Proteomic Biomarkers for the Prediction of Transition to Psychosis in Individuals at Clinical High Risk: A Multi-cohort Model Development Study.

Psychosis risk prediction is one of the leading challenges in psychiatry. Previous investigations have suggested that plasma proteomic data may be useful in accurately predicting transition to psychosis in individuals at clinical high risk (CHR). We hypothesized that an a priori-specified proteomic prediction model would have strong predictive accuracy for psychosis risk and aimed to replicate longitudinal associations between plasma proteins and transition to psychosis. This study used plasma samples from participants in 3 CHR cohorts: the North American Prodrome Longitudinal Studies 2 and 3, and the NEURAPRO randomized control trial (total n = 754). Plasma proteomic data were quantified using mass spectrometry. The primary outcome was transition to psychosis over the study follow-up period. Logistic regression models were internally validated, and optimism-corrected performance metrics derived with a bootstrap procedure. In the overall sample of CHR participants (age: 18.5, SD: 3.9; 51.9% male), 20.4% (n = 154) developed psychosis within 4.4 years. The a priori-specified model showed poor risk-prediction accuracy for the development of psychosis (C-statistic: 0.51 [95% CI: 0.50, 0.59], calibration slope: 0.45). At a group level, Complement C8B, C4B, C5, and leucine-rich α-2 glycoprotein 1 (LRG1) were associated with transition to psychosis but did not surpass correction for multiple comparisons. This study did not confirm the findings from a previous proteomic prediction model of transition from CHR to psychosis. Certain complement proteins may be weakly associated with transition at a group level. Previous findings, derived from small samples, should be interpreted with caution

Proteomic biomarkers for the prediction of transition to psychosis in individuals at clinical high risk: a multi-cohort model development study

Psychosis risk prediction is one of the leading challenges in psychiatry. Previous investigations have suggested that plasma proteomic data may be useful in accurately predicting transition to psychosis in individuals at clinical high risk (CHR). We hypothesized that an a priori-specified proteomic prediction model would have strong predictive accuracy for psychosis risk and aimed to replicate longitudinal associations between plasma proteins and transition to psychosis. This study used plasma samples from participants in 3 CHR cohorts: the North American Prodrome Longitudinal Studies 2 and 3, and the NEURAPRO randomized control trial (total n = 754). Plasma proteomic data were quantified using mass spectrometry. The primary outcome was transition to psychosis over the study follow-up period. Logistic regression models were internally validated, and optimism-corrected performance metrics derived with a bootstrap procedure. In the overall sample of CHR participants (age: 18.5, SD: 3.9; 51.9% male), 20.4% (n = 154) developed psychosis within 4.4 years. The a priori-specified model showed poor risk-prediction accuracy for the development of psychosis (C-statistic: 0.51 [95% CI: 0.50, 0.59], calibration slope: 0.45). At a group level, Complement C8B, C4B, C5, and leucine-rich α-2 glycoprotein 1 (LRG1) were associated with transition to psychosis but did not surpass correction for multiple comparisons. This study did not confirm the findings from a previous proteomic prediction model of transition from CHR to psychosis. Certain complement proteins may be weakly associated with transition at a group level. Previous findings, derived from small samples, should be interpreted with caution

The association between migrant status and transition in an ultra-high risk for psychosis population

Purpose: Migrant status is one of the most replicated and robust risk factors for developing a psychotic disorder. This study aimed to determine whether migrant status in people identified as Ultra-High Risk for Psychosis (UHR) was associated with risk of transitioning to a full-threshold psychotic disorder. Methods: Hazard ratios for the risk of transition were calculated from five large UHR cohorts (n = 2166) and were used to conduct a meta-analysis using the generic inverse-variance method using a random-effects model. Results: 2166 UHR young people, with a mean age of 19.1 years (SD ± 4.5) were included, of whom 221 (10.7%) were first-generation migrants. A total of 357 young people transitioned to psychosis over a median follow-up time of 417 days (I.Q.R.147–756 days), representing 17.0% of the cohort. The risk of transition to a full-threshold disorder was not increased for first-generation migrants, (HR = 1.08, 95% CI 0.62–1.89); however, there was a high level of heterogeneity between studies The hazard ratio for second-generation migrants to transition to a full-threshold psychotic disorder compared to the remainder of the native-born population was 1.03 (95% CI 0.70–1.51). Conclusions: This meta-analysis did not find a statistically significant association between migrant status and an increased risk for transition to a full-threshold psychotic disorder; however, several methodological issues could explain this finding. Further research should focus on examining the risk of specific migrant groups and also ensuring that migrant populations are adequately represented within UHR clinics