Researchers from Johns Hopkins and collaborators published pilot studies demonstrating that genome‑wide cell‑free DNA (cfDNA) fragmentomics and AI analysis can detect liver fibrosis and cirrhosis, expanding liquid biopsy applications beyond oncology. The approach leverages fragment size and genomic packaging patterns—termed the fragmentome—to infer tissue injury and immune‑mediated changes, enabling noninvasive staging of chronic liver disease. The teams showed fragmentomic signatures can distinguish cirrhosis and fibrosis from healthy controls and identified patterns tied to immune cell composition. The method was validated across clinical cohorts and presented as adaptable to other non‑cancer pathologies that release characteristic cfDNA fragmentation patterns. If scaled and commercialized, fragmentomic liquid biopsies could fill a major unmet need for less invasive diagnostics in hepatology, where liver biopsy is risky and existing noninvasive tests have limited sensitivity. The work also illustrates how combining epigenomic and fragmentomic signals with AI creates a platform capable of multi‑disease detection from a single blood draw.