Association between clonal hematopoiesis and periodontitis: a two-sample mendelian randomization study

Abstract

Clonal hematopoiesis (CH) is an age-associated phenomenon characterized by the proliferation of blood cells carrying somatic mutations. Recent studies suggest a potential link between CH and periodontitis, but the causal relationship remains unclear. A two-sample Mendelian randomization (MR) analysis was implemented, examining whether CH phenotypes are causally associated with periodontitis. CH phenotypes included overall clonal hematopoiesis (CH-overall), CH with a DNMT3A mutation (CH-DNMT3A), CH with a TET2 mutation (CH-TET2), large clones (CH-large), and small clones (CH-small). Genetic instruments were derived from genome-wide association studies, and the inverse-variance weighted (IVW) method was the primary analytical approach. Sensitivity analyses and reverse MR were also performed to ensure robustness. MR analysis demonstrated a significant association between CH-DNMT3A and periodontitis (odds ratio: 0.084, 95% CI: 0.007–0.972, P = 0.047), suggesting a protective role. No significant associations were found for other CH phenotypes. Reverse MR analyses showed no statistical evidence of a bidirectional relationship between periodontitis and any CH phenotype. Additionally, the analyses showed no signs of pleiotropy or heterogeneity that could confound the results. Our findings suggest a novel protective role for DNMT3A-mutated CH in periodontitis. Further research is warranted to explore the mechanisms underlying this association.

Background

Periodontitis is a common chronic inflammatory condition that targets the supporting structures of teeth, with a prevalence that increases with age¹. If untreated, it can lead to progressive destruction of periodontal tissues and eventual tooth loss². Global estimates suggest that periodontitis affects 20–50% of the population³. The etiology of periodontitis is multifactorial, involving microbial, environmental, and genetic factors. Additionally, emerging research has highlighted the critical role of systemic conditions, such as hematopoietic abnormalities, in the onset and progression of periodontitis^4,5,6.

Clonal hematopoiesis (CH) is a condition associated with aging, characterized by the clonal expansion of hematopoietic stem cells (HSCs) harboring somatic mutations in genes regulating hematopoiesis and epigenetics, including DNMT3A and TET2^6,7,8,9. These mutations confer a selective growth advantage, resulting in the disproportionate proliferation of mutant clones compared to non-mutant HSCs^9,10. CH prevalence rises with age, affecting an estimated 10–20% of individuals over the age of 70¹¹. CH has been linked to increased risks of hematological malignancies and various inflammatory conditions^12,13,14. However, the causal relationship between CH and chronic inflammatory diseases, including periodontitis, remains unclear.

Understanding the interplay between CH and periodontitis could provide valuable insights into underlying biological pathways and potential therapeutic targets. This study probed into the bidirectional causality between CH phenotypes and periodontitis employing a two-sample Mendelian randomization (MR) approach. MR employs genetic variants as instrumental variables (IVs) to infer causality between exposures and outcomes^15,16, leveraging the random allocation of genetic variants at conception to reduce confounding and reverse causality common in observational studies¹⁷.

Here, we explored potential causal relationships between five CH phenotypes—overall clonal hematopoiesis (CH-overall), CH with DNMT3A mutation (CH-DNMT3A), CH with TET2 mutation (CH-TET2), large clones (CH-large), and small clones (CH-small)—and periodontitis. Additionally, reverse MR analyses were implemented to assess the potential influence of periodontitis on CH phenotypes, providing further insight into the interactions between these conditions.

Methods

Study design

This study employed a two-sample MR approach, utilizing genetic data from two independent genome-wide association study (GWAS) datasets: one for CH and the other for periodontitis. This design allowed us to explore the causal relationship between CH and periodontitis by using genetic variants strongly associated with CH phenotypes as IVs. The analysis was conducted under the assumptions of MR: (1) IVs were evidently linked to the exposure (CH phenotypes); (2) IVs were not associated with confounders; and (3) IVs influenced the outcome (periodontitis) only via their association with the exposure.

Data sources

Summary statistics for genetic associations with CH were sourced from a large-scale GWAS conducted by Siddhartha et al.¹⁸. This study analyzed whole-exome sequencing data from 200,453 individuals of European ancestry in the UK Biobank to assess the prevalence of CH and its association with various somatic mutations, including DNMT3A and TET2.

Periodontitis-related genetic data were sourced from a meta-analysis of GWAS conducted by the FinnGen consortium¹⁹. This dataset included genomic data from 346,731 Finnish participants, comprising 87,497 cases of chronic periodontitis and 259,234 controls. Periodontitis diagnoses were based on the International Classification of Diseases (ICD-10) code K05.3 (https://risteys.finregistry.fi/endpoints/K11_PERIODON_CHRON) and adhered to diagnostic criteria established by the American Academy of Periodontology and the European Federation of Periodontology. Specifically, individuals were identified as having periodontitis if they exhibited: (1) interdental clinical attachment loss (CAL) at two or more non-adjacent teeth, or (2) CAL ≥ 3 mm combined with pocket depths ≥ 3 mm at two or more teeth. Although diagnostic criteria varied slightly across studies within the meta-analysis, the use of standardized case definitions ensured comparability. The UK Biobank and FinnGen datasets are publicly available resources, with approvals obtained from respective institutional review boards and ethics committees. The UK Biobank operates under strict ethical guidelines, while the FinnGen project is managed by the University of Helsinki. Detailed information on these datasets is summarized in Table 1.

Table 1 Data sources for clonal hematopoiesis and periodontitis.

IV

Reliable IVs for the MR analysis were constructed by selecting single-nucleotide polymorphisms (SNPs) notably associated with each CH phenotype at a threshold of p < 1 × 10⁻⁵. To ensure independence among the selected SNPs, linkage disequilibrium pruning was implemented, retaining only those with an r² < 0.001. This process minimized potential correlations and chain reactions among SNPs. The resulting SNPs were used as IVs in the analysis.

Statistical analysis for MR

The strength of the IVs was tested by calculating the F-statistic utilizing the formula:

$${\text{F = ((R2 * (NK - 1))/(1 - R2 * K)}}$$

Where R²is the proportion of variance in the exposure explained by the genetic instruments, N is the sample size, and K denotes the number of instruments. An F-statistic > 10 signifies strong instruments with minimal risk of weak instrument bias²⁰.

Bidirectional two-sample MR analyses were conducted using the inverse variance weighting (IVW) method as the primary approach. IVW provides a weighted average of the Wald ratios for each genetic variant, offering robust estimates of causal effects²¹. Sensitivity analyses, including MR-Egger regression and the weighted median (WM) method, were employed to test the robustness of the findings. The MR-Egger intercept test was used to detect directional pleiotropy by evaluating horizontal pleiotropy²². The WM method generates valid causal estimates even if up to 50% of the genetic instruments are invalid²³. The MR-PRESSO method was applied to identify and correct horizontal pleiotropy, ensuring the reliability of causal estimates²⁴. Heterogeneity across genetic variants was assessed using Cochran’s Q statistic, which evaluates variability in causal effect estimates²⁵.

The causal effects of CH phenotypes on periodontitis were summarized as odds ratios (ORs) with 95% confidence intervals (CIs). A p-value < 0.05 was deemed statistically significant. Additionally, inverse MR analyses were implemented to test the potential causal effects of periodontitis on CH phenotypes, employing SNPs associated with periodontitis at a threshold of p < 5 × 10⁻⁵as IVs. All statistical analyses were done with the help of R software (version 4.2.1) utilizing the two-sample MR package (version 0.5.6)²⁶ and the MR-PRESSO package (version 1.0).

Results

Selection of IVs

Based on the IV selection criteria (p < 1 × 10⁻⁵), a total of 159 SNPs were identified as IVs associated with five subtypes of CH. Detailed information on these selected IVs is summarized in Additional File Table S1.

Statistical analysis

The F-statistic for the selected IVs ranged from 19.42 to 222.54, ensuring that weak instrument bias was not a concern in the analysis.

In the primary forward MR analysis employing the IVW method, a significant causal effect of CH with DNMT3A mutations (CH-DNMT3A) on the risk of periodontitis was observed (OR = 0.084, 95% CI: 0.007–0.972, P = 0.047) (Table 2; Fig. 1). This result suggests that CH-DNMT3A may have a protective effect against periodontitis. No significant causal associations were identified for the other CH subtypes (Fig. 2).

Table 2 MR estimates for the association between clonal hematopoiesis and periodontitis.

Sensitivity analyses using MR-Egger regression and WM estimators supported the findings of the IVW analysis (Table 3). MR-Egger regression showed no evidence of horizontal pleiotropy, as evidenced by the nonsignificant intercept term (P > 0.05). The WM analysis further reinforced the protective association of CH-DNMT3A against periodontitis, demonstrating robustness to potential violations of MR assumptions. Cochran’s Q test indicated no significant heterogeneity in the IVW results (Table S2). While gross inspection of the leave-one-out analysis suggested potential outliers (Figure S1), MR-PRESSO analysis identified no significant outliers (P > 0.05, Table S3). Collectively, these findings indicate that horizontal pleiotropy and heterogeneity did not significantly affect the results.

Table 3 Pleiotropy test of clonal hematopoiesis genetic variants in the risk of periodontitis.

In the reverse MR analysis, no evidence was found to support a causal effect of periodontitis on any CH phenotype (Figure S2). The heterogeneity test for periodontitis and overall CH was significant (Table S4), but the MR-Egger regression intercept did not detect horizontal pleiotropy (Table S5). However, MR-PRESSO analysis identified significant outliers (P < 0.05, Table S6). After removing these outliers to reduce heterogeneity and pleiotropy, the adjusted P-value was above 0.05, confirming no significant causal effect. Overall, genetic variants associated with periodontitis did not influence the risk of any CH phenotype (P > 0.05 for all CH outcomes). These findings indicate a unidirectional relationship, where CH impacts the risk of periodontitis but not vice versa.

Discussion

This two-sample MR study utilized summary statistics from GWAS meta-analyses conducted by the UK Biobank consortium for CH and from FinnGen consortium R10 data for periodontitis. Our findings provide novel insights, highlighting a significant inverse association between the risk of periodontitis and CH driven by DNMT3A mutations. No significant associations were observed with other CH phenotypes, and reverse MR analyses demonstrated no sign of reverse causality, indicating that periodontitis does not influence CH development.

The protective effect of DNMT3A-mutated CH on periodontitis risk is both intriguing and unexpected, challenging the conventional view of CH as predominantly a pathological condition associated with increased inflammation and age-related diseases²⁷. While previous studies have demonstrated that an inflammatory milieu promotes CH development and persistence—creating a feedback loop that exacerbates both CH and inflammatory conditions^28,29 —our findings suggest a more nuanced role for DNMT3A. Proinflammatory cytokines, like TNF-α and IL-6, are known to drive the expansion of CH clones, particularly those with mutations in TET2 and DNMT3A, which are associated with heightened inflammatory responses, including those seen in periodontitis³⁰. However, recent research has shown that DNMT3Amutations may induce epigenetic modifications through altered DNA methylation patterns, potentially regulating genes involved in inflammatory pathways^31,32. Observational studies have reported that DNA methylation changes are more pronounced in individuals with periodontitis compared to healthy controls^33,34,35. These epigenetic changes may dampen inflammatory responses in periodontal tissues, thereby mitigating tissue destruction and alveolar bone loss.

DNMT3A-mutated CH also appears to modulate the differentiation and function of immune cells, particularly those implicated in periodontitis pathogenesis. DNMT3Ais critical in modulating the differentiation and function of multiple immune cell types, such as T cells and bone marrow-derived cells³⁶. Alterations in T-cell subsets, such as a shift towards regulatory T cells, may contribute to a more balanced immune response in periodontal tissues, reducing the risk of periodontitis^37,38,39. Furthermore, the oral microbiome is a well-established factor in periodontitis development^40,41,42. We hypothesize that DNMT3A mutations may indirectly influence the composition or virulence of the oral microbiome by altering immune function, thereby reducing periodontitis risk. However, this hypothesis requires further investigation to elucidate the precise mechanisms involved.

Strikingly, the protective effect observed in DNMT3A-mutated CH appears to be specific, as it was not detected in other CH subtypes. This finding suggests that the protective mechanism may be tied to the unique role of DNMT3Ain epigenetic regulation and hematopoietic stem cell biology³⁶. The absence of significant associations with other CH subtypes, such as those driven by TET2 mutations or overall CH, supports the hypothesis that the protective effect is specifically mediated by DNMT3A-associated epigenetic alterations.

These results underscore the complexity of CH and its heterogeneous effects on inflammatory diseases. While previous studies have linked CH to increased cardiovascular and all-cause mortality¹², our findings indicate that DNMT3A-mutated CH may exert a protective effect against certain inflammatory conditions, such as periodontitis. This highlights the importance of further investigating the biology of CH and its diverse roles in age-related diseases.

The research possesses numerous strengths worth highlighting. First, the use of MR provides a robust framework to infer causality with reduced confounding and reverse causality. Second, the large sample size of the GWAS datasets ensures strong genetic associations for CH subtypes and periodontitis. Third, the consistency of results across multiple MR methods, including sensitivity analyses, reinforces the reliability of our findings.

Several limitations must also be acknowledged. First, while MR minimizes confounding and reverse causality, its accuracy depends on the validity of the genetic instruments. Although we selected SNPs strongly associated with CH phenotypes, potential pleiotropy—where genetic variants affect outcomes through pathways other than the exposure—cannot be entirely excluded. Second, the study population was predominantly of European ancestry, which limits the generalizability of the findings to other ethnic groups. Third, while MR provides evidence for causality, the exact magnitude of the causal effect should be interpreted cautiously. Larger datasets and more advanced analytical approaches will be required to refine these estimates and deepen our understanding of the underlying mechanisms.

Conclusions

This bidirectional two-sample MR study provides robust evidence supporting a potential causal relationship between CH with DNMT3A mutations and a reduced risk of periodontitis. These findings uncover the intricate interplay between CH and inflammatory conditions, underscoring the necessity for further research to elucidate the underlying biological mechanisms and explore potential therapeutic implications. The unexpected protective effect of DNMT3A-mutated CH on periodontitis risk presents a novel perspective in both hematology and periodontal medicine. This discovery opens new avenues for understanding the role of CH in age-related.

We thank all the researchers and participants of the studies involved in the Mendelian randomization.

Fig. 1

Scatter plots for the causal association between clonal hematopoiesis andperiodontitis.

Fig. 2

Forest plots of univariable Mendelian randomization analvsis of the relationship between clonal hematopoiesis and periodontitis.