Evidence map›Paper›PMID 32164769›Full record

ArticleClinical epigenetics2020

Estimating breast tissue-specific DNA methylation age using next-generation sequencing data.

James R Castle, Nan Lin, Jinpeng Liu, Anna Maria V Storniolo, Aditi Shendre, Lifang Hou, Steve Horvath, Yunlong Liu, Chi Wang, Chunyan He

Abstract read
In one paragraph

Article in Clinical epigenetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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  11. Current status and challenges of breast cancer prevention~DNA methylation would lead to groundbreaking progress in breast cancer prevention~.Genes and environment : the official journal of the Japanese Environmental Mutagen Society · 2023
    Review
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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

10 authors.

James R CastleUniversity of Kentucky Markey Cancer Center, 800 Rose Street, Lexington, KY, 40536, USA.
Nan LinUniversity of Kentucky Markey Cancer Center, 800 Rose Street, Lexington, KY, 40536, USA.
Jinpeng LiuUniversity of Kentucky Markey Cancer Center, 800 Rose Street, Lexington, KY, 40536, USA.
Anna Maria V StornioloSusan G. Komen Tissue Bank at Indiana University Simon Cancer Center, Indianapolis, IN, USA.
Aditi ShendreDepartment of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.
Lifang HouCenter for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Steve HorvathDepartment of Biostatistics, UCLA School of Public Health, Los Angeles, CA, USA.
Yunlong LiuDepartment of Molecular and Medical Genetics, Indiana University School of Medicine, Indianapolis, IN, USA.
Chi WangUniversity of Kentucky Markey Cancer Center, 800 Rose Street, Lexington, KY, 40536, USA.
Chunyan HeUniversity of Kentucky Markey Cancer Center, 800 Rose Street, Lexington, KY, 40536, USA. chunyan.he@uky.edu.

Funding

University of Kentucky Markey Cancer Center Support Grant ECIA SupplementP30CA177558 · NCI · UNIVERSITY OF KENTUCKY · PI KATHLEEN L. O'CONNOR · 2013 to 2026
$38.3M
An Integrative Approach to Identify Causal Epigenetic Markers for Breast CancerR01CA194030 · NCI · UNIVERSITY OF KENTUCKY · PI HE, CHUNYAN · 2015 to 2018
$1.5M
NCI NIH HHS P30 CA177558NCI NIH HHS R01 CA194030
6 · The paper itself

Abstract

backgroundDNA methylation (DNAm) age has been widely accepted as an epigenetic biomarker for biological aging. Emerging evidence suggests that DNAm age can be tissue-specific and female breast tissue ages faster than other parts of the body. The Horvath clock, which estimates DNAm age across multiple tissues, has been shown to be poorly calibrated in breast issue. We aim to develop a model to estimate breast tissue-specific DNAm age.

methodsGenome-wide DNA methylation sequencing data were generated for 459 normal, 107 tumor, and 45 paired adjacent-normal breast tissue samples. We determined a novel set of 286 breast tissue-specific clock CpGs using penalized linear regression and developed a model to estimate breast tissue-specific DNAm age. The model was applied to estimate breast tissue-specific DNAm age in different breast tissue types and in tumors with distinct clinical characteristics to investigate cancer-related aging effects.

resultsOur estimated breast tissue-specific DNAm age was highly correlated with chronological age (r = 0.88; p = 2.9 × 10

conclusionsThe intended applications for this model are wide-spread and have been shown to provide biologically meaningful results for cancer-related aging effects in breast tumor tissue. Future studies are warranted to explore whether breast tissue-specific epigenetic age acceleration is predictive of breast cancer development, treatment response, and survival as well as the clinical utility of whether this model can be extended to blood samples.

Indexed as

DNA MethylationAdultAgingBreastBreast NeoplasmsCpG IslandsEpigenesis, GeneticFemaleHigh-Throughput Nucleotide SequencingHumansLinear ModelsMiddle AgedModels, GeneticOrgan SpecificitySequence Analysis, DNAAgingBreastDNA methylationEpigenetic ageNext-generation sequencing

Identifiers

PMID32164769
PMCPMC7282053

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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.