Age at onset mixture analysis and systematic comparison in schizophrenia spectrum disorders: Is the onset heterogeneity dependent on heterogeneous diagnosis?

Abstract

A major obstacle to the identification of the neurobiological correlates of schizophrenia is the substantial diagnostic heterogeneity of this disorder. Dividing schizophrenia into “early” and “late” subtypes may reduce heterogeneity and facilitate identification of biomarkers related to this disease. Our objective was to assess the presence of different sub-groups in schizophrenia by age at onset analysis. The participants in this study were 612 unrelated patients with schizophrenia. Admixture analysis was applied in order to identify a model of separate normal distributions of age at onset characterized by different means, variances and population proportions to evaluate the effect of winter birth and ethnicity on early onset schizophrenia. The best-fitting model suggested three subgroups with means and standard deviations of 17.11±2.09, 21.96±3.43 and 30.02±7.1years, comprising 34.6%, 42.6% and 22.8% of the sample respectively. We considered as predictors of early onset schizophrenia: male gender, winter birth, white ethnicity and positive family history for psychiatric disorders. Earlier onset was significantly associated with male gender. We also compared our age at onset distribution with those published in other studies and we found significant differences with several studies suggesting heterogeneity in age at onset that is likely influenced by diagnostic heterogeneity in applying the DSM-IV criteria. Overall, our study showed that a typical early onset schizophrenia patient is more likely to be a white male with cannabis abuse and positive family history of psychiatric disorders. The heterogeneity in reporting age at onset across different studies suggests the application of more stringent criteria in diagnosing schizophrenia.