Individualized prediction of consummatory anhedonia from functional connectome in major depressive disorder

Fengqiong Yu; Huihua Fang; Junfeng Zhang; Zhihao Wang; Hui Ai; Veronica P Y Kwok; Ya Fang; Yaru Guo; Xin Wang; Chunyan Zhu; Yuejia Luo; Pengfei Xu; Kai Wang

doi:10.1002/da.23292

Individualized prediction of consummatory anhedonia from functional connectome in major depressive disorder

Depress Anxiety. 2022 Dec;39(12):858-869. doi: 10.1002/da.23292. Epub 2022 Nov 3.

Authors

Fengqiong Yu^{1

2

3

4}, Huihua Fang^{5

6}, Junfeng Zhang⁷, Zhihao Wang⁷, Hui Ai⁵, Veronica P Y Kwok⁸, Ya Fang^{2

4

9}, Yaru Guo^{2

4

9}, Xin Wang^{2

4

9}, Chunyan Zhu^{2

4

9}, Yuejia Luo⁷, Pengfei Xu^{7

8}, Kai Wang^{2

3

4

9}

Affiliations

¹ Research Center for Translational Medicine, The Second Hospital of Anhui Medical University, Hefei, China.
² School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China.
³ Department of Neurology, The First Affiliated Hospital of Anhui Medical University, The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, Anhui Province, China.
⁴ Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.
⁵ Shenzhen Key Laboratory of Affective and Social Neuroscience, Magnetic Resonance Imaging Center, Center for Brain Disorders and Cognitive Sciences, Shenzhen University, Shenzhen, China.
⁶ Department of Psychology, University of Mannheim, Mannheim, Germany.
⁷ Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (BNU), Faculty of Psychology, Beijing Normal University, Beijing, China.
⁸ Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen, China.
⁹ Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Anhui Province, China.

PMID: 36325748
DOI: 10.1002/da.23292

Abstract

Background: Anhedonia is a key symptom of major depressive disorder (MDD) and other psychiatric diseases. The neural basis of anhedonia has been widely examined, yet the interindividual variability in neuroimaging biomarkers underlying individual-specific symptom severity is not well understood.

Methods: To establish an individualized prediction model of anhedonia, we applied connectome-based predictive modeling (CPM) to whole-brain resting-state functional connectivity profiles of MDD patients.

Results: The CPM can successfully and reliably predict individual consummatory but not anticipatory anhedonia. The predictive model mainly included salience network (SN), frontoparietal network (FPN), default mode network (DMN), and motor network. Importantly, subsequent computational lesion prediction and consummatory-specific model prediction revealed that connectivity of the SN with DMN and FPN is essential and specific for the prediction of consummatory anhedonia.

Conclusions: This study shows that brain functional connectivity, especially the connectivity of SN-FPN and SN-DMN, can specifically predict individualized consummatory anhedonia in MDD. These findings suggest the potential of functional connectomes for the diagnosis and prognosis of anhedonia in MDD and other disorders.

Keywords: anhedonia; connectome-based predictive modeling; default mode network; depression; frontoparietal network; salience network.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Anhedonia
Brain / diagnostic imaging
Connectome* / methods
Depressive Disorder, Major* / psychology
Humans
Magnetic Resonance Imaging / methods
Neural Pathways