부지윤 (인하대학교) | 한빛사논문 > 한빛사

한빛사논문

조회130

인하대학교

CV File 312 kb

Biosens. Bioelectron., Oct 30 2025, 293 S0956-5663(25)01057-7 | https://doi.org/10.1016/j.bios.2025.118180 Synovial exosomal type II collagen as a biomarker for osteoarthritis Progression: From molecular evaluation to AI-powered SERS-based diagnosis

Dongjun Shin ^{a 1}, Jung Hyun Choi ^{a b 1}, Myeong Jin Jeon ^{c 1}, Sunwoo Hong ^a, Hosu Lee ^a, Samuel Jaeyoon Won ^d, Dong Hyung Kim ^{b e}, Jiyoon Bu ^{a f g h *}, Dong Jin Ryu ^{d i *}, Jong Uk Lee^{j *}

^aDepartment of Biological Sciences and Bioengineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon, 22212, Republic of Korea
^bDivision of Biomedical Metrology, Korea Research Institute of Standards and Science, 267 Gajeongno, Yuseong-Gu, Daejeon, 34113, Republic of Korea
^cAbG Tech, 123 Dongil-ro 173ga-gil, Nowon-gu, Seoul, 01856, Republic of Korea
^dDepartment of Orthopedic Surgery, Inha University Hospital, 27 Inhang-ro, Jung-gu, Incheon, 22332, Republic of Korea
^eDepartment of Applied Measurement Science, University of Science and Technology (UST), 217 Gajeong-ro, Yuseong-gu, Daejeon, 34113, Republic of Korea
^fDepartment of Biological Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon, 22212, Republic of Korea
^gBiohybrid Systems Research Center, Inha University, 100 Inha-ro, Michuhol-gu, Incheon, 22212, Republic of Korea
hResearch Institute of Biomedical Engineering, Inha University Hospital, Incheon, 22332, Republic of Korea
ⁱSchool of Medicine, Inha University, Incheon, 22212, Republic of Korea
^jDepartment of Biomedical Engineering, Dongguk University, Seoul, 10326, Republic of Korea

¹These authors contributed equally

^*Corresponding authors: correspondence to Jiyoon Bu, Dong Jin Ryu or Jong Uk Lee

Abstract

Osteoarthritis (OA) is a degenerative joint disease which lacks reliable biomarkers for monitoring disease progression. Current assessment methods rely primarily on radiographic Kellgren-Lawrence (K-L) grading and symptom-based scores, which often show poor concordance with underlying molecular changes. Here, we present a label-free diagnostic strategy for classifying OA severity based on type II collagen in synovial exosomes, using surface-enhanced Raman spectroscopy (SERS). Exosomal surface type II collagen (ExoCOL2A1), quantified from synovial fluid of OA patients, exhibited a significant inverse correlation with radiographic severity and demonstrated superior diagnostic capability compared to other protein markers. To enable non-destructive detection, a plasmonic gold nanoparticle substrate was used to acquire the SERS spectra of whole synovial exosomes, which were subsequently analyzed using a deep neural network (DNN). The DNN model accurately classified OA severity based on spectral characteristics, achieving a prediction accuracy of 95.3 %, and outperforming traditional machine learning models such as LDA, SVM, and kNN. Principal component analysis further identified ExoCOL2A1-associated spectral peaks as key contributing factors for the exosomal SERS spectrum. These findings establish the clinical potential of exosomal type II collagen as OA severity-associated markers and highlight the utility of AI-integrated SERS as a non-invasive diagnostic platform.

논문정보

형식Research article
게재일2025년 10월 (BRIC 등록일 2025-11-05)
연구진국내 연구진
분야 바이오·의료융합 > 바이오센싱 및 나노바이오물질

댓글 작성 로그인

CV 열람하기

연락처 보기