Towards a multidimensional model of inflamed depression

Major depressive disorder (MDD) continues to impose a significant burden on individuals and society. Existing data support the important role that inflammatory responses play in its pathophysiology, with new findings continuing to be reported. In this narrative review paper, we focus on three dimensions of inflamed depression: risk factors, clinical symptoms, and neurofunctional changes. We aim to answer the following questions: What characteristics most robustly discriminate between inflamed and non-inflamed depression? How can we leverage on these discriminative characteristics to classify inflamed depressed patients? One important point that has emerged is the heterogeneous nature of the relationship between inflammation and depression. Not all inflamed patients are depressed, and not all depressed patients are inflamed. Some risk factors heighten vulnerability to inflamed depression, including childhood adversity, old age, and being female. The inflamed depression subtype has been associated with distinct clinical phenotypes, most robustly with physical symptoms such as sleep problems, changes in appetite, and fatigue. Neurofunctional changes are found in the dopaminergic reward processing pathways. A better characterization of the inflamed depression subtype by leveraging multidimensional data will help craft a more precise treatment for these patients.