MIXTURE DISTRIBUTIONS IN PSYCHIATRIC RESEARCH

Abstract

This paper describes the application of Gaussian mixture distributions to biological marker research in psychiatry. Mixtures of univariate and multivariate normal distributions can be used to determine if diagnostically similar psychiatric patients belong to biologically distinct subpopulations. The resulting biological subtypes may be important in understanding the etiology of psychiatric disorders. The general model and estimation procedure are described. The method is illustrated using 2 examples of biological data: red cell membranes and monoamine oxidase activity data in normal individuals having no family history of psychiatric illness, the 1st-degree relatives of bipolar depressed patients and a heterogeneous patient population; and smooth pursuit eye movements that classify relatives of schizophrenics, nonschizophrenics and normal controls into biologically distinct populations.