Evidence map›Paper›PMID 38859818›Full record

ArticleFrontiers in cardiovascular medicine2024

Causal role of immune cells in hypertension: a bidirectional Mendelian randomization study.

Xinhe Zhang, Guanying Li, Wei Wu, Bin Li

Abstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Unveiling the Immune Mechanisms of Hypertension With Single-Cell Transcriptome-Wide Mendelian Randomization.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
    Article
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

4 authors.

Xinhe ZhangDepartment of Cardiology, Central Hospital Affiliated to Shandong First Medical University, Jinan, China.
Guanying LiJinan Foreign Language School International Center, Jinan, China.
Wei WuDepartment of Cardiology, Hekou District People Hospital, Dongying, China.
Bin LiDepartment of Cardiology, Central Hospital Affiliated to Shandong First Medical University, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Although Hypertension (HTN) is considered to be a cardiovascular disease caused by multiple factors, the cause of it is still unknown. In this study, we aim to find out whether circulating immune cell characteristics have an impact on susceptibility to HTN. Methods: This study employed a comprehensive two-sample Mendelian randomization (MR) analysis to investigate the causal association between immune cell characteristics and HTN. Utilizing publicly accessible genetic data, we examined the causal relationship between HTN and the susceptibility to 731 immune cell signatures. To ensure the reliability and validity of the findings, a comprehensive sensitivity analysis was conducted to assess heterogeneity, confirm the robustness of the results and evaluate the presence of horizontal pleiotropy. Results: After FDR correction, immune phenotype had an effect on HTN. In our study, one immunophenotype was identified as being positively associated with HTN risk significance: HLA DR on CD33- HLA DR+. In addition, we examined 8 immune phenotype with no statistically significant effect of HTN, but it is worth mentioning that they had an unadjusted low Conclusions: Our MR study by genetic means demonstrated the close relationship between HTN and immune cells, thus providing guidance for future clinical prediction and subsequent treatment of HTN.

Indexed as

hypertensionimmune cellMendelian randomizationprehypertensiontwo-sample mendelian randomization

Identifiers

PMID38859818
PMCPMC11163045

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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.