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

Jonah F Byrne, Colm Healy, Melanie Föcking, Subash Raj Susai, David Mongan, Kieran Wynne, Eleftheria Kodosaki, Meike Heurich, Lieuwe de Haan, Ian B Hickie, Stefan Smesny, Andrew Thompson, Connie Markulev, Alison Ruth Young, Miriam R Schäfer, Anita Riecher-Rössler, Nilufar Mossaheb, Gregor Berger, Monika Schlögelhofer, Merete NordentoftEric Y H Chen, Swapna Verma, Dorien H Nieman, Scott W Woods, Barbara A Cornblatt, William S Stone, Daniel H Mathalon, Carrie E Bearden, Kristin S Cadenhead, Jean Addington, Elaine F Walker, Tyrone D Cannon, Mary Cannon, Pat McGorry, Paul Amminger, Gerard Cagney, Barnaby Nelson, Clark Jeffries, Diana Perkins, David R Cotter

Research output: Contribution to journalArticlepeer-review

5 Downloads (Pure)

Abstract

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.
Original languageEnglish
Pages (from-to)579–588
JournalSchizophrenia Bulletin
Volume50
Issue number3
Early online date19 Jan 2024
DOIs
Publication statusPublished - May 2024

Keywords

  • high risk
  • model
  • coagulation
  • prediction
  • immune
  • complement
  • psychosis
  • proteome

Fingerprint

Dive into the research topics of 'Proteomic biomarkers for the prediction of transition to psychosis in individuals at clinical high risk: a multi-cohort model development study'. Together they form a unique fingerprint.

Cite this