Epigenome-wide Association Studies Without the Need for Cell-type Composition

Overview

Journal Nat Methods

Specialties Biomedical Engineering
Pathology

Date 2014 Jan 28

PMID 24464286

Citations 114

Authors

James Zou

Christoph Lippert

David Heckerman

Martin Aryee

Jennifer Listgarten

Affiliations

Soon will be listed here.

Abstract

In epigenome-wide association studies, cell-type composition often differs between cases and controls, yielding associations that simply tag cell type rather than reveal fundamental biology. Current solutions require actual or estimated cell-type composition--information not easily obtainable for many samples of interest. We propose a method, FaST-LMM-EWASher, that automatically corrects for cell-type composition without the need for explicit knowledge of it, and then validate our method by comparison with the state-of-the-art approach. Corresponding software is available from http://www.microsoft.com/science/.

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References

Lippert C, Quon G, Kang E, Kadie C, Listgarten J, Heckerman D . The benefits of selecting phenotype-specific variants for applications of mixed models in genomics. Sci Rep. 2013; 3:1815. PMC: 3648840. DOI: 10.1038/srep01815. View

Houseman E, Accomando W, Koestler D, Christensen B, Marsit C, Nelson H . DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics. 2012; 13:86. PMC: 3532182. DOI: 10.1186/1471-2105-13-86. View

Huang D, Sherman B, Lempicki R . Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009; 4(1):44-57. DOI: 10.1038/nprot.2008.211. View

Koestler D, Christensen B, Karagas M, Marsit C, Langevin S, Kelsey K . Blood-based profiles of DNA methylation predict the underlying distribution of cell types: a validation analysis. Epigenetics. 2013; 8(8):816-26. PMC: 3883785. DOI: 10.4161/epi.25430. View

Reinius L, Acevedo N, Joerink M, Pershagen G, Dahlen S, Greco D . Differential DNA methylation in purified human blood cells: implications for cell lineage and studies on disease susceptibility. PLoS One. 2012; 7(7):e41361. PMC: 3405143. DOI: 10.1371/journal.pone.0041361. View

Lippert C, Listgarten J, Liu Y, Kadie C, Davidson R, Heckerman D . FaST linear mixed models for genome-wide association studies. Nat Methods. 2011; 8(10):833-5. DOI: 10.1038/nmeth.1681. View

Listgarten J, Lippert C, Kadie C, Davidson R, Eskin E, Heckerman D . Improved linear mixed models for genome-wide association studies. Nat Methods. 2012; 9(6):525-6. PMC: 3597090. DOI: 10.1038/nmeth.2037. View

Huang B, Qu Z, Ong C, Tsang Y, Xiao G, Shapiro D . RUNX3 acts as a tumor suppressor in breast cancer by targeting estrogen receptor α. Oncogene. 2011; 31(4):527-34. PMC: 3697905. DOI: 10.1038/onc.2011.252. View

Devlin B, Roeder K . Genomic control for association studies. Biometrics. 2001; 55(4):997-1004. DOI: 10.1111/j.0006-341x.1999.00997.x. View

10.

Devlin B, Roeder K, Wasserman L . Genomic control, a new approach to genetic-based association studies. Theor Popul Biol. 2002; 60(3):155-66. DOI: 10.1006/tpbi.2001.1542. View

11.

. Comprehensive molecular portraits of human breast tumours. Nature. 2012; 490(7418):61-70. PMC: 3465532. DOI: 10.1038/nature11412. View

12.

Yang J, Weedon M, Purcell S, Lettre G, Estrada K, Willer C . Genomic inflation factors under polygenic inheritance. Eur J Hum Genet. 2011; 19(7):807-12. PMC: 3137506. DOI: 10.1038/ejhg.2011.39. View

13.

Price A, Zaitlen N, Reich D, Patterson N . New approaches to population stratification in genome-wide association studies. Nat Rev Genet. 2010; 11(7):459-63. PMC: 2975875. DOI: 10.1038/nrg2813. View

14.

Heichman K, Warren J . DNA methylation biomarkers and their utility for solid cancer diagnostics. Clin Chem Lab Med. 2012; 50(10):1707-21. DOI: 10.1515/cclm-2011-0935. View

15.

Rakyan V, Down T, Balding D, Beck S . Epigenome-wide association studies for common human diseases. Nat Rev Genet. 2011; 12(8):529-41. PMC: 3508712. DOI: 10.1038/nrg3000. View

16.

Hanavadi S, Martin T, Watkins G, Mansel R, Jiang W . Expression of interleukin 11 and its receptor and their prognostic value in human breast cancer. Ann Surg Oncol. 2006; 13(6):802-8. DOI: 10.1245/ASO.2006.05.028. View

17.

Balding D . A tutorial on statistical methods for population association studies. Nat Rev Genet. 2006; 7(10):781-91. DOI: 10.1038/nrg1916. View

18.

Bortsov A, Millikan R, Belfer I, Boortz-Marx R, Arora H, McLean S . μ-Opioid receptor gene A118G polymorphism predicts survival in patients with breast cancer. Anesthesiology. 2012; 116(4):896-902. PMC: 3310356. DOI: 10.1097/ALN.0b013e31824b96a1. View

19.

Huang D, Sherman B, Lempicki R . Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 2008; 37(1):1-13. PMC: 2615629. DOI: 10.1093/nar/gkn923. View

20.

Liu Y, Aryee M, Padyukov L, Daniele Fallin M, Hesselberg E, Runarsson A . Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis. Nat Biotechnol. 2013; 31(2):142-7. PMC: 3598632. DOI: 10.1038/nbt.2487. View