Targeted DNA Methylation Analysis Facilitates Leukocyte Counts in Dried Blood Samples

Author:

Hubens Wouter H G12ORCID,Maié Tiago3,Schnitker Matthis12,Bocova Ledio12,Puri Deepika12,Wessiepe Martina4,Kramer Jan56,Rink Lothar7ORCID,Koschmieder Steffen89ORCID,Costa Ivan G3ORCID,Wagner Wolfgang129ORCID

Affiliation:

1. Institute for Stem Cell Biology, Faculty of Medicine, RWTH Aachen University , Aachen , Germany

2. Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University , Aachen , Germany

3. Institute for Computational Genomics, Faculty of Medicine, RWTH Aachen University , Aachen , Germany

4. Institute for Transfusion Medicine, Faculty of Medicine, RWTH Aachen University , Aachen , Germany

5. Division of Nephrology and Transplantation Unit, Department of Internal Medicine I, University of Lübeck , Lübeck , Germany

6. LADR Laboratory Group Dr. Kramer & Colleagues , Geesthacht , Germany

7. Institute of Immunology, Faculty of Medicine, RWTH Aachen University , Aachen , Germany

8. Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, Faculty of Medicine, RWTH Aachen University , Aachen , Germany

9. Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD) , Aachen , Germany

Abstract

Abstract Background Cell-type specific DNA methylation (DNAm) can be employed to determine the numbers of leukocyte subsets in blood. In contrast to conventional methods for leukocyte counts, which are based on cellular morphology or surface marker protein expression, the cellular deconvolution based on DNAm levels is applicable for frozen or dried blood. Here, we further enhanced targeted DNAm assays for leukocyte counts in clinical application. Methods DNAm profiles of 40 different studies were compiled to identify CG dinucleotides (CpGs) with cell-type specific DNAm using a computational framework, CimpleG. DNAm levels at these CpGs were then measured with digital droplet PCR in venous blood from 160 healthy donors and 150 patients with various hematological disorders. Deconvolution was further validated with venous blood (n = 75) and capillary blood (n = 31) that was dried on Whatman paper or on Mitra microsampling devices. Results In venous blood, automated cell counting or flow cytometry correlated well with epigenetic estimates of relative leukocyte counts for granulocytes (r = 0.95), lymphocytes (r = 0.97), monocytes (r = 0.82), CD4 T cells (r = 0.84), CD8 T cells (r = 0.94), B cells (r = 0.96), and NK cells (r = 0.72). Similar correlations and precisions were achieved for dried blood samples. Spike-in with a reference plasmid enabled accurate epigenetic estimation of absolute leukocyte counts from dried blood samples, correlating with conventional venous (r = 0.86) and capillary (r = 0.80) blood measurements. Conclusions The advanced selection of cell-type specific CpGs and utilization of digital droplet PCR analysis provided accurate epigenetic blood counts. Analysis of dried blood facilitates self-sampling with a finger prick, thereby enabling easier accessibility to testing.

Publisher

Oxford University Press (OUP)

Subject

Biochemistry (medical),Clinical Biochemistry

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