Evidence map›Paper›PMID 41824785›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Mapping Genetic Regulation of Transcription to Identify Functional Variants and Genes Associated with Pancreatic Cancer Risk.

Xiaoyang Wang, Hui Geng, Zhengyan Yao, Yuan Jiang, Can Chen, Zequn Lu, Shuangshuang Tian, Ming Zhang, Ruiyan Liu, Chenxi Feng and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. 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

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

15 authors.

Xiaoyang WangDepartment of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China.
Hui GengDepartment of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China.
Zhengyan YaoDepartment of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China.
Yuan JiangDepartment of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China.
Can ChenDepartment of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China.
Zequn LuDepartment of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China.
Shuangshuang TianDepartment of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China.
Ming ZhangDepartment of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China.
Ruiyan LiuDepartment of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China.
Chenxi FengDepartment of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China.
Bin LiDepartment of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China.
Xiaoping MiaoDepartment of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China.
Jianbo TianDepartment of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China.
Shaokai ZhangDepartment of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China.
Ying ZhuDepartment of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China.ORCID https://orcid.org/0000-0002-3813-7577

Funding

Henan Provincial Medical Science and Technology Research Program-Provincial-Ministerial Co-constructed Youth Project SBGJ202303015Henan Provincial Science and Technology Research Program 242102310040National Key R&D Program of China 2024YFC3405804National Natural Science Foundation of China 82204128National Natural Science Foundation of China 82273713National Natural Science Foundation of China 82322058National Natural Science Foundation of China 82373663Natural Science Foundation of Hubei Province of China 2024AFB777Noncommunicable Chronic Diseases-National Science and Technology Major Project 2023ZD0501400Program of Health Commission of Hubei Province WJ2023M045
6 · The paper itself

Abstract

Pancreatic cancer is one of the most lethal malignancies. Genome-wide association studies (GWAS) identify multiple susceptibility loci, but most map to noncoding regions, leaving variant-to-gene links unresolved. In this study, a genome-wide regulatory map is constructed using expression quantitative trait loci (eQTL) analysis of 482 pancreatic tissues, and integrated with a GWAS meta-analysis to prioritize causal variants. A total of 82 significant variants and 15 target genes for pancreatic cancer risk are identified, with enrichment in cancer-related pathways. The variant rs11102484 is validated in an independent cohort of 569 cases and 2691 controls. The combined analysis of 5699 cases and 8467 controls confirms that the G allele of rs11102484 significantly reduces pancreatic cancer risk (odds ratio = 0.85, 95% confidence interval = 0.80-0.90, P = 4.83 × 10

Indexed as

Gene Expression Regulation, NeoplasticGenetic Predisposition to DiseasePancreatic NeoplasmsQuantitative Trait LociGenome-Wide Association StudyHumansPolymorphism, Single Nucleotideexpression quantitative trait locigenome‐wide association studiespancreatic cancersilencersST7L

Identifiers

PMID41824785
PMCPMC13205582

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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.