Triglyceride Level is Predicted by Reduced Functional Connectivity Between Nodes of Salience and Default Networks

Abstract

Metabolic disorders like insulin resistance and dyslipidemia can indirectly affect brain activity and have separately been found to be associated with depressive symptoms. In addition, previous research has shown that Depression Disorder (MDD) is associated with specific differences in cross-network connectivity. Yet, no research has analyzed how metabolic variables are associated with the differences in network-level brain connectivity in general, and whether they map onto the patterns characteristic of MDD. Using data from patients in the Leipzig study for Mind-Body-Emotion Interactions (LEMON) (N = 193), we investigated whether metabolic variables (concentration of triglycerides, HDL, the ratio of triglycerides to HDL (TRIG/HDL), hemoglobin a1c) predict the level of internetwork connectivity between the so-called triple networks. HDL and hemoglobin a1c did not significantly predict connectivity between any networks, while TRIG/HDL was significantly predicted by reduced SN-FPCN connectivity, and triglyceride levels was significantly predicted by reduced SN-DN and reduced SN-FPCN connectivity. In a more fine-grained analysis, we found that these metabolic variables were specifically predicted by connections between the DN lateral parietal areas and SN nodes (predicting triglycerides), and connections between the LPFC area and the SN Anterior Insula nodes (predicting triglycerides and TRIG/HDL). This finding shows no resemblance to the connectivity patterns observed in depression, either in our sample or in previous depression research, and therefore serves as a reminder that the link between peripheral metabolism and depression is highly indirect, and metabolic theories will face challenges when expected to operate at the same level of analysis that is used to describe the mechanisms underlying depression.