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.

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

Detection of cardiomyocyte death is crucial for the diagnosis and treatment of heart disease. Here we use comparative methylome analysis to identify genomic loci that are unmethylated specifically in cardiomyocytes, and develop these as biomarkers to quantify cardiomyocyte DNA in circulating cell-free DNA (cfDNA) derived from dying cells. Plasma of healthy individuals contains essentially no cardiomyocyte cfDNA, consistent with minimal cardiac turnover. Patients with acute ST-elevation myocardial infarction show a robust cardiac cfDNA signal that correlates with levels of troponin and creatine phosphokinase (CPK), including the expected elevation-decay dynamics following coronary angioplasty. Patients with sepsis have high cardiac cfDNA concentrations that strongly predict mortality, suggesting a major role of cardiomyocyte death in mortality from sepsis. A cfDNA biomarker for cardiomyocyte death may find utility in diagnosis and monitoring of cardiac pathologies and in the study of normal human cardiac physiology and development.

Blood contains cfDNA fragments derived from dying cells 1 . cfDNA has a half-life of ~15 min 2 and, therefore, represents events that occurred close to sampling time. cfDNA analysis is used for assessment of fetus chromosomal aberrations, graft rejection, monitoring tumor dynamics and targeted treatment [3][4][5][6][7] . These applications rely on genetic differences between the host and the tissue of interest. Analysis of CpG methylation in cfDNA is emerging as an alternative independent of genetic alteration 5,[8][9][10][11] . CpG methylation profiles are determined during differentiation and are stable afterwards and, thus, are highly informative about cell identity (for example, liver or lung). However, genetic and methylation-based approaches do not report on recent transcriptional events, as mutations and methylation changes occur over developmental time scales.The basic repeating unit of chromatin is the nucleosome, which is a histone-DNA complex encompassing ~150 base pairs (bp) of DNA 12 . Histone proteins are subject to multiple covalent modifications, which are involved in nearly all aspects of messenger RNA (mRNA) biogenesis [13][14][15][16] . Histone modification patterns reflect recent events related to chromatin regulation and activity of RNA polymerase 13,15 , and different combinations of such modifications mark the location and activity of non-coding regions, enhancers, promoters and gene bodies [17][18][19][20][21][22] . Chromatin immunoprecipitation and sequencing (ChIP-seq) enables genome-wide mapping of histone modifications and provides detailed understanding of the regulatory activity within cells [17][18][19][23][24][25][26][27] .Upon cell death, the genome is fragmented, and chromatin, mostly in the form of nucleosomes, is released into the circulation as cell-free nucleosomes (cf-nucleosomes) 28-30 that retain some histone modifications [31][32][33] . We reasoned that capturing and DNA sequencing of modified nucleosomes from plasma might inform on DNA-related activities, including transcription, within the cells of origin (Fig. 1a). This currently inaccessible epigenetic information extends beyond cfDNA modalities examined to date [4][5][6][7][8][9][10][11][34][35][36][37][38][39][40][41][42][43] .In this study, we performed chromatin immunoprecipitation and sequencing of cell-free nucleosomes directly from human plasma (cfChIP-seq). We show that cfChIP-seq recapitulates the original genomic distribution of modifications associated with transcriptionally active promoters, enhancers and gene bodies, demonstrating that plasma nucleosomes retain the epigenetic information of their