Strategies and challenges in the detection of clonal hematopoiesis: current advances and future perspectives

Clonal hematopoiesis (CH) is the clonal expansion of hematopoietic stem and progenitor cell lineages carrying acquired somatic mutations, a common feature of hematopoietic aging. Its clinical relevance extends beyond hematologic malignancy risk to inflammation-linked comorbidities and emerging implications for cancer therapy response. CH detection faces a depth-dependent trade-off: cohort-scale whole-genome and whole-exome sequencing often miss small clones, whereas ultra-deep targeted panels increase exposure to technical artifacts that mimic low-frequency variants. We summarize approaches to stabilize low-variant allele fraction calls, including UMI-based error suppression, background modeling with panels of normals, and consensus calling across complementary variant callers. We also note how deep learning can improve artifact discrimination and variant prioritization when rule-based filters become brittle. Finally, we outline an interpretation framework integrating orthogonal evidence, including non-coding risk variants, routine clinical measures, and proteomic/metabolomic readouts, and we emphasize the need for better harmonization of detection and reporting standards.