Gray matter volume and corresponding covariance connectivity are biomarkers for major depressive disorder

• Published in: Brain research Vol. 1837; p. 148986
• Main Authors: Hu, Xiao, Cheng, Bochao, Tang, Yuying, Long, Tong, Huang, Yan, Li, Pei, Song, Yu, Song, Xiyang, Li, Kun, Yin, Yijie, Chen, Xijian
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 15.08.2024
• Subjects: Classification; Grey matter volume; Major depressive disorder; Structural covariance connectivity; Major depressive disorder; Grey matter volume; Structural covariance connectivity; Classification
• ISSN: 0006-8993; 1872-6240
• DOI: 10.1016/j.brainres.2024.148986

Gray matter volume, group and individual structural covariance connectivity, transcriptome and machine learning were used to reveal structural, connectivity and molecular basis for major depressive disorder. [Display omitted] •First episode, medication-naïve patients with MDD were recruited to excluded the effect of different disease durations and treatments.•The abnormal GMV and group-level/individual-level covariance connections were applied to classify MDD from HC.•Allen Human Brain Atlas (AHBA) was applied and revealed the genetic basis for the changes of GMV. The major depressive disorder (MDD) is a common and severe mental disorder. To identify a reliable biomarker for MDD is important for early diagnosis and prevention. Given easy access and high reproducibility, the structural magnetic resonance imaging (sMRI) is an ideal method to identify the biomarker for depression. In this study, sMRI data of first episode, treatment-naïve 66 MDD patients and 54 sex-, age-, and education-matched healthy controls (HC) were used to identify the differences in gray matter volume (GMV), group-level, individual-level covariance connections. Finally, the abnormal GMV and individual covariance connections were applied to classify MDD from HC. MDD patients showed higher GMV in middle occipital gyrus (MOG) and precuneus (PCun), and higher structural covariance connections between MOG and PCun. In addition, the Allen Human Brain Atlas (AHBA) was applied and revealed the genetic basis for the changes of gray matter volume. Importantly, we reported that GMV in MOG, PCun and structural covariance connectivity between MOG and PCun are able to discriminate MDD from HC. Our results revealed structural underpinnings for MDD, which may contribute towards early discriminating for depression.