Identifying OGN as a Biomarker Covering Multiple Pathogenic Pathways for Diagnosing Heart Failure: From Machine Learning to Mechanism Interpretation

孟德尔随机化 生物标志物 生物信息学 计算生物学 基因 遗传学 生物 基因型 遗传变异
作者
Yihao Zhu,Bin Chen,Yao Zu
出处
期刊:Biomolecules [Multidisciplinary Digital Publishing Institute]
卷期号:14 (2): 179-179
标识
DOI:10.3390/biom14020179
摘要

Background: The pathophysiologic heterogeneity of heart failure (HF) necessitates a more detailed identification of diagnostic biomarkers that can reflect its diverse pathogenic pathways. Methods: We conducted weighted gene and multiscale embedded gene co-expression network analysis on differentially expressed genes obtained from HF and non-HF specimens. We employed a machine learning integration framework and protein–protein interaction network to identify diagnostic biomarkers. Additionally, we integrated gene set variation analysis, gene set enrichment analysis (GSEA), and transcription factor (TF)-target analysis to unravel the biomarker-dominant pathways. Leveraging single-sample GSEA and molecular docking, we predicted immune cells and therapeutic drugs related to biomarkers. Quantitative polymerase chain reaction validated the expressions of biomarkers in the plasma of HF patients. A two-sample Mendelian randomization analysis was implemented to investigate the causal impact of biomarkers on HF. Results: We first identified COL14A1, OGN, MFAP4, and SFRP4 as candidate biomarkers with robust diagnostic performance. We revealed that regulating biomarkers in HF pathogenesis involves TFs (BNC2, MEOX2) and pathways (cell adhesion molecules, chemokine signaling pathway, cytokine–cytokine receptor interaction, oxidative phosphorylation). Moreover, we observed the elevated infiltration of effector memory CD4+ T cells in HF, which was highly related to biomarkers and could impact immune pathways. Captopril, aldosterone antagonist, cyclopenthiazide, estradiol, tolazoline, and genistein were predicted as therapeutic drugs alleviating HF via interactions with biomarkers. In vitro study confirmed the up-regulation of OGN as a plasma biomarker of HF. Mendelian randomization analysis suggested that genetic predisposition toward higher plasma OGN promoted the risk of HF. Conclusions: We propose OGN as a diagnostic biomarker for HF, which may advance our understanding of the diagnosis and pathogenesis of HF.
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
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
刚刚
崔崔发布了新的文献求助10
1秒前
ff不吃芹菜完成签到,获得积分10
2秒前
叶子完成签到,获得积分10
2秒前
唐唐完成签到,获得积分10
3秒前
123发布了新的文献求助10
3秒前
6秒前
朵朵完成签到,获得积分10
8秒前
发呆的小号完成签到 ,获得积分10
8秒前
充电宝应助原本采纳,获得10
10秒前
山260完成签到 ,获得积分10
10秒前
badada完成签到,获得积分10
10秒前
田様应助科研通管家采纳,获得10
12秒前
大模型应助科研通管家采纳,获得10
12秒前
科研通AI2S应助科研通管家采纳,获得10
12秒前
伶俐乐菱应助科研通管家采纳,获得10
13秒前
13秒前
13秒前
13秒前
shadow完成签到,获得积分10
14秒前
sen123完成签到,获得积分10
15秒前
123完成签到,获得积分20
16秒前
17秒前
NATURECATCHER完成签到,获得积分10
17秒前
温暖霸完成签到,获得积分10
17秒前
以筱完成签到,获得积分10
18秒前
NexusExplorer应助崔崔采纳,获得10
18秒前
CipherSage应助Passskd采纳,获得10
22秒前
23秒前
子睿完成签到,获得积分10
23秒前
背后雨柏完成签到 ,获得积分10
23秒前
24秒前
nanana发布了新的文献求助10
25秒前
量子星尘发布了新的文献求助10
25秒前
五月初夏完成签到,获得积分10
25秒前
hannah发布了新的文献求助10
28秒前
songvv完成签到,获得积分20
29秒前
哟哟哟完成签到,获得积分10
30秒前
30秒前
wanglejia完成签到,获得积分10
30秒前
高分求助中
【提示信息,请勿应助】关于scihub 10000
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 3000
徐淮辽南地区新元古代叠层石及生物地层 3000
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
Handbook of Industrial Diamonds.Vol2 1100
Global Eyelash Assessment scale (GEA) 1000
Picture Books with Same-sex Parented Families: Unintentional Censorship 550
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4038235
求助须知:如何正确求助?哪些是违规求助? 3575992
关于积分的说明 11374009
捐赠科研通 3305760
什么是DOI,文献DOI怎么找? 1819276
邀请新用户注册赠送积分活动 892662
科研通“疑难数据库(出版商)”最低求助积分说明 815022