Evidence map›Paper›PMID 40832405›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Multi-Ancestry Transcriptome-wide Association Studies Uncover New Insights into Breast Cancer Genetics and Biology.

Jie Ping, Guochong Jia, Qiuyin Cai, Xingyi Guo, Jifeng Wang, Ran Tao, Bingshan Li, Joshua A Bauer, Yuhan Xie, Stefan Ambs and 58 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

68 authors.

Guochong Jia
Qiuyin Cai
Xingyi Guo
Jifeng Wang
Ran Tao
Bingshan Li
Joshua A Bauer
Yuhan Xie
Stefan Ambs
Mollie E Barnard
Yu Chen
Ji-Yeob Choi
Yu-Tang Gao
Montserrat Garcia-Closas
Jian Gu
Jennifer J Hu
Motoki Iwasaki
Esther M John
Sun-Seog Kweon
Christopher I Li
Koichi Matsuda
Keitaro Matsuo
Katherine L Nathanson
Barbara Nemesure
Olufunmilayo I Olopade
Tuya Pal
Sue K Park
Boyoung Park
Michael F Press
Maureen Sanderson
Dale P Sandler
Song Yao
Ying Zheng
Thomas Ahearn
Abenaa M Brewster
Adeyinka Falusi
Anselm J M Hennis
Hidemi Ito
Michiaki Kubo
Eun-Sook Lee
Timothy Makumbi
Berthe S E Mapoko
Dong-Young Noh
Katie M O'Brien
Oladosu Ojengbede
Andrew F Olshan
Min-Ho Park
Sonya Reid
Taiki Yamaji
Gary Zirpoli
Ebonee N Butler
Maosheng Huang
Siew-Kee Low
John Obafunwa
Clarice R Weinberg
Haoyu Zhang
Hongyu Zhao
Christine B Ambrosone
Michelle L Cote
Dezheng Huo
Christopher A Haiman
Daehee Kang
Julie R Palmer
Melissa A Troester
Xiao-Ou Shu
Jirong Long
Wei Zheng

Funding

Molecular Epidemiology and Prevention of Breast CancerR01CA073629 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI HU, JENNIFER J. · 2003 to 2007
$1.3M
NCI NIH HHS R01 CA073629
6 · The paper itself

Abstract

Genome-wide association studies (GWAS) have identified over 200 genetic risk loci for breast cancer, yet the target genes in these loci remain largely unknown. To address this knowledge gap, we conducted a series of multi-ancestry transcriptome-wide association studies (TWAS) to discover potential breast cancer susceptibility genes. We developed and validated ancestry-specific genetic models to predict levels of gene expression, alternative splicing, and 3' UTR alternative polyadenylation, using genomic and transcriptomic data from normal breast tissue samples of 652 females of African, Asian, or European ancestry. These models were then applied to GWAS data of 178,534 breast cancer cases and 248,300 controls from these ancestry groups for association analyses. We identified 290 genes associated with breast cancer risk, including 103 previously unreported in TWAS and 46 located at least 500Kb away from any previously identified risk variants. Among them, 39 genes exhibited distinct associations with breast cancer risk by estrogen receptor status. The identified genes were enriched in pathways related to homologous recombination, apoptosis, p53, PI3K/AKT/mTOR, estrogen, and IL-2/STAT5 signaling. Single-cell RNA sequencing and

Identifiers

PMID40832405
PMCPMC12363744

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.