Aberrant brain structural–functional connectivity coupling in euthymic bipolar disorder. Issue 12 (24th April 2019)

• Record Type: Journal Article
• Authors: Zhang, Ruibin; Shao, Robin; Xu, Guiyun; Lu, Weicong; Zheng, Wenjing; Miao, Qingzhe; Chen, Kun; Gao, Yanling; Bi, Yanan; Guan, Lijie; McIntyre, Roger S.; Deng, Yue; Huang, Xuejun; So, Kwok‐Fai; Lin, Kangguang
• Is Part Of: Human brain mapping. Volume 40:Issue 12(2019)
• Page Start: 3452
• Page End: 3463
• Publication Date: 2019-04-24
• Subjects: bipolar disorder -- modularity -- predictive analysis -- rich club -- structural–functional coupling; Brain mapping -- Periodicals; 611.81
• DOI: 10.1002/hbm.24608
• Languages: English
• ISSNs: 1065-9471

Abstract

Abstract: Aberrant structural (diffusion tensor imaging [DTI]) and resting‐state functional magnetic resonance imagining connectivity are core features of bipolar disorder. However, few studies have explored the integrity agreement between structural and functional connectivity (SC–FC) in bipolar disorder. We examine SC connectivity coupling index whether could potentially provide additional clinical predictive value for bipolar disorder spectrum disorders besides the intramodality network measures. By examining the structural (DTI) and resting‐state functional network properties, as well as their coupling index, among 57 euthymic bipolar disorder patients (age 13–28 years, 18 females) and 42 age‐ and gender‐matched healthy controls (age 13–28 years, 16 females), we found that compared to controls, bipolar disorder patients showed increased structural rich‐club connectivity as well as decreased functional modularity. Importantly, the coupling strength between structural and functional connectome was decreased in patients compared to controls, which emerged as the most powerful feature discriminating the two groups. Our findings suggest that structural–functional coupling strength could serve as a valuable biological trait‐like feature for bipolar disorder over and above the intramodality network measures. Such measure can have important clinical implications for early identification of bipolar disorder individuals, and inform strategies for prevention of bipolar disorder onset and relapse.