Comparison Analysis between the Medication Efficacy of the Milnacipran and Functional Connectivity of Neural Networks in Fibromyalgia Patients

Abstract

Milnacipran is a reuptake inhibitor of both serotonin and noradrenaline, used in the treatment of fibromyalgia with severe depression. However, few studies have been conducted on the efficacies of milnacipran drug on the functional connectivity of the neural network. The authors aimed to find the correlation between the drug efficacy and the changes in neural network in fibromyalgia patients. Resting-state-functional magnetic resonance imaging (rs-fMRI) were obtained before and after milnacipran drug administration. Graph theory indexes and small-worldness were calculated using preprocessed blood-oxygen-level-dependent signals from the rs-fMRI scans of 14 brain regions-of-interest. Statistical analyses were conducted to compare the topological network parameters. Significant changes in the neural network indexes appeared in three of the 14 brain regions-of-interest. In the pain network, the average path length on the left side of Brodmann area 32 was shortened. In the default mode network, functional connectivity changes were observed in the left lateral parietal cortex and medial prefrontal cortex. In the left lateral parietal cortex, the degree and betweenness centrality increased, whereas the clustering coefficient decreased. In the medial prefrontal cortex, local efficiency decreased. The small-worldness declined after milnacipran medication. The present results demonstrate that functional connectivity indexes in the brains of female fibromyalgia patients obtained from rs-fMRI data can be used as potential prognosis markers of milnacipran drug treatment.

Keywords

• fibromyalgia
• milnacipran
• drug efficacy
• graph theory
• rs-fMRI
• neural network connectivity