亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Identification of Shared Gene Signatures and Pathways for Diagnosing Osteoporosis with Sarcopenia through Integrated Bioinformatics Analysis and Machine Learning

肌萎缩 骨质疏松症 Lasso(编程语言) 候选基因 接收机工作特性 基因 计算生物学 生物信息学 生物 计算机科学 机器学习 医学 遗传学 病理 内科学 万维网
作者
Xiaoli Zhou,Guangdong Chen,Yang Chen,Zepei Zhang,Jun Miao
出处
期刊:Research Square - Research Square
标识
DOI:10.21203/rs.3.rs-3940690/v1
摘要

Abstract Background Prior studies have suggested a potential relationship between osteoporosis and sarcopenia, both of which can present symptoms of compromised mobility. Additionally, fractures among the elderly are often considered a common outcome of both conditions. There is a strong correlation between fractures in the elderly population, decreased muscle mass, weakened muscle strength, heightened risk of falls, and diminished bone density. This study aimed to pinpoint crucial diagnostic candidate genes for osteoporosis patients with concomitant sarcopenia. Methods Two osteoporosis datasets and one sarcopenia dataset were obtained from the Gene Expression Omnibus (GEO). Differential expression genes (DEGs) and module genes were identified using Limma and Weighted Gene Co-expression Network Analysis (WGCNA), followed by functional enrichment analysis, construction of protein-protein interaction (PPI) networks, and application of a machine learning algorithm (least absolute shrinkage and selection operator (LASSO)regression) to determine candidate hub genes for diagnosing osteoporosis combined with sarcopenia. Receiver operating characteristic (ROC) curves and column line plots were generated. Results The merged osteoporosis dataset comprised 2067 DEGs, with 424 module genes filtered in sarcopenia. The intersection of DEGs between osteoporosis and sarcopenia module genes consisted of 60 genes, primarily enriched in viral infection. Through construction of the PPI network, 30 node genes were filtered, and after machine learning, 7 candidate hub genes were selected for column line plot construction and diagnostic value assessment. Both the column line plots and all 7 candidate hub genes exhibited high diagnostic value (area under the curve ranging from 1.00 to 0.93). Conclusion We identified 7 candidate hub genes (PDP1, ALS2CL, VLDLR, PLEKHA6, PPP1CB, MOSPD2, METTL9) and constructed column line plots for osteoporosis combined with sarcopenia. This study provides reference for potential peripheral blood diagnostic candidate genes for sarcopenia in osteoporosis patients.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
lalala应助Wei采纳,获得10
11秒前
11秒前
newplayer完成签到,获得积分10
13秒前
newplayer发布了新的文献求助10
16秒前
1分钟前
Criminology34应助科研通管家采纳,获得10
1分钟前
Criminology34应助科研通管家采纳,获得10
1分钟前
Criminology34应助科研通管家采纳,获得10
1分钟前
Criminology34应助科研通管家采纳,获得10
1分钟前
Criminology34应助科研通管家采纳,获得10
1分钟前
zzz完成签到 ,获得积分10
1分钟前
2分钟前
星空下的守望者完成签到,获得积分10
2分钟前
鹏虫虫完成签到 ,获得积分10
2分钟前
2分钟前
FashionBoy应助涨涨涨采纳,获得10
3分钟前
3分钟前
3分钟前
丿丶恒发布了新的文献求助10
3分钟前
顾良完成签到 ,获得积分10
3分钟前
英俊的铭应助丿丶恒采纳,获得30
3分钟前
Criminology34应助科研通管家采纳,获得10
3分钟前
Criminology34应助科研通管家采纳,获得10
3分钟前
Criminology34应助科研通管家采纳,获得10
3分钟前
Criminology34应助科研通管家采纳,获得10
3分钟前
3分钟前
3分钟前
3分钟前
涨涨涨发布了新的文献求助10
4分钟前
cxk完成签到 ,获得积分10
4分钟前
BUTTOND完成签到 ,获得积分10
4分钟前
淡然的新晴应助涨涨涨采纳,获得10
4分钟前
4分钟前
didididm完成签到,获得积分10
5分钟前
5分钟前
chenchen完成签到,获得积分10
5分钟前
histamin完成签到,获得积分10
5分钟前
5分钟前
Criminology34应助科研通管家采纳,获得10
5分钟前
Criminology34应助科研通管家采纳,获得10
5分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Les Mantodea de Guyane Insecta, Polyneoptera 2000
Emmy Noether's Wonderful Theorem 1200
Leading Academic-Practice Partnerships in Nursing and Healthcare: A Paradigm for Change 800
基于非线性光纤环形镜的全保偏锁模激光器研究-上海科技大学 800
Signals, Systems, and Signal Processing 610
Research Methods for Business: A Skill Building Approach, 9th Edition 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6410609
求助须知:如何正确求助?哪些是违规求助? 8229888
关于积分的说明 17463162
捐赠科研通 5463571
什么是DOI,文献DOI怎么找? 2886925
邀请新用户注册赠送积分活动 1863264
关于科研通互助平台的介绍 1702455