Methylation patterns of circulating cell-free DNA (cfDNA) contain rich information about recent cell death events in the body. Here, we present an approach for unbiased determination of the tissue origins of cfDNA, using a reference methylation atlas of 25 human tissues and cell types. The method is validated using in silico simulations as well as in vitro mixes of DNA from different tissue sources at known proportions. We show that plasma cfDNA of healthy donors originates from white blood cells (55%), erythrocyte progenitors (30%), vascular endothelial cells (10%) and hepatocytes (1%). Deconvolution of cfDNA from patients reveals tissue contributions that agree with clinical findings in sepsis, islet transplantation, cancer of the colon, lung, breast and prostate, and cancer of unknown primary. We propose a procedure which can be easily adapted to study the cellular contributors to cfDNA in many settings, opening a broad window into healthy and pathologic human tissue dynamics.

Minimally invasive detection of cell death could prove an invaluable resource in many physiologic and pathologic situations. Cell-free circulating DNA (cfDNA) released from dying cells is emerging as a diagnostic tool for monitoring cancer dynamics and graft failure. However, existing methods rely on differences in DNA sequences in source tissues, so that cell death cannot be identified in tissues with a normal genome. We developed a method of detecting tissue-specific cell death in humans based on tissue-specific methylation patterns in cfDNA. We interrogated tissue-specific methylome databases to identify cell type-specific DNA methylation signatures and developed a method to detect these signatures in mixed DNA samples. We isolated cfDNA from plasma or serum of donors, treated the cfDNA with bisulfite, PCR-amplified the cfDNA, and sequenced it to quantify cfDNA carrying the methylation markers of the cell type of interest. Pancreatic β-cell DNA was identified in the circulation of patients with recently diagnosed type-1 diabetes and islet-graft recipients; oligodendrocyte DNA was identified in patients with relapsing multiple sclerosis; neuronal/glial DNA was identified in patients after traumatic brain injury or cardiac arrest; and exocrine pancreas DNA was identified in patients with pancreatic cancer or pancreatitis. This proof-of-concept study demonstrates that the tissue origins of cfDNA and thus the rate of death of specific cell types can be determined in humans. The approach can be adapted to identify cfDNA derived from any cell type in the body, offering a minimally invasive window for diagnosing and monitoring a broad spectrum of human pathologies as well as providing a better understanding of normal tissue dynamics.

Methylation patterns of specific genes have been studied by polymerase chain reaction and found to undergo dynamic changes in the germ line and early embryo. Some CpG sites are methylated in sperm DNA and unmodified in mature oocytes, indicating that the parental genomes have differential methylation profiles. These differences, however, are erased by a series of early embryonic demethylation and postblastula remodification events, which serve to reestablish the basic adult methylation pattern prior to organogenesis. During gametogenesis, all of these sites are unmethylated in primordial germ cells but eventually become remodified by 18.5 days postcoitum in both males and females. The final methylation profile of the mature germ cells is then formed by a multistep process of site-specific demethylation events. These results form a basis for the understanding of the biochemical mechanisms and role of DNA methylation in embryonic development.

1Methylation patterns of circulating cell-free DNA (cfDNA) contain rich information about recent 2 cell death events in the body. Here, we present an approach for unbiased determination of the 3 tissue origins of cfDNA, using a reference methylation atlas of 25 human tissues and cell types. 4The method is validated using in silico simulations as well as in vitro mixes of DNA from 5 different tissue sources at known proportions. We show that plasma cfDNA of healthy donors 6 originates from white blood cells (55%), erythrocyte progenitors (30%), vascular endothelial 7 cells (10%) and hepatocytes (1%). Deconvolution of cfDNA from patients reveals tissue 8 contributions that agree with clinical findings in sepsis, islet transplantation, cancer of the 9 colon, lung, breast and prostate, and cancer of unknown primary. We propose a procedure 10 which can be easily adapted to study the cellular contributors to cfDNA in many settings, 11 opening a broad window into healthy and pathologic human tissue dynamics. 12 13

DNA methylation is a fundamental epigenetic mark that governs gene expression and chromatin organization, thus providing a window into cellular identity and developmental processes1. Current datasets typically include only a fraction of methylation sites and are often based either on cell lines that underwent massive changes in culture or on tissues containing unspecified mixtures of cells2–5. Here we describe a human methylome atlas, based on deep whole-genome bisulfite sequencing, allowing fragment-level analysis across thousands of unique markers for 39 cell types sorted from 205 healthy tissue samples. Replicates of the same cell type are more than 99.5% identical, demonstrating the robustness of cell identity programmes to environmental perturbation. Unsupervised clustering of the atlas recapitulates key elements of tissue ontogeny and identifies methylation patterns retained since embryonic development. Loci uniquely unmethylated in an individual cell type often reside in transcriptional enhancers and contain DNA binding sites for tissue-specific transcriptional regulators. Uniquely hypermethylated loci are rare and are enriched for CpG islands, Polycomb targets and CTCF binding sites, suggesting a new role in shaping cell-type-specific chromatin looping. The atlas provides an essential resource for study of gene regulation and disease-associated genetic variants, and a wealth of potential tissue-specific biomarkers for use in liquid biopsies.