Targeted DNA Methylation Analysis Facilitates Leukocyte Counts in Dried Blood Samples.

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 DNA...

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Publicado en:Clinical Chemistry Vol. 69; no. 11; pp. 1283 - 1295
Autores principales: Hubens, Wouter H. G., Maié, Tiago, Schnitker, Matthis, Bocova, Ledio, Puri, Deepika, Wessiepe, Martina, Kramer, Jan, Rink, Lothar, Koschmieder, Steffen, Costa, Ivan G., Wagner, Wolfgang
Formato: Journal Article
Publicado: Oxford University Press / USA Nov2023
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Nov2023
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      pub: Oxford University Press / USA
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        10.1093/clinchem/hvad143
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        atl: Targeted DNA Methylation Analysis Facilitates Leukocyte Counts in Dried Blood Samples.
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        au:
          Hubens, Wouter H. G.
          Maié, Tiago
          Schnitker, Matthis
          Bocova, Ledio
          Puri, Deepika
          Wessiepe, Martina
          Kramer, Jan
          Rink, Lothar
          Koschmieder, Steffen
          Costa, Ivan G.
          Wagner, Wolfgang
        affil: Institute for Stem Cell Biology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
      sug:
      ab: 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 celltype 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.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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