Cell GenomicsGenomicsPeer-reviewed journal article
The circulating cell-free DNA landscape in sepsis is dominated by impaired liver clearance
Kiki Cano-GameziD, Patrick Maclean, Masato Inoue, Sakineh Hussainy, Elisabeth Foss, Chloe Wainwright, Hanyu Qin, Stuart McKechnieiD, Chun‐Xiao SongiD, Julian Charles KnightiD
- Citations
- 17
- FWCI
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- Field percentile
- top 1%
Abstract
Circulating cell-free DNA (cfDNA) is a promising molecular biomarker. However, its utility in severe infection remains poorly understood. Here, we isolated cfDNA from sepsis patients and controls, demonstrating a 41-fold increase in the amount of cfDNA in circulation during disease. We used sequencing to reconstruct cfDNA methylomes, fragmentation profiles, and nucleosome footprints across 56 samples. We observed no difference in cfDNA composition between patients and controls, challenging the idea that cfDNA increases due to higher immune cell death during sepsis. Instead, we suggest that liver dysfunction prevents efficient clearance of cfDNA during disease. This was supported by fragmentation and end-motif patterns, both of which showed evidence of cfDNA being exposed to circulating nucleases for a prolonged period, proportionally to the extent of liver dysfunction. Variation in cfDNA of megakaryocyte-erythroid progenitor origin was also a significant contributor in sepsis, increasing over time. Moreover, we showed that cfDNA retains nucleosome footprints with cell type-specific gene activity information. We developed a novel approach to study nucleosome phasing that successfully recovers tissue-specific signatures. By combining this with single-cell data, we demonstrated that sepsis patients with liver dysfunction have higher amounts of cfDNA derived from Kupffer cells and the liver parenchyma. In conclusion, we present the first high-throughput multi-modal study of cfDNA during sepsis, which will serve as a reference point for future studies on the role of this biomarker in critical illness.
- organism: human
- assay: DNA methylation
- assay: whole-genome sequencing
- research focus: differential expression
- research focus: benchmarking
- approach: statistical model
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