This study presents a method for inferring changes in the distribution of white blood cell types between different populations using DNA methylation signatures. The method uses DNA methylation data from purified leukocyte samples as an external validation set to estimate the proportions of immune cells in unfractionated whole blood. The approach is based on the assumption that DNA methylation signatures can serve as a high-dimensional multivariate surrogate for the distribution of white blood cells. The method was validated using data from several studies, including a Head and Neck Squamous Cell Carcinoma (HNSCC) study and an ovarian cancer study. The results showed that the method produces results consistent with prior biological findings, validating the approach. The study also highlights the potential of DNA methylation arrays as a new tool for large-scale immunological studies of disease states and noxious exposures. The method was tested on various data sets, including those from Down syndrome, obesity in African Americans, and ovarian cancer. The results demonstrated that the method can accurately estimate the proportions of different cell types in whole blood, with accuracy within 10% and often less than 5%. The study also discusses the implications of the findings for understanding the underlying immuno-biology of disease states and the immune response to chronic medical conditions. The method was shown to be robust and effective in estimating cell mixture distributions, even in the presence of measurement error. The study concludes that DNA methylation arrays have the potential to provide valuable insights into the composition of leukocyte populations and their role in disease processes.This study presents a method for inferring changes in the distribution of white blood cell types between different populations using DNA methylation signatures. The method uses DNA methylation data from purified leukocyte samples as an external validation set to estimate the proportions of immune cells in unfractionated whole blood. The approach is based on the assumption that DNA methylation signatures can serve as a high-dimensional multivariate surrogate for the distribution of white blood cells. The method was validated using data from several studies, including a Head and Neck Squamous Cell Carcinoma (HNSCC) study and an ovarian cancer study. The results showed that the method produces results consistent with prior biological findings, validating the approach. The study also highlights the potential of DNA methylation arrays as a new tool for large-scale immunological studies of disease states and noxious exposures. The method was tested on various data sets, including those from Down syndrome, obesity in African Americans, and ovarian cancer. The results demonstrated that the method can accurately estimate the proportions of different cell types in whole blood, with accuracy within 10% and often less than 5%. The study also discusses the implications of the findings for understanding the underlying immuno-biology of disease states and the immune response to chronic medical conditions. The method was shown to be robust and effective in estimating cell mixture distributions, even in the presence of measurement error. The study concludes that DNA methylation arrays have the potential to provide valuable insights into the composition of leukocyte populations and their role in disease processes.