This proposal is designed to produce data for the development of a biological classification of schizophrenia and bipolar disorder, based on high density microarray measurements of transcribed white blood cell (leukocyte) mRNA. The rationale behind this proposal is based on two sources of data; 1) reports in the literature that document differential expression of immune system response mediators among patients with schizophrenia and bipolar disorder, and 2) preliminary results obtained as part of a recently completed NIMH B-start grant. In the preliminary experiments, the PI utilized global gene expression analysis of peripheral leukocytes as a classification medium for schizophrenia. The study results were striking; unsupervised hierarchical clustering of the gene expression data from eight schizophrenic patients and five control subjects, resulted in classification of all the samples into their correct group (schizophrenic patients or healthy controls). In addition, and of significance to this current proposal, hierarchical clustering of the gene expression data from the schizophrenic patients and from two bipolar disorder patients, resulted in the bipolar disorder patients grouping into a single, discrete subnode from the schizophrenics. Based on this exciting result, the present proposal has been developed with the following specific aims: la) To collect peripheral blood leukocytes from 25 men with bipolar disorder and 25 men with schizophrenia, over the two year period of this project, lb) To measure global gene expression in the leukocyte samples, using Affymetrix GeneChip microarray technology, and 2) To employ the leukocyte gene expression dataset obtained under Specific Aim 1 of the proposal, in hierarchical clustering and supervised learning algorithms to identify and validate multi-gene expression signatures that distinguish between the subjects by diagnostic group. The current proposed study, which involves the collection of leukocyte samples from patients with bipolar disorder or schizophrenia, has been designed to extend our positive findings from the preliminary investigation of schizophrenics. We are optimistic that the completion of this proposed exploratory study will lead to the creation of multigene expression signatures that can classify leukocyte samples into bipolar disorder or schizophrenic patient groups, and which can be employed to predict the classes of unknown samples. If the validity of our approach is demonstrated in this exploratory R21 study, our longer-term aims for this research are to increase the scope of this work by: 1) increasing the number of subjects in our datasets to the level of acceptable statistical power, 2) investigating the feasibility of a biological signature for diagnosis of schizophrenia and bipolar disorder, and to extend this investigation to include other psychiatric disorders such as major depression, and 3) investigating correlations between patient responses to treatment regimes and biological expression signatures. These biological signatures may, in turn, stimulate the development of targeted novel medications. Finally, it may be possible to perform additional follow-up studies, recruiting families with members at increased risk of developing bipolar disorder or schizophrenia, which would allow us to test whether gene expression patterns that classify the disorders are present in premorbid subjects and whether it is possible to predict risk of illness. The public health benefits of a biological classification of psychiatric disorders are potentially large, especially if predictive testing in the premorbid stage is possible, raising the possibility of targeted preventative interventions.