Affect Regulation–Related Emergent Brain Network Properties Differentiate Depressed Bipolar Disorder From Major Depression and Track Risk for Bipolar Disorder

• Published in: Biological psychiatry : cognitive neuroscience and neuroimaging Vol. 7; no. 8; pp. 765 - 773
• Main Authors: Spielberg, Jeffrey M., Sadeh, Naomi, Cha, Jungwon, Matyi, Melanie A., Anand, Amit
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.08.2022
• Subjects: Bipolar; Bipolar Disorder - diagnosis; Brain; Brain networks; Depression; Depressive Disorder, Major - diagnosis; Emotion; Emotion regulation; Graph theory; Humans; Iatrogenic Disease; Magnetic Resonance Imaging - methods; Mania; Bipolar; Depression; Graph theory; Emotion; Brain networks; Emotion regulation
• ISSN: 2451-9022; 2451-9030
• DOI: 10.1016/j.bpsc.2021.09.007

Individuals with or at risk for bipolar disorder (BD) often present initially for the treatment of depressive symptoms. Unfortunately, pharmacological treatments for major depressive disorder (MDD) can be iatrogenic, precipitating mania that may not have otherwise occurred. Current diagnostic procedures rely solely on self-reported/observable symptoms, and thus alternative data sources, such as brain network properties, are needed to supplement current self-report/observation–based indices of risk for mania. Brain connectivity during affect maintenance/regulation was examined in a large (N = 249), medication-free sample of currently depressed patients with BD (n = 50) and MDD (n = 116) and healthy control subjects (n = 83). BD risk was categorized in a subset of patients with MDD. We used graph theory to identify emergent network properties that differentiated between patients with BD and MDD and between patients with MDD at high and low risk for BD. BD and MDD differed in the extent to which the rostral anterior cingulate cortex was embedded in the local network, amount of influence the hippocampus exerted over global network communication, and clarity of orbitofrontal cortex communication. Patients with MDD at high risk for BD showed a pattern of local network clustering around the right amygdala that was similar to the pattern observed in healthy control subjects, whereas patients with MDD at low risk for BD deviated from this pattern. BD and MDD differed in emergent network mechanisms subserving affect regulation, and amygdala properties tracked BD risk in patients with MDD. If replicated, our findings may be combined with other markers to assess the presence of BD and/or BD risk in individuals presenting with depressive symptoms to prevent the use of iatrogenic treatments.