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.

The Oxford Nanopore (ONT) platform provides portable and rapid genome sequencing, and its ability to natively profile DNA methylation without complex sample processing is attractive for point-of-care real-time sequencing. We recently demonstrated ONT shallow whole-genome sequencing to detect copy number alterations (CNAs) from the circulating tumor DNA (ctDNA) of cancer patients. Here, we show that cell type and cancer-specific methylation changes can also be detected, as well as cancer-associated fragmentation signatures. This feasibility study suggests that ONT shallow WGS could be a powerful tool for liquid biopsy. Graphical Abstract

Cancer inflicts damage to surrounding normal tissues, which can culminate in fatal organ failure. Here, we demonstrate that cell death in organs affected by cancer can be detected by tissue-specific methylation patterns of circulating cell-free DNA (cfDNA). We detected elevated levels of hepatocyte-derived cfDNA in the plasma of patients with liver metastases originating from different primary tumors, compared with cancer patients without liver metastases. In addition, patients with localized pancreatic or colon cancer showed elevated hepatocyte cfDNA, suggesting liver damage inflicted by micrometastatic disease, by primary pancreatic tumor pressing the bile duct, or by a systemic response to the primary tumor. We also identified elevated neuron-, oligodendrocyte-, and astrocyte-derived cfDNA in a subpopulation of patients with brain metastases compared with cancer patients without brain metastasis. Cell type–specific cfDNA methylation markers enable the identification of collateral tissue damage in cancer, revealing the presence of metastases in specific locations and potentially assisting in early cancer detection.

It has been proposed that unmethylated insulin promoter fragments in plasma derive exclusively from β cells, reflect their recent demise, and can be used to assess β cell damage in type 1 diabetes. Herein we describe an ultrasensitive assay for detection of a β cell–specific DNA methylation signature, by simultaneous assessment of 6 DNA methylation markers, that identifies β cell DNA in mixtures containing as little as 0.03% β cell DNA (less than 1 β cell genome equivalent). Based on this assay, plasma from nondiabetic individuals ( N = 218, aged 4–78 years) contained on average only 1 β cell genome equivalent/mL. As expected, cell-free DNA (cfDNA) from β cells was significantly elevated in islet transplant recipients shortly after transplantation. We also detected β cell cfDNA in a patient with KATP congenital hyperinsulinism, in which substantial β cell turnover is thought to occur. Strikingly, in contrast to previous reports, we observed no elevation of β cell–derived cfDNA in autoantibody-positive subjects at risk for type 1 diabetes ( N = 32), individuals with recent-onset type 1 diabetes (4 months, N = 38). We discuss the utility of sensitive β cell cfDNA analysis and potential explanations for the lack of a β cell cfDNA signal in type 1 diabetes.