본문 바로가기

추천 검색어

실시간 인기 검색어

학술논문

Identification of telomere-related diagnostic markers in osteoarthritis based on bioinformatics analysis and machine learning

이용수  0

영문명
발행기관
대한생리학회-대한약리학회
저자명
Sheng Xu Jia Ye Xiaochong Cai
간행물 정보
『The Korean Journal of Physiology & Pharmacology』제29권 제3호, 359~372쪽, 전체 14쪽
주제분류
의약학 > 의학일반
파일형태
PDF
발행일자
2025.05.01
4,480

구매일시로부터 72시간 이내에 다운로드 가능합니다.
이 학술논문 정보는 (주)교보문고와 각 발행기관 사이에 저작물 이용 계약이 체결된 것으로, 교보문고를 통해 제공되고 있습니다.

1:1 문의
논문 표지

국문 초록

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues. Finally, potential drugs targeting candidate genes were predicted. Three telomere-related genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

영문 초록

목차

INTRODUCTION
METHODS
RESULTS
DISCUSSION
References

키워드

해당간행물 수록 논문

참고문헌

교보eBook 첫 방문을 환영 합니다!

신규가입 혜택 지급이 완료 되었습니다.

바로 사용 가능한 교보e캐시 1,000원 (유효기간 7일)
지금 바로 교보eBook의 다양한 콘텐츠를 이용해 보세요!

교보e캐시 1,000원
TOP
인용하기
APA

Sheng Xu,Jia Ye,Xiaochong Cai. (2025).Identification of telomere-related diagnostic markers in osteoarthritis based on bioinformatics analysis and machine learning. The Korean Journal of Physiology & Pharmacology, 29 (3), 359-372

MLA

Sheng Xu,Jia Ye,Xiaochong Cai. "Identification of telomere-related diagnostic markers in osteoarthritis based on bioinformatics analysis and machine learning." The Korean Journal of Physiology & Pharmacology, 29.3(2025): 359-372

결제완료
e캐시 원 결제 계속 하시겠습니까?
교보 e캐시 간편 결제