Cell-free chromatin state tracing reveals disease origin and therapy responses

Cell-free DNA in blood originates from fragmented chromatin released by dying cells from both healthy and diseased tissues<sup>1,2</sup>. These fragments carry rich molecular modalities that can reveal pathological alterations in tissues of origin<sup>3-10</sup>. Here we develop cf-EpiTracing, a highly sensitive automated platform that profiles histone modifications in cell-free DNA from as little as 50 μl of human plasma. By integrating multimodal chromatin states with machine learning, cf-EpiTracing enables accurate deconvolution of cell types of origin. We generated 2,417 cf-EpiTracing profiles from plasma of 125 healthy individuals and 549 patients with inflammatory bowel disease, colorectal cancer, coronary heart disease or lymphoma. cf-EpiTracing enabled unbiased identification of primary diseased tissues and other organ involvement, stratification of B cell lymphoma subtypes with different genetic and epigenetic underpinnings, and detection of early-stage diseases or lesions. Surveying dynamics of epigenetic signatures uncovered disease transformation from follicular lymphoma to diffuse large B cell lymphoma. Further, cf-EpiTracing revealed genomic translocations and epigenetic alterations in patients with mantle cell lymphoma. Of note, our study leverages holistic epigenetic signatures, independently of knowledge of gene transcription, to accurately report recurrence risk and therapeutic response. Together, these findings establish cf-EpiTracing as an automated, non-invasive, epigenome-centric framework with broad applications in early diagnosis, molecular subtyping and prognostic prediction.

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Publication Details

Journal
Nature
Published
2026-03-04
DOI
https://doi.org/10.1038/s41586-026-10224-0
Primary Topic
Genomics and Chromatin Dynamics
Type
article
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0.00
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article

Cell-free chromatin state tracing reveals disease origin and therapy responses

Aibin He, Zongchao Liu, Xubin Chen, Yanzhu Yue et al.
Nature
Genomics and Chromatin Dynamics
article

Cell-free chromatin state tracing reveals disease origin and therapy responses

Aibin He, Zongchao Liu, Xubin Chen, Yanzhu Yue, Yaping Zhang, Fang Bao, Libo Zhu, Zhengting Wang, Hongmei Jing, Xinyu Qi, Peng Du, Ping Yang, Lan Mi, Yan Hou, Jing Sun, Xiawei Zhang, Junke Zheng, Yan Liu, Yu Tian, Jing Wang (6206297), Sen Li, Liping Dou, Jia Liu, Changjian Yan, Lingke Zhang, Wenqing Li, Guoqiang Chen, Chunyuan Li, Xiaoxuan Meng
article en

Abstract

Cell-free DNA in blood originates from fragmented chromatin released by dying cells from both healthy and diseased tissues<sup>1,2</sup>. These fragments carry rich molecular modalities that can reveal pathological alterations in tissues of origin<sup>3-10</sup>. Here we develop cf-EpiTracing, a highly sensitive automated platform that profiles histone modifications in cell-free DNA from as little as 50 μl of human plasma. By integrating multimodal chromatin states with machine learning, cf-EpiTracing enables accurate deconvolution of cell types of origin. We generated 2,417 cf-EpiTracing profiles from plasma of 125 healthy individuals and 549 patients with inflammatory bowel disease, colorectal cancer, coronary heart disease or lymphoma. cf-EpiTracing enabled unbiased identification of primary diseased tissues and other organ involvement, stratification of B cell lymphoma subtypes with different genetic and epigenetic underpinnings, and detection of early-stage diseases or lesions. Surveying dynamics of epigenetic signatures uncovered disease transformation from follicular lymphoma to diffuse large B cell lymphoma. Further, cf-EpiTracing revealed genomic translocations and epigenetic alterations in patients with mantle cell lymphoma. Of note, our study leverages holistic epigenetic signatures, independently of knowledge of gene transcription, to accurately report recurrence risk and therapeutic response. Together, these findings establish cf-EpiTracing as an automated, non-invasive, epigenome-centric framework with broad applications in early diagnosis, molecular subtyping and prognostic prediction.

Nature
Shanghai Jiao Tong University (CN), Jilin University (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Peking University (CN), Ruijin Hospital (CN), Chinese PLA General Hospital (CN), Peking University Cancer Hospital (CN), Shanghai Ninth People's Hospital (CN), Tongren Hospital (CN), First Hospital of Jilin University (CN), Chengdu University (CN), Peking University First Hospital (CN), Peking University Third Hospital (CN), Ministry of Education (ET), PLA Academy of Military Science (CN), Center for Life Sciences (CN), Hainan Medical University (CN)
Openalex Percentile: Top 34%
Genomics and Chromatin Dynamics
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