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April 10, 2019

Toward High Reproducibility and Accountable Heterogeneity in Schizophrenia Research

Author Affiliations
  • 1Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore
  • 2Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging and Informatics, University of Southern California Keck School of Medicine, Los Angeles
JAMA Psychiatry. 2019;76(7):680-681. doi:10.1001/jamapsychiatry.2019.0208

Schizophrenia is a neuropsychiatric illness with substantial individual variability. The heterogeneity spans most aspects of the illness: genetics, environmental risk factors, age at onset, symptoms, treatment response, and long-term prognosis. The causative mechanisms of these heterogeneities have remained elusive from Bleuler’s definition of the disorder1 to modern clinical and imaging studies. While variability may be because of distinct clinical or neurobiological subtypes, efforts to confirm this hypothesis have not yet succeeded. In fact, heterogeneity has prevented reproducible research on the effects of candidate genes and clinical, neuroanatomical, and functional findings. As a result, some call to retire the terms schizophrenia or schizoaffective disorder in favor of psychosis spectrum or psychosis syndrome, arguing that the former diagnoses incorrectly imply discrete illnesses.2,3 Recent big data studies, such as those conducted by Alnæs et al4 in this issue of JAMA Psychiatry, provide a new way of examining individual heterogeneity and reproducibility of observations associated with this illness.

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