Literature DB >> 25421654

Epigenome-wide association studies (EWAS): past, present, and future.

James M Flanagan1.   

Abstract

Just as genome-wide association studies (GWAS) grew from the field of genetic epidemiology, so too do epigenome-wide association studies (EWAS) derive from the burgeoning field of epigenetic epidemiology, with both aiming to understand the molecular basis for disease risk. While genetic risk of disease is currently unmodifiable, there is hope that epigenetic risk may be reversible and or modifiable. This review will take a look back at the origins of this field and revisit the past early efforts to conduct EWAS using the 27k Illumina methylation beadarrays, to the present where most investigators are using the 450k Illumina beadarrays and finally to the future where next generation sequencing based methods beckon. There have been numerous diseases, exposures and lifestyle factors investigated with EWAS, with several significant associations now identified. However, much like the GWAS studies, EWAS are likely to require large international consortium-based approaches to reach the numbers of subjects, and statistical and scientific rigor, required for robust findings.

Entities:  

Mesh:

Year:  2015        PMID: 25421654     DOI: 10.1007/978-1-4939-1804-1_3

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  41 in total

1.  Epigenome-wide association study for transgenerational disease sperm epimutation biomarkers following ancestral exposure to jet fuel hydrocarbons.

Authors:  Millissia Ben Maamar; Eric Nilsson; Jennifer L M Thorson; Daniel Beck; Michael K Skinner
Journal:  Reprod Toxicol       Date:  2020-09-06       Impact factor: 3.143

2.  Epigenomic Disruption of Cardiovascular Care: What It Will Take.

Authors:  Emma Monte; Matthew A Fischer; Thomas M Vondriska
Journal:  Circ Res       Date:  2017-05-26       Impact factor: 17.367

3.  Mining the Selective Remodeling of DNA Methylation in Promoter Regions to Identify Robust Gene-Level Associations With Phenotype.

Authors:  Yuan Quan; Fengji Liang; Si-Min Deng; Yuexing Zhu; Ying Chen; Jianghui Xiong
Journal:  Front Mol Biosci       Date:  2021-03-26

Review 4.  Deciphering DNA Methylation in HIV Infection.

Authors:  Thilona Arumugam; Upasana Ramphal; Theolan Adimulam; Romona Chinniah; Veron Ramsuran
Journal:  Front Immunol       Date:  2021-12-02       Impact factor: 7.561

5.  A Novel Framework for the Identification of Reference DNA Methylation Libraries for Reference-Based Deconvolution of Cellular Mixtures.

Authors:  Shelby Bell-Glenn; Jeffrey A Thompson; Lucas A Salas; Devin C Koestler
Journal:  Front Bioinform       Date:  2022-03-21

6.  SeSAMe: reducing artifactual detection of DNA methylation by Infinium BeadChips in genomic deletions.

Authors:  Wanding Zhou; Timothy J Triche; Peter W Laird; Hui Shen
Journal:  Nucleic Acids Res       Date:  2018-11-16       Impact factor: 16.971

Review 7.  Systems Genetics for Mechanistic Discovery in Heart Diseases.

Authors:  Christoph D Rau; Aldons J Lusis; Yibin Wang
Journal:  Circ Res       Date:  2020-06-04       Impact factor: 17.367

8.  Detecting differentially methylated regions with multiple distinct associations.

Authors:  Samantha Lent; Andres Cardenas; Sheryl L Rifas-Shiman; Patrice Perron; Luigi Bouchard; Ching-Ti Liu; Marie-France Hivert; Josée Dupuis
Journal:  Epigenomics       Date:  2021-03-01       Impact factor: 4.778

9.  Epigenome-Wide Association Study of Thyroid Function Traits Identifies Novel Associations of fT3 With KLF9 and DOT1L.

Authors:  Nicole Lafontaine; Purdey J Campbell; Juan E Castillo-Fernandez; Shelby Mullin; Ee Mun Lim; Phillip Kendrew; Michelle Lewer; Suzanne J Brown; Rae-Chi Huang; Phillip E Melton; Trevor A Mori; Lawrence J Beilin; Frank Dudbridge; Tim D Spector; Margaret J Wright; Nicholas G Martin; Allan F McRae; Vijay Panicker; Gu Zhu; John P Walsh; Jordana T Bell; Scott G Wilson
Journal:  J Clin Endocrinol Metab       Date:  2021-04-23       Impact factor: 5.958

10.  Detecting Differentially Methylated Promoters in Genes Related to Disease Phenotypes Using R.

Authors:  Jordi Martorell-Marugán; Pedro Carmona-Sáez
Journal:  Bio Protoc       Date:  2021-06-05
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