Patterns of deficits in brain function in bipolar disorder and schizophrenia: A cluster analytic study

Abstract

Historically, bipolar disorder and schizophrenia have been considered distinct disorders with different etiologies. Growing evidence suggests that overlapping genetic influences contribute to risk for these disorders and that each disease is genetically heterogeneous. Using cluster analytic methods, we empirically identified homogeneous subgroups of patients, their relatives, and controls based on distinct neurophysiologic profiles. Seven phenotypes were collected from two independent cohorts at two institutions. K-means clustering was used to identify neurophysiologic profiles. In the analysis of all participants, three distinct profiles emerged: “globally impaired”, “sensory processing”, and “high cognitive”. In a secondary analysis, restricted to patients only, we observed a similar clustering into three profiles. The neurophysiological profiles of the Schizophrenia (SZ) and Bipolar Disorder (BPD) patients did not support the Diagnostic and Statistical Manual of Mental Disorders (DSM) diagnostic distinction between these two disorders. Smokers in the globally impaired group smoked significantly more cigarettes than those in the sensory processing or high cognitive groups. Our results suggest that empirical analyses of neurophysiological phenotypes can identify potentially biologically relevant homogenous subgroups independent of diagnostic boundaries. We hypothesize that each neurophysiology subgroup may share similar genotypic profiles, which may increase statistical power to detect genetic risk factors.