 4 family sessions), 30 help seeking CHR adolescents, aged 14–18, are being recruited. At-risk and comorbid symptoms, functioning, self-efficacy and quality of life are monitored at six time points (baseline, during the treatment period, immediately after intervention, and 6, 12, and 24 months later) and compared to the respective measures of the active control group. Results The data from a pilot investigation showed, that “Robin” was accepted by clinicians and patients. Therefore, the authors hypothesize that the “Robin” will enhance the treatment engagement. Within the first 2 years of the systematic evaluation, 18 CHR individuals (61% female, mean age 16.1) have been included in the intervention condition. In Florence, the preliminary results and their implications will be presented. This will include baseline data of the first patients in the intervention group, the intraindividual changes in symptomatology and well-being after 6 months of treatment and data about the treatment satisfaction. Discussion “Robin” is a newly developed treatment approach for adolescents at clinical high risk (CHR) of developing a psychotic disorder combining a standardized treatment manual with a smartphone application. To the best of the author’s knowledge, this is the first controlled trial to test the efficacy of a specific early psychosis treatment in combination with a smartphone application for CHR adolescents. The results of the study are of clinical importance and expected to add essential information in the fields of eMental Health as well as in prevention and early intervention in psychosis.
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Fusar-Poli, Paolo, Andrea De Micheli, Rashmi Patel, Lorenzo Signorini, Syed Miah, Thomas Spencer, and Philip McGuire. "Real-World Clinical Outcomes Two Years After Transition to Psychosis in Individuals at Clinical High Risk: Electronic Health Record Cohort Study." Schizophrenia Bulletin 46, no. 5 (April 18, 2020): 1114–25. http://dx.doi.org/10.1093/schbul/sbaa040.
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Abstract The objective of this study is to describe the 2-year real-world clinical outcomes after transition to psychosis in patients at clinical high-risk. The study used the clinical electronic health record cohort study including all patients receiving a first index primary diagnosis of nonorganic International Classification of Diseases (ICD)-10 psychotic disorder within the early psychosis pathway in the South London and Maudsley (SLaM) National Health Service (NHS) Trust from 2001 to 2017. Outcomes encompassed: cumulative probability (at 3, 6, 12, and 24 months) of receiving a first (1) treatment with antipsychotic, (2) informal admission, (3) compulsory admission, and (4) treatment with clozapine and (5) numbers of days spent in hospital (at 12 and 24 months) in patients transitioning to psychosis from clinical high-risk services (Outreach and Support in south London; OASIS) compared to other first-episode groups. Analyses included logistic and 0-inflated negative binomial regressions. In the study, 1561 patients were included; those who had initially been managed by OASIS and had subsequently transitioned to a first episode of psychosis (n = 130) were more likely to receive antipsychotic medication (at 3, 6, and 24 months; all P < .023), to be admitted informally (at all timepoints, all P < .004) and on a compulsory basis (at all timepoints, all P < .013), and to have spent more time in hospital (all timepoints, all P < .007) than first-episode patients who were already psychotic when seen by the OASIS service (n = 310), or presented to early intervention services (n = 1121). The likelihood of receiving clozapine was similar across all groups (at 12/24 months, all P < .101). Transition to psychosis from a clinical high-risk state is associated with severe real-world clinical outcomes. Prevention of transition to psychosis should remain a core target of future research. The study protocol was registered on www.researchregistry.com; researchregistry5039).
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Rosen, Marlene, Nathalie Kaiser, Linda Betz, Theresa Haidl, Mauro Seves, Tanja Pilgram, Frauke Schultze-Lutter, et al. "S219. SINGLE-SUBJECT PREDICTION OF FUNCTIONAL OUTCOMES ACROSS DIAGNOSTIC GROUPS USING CLINICAL DATA." Schizophrenia Bulletin 46, Supplement_1 (April 2020): S122. http://dx.doi.org/10.1093/schbul/sbaa031.285.
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Abstract Background Psychotic disorders are associated with serious deterioration in functioning even before the first psychotic episode. Also on clinical high risk (CHR) states of developing a first psychotic episode, several studies reported a decreased global functioning. In a considerable proportion of CHR individuals, functional deterioration remains even after (transient) remission of symptomatic risk indicators. Furthermore, deficits in functioning cause immense costs for the health care system and are often more debilitating for individuals than positive symptoms. However in the past, CHR research has mostly focused on clinical outcomes like transition. Prediction of functioning in CHR populations has received less attention. Therefore, the current study aims at predicting functioning in CHR individuals at a single subject level applying multi pattern recognition to clinical data. Patients with a first depressive episode who frequently have persistent functional deficits comparable to patients in the CHR state were investigated in addition. Methods PRONIA (‘Personalized Prognostic Tools for Early Psychosis Management’) is a prospective collaboration project funded by the European Union under the 7th Framework Programme (grant agreement n°602152). Considering a broad set of variables (MRI, clinical data, neurocognition, genomics and other blood derived parameters) as well as advanced statistical methods, PRONIA aims at developing an innovative multivariate prognostic tool enabling an individualized prediction of illness trajectories and outcome. 11 university centers in five European countries and in Australia (Munich, Basel, Birmingham, Cologne, Düsseldorf, Münster, Melbourne, Milan, Udine, Bari, Turku) participate in the evaluation of three clinical groups (subjects clinically at high risk of developing a psychosis [CHR], patients with a recent onset psychosis [ROP] and patients with a recent onset depression [ROD]) as well as healthy controls. In the current study, we analysed data of 114 CHR and 106 ROD patients. Functioning was measured by the ‘Global Functioning: Social and Role’ Scales (GF S/R). In a repeated, nested cross validation framework we trained a l1-regularized SVM to predict good versus bad outcome. Multivariate pattern recognition analysis allowed to identify most predictive variables from a multitude of clinical, environmental as well as sociodemographic potential predictors assessed in PRONIA. Results Based on the 5 to 20 identified most predictive features, prediction models revealed a balanced accuracy (BAC) up to 77/72 for social functioning in CHR/ROD patients and up to 73/69 for role functioning. These models showed satisfying performance of BACs up to 69/63 for social functioning and 67/60 for role functioning in an independent test sample. As expected, prior functioning levels were identified as main predictive factor but also distinct protective and risk factors were selected into the prediction models. Discussion Results suggest that especially prediction of the multi-faceted construct of role functioning could benefit from inclusion of a rich set of clinical variables. To the best of our knowledge this is the first study that has validated clinical prediction models of functioning in an independent test sample. Identification of predictive variables enables a much more efficient prognostic process. Moreover, understanding the mechanisms underlying functional decline and its illness related pattern might enable an improved definition of targets for intervention. Future research should aim at further maximisation of prediction accuracy and cross-centre generalisation capacity. In addition, other functioning outcomes as well as clinical outcomes need to be focused on.
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Hasmi, Laila, Lotta-Katrin Pries, Margreet ten Have, Ron de Graaf, Saskia van Dorsselaer, Maarten Bak, Gunter Kenis, et al. "What makes the psychosis ‘clinical high risk’ state risky: psychosis itself or the co-presence of a non-psychotic disorder?" Epidemiology and Psychiatric Sciences 30 (2021). http://dx.doi.org/10.1017/s204579602100041x.
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Abstract Aims Although attenuated psychotic symptoms in the psychosis clinical high-risk state (CHR-P) almost always occur in the context of a non-psychotic disorder (NPD), NPD is considered an undesired ‘comorbidity’ epiphenomenon rather than an integral part of CHR-P itself. Prospective work, however, indicates that much more of the clinical psychosis incidence is attributable to prior mood and drug use disorders than to psychosis clinical high-risk states per se. In order to examine this conundrum, we analysed to what degree the ‘risk’ in CHR-P is indexed by co-present NPD rather than attenuated psychosis per se. Methods We examined the incidence of early psychotic experiences (PE) with and without NPD (mood disorders, anxiety disorders, alcohol/drug use disorders), in a prospective general population cohort (n = 6123 at risk of incident PE at baseline). Four interview waves were conducted between 2007 and 2018 (NEMESIS-2). The incidence of PE, alone (PE-only) or with NPD (PE + NPD) was calculated, as were differential associations with schizophrenia polygenic risk score (PRS-Sz), environmental, demographical, clinical and cognitive factors. Results The incidence of PE + NPD (0.37%) was lower than the incidence of PE-only (1.04%), representing around a third of the total yearly incidence of PE. Incident PE + NPD was, in comparison with PE-only, differentially characterised by poor functioning, environmental risks, PRS-Sz, positive family history, prescription of antipsychotic medication and (mental) health service use. Conclusions The risk in ‘clinical high risk’ states is mediated not by attenuated psychosis per se but specifically the combination of attenuated psychosis and NPD. CHR-P/APS research should be reconceptualised from a focus on attenuated psychotic symptoms with exclusion of non-psychotic DSM-disorders, as the ‘pure' representation of a supposedly homotypic psychosis risk state, towards a focus on poor-outcome NPDs, characterised by a degree of psychosis admixture, on the pathway to psychotic disorder outcomes.