Cost-Effective and Scalable Clonal Hematopoiesis Assay Provides Insight into Clonal Dynamics

Abstract

Clonal hematopoiesis of indeterminate potential (CHIP) is a common age-related phenomenon in which hematopoietic stem cells acquire mutations in a select set of genes commonly mutated in myeloid neoplasia which then expand clonally. Current sequencing assays to detect CHIP mutations are not optimized for the detection of these variants and can be cost-prohibitive when applied to large cohorts or to serial sequencing. In this study, an affordable (approximately US $8 per sample), accurate, and scalable sequencing assay for CHIP is introduced and validated. The efficacy of the assay was demonstrated by identifying CHIP mutations in a cohort of 456 individuals with DNA collected at multiple time points in Vanderbilt University's biobank and quantifying clonal expansion rates over time. A total of 101 individuals with CHIP/clonal cytopenia of undetermined significance were identified, and individual-level clonal expansion rate was calculated using the variant allele fraction at both time points. Differences in clonal expansion rate by driver gene were observed, but there was also significant individual-level heterogeneity, emphasizing the multifactorial nature of clonal expansion. Additionally, mutation co-occurrence and clonal competition between multiple driver mutations were explored.

Figure 1

Study design. A: Schematic representation of CHIP identification assay. DNA is extracted from the blood and tested for CHIP mutations using the low-cost, scalable targeted assay that tests for 22 specific genes and positions. CHIP mutations are identified and the variant allele fraction (VAF) is estimated. B: Schematic representation of characterizing CHIP clones over time in BioVU. The CHIP assay was applied to a cohort using Vanderbilt BioVU with multiple blood samples over time. CHIP/CCUS was identified in one or both time points and VAF was estimated, allowing for the estimation of clonal growth rate over time and characterization of clonal behavior.

Figure 2

CHIP detected in the BioVU cohort. A: Counts of mutations per driver gene in the cohort, and counts of CHIP driver mutations in individuals. DNMT3A and TET2 are the most common driver genes, and the vast majority of individuals have one CHIP driver mutation. B: Distribution of age at time point 1, and differences between time points in each individual in the cohort. Histograms along the axes reflect total counts as well as the driver-gene distribution. C: Distribution of variant allele fraction (VAF) at time point 1 across the most common driver genes. There were no significant differences between driver genes. D: Distribution of TET2 and DNMT3A driver mutations across age categories. The sample sizes refer to the numbers of mutations per age category (not the numbers of individuals).

Figure 3

CHIP clonal behavior, by driver gene. A: Mean growth rate across the most common driver genes in individuals with CHIP mutations. Each point represents one CHIP mutation. Genes are arranged in descending order on the y axis based on mean growth rate, and the x axis is limited and excludes values of >1.2. Mean growth rates are marked by dots. B and C: Mean growth rates (dots) of DNMT3A hotspot mutations (B) and missense and loss-of-function (LOF) mutations (C). D: CHIP clone trajectories, shown as change in variant allele fraction (VAF) over time. Each line represents one clone, the length of the line represents years between time points, and the slope of the line represents net change in VAF over time. Lines are colored by clonal-behavior category and are stratified by CHIP driver gene.

Figure 4

Clonal trajectories over time in individuals with >one driver mutation. A: In individuals with >one driver mutation, different clonal trajectories are possible. The mutations can be either in completely separate cells (distinct clones) or in the same cells (sub-clones). For distinct clones, different growth rates and clonal behavior would be expected, while sub-clones should show similar growth rates. In this hypothetical example, Individual 1 likely shows distinct clonal behavior, while Individual 2 likely shows sub-clonal behavior. B: Number of individuals in each sub-clone and distinct clone group. C: CHIP driver genes in each individual with two CHIP driver mutations. Each vertical line on the x axis represents one individual, and each point represents a CHIP clone. If an individual has both mutations on the same driver gene, the points are slightly overlapping.