Evidence map›Paper›PMID 40791276›Full record

ArticleJournal of multidisciplinary healthcare2025

Unraveling Genetic Causality Between Type 2 Diabetes Mellitus and Hemiplegia Based on Mendelian Randomization.

Ying Li, Zhengyu Zhang, Wen Jin, Yuan Yuan, Xingzu Cen, Juntao Tan, Xiaoxin Wu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of multidisciplinary healthcare, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

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No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Ying Li *Department of Medical Administration, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, People's Republic of China.
Zhengyu Zhang *Medical Records Department, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, People's Republic of China.
Wen JinMedical Records Department, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, People's Republic of China.
Yuan YuanMedical Records Department, Women and Children's Hospital of Chongqing Medical University, Chongqing, 401147, People's Republic of China.
Xingzu CenMedical Records Department, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, People's Republic of China.
Juntao TanCollege of Medical Informatics, Chongqing Medical University, Chongqing, 400016, People's Republic of China.
Xiaoxin WuState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Centre for Infectious Diseases, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310003, People's Republic of China.ORCID 0000-0001-9785-8916

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Observational studies have shown a high comorbidity rate between type 2 diabetes mellitus (T2DM) and hemiplegia, but the causal relationship between the two remains to be proven. Therefore, we performed two-sample Mendelian randomization (MR) analysis to explore the causal relationship between T2DM and hemiplegia. Methods: Genome-wide association study (GWAS) data related to hemiplegia was obtained from the FinnGen study. We also obtained GWAS data for T2DM from the IEU OpenGWAS project. Single nucleotide polymorphisms (SNPs) that were closely associated with T2DM were selected as instrumental variables (IVs) ( Results: A total of 170 independent SNPs were selected as IVs to assess the genetic causality between T2DM and hemiplegia. Our findings suggest that genetic liability to T2DM has been linked with increased risk of hemiplegia (IVW: OR = 1.168, 95% confidence interval [CI], 1.025-1.331, Conclusion: This study shows a causal relationship between T2DM and hemiplegia, indicating that T2DM increases the risk of hemiplegia, which may provide guidance for additional hemiplegia screening in T2DM patients.

Indexed as

genetic causalityhemiplegiaIEU OpenGWASMendelian randomizationtype 2 diabetes mellitus

Identifiers

PMID40791276
PMCPMC12338326

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.