Evidence map›Paper›PMID 39697733›Full record

ArticleTranslational cancer research2024

Exploring potential causal genetic variants and genes for endometrial cancer: Open Targets Genetics, Mendelian randomization, and multi-tissue transcriptome-wide association analysis.

Guorui Zhang, Su Mao, Guangwei Yuan, Yang Wang, Jingyun Yang, Yuxin Dai

Abstract read
In one paragraph

Article in Translational cancer research, 2024. 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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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Guorui ZhangDepartment of Obstetrics and Gynecology, State Key Laboratory of Complex, Severe and Rare Diseases, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Su MaoDepartment of Obstetrics and Gynecology, State Key Laboratory of Complex, Severe and Rare Diseases, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Guangwei YuanDepartment of Biostatistics & Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA.
Yang WangDivision of Biomedical Science, Analytics and Technology, Sanofi, Toronto, ON, Canada.
Jingyun YangRush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA.
Yuxin DaiDepartment of Obstetrics and Gynecology, State Key Laboratory of Complex, Severe and Rare Diseases, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Endometrial cancer (EC) is the most common gynecological malignancy in developed countries, with incidence rates continuing to rise globally. However, the precise mechanisms underlying EC pathogenesis remain largely unexplored. This study aims to prioritize genes associated with EC by leveraging multi-omics data through various bioinformatic methods. Methods: We utilized the Open Targets Genetics (OTG) database to pinpoint potential causal variants and target genes for EC. To explore the pleiotropic effects of gene expression on EC, we applied the Summary-based Mendelian Randomization (SMR) using summary data from a genome-wide association study (GWAS) on EC and expression quantitative trait loci (eQTL) data from the Consortium for the Architecture of Gene Expression (CAGE). We also conducted a cross-tissue transcriptome-wide association study (TWAS) employing sparse canonical correlation analysis (sCCA). Results from the sCCA TWAS and single-tissue TWAS for 22 tissues were combined using the aggregated Cauchy association test (sCCA + ACAT) to identify genes with cis-regulated expression levels linked to EC. Results: The OTG database recognized 15 genomic loci showing independent association with EC. Gene prioritization highlighted nine genes with relatively high locus-to-gene (L2G) scores (≥0.5), the majority of which aligned with those identified using the closest gene. Colocalization analysis identified 11 additional genes at these loci. Our SMR analysis revealed two genes, Conclusions: We confirmed the involvement of

Indexed as

Endometrial cancer (EC)expression quantitative trait loci (eQTL)genome-wide association study (GWAS)summary Mendelian randomizationtranscriptome-wide association study (TWAS)

Identifiers

PMID39697733
PMCPMC11651742

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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.