Resting-state functional network connectivity is altered in patients with major depressive disorder

Introduction:

Major depressive disorder (MDD) is one of the most common and disabling psychiatric disorders. Its increasing prevalence and huge social and economic burden necessitate improved diagnostic and treatment procedures. To this end, a deeper understanding of the underlying pathophysiological mechanisms is essential. Neuroscientific research of the past decade has formed the current concept of depression as being a disorder of several (large-scale) brain networks, including the Default Mode Network (DMN), Central Executive Network (CEN), and Salience Network (SN) (Mulders et al., 2015). While previous studies reported aberrant within- and between-network connectivity in MDD, sample sizes were relatively small. In the present study, we investigated potential alterations in the above mentioned resting state networks (RSNs) in a large multicentric cohort of N = 995 subjects.

Methods:

Specifically, n = 410 patients with MDD and n = 585 healthy controls were assessed using an 8 min resting-state fMRI (rs-fMRI) sequence. Low-model-order group independent component analysis (gICA) was used to identify the RSNs of interest at the group level. Afterwards, individual RSN maps were obtained through back-reconstruction and compared between groups.

Results:

MDD patients showed, in line with previous studies (e.g. Zhu et al., 2012) though with lower effect size, an increased connectivity in the frontal DMN (PFC) as well as decreased connectivity in posterior parts of the DMN (PCC, left parietal cortex). Within the SN, we found, also with lower effect size than previously reported but in accordance with earlier reports (e.g. Veer et al., 2010), decreased connectivity in frontal parts (anterior insula, right frontal gyrus) and increased connectivity in cingulate cortex.

Conclusion:

In conclusion, even though we found only small effects in a large cohort of n = 410 MDD patients and n = 585 healthy controls, the aforementioned findings are, in principle, consistent with the existing literature and support the notion of depression as a network-based disorder. Nevertheless, previous findings based on small sample sizes should be treated with caution. We therefore emphasize the importance of replication studies in large (multicentric) cohorts that allow more accurate estimations of population effects and are less prone to spurious results.