Abstract
Clonal hematopoiesis of indeterminate potential (CHIP) is a common risk factor for both hematological malignancies and cardiovascular (CV) diseases. The purpose of this study was to investigate the association between CHIP-related mutations and symptomatic heart failure in patients diagnosed with acute myeloid leukemia (AML). A total of 563 patients with newly-diagnosed AML who underwent DNA sequencing of bone marrow before treatment were retrospectively investigated. Cox proportional hazard regression models and Fine and Gray’s subdistribution hazard regression models were used to assess the association between CHIP-related mutations and symptomatic heart failure (HF). 79.0% patients had at least 1 CHIP-related mutation; the most frequent mutations were DNMT3A, ASXL1 and TET2. Fifty-one patients (9.1%) developed symptomatic HF. The incidence of symptomatic HF was more frequent in patients with DNMT3A mutations (P<0.01), with a 1-year cumulative incidence of symptomatic HF in patients with DNMT3A mutations of 11.4%, compared to 3.9% in wild-type DNMT3A patients (P<0.01). After adjustment for age and anthracyclines dose, DNMT3A mutations remained independently correlated with HF (HR: 2.32, 95% CI: 1.26–4.29, P=0.01). In conclusion, in patients with AML, the presence of DNMT3A mutations was associated with a 2-fold increased risk for symptomatic HF irrespective of age and anthracyclines use.
Keywords: Heart failure, Clonal hematopoiesis of indeterminate potential, acute myeloid leukemia, DNMT3A
Introduction
Patients with acute leukemia have a higher prevalence of symptomatic heart failure (HF) than patients with other cancers1,2. Shared risk factors between acute leukemia and cardiovascular diseases may contribute to the high incidence of symptomatic HF in this specific cohort. Clonal hematopoiesis of indeterminate potential (CHIP) is a common, age-associated phenomenon characterized by any clonal outgrowth of hematopoietic cells in individuals without evidence of hematologic malignancy, dysplasia or cytopenia3. The genetic variants associated with CHIP (for example DNMT3A, TET2, ASXL1) are known driver mutations for hematological malignancies4. In population-based studies, CHIP mutations were associated with an increased risk of a first episode of hospitalized HF, independently of traditional CV risk factors5,6. In patients with chronic heart failure, the presence of mutated TET2 or DNMT3A is correlated with the progression and poor prognosis of HF7,8. Additionally, among patients with acute myeloid leukemia (AML), mutations in CHIP-related genes are associated with a higher risk for a composite outcome of all cardiovascular (CV) events9. However, the association of symptomatic HF in patients with AML and CHIP-related mutations has not been widely explored. Therefore, the objective of the present study was to characterize the relationship of CHIP-related mutations with the occurrence of symptomatic HF in a large contemporary population of patients with AML.
Methods
Identification of patients
All consecutive newly diagnosed AML adult patients (≥18 years of age) with next-generation sequencing of DNA of bone marrow treated at the Penn Medicine system between January 2012 and November 2019 were included. Patients with prior history of HF or without available follow-up record after the first hospital admission were excluded. The patients were monitored based on a recommended protocol, that included quarterly visits throughout the first to third year and biannual visits thereafter, ensuring that events of interest could be successfully captured. Pre-existing CV risk factors and CV diseases were extracted electronically from the Epic electronic medical record (Epic systems Corporation, Verona, WI) using the relevant International Classification of Diseases-9th and/or 10th Revision-Clinical Modification (ICD-9 and/or ICD-10) codes. The confirmation of all the pre-existing diseases or risk factors required the presence of diagnostic codes as well as either relevant pharmacological therapies or objective findings or signs, including laboratory evidence supporting the diagnosis. Anthracyclines dose was calculated based on the following doxorubicin hematologic toxicity equivalence: daunorubicin, 1.0; idarubicin, 5.0 and mitoxantrone, 4.010.
Clinical outcomes
The primary outcome was new-onset symptomatic HF. To identify the occurrence of HF, each chart was reviewed individually. Symptomatic HF was identified as defined by the Standardized Data Collection for Cardiovascular Trials Initiative and the US Food and Drug Administration11. Briefly, HF was diagnosed when 3 or more of the following 4 criteria were met: (1) symptoms of HF; (2) clinical signs of HF; (3) diagnostic testing results consistent with the diagnosis of HF (B-type natriuretic peptide or N-terminal pro–B-type natriuretic peptide, Kerley B-lines or pulmonary edema, pleural effusion, decreased left ventricular ejection fraction [LVEF]), and (4) initiation of new treatment for HF (pharmacological therapies such as diuretic agents and/or mechanical support). One or more symptoms of HF and 2 or more signs on physical examination were necessary for the diagnosis. Symptoms of HF were defined as dyspnea at rest or during exercise, decreased exercise capacity, and symptoms of volume overload. Clinical signs on physical examination were defined as peripheral edema, ascites in the absence of hepatic disease, pulmonary crackles or rales, increased jugular venous pressure, S3 gallop, and significant and rapid weight gain related to fluid retention. Symptomatic HF was adjudicated by 2 independent cardiologists (YK and BL). Disagreement between the 2 readers was adjudicated by a third cardiologist (MSC). HF concomitant with sepsis was not considered a primary outcome.
If patients had no encounters over the preceding 12 months before the end of the study (March 2021), and no date of death was found in the chart, published obituaries were searched. Incomplete follow-up was defined as no encounters within 12 months of the end of the study and no notice of death.
DNA analysis
Genomic DNA was extracted from bone marrow samples before initiation of the leukemia treatment, and fragmented using sonication. PennSeq™ Hematological Malignancies Sequencing Panel (PennSeq™Heme) was used to analyze 116 genes (supplemental 1). Variants are reported according to Human Genome Variation Society nomenclature and classified into the following reported categories: disease-associated variants and variants of uncertain significance. The variant allele fraction (VAF) was defined as the proportion of variant reads detected at a locus.
All oncogenic mutations with variant allele frequencies (VAFs) >5% in the following genes were considered as CHIP-related mutations: DNMT3A, TET2, ASXL1, TP53, JAK2, SRSF2 and SF3B19. Only disease-associated variants were considered as CHIP-related mutations, variants of uncertain significance were excluded. Mutations in these genes are the most common variants among individuals with CHIP12, and are known as driver mutations for hematological malignancies4.
Statistical analysis
Values were expressed as mean±SD or counts (percentages). Follow-up time was presented as median and interquartile range (IQR, [25th −75th percentile]). Differences between patients with HF or non-HF or between patients with or without oncogenic mutations were determined using one-way analysis of variance or Kruskal-Wallis test. Categorical variables were compared using the chi-square test. The primary analysis was the association of CHIP-related mutations with the occurrence of HF. Time-on-study was used as time scale in all survival analyses. Follow-up began at the diagnosis of AML and ended in case of death, event of interest, or the date of last encounter, whichever came first. The cumulative incidence function was used to estimate the incidence of HF, with non-HF-related death as a competing event, and Fine and Gray’s method was applied to determine if there were significant differences between groups. Univariable Cox proportional hazard regression models were used to analyze the association between baseline variables and HF. We developed a multivariable Cox proportional hazard model (Model 1) through the inclusion of variables with a P <0.10 in univariable analysis, and according to their hypothesized clinical relevance, while avoiding collinearity. Because of competing risks, univariable and multivariable Fine and Gray’s subdistribution hazard regression models were also used to determine the association between clinical parameters and HF. The results of Cox proportional hazard models and Fine-Gray subdistribution hazard models are presented as hazard ratios (HRs) with 95% confidence interval (CI).
To understand the interaction between individual CV risk factors (hypertension, diabetes, obesity, hypercholesteremia) or pre-existing CV diseases (atrial fibrillation/flutter, coronary artery disease, cerebrovascular disease, chronic kidney disease and peripheral artery disease), DNMT3A mutation and subsequent HF, we created separate models to evaluate the differential risk of HF in the following patients subgroups: (1) no CV risk factors or prior CV diseases and no DNMT3A mutation (reference group), (2) CV risk factors or prior CV diseases and no DNMT3A mutation, (3) no CV risk factors or prior CV diseases and DNMT3A mutation, (4) CV risk factors or prior CV diseases and DNMT3A mutation. The cumulative incidence of HF for each category was calculated as described above and multivariable Fine-Gray subdistribution hazard models were used to adjust for potential confounders.
Data were analyzed by SPSS version 16.0 (SPSS, Chicago, Illinois) and R version ii386 3.5.0 (Vienna, Austria). A P < 0.05 was considered statistically significant.
Results
Patient enrollment
Five hundred and eighty-two consecutive patients with AML and next-generation sequencing of DNA of bone marrow were identified. After patients with incomplete follow-up or prior history of HF were excluded (n=19), 563 patients (298/52.9% men, age range of the cohort: 19–92 years, IQR [54–71 years]) were included in the study cohort (median follow-up period: 445 days, range: 1–5023 days IQR [150 – 1061 days]).
Clinical characteristics of enrolled patients
The baseline clinical characteristics of the patients are presented in Table 1. Fifty-one patients (9.1%) developed symptomatic HF, including 46 patients (90.2%) with HF with reduced ejection fraction and 5 (9.8%) with HF with preserved ejection fraction. The median time to HF was 121 days (range: 1 to 1596 days, IQR [42–371 days]). Three hundred and forty-one patients (60.6%) died of non-heart failure-related causes. The median time to death was 261 days (range: 1–3118 days, IQR [73–504 days]). Patients developing HF had a higher prevalence of hypertension and hypercholesterolemia (Table 1).
Table 1.
Baseline clinical characteristics of the study cohort.
| All (n=563) | HF (n=51) | Non-HF (n=512) | P Value | |
|---|---|---|---|---|
| Demographics | ||||
| Age, years | 62±14 | 62±14 | 62±14 | 0.96 |
| Age>60y, n(%) | 350 (64.8) | 30 (58.8) | 320 (62.5) | 0.65 |
| Male sex, n(%) | 298 (52.9) | 24 (47.1) | 274 (53.5) | 0.38 |
| BMI, kg/m2 | 28.2±6.6 | 26.8±5.4 | 28.3±6.7 | 0.07 |
| Duration of follow-up,d,[Q1,Q3] | 445,[148,1066] | 448,[239,1019] | 442,[144,1068] | 0.24 |
| Cardiovascular risks and disease history | ||||
| Hypercholesterolemia, n(%) | 139 (24.7) | 20 (39.2) | 119 (23.2) | 0.01 |
| Hypertension, n(%) | 169 (30.0) | 23 (45.1) | 146 (28.5) | 0.01 |
| Diabetes, n(%) | 58 (10.3) | 6 (11.8) | 52 (10.2) | 0.43 |
| Obesity, n(%) | 160 (28.4) | 13 (25.5) | 147 (28.7) | 0.75 |
| Current/previous | 215 (38.2) | 23 (451.) | 192 (37.5) | 0.53 |
| smoker,n(%) | ||||
| ≥2 CV risk factors*, n(%) | 148 (26.3) | 19 (37.3) | 129 (25.2) | 0.07 |
| Coronary heart disease, n(%) | 66 (11.7) | 10 (19.6) | 56 (10.4) | 0.06 |
| Atrial fibrillation/flutter, n(%) | 37 (6.6) | 2 (3.9) | 35 (6.8) | 0.33 |
| Peripheral artery disease, n(%) | 32 (5.7) | 3 (5.9) | 29 (5.7) | 0.57 |
| All | HF | Non-HF | P | |
| Chronic kidney disease, n(%) | 18 (3.2) | 2 (3.9) | 16 (3.1) | 0.50 |
| Cerebrovascular disease, n(%) | 36 (6.4) | 4 (7.8) | 32 (6.3) | 0.42 |
| DVT/pulmonary embolism, n(%) | 29 (5.2) | 1 (2.0) | 28 (5.5) | 0.24 |
| Pre-existing CV diseases#, n (%) | 130 (23.1) | 14 (27.5) | 116 (22.7) | 0.27 |
| Cardiovascular medicine | ||||
| Beta-blockers, n(%) | 60 (10.7) | 12 (23.5) | 48 (9.4) | <0.01 |
| ACEI, n(%) | 60 (10.7) | 7 (13.7) | 53 (10.4) | 0.29 |
| ARBs, n(%) | 53 (9.4) | 4 (7.8) | 49 (9.6) | 0.46 |
| Aspirin, n(%) | 138 (24.5) | 11 (21.6) | 127 (24.8) | 0.38 |
| Anticoagulants, n(%) | 53 (9.4) | 2 (3.9) | 51 (10.0) | 0.12 |
| Statins, n(%) | 132 (23.4) | 13 (25.5) | 119 (23.2) | 0.42 |
| Cancer related treatment | ||||
| Anthracycline, n(%) | 481 (85.4) | 47 (92.2) | 434 (84.8) | 0.11 |
| Anthracycline dose, mg/m2, [Q1,Q3] | 180,[177,300] | 255,[180,330] | 180,[173,300] | 0.20 |
| Anthracycline dose >250mg/m2, n(%) | 164 (29.1) | 19 (37.3) | 145 (28.3) | 0.06 |
BMI: body mass index; CV: cardiovascular; DVT: deep venous thrombosis; ACEI: angiotensin-converting enzyme inhibitor; ARB: angiotensin II receptor blocker;
CV risk factors include obesity, hypertension, hypercholesterolemia and diabetes;
CV diseases include coronary artery disease, atrial fibrillation/flutter, cerebrovascular disease, and peripheral artery disease; P value: compared between patients with and with no HF.
CHIP-related gene mutations
Four hundred and forty-five patients (79.0%) had at least one CHIP-related mutation and 197 patients (35.0%) had more than 1 CHIP-related mutations. Patients with CHIP-related mutations were older (64±13y vs 55±16y, P<0.01), and had a higher cumulative incidence of death over the total duration of follow-up (70.1% vs 54.5%, P<0.01) (supplemental Table 1). The cumulative incidence of death in patients with CHIP-related mutations was higher, with a 1-year cumulative incidence of 41.7%, compared with 24.2% in patients with no CHIP-related mutations (P<0.01). There was no difference in the cumulative incidence of HF between patients with and with no CHIP-related mutations (P=0.31), or between patients with 1 and multiple CHIP-related mutations (P=0.47). There was no difference in the cumulative incidence of death between individuals with one or with multiple mutations (P=0.09). DNMT3A (36.1%), ASXL1 (24.0%) and TET2 (22.2%) were the most common mutated genes (Table 2). Patients with DNMT3A mutations were older, more likely to be treated with anthracyclines, and to receive higher dose of anthracyclines than patients without the DNMT3A mutation (Table 3). The median VAF and first to third quartiles of DNMT3A, TET2 and ASXL1 were 42.1% (26.3% to 45.8%), 44.6% (30.3% to 48.3%) and 40.6% (25.2% to 45.4%), respectively.
Table 2.
Distribution of clonal hematopoiesis of indeterminate potential (CHIP)-related mutations.
| (n=563) | (n=51) | (n=512) | Value | |
|---|---|---|---|---|
| DNMT3A, n(%) | 203 (36.1) | 28 (54.9) | 175 (34.2) | <0.01* |
| TET2, n(%) | 125 (22.2) | 10 (19.6) | 115 (22.5) | 0.73 |
| ASXL1, n(%) | 135 (24.0) | 11 (21.6) | 124 (24.2) | 0.73 |
| JAK2, n(%) | 37 (6.6) | 3 (5.9) | 34 (6.6) | 1.00 |
| TP53, n(%) | 116 (20.6) | 10 (19.6) | 106 (20.7) | 1.00 |
| SF3B1, n(%) | 22 (9.7) | 1(2.0) | 21(4.1) | 0.71 |
| SRSF2, n(%) | 57(10.1) | 3(5.9) | 54(10.5) | 0.46 |
| Presence of CHIP-related mutation, n(%) | 445(79.0) | 45(88.2) | 400(78.1) | 0.11 |
| Presence of ≥2 CHIP-related mutations, n(%) | 197(35.0) | 18(35.3) | 179(35.0) | 1.00 |
CHIP: clonal hematopoiesis of indeterminate potential; P value: compared between patients with and without HF;
The p value corrected by Bonferroni adjustment is 0.021.
Table 3.
Baseline clinical characteristics of patients with and without DNMT3A mutations
| Non-DNMT3A (n=360) | DNMT3A (n=203) | P Value | |
|---|---|---|---|
| Demographics | |||
| Age (y) | 61±15 | 65±13 | <0.01 |
| Age >60y, n(%) | 213 (59.2) | 137 (67.5) | 0.06 |
| Male sex, n(%) | 209 (58.1) | 89 (43.4) | <0.01 |
| BMI (kg/m2) | 28.7±6.9 | 27.2±5.8 | 0.01 |
| Duration of follow-up, d,[Q1,Q3] | 423,[144,1099] | 483,[171,980] | 0.97 |
| Cardiovascular risks and disease history | |||
| Hypercholesterolemia, n(%) | 90 (25.0) | 49 (24.1) | 0.45 |
| Hypertension, n(%) | 118 (32.8) | 51 (25.1) | 0.04 |
| Diabetes, n(%) | 43 (11.9) | 15 (7.4) | 0.06 |
| Obesity, n(%) | 109 (30.3) | 51 (25.1) | 0.11 |
| Current/previous smoker, n(%) | 133 (36.9) | 82 (40.4) | 0.36 |
| ≥2 CV risk factors*, n(%) | 103 (28.6) | 45 (22.2) | 0.06 |
| Coronary heart disease, n(%) | 42 (11.7) | 24 (11.8) | 0.53 |
| Atrial fibrillation/flutter, n(%) | 31 (8.6) | 6 (3.0) | 0.01 |
| Peripheral artery disease, n(%) | 23 (6.4) | 9 (4.4) | 0.22 |
| Chronic kidney disease, n(%) | 14 (3.9) | 4 (2.0) | 0.16 |
| Cerebrovascular disease, n(%) | 25 (6.9) | 11 (5.4) | 0.30 |
| DVT/pulmonary embolism, n(%) | 20 (5.6) | 9 (4.4) | 0.36 |
| Pre-existing CV diseases#, n(%) | 89 (24.7) | 41 (20.2) | 0.13 |
| Chemotherapy | |||
| With Anthracycline, n(%) | 279 (77.5) | 202 (99.5) | <0.01 |
| Anthracycline dose, mg/m2,[Q1,Q3] | 180,[134,276] | 194,[180,340] | <0.01 |
| Anthracycline >250mg/m2, n(%) | 103 (28.6) | 62 (30.5) | 0.05 |
| Outcome | |||
| Heart failure, n(%) | 23 (6.4) | 28 (13.8) | <0.01 |
| Time to heart failure, d,[Q1,Q3] | 414,[104,917] | 401,[141,1083] | 0.40 |
| Death, n(%) | 247 (68.6) | 130 (64.0) | 0.16 |
| Time to death, d,[Q1,Q3] | 271,[74,484] | 277,[83,546] | 0.64 |
BMI: body mass index; CV: cardiovascular; DVT: deep venous thrombosis;
CV risk factors include obesity, hypertension, hypercholesterolemia and diabetes;
CV diseases include coronary artery disease, atrial fibrillation/flutter, cerebrovascular disease, and peripheral artery disease
Heart failure and CHIP-related gene mutations
The incidence of symptomatic HF was more frequent in patients with DNMT3A mutations; at 1 year, the cumulative incidence of symptomatic HF in patients with DNMT3A mutations was 11.4%, compared to 3.9% in wild-type DNMT3A patients (P<0.01) (Figure 1).
Figure 1:
Cumulative incidence of heart failure in patients with and without DNMT3A mutation, with non-HF-related death as competing risk factor
Univariable Cox proportional hazard analysis and Fine and Gray’s subdistribution hazard regression analysis demonstrated that CV risk factors, including hypertension and hypercholesterolemia, previous coronary heart disease, and DNMT3A mutations were associated with symptomatic HF (Tables 4 and 5). However, the VAF of DNMT3A mutations did not correlate with HF (P=0.34, 95% CI: 0.96–1.01). A total of 63 patients (11.2%) with missing variables were not included in the multivariable analysis. There was no difference in baseline characteristics between patients included and not included in the multivariable analysis (supplemental Table 2). After adjustment of age and anthracyclines doses, the presence of DNMT3A mutations remained significantly associated with HF (Tables 4 and 5).
Table 4.
Cox proportional hazard analysis of the baseline characteristics associated with heart failure.
| Univariable | Multivariable regression Model 1 | Multivariable regression Model 2 (age and anthracycline adjusted) | ||||
|---|---|---|---|---|---|---|
| HR (95% CI) | P Value | HR (95% CI) | P Value | HR (95% CI) | P Value | |
| Age | 1.02(1.00–1.04) | 0.06 | 1.01(0.99–1.04) | 0.38 | ||
| Hypercholesterolemia | 2.36(1.33–4.19) | <0.01 | ||||
| Hypertension | 2.53(1.44–4.43) | <0.01 | ||||
| ≥2 CV risk factors* | 2.17(1.22–3.87) | 0.01 | 2.33(1.30–4.18) | <0.01 | 2.16(1.18–3.96) | 0.01 |
| Coronary heart disease | 2.69(1.33–5.42) | 0.01 | 2.02(0.96–4.25) | 0.06 | 1.95(0.92–4.15) | 0.08 |
| Anthracycline dose | 1.00(1.00–1.00) | 0.83 | 1.14(0.37–3.46) | 0.82 | ||
| DNMT3A mutations | 2.38(1.36–4.16) | <0.01# | 2.50(1.42–4.18) | <0.01 | 2.32(1.26–4.29) | 0.01 |
CV risk factors include obesity, hypertension, hypercholesterolemia and diabetes.
The p value corrected by Bonferroni adjustment is 0.014
Table 5.
Fine and Gray’s subdistribution hazard regression (non-cardiac death as competing risk) of the baseline characteristics associated with heart failure.
| Univariable | Multivariable regression Model 1 | Multivariable regression Model 2 (age and anthracycline adjusted) | ||||
|---|---|---|---|---|---|---|
| HR (95% CI) | P Value | HR (95% CI) | P Value | HR (95% CI) | P Value | |
| Age | 1.00(0.98–1.02) | 0.87 | 0.99(0.97–1.01) | 0.39 | ||
| Hypercholesterolemia | 2.04(1.17–3.57) | 0.01 | ||||
| Hypertension | 2.03(1.18–3.51) | 0.01 | ||||
| ≥2 CV risk factors* | 1.74(0.99–3.05) | 0.05 | 0.73(0.91–3.30) | 0.10 | 1.84(0.97–3.50) | 0.06 |
| Coronary heart disease | 1.94(0.98–3.86) | 0.06 | 1.61(0.75–3.46) | 0.22 | 1.74(0.79–3.83) | 0.17 |
| Anthracycline dose | 1.00(0.99–1.00) | 0.40 | 1.41(0.45–4.37) | 0.56 | ||
| DNMT3A | 2.33(1.35–4.02) | <0.01# | 2.50(1.41–4.44) | <0.01 | 1.99(1.06–3.74) | 0.03 |
CV risk factors include obesity, hypertension, hypercholesterolemia and diabetes;
The p value corrected by Bonferroni adjustment is 0.02.
There were 481 patients treated with anthracyclines (85.4% of all patients), amongst whom 47 (9.8%) developed symptomatic HF. In patients treated with anthracyclines, HF was associated with age (HR: 1.03, 95% CI: 1.00–1.05, P=0.03), history of hypercholesterolemia (HR: 2.36, 95% CI: 1.29–4.31, P=0.01), history of hypertension (HR:2.64, 95% CI: 1.47–4.75, P<0.01), history of coronary heart disease (HR: 3.28, 95% CI: 1.61–6.68, P<0.01), and the presence of DNMT3A mutations (HR: 2.42, 95% CI: 1.34–4.40, P<0.01). After adjustment for age and anthracyclines dose, the presence of DNMT3A mutations (HR: 2.34, 95% CI: 1.23–4.25, P=0.01) and a history of coronary artery disease (HR: 3.10, 95% CI: 1.52–6.30, P<0.01) remained independently correlated with HF.
Heart failure, CV risk factors, pre-existing CV diseases and CHIP-related mutations
There was a statistically significant incremental increase in the 1-year cumulative incidence of HF in patients with both DNMT3A mutation and CV risk factors or pre-existing CV diseases (Table 6). In the multivariable regression models adjusting for age, anthracycline doses and respective cardiovascular risk factors, the highest risk of HF was observed among patients with both DNMT3A mutation and more than one CV risk factors (HR:5.52, 95% CI: 2.50–12.19) followed by patients carrying DNMT3A mutation and hypertension (HR:4.91, 95% CI:2.35–10.29). In addition, after adjusting for age and anthracycline doses, the presence of DNMT3A mutation and a prior history of coronary heart disease increased the risk of HF by 5.5-fold (95% CI:2.27–13.42) (Table 6).
Table 6.
One-year Cumulative Incidence and Risk of Cardiovascular Disease
| 1-year cumulative incidence of HF, % | Unadjusted | Adjusted* | |||
|---|---|---|---|---|---|
| HR (95% CI) | P value | HR (95% CI) | P value | ||
| Model 1 | |||||
| No hypertension | |||||
| No DNMT3A | 3.31 | 1[Reference] | NA | 1[Reference] | NA |
| DNMT3A | 6.62 | 1.46(0.70–3.04) | 0.31 | 1.49(0.70–3.20) | 0.30 |
| Hypertension | |||||
| No DNMT3A | 5.09 | 1.14(0.49–2.66) | 0.77 | 1.02(0.38–2.74) | 0.97 |
| DNMT3A | 25.49 | 5.74(2.84–11.64) | <0.001 | 4.91(2.35–10.29) | <0.001 |
| Model 2 | |||||
| No hypercholesterolemia | |||||
| No DNMT3A | 3.72 | 1[Reference] | NA | 1[Reference] | NA |
| DNMT3A | 6.52 | 1.32(0.65–2.67) | 0.44 | 1.39(0.65–2.95) | 0.39 |
| Hypercholesterolemia | |||||
| No DNMT3A | 4.44 | 0.82(0.31–2.21) | 0.70 | 0.67(0.23–1.93) | 0.46 |
| DNMT3A | 26.53 | 5.52(2.81–10.84) | <0.001 | 4.54(2.09–9.89) | <0.001 |
| Model 3 | |||||
| No obesity | |||||
| No DNMT3A | 3.69 | 1[Reference] | NA | 1[Reference] | NA |
| DNMT3A | 9.88 | 1.95(1.05–3.65) | 0.04 | 2.00(1.05–3.81) | 0.04 |
| Obesity | |||||
| No DNMT3A | 3.99 | 0.64(0.34–1.72) | 0.38 | 0.50(0.18–1.45) | 0.20 |
| DNMT3A | 15.87 | 2.46(1.07–5.66) | 0.03 | 2.38(1.04–5.43) | 0.04 |
| Model 4 | |||||
| No ≥2 CV risk factors# | |||||
| No DNMT3A | 3.51 | 1[Reference] | NA | 1[Reference] | NA |
| DNMT3A | 7.00 | 1.51(0.76–2.99) | 0.24 | 1.50(0.73–3.08) | 0.28 |
| ≥2 CV risk factors | |||||
| No DNMT3A | 4.90 | 0.89(0.35–2.24) | 0.80 | 0.95(0.38–2.35) | 0.91 |
| DNMT3A | 26.67 | 5.31(2.59–10.86) | <0.001 | 5.52(2.50–12.19) | <0.001 |
| Model 5 | |||||
| No prior coronary artery disease | |||||
| No DNMT3A | 2.38 | 1[Reference] | NA | 1[Reference] | NA |
| DNMT3A | 9.52 | 1.99(1.01–3.65) | 0.03 | 1.93(1.05–3.54) | 0.04 |
| Prior coronary artery disease | |||||
| No DNMT3A | 4.10 | 1.16(0.35–3.83) | 0.80 | 1.28(0.37–4.38) | 0.70 |
| DNMT3A | 25.00 | 5.61(2.37–13.26) | <0.001 | 5.51(2.27–13.42) | <0.001 |
| Model 6 | |||||
| No prior CV diseases@ | |||||
| No DNMT3A | 2.27 | 1[Reference] | NA | 1[Reference] | NA |
| DNMT3A | 8.67 | 1.68(0.89–3.17) | 0.11 | 1.61(0.83–3.13) | 0.16 |
| Prior CV diseases | |||||
| No DNMT3A | 4.44 | 0.66(0.23–1.90) | 0.44 | 0.68(0.24–1.93) | 0.47 |
| DNMT3A | 21.95 | 4.21(1.95–9.10) | <0.001 | 4.06(1.84–8.95) | <0.001 |
HF: heart failure; HR: hazard ratio;
All models were adjusted for age, sex and anthracycline doses. Additionally, model 1 was adjusted for hypercholesterolemia, diabetes and obesity; model 2 was adjusted for hypertension, diabetes and obesity; model 3 was adjusted for hypertension, diabetes and hypercholesterolemia;
CV risk factors include obesity, hypertension, hypercholesterolemia and diabetes;
CV diseases include coronary artery disease, atrial fibrillation/flutter, cerebrovascular disease, and peripheral artery disease; In this study cohort, the number of cases of diabetes, atrial fibrillation/flutter, cerebrovascular disease, chronic renal disease and peripheral artery disease was insufficient to stratify the risk of HF of the individual variables.
Discussion
In a retrospective cohort study, patients with AML had a high prevalence of CHIP-related mutations (80.1%). DNMT3A, ASXL1 and TET2 were the most commonly mutated genes. Incidence of symptomatic HF was more frequent in patients with DNMT3A mutations, compared with those with DNMT3A-wild type. The presence of DNMT3A mutations was independently associated with symptomatic HF, regardless of age and anthracyclines use. For patients carrying a DNMT3A mutation, the risk of HF was increased by approximately 5-fold in the presence of hypertension, hypercholesteremia or when a prior history of coronary heart disease was noted.
The mutations of the hematopoietic stem cells that are observed in clonal hematopoiesis are associated with impaired differentiation and increased self-renewal of the cells13. Clonal hematopoiesis of driver gene mutations found in acute leukemia (also defined as clonal hematopoiesis of indeterminate prognosis CHIP) is strongly associated with substantial increases in the risk of developing hematological neoplasia14 with an absolute risk of progression to malignancy of about 0.5–1% per year vs <0.1% in non-CHIP carriers15. In concordance with prior studies16,17, patients with CHIP-related mutations were older and had a higher death rate.
In patients without hematologic malignancies, recent studies demonstrated a connection between CHIP and CV diseases including HF5,15,18–20. Yu et al5 reported a strong association with an increased risk of HF for ASXL1, TET2 and JAK2 mutations than for DNMT3A in the general population. However, DNA sequencing of blood samples in patients without blasts may not adequately capture the correlation between CHIP-related mutations and cardiac events in individuals diagnosed with acute leukemia. In experimental models and in human samples, CHIP-related mutations can be present in AML blasts, where the mutational burden may be very high21. Therefore, the spectrum and burden of somatic mutation in patients with AML might differ from those without hematologic malignancies. Additionally, death from AML may function as a competing risk and limit the occurrence of CV events. Therefore, in the present study, we conducted targeted sequencing on pre-treatment bone marrow samples to determine the association between CHIP-related mutation and symptomatic HF in patients diagnosed with AML.
DNMT3A is a de novo DNA methyltransferase that plays a significant role in epigenetically regulated gene expression and repression22. In our cohort, 36% patients had mutations in DNMT3A, which was consistent with prior studies23. In a model of angiotensin challenge in mice, genome editing of DNMT3A in hematopoietic stem cells resulted in increased cardiac hypertrophy, diminished cardiac function, and greater cardiac fibrosis24. Mast cells from mice that lacked DNMT3A displayed higher levels of interleukin-6 (IL-6), tumor necrosis factor α and IL-13 in response to stimulation with immunoglobulin E25. In patients with ST-segment elevation myocardial infarction, those with DNMT3A/TET2 mutations also showed elevated levels of circulating IL-626. Recently, Dorsheimer et al. reported that patients with pre-existing HF harboring either TET2 or DNMT3A mutations had an increased risk of death or HF hospitalization during a median follow-up of 4.4 years7, a finding that the present study extends to patients with AML and no pre-existing HF.
The presence of DNMT3A mutations in AML portends a poor prognosis23,27. High-dose anthracyclines might overcome the negative impact of DNMT3A mutations28,29, thus patients with DNMT3A mutations are often treated with more intensive chemotherapy and higher anthracycline doses, as confirmed by the present results. Nevertheless, the presence of DNMT3A mutation persisted as an independent association with symptomatic HF after adjustment of age and anthracyclines dose, with a 2.3-fold increased risk of HF.
Rhee et al reported that the highest risks of CV disease were observed among multiple myeloma patients, if they harbored both a CHIP mutation and CV risk factors, such as hypertension, dyslipidemia or diabetes30. In the present study, AML patients with both DNMT3A mutation and hypertension or hypercholesteremia had an approximately 5-fold risk of developing HF, compared with patients without DNMT3A mutation and these CV risk factors. Despite the strong association between CHIP and CV diseases, to our knowledge, no CHIP-targeted interventions for reducing CV disease risk currently exist. However, our results highlighted the significantly increased risk of HF in patients with AML who also have a DNMT3A mutation and modifiable CV risk factors. This finding may support the development of more personalized interventions, such as early screening for these modifiable risk factors, intensive blood pressure control or lipidlowing therapy.
No correlation between the mutation burden (VAF) and the occurrence of HF was observed. A potential hypothesis for this absence of correlation is that DNMT3A mutant macrophages activate wild-type macrophages and CD4+ T cells, which could then promote hypertrophy and fibrosis of cardiac cells as shown experimentally24. The amplitude of the effect of the mutant macrophages on wild-type macrophages and CD4+T cells may be independent of the frequency of the initial mutation.
A previous study9 demonstrated that among patients with AML treated by anthracycline, harboring TP53 mutations increased the risk for developing a CV by approximately 4-fold. In that cohort, approximately 50% (49/101) CV events were venous thromboembolism, and only 36% (37/101) were HF hospitalizations. It has been demonstrated that TP53 mutations are associated with elevated expression of coagulation factor V mRNA31 and increased tissue factor activity32, which might explain the lack of a clear association between TP53 and HF in our cohort.
Study Limitations
This study was retrospective in nature, which may lead to unknown biases. We observed that the presence of CHIP-related mutations tended to be higher in patients with HF. However, our study was not powered to analyze the attributing risks of individual variants of the genes or rare CHIP-related mutations. And we were unable to explore further into the interactions among multiple mutations concerning the onset of heart failure.
Conclusion
In summary, in a large cohort of patients with AML, patients harboring CHIP-related mutations exhibited an elevated mortality rate. The presence of DNMT3A mutations was associated with a 2-fold increased risk for symptomatic HF, irrespective of age and anthracyclines use and dose. These findings suggest that individuals with AML and DNMT3A mutations have a higher incidence of HF than other patients with AML and may be assisted by intensive cardiovascular monitoring and comprehensive management.
Supplementary Material
Acknowledgements:
Marielle Scherrer-Crosbie reports administrative support and article publishing charges were provided by National Heart, Lung, and Blood Institute Grant 1R01HL130539-01. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Footnotes
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Conflicts of Interest: None declared
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