相关实验视频

Updated: Jul 6, 2025

Tissue Collection and RNA Extraction from the Human Osteoarthritic Knee Joint

Tissue Collection and RNA Extraction from the Human Osteoarthritic Knee Joint

Published on: July 22, 2021

在通过整合生物信息学分析和机器学习来诊断骨关节炎时识别与衰老相关的基因

Jian Huang^1,2, Jiangfei Zhou³, Xiang Xue³

¹Guangzhou Institute of Traumatic Surgery, Guangzhou Red Cross Hospital of Jinan University, Guangzhou 510220, China.

|January 4, 2024

概括

与衰老相关的基因在骨关节炎 (OA) 进展中发挥作用. 四个关键基因 (HMGB2,CDKN1A,JUN,DDIT3) 被确定为OA的诊断潜力,为衰老机制提供了洞察力.

科学领域:

遗传学是一个遗传学.
老年学是一门学科.
生物化学生物化学

背景情况:

骨关节炎 (OA) 是全球疼痛和残疾的主要原因.
衰老是OA发病和进展的一个重要因素,但潜在的机制尚不清楚.
这项研究调查了与衰老相关的基因在OA进展中的作用.

研究的目的:

为了确定与骨关节炎有关的与衰老相关的基因.
探索这些基因在OA中的诊断和治疗潜力.

主要方法:

在人类OA数据集和与衰老相关的基因上利用生物信息学分析.
应用基因本体学 (GO),KEGG通路丰富和蛋白质-蛋白质相互作用 (PPI) 网络分析.
采用WGCNA,LASSO和随机森林算法来识别中心基因.

主要成果:

他们确定了四个重叠的枢纽基因:HMGB2,CDKN1A,JUN和DDIT3.
这些基因在将OA与正常对照区分开来时具有诊断价值.
这四种基因的mRNA表达水平在OA组中低于正常组.

结论:

已识别的与衰老相关的基因 (HMGB2,CDKN1A,JUN,DDIT3) 可能会阐明OA衰老机制.
这些基因代表了骨关节炎的潜在诊断和治疗点.

关键词:

与衰老相关的基因生物信息学分析分析机器学习算法的算法骨关节炎是一种关节炎.

更多相关视频

Standardized Histomorphometric Evaluation of Osteoarthritis in a Surgical Mouse Model

Standardized Histomorphometric Evaluation of Osteoarthritis in a Surgical Mouse Model

Published on: May 6, 2020

Application of Atomic Force Microscopy to Detect Early Osteoarthritis

Application of Atomic Force Microscopy to Detect Early Osteoarthritis

Published on: May 24, 2020

相关概念视频

Genome-wide Association Studies-GWAS

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...