Inflammation and decreased functional connectivity in a widely-distributed network in depression: Centralized effects in the ventral medial prefrontal cortex.

Affiliation

School of Psychology and Sociology, Shenzhen University, Shenzhen, Guangdong 518060, China; Shenzhen Key Laboratory of Affective and Social Cognitive Science, Shenzhen University, Shenzhen, Guangdong 518060, China; Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA 30322, USA. Electronic address: [Email]

Abstract

Major depressive disorder is a heterogeneous disease involving widespread disruptions in functional brain networks, the neurobiological mechanisms of which are poorly understood. Amassing evidence supports innate immune activation as one pathophysiologic mechanism contributing to depression in a subgroup of patients with elevated inflammatory markers. Although inflammation is known to alter monoamine and glutamate neurotransmitters, little work has been done to understand its role in network dysfunction in patients with depression. Here we conducted a large-scale network-based analyses of resting-state functional magnetic resonance imaging (rfMRI) data acquired from depressed patients with varying levels of inflammation to develop a comprehensive characterization of network alterations as an effect of inflammation. Complementary approaches of global brain connectivity and parcellation-based network analysis applied to the whole brain revealed that increased plasma C-reactive protein (CRP) was associated with reduced functional connectivity in a widely-distributed network including ventral striatum, parahippocampal gyrus/amygdala, orbitofrontal and insular cortices, and posterior cingulate cortex. These broad alterations were centralized in the ventral medial prefrontal cortex (vmPFC), representing a hub for the effects of inflammation on network function in the whole brain. When feeding the identified multivariate network features into a machine learning algorithm of support vector regression, we achieved high prediction accuracies for depressive symptoms that have been associated with inflammation in previous studies including anhedonia and motor slowing. These findings extend and broaden previous observations from hypothesis-driven studies, providing further support for inflammation as a distinct contributing factor to network dysfunction and symptom severity in depression.

Keywords

C-reactive protein,Depression,Functional connectivity,Inflammation,Resting-state functional magnetic resonance imaging,Ventral medial prefrontal cortex,