Utilization of never-medicated bipolar disorder patients towards development and validation of a peripheral biomarker profile.

There are currently no biological tests that differentiate patients with bipolar disorder (BPD) from healthy controls. While there is evidence that peripheral gene expression differences between patients and controls can be utilized as biomarkers for psychiatric illness, it is unclear whether current use or residual effects of antipsychotic and mood stabilizer medication drives much of the differential transcription. We therefore tested whether expression changes in first-episode, never-medicated BPD patients, can contribute to a biological classifier that is less influenced by medication and could potentially form a practicable biomarker assay for BPD. We employed microarray technology to measure global leukocyte gene expression in first-episode (n=3) and currently medicated BPD patients (n=26), and matched healthy controls (n=25). Following an initial feature selection of the microarray data, we developed a cross-validated 10-gene model that was able to correctly predict the diagnostic group of the training sample (26 medicated patients and 12 controls), with 89% sensitivity and 75% specificity (p<0.001). The 10-gene predictor was further explored via testing on an independent cohort consisting of three pairs of monozygotic twins discordant for BPD, plus the original enrichment sample cohort (the three never-medicated BPD patients and 13 matched control subjects), and a sample of experimental replicates (n=34). 83% of the independent test sample was correctly predicted, with a sensitivity of 67% and specificity of 100% (although this result did not reach statistical significance). Additionally, 88% of sample diagnostic classes were classified correctly for both the enrichment (p=0.015) and the replicate samples (p<0.001). We have developed a peripheral gene expression biomarker profile, that can classify healthy controls from patients with BPD receiving antipsychotic or mood stabilizing medication, which has both high sensitivity and specificity. Moreover, assay of three first-episode patients who had never received such medications, to first enrich the expression dataset for disease-related genes independent of medication effects, and then to test the 10-gene predictor, validates the peripheral biomarker approach for BPD.

The NKI-Rockland Sample: A Model for Accelerating the Pace of Discovery Science in Psychiatry.

The National Institute of Mental Health strategic plan for advancing psychiatric neuroscience calls for an acceleration of discovery and the delineation of developmental trajectories for risk and resilience across the lifespan. To attain these objectives, sufficiently powered datasets with broad and deep phenotypic characterization, state-of-the-art neuroimaging, and genetic samples must be generated and made openly available to the scientific community. The enhanced Nathan Kline Institute-Rockland Sample (NKI-RS) is a response to this need. NKI-RS is an ongoing, institutionally centered endeavor aimed at creating a large-scale (N > 1000), deeply phenotyped, community-ascertained, lifespan sample (ages 6-85 years old) with advanced neuroimaging and genetics. These data will be publically shared, openly, and prospectively (i.e., on a weekly basis). Herein, we describe the conceptual basis of the NKI-RS, including study design, sampling considerations, and steps to synchronize phenotypic and neuroimaging assessment. Additionally, we describe our process for sharing the data with the scientific community while protecting participant confidentiality, maintaining an adequate database, and certifying data integrity. The pilot phase of the NKI-RS, including challenges in recruiting, characterizing, imaging, and sharing data, is discussed while also explaining how this experience informed the final design of the enhanced NKI-RS. It is our hope that familiarity with the conceptual underpinnings of the enhanced NKI-RS will facilitate harmonization with future data collection efforts aimed at advancing psychiatric neuroscience and nosology.

Evidence for association of hyperprolinemia with schizophrenia and a measure of clinical outcome.

There are multiple genetic links between schizophrenia and a deficit of proline dehydrogenase (PRODH) enzyme activity. However, reports testing for an association of schizophrenia with the resulting proline elevation have been conflicting. The objectives of this study were to investigate whether hyperprolinemia is associated with schizophrenia, and to measure the relationship between plasma proline, and clinical features and symptoms of schizophrenia. We performed a cross-sectional case-control study, comparing fasting plasma proline in 90 control subjects and 64 schizophrenic patients and testing for association of mild to moderate hyperprolinemia with schizophrenia. As secondary analyses, the relationship between hyperprolinemia and five measures of clinical onset, symptoms and outcome were investigated. Patients had significantly higher plasma proline than matched controls (p<0.0001), and categorical analysis of gender adjusted hyperprolinemia showed a significant association with schizophrenia (OR 6.15, p=0.0003). Hyperprolinemic patients were significantly older at their first hospitalization (p=0.015 following correction for multiple testing). While plasma proline level was not related to total, positive or negative symptoms, hyperprolinemic status had a significant effect on length of hospital stay (p=0.005), following adjustment for race, BPRS score, and cross-sectional time from admission to proline measurement. Mild to moderate hyperprolinemia is a significant risk factor for schizophrenia, and may represent an intermediate phenotype in the disease. Hyperprolinemic patients have a significantly later age of first psychiatric hospitalization, suggestive of later onset, and hospital stays 46% longer than non-hyperprolinemic subjects. These findings have implications in the etiology of schizophrenia, and for the clinical management of these patients.