Cell type signatures in cell-free DNA fragmentation profiles reveal disease biology

Abstract

Circulating cell-free DNA (cfDNA) fragments have characteristics that are specific to the cell types that release them. Current methods for cfDNA deconvolution typically use disease tailored marker selection in a limited number of bulk tissues or cell lines. Here, we utilize single cell transcriptome data as a comprehensive cellular reference set for disease-agnostic cfDNA cell-of-origin analysis. We correlate cfDNA-inferred nucleosome spacing with gene expression to rank the relative contribution of over 490 cell types to plasma cfDNA. In 744 healthy individuals and patients, we uncover cell type signatures in support of emerging disease paradigms in oncology and prenatal care. We train predictive models that can differentiate patients with colorectal cancer (84.7%), early-stage breast cancer (90.1%), multiple myeloma (AUC 95.0%), and preeclampsia (88.3%) from matched controls. Importantly, our approach performs well in ultra-low coverage cfDNA datasets and can be readily transferred to diverse clinical settings for the expansion of liquid biopsy.

Ampholytic ion-exchange magnetic beads: a promising tool for selecting short fragments in circulating cell-free DNA analysis

“…In terms of size analysis, cfDNA mostly contained fragments less than 1000 base pairs (bp) ( 6 ). These cfDNA fragments are derived from nuclease-processed nucleosome arrays which consist of 147 bp of DNA wrapped around a histone octamer core with approximately 20-40 bp of unbound linker DNA interspersed ( 7 , 8 ). Short cfDNA fragments(<150 bp) contain a larger fraction of mutated fragments than the total cfDNA pool ( 9 ).…”