cfGWAS reveal genetic basis of cell-free DNA end motifs

Cell-free DNA (cfDNA) consists of degraded DNA fragments released into body fluids. Its genetic and pathological information makes it useful for prenatal testing and early tumor detection. However, the mechanisms behind cfDNA biology are largely unknown. In this study, for the first time, we conduct a genome-wide association study (GWAS) to explore the genetic basis of cfDNA end motif frequencies, termed cfGWAS, in 28,016 pregnant women. We identify 15 study-wide significant loci, including the well-known cfDNA-related genes DFFB and DNASE1L3, as well as novel genes potentially involved in cfDNA biology, such as PANX1 and DNASE1L1. The findings are further verified through three independent GWAS studies and experimental validation in knockout mice and cell lines. Subsequent analyses reveal strong causal relationships of leukocytes, especially neutrophils, with cfDNA features. In summary, we introduce the cfGWAS, revealing the genetic basis of cfDNA biology on a genome-wide scale. Novel knowledge uncovered by this study promises to revolutionize liquid biopsy technology and lead to potential new drugs targeting certain diseases. Given that millions of cfDNA whole genome sequencing data have been generated from clinical testing, the potential of this paradigm is enormous.

Authors

Institutions

Publication Details

Journal
Nature Communications
Published
2026-02-14
DOI
https://doi.org/10.1038/s41467-025-67940-w
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

cfGWAS reveal genetic basis of cell-free DNA end motifs

Chuang Xu, Guodan Zeng, Ran Zhao, Yongjian Jia et al.
Nature Communications
Cancer Genomics and Diagnostics
article

cfGWAS reveal genetic basis of cell-free DNA end motifs

Chuang Xu, Guodan Zeng, Ran Zhao, Yongjian Jia, Aifen Zhou, Yan Zhang, Xiameizi Li, Yuxuan Hu, Xinyi Zhang, Fei Luo, Han Xiao, Huanhuan Zhu, Jian Wang, Jingyu Zeng, Lin Wang, Yu Lin, Xun Xu, Meng Yang, Ying Lin, Shuang Zeng, Xin Jin, Linxuan Li, Lingguo Li, Yu Wang, Rijing Ou, Haiqiang Zhang
article en

Abstract

Cell-free DNA (cfDNA) consists of degraded DNA fragments released into body fluids. Its genetic and pathological information makes it useful for prenatal testing and early tumor detection. However, the mechanisms behind cfDNA biology are largely unknown. In this study, for the first time, we conduct a genome-wide association study (GWAS) to explore the genetic basis of cfDNA end motif frequencies, termed cfGWAS, in 28,016 pregnant women. We identify 15 study-wide significant loci, including the well-known cfDNA-related genes DFFB and DNASE1L3, as well as novel genes potentially involved in cfDNA biology, such as PANX1 and DNASE1L1. The findings are further verified through three independent GWAS studies and experimental validation in knockout mice and cell lines. Subsequent analyses reveal strong causal relationships of leukocytes, especially neutrophils, with cfDNA features. In summary, we introduce the cfGWAS, revealing the genetic basis of cfDNA biology on a genome-wide scale. Novel knowledge uncovered by this study promises to revolutionize liquid biopsy technology and lead to potential new drugs targeting certain diseases. Given that millions of cfDNA whole genome sequencing data have been generated from clinical testing, the potential of this paradigm is enormous.

Nature CommunicationsVol. 17(1)
BGI Group (China) (CN), Shanxi Medical University (CN), Peking University (CN), Guiyang University (CN), Wuhan Children's Hospital (CN), University of Chinese Academy of Sciences (CN), BGI Research (CN), Huazhong University of Science and Technology (CN), South China University of Technology (CN)
National Natural Science Foundation of China, Natural Science Foundation of Hubei Province, Peking University, National Key Research and Development Program of China
Good health and well-being
Openalex Percentile: Top 58%
Cancer Genomics and Diagnostics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.