Evidence map›Paper›PMID 38886730›Full record

ArticleBMC cancer2024

Integrated mendelian randomization analyses highlight AFF3 as a novel eQTL-mediated susceptibility gene in renal cancer and its potential mechanisms.

Qiming Wang, Shaopeng Chen, Gang Wang, Tielong Zhang, Yulong Gao

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In one paragraph

Article in BMC cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

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2citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Qiming WangDepartment of Urology, Jianhu Clinical Medical College of Yangzhou University, No. 666 South Ring Road, Yancheng, Jiangsu Province, 224700, China.
Shaopeng ChenDepartment of Urology, Jianhu Clinical Medical College of Yangzhou University, No. 666 South Ring Road, Yancheng, Jiangsu Province, 224700, China.
Gang WangDepartment of Urology, Jianhu Clinical Medical College of Yangzhou University, No. 666 South Ring Road, Yancheng, Jiangsu Province, 224700, China.
Tielong ZhangDepartment of Urology, Jianhu Clinical Medical College of Yangzhou University, No. 666 South Ring Road, Yancheng, Jiangsu Province, 224700, China.
Yulong GaoDepartment of Urology, Jianhu Clinical Medical College of Yangzhou University, No. 666 South Ring Road, Yancheng, Jiangsu Province, 224700, China. gaoyulong202204@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundsA growing number of expression quantitative trait loci (eQTLs) have been found to be linked with tumorigenesis. In this article, we employed integrated Mendelian randomization (MR) analyses to identify novel susceptibility genes in renal cancer (RC) and reveal their potential mechanisms.

methodsTwo-sample MR analyses were performed to infer causal relationships between eQTLs, metabolites, and RC risks through the "TwoSampleMR" R package. Sensitivity analyses, such as heterogeneity, pleiotropy, and leave-one-out analysis, were used to assess the stability of our outcomes. Summary-data-based MR (SMR) analyses were used to verify the causal relationships among cis-eQTLs and RC risks via the SMR 1.3.1 software.

resultsOur results provided the first evidence for AFF3 eQTL elevating RC risks, suggesting its oncogenic roles (IVW method; odds ratio (OR) = 1.0005; 95% confidence interval (CI) = 1.0001-1.0010; P = 0.0285; heterogeneity = 0.9588; pleiotropy = 0.8397). Further SMR analysis validated the causal relationships among AFF3 cis-eQTLs and RC risks (P < 0.05). Moreover, the TCGA-KIRC, the ICGC-RC, and the GSE159115 datasets verified that the AFF3 gene was more highly expressed in RC tumors than normal control via scRNA-sequencing and bulk RNA-sequencing (P < 0.05). Gene set enrichment analysis (GSEA) analysis identified six potential biological pathways of AFF3 involved in RC. As for the potential mechanism of AFF3 in RC, we concluded in this article that AFF3 eQTL could negatively modulate the levels of the X-11,315 metabolite (IVW method; OR = 0.9127; 95% CI = 0.8530-0.9765; P = 0.0081; heterogeneity = 0.4150; pleiotropy = 0.8852), exhibiting preventive effects against RC risks (IVW method; OR = 0.9987; 95% CI = 0.9975-0.9999; P = 0.0380; heterogeneity = 0.5362; pleiotropy = 0.9808).

conclusionsWe concluded that AFF3 could serve as a novel eQTL-mediated susceptibility gene in RC and reveal its potential mechanism of elevating RC risks via negatively regulating the X-11,315 metabolite levels.

Indexed as

Genetic Predisposition to DiseaseKidney NeoplasmsMendelian Randomization AnalysisQuantitative Trait LociGenome-Wide Association StudyHumansNuclear ProteinsPolymorphism, Single NucleotideAFF3 protein, humanNuclear ProteinsAFF3eQTLMendelian randomizationRenal cancerSMR

Identifiers

PMID38886730
PMCPMC11181572

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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.