Asian Journal of Medicine and Health

Cell-free DNA (cfDNA) circulating in plasma is fragmented non-randomly, and the resulting patterns carry information about the cells and tissues from which the molecules were released. The analysis of these patterns, termed fragmentomics, includes fragment size distributions, preferred end coordinates, end-motif frequencies, nucleosome and transcription-factor footprints, and sequencing coverage around transcription start sites. Enthusiasm for applying fragmentomics within paediatric genetics has grown alongside proposals that plasma-based assays might shorten the diagnostic pathway for rare congenital and inherited metabolic disorders. The present review examines whether the accessible evidence supports that expectation. Literature was identified through Europe PMC and Crossref Metadata Search, supplemented by targeted retrieval of works cited in recent reviews and by verification against digital object identifier landing pages, covering January 2004 to 1 June 2026. Studies were appraised for design adequacy, cohort composition, analytical validation, and the correspondence between the claim advanced and the data presented. Three observations dominate the synthesis. The mechanistic foundations of fragmentomics are comparatively secure, since nuclease activity, chromatin accessibility, and hepatic clearance jointly govern fragment length and terminal characteristics, and genome-wide association analysis has linked end-motif phenotypes to specific nuclease loci. The strongest clinical evidence nevertheless remains obstetric rather than paediatric, concerning fetal fraction estimation, aneuploidy screening, and placental phenotypes, where fragmentomic features operate as quantitative adjuncts rather than as primary determinants of a molecular diagnosis. Direct evidence in postnatal paediatric rare and metabolic disease is sparse, derives largely from small single-centre cohorts, and has been generated principally in graft-injury monitoring rather than in primary diagnosis. Paediatric normative fragmentomic reference data are largely absent, pre-analytical standardisation remains inconsistent, and cohort sizes attainable for individual rare disorders are incompatible with the sample requirements of the statistical learning methods commonly applied. Fragmentomics is best characterised at present as a biologically well-grounded measurement framework whose diagnostic utility in paediatric rare disease remains largely unevaluated rather than established.