Genes for schizophrenia and bipolar disorder? Implications for psychiatric nosology

Abstract

It has been conventional for psychiatric research, including the search for predisposing genes, to proceed under the assumption that schizophrenia and bipolar disorder are separate disease entities with different underlying etiologies. These represent Emil Kraepelin's traditional dichotomous classification of the so-called "functional" psychoses and form the basis of modern diagnostic practice. However, findings emerging from many fields of psychiatric research do not fit well with this model. In particular, the pattern of findings emerging from genetic studies shows increasing evidence for an overlap in genetic susceptibility across the traditional classification categories-including association findings at DAOA(G72), DTNBP1 (dysbindin), COMT, BDNF, DISC1, and NRG1. The emerging evidence suggests the possibility of relatively specific relationships between genotype and psychopathology. For example, DISC1 and NRG1 may confer susceptibility to a form of illness with mixed features of schizophrenia and mania. The elucidation of genotype-phenotype relationships is at an early stage, but current findings highlight the need to consider alternative approaches to classification and conceptualization for psychiatric research rather than continuing to rely heavily on the traditional Kraepelinian dichotomy. As psychosis susceptibility genes are identified and characterized over the next few years, this will have a major impact on our understanding of disease pathophysiology and will lead to changes in classification and the clinical practice of psychiatry.

Fig. 1.

Simplified hypothesized relationship between specific susceptibility genes (above the black line) and clinical phenotype (below the line) using the model outlined in Craddock and Owen The overlapping ellipses represent overlapping sets of genes: red influencing susceptibility to phenotypes with prominent schizophrenia-like features, blue to prominent mood features, and green to phenotypes with a prominent mix of both types of feature. These assignments are based on current data and are likely to require revision as more data accumulate.