Evidence map›Paper›PMID 40746642›Full record

SynthesisFrontiers in neurology2025

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

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

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Shengnan Yin *Department of Neurosurgery, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Kudelati Zakeer *College of Health Management, Xinjiang Medical University, Urumqi, China.
Zekun MaDepartment of Neurosurgery, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Miaomiao ZhaoCollege of Health Management, Xinjiang Medical University, Urumqi, China.
Aierpati MaimaitiDepartment of Neurosurgery, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Zengliang WangDepartment of Neurosurgery, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

bibliometric analysisMendelian randomizationneurological diseaseresearch trendsreview

Identifiers

PMID40746642
PMCPMC12312639

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.