Blood ‐based dynamic genomic signature for obsessive–compulsive disorder

This study enrolled 77 patients with OCD, 67 controls with no psychiatric illness, 39 patients with MDD, and 40 with schizophrenia. An OCD‐specific gene signature was identified using blood gene expression analysis to construct a predictive model of OCD that can differentiate this disorder from healthy controls, MDD, and schizophrenia using a logistic regression algorithm. To verify that the genes selected were not derived as a result of chance, the algorithm was tested twice. First, the algorithm was used to predict the cohort with true disease/control status and second, the algorithm predicted the cohort with disease/control status randomly reassigned (null set). A six‐gene panel (COPS7A, FKBP1A, FIBP, TP73 ‐AS1, SDF4, andGOLGA8A) discriminated patients with OCD from healthy controls, MDD, and schizophrenia in the training set (with an area under the receiver ‐operating‐characteristic curve of 0.938; accuracy, 86%; sensitivity, 88%; and specificity, 85%). Our findings indicate that a blood transcriptomic signature can distinguish OCD from healthy controls, MDD, and schizophrenia. This finding further confirms the feasibility of using dynamic blood‐ based genomic signatures in psychiatric disorders and may provide a useful tool for clinical staff engaged in OCD diagnosis and decision making.
Source: American Journal of Medical Genetics Part B: Neuropsychiatric Genetics - Category: Genetics & Stem Cells Authors: Tags: ORIGINAL ARTICLE Source Type: research