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Precursors and prodromata of schizophrenia: findings from the Edinburgh High Risk Study and their literature context

Published online by Cambridge University Press:  03 July 2006

D. G. CUNNINGHAM OWENS
Affiliation:
Division of Psychiatry, School of Molecular and Clinical Medicine, University of Edinburgh, Edinburgh, UK
EVE C. JOHNSTONE
Affiliation:
Division of Psychiatry, School of Molecular and Clinical Medicine, University of Edinburgh, Edinburgh, UK

Abstract

Background. In schizophrenia research, ‘high risk’ traditionally referred to studies of the offspring of schizophrenic parents at genetically enhanced risk of illness development. Sixteen major high-risk studies have been undertaken although only six followed through to formal illness so data on prediction remain weak. Recently, ‘high risk’ has widened to encompass individuals considered ‘at risk’ by having ‘high risk mental states’, regardless of family history, in whom initiation of early treatment is postulated to improve outcome.

Method. The major familial high-risk studies are reviewed from the perspective of the Edinburgh High Risk Study of Schizophrenia (EHRS), with emphasis on prediction.

Results. Familial high-risk studies have established multiple biological markers, the most reproducible of which relate to neuromotor development and cognition, especially aspects of memory/learning. Although most are probably not specific, they support a neurodevelopmental hypothesis. Family and environmental variables point largely to secondary or indirect associations. Pre-illness, non-specific affective symptomatology may be of greater predictive power than most psychotic phenomena.

Conclusions. Traditional high-risk designs embody many problems but are able to distinguish non-specific markers from illness predictors, and are ideally suited to exploring the evolution of schizophrenia both clinically and biologically (especially with imaging techniques). The EHRS supports the view that greater specificity may accrue to cognitive domains as precursors of predictive utility.

Type
Invited Review
Copyright
© 2006 Cambridge University Press

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