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神经疾病研究中孟德尔随机化的趋势:一项文献计量分析。

Trends in Mendelian randomization in neurological disease research: a bibliometric analysis.

作者信息

Yin Shengnan, Zakeer Kudelati, Ma Zekun, Zhao Miaomiao, Maimaiti Aierpati, Wang Zengliang

机构信息

Department of Neurosurgery, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.

College of Health Management, Xinjiang Medical University, Urumqi, China.

出版信息

Front Neurol. 2025 Jul 17;16:1525481. doi: 10.3389/fneur.2025.1525481. eCollection 2025.

Abstract

Bibliometric analysis (BA) was used in this study to examine the current state and trends of Mendelian randomization (MR) in neurological disease research. The Web of Science database was searched between 1 January 2014 and 1 September 2024 to retrieve relevant literature. The volume of publications, research themes, collaborative networks, and geographical distribution were studied quantitatively. A keyword co-occurrence analysis identified prominent research hotspots, including stroke, cardiovascular disease, and genome-wide association studies. Furthermore, highly cited literature underscored the potential of MR to elucidate causal relationships between genetic variants and health outcomes. International collaborative networks indicate that China, the United Kingdom, and the United States are the most engaged in collaborative efforts within this domain. The findings suggest that MR methods hold significant potential for applications in the investigation of neurological disorders, highlighting the necessity of international collaboration to foster scientific advancement. Future research should prioritize enhancing interdisciplinary collaboration and conducting comprehensive explorations of disease mechanisms to aid in prevention and treatment.

摘要

本研究采用文献计量分析(BA)来审视孟德尔随机化(MR)在神经疾病研究中的现状和趋势。在2014年1月1日至2024年9月1日期间检索了Web of Science数据库,以获取相关文献。对出版物数量、研究主题、合作网络和地理分布进行了定量研究。关键词共现分析确定了突出的研究热点,包括中风、心血管疾病和全基因组关联研究。此外,高被引文献强调了MR在阐明基因变异与健康结果之间因果关系方面的潜力。国际合作网络表明,中国、英国和美国在该领域的合作最为积极。研究结果表明,MR方法在神经疾病调查中具有巨大的应用潜力,凸显了国际合作促进科学进步的必要性。未来的研究应优先加强跨学科合作,并对疾病机制进行全面探索,以助力预防和治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3df6/12312639/fee4cf127a7b/fneur-16-1525481-g001.jpg

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