Error-corrected ultradeep next-generation sequencing for detection of clonal haematopoiesis and haematological neoplasms – sensitivity, specificity and accuracy - Melinda L. Tursky; Crisbel M. Artuz; Melissa Rapadas; Gary A. Wittert; Timothy J. Molloy; David D. Ma (PLoS ONE, 2025)
Clonal haematopoiesis of indeterminate potential (CHIP) is an aging-associated phenomenon that has recently been correlated with a broad spectrum of human diseases, including haematological malignancy, cytopenia, coronary heart disease, stroke, and overall mortality. CHIP is defined as a somatic variant in blood cells with an allele frequency (VAF) ≥ 0.02, however recent reports show smaller clones are associated with poorer clinical outcome. Error-corrected ultradeep next-generation sequencing (NGS) assays detecting variants < 0.02 VAF also have clinical value for monitoring measurable residual disease (MRD) for myeloid neoplasms. However, limited data are available on optimal parameters, limits of detection, and accuracy of ultra-sensitive detection. We investigated parameters to improve accuracy of Illumina sequencing-by-synthesis method, including read depth, input DNA quantity, and molecular barcoding-based data filtering, while adhering to clinical accreditation criteria. Validation data were generated from reference standards and reference samples from a clinically accredited pathology laboratory. Analytical range measurements included linearity and bias, and precision included repeatability, reproducibility and detection rate. The lower limit of detection was ≥ 0.004 (0.4%) at depth > 3,000 × . Trueness measured using reference standards demonstrated a sensitivity, specificity, positive and negative predictive values, and accuracy of 100%, including FLT3-ITD, and 100% concordance was achieved with reference samples for reported variants and absence of variants. Sequencing blood samples from 383 community-dwelling adults (mean depth 3758×) revealed 2,190 somatic variants/sample, > 99.9% were < 0.02 VAF. Our data including cost-benefit analysis enables pathology and research laboratories to make informed decisions for detection of CHIP (VAF ≥ 0.02), sub-CHIP (VAF 0.01–0.02) and MRD (VAF ≥ 0.004).