Predictive Performance of Exposome Score for Schizophrenia in the General Population

L.K. Pries, G. Erzin, J. van Os, M. ten Have, R. de Graaf, S. van Dorsselaer, M. Bak, B.P.F. Rutten, S. Guloksuz*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

12 Citations (Web of Science)


Previously, we established an estimated exposome score for schizophrenia (ES-SCZ) as a cumulative measure of environmental liability for schizophrenia to use in gene-environment interaction studies and for risk stratification in population cohorts. Hereby, we examined the discriminative function of ES-SCZ for identifying individuals diagnosed with schizophrenia spectrum disorder in the general population by measuring the area under the receiver operating characteristic curve (AUC). Furthermore, we compared this ES-SCZ method to an environmental sum score (Esum SCZ) and an aggregate environmental score weighted by the meta-analytical estimates (Emet-SCZ). We also estimated ORs and Nagelkerke's R-2 for ES-SCZ in association with psychiatric diagnoses and other medical outcomes. ES-SCZ showed a good discriminative function (AUC = 0.84) and statistically significantly performed better than both Fsum-SCZ (AUC = 0.80) and Emet-SCZ (AUC = 0.80). At optimal cut point, ES-SCZ showed similar performance in ruling out (LR- = 0.20) and ruling in (LR+ = 3.86) schizophrenia. ES-SCZ at optimal cut point showed also a progressively greater magnitude of association with increasing psychosis risk strata. Among all clinical outcomes, ES-SCZ was associated with schizophrenia diagnosis with the highest OR (2.76, P < .001) and greatest explained variance (R-2 = 14.03%), followed by bipolar disorder (OR = 2.61, P < .001, R-2 = 13.01%) and suicide plan (OR = 2.44, P < .001, R-2 = 12.44%). Our findings from an epidemiologically representative general population cohort demonstrate that an aggregate environmental exposure score for schizophrenia constructed using a predictive modeling approach-ES-SCZ-has the potential to improve risk prediction and stratification for research purposes and may help gain insight into the multicausal etiology of psychopathology.

Original languageEnglish
Pages (from-to)277-283
Number of pages7
JournalSchizophrenia Bulletin
Issue number2
Publication statusPublished - 1 Mar 2021


  • environment
  • exposome
  • prediction
  • psychosis
  • risk score
  • schizophrenia

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