Abstract
Purpose
Clonal hematopoiesis (CH) is associated with cardiovascular disease (CVD), inflammation, and increased mortality. However, its prevalence and clinical impact in patients with cytopenia and chronic kidney disease (CKD) remain unclear.
Methods
We conducted a retrospective cohort study of patients with cytopenia and CKD who underwent targeted sequencing to evaluate the association between CH, CKD progression, and overall mortality.
Results
A total of 67 patients were included (mean age 75.7 ± 10.5 years; 58.2% male). Most patients had myelodysplastic neoplasms (MDS) (79.1%), followed by clonal cytopenia of undetermined significance (CCUS) and idiopathic cytopenia of undetermined significance (ICUS) (14.9%). CH was detected in 53.7% of the patients, most commonly involving TET2 (44.4%), DNMT3A (22.2%), and ASXL1 (22.2%). Over a median follow-up of 43.5 months (interquartile range [IQR] 34.3–79.3), CKD progression occurred in 34.3%. The 5-year cumulative incidence of CKD progression tended to be higher in the CH carriers than in the non-carriers (55.4% vs. 31.4%; log-rank p = 0.066). In multivariable Cox analysis, CH remained independently associated with CKD progression (adjusted hazard ratio [HR] 2.83; 95% confidence intervals [CI] 1.03–7.79; p = 0.044). CKD progression was most frequent in patients with MDS and CH (46%), followed by MDS without CH (30%) and CCUS (16%), with no progression in ICUS. Mortality was higher in CH carriers (50.0% vs. 16.1%; p = 0.004) and remained independently associated with CH (adjusted HR 3.90; 95% CI 1.41–10.83; p = 0.009).
Conclusions
CH is common in cytopenic patients with CKD and is independently associated with an increased risk of CKD progression and mortality. The assessment of CH may improve risk stratification and identify high-risk patients with adverse renal and survival outcomes.
Supplementary Information
The online version contains supplementary material available at 10.1007/s44313-026-00161-2.
Keywords: Clonal hematopoiesis, Chronic kidney disease, Myelodysplastic neoplasms, Glomerular filtration rate decline, CHIP
Introduction
Clonal hematopoiesis (CH) is an age-associated condition characterized by the expansion of hematopoietic stem and progenitor cell clones [1] harboring somatic mutations in the absence of an overt hematologic malignancy. According to the 2022 World Health Organization (WHO) [2] and International Consensus Classification (ICC) [3], CH encompasses CH of indeterminate potential (CHIP), which is defined by the presence of myeloid-associated somatic mutations, typically with a variant allele fraction of ≥ 2%, in individuals without unexplained cytopenia or diagnostic evidence of a myeloid neoplasm. In patients with persistent unexplained cytopenia, idiopathic cytopenia of undetermined significance (ICUS) refers to cytopenia without identifiable clonality or morphologic evidence of a myeloid neoplasm, whereas clonal cytopenia of undetermined significance (CCUS) is characterized by persistent cytopenia together with one or more myeloid-associated somatic mutations, but lacks the morphologic or genetic diagnostic criteria for myelodysplastic neoplasm (MDS). According to the current WHO and ICC classifications, MDS is a clonal myeloid neoplasm characterized by persistent cytopenia accompanied by morphological dysplasia, increased blasts, and/or disease-defining genetic abnormalities. The prevalence of CH increases with advancing age [4–6], affecting 10–20% of individuals > 65 years of age, and most commonly involves mutations in DNMT3A, TET2, and ASXL1 [1]. Accumulating evidence indicates that CH promotes dysregulated inflammatory signaling through altered myeloid cell function, leading to chronic systemic inflammation. This proinflammatory state [7] has been linked to multiple forms of end-organ damage [8], including cardiovascular disease (CVD) [1, 9], heart failure [10–12], diabetes mellitus [13], chronic kidney disease (CKD) [8, 14–17], and chronic obstructive pulmonary disease [18, 19], with increased all-cause mortality [1, 5, 10, 20, 21].
Increasing attention has been focused on the role of CH in kidney diseases [7, 8, 14–17, 22]. Experimental studies have revealed that mutant myeloid cells accelerate renal inflammation and tubulointerstitial fibrosis [8, 17] through infiltration of mutant macrophages. Consistent with these findings, observational studies in both population-based cohorts and CKD populations have reported associations between CH and kidney function decline as well as progression to end-stage kidney disease (ESKD). [7, 8, 14, 16, 17]. CH carriers have a 2.2-fold increased risk of kidney failure compared with non-carriers [16]. CH carriers have been shown to have a significantly increased risk of kidney failure compared to non-carriers, with emerging evidence revealing heterogeneity in renal risk according to CH genotype, particularly among non-DNMT3A mutations. [8, 22].
Despite these advances, the clinical impact of CH in patients with cytopenia and CKD remains limited. Patients with persistent cytopenia frequently harbor a spectrum of clonal myeloid disorders, including ICUS, CCUS, and MDS, which may exhibit greater clonal complexity and inflammatory activation. Therefore, in this study, we investigated the prevalence and prognostic significance of detectable clonal hematopoietic mutations in a cohort of patients with cytopenic CKD, including individuals with ICUS, CCUS, and MDS. The association between clonal hematopoietic mutations, CKD progression, and overall mortality were evaluated to expand the current evidence to this high-risk clinical population.
Methods
Study design and oversight
This study includes participants ≥ 40 years of age with persistent cytopenia at least 4 months (Hb < 13 g/dL (men), < 12 g/dL (women); ANC < 1,800/mm3; platelets < 150,000/mm3) and CKD (estimated glomerular filtration rate [eGFR] < 60 ml/min/1.73 m2) at King Chulalongkorn Memorial Hospital (KCMH) in Bangkok, Thailand between January 1, 2015, and July 31, 2025, were enrolled in the study. Patients with incomplete clinical data or acute kidney injury (AKI) superimposed on patients with CKD were excluded. In cases with AKI, kidney function was reassessed after recovery to ensure accurate classification of baseline CKD. Clinical data, including age, sex, diagnosis, underlying disease, body mass index (BMI), Thai atherosclerotic cardiovascular disease (ASCVD) risk [23], and laboratory values, such as complete blood count (CBC), cytogenetics, next-generation sequencing (NGS) results, serum creatinine levels, and eGFR, were retrieved from medical records. Conventional G-banding cytogenetic analysis was performed on the bone marrow (BM) aspirate specimens according to standard laboratory procedures. The BM images were reviewed by an expert hematopathologist. Dysplasia was defined in accordance with the 2016 World Health Organization criteria [24].
Targeted NGS
Genomic DNA was isolated from BM mononuclear cells using a Gentra Puregene Blood Kit (Qiagen, Hilden, Germany). Sequencing libraries were prepared with the Ion Chef™ System following the manufacturer's instructions, achieving a mean sequencing depth of approximately 1,000 × . NGS was then performed using a customized 40-gene myeloid panel on the Ion S5 platform (Thermo Fisher Scientific, Waltham, MA, USA) (supplementary table S1).
Raw sequencing data were processed using Torrent Suite™ software, and variants were identified and annotated with Ion Reporter™ Oncomine™ software (Thermo Fisher Scientific). Only somatic variants identified by the Oncomine™ somatic variant-calling pipeline were retained for analysis. Variants with a variant allele frequency (VAF) < 5% were excluded to minimize false-positive calls.
CH state definition
For the purposes of this study, CH was defined as the presence of at least one somatic mutation in myeloid malignancy–associated genes with a VAF ≥ 5%. As this study included patients across the spectrum of clonal cytopaenic disorders, including CCUS and MDS, this operational definition was applied, irrespective of the underlying diagnostic category, to evaluate the prognostic impact of detectable clonal hematopoietic mutations. Accordingly, patients with MDS harboring qualifying somatic mutations were classified as having MDS with CH, whereas those without detectable mutations in the targeted sequencing panel were classified as having MDS without CH. This operational definition should not be interpreted as equating MDS with CHIP or CCUS as defined by the current WHO 2022 and ICC classifications.
Clinical outcomes
CKD progression was defined according to the 2012 Kidney Disease: Improving Global Outcomes (KDIGO) guidelines as a sustained decline in the eGFR of ≥ 25% from baseline or progression to ESKD requiring kidney replacement therapy. To minimize misclassification due to biological variations or acute illness, CKD progression was assessed using serial outpatient serum creatinine measurements and confirmed by measurements, with the decline in eGFR confirmed by a subsequent measurement obtained at least 3 months apart. [25]. Secondary outcomes included the rate of eGFR deterioration over time, common mutations, and overall mortality rate. Mortality outcomes were collected at the last follow-up at the KCMH. The study protocol was reviewed and approved by the Institutional Review Board of Faculty of Medicine, Chulalongkorn University (approval number 0633/67). This study was conducted in accordance with the principles of the Declaration of Helsinki.
Statistical analysis
Continuous variables are presented as mean ± standard deviation (SD) or median with interquartile range (IQR), as appropriate, and categorical variables as counts and percentages. Group comparisons between patients with and without CH were performed using the independent samples t test or Mann–Whitney U test for continuous variables and the chi-square or Fisher’s exact test for categorical variables, as appropriate. Time to CKD progression was analyzed using the Kaplan–Meier method with group comparisons using the log-rank test, and five-year cumulative incidence rates were estimated with 95% confidence intervals (CIs) to represent the primary outcome. Associations between CH and CKD progression were assessed using the Cox proportional hazards regression analysis. Variables with p < 0.1 in univariable analyses were included in multivariable models, which were adjusted for sex, comorbidities, ASCVD risk, cytopenia series, and baseline eGFR. Longitudinal eGFR trajectories were analyzed using linear mixed-effects models with an unstructured covariance matrix incorporating fixed effects for group, time, and their interaction. Missing longitudinal data were handled using multiple imputations with chained equations (MICE). Overall survival was analyzed using Kaplan–Meier and Cox proportional hazards models with adjustment for age, relevant comorbidities, and baseline eGFR. All tests were two-sided, and statistical significance wat set at p < 0.05. All statistical analyses were performed using IBM SPSS Statistics software version 30 (IBM Corp., Armonk, NY, USA).
Results
Baseline demographic and clinical characteristics
A total of 67 patients with persistent cytopenia and CKD were included in this study. The mean age was 75.7 ± 10.5 years. Among these patients, 58.2% were male. Most patients were diagnosed with MDS (79.1%), followed by CCUS/ICUS (14.9%), and other diagnoses (6.0%). Cytogenetic abnormalities were detected in 25.4% of patients. The cohort had a high burden of cardiovascular risk factors, with 59.7% of patients having hypertension, 43.3% having CVD, 38.8% having diabetes mellitus, and 35.8% having dyslipidemia (DLP). Most patients (73.1%) were classified as having high ASCVD risk.
Baseline kidney function showed moderate CKD, with a mean serum creatinine of 1.39 ± 0.5 mg/dL and mean eGFR of 48.1 ± 12.0 mL/min/1.73 m2. Hematologic parameters revealed significant cytopenias, with a mean hemoglobin of 9.0 ± 1.9 g/dL, median absolute neutrophil count of 2500 (1320–4350) cells/mm3, and Platelet 166 × 103 (89–278 × 103) cells/mm3. The baseline demographic and clinical characteristics stratified by CH status are summarized in Table 1.
Table 1.
Demographic and clinical characteristics of patients. (n = 67)
| Characteristics | All Patients (n = 67) |
Mutation | p-value | |
|---|---|---|---|---|
| CH (n = 36) | No CH (n = 31) | |||
| All patients | 67 (100) | 36 (53.7) | 31 (46.3) | |
| Sex | 0.044 | |||
| Male | 39 (58.2) | 25 (69.4) | 14 (45.2) | |
| Female | 28 (41.8) | 11 (30.6) | 17 (54.8) | |
| Age (years) | 75.73 ± 10.54 | 78.64 ± 7.82 | 72.35 ± 12.29 | 0.014 |
| BMI (kg/m2) | 22.26 ± 3.22 | 22.55 ± 3.42 | 21.92 ± 3.00 | 0.432 |
| Comorbidities | ||||
| Hypertension | 40 (59.7) | 22 (61.1) | 18 (58.1) | 0.800 |
| Cardiovascular disease | 29 (43.3) | 13 (36.1) | 16 (51.6) | 0.202 |
| Diabetes mellitus | 26 (38.8) | 13 (36.1) | 13 (41.9) | 0.626 |
| Dyslipidemia | 24 (35.8) | 12 (33.3) | 12 (38.7) | 0.647 |
| Others | 18 (26.9) | 10 (27.8) | 8 (25.8) | 0.856 |
| Thai ASCVD risk | 18.19 (26.36—> 30) | 26.99 (17.85—> 30) | 24.89 (20.42—> 30) | 0.918 |
| Borderline | 1 (1.5) | 1 (2.8) | 0 (0.0) | |
| Moderate | 17 (25.4) | 10 (27.8) | 7 (22.6) | |
| High | 49 (73.1) | 25 (69.4) | 24 (77.4) | |
| Diagnosis | 0.620 | |||
| MDS | 53 (79.1) | 30 (83.3) | 23 (74.2) | |
| CCUS/ICUS | 10 (14.9) | 4 (11.1) | 6 (19.4) | |
| Others | 4 (6.0) | 2 (5.6) | 2 (6.4) | |
| Cytogenetics | 0.523 | |||
| Normal | 50 (74.6) | 28 (77.8) | 22 (71.0) | |
| Abnormal | 17 (25.4) | 8 (22.2) | 9 (29.0) | |
| CBC parameters | ||||
| Hb (g/dL) | 9.06 ± 1.88 | 8.76 ± 2.00 | 9.41 ± 1.70 | 0.159 |
| WBC (cells/mm3) | 5080 (3000—7120) | 4395 (2530—6895) | 5790 (3845—7185) | 0.127 |
| ANC | 2500 (1320—4350) | 2090 (970—3430) | 3050 (2010—4890) | 0.067 |
| Platelet (× 103 cells/mm3) | 166 (89—278) | 152 (86.5—283.5) | 194 (114—256.5) | 0.655 |
| Hematologic parameters | ||||
| Anemia, n (%) | 27 (40.3%) | 11 (30.5%) | 16 (51.6%) | 0.089 |
| Neutropenia, n (%) | 1 (1.5%) | 0 (0.0%) | 1 (3.2%) | 0.463 |
| Thrombocytopenia, n (%) | 2 (3.0%) | 1 (2.8%) | 1 (3.2%) | 1.000 |
| Bicytopenia, n (%) | 25 (37.3%) | 14 (38.9%) | 11 (35.5%) | 0.805 |
| Pancytopenia, n (%) | 12 (17.9%) | 10 (27.8%) | 2 (6.5%) | 0.028 |
| Kidney function parameters | ||||
| Creatinine (mg/dL) | 1.39 ± 0.52 | 1.41 ± 0.55 | 1.35 ± 0.49 | 0.634 |
| eGFR (mL/min/1.73m2) | 48.12 ± 12.02 | 47.92 ± 12.38 | 48.35 ± 11.79 | 0.883 |
| CKD stage | 0.186 | |||
| G3a (eGFR 45–59) | 50 (74.7%) | 28 (77.8%) | 22 (70.9%) | |
| G3b (eGFR 30–44) | 8 (11.9%) | 2 (5.6%) | 6 (19.4%) | |
| G4a (eGFR 15–29) | 9 (13.4%) | 6 (16.7%) | 3 (9.7%) | |
Data are presented as number (%), mean ± standard deviation or median (interquartile range)
P-value corresponds to independent samples t-test, Mann–Whitney U test, Chi-square test or Fisher’s exact test
Prevalence and spectrum of CH
CH–associated gene mutations were identified in 36 of the 67 patients (53.7%) (Fig. 1). The most frequently mutated genes were TET2 (44.4%), followed by DNMT3A (22.2%), ASXL1 (22.2%), SF3B1 (16.7%), whereas the least frequently mutated genes included SRSF2 (11.1%), IDH1/2 (11.1%), TP53 (8.3%), and STAG2 (2.8%). Among CH carriers, 20 (55.6%) harbored multiple mutations, indicating a substantial degree of clonal complexity in this population.
Fig. 1.
Clonal architecture and prevalence of CH Distribution of clonal hematopoiesis–associated gene mutations in the study cohort (n = 36). TET2 was the most frequently mutated gene, followed by DNMT3A and ASXL1
The prevalence of CH increased with age, from 14.3% in patients aged < 60 years to 61.3% in those aged ≥ 80 years (Fig. 2A). The spectrum of gene mutations according to the age group is shown in (Fig. 2B). When stratified by CH status, patients with CH were significantly older than those without mutations (78.6 ± 7.8 vs. 72.4 ± 12.3 years; p = 0.014) and were more frequently male (69.4% vs. 45.2%; p = 0.044). BMI, cardiovascular risk factors, diagnosis categories, cytogenetic abnormalities, baseline kidney function, and other hematological parameters were comparable between the groups. Detailed comparisons between groups are presented in Table 1.
Fig. 2.
A Age-specific prevalence of clonal hematopoiesis among study participants. B Distribution of gene mutations detected in patients with clonal hematopoiesis
Association between CH and CKD progression
During a median follow-up of 43.5 months (IQR, 34.3–79.3), CKD progression occurred in 23 of the 67 patients (34.3%). The baseline kidney function was consistent with predominantly moderate CKD, with most patients classified as having stage G3a CKD at the time of study entry (Table 1). During follow-up, five patients progressed to ESKD requiring kidney replacement therapy, including four patients with CH (11.1%) and one patient without detectable clonal mutations (3.2%). The 5-year cumulative incidence of CKD progression tended to be higher among patients with CH (55.4% [95% CI, 35.1–78.0] vs. 31.4% [95% CI, 14.0–61.1]; Fig. 3A), showing a trend toward an increased risk, although the difference was not statistically significant (log-rank p = 0.066). In univariable Cox regression analysis, CH was associated with a 2.10-fold increased risk of CKD progression (hazard ratio [HR] 2.10; 95% CI 0.89–4.99; p = 0.092). After adjustment for sex, CVD, ASCVD risk, cytopenia status, and baseline eGFR, CH remained independently associated with CKD progression (adjusted HR 2.83; 95% CI 1.03–7.79; p = 0.044) (Table 2). To further explore this association, CKD progression was analyzed across the diagnostic subgroups (Fig. 3B and Supplementary Table S2). When stratified by the underlying hematologic condition, CKD progression was most frequently observed in patients with MDS harboring CH (46%, 14/30), followed by MDS without CH (30%, 7/23) and CCUS (16%, 1/6). In contrast, none of the patients with ICUS experienced CKD progression (0%, 0/8). These findings revealed a gradient in the frequency of CKD progression across the diagnostic subgroups, with the highest proportion among patients with MDS and CH.
Fig. 3.
A Kaplan–Meier estimates of CKD progression stratified by CH status. Shaded areas represent 95% confidence intervals. B Frequency of CKD progression according to diagnostic subgroup
Table 2.
Multivariable analyses for association between CH and kidney function decline. (n = 67)
| Factors | Univariable analysis | Multivariable analysis | Forest | ||
|---|---|---|---|---|---|
| Unadjusted HR† (95% CI) | p-value | Adjusted HR‡ (95% CI) | p-value | plot | |
| Mutation | |||||
| Yes | 2.10 (0.89–4.99) | 0.092 | 2.83 (1.03–7.79) | 0.044 | ──●──── |
| No | 1.00 | Reference | 1.00 | Reference | |
| Sex | |||||
| Male | 2.90 (1.13–7.44) | 0.027 | 2.41 (0.82–7.10) | 0.109 | ──●──── |
| Female | 1.00 | Reference | 1.00 | Reference | |
| Age (per 1 year increment) | 1.00 (0.96–1.04) | 0.928 | — | — | |
| Diagnosis | |||||
| MDS | 0.63 (0.14–2.77) | 0.537 | — | — | |
| CCUS / ICUS | 0.89 (0.16–4.97) | 0.897 | — | — | |
| Others | 1.00 | Reference | — | — | |
| Comorbidities | |||||
| Hypertension | 1.88 (0.74–4.82) | 0.187 | — | — | |
| Cardiovascular disease | 2.49 (1.01–6.14) | 0.047 | 1.96 (0.72–5.32) | 0.187 | ──●── |
| Diabetes mellitus | 1.92 (0.83–4.41) | 0.125 | — | — | |
| Dyslipidemia | 0.65 (0.27–1.57) | 0.342 | — | — | |
| Others | 1.33 (0.54–3.24) | 0.534 | — | — | |
| ASCVD risk | |||||
| Borderline / Moderate | 1.00 | Reference | 1.00 | Reference | |
| High | 2.86 (0.85–9.59) | 0.088 | 2.28 (0.64–8.10) | 0.201 | ───●─── |
| Cytogenetics | |||||
| Normal | 1.00 | Reference | — | — | |
| Abnormal | 1.94 (0.79–4.77) | 0.151 | — | — | |
| eGFR (per 10 mL/min/ 1.73m² increment) | 0.64 (0.44–0.92) | 0.016 | 0.62 (0.41–0.94) | 0.025 | ──●─ |
Abbreviations: CI confidence interval, HR Hazard ratio, NA data not applicable
Variable was included in multivariable model due to have p-value < 0.100 in univariable analysis
†Unadjusted hazard ratio estimated by Cox proportional hazards model
‡Adjusted hazard ratio estimated by Cox proportional hazards model adjusting for sex, cardiovascular disease, ASCVD risk, and eGFR
Association between CH and mortality
During the study period, mortality occurred in 50.0% of the patients with CH compared with 16.1% of patients without CH (p = 0.004). Kaplan–Meier survival analysis showed significantly inferior survival among CH carriers, with a 5-year overall survival rate of 41.9%, compared to 74.6% in patients without CH (log-rank p = 0.001) (Fig. 4).
Fig. 4.
Kaplan–Meier overall survival curves stratified by clonal hematopoiesis (CH) status
In univariable Cox regression analysis, CH was associated with a markedly increased risk of mortality (HR 4.43; 95% CI 1.64–11.99; p = 0.003). After multivariable adjustment for age, DLP, ASCVD risk, and baseline eGFR, CH remained independently associated with mortality (adjusted HR 3.90; 95% CI 1.41–10.83; p = 0.009) (Table 3). The distribution of causes of death according to the CH status is shown in Supplementary Figure S1. Infection was the leading cause of death in both groups, followed by CVD, and kidney-related causes (uremia/ESKD). Deaths related to hematological disease progression and other causes occurred less frequently.
Table 3.
Multivariable analyses for association between CH and mortality. (n = 67)
| Factors | Univariable analysis | Multivariable analysis | Forest | ||
|---|---|---|---|---|---|
| Unadjusted HR† (95% CI) | p-value | Adjusted HR‡ (95% CI) | p-value | plot | |
| Mutation | |||||
| Yes | 4.43 (1.64–11.99) | 0.003 | 3.90 (1.41–10.83) | 0.009 | ──●── |
| No | 1.00 | Reference | 1.00 | Reference | |
| Sex | |||||
| Male | 1.17 (0.51–2.70) | 0.705 | — | — | |
| Female | 1.00 | Reference | 1.00 | Reference | |
| Age (per 1 year increment) | 1.06 (1.01–1.11 | 0.014 | 1.04 (0.99–1.10) | 0.116 | ─●─ |
| Diagnosis | |||||
| MDS | 1.32 (0.28–6.18) | 0.723 | — | — | |
| CCUS / ICUS | 0.87 (0.14–5.40) | 0.880 | — | — | |
| Others | 1.00 | Reference | — | — | |
| Comorbidities | |||||
| Hypertension | 1.80 (0.74–4.39) | 0.194 | — | — | |
| Cardiovascular disease | 1.80 (0.74–4.39) | 0.254 | — | — | |
| Diabetes mellitus | 1.61 (0.71–3.66) | 0.595 | — | — | |
| Dyslipidemia | 0.35 (0.12–1.04) | 0.060 | 0.41 (0.13–1.32) | 0.137 | ──●──── |
| Others | 0.71 (0.26–1.91) | 0.499 | — | — | |
| ASCVD risk | |||||
| Borderline / Moderate | 1.00 | Reference | 1.00 | Reference | |
| High | 1.28 (0.52–3.17) | 0.591 | 2.28 (0.64–8.10) | 0.201 | ───●── |
| Cytogenetics | |||||
| Normal | 1.00 | Reference | — | — | |
| Abnormal | 1.42 (0.58–3.47) | 0.437 | — | — | |
| eGFR (per 10 mL/min/ 1.73m² increment) | 0.73 (0.52–1.01) | 0.059 | 0.68 (0.48–0.97) | 0.033 | ─●── |
Abbreviations: CI confidence interval, HR Hazard ratio, NA data not applicable
Variable was included in multivariable model due to have p-value < 0.100 in univariable analysis
†Unadjusted hazard ratio estimated by Cox proportional hazards model
‡Adjusted hazard ratio estimated by Cox proportional hazards model adjusting for age, DLP, ASCVD risk, and eGFR
Discussion
CH is increasingly being recognized as a systemic condition associated with chronic inflammation and vascular dysfunction [4, 19, 26]. CH stem cells can produce elevated levels of proinflammatory cytokines, leading to endothelial injury in CVD and kidney diseases [4, 14, 27]. Sustained inflammatory signaling in the kidneys may promote microvascular injury, interstitial fibrosis, and progressive decline in renal function [8, 14, 16, 22].
In this study, we evaluated the prevalence and clinical impact of clonal hematopoietic mutations in patients with cytopenia and CKD. As most of the cohort consisted of patients with established MDS, CH was used as an operational molecular descriptor instead of as a strict diagnostic entity. Under the current WHO 2022 and ICC classifications, MDS represents an overt clonal myeloid neoplasm instead of a CHIP. Therefore, our findings should not be interpreted as reflecting the effects of CHIP alone, but instead as showing the prognostic impact of clonal hematopoietic mutations across the spectrum of clonal cytopenic disorders, including ICUS, CCUS, and MDS. The observed gradient of renal risk from ICUS to CCUS, MDS without detectable mutations, and MDS with mutations further supports the concept that increasing clonal burden is associated with adverse renal outcomes.
CH was detected in more than half of the cohort, with CHIP-like mutations in TET2, DNMT3A, and ASXL1 being the most frequently mutated genes. [1, 8, 9, 14, 17, 22] and reflects the canonical pattern of age-related CH [1, 14]. Notably, CH was independently associated with CKD progression and mortality even after adjusting for baseline kidney function and comorbid conditions. Although the difference in CKD progression by Kaplan–Meier analysis revealed only a trend toward statistical significance, the consistent association observed in the multivariable models supports the potential pathogenic role of CH in renal disease progression.
Notably, we observed an apparent gradient in CKD progression across cytopaenia subgroups ranging from ICUS to CCUS, MDS without CH, and MDS with CH, revealing a gradient of renal risk across clonal cytopaenic states. A particularly high rate of CKD progression was observed in the patients with MDS and CH (Fig. 3B and Supplementary Table S1). Although this pattern shows increasing renal risk with progressive clonal disease states, the analysis was descriptive, and no formal trend analysis was performed. However, this raises the possibility of a synergistic effect between CH and overt myeloid neoplasia. This may be mediated by increased inflammatory signaling associated with clonal myeloid expansion, which has been increasingly implicated in organ damage beyond the hematopoietic system. Our findings are broadly consistent with prior studies revealing an approximately 2.0-fold increased risk of CKD progression among CH carriers [10, 14, 16], as well as, 1.4–1.9-fold increase risk of all-cause mortality compared with non-carriers largely driven by CVD and inflammatory complications [1, 9, 10, 13]. However, the magnitude of risk observed in our study was slightly higher, with an adjusted hazard ratio of approximately 2.8 for CKD progression and a nearly four-fold increased mortality risk. This discrepancy may be explained by differences in the study populations. Unlike population-based cohorts of largely asymptomatic individuals, our cohort consisted predominantly of patients with MDS, CCUS, and ICUS, conditions that are often associated with a greater clonal burden and systemic inflammatory activation. Consequently, the biological effects of CH in this setting may be amplified [7–10, 13, 14, 16, 17, 22, 28]. Another important consideration is the gene-specific heterogeneity of CH. Several studies have reported that non-DNMT3A mutations, particularly TET2 and ASXL1, are associated with a greater inflammatory burden and a higher risk of adverse cardiovascular and renal outcomes than DNMT3A mutations [1, 9, 11, 26]. Experimental models have revealed that TET2-deficient myeloid cells promote inflammatory signaling pathways that contribute to vascular injury and tissue damage [8, 17, 22, 29, 30]. To further explore mutation-specific effects, we performed an exploratory analysis comparing CKD progression between patients with DNMT3A and non-DNMT3A mutations (Supplementary Figure S2). No significant differences were observed between groups. However, this analysis should be interpreted with caution due to the limited number of patients included. Notably, our cohort was characterized by a high prevalence of non-DNMT3A mutations and multiple co-occurring mutations, reflecting greater clonal complexity. These features may amplify inflammatory signaling and partly explain the higher magnitude of CKD progression and mortality risk compared to prior population-based CHIP cohorts [10, 16]. This study had certain limitations. This was a single-center retrospective cohort study with a relatively small sample size, which may limit the generalizability of the results. In addition, owing to the retrospective design, we were unable to evaluate longitudinal inflammatory biomarkers that might further clarify the mechanistic pathways linking CH and kidney disease progression.
Future studies should validate these findings in larger prospective cohorts using appropriate comparators. In particular, the inclusion of non-CKD control groups is essential to clarify whether CKD itself is associated with an increased prevalence or distinct mutational spectrum of CH. Further investigations should focus on the effects of gene-specific mutations, clonal burden, and inflammatory biomarkers. Such studies may help to determine whether specific mutation profiles confer differential renal risk and whether targeting inflammatory pathways could mitigate the adverse systemic consequences of CH.
Conclusion
CH is frequently observed in patients with cytopenia and CKD and is independently associated with an increased risk of CKD progression and mortality. Compared with previously reported international CHIP cohorts, the magnitude of the risk observed in our study was greater, possibly reflecting the higher inflammatory burden and clonal complexity present in patients with MDS, CCUS, and ICUS. These findings revealed that CH is an important molecular determinant of adverse renal outcomes in this population. Further prospective studies are required to clarify the biological mechanisms underlying this association and to determine whether molecular screening for CH can improve the risk stratification and clinical management of CKD.
Supplementary Information
Acknowledgements
The authors would like to thank all the patients who participated in this study and the clinical staff, the nurses, and medical technicians of the Hematology Units for their support in patient care and data collection.
Authors’ contributions
S.Y. collected data, performed analyses, and drafted the manuscript; Su.K. conceived, supervised the study and critically edited and revised the manuscript; Si.Ko. performed next-generation sequencing analyses; C.P. and P.R. reviewed and edited the manuscript. All authors approved the final version.
Funding
This study was supported by the Ratchadapisek Research Fund (grant no. GA69/064).
Data availability
De-identified individual participant data are available upon reasonable request from the corresponding author and subject to institutional and ethical regulations.
Declarations
Ethics approval and consent to paticipate
This study was approved by the Institutional Review Board of the Faculty of Medicine at Chulalongkorn University (approval number 0633/67). The requirement for informed consent was waived owing to the retrospective design.
Consent for Publication
Not applicable.
Competing interests
The authors have no relevant financial or non-financial interests to disclose.
Footnotes
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