Evidence map›Paper›PMID 34497089›Full record

ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2021

Integrating Genome and Methylome Data to Identify Candidate DNA Methylation Biomarkers for Pancreatic Cancer Risk.

Jingjing Zhu, Yaohua Yang, John B Kisiel, Douglas W Mahoney, Dominique S Michaud, Xingyi Guo, William R Taylor, Xiao-Ou Shu, Xiang Shu, Duo Liu and 6 more

Open access · bronzeAbstract readComment
In one paragraph

Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 pooled it
2.0field-weighted citation impact, top 11% of its field
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

16 citing papers in PubMed, 2 syntheses or guidelines pooled it, 23 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 5 institutions in 2 countries.

Jingjing Zhu *Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, Hawaii.
Yaohua Yang *Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee.ORCID 0000-0002-3815-7172
John B KisielDivision of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota.ORCID 0000-0002-3840-5324
Douglas W MahoneyDepartment of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota.
Dominique S MichaudDepartment of Public Health and Community Medicine, Tufts University Medical School, Boston, Massachusetts.
Xingyi GuoDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee.
William R TaylorDivision of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota.
Xiao-Ou ShuDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee.
Xiang ShuDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee.ORCID 0000-0002-4129-9403
Duo LiuCancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, Hawaii.
Bingshan LiDepartment of Molecular Physiology & Biophysics, Vanderbilt University, Nashville, Tennessee.
Ran TaoVanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee.
Qiuyin CaiDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee.ORCID 0000-0002-9384-5648
Wei ZhengDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee.ORCID 0000-0003-1226-070X
Jirong LongDivision of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee. lwu@cc.hawaii.edu jirong.long@vanderbilt.edu.
Lang WuCancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, Hawaii. lwu@cc.hawaii.edu jirong.long@vanderbilt.edu.
Vanderbilt University Medical Center · USMayo Clinic · USUniversity of Hawaiʻi at Mānoa · USTufts University · USVanderbilt University · US

Funding

Validation and Fine-Scale Mapping of Pancreatic Cancer Susceptibility Loci (Study)R01CA154823 · NCI · JOHNS HOPKINS UNIVERSITY · PI KLEIN, ALISON P · 2011 to 2020
$5.7M
Cohort Study of Biochemical and Genetic Risk Factors for Pancreatic CancerK07CA140790 · NCI · DANA-FARBER CANCER INST · PI WOLPIN, BRIAN MATTHEW · 2009 to 2013
$890k
Uncovering roles of polyunsaturated fatty acids in pancreatic cancer etiologyR00CA218892 · NCI · UNIVERSITY OF HAWAII AT MANOA · PI WU, LANG · 2019 to 2021
$747k
CCR NIH HHS HHSN261200800001CNCI NIH HHS HHSN261200800001ENCI NIH HHS K07 CA140790NCI NIH HHS R00 CA218892NCI NIH HHS R01 CA154823NHLBI NIH HHS HHSN268201100011I
6 · The paper itself

Abstract

backgroundThe role of methylation in pancreatic cancer risk remains unclear. We integrated genome and methylome data to identify CpG sites (CpG) with the genetically predicted methylation to be associated with pancreatic cancer risk. We also studied gene expression to understand the identified associations.

methodsUsing genetic data and white blood cell methylation data from 1,595 subjects of European descent, we built genetic models to predict DNA methylation levels. After internal and external validation, we applied prediction models with satisfactory performance to the genetic data of 8,280 pancreatic cancer cases and 6,728 controls of European ancestry to investigate the associations of predicted methylation with pancreatic cancer risk. For associated CpGs, we compared their measured levels in pancreatic tumor versus benign tissue.

resultsWe identified 45 CpGs at nine loci showing an association with pancreatic cancer risk, including 15 CpGs showing an association independent from identified risk variants. We observed significant correlations between predicted methylation of 16 of the 45 CpGs and predicted expression of eight adjacent genes, of which six genes showed associations with pancreatic cancer risk. Of the 45 CpGs, we were able to compare measured methylation of 16 in pancreatic tumor versus benign pancreatic tissue. Of them, six showed differentiated methylation.

conclusionsWe identified methylation biomarker candidates associated with pancreatic cancer using genetic instruments and added additional insights into the role of methylation in regulating gene expression in pancreatic cancer development. IMPACT: A comprehensive study using genetic instruments identifies 45 CpG sites at nine genomic loci for pancreatic cancer risk.

Indexed as

DNA MethylationPancreatic NeoplasmsBiomarkers, TumorCpG IslandsEpigenomeHumansBiomarkers, Tumor

Identifiers

PMID34497089
PMCPMC8568683
OpenAlexW3196971180

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.