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Umbilical cord blood artificial mixtures validation dataset: An Enhanced DNA Methylation Library for Deconvoluting Peripheral Blood

ABSTRACT: DNA methylation microarrays have been extensively used for understanding cell type composition in complex tissue samples. Here we expand on existing libraries for reference-based deconvolution of blood DNA methylation data assayed using the Illumina HumanMethylationEPIC array to include 12 different leukocyte subtypes (neutrophils, eosinophils, basophils, monocytes, B cells naïve and memory, CD4+ and CD8+ naïve and memory cells, natural killers, and T regulatory cells). Application of the IDOL algorithm for identifying optimal libraries for the deconvolution of blood-derived DNA methylation data led to to a library consisting of 1200 CpGs. The accuracy of deconvolution estimates obtained using our IDOL-optimized library was evaluated using artificial mixtures with known cellular composition and in samples were both whole-blood DNA methylation data and FACS information were available. We further showcase potential applications of our expanded library using publicly available cancer, aging, and autoimmune disease data sets.

ORGANISM(S): Homo sapiens

PROVIDER: GSE180970 | GEO | 2022/02/07

REPOSITORIES: GEO

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Project description:DNA methylation assessments of peripheral blood DNA can be used to accurately estimate the relative proportions of underlying leukocyte subtypes. Such cell deconvolution analysis relies on libraries of discriminating differentially methylated regions that are developed for each specific cell type measured. The relationship between estimated cell type proportions can then be tested for their association with phenotypes, disease states, and subject outcomes, or used in multivariable models as terms for adjustment in epigenome-wide association studies (EWAS). We obtained purified neutrophils, monocytes, B-lymphocytes, natural killer (NK) cells, CD4+ T-cells, and CD8+ T-cells from healthy subjects and measured DNA methylation with the Illumina HumanMethylationEPIC array platform. In addition, we measured DNA methylation with the EPIC array in two sets of artificial DNA mixtures comprising the above cell types. We compared three separate approaches to select reference differentially methylated region libraries (DMR library), for cell type proportion inference. The IDOL algorithm identified an optimal DMR library consisting of 450 CpG sites for inferring leukocyte subtype proportions (average R2=99.2). Importantly, the majority of CpG sites (69%) in the IDOL DMR library were unique to the new EPIC methylation array, in that they were not present on the 450K array. Our new reference DMR library is available as a Bioconductor package, has the potential to reduce any unintended technical differences arising from the combination of different generations of array platforms, and may be helpful in generating larger DMR libraries that include novel cell subtypes. A longitudinal dataset of 12 measurements in a single healthy subject (age 33 at the beginning of the blood collection) was used to apply our new DMR library. The subject was followed up for approximately 400 days with samples collected every 40 days. One of the samples was excluded from the final analysis due to a potential mix-up.

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Umbilical cord blood artificial mixtures validation dataset: An Enhanced DNA Methylation Library for Deconvoluting Peripheral Blood

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