A Comprehensive Dataset on Microbiome Dynamics in Rheumatoid Arthritis from a Large-Scale Cohort Study.

IF 6.9 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

Scientific Data Pub Date : 2025-02-07 DOI:10.1038/s41597-025-04422-0

Jing Li, Jun Xu, Jiayang Jin, Congmin Xu, Yuzhou Gan, Yifan Wang, Ruiling Feng, Wenqiang Fan, Yingni Li, Xiaozhen Zhao, Yucui Li, Shushi Gong, Linchong Su, Yueming Cai, Lianjie Shi, Xiaolin Sun, Yang Xiang, Qingwen Wang, Ru Li, Jinxia Zhao, Yulan Liu, Junjie Qin, Zhanguo Li, Jing He

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Abstract

Alterations in intestinal microbiota have been identified as a key risk factor in rheumatoid arthritis (RA). This study presents a multidimensional gut microbiota profile from a large cohort of RA patients, stratified by disease stage and treatment regimens, and compared to healthy controls. Our dataset comprises gut microbiota profiles from 2,238 individuals, including 1,034 RA patients (Ascia Pacific RA cohort, APRAC) and 1,204 healthy controls. This dataset is enriched with detailed clinical metadata, including patient profiles, treatment histories, and environmental factors, providing a comprehensive "disease exposome" for RA. By integrating 16S rRNA gene sequencing with demographic, clinical, and environmental data, we offer a valuable resource to explore the complex relationships between gut microbiota and RA progression. This large-scale dataset is expected to be a foundation for collaborative research, advancing our understanding of the microbiome's systemic effects in RA and other autoimmune diseases and potentially guiding new therapeutic approaches.

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来自大规模队列研究的类风湿关节炎微生物组动态综合数据集。

肠道微生物群的改变已被确定为类风湿关节炎（RA）的关键危险因素。本研究展示了一大批RA患者的多维肠道微生物群概况，按疾病分期和治疗方案分层，并与健康对照进行了比较。我们的数据集包括来自2238名个体的肠道微生物群概况，其中包括1034名RA患者（亚太RA队列，APRAC）和1204名健康对照。该数据集丰富了详细的临床元数据，包括患者资料、治疗史和环境因素，为RA提供了全面的“疾病暴露点”。通过将16S rRNA基因测序与人口统计学、临床和环境数据相结合，我们为探索肠道微生物群与RA进展之间的复杂关系提供了宝贵的资源。这个大规模的数据集有望成为合作研究的基础，促进我们对微生物组在RA和其他自身免疫性疾病中的全身作用的理解，并有可能指导新的治疗方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Scientific Data Social Sciences-Education

CiteScore

11.20

自引率

4.10%

发文量

689

审稿时长

16 weeks

期刊介绍： Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.