Abstract

Assessment of Proteomic Measures Across Serious Psychiatric Illness

Author(s): S. Charles Schulz, Shauna Overgaard, David J. Bond, Rajesh Kaldate

The diagnoses of serious psychiatric illnesses, such as schizophrenia, schizoaffective disorder, and bipolar disorder, rely on the subjective recall and interpretation of often overlapping symptoms, and are not based on the objective pathophysiology of the illnesses. The subjectivity of symptom reporting and interpretation contributes to the delay of accurate diagnoses and limits effective treatment of these illnesses. Proteomics, the study of the types and quantities of proteins an organism produces, may offer an objective biological approach to psychiatric diagnosis. For this pilot study, we used the Myriad RBM Discovery Map 250+ platform to quantify 205 serum proteins in subjects with schizophrenia (n=26), schizoaffective disorder (n=20), bipolar disorder (n=16), and healthy controls with no psychiatric illness (n=23). Fifty-seven analytes that differed significantly between groups were used for multivariate modeling with linear discriminant analysis (LDA). Diagnoses generated from these models were compared to SCID-generated clinical diagnoses to determine whether the proteomic markers: 1) distinguished the three disorders from controls, and 2) distinguished between the three disorders. We found that a series of binary classification models including 8–12 analytes produced separation between all subjects and controls, and between each diagnostic group and controls. There was a high degree of accuracy in the separations, with training areas-under-the-curve (AUC) of 0.94–1.0, and crossvalidation AUC of 0.94–0.95. Models with 7–14 analytes produced separation between the diagnostic groups, though less robustly, with training AUC of 0.72–1.0 and validation AUC of 0.69–0.89. While based on a small sample size, not adjusted for medication state, these preliminary results support the potential of proteomics as a diagnostic aid in psychiatry. The separation of schizophrenia, schizoaffective disorder, and bipolar disorder suggests that further work in this area is warranted.

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