Evidence map›Paper›PMID 42255490›Full record

ArticleInternational journal of genomics2026

Integrative Analysis of Genetic Risk Factors for Acute Myeloid Leukemia Using Mendelian Randomization and Single-Cell RNA Sequencing Validation.

Tian Xia, Ruiting Wen, Guocai Wu, Yunguang Hong, Dasi Luo

Abstract read
In one paragraph

Article in International journal of genomics, 2026. 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. 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

5 authors.

Tian XiaDepartment of Hematology, Zhanjiang Central People's Hospital, Zhanjiang, Guangdong, China.ORCID https://orcid.org/0009-0005-9821-2021
Ruiting WenDepartment of Hematology, Zhanjiang Central People's Hospital, Zhanjiang, Guangdong, China.ORCID https://orcid.org/0000-0001-7427-4029
Guocai WuDepartment of Hematology, Zhanjiang Central People's Hospital, Zhanjiang, Guangdong, China.ORCID https://orcid.org/0009-0005-7614-446X
Yunguang HongDepartment of Hematology, Zhanjiang Central People's Hospital, Zhanjiang, Guangdong, China.ORCID https://orcid.org/0009-0003-4911-130X
Dasi LuoDepartment of Hematology, Zhanjiang Central People's Hospital, Zhanjiang, Guangdong, China.ORCID https://orcid.org/0009-0004-3763-5365

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Acute myeloid leukemia (AML) is a heterogeneous hematologic malignancy with complex genetic underpinnings. Understanding the causal relationships between genetic factors and AML risk is crucial for developing targeted therapeutic strategies. Methods: We conducted a comprehensive Mendelian randomization (MR) analysis to evaluate causal effects of 10 genetic exposures on AML risk using multiple analytical methods including inverse-variance weighted, weighted median, simple mode, weighted mode, and MR-Egger regression. Single-cell RNA sequencing analysis was performed to validate gene expression patterns and investigate cellular heterogeneity in AML. Quality control, clustering analysis, and cell type annotation were conducted to characterize the expression profiles of identified risk genes. Results: MR analysis revealed heterogeneous causal effects across genetic exposures. Three genes demonstrated significant protective effects: Conclusions: This integrative approach provides robust evidence for causal relationships between specific genetic factors and AML risk, offering insights into disease mechanisms and potential therapeutic targets at the cellular level.

Indexed as

acute myeloid leukemiacausal inferencegenetic risk factorsMendelian randomizationsingle-cell RNA sequencing

Identifiers

PMID42255490
PMCPMC13239298

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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 Socratic graph.