Predictors of remission from the ultra-high risk state for psychosis

Genome-wide association exploratory studies in individuals with ultra-high risk for schizophrenia in Chinese Han nationality in two years follow-up: A subpopulation study

BACKGROUND

Although ultra-high risk for schizophrenia (UHR) is related to both genetic and environment factors, the precise pathogenesis is still unknow. To date, few studies have explored the Genome-Wide Association Studies (GWAS) in UHR or HR individuals especially in Han population in China.

METHODS

In this study, a GWAS analysis for 36 participants with UHR and 43 with HR were performed, and all deletion variations in 22q11 region were also compared.

RESULTS

Sixteen individuals with UHR (44.4%) and none with HR converted into schizophrenia in follow-up after two years. Six loci including neurexin-1(NRXN1) (rs1045881), dopamine D1 receptor (DRD1) (rs686, rs4532), chitinase-3-like protein 1 (CHI3L1) (rs4950928), velocardiofacial syndrome (ARVCF) (rs165815), dopamine D2 receptor (DRD2) (rs1076560) were identified higher expression with significant difference in individuals converted into schizophrenia after two years. The Family with Sequence Similarity 230 Member H (FAM230H) gene in the 22q11 region were also found high expression in UHR group.

CONCLUSIONS

Further expansion of sample size and validation studies are needed to explore the pathogenesis of these risk loci in UHR conversion into schizophrenia in the future.

Effectiveness of a two-stage strategy using the 16-item Prodromal Questionnaire (PQ16/fPQ16) and the Comprehensive Assessment of At Risk Mental States (CAARMS) in the early detection of Ultra High Risk (UHR) patients in Lebanon: a cross-sectional pilot study

OBJECTIVES

This study aims to identify the prevalence of Ultra High Risk (UHR) adults in a sample of patients in Lebanon and to compare screening and diagnostic tools.

METHODS

This is a cross-sectional pilot study which targeted patients aged 17-30 years willingly seeking psychiatric care in a university hospital in Beirut, Lebanon. Participants were invited to fill either the English or the French version of the Prodromal Questionnaire (respectively, PQ16 or fPQ16). The abbreviated version of the "Comprehensive Assessment of At-Risk Mental States" (CAARMS) was then administered to all participants. The latter were subsequently sorted into one of the three UHR groups - vulnerability group, attenuated psychosis (APS), intermittent psychosis (BLIPS) - or were diagnosed as suffering from a psychotic disorder.

RESULTS

Thirty-one patients participated in this study. The prevalence of positive screening on the PQ16/fPQ16 and positive diagnosis of UHR on the CAARMS were respectively of 61.29% and 45%. The APS group was the most prevalent (71.42%). A positive psychosis screening on PQ16/fPQ16 was statistically related to a UHR diagnosis on CAARMS (p-value: 0.011 on Chi2 test), OR=8.5 (95% CI: 1.4-50.9; p-value: 0.018). No relation was found between PQ16/fPQ16 results and risk stratification or between the number of "True" responses on PQ16/fPQ16 and the intensity of symptoms on CAARMS. PQ16/fPQ16 statements 5, 9, 11 and 16 predicted a UHR diagnosis on CAARMS (p-value of 0.045, 0.006, 0.045 and 0.045, respectively).

CONCLUSION

This two-stage strategy for identifying UHR patients can be adopted in a tertiary health care center.

Prediction of psychosis: model development and internal validation of a personalized risk calculator

BACKGROUND

Over the past two decades, early detection and early intervention in psychosis have become essential goals of psychiatry. However, clinical impressions are insufficient for predicting psychosis outcomes in clinical high-risk (CHR) individuals; a more rigorous and objective model is needed. This study aims to develop and internally validate a model for predicting the transition to psychosis within 10 years.

METHODS

Two hundred and eight help-seeking individuals who fulfilled the CHR criteria were enrolled from the prospective, naturalistic cohort program for CHR at the Seoul Youth Clinic (SYC). The least absolute shrinkage and selection operator (LASSO)-penalized Cox regression was used to develop a predictive model for a psychotic transition. We performed k-means clustering and survival analysis to stratify the risk of psychosis.

RESULTS

The predictive model, which includes clinical and cognitive variables, identified the following six baseline variables as important predictors: 1-year percentage decrease in the Global Assessment of Functioning score, IQ, California Verbal Learning Test score, Strange Stories test score, and scores in two domains of the Social Functioning Scale. The predictive model showed a cross-validated Harrell's C-index of 0.78 and identified three subclusters with significantly different risk levels.

CONCLUSIONS

Overall, our predictive model showed a predictive ability and could facilitate a personalized therapeutic approach to different risks in high-risk individuals.

Verbal memory performance predicts remission and functional outcome in people at clinical high-risk for psychosis

Robust deficits in cognitive functioning are present in people with psychosis and are evident in the early stages of the disorder. Impairments in verbal memory and verbal fluency are reliably seen in individuals at clinical high-risk for psychosis (CHR) compared to healthy populations. As previous studies have shown a relationship between cognition and longer-term outcomes in schizophrenia, the aim of this paper was to explore whether verbal memory and verbal fluency performance predicted outcomes in a large CHR sample recruited as part of the EU-GEI High Risk Study. Participants included 316 CHR individuals, 90.8% of whom were not currently on antipsychotic medication, and 60 healthy controls. Verbal memory and verbal fluency performance were measured at baseline. At two-year follow-up, CHR individuals were assessed by three different outcome measures, those who did and did not (1) transition to psychosis, (2) experience burdening impairment or disabilities, or (3) remit clinically from CHR status. Individuals with CHR displayed significant verbal memory and verbal fluency deficits at baseline compared to healthy controls (Hedges' g effect size = 0.24 to 0.66). There were no significant differences in cognitive performance of those who did and did not transition to psychosis. However, impaired immediate verbal recall predicted both functional disability and non-remission from the CHR state. Results remained significant when analyses were restricted to only include antipsychotic-free CHR participants. These findings may inform the development of early interventions designed to improve cognitive deficits in the early stages of psychosis.

Individualized Prediction of Prodromal Symptom Remission for Youth at Clinical High Risk for Psychosis

The clinical high-risk period before a first episode of psychosis (CHR-P) has been widely studied with the goal of understanding the development of psychosis; however, less attention has been paid to the 75%-80% of CHR-P individuals who do not transition to psychosis. It is an open question whether multivariable models could be developed to predict remission outcomes at the same level of performance and generalizability as those that predict conversion to psychosis. Participants were drawn from the North American Prodrome Longitudinal Study (NAPLS3). An empirically derived set of clinical and demographic predictor variables were selected with elastic net regularization and were included in a gradient boosting machine algorithm to predict prodromal symptom remission. The predictive model was tested in a comparably sized independent sample (NAPLS2). The classification algorithm developed in NAPLS3 achieved an area under the curve of 0.66 (0.60-0.72) with a sensitivity of 0.68 and specificity of 0.53 when tested in an independent external sample (NAPLS2). Overall, future remitters had lower baseline prodromal symptoms than nonremitters. This study is the first to use a data-driven machine-learning approach to assess clinical and demographic predictors of symptomatic remission in individuals who do not convert to psychosis. The predictive power of the models in this study suggest that remission represents a unique clinical phenomenon. Further study is warranted to best understand factors contributing to resilience and recovery from the CHR-P state.

Prediction and Prevention in the Clinical High-Risk for Psychosis Paradigm: A Review of the Current Status and Recommendations for Future Directions of Inquiry

Prediction and prevention of negative clinical and functional outcomes represent the two primary objectives of research conducted within the clinical high-risk for psychosis (CHR-P) paradigm. Several multivariable "risk calculator" models have been developed to predict the likelihood of developing psychosis, although these models have not been translated to clinical use. Overall, less progress has been made in developing effective interventions. In this paper, we review the existing literature on both prediction and prevention in the CHR-P paradigm and, primarily, outline ways in which expanding and combining these paths of inquiry could lead to a greater improvement in individual outcomes for those most at risk.