Longitudinal cell-free DNA methylome and fragmentome profiles in health uncover signatures of cell type and demographic origin.

backgroundCell-free DNA (cfDNA) is a powerful analyte for liquid biopsy applications. However, the composition and fragmentation of cfDNA in health remains incompletely characterized. Understanding this baseline variation is key to advancing cfDNA-based assay development.

methodsWe profiled 432 plasma cfDNA samples from 160 healthy individuals across two cohorts: a diurnal (n = 16) and a cross-sectional (n = 144) cohort, to evaluate circadian as well as demographic effects on estimated cfDNA concentration, cellular composition and fragmentomic characteristics. Targeted enzymatic methyl-sequencing was used to infer cell-type of origin and assess fragmentation patterns.

resultscfDNA concentration and fragment size exhibited circadian patterns, with morning samples showing 63% higher cfDNA concentrations (P = 1.8 × 10–5) and a 7% increase in mononucleosomal fragments (P = 2.3 × 10–4) compared to afternoon and evening samples. Cell-type-specific rhythms were observed in natural killer cells, monocytes, and hepatocytes, while other cell types remained relatively stable. In both the diurnal and cross-sectional cohort, hematopoietic lineages were the predominant sources of cfDNA. Cell-type contributions to cfDNA were more consistent within individuals than between individuals, reflecting relatively robust intraindividual profiles. Demographic variables, including sex, age and body mass index, influenced the contribution of specific blood cell types. By integrating cell-type-specific methylation, fragment size, and dinucleotide end motifs we uncovered distinct fragmentation signatures associated with individual cell type proportions. Granulocyte-derived cfDNA showed a consistent enrichment in mononucleosomal sizes (P < 1.0 × 10–16) and CC end motifs, while cfDNA from other cells exhibited distinct size and end-motif profiles. Additionally, hypomethylated DNA was associated with shorter fragment sizes and altered end-motif frequencies, emphasizing interactions between DNA methylation, nuclease activity and chromatin context in shaping cfDNA fragment characteristics.

conclusionsOur findings provide a comprehensive view on processes and cell types involved in cfDNA biogenesis in healthy individuals. They underscore that demographic variables and sampling time should be considered in cfDNA-based assay design, but also highlight opportunities to improve the representation of specific cell types in cfDNA, thus providing a foundation for optimizing cfDNA diagnostics by leveraging multiple axes of information.