Objective: Considerable evidence suggests that neuroinflammation plays an important role in the pathophysiology of major depressive disorder (MDD). However, the relationship between serum C4 binding protein (C4BP) and white matter (WM) tract integrity in MDD has not been investigated. Methods: We obtained diffusion tensor images of 44 patients with MDD and 44 healthy controls and performed TRActs Constrained by UnderLying Anatomy (TRACULA) analysis to assess WM tract integrity. Serum C4-binding protein alpha chain (C4BPA) and C4- binding protein beta chain (C4BPB) levels were measured and in-between group comparisons were obtained. The correlation between serum C4BP levels and WM tract integrity was examined. Results: In comparison to healthy controls, both serum C4BPA and C4BPB were higher in MDD. Also, fractional anisotropy (FA) was increased in the left cingulum-angular bundle (CAB) in MDD, but not healthy controls (HCs). A significant correlation was found between serum C4BP and FA levels in the right cingulum-cingulate gyrus bundle (CCG) in MDD. Conclusion This study is the first to investigate the correlation between serum C4BP levels and WM tract integrity in MDD. We identified an increase in WM integrity in the left CAB region in MDD. Furthermore, serum C4BP levels were higher in MDD, and this finding correlated with increased WM integrity in the right CCG region.

Purpose: Breast cancer is known to be influenced by genetic and environmental factors, and several susceptibility genes have been discovered. Still, the majority of genetic contributors remain unknown. We aimed to analyze the plasma proteome of breast cancer patients in comparison to healthy individuals to identify differences in protein expression profiles and discover novel biomarkers. Methods: This pilot study was conducted using bioresources from Seoul National University Bundang Hospital’s Human Bioresource Center. Serum samples from 10 breast cancer patients and 10 healthy controls were obtained. Liquid chromatography-mass spectrometry analysis was performed to identify differentially expressed proteins. Results: We identified 891 proteins; 805 were expressed in the breast cancer group and 882 in the control group. Gene set enrichment and differential expression analysis identified 30 upregulated and 100 downregulated proteins in breast cancer. Among these, 10 proteins were selected as potential biomarkers. Three proteins were upregulated in breast cancer patients, including cluster of differentiation 44, eukaryotic translation initiation factor 2-α kinase 3, and fibronectin 1. Seven proteins downregulated in breast cancer patients were also selected: glyceraldehyde-3-phosphate dehydrogenase, α-enolase, heat shock protein member 8, integrin‑linked kinase, tissue inhibitor of metalloproteinases-1, vasodilatorstimulated phosphoprotein, and 14-3-3 protein gamma. All proteins had been previously reported to be related to tumor development and progression. Conclusion The findings suggest that plasma proteome profiling can reveal potential diagnostic biomarkers for breast cancer and may contribute to early detection and personalized treatment strategies. A further validation study with a larger sample cohort of breast cancer patients is planned.