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Clin Chem. 2018 Mar;64(3):566-575. doi: 10.1373/clinchem.2017.279935. Epub 2017 Nov 8.

Leukocyte Counts Based on DNA Methylation at Individual Cytosines.

Author information

1
Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, Aachen, Germany.
2
Institute for Biomedical Engineering - Cell Biology, University Hospital of RWTH Aachen, Aachen, Germany.
3
Joint Research Center for Computational Biomedicine, RWTH Aachen University, Aachen, Germany.
4
Aachen Institute for Advanced Study in Computational Engineering Science (AICES), RWTH Aachen University, Aachen, Germany.
5
Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, the Netherlands.
6
Institute of Immunology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany.
7
Department of Hematology, Oncology, Hemostaseology, and Stem Cell Transplantation, Faculty of Medicine, RWTH Aachen University, Aachen, Germany.
8
Institute for Transfusion Medicine, University Hospital Aachen, Aachen, Germany.
9
Institute for Occupational and Social Medicine, RWTH Aachen University, Aachen, Germany.
10
Varionostic GmbH, Ulm, Germany.
11
Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, Aachen, Germany; wwagner@ukaachen.de.

Abstract

BACKGROUND:

White blood cell counts are routinely measured with automated hematology analyzers, by flow cytometry, or by manual counting. Here, we introduce an alternative approach based on DNA methylation (DNAm) at individual CG dinucleotides (CpGs).

METHODS:

We identified candidate CpGs that were nonmethylated in specific leukocyte subsets. DNAm levels (ranging from 0% to 100%) were analyzed by pyrosequencing and implemented into deconvolution algorithms to determine the relative composition of leukocytes. For absolute quantification of cell numbers, samples were supplemented with a nonmethylated reference DNA.

RESULTS:

Conventional blood counts correlated with DNAm at individual CpGs for granulocytes (r = -0.91), lymphocytes (r = -0.91), monocytes (r = -0.74), natural killer (NK) cells (r = -0.30), T cells (r = -0.73), CD4+ T cells (r = -0.41), CD8+ T cells (r = -0.88), and B cells (r = -0.66). Combination of these DNAm measurements into the "Epi-Blood-Count" provided similar precision as conventional methods in various independent validation sets. The method was also applicable to blood samples that were stored at 4 °C for 7 days or at -20 °C for 3 months. Furthermore, absolute cell numbers could be determined in frozen blood samples upon addition of a reference DNA, and the results correlated with measurements of automated analyzers in fresh aliquots (r = 0.84).

CONCLUSIONS:

White blood cell counts can be reliably determined by site-specific DNAm analysis. This approach is applicable to very small blood volumes and frozen samples, and it allows for more standardized and cost-effective analysis in clinical application.

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