Impact of Clinical Variables on cfDNA Fragmentomic Signatures and Their Potential as Confounders in Cancer Detection

Abstract Background Circulating cell-free DNA (cfDNA) fragmentomic features, such as fragment size and end motifs, have emerged as promising noninvasive biomarkers for cancer detection. However, the influence of nonmalignant clinical factors on these features remains unclear, potentially confounding liquid biopsy assays. Methods We analyzed cfDNA fragmentomic data from 1154 noncancerous individuals undergoing routine health checkups. Three cfDNA features were examined: cfDNA concentration, short fragment ratio (SFR), and cancer-enriched motif (CEM) frequency. Associations with 65 demographic, hematologic, and biochemical variables were assessed using univariate and multivariate analyses. High-resolution correlation mapping of fragment size (110 to 230 bp) and 4-mer end motifs was performed. Patterns were compared with profiles from 283 lung cancer patients, and confounding effects were evaluated using receiver operating characteristic (ROC) analysis. Results Multiple nonmalignant variables significantly correlated with cfDNA features. Age was associated with all three features, while liver function markers (aspartate aminotransferase [AST], alkaline phosphatase [ALP], γ-glutamyl transferase [γ-GTP]) showed strong associations with SFR and CEM frequency. High-resolution analyses revealed that AST-related fragment size profiles closely resembled cancer-associated patterns, whereas age showed partial similarity to cancer-associated end motif alterations. ROC analyses demonstrated that elevated AST or older age reduced the discriminative performance of SFR and CEM, indicating their potential as confounders in lung cancer detection. Conclusions Physiological factors such as liver enzyme levels and age can significantly alter cfDNA fragmentomic profiles, generating patterns that resemble lung cancer-associated signals. These results highlight the importance of incorporating strategies to mitigate nonmalignant variability when developing cfDNA-based liquid biopsy assays, to ensure their accuracy, specificity, and clinical applicability.