Functional Connectivity Disturbances of the Locus Coeruleus in Chronic Insomnia Disorder

Nat Sci Sleep. 2022 Aug 2:14:1341-1350. doi: 10.2147/NSS.S366234. eCollection 2022.

Abstract

Introduction: In recent years, people have gained a profound understanding of chronic insomnia disorder (CID), but the pathophysiological mechanism of CID is still unclear. There is some evidence that the locus coeruleus (LC) is involved in the regulation of wakefulness in CID, but there have been few studies using brain functional imaging. The purpose of this study was to evaluate the resting-state functional connectivity (FC) between the LC and other brain voxels in CID and whether these abnormal FC are involved in the regulation of wakefulness.

Methods: A total of 49 patients with chronic insomnia disorder and 47 healthy controls (HC) matched for gender, age, and education were examined with rs-fMRI in this study. The LC was selected as the region of interest, and then seed-based analysis was conducted on the LC and other voxels to obtain the brain regions with abnormal FC. The correlation between the FC value of the abnormal connection area and the clinical scale score was analyzed.

Results: Compared with the HC, the FC between the LC and right precuneus, right posterior cingulate cortex, left middle temporal gyrus, left calcarine, and right superior orbitofrontal cortex was significantly enhanced (p < 0.05, FDR correction), and the functional connectivity signal value between the locus coeruleus and left middle temporal gyrus was positively correlated with the Self-Rating Depression Scale (p = 0.021).

Conclusion: The abnormal FC between the LC and multiple brain regions may contribute to a better understanding of the neurobiological mechanism of CID.

Keywords: chronic insomnia disorder; default mode network; functional connectivity; locus coeruleus; seed-based analysis.

Grants and funding

This study was funded by grants from the National Natural Science Foundation of China (Grant Nos. 81771807 and 81901729), the Science and Technology Planning Project of Guangzhou (Grant No. 202002030234) and National Science Foundation for Young Scientists of China (Grant No. 82001792).