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White-Matter Functional Topology: A Neuromarker for Classification and Prediction in Unmedicated Depression

46 Pages Posted: 10 Aug 2020

See all articles by Wei Liao

Wei Liao

University of Electronic Science and Technology of China (UESTC) - The Clinical Hospital of Chengdu Brain Science Institute; University of Electronic Science and Technology of China (UESTC) - Center for Information in Medicine

Jiao Li

University of Electronic Science and Technology of China (UESTC) - The Clinical Hospital of Chengdu Brain Science Institute; University of Electronic Science and Technology of China (UESTC) - Center for Information in Medicine

Heng Chen

University of Electronic Science and Technology of China (UESTC) - The Clinical Hospital of Chengdu Brain Science Institute

Feiyang Fan

University of Electronic Science and Technology of China (UESTC) - The Clinical Hospital of Chengdu Brain Science Institute

Jiang Qiu

Southwest University - Faculty of Psychology

Lian Du

Chongqing Medical University - Department of Psychiatry

Jinming Xiao

University of Electronic Science and Technology of China (UESTC) - The Clinical Hospital of Chengdu Brain Science Institute; University of Electronic Science and Technology of China (UESTC) - Center for Information in Medicine

Xujun Duan

University of Electronic Science and Technology of China (UESTC) - The Clinical Hospital of Chengdu Brain Science Institute; University of Electronic Science and Technology of China (UESTC) - Center for Information in Medicine

Huafu Chen

University of Electronic Science and Technology of China (UESTC) - The Clinical Hospital of Chengdu Brain Science Institute; University of Electronic Science and Technology of China (UESTC) - Center for Information in Medicine; University of Electronic Science and Technology of China (UESTC) - Key Laboratory for Neuroinformation of Ministry of Education

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Abstract

Aberrant topological organization of brain connectomes underlies pathological mechanisms in major depressive disorder (MDD). However, accumulating evidence has only focused on functional organization in brain gray-matter, ignoring functional information in white-matter (WM) that has been confirmed to have reliable and stable topological organizations. The present study aimed to characterize the functional pattern disruptions of MDD from a new perspective – WM functional connectome topological organization. A case-control, cross-sectional resting-state functional magnetic resonance imaging study was conducted on both discovery [91 unmedicated MDD patients, and 225 healthy controls (HCs)], and replication samples (34 unmedicated MDD patients, and 25 HCs). The WM functional networks were constructed in 128 brain regions, and their global topological properties (e.g., small-worldness) were analyzed using graph theory-based approaches. At the system-level, ubiquitous small-worldness architecture and local information-processing capacity were detectable in unmedicated MDD patients but were less salient than in HCs, implying a shift toward randomization in MDD WM functional connectomes. Consistent results were replicated in an independent sample. For clinical applications, small-world topology of WM functional connectome showed a predictive effect on disease severity (HAMD scores) in discovery sample ( r = 0.34, p = 0.001). Furthermore, the topologically-based classification model could be generalized to discriminate MDD patients from HCs in replication sample (accuracy, 76%; sensitivity, 74%; specificity, 80%). Our results highlight a reproducible topologically shifted WM functional connectome structure and provide possible clinical applications involving an optimal small-world topology as a neuromarker for the classification and prediction of MDD patients.

Funding Statement: This work was supported by the National Key Project of Research and Development (2018AAA0100705), National Natural Science Foundation of China (61871077, 61533006, U1808204, and 61673089), and Sichuan Science and Technology Program (2018TJPT0016).

Declaration of Interests: The authors declare no conflict of interest.

Ethics Approval Statement: This study was approved by the Ethics Committee of Southwest University and First Affiliated Hospital of Chongqing Medical University. Written informed consent was obtained from all subjects

Keywords: Resting-state functional magnetic resonance imaging; unmedicated major depressive disorder; neuromarker; small-world topology; white-matter functional connectome

Suggested Citation

Liao, Wei and Li, Jiao and Chen, Heng and Fan, Feiyang and Qiu, Jiang and Du, Lian and Xiao, Jinming and Duan, Xujun and Chen, Huafu, White-Matter Functional Topology: A Neuromarker for Classification and Prediction in Unmedicated Depression (4/24/2020). Available at SSRN: https://ssrn.com/abstract=3588513 or http://dx.doi.org/10.2139/ssrn.3588513

Wei Liao

University of Electronic Science and Technology of China (UESTC) - The Clinical Hospital of Chengdu Brain Science Institute ( email )

Chengdu
China

University of Electronic Science and Technology of China (UESTC) - Center for Information in Medicine ( email )

Chengdu
China

Jiao Li

University of Electronic Science and Technology of China (UESTC) - The Clinical Hospital of Chengdu Brain Science Institute

Chengdu
China

University of Electronic Science and Technology of China (UESTC) - Center for Information in Medicine

Chengdu
China

Heng Chen

University of Electronic Science and Technology of China (UESTC) - The Clinical Hospital of Chengdu Brain Science Institute

Chengdu
China

Feiyang Fan

University of Electronic Science and Technology of China (UESTC) - The Clinical Hospital of Chengdu Brain Science Institute

Chengdu
China

Jiang Qiu

Southwest University - Faculty of Psychology

Chongqing
China

Lian Du

Chongqing Medical University - Department of Psychiatry

China

Jinming Xiao

University of Electronic Science and Technology of China (UESTC) - The Clinical Hospital of Chengdu Brain Science Institute

Chengdu
China

University of Electronic Science and Technology of China (UESTC) - Center for Information in Medicine

Chengdu
China

Xujun Duan

University of Electronic Science and Technology of China (UESTC) - The Clinical Hospital of Chengdu Brain Science Institute

Chengdu
China

University of Electronic Science and Technology of China (UESTC) - Center for Information in Medicine

Chengdu
China

Huafu Chen (Contact Author)

University of Electronic Science and Technology of China (UESTC) - The Clinical Hospital of Chengdu Brain Science Institute ( email )

Chengdu
China

University of Electronic Science and Technology of China (UESTC) - Center for Information in Medicine ( email )

Chengdu
China

University of Electronic Science and Technology of China (UESTC) - Key Laboratory for Neuroinformation of Ministry of Education ( email )

Chengdu, 610054
China

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