Development of a Novel Neuro-immune and Opioid-Associated Fingerprint with a Cross-Validated Ability to Identify and Authenticate Unknown Patients with Major Depression: Far Beyond Differentiation, Discrimination, and Classification

Major depressive disorder (MDD) is characterized by signaling aberrations in interleukin (IL)-6, IL-10, beta-endorphins as well as mu (MOR) and kappa (KOR) opioid receptors. Here we examined whether these biomarkers may aid in the classification of unknown subjects into the target class MDD. The aforementioned biomarkers were assayed in 60 first-episode, drug-naive depressed patients and 30 controls. We used joint principal component analysis (PCA) performed on all subjects to check whether subjects cluster by classes; support vector machine (SVM) with 10-fold validation; and linear discriminant analysis (LDA) and SIMCA performed on calibration and validation sets and we computed the figures of merit and learnt from the data. PCA shows that both groups were well separated using the first three PCs, while correlation loadings show that all five biomarkers have discriminatory value. SVM and LDA yielded an accuracy of 100% in validation samples. Using SIMCA, there was a highly significant discrimination of both groups (model-to-model distance = 110.2); all biomarkers showed a significant discrimination and modeling power, while 100% of the patients were authenticated as MDD cases with a specificity of 93.3%. We have delineated that MDD is a distinct class with respect to neuro-immune and opioid biomarkers and that future unknown subjects can be authenticated as having MDD using this SIMCA fingerprint. Precision psychiatry should employ SIMCA to (a) authenticate patients as belonging to the claimed target class and identify other subjects as outsiders, members of another class, or aliens; and (b) acquire knowledge through learning from the data by constructing a biomarker fingerprint of the target class.