Accounting for cellular heterogeneity is critical in epigenome-wide association studies
Open accessAbstract
Background: Epigenome-wide association studies of human disease and other quantitative traits are becoming increasingly common. A series of papers reporting age-related changes in DNA methylation profiles in peripheral blood have already been published. However, blood is a heterogeneous collection of different cell types, each with a very different DNA methylation profile. Results: Using a statistical method that permits estimating the relative proportion of cell types from DNA methylation profiles, we examine data from five previously published studies, and find strong evidence of cell composition change across age in blood. We also demonstrate that, in these studies, cellular composition explains much of the observed variability in DNA methylation. Furthermore, we find high levels of confounding between age-related variability and cellular composition at the CpG level. Conclusions: Our findings underscore the importance of considering cell composition variability in epigenetic studies based on whole blood and other heterogeneous tissue sources. We also provide software for estimating and exploring this composition confounding for the Illumina 450k microarray.
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Bulk tissue analyses cannot easily distinguish molecular signatures contributed by distinct cell populations.
“Although computational approaches for tissue deconvolution are improving (48), bulk tissue analyses cannot easily distinguish molecular signatures contributed by distinct cell populations.”
From Dynamic DNA methylation: In the right place at the right time (2018) · cites this paper as [48]
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Self-citation
- Authors
- Jaffe, A. E., & Irizarry, R. A.
- Affiliations
- Johns Hopkins University (US)
- Harvard University (US)
- Corresponding author
- Jaffe, Andrew E
- Irizarry, Rafael A
- Venue
- Genome Biology
- Published
- 2014-02-04
- Volume
- 15
- Issue
- 2
- Pages
- R31-R31
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- PMC
- PMC4053810
- OpenAlex
- W2130523009
- Cited by
- 1,067
- References
- 30
- Citations by year
- 2026: 56 · 2025: 62 · 2024: 62 · 2023: 92 · 2022: 104 · 2021: 94 · 2020: 71 · 2019: 107 · 2018: 85 · 2017: 118 · 2016: 88 · 2015: 90 · 2014: 35
- FWCI
- 45.21
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Genome biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- Funders
- National Institutes of Health
- National Human Genome Research Institute (1X01HG006605-01)
- National Institute of General Medical Sciences (R01GM083084)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Keywords
- cellular heterogeneity, DNA methylation, epigenome-wide association study, age-related methylation changes, blood cell types, confounding, CpG sites, whole blood
- MeSH terms
- Aging, DNA, Humans, CpG Islands, DNA Methylation, Polymorphism, Single Nucleotide, Epigenesis, Genetic, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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