Age-related clonal hematopoiesis associated with adverse outcomes

Abstract

Background: The incidence of hematologic cancers increases with age. These cancers are associated with recurrent somatic mutations in specific genes. We hypothesized that such mutations would be detectable in the blood of some persons who are not known to have hematologic disorders.

Methods: We analyzed whole-exome sequencing data from DNA in the peripheral-blood cells of 17,182 persons who were unselected for hematologic phenotypes. We looked for somatic mutations by identifying previously characterized single-nucleotide variants and small insertions or deletions in 160 genes that are recurrently mutated in hematologic cancers. The presence of mutations was analyzed for an association with hematologic phenotypes, survival, and cardiovascular events.

Results: Detectable somatic mutations were rare in persons younger than 40 years of age but rose appreciably in frequency with age. Among persons 70 to 79 years of age, 80 to 89 years of age, and 90 to 108 years of age, these clonal mutations were observed in 9.5% (219 of 2300 persons), 11.7% (37 of 317), and 18.4% (19 of 103), respectively. The majority of the variants occurred in three genes: DNMT3A, TET2, and ASXL1. The presence of a somatic mutation was associated with an increase in the risk of hematologic cancer (hazard ratio, 11.1; 95% confidence interval [CI], 3.9 to 32.6), an increase in all-cause mortality (hazard ratio, 1.4; 95% CI, 1.1 to 1.8), and increases in the risks of incident coronary heart disease (hazard ratio, 2.0; 95% CI, 1.2 to 3.4) and ischemic stroke (hazard ratio, 2.6; 95% CI, 1.4 to 4.8).

Conclusions: Age-related clonal hematopoiesis is a common condition that is associated with increases in the risk of hematologic cancer and in all-cause mortality, with the latter possibly due to an increased risk of cardiovascular disease. (Funded by the National Institutes of Health and others.).

Figure 1. Prevalence of Somatic Mutations, According to Age

Colored bands, in increasingly lighter shades, represent the 50th, 75th, and 95th percentiles.

Figure 2. Characteristics of Candidate Somatic Variants

Panel A shows the 10 most frequently mutated genes implicated in hematologic cancers. Panel B shows the number of persons with 1, 2, 3, or 4 candidate variants. Panel C shows the distribution of the types of single-nucleotide base-pair changes seen in the candidate variants. Panel D shows the allele fractions (AFs) of candidate somatic variants. The allele fraction was calculated as the number of variant reads divided by the number of variant-plus-reference reads. For variants on the X chromosome in men, this number was divided by 2. Indel denotes insertions and deletions.

Figure 3. Development of Hematologic Cancers

Panel A is a forest plot of the risk of a hematologic cancer among persons with somatic mutations overall and among those with a variant allele fraction (VAF) of 0.10 or higher, as compared with those without mutations, in two cohorts: the Jackson Heart Study (JHS) cohort and the Multiethnic Cohort (MEC). Boxes indicate the hazard ratio for an individual cohort, with horizontal lines indicating 95% confidence intervals, and diamonds represent the results of a fixed-effects meta-analysis of the two cohorts. We estimated hazard ratios by means of competing risks regression, with death as the competing risk. The analysis includes adjudicated cancer information from the MEC and unadjudicated information ascertained through annual interviews with participants in the JHS. For interview data, leukemia, lymphoma, multiple myeloma, blood cancer, and spleen cancer were considered to be hematologic cancers. All models included age groups (<50 years, 50 to 59 years, 60 to 69 years, and ≥70 years), status with respect to type 2 diabetes, and sex as covariates. Panel B shows the cumulative incidence of hematologic cancer in the JHS cohort and the MEC. Curves were generated from competing-risks data, with death as the competing risk. Panel C shows the VAF in persons in whom a hematologic cancer developed and in those in whom a hemato-logic cancer did not develop. The top and bottom of each box represent the first and third quartiles, the horizontal line within the box represents the median, and the I bars represent 1.5 times the interquartile range.

Figure 4. Effect of Somatic Mutations on All-Cause Mortality

Panel A is a forest plot of the risk of death from any cause associated with having a somatic clone, among participants from the JHS cohort, the Ashkenazi cohort of the Longevity Genes Project (UA), the MEC, the Finland–United States Investigation of NIDDM Genetics Study (FUSION) cohort, and the Botnia Study cohort. Boxes indicate the hazard ratio for an individual cohort, with horizontal lines indicating 95% confidence intervals, and diamonds represent the results of a fixed-effects meta-analysis of all cohorts. All models included age groups (<60 years, 60 to 69 years, 70 to 79 years, 80 to 89 years, and 90 years or older), status with respect to type 2 diabetes, and sex as covariates in a Cox proportional-hazards analysis. The Botnia Study includes the Helsinki Siblings with Diabetes cohort and data from the Scania Diabetes Registry. Panel B shows Kaplan–Meier survival curves generated from data from the same cohorts as those included in Panel A. The left panel includes data from participants who were younger than 70 years of age at the time of DNA ascertainment, and the right panel data from participants who were 70 years of age or older. Panel C shows the results of a Cox proportional-hazards analysis of all-cause mortality among persons with and those without mutations, stratified according to normal or high red-cell distribution width (RDW). Boxes indicate the hazard ratio for an individual cohort, with horizontal lines indicating 95% confidence intervals, and diamonds represent the results of a fixed-effects meta-analysis of all cohorts. All models included age groups (<60 years, 60 to 69 years, 70 to 79 years, 80 to 89 years, and 90 years or older), status with respect to type 2 diabetes, and sex as covariates.