Clinical, cortical thickness and neural activity predictors of future affective lability in youth at risk for bipolar disorder: initial discovery and independent sample replication

Abstract

We aimed to identify markers of future affective lability in youth at bipolar disorder risk from the Pittsburgh Bipolar Offspring Study (BIOS) (n=41, age=14, SD=2.30), and validate these predictors in an independent sample from the Longitudinal Assessment of Manic Symptoms study (LAMS) (n=55, age=13.7, SD=1.9). We included factors of mixed/mania, irritability, and anxiety/depression (29 months post MRI scan) in regularized regression models. Clinical and demographic variables, along with neural activity during reward and emotion processing and gray matter structure in all cortical regions at baseline, were used to predict future affective lability factor scores, using regularized regression. Future affective lability factor scores were predicted in both samples by unique combinations of baseline neural structure, function, and clinical characteristics. Lower bilateral parietal cortical thickness, greater left ventrolateral prefrontal cortex thickness, lower right transverse temporal cortex thickness, greater self-reported depression, mania severity, and age at scan predicted greater future mixed/mania factor score. Lower bilateral parietal cortical thickness, greater right entorhinal cortical thickness, greater right fusiform gyral activity during emotional face processing, diagnosis of Major Depressive Disorder, and greater self-reported depression severity predicted greater irritability factor score. Greater self-reported depression severity predicted greater anxiety/depression factor score. Elucidating unique clinical and neural predictors of future specific affective lability factors is a step toward identifying objective markers of bipolar disorder risk, to provide neural targets to better guide and monitor early interventions in bipolar disorder at-risk youth.

Great Expectations: A Critical Review of and Suggestions for the Study of Reward Processing as a Cause and Predictor of Depression

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The correlation between fractional amplitude of low-frequency fluctuation-based resting-state functional magnetic resonance imaging and facial emotion recognition ability in patients with first-episode schizophrenia

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