Quantitative reconstruction of leukocyte subsets using DNA methylation

Area of Science:

• Immunology
• Epigenetics
• Bioinformatics

Background:

• Cell lineage-specific DNA methylation patterns differentiate human leukocyte subsets.
• DNA methylation analysis enables simultaneous quantification of multiple leukocyte subsets.
• This approach allows investigation of immune modulations in various blood samples, including archived specimens.

Purpose of the Study:

• To assess the performance characteristics and validity of a DNA methylation-based approach for quantifying leukocyte subsets.
• To establish a method for simultaneous quantification of multiple immune cell types in peripheral blood.
• To enable analysis of immune modulations in previously inaccessible archived blood samples.

Main Methods:

• Utilized Illumina Infinium HumanMethylation27 and VeraCode GoldenGate Methylation Assay microarrays to measure DNA methylation.
• Identified cell lineage-specific DNA methylation signatures distinguishing T cells, B cells, NK cells, monocytes, eosinophils, basophils, and neutrophils.
• Employed a bioinformatics approach to quantify cell types in complex mixtures using DNA methylation at minimal CpG loci.

Main Results:

• Established distinct DNA methylation signatures for major human leukocyte subsets.
• Developed a bioinformatics method to accurately quantify leukocyte composition in whole blood mixtures using as few as 20 CpG loci.
• Validated the DNA methylation approach against gold standard immune quantification methods and demonstrated robustness with stored samples.

Conclusions:

• DNA methylation analysis provides accurate and reliable assessment of cell mixture distributions in peripheral blood.
• Precise immune cell differential estimates can be reconstructed solely from DNA, eliminating the need for whole cells.
• This method expands the utility of archived blood samples for immunological studies.