Cell-free DNA fragmentomes for noninvasive detection of liver cirrhosis and other diseases.

Abstract

Accessible liquid biopsies, including analyses of genome-wide cell-free DNA (cfDNA) fragmentation, are emerging for early detection of cancer but remain largely unexplored in other diseases. Here, we used whole-genome sequencing to examine cfDNA fragmentomes in 1576 individuals, including those with liver disease or with other morbidities such as vascular, autoimmune, and neurodegenerative conditions. As a prototype for disease-specific cfDNA fragmentomic biomarkers, we developed a machine learning classifier that detected early liver disease, advanced fibrosis, and cirrhosis with high sensitivity in separate discovery (<i>n</i> = 423) and validation cohorts (<i>n</i> = 221) and had limited cross-reactivity for other diseases. Genome-wide fragmentome and methylome analyses revealed liver-derived and immune-mediated changes in cfDNA in the circulation of individuals affected with liver disease. Fragmentomic changes were also observed across a range of other human morbidities and reflected disease-specific changes in the circulation. A machine learning model using cfDNA fragmentomes predicted overall survival in separate morbidity discovery (<i>n</i> = 571) and validation cohorts (<i>n</i> = 231). These analyses demonstrate the connection between cfDNA fragmentomes and an individual's physiologic state and provide previously unrecognized possibilities for cfDNA liquid biopsies across human disease.