Literature DB >> 29693419

A novel cell-type deconvolution algorithm reveals substantial contamination by immune cells in saliva, buccal and cervix.

Shijie C Zheng1,2, Amy P Webster3, Danyue Dong1,2, Andy Feber4, David G Graham4, Roisin Sullivan4, Sarah Jevons4, Laurence B Lovat4, Stephan Beck3, Martin Widschwendter5, Andrew E Teschendorff1,5.   

Abstract

AIM: An outstanding challenge in epigenome studies is the estimation of cell-type proportions in complex epithelial tissues. MATERIALS &
METHODS: Here, we construct and validate a DNA methylation reference and algorithm for complex tissues that contain epithelial, immune and nonimmune stromal cells.
RESULTS: Using this reference, we show that easily accessible tissues such as saliva, buccal and cervix exhibit substantial variation in immune cell (IC) contamination. We further validate our reference in the context of oral cancer, where it correctly predicts an increased IC infiltration in cancer but suppressed in patients with highest smoking exposure. Finally, our method can improve the specificity of differentially methylated CpG calls in epithelial cancer.
CONCLUSION: The degree and variation of IC contamination in complex epithelial tissues is substantial. We provide a valuable resource and tool for assessing the epithelial purity and IC contamination of samples and for identifying differential methylation in such complex tissues.

Entities:  

Keywords:  DNA methylation; EWAS; buccal; cell-type heterogeneity; cervix; immune cell; saliva; surrogate tissue

Mesh:

Year:  2018        PMID: 29693419     DOI: 10.2217/epi-2018-0037

Source DB:  PubMed          Journal:  Epigenomics        ISSN: 1750-192X            Impact factor:   4.778


  47 in total

1.  Don't brush off buccal data heterogeneity.

Authors:  Andrei L Turinsky; Darci T Butcher; Sanaa Choufani; Rosanna Weksberg; Michael Brudno
Journal:  Epigenetics       Date:  2019-03-01       Impact factor: 4.528

2.  Robust partial reference-free cell composition estimation from tissue expression.

Authors:  Ziyi Li; Zhenxing Guo; Ying Cheng; Peng Jin; Hao Wu
Journal:  Bioinformatics       Date:  2020-06-01       Impact factor: 6.937

3.  Low variability in the underlying cellular landscape adversely affects the performance of interaction-based approaches for conducting cell-specific analyses of DNA methylation in bulk samples.

Authors:  Richard Meier; Emily Nissen; Devin C Koestler
Journal:  Stat Appl Genet Mol Biol       Date:  2021-08-10

4.  scDeconv: an R package to deconvolve bulk DNA methylation data with scRNA-seq data and paired bulk RNA-DNA methylation data.

Authors:  Yu Liu
Journal:  Brief Bioinform       Date:  2022-05-13       Impact factor: 13.994

5.  Adapting Blood DNA Methylation Aging Clocks for Use in Saliva Samples With Cell-type Deconvolution.

Authors:  Fedor Galkin; Kirill Kochetov; Polina Mamoshina; Alex Zhavoronkov
Journal:  Front Aging       Date:  2021-07-29

6.  A transdisciplinary approach to understand the epigenetic basis of race/ethnicity health disparities.

Authors:  Lucas A Salas; Lauren C Peres; Zaneta M Thayer; Rick Wa Smith; Yichen Guo; Wonil Chung; Jiahui Si; Liming Liang
Journal:  Epigenomics       Date:  2021-03-10       Impact factor: 4.778

7.  Saliva cell type DNA methylation reference panel for epidemiological studies in children.

Authors:  Lauren Y M Middleton; John Dou; Jonah Fisher; Jonathan A Heiss; Vy K Nguyen; Allan C Just; Jessica Faul; Erin B Ware; Colter Mitchell; Justin A Colacino; Kelly M Bakulski
Journal:  Epigenetics       Date:  2021-02-22       Impact factor: 4.528

8.  A comparison of epithelial cell content of oral samples estimated using cytology and DNA methylation.

Authors:  Yen Ting Wong; Michael A Tayeb; Timothy C Stone; Laurence B Lovat; Andrew E Teschendorff; Rafal Iwasiow; Jeffrey M Craig
Journal:  Epigenetics       Date:  2021-07-13       Impact factor: 4.861

9.  Reference-free deconvolution, visualization and interpretation of complex DNA methylation data using DecompPipeline, MeDeCom and FactorViz.

Authors:  Michael Scherer; Petr V Nazarov; Reka Toth; Shashwat Sahay; Tony Kaoma; Valentin Maurer; Nikita Vedeneev; Christoph Plass; Thomas Lengauer; Jörn Walter; Pavlo Lutsik
Journal:  Nat Protoc       Date:  2020-09-25       Impact factor: 13.491

10.  Prediagnostic breast milk DNA methylation alterations in women who develop breast cancer.

Authors:  Lucas A Salas; Sara N Lundgren; Eva P Browne; Elizabeth C Punska; Douglas L Anderton; Margaret R Karagas; Kathleen F Arcaro; Brock C Christensen
Journal:  Hum Mol Genet       Date:  2020-03-13       Impact factor: 6.150

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