多发性硬化症的预测、预防和个性化医学:铁死亡与循环蛋白质
多发性硬化症铁死亡与循环蛋白的孟德尔随机化研究数据集,包含GWAS和蛋白质汇总统计,用于因果推断。

基本信息
资源简介
多发性硬化症的预测、预防和个性化医学:铁死亡与循环蛋白质
【一句话概览】
本数据集是 figshare 公开的结构化表格数据集,收录 1 个文件、合计 139.17 KB,主题涵盖 Circulating proteins、ferroptosis、FTMT、Mendelian randomization、multiple sclerosis,可用于统计建模、特征工程与队列分析,CC BY 4.0 许可开放获取。
【数据集背景】
本数据集源站标题为《The predictive, preventive, and personalized medicine of multiple sclerosis: ferroptosis and circulating proteins》。配套论文《The predictive, preventive, and personalized medicine of multiple sclerosis: ferroptosis and circulating proteins》发表于 Neurological Research(2025),DOI:10.1080/01616412.2025.2541908。项目资助方:The author(s) reported there is no funding associated with the work featured in this article.。源站首次发布:2025-08-15。
【数据内容】
源站原始描述:Based on the principles of Predictive, Preventive, and Personalized Medicine (PPPM), this study aimed to identify ferroptosis-related genes associated with multiple sclerosis (MS) and to explore the underlying mechanisms through genetic approaches. Summary statistics of circulating proteins were obtained from the UK Biobank Pharma Proteomics Project (UKB-PPP), ferroptosis-related genes were curated from the FerrDb database, and MS genome-wide association study (GWAS) data were sourced from the I…
【数据结构与技术规格】
文件数 1 个,合计 139.17 KB。yner_a_2541908_sm5921.xlsx:application/vnd.openxmlformats-officedocument.spreadsheetml.sheet,139.17 KB。数据集 DOI:10.6084/m9.figshare.29917021.v1。
【主题与分类】
源站学科分类:Biophysics、Biochemistry、Microbiology、Genetics、Molecular Biology、Immunology。主题标签:Circulating proteins、ferroptosis、FTMT、Mendelian randomization、multiple sclerosis。
【适用方向】
结构化表格数据可直接用于统计建模、特征工程与队列分析。
【获取与许可】
源站页面:https://tandf.figshare.com/articles/dataset/The_predictive_preventive_and_personalized_medicine_of_multiple_sclerosis_ferroptosis_and_circulating_proteins/29917021
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:The predictive, preventive, and personalized medicine of multiple sclerosis: ferroptosis and circulating proteins. Taylor & Francis. Xiong, Yao; Yang, Daifeng; Cai, Shanshan
【使用注意】
· 源站最后修改于 2026-06-01,引用时请注意版本时效。
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载,适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
无需注册即可直接获取公开样本或文档,适合快速预览和评估数据集质量。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务(收技术服务费,非数据销售)
暂未开放当前数据集主要来源为 Kaggle 公开托管,完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取(Figshare)
- 源站标题:The predictive, preventive, and personalized medicine of multiple sclerosis: ferroptosis and circulating proteins
- DOI:10.6084/m9.figshare.29917021.v1
- 发布日期:2025-08-15
- 文件数:1 个
- 文件总体积:139.17 KB
- 源站页面:https://tandf.figshare.com/articles/dataset/The_predictive_preventive_and_personalized_medicine_of_multiple_sclerosis_ferroptosis_and_circulating_proteins/29917021
命令行下载
curl -L -o "yner_a_2541908_sm5921.xlsx" "https://ndownloader.figshare.com/files/57200889"
文件清单
yner_a_2541908_sm5921.xlsx(139.17 KB)
文件总体积 139.17 KB(源站 API 实测)。
数据加载示例(图像类)
from PIL import Image
import glob, os
files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)
# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path) # 要求 子目录=类别
目录组织与标注格式以源站说明和下载后实际文件为准。
数据说明
Based on the principles of Predictive, Preventive, and Personalized Medicine (PPPM), this study aimed to identify ferroptosis-related genes associated with multiple sclerosis (MS) and to explore the underlying mechanisms through genetic approaches.
Summary statistics of circulating proteins were obtained from the UK Biobank Pharma Proteomics Project (UKB-PPP), ferroptosis-related genes were curated from the FerrDb database, and MS genome-wide association study (GWAS) data were sourced from the International Multiple Sclerosis Genetics Consortium (IMSGC). Two-sample Mendelian randomization (MR) analyses were performed to assess the causal relationships between proteins, ferroptosis-related genes, and MS risk. Mediation MR analysis was conducted to explore the potential mediating role of ferroptosis-related genes. The primary analytical method was inverse variance weighting (IVW), supplemented by MR-Egger and weighted median approaches.
After Bonferroni correction, one ferroptosis-related gene (Ferritin Mitochondrial, FTMT) and 21 circulating proteins were significantly associated with MS. Eleven protein-gene pairs were identified. Mediation analysis further revealed that FTMT mediated the effects of several proteins on MS risk, including CD8A (17.6%), CFB (9.0%), ENPP6 (9.5%), GZMA (22.9%), KIR2DL2 (17.4%), KIR2DL3 (16.9%), and TNXB (13.2%).
This study highlights the critical role of FTMT in linking circulating proteins to MS pathogenesis through ferroptosis regulation, providing novel insights into predictive, preventive, and personalized medicine strategies for MS management.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.6084/m9.figshare.29917021.v1(source: https://tandf.figshare.com/articles/dataset/The_predictive_preventive_and_personalized_medicine_of_multiple_sclerosis_ferroptosis_and_circulating_proteins/29917021)。
数据缺失?
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