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Abstract
Objectives Ageing and inflammation are associated with clonal haematopoiesis (CH), the emergence of somatic mutations in haematopoietic cells. This study details CH in patients with systemic vasculitis in association with clinical, haematological and immunological parameters.
Methods Patients with three forms of vasculitis were screened for CH in peripheral blood by error-corrected sequencing. Relative contributions of age and vasculitis on CH prevalence were calculated using multivariable logistic regression. Clonal hierarchies were assessed by proteogenomic single-cell DNA sequencing, and functional experiments were performed in association with CH status.
Results Patients with Takayasu’s arteritis (TAK; n=70; mean age=33.2 years), antineutrophil cytoplasmic antibody-associated vasculitis (AAV; n=47; mean age=55.3 years) and giant cell arteritis (GCA; n=59; mean age=71.2 years) were studied. CH, most commonly in DNMT3A and TET2, was detected in 34% (60/176) of patients versus 18% (28/151) of age-matched controls (p<0.01). Prevalence of CH was independently associated with age (standardised B=0.96, p<0.01) and vasculitis (standardised B=0.46, p<0.01), occurring in 61%, 32% and 13% of patients with GCA, AAV and TAK, respectively. Both branched and linear clonal trajectories showed myeloid-lineage bias, and CH was associated with markers of cellular activation. In GCA, mutations were detected in temporal artery biopsies, and clinical relapse correlated with CH in a dose-dependent relationship with clone size.
Conclusions Age was more strongly associated with CH prevalence than inflammation in systemic vasculitis. Clonal profile was dominated by DNMT3A mutations which were associated with relapse in GCA. CH is not likely a primary causal factor in systemic vasculitis but may contribute to inflammation.
- Vasculitis
- Giant Cell Arteritis
- Polymorphism, Genetic
Data availability statement
Data are available upon reasonable request. All data relevant to the study are included in the article or uploaded as supplementary information.
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WHAT IS ALREADY KNOWN ON THIS TOPIC
Although clonal haematopoiesis (CH) has been linked to chronic inflammation and age-related immune dysregulation (‘inflammaging’), the causal role of inflammation and its synergism with ageing for CH selection are uncertain.
WHAT THIS STUDY ADDS
This study characterises the CH profile of blood from patients with three forms of vasculitis, demonstrates that age is a stronger predictor of CH than inflammation and shows an association between relapse and CH in patients with giant cell arteritis.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
Somatic mutations in blood are common in patients with vasculitis; however, CH is likely a biomarker of ‘inflammaging’ rather than an aetiological risk factor for vasculitis.
Introduction
The systemic vasculitides are a family of diseases characterised by inflammation of blood vessels. Takayasu’s arteritis (TAK), antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) and giant cell arteritis (GCA) are forms of systemic vasculitis that in aggregate affect patients across a broad age spectrum. TAK is a large-vessel vasculitis that primarily affects younger patients, while AAV is a small-vessel vasculitis that most commonly occurs in middle age, and GCA is a large-vessel vasculitis that is exclusive to later life.1–3 Although clinical and demographic differences exist between these forms of vasculitis, severe and organ-threatening disease due to vascular inflammation is common.
Systemic inflammation and ageing have been linked to increased prevalence of clonal haematopoiesis (CH), a phenomenon characterised by the emergence and subsequent expansion of somatic mutations in blood cells that is associated with all-cause mortality.4–6 In healthy individuals, CH frequency in peripheral blood increases with age and is prevalent in >10% individuals older than 70 years at a variant allele fraction (VAF) ≥2%, but ubiquitous in people older than 65 years of age when more sensitive sequencing techniques are used for screening.5 7 8 DNMT3A, TET2 and ASXL1 mutations are most common in healthy. A preferential selection of DNMT3A and TET2 clones has been described in many inflammatory disorders. DNMT3A mutations are preferentially selected in rheumatoid arthritis, ulcerative colitis, small cross-sectional studies in vasculitis and chronic infection,8–12 while TET2 mutations have been linked with low-grade inflammation and increased risk of cardiovascular disorders.13
Whether age and chronic inflammation are synergistic or independent contributors to CH is not well established. CH in myeloid cells has been hypothesised to fuel a vicious inflammatory feedback loop via increased production of pro-inflammatory cytokines.6 14–22 Conversely, CH may be a molecular marker of an underlying inflammatory environment with minimum modulatory impact on cellular function.
In this study, we characterised the CH landscape of a unique cohort of patients with vasculitis representing the human lifespan using error-corrected sequencing and single-cell proteogenomic sequencing. We modelled the relative contribution of age versus systemic inflammation on CH prevalence in patients with vasculitis and correlated results to clinical outcomes and functional assays.
Methods
Study population
Patients with vasculitis were recruited across North America into a prospective, observational cohort at the National Institutes of Health in Bethesda, Maryland, USA (NCT02257866). All patients included in this study fulfilled the 2022 American College of Rheumatology Classification Criteria for TAK, AAV or GCA.1–3 23 Patients were enrolled at any point during their illness, regardless of treatment. All patients underwent standardised clinical assessment at each study visit. Relapsing disease was defined as recurrence of clinical symptoms attributed to active vasculitis requiring increase in glucocorticoid therapy ≥50% from baseline dose or addition of steroid-sparing therapy. Age-matched healthy individuals were used as controls; up to two patients with vasculitis were matched to each healthy control within 5 years of age at the time of baseline DNA sample collection. The same control could be matched across different forms of vasculitis depending on age. All subjects provided informed consent. Samples were collected according to the Declaration of Helsinki. Patients were not directly involved in study design.
Bulk and single-cell DNA sequencing
Patients and controls were screened for CH using a customised error-corrected sequencing (ECS) panel covering common myeloid-related genes and UBA1, the causal gene for VEXAS syndrome,24 as previously described.25 DNA libraries were sequenced on the NovaSeq6000 (average coverage of 600× deduplicated reads), and variants with a deduplication ratio >3:1 and minimum VAF ≥0.5% were included in the analysis. When available, mutations were tracked over time in blood and quantified in DNA from sorted monocytes, neutrophils and temporal arterial biopsy (TAB). De novo variants (VAF ≥0.5%) identified at any time point were serially tracked in all other samples and retrospectively included in the analysis if detectable at VAF ≥0.1%. Single-cell proteogenomic DNA (scDNA) sequencing (genotype coupled with immunophenotyping) was performed in total blood cells from three patients with GCA and two patients with multiple CH mutations, according to the Mission Bio Tapestry platform protocols as previously described.25 scDNA data derived from healthy controls were used as reference for cell cluster analysis based on the expression of 45 protein surface markers. Details are shown in online supplemental material.
Supplemental material
Isolation of blood subpopulations and CD14+ monocyte stimulation experiments
Peripheral blood mononuclear cells (PBMCs) and neutrophils were first isolated from EDTA blood samples by Ficoll density gradient. Briefly, after PBMCs were isolated, the granulocyte layer was resuspended in half of the blood volume of 20% dextran for 15 min. Phosphate-buffered saline (PBS) was added to a total volume of 30 mL. After 30 min, the top layer of the separation (neutrophils) were moved to a new tube then washed in PBS. Monocytes and T lymphocytes were purified from PBMCs by positive selection using CD14 and CD3 beads (Miltenyi Biotec #130-050-201) following manufacturer’s instructions. For each patient and control, 1×106/mL CD14+ cells were seeded in triplicate in 12-well plates for stimulation with (100 ng/mL). After an overnight interferon gamma (IFN-ɣ) stimulation, CD14+ cells were stimulated with lipopolysaccharides (LPS) (100 ng/mL) for 4.5 hours and adenosine triphosphate (ATP) (5 mM) for 30 min. Media from each condition was harvested for cytokine/chemokine profiling using a custom designed Luminex Multiplex array with the following targets: interleukin (IL)-1β, IL-1 receptor antagonist (RA), IL-8, IL-10, IL-12p70, IL-23, IP-10, monocyte chemoattractant protein (MCP)-1, macrophage inflammatory protein (MIP)-1α, MIP-1β, tumour necrosis factor (TNF). Subsequent comparative analyses were considered exploratory and were not adjusted for multiple comparisons.
Statistical analyses
The prevalence of CH detected in peripheral blood was compared between patients with each form of vasculitis to age-matched controls using a VAF ≥0.5% threshold. To enable comparisons to prior studies that used lower depth of sequencing, results using a VAF threshold of ≥2% are also reported. Multivariable logistic regression was used to assess the independent association of age and vasculitis with presence of CH. Standardised beta coefficients were calculated to compare the relative strength of association. Clinical associations between categorical and continuous variables were compared using Fisher’s exact test and Wilcoxon rank-sum test.
Results
Study population
Patients with vasculitis (n=176) ranged in age from 5 to 88 years. Patients with TAK (n=70) were the youngest (mean age=33.6±14.8 years) followed by patients with AAV (n=47; median age=55.3±14.7 years) and GCA (n=59; mean age=71.1±8.6 years; table 1). The majority of patients were women (71%) and disease duration was variable at time of assessment (table 1). On average, patients with GCA were initially evaluated earlier in the disease course on higher doses of daily prednisone compared with patients with TAK and AAV.
Baseline characteristics of patients with vasculitis
Clonal landscape of systemic vasculitis
CH incidence in TAK, AAV and GCA was 13% (9/70), 32% (15/47) and 61% (36/59) respectively (figure 1A,B; online supplemental table 1). These frequencies decreased to 3% in TAK, 13% in AAV and 24% in GCA when the VAFs cut-off >2% were used (figure 1B). In all cohorts, DNMT3A was the most commonly mutated gene followed by TET2. DNMT3A mutations were seen in 10% of patients with TAK, 19% with AAV and 43% with GCA. TET2 mutations were absent in the TAK cohort but found in 11% of patients with AAV and 21% with GCA (figure 1C). Most patients with somatic mutations (65%) had variants at VAF <2% (median VAF=1%), regardless of the mutated gene and type of vasculitis (figure 1C). The frequency of patients with mutations at VAF ≥2% increased with age (figure 1D). Somatic mutations at VAF ≥10% were only seen in a minority of patients (10%), all were ≥58 years, had GCA (n=5) or AAV (n=2), and had ≥2 mutations (figure 1A,C). The frequency of patients with ≥2 CH mutations was similar among different forms of vasculitis (3/9 (33%) of TAK, 6/15 (40%) of AAV, 14/37 (38%) of GCA), and the number of concurrent CH mutations increased with age (figure 1D). TET2 mutations were all truncated and most DNMT3A mutations were located in the MTase domain, including the p.R882 hotspot mutations seen in four patients (one TAK, one AAV and two GCA) at VAFs ranging from 1% to 30%.
Clonal landscape of systemic vasculitis. (A) Oncoprint with somatic mutations identified in 176 patients with systemic vasculitis according to their age. Patients with Takayasu’s arteritis (TAK; n=70), antineutrophil cytoplasmic antibody-associated vasculitis (AAV; n=47) and giant cell arteritis (GCA; n=59) are coloured in the graph. The mutated gene and range of variants allele frequency (VAF), as well as their frequencies, are shown in the figure. (B) Frequency of patients with clonal haematopoiesis (CH) according to their vasculitis type and variants VAFs. (C) VAF of somatic mutations identified in peripheral blood. The median VAFs and ranges are shown in the figure according to the mutated gene. (D) Frequency of patients with vasculitis (TAK, AAV and GCA) and healthy controls (HC) with multiple variants (>2 somatic mutations), or with both DNMT3A and TET2 mutations. (E) CH frequency in TAK, AAV, GCA and HC according to age range and the two most commonly mutated genes, DNMT3A and TET2.
When compared with age-matched controls, CH was significantly enriched in GCA (61% vs 35%; p<0.01) but not in TAK (13% vs 6%; p=0.25) or AAV (32% vs 17%; p=0.15; figure 1E). This difference was not observed when a VAF ≥2% was used for analysis. Preferential selection of DNMT3A clones was associated with ageing and vasculitis type. DNMT3A mutations were enriched in middle age and older patients (30–69 years) with GCA and AAV compared with age-matched healthy controls (44% in GCA vs 24% in AAV vs 15% in TAK vs 12% in controls) but found at similar frequencies among patients and controls older than 70 years (44% in GCA vs 50% in AAV and 40% in controls; figure 1E). TET2 mutations were mostly enriched in AAV patients (7% in GCA vs 13% in AAV vs 3% in controls) (figure 1E).
In multivariable regression analysis, both age (B=0.05, p<0.01) and vasculitis (B=0.50, p<0.01) were independently associated with CH at VAF ≥0.5%. Using standardised beta coefficients, age (beta=0.96) was 2.09 times more strongly associated with CH than vasculitis (beta=0.46). Only two patients younger than 30 years were found with CH, both had TAK; no controls at the same age range had CH (figure 1A,D).
Clonal dynamics, trajectories and functional impact
Clonal dynamics were tracked in 35 patients, including 17 with CH at baseline. All patients with serial samples were on immunosuppressant treatment at time of initial sampling, and 10 patients successfully discontinued therapy during follow-up due to established disease remission. In 16 GCA and 1 TAK, clone sizes were stable or slightly changed in blood over a mean follow-up of 3.1 (±2.1) years (figure 2A and online supplemental figure 1). During follow-up, a new mutation was detected in one patient (V031) and a pre-existent clone disappeared in another (V669); CH was not detected in 17 patients at baseline or after a median of 2 years of follow-up (ranging from 0.5 to 5.5 years).
Clonal dynamics and trajectories in systemic vasculitis. (A) Longitudinal analysis of clonal haematopoiesis (CH). Somatic mutations in DNMT3A, TET2 and other genes identified in 17 patients at first visit were tracked over a median follow-up of 3.1 (±2.1) years; all variants were mostly stable. Variants at variant allele fractions (VAFs) >5% are coloured and their location is shown in the graph. (B) Clonal trajectories of two patients (V053 and V639) with giant cell arteritis (GCA) with multiple somatic mutations in DNMT3A/TET2. Clonal hierarchies, both linear and branched, of variants detected by bulk error-corrected sequencing (ECS) were assessed by single-cell proteogenomic analysis (scDNA). The frequency of different cell clusters based on the expression of protein surface markers are shown in figure according to cells’ genotype. Representative data from peripheral blood cells derived from a healthy control (HC) were used as a reference for analysis. Single cells were labelled according to their genotypes; wild-type (WT) cells were labelled as either from the healthy control (WT-HC) or V053 and V639 patients. Cells clusters were characterised according to their differentially expressed protein surface markers (normalised reads) when stained with the cocktail of 45 antibodies targeting common blood protein surface markers (TotalSeq-D Heme Oncology Cocktail antibody-oligo conjugate) and processed with the Tapestry protocol (Mission Bio). Cell populations were characterised based on a reference data from healthy samples and available Mission Bio data sets as: myeloid progenitor cells (MP; CD34lowCD38+CD117+CD123+CD45RA-CD141+CD71+CD7+CD33+CD64+), neutrophils (Net; CD16+CD62L+Lin−) with high or lower CD11b expression, monocytes (Mono; CD14+CD16±), plasmacytoid dendritic cells (pDC; CD14−CD123+FcεRIa+), and conventional DC (DC; CD14−CD141+CD11c+CD11b+), T lymphocytes (CD3+CD8+ or CD4+), B lymphocytes (CD19+), natural killer (NK; CD3−CD56+CD7). (C) scDNA profiles and relative expression of specific protein markers in blood subpopulations. The Uniform Manifold Approximation and Projection (UMAP) scDNA profiles for healthy and vasculitis samples are shown in the graph. Cells from healthy and V421 were all WT while a subset of cells from V053 and V639 were DNMT3A/TET2 mutated. Cells’ genotypes according to their UMAP projection are shown in the figure. Bottom panels show the relative expression of markers linked to activation of monocytes, NK and T cells in cells from controls (HC), V421, V053, and V639 according to their genotype, WT or with CH mutations (CH).
To better investigate the clonal trajectories and composition of mutated cells, we performed scDNA sequencing in peripheral cells from three patients with GCA, two with multiple mutations in DNMT3A/TET2. In V053, a branched trajectory with four independent clones was seen: the DNMT3A p.R882H and p.R882S were independent driver mutations, and two TET2 mutations were subclonal to the p.R882H (figure 2B). In contrast, a linear trajectory was seen in V639; a driver mutation in DNMT3A preceded the acquisition of the TET2 mutation seen in similar VAFs in bulk ECS. In both patients, TET2 mutations co-occurred with DNMT3A in single cells, which were mostly of myeloid lineage; up to 15–20% of CD4+ and CD8+ T cells, B cells and natural killer (NK) cells were also mutated (also carrying the classical myeloid-related DNMT3A p.R882 mutations). The fractions of monocytes (Lin−CD14+), neutrophils (Lin−CD16+CD62L+) and myeloid progenitor cells (CD117+CD38+CD33+) were mostly CH mutated and increased in comparison to healthy controls (figure 2B). Also, myelopoiesis was shifted towards increasing counts of intermediate monocytes (CD14+CD16+) and neutrophils expressing CD11bhigh, a phenomenon reported in systemic inflammation and associated with pro-inflammatory phenotype.26 27 Similar results were seen in a single patient with GCA without CH (V421), suggesting that cell composition may not be primarily driven by CH presence; a significant B cell clonal expansion, all wild-type, was also seen in this patient (online supplemental figures 2 and 3A).
We next compared whether mutated DNMT3A/TET2 cells were associated with increased expression of classical protein surface markers linked to inflammatory and cytotoxic characteristics.28–30 We found no differences in the expression of CD10, CD11b, CD62L and CD64 in neutrophils, regardless of mutation status, among patients and controls (online supplemental figure 3B). In contrast, CH presence is associated with an inflammatory CD16+ phenotype in monocytes and higher expression of cytotoxic markers in NK cells, and T lymphocytes (figure 2C). Higher CD14+/CD16+ expression was seen in monocytes from V053 and V639 but not V421 when compared with controls; among these, cells with CH had significantly higher expression of these markers. Higher expression of CD10, CD16 and CD11b linked to high cytotoxic activity was significantly increased in NK cells, CD4+ and CD8+ T cells harbouring a CH mutation but not in wild-type cells.
To investigate whether CH impacted monocyte function, we stimulated purified cells from 13 and 10 patients with GCA with and without CH, respectively. Results were compared with data derived from 6 and 9 age-matched controls with and without CH, respectively. Monocytes from patients with GCA with and without CH on stimulation with LPS and IFN-ɣ produced similar levels of cytokines, however, chemokine production of MCP-1, MIP1α and MIP1β were significantly higher in monocytes from patients with CH after IFN-ɣ stimulation (figure 3A). Monocytes from healthy controls with CH also produced more MIP-1α compared with those without CH across a series of different experimental conditions (figure 3A).
Clinical and functional impact of clonal haematopoiesis (CH). (A) CD14+ cell stimulation experiments. Protein levels of MCP-1, MIP1α and MIP1β were increased in supernatants of CD14+ cells from giant cell arteritis (GCA) patients with CH stimulated with interferon (IFN)-ɣ in comparison to stimulated non-mutated cells. MIP1α levels were also increased in supernatants of CD14+ cells from healthy controls with CH in comparison to non-mutated cells stimulated under different experimental conditions. (B) Dose response association of CH variant allele frequency (VAF) and relapse risk of patients with GCA. Higher mutations VAFs correlated with relapse in GCA. All patients with GCA with CH at VAF ≥5% experienced relapse. LPS, lipopolysaccharides; MCP, monocyte chemoattractant protein; MIP, macrophage inflammatory protein.
CH associated with increased myeloid counts and lineage bias in peripheral blood
Clinically, presence of CH at VAF ≥0.5% was associated with higher absolute neutrophils counts (ANC; p<0.02) while CH at VAF ≥2% was significantly associated with higher ANC and absolute monocyte counts, higher neutrophil frequency and neutrophil to lymphocyte ratio and lower lymphocyte frequency compared with patients without CH (table 2). There were no significant differences in haemoglobin levels, red blood cell count or daily prednisone dose at the time of haematological assessment between patients with and without CH defined at both VAF thresholds. Overall, presence of CH did not associate with cytopenias but with increased number of myeloid cells in peripheral blood. No patients developed haematological malignancies.
Association of clonal haematopoiesis (CH) and haematological parameters in vasculitis
CH associated with relapse in patients with GCA
Given the high prevalence of CH in GCA relative to the other forms of systemic vasculitis, associations between CH and clinical features of vasculitis were only studied in patients with GCA. Patients with GCA with CH defined at VAF ≥0.5% only had lower erythrocyte sedimentation rate (ESR) values at diagnosis compared with those without CH (51 vs 85 mm/hr; p=0.03). However, patients with CH defined at VAF ≥2% were more likely to have relapsing disease (67 vs 25%, p<0.01), were older at time of CH assessment (74 vs 71 years, p=0.07), had a lower maximum ESR value at diagnosis (28 vs 83 mm/hr; p=0.03) and were less likely to experience clinical response when treated with tocilizumab (63% vs 93%; p=0.06; table 3). A dose response was observed between CH VAF% and relapse (figure 3B). The association of CH and relapsing disease was mediated by DNMT3A-defined CH (82% of relapsed patients) more strongly than TET2-defined CH (24% of relapsed patients). Survival outcomes were not assessed as only one death occurred during the study period in a patient with GCA and CH.
Associations of clonal haematopoiesis (CH) defined at different variant allele frequency (VAF) thresholds and clinical features of giant cell arteritis (GCA)
To determine whether CH mutations from circulating immune cells could be detected in arterial tissue, we sequenced TAB specimen material from five patients with GCA at diagnosis in parallel with peripheral blood sequencing. Four of five patients had mutations detected in TAB and peripheral blood. In two patients with TAB results positive for transmural inflammation, CH mutations were detected in both peripheral blood and TAB tissue: in one, TET2 mutations were detected at VAF of 0.5% in both blood and TAB, while in the second, a DNMT3A mutation was enriched in blood over TAB (1% vs 0.4% VAFs, respectively). Among three patients with negative TAB results but a clinical diagnosis of GCA confirmed by vascular imaging studies, two were found with CH in blood at VAFs of 1% that was detected in TAB at very low levels (VAF<0.5%; online supplemental table 2).
UBA1 somatic mutations in systemic vasculitis
Somatic mutations in UBA1 are now considered within the spectrum of CH and define the VEXAS syndrome, which is associated with different clinical forms of vasculitis. We therefore screened all study participants for UBA1 mutations. No patient had a detectable mutation in UBA1 at a VAF consistent with VEXAS syndrome; however, one female patient with GCA had a pathogenic UBA1 mutation (c.118-G>T) in blood on two separate occasions over a 4-year interval, at VAFs of 0.3% and 0.9%. This patient had negative bilateral temporal artery biopsies in the setting of frontotemporal headaches, constitutional symptoms, polymyalgia rheumatica and elevated acute phase reactants. Her disease was also defined by acute onset and rapidly progressive upper and lower extremity claudication with severe arterial damage restricted to the bilateral axillary arteries and femoral arteries. She had no cytopenia but did have chronic unexplained macrocytosis (maximum mean corpuscular volume 99 fL). She responded well to tocilizumab and tapered glucocorticoids, and her vasculitis has been in stable remission off treatment for 5 years.
Discussion
In three forms of systemic vasculitis representing a broad age spectrum of patients, both age and inflammation were independent predictors of CH. The relative association was twice as strong for age compared with a diagnosis of systemic vasculitis. Thus, while systemic inflammation may be associated with increased risk for CH, age remained the strongest predictor of CH in patients with vasculitis. When compared with age-matched controls, increased CH frequency was most prominently seen during middle age, with no differences in CH prevalence observed in study subjects younger than 30 years or older than 70 years. However, most clones were small and when the traditional VAF cut-off of 2% was used for CH detection, there was no difference between the controls and patients with vasculitis. The largest VAFs in this study were restricted to older patients with AAV or GCA, further supporting the importance of age in the generation and expansion of CH clones. Of note, most mutated cells were myeloid but unexpected frequencies (up to 20%) of mutated lymphocytes and NK cells were also seen, suggesting that clonal selection occurred at the haematopoietic stem and progenitor cell level.
CH has been studied in a few rheumatological diseases. CH prevalence was reported to be 15% in rheumatoid arthritis and systemic sclerosis and 30% in case series of AAV and GCA.8 11 12 31 Similar to this study, DNMT3A followed by TET2 mutations dominated the clonal landscape, mostly detected at VAFs of 2–10%. In these studies, the traditional VAF cut-off of 2% was often used to define CH, which would not have comprehensively characterised the mutational burden observed in this study with variants predominantly found at VAFs <2%. Indeed, at VAF >1%, CH incidence in a small GCA cohort and population-based controls was similar.32 CH has also been recently characterised in the newly discovered VEXAS syndrome. A clonal landscape dominated by DNMT3A (including the DNMT3A p.R882 hotspot mutations known to be highly associated with myeloid malignancies) and TET2 mutations with skewed haematopoiesis towards myeloid production was observed.24 25 VEXAS provides an excellent comparator disease to GCA, as both diseases are exclusive to adulthood. Interestingly the prevalence of CH in GCA reported here (61%) was nearly identical to the previously reported prevalence of CH in VEXAS (60%) using the same sequencing methods and CH definitions. These comparisons highlight that CH mutations, particularly those in DNMT3A and TET2, are not specific to vasculitis, but rather are associated with systemic inflammation in older patients across a spectrum of inflammatory diseases.
Population-based studies suggest that CH in TET2, but not DNMT3A, may increase risk for specific cardiovascular and inflammatory diseases.6 33–35 A recent study demonstrated a 1.48-fold increased risk of incident GCA and TET2-CH.36 Corresponding functional studies of TET2 knockout haematopoietic cells reveal increased myeloid-mediated inflammation in murine models of atherosclerosis and gout.6 33 37 While these studies show an association between CH and various inflammatory diseases, they do not establish causality. In contrast, our findings support the hypothesis that CH mutations are likely a consequence more than a cause of inflammation in systemic vasculitis. More specifically, DNMT3A-CH is preferentially associated with ageing whereas TET2-CH seems to be preferentially selected in an aged inflammatory environment. Indeed, multiple TET2 mutations in two patients with GCA were subclonal to DNMT3A in single cells. The increased risk of inflammatory diseases inferred by large association studies likely reflects an association between CH and inflammation in older populations.
Our findings support the concept that CH primes myeloid cells to a pro-inflammatory phenotype,37 which potentially may modulate an underlying inflammatory process and alter the course of disease. Patients with GCA with CH had increased myeloid cell burden, and monocytes, NK cells and T lymphocytes displayed an activated phenotype marked by high expression of CD10, CD11b and CD16. CH mutations were found in affected arteries at similar levels found in peripheral blood, similar to the finding that CH clones can be also detected in atherosclerotic plaques.38 Monocytes from patients with GCA with CH secreted higher levels of chemokines that modulate macrophage proinflammatory signalling pathways (MCP1, MIP1b and MIP1a), findings consistent with recently reported study that identified pathways involved in macrophage function as a mediator of inflammation linked to TET2 mutations in monocytes.37 These chemokines regulate monocyte/macrophage migration from blood across vascular endothelium during immunological surveillance of tissue in response to inflammation, suggesting CH may contribute to vascular inflammation.39 40 A bidirectional association between CH and vascular inflammation may exist and explain the higher likelihood of patients with GCA with CH to experience clinical relapse. However, a casual directionality with relapse remains uncertain, as patients were sampled at different points in the disease course, and the association may simply reflect the burden of recurrent inflammation on CH prevalence in patients with vasculitis. Although sample size was modest, less frequent clinical response to tocilizumab was observed in patients with GCA with CH at VAF ≥2%. Larger, prospective observational cohort studies are needed to further define potential associations of CH and clinical features of disease in patients with vasculitis, including risk relapse risk, treatment response, cardiovascular events, and risk for haematological malignancy.
With the recent discovery of the VEXAS syndrome, UBA1 is now included in a panel of genes linked to CH. Accordingly, we sequenced all patients in this study to detect variants in UBA1, especially since patients with VEXAS can be clinically diagnosed with various forms of vasculitis, including biopsy-proven GCA. Another recent study sequenced a large cohort of patients with GCA and found no UBA1 mutations,41 suggesting that prevalence of VEXAS in GCA is not common. Similarly, in this study, only one patient with vasculitis was found to have a UBA1 VEXAS-defining mutation in blood. The patient was female with GCA who had a very small UBA1 clone (VAF <1%) that persisted for years. She had unexplained macrocytosis and somewhat atypical features of GCA including severe stenosis in the femoral arteries, an arterial bed not typically damaged in GCA. In parallel to this observation, a prior study from Japan also detected UBA1 mutation at VAF of 0.1% in a single female patient with a clinical diagnosis of relapsing polychondritis.42 Whether low prevalence UBA1 mutations detected in peripheral blood influence clinical phenotypes in systemic inflammatory diseases, particularly in female patients, warrants further investigation.
Study limitations include small sample sizes that precluded robust analyses to detect clinical associations with CH at both bulk and single-cell levels, and the lack of cytokine profiles and marrow biopsies for morphological analysis prior to any treatment. Although monocyte stimulation experiments were not adjusted for multiple comparisons and were performed on bulk cell populations rather than purified mutant cell populations, a recent study showed that single-cell transcriptome of wild-type DNMT3A cells were similar to mutated cells from the same environment, suggesting that these mutations may globally affect cell function and are not restricted to mutated cells.43 CH was only screened in small set of previously identified myeloid-related genes. Whether mutations in lymphoid lineages across a different set of genes are present and are clinically relevant in patients with vasculitis remains to be determined. Clinical associations were only studied in patients with GCA due to sample size restrictions.
In summary, CH is frequently detected in patients with systemic vasculitis with increased prevalence in association with ageing. Inflammation accelerates age-related CH, dominated by DNMT3A and TET2 mutations. CH clones are mostly stable regardless of treatment, biased towards myeloid differentiation and associated with increased counts of pro-inflammatory monocytes, T lymphocytes and NK cells with high cytotoxic activity. Clinically, CH is a marker of relapse in GCA and correlates with increasing clone size. To what extent CH mutations are a consequence or cause of inflammation in patients with vasculitis requires further study; however, findings from this study suggest on balance that these mutations do not have a strong primary effect on risk to develop vasculitis but may modify disease course. Exploration of a wider set of genes, beyond those commonly associated with CH, may yield further insight into causal mechanisms of disease in systemic vasculitis.
Data availability statement
Data are available upon reasonable request. All data relevant to the study are included in the article or uploaded as supplementary information.
Ethics statements
Patient consent for publication
Ethics approval
This study involves human participants and was approved by NIH IRB: 14-AR-0200. Participants gave informed consent to participate in the study before taking part.
Acknowledgments
We would like to thank all patients and their families, the DNA Sequencing and Genomics Core from NHLBI. Some Figures were created with BioRender.com.
References
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Footnotes
Handling editor Josef S Smolen
Twitter @MassimoGadina
Contributors FG-R, KVW, AIJ, MG, BP, NSY and PCG conceptualised and designed the study, and interpreted the results, wrote and edited the manuscript. FG-R, DH and LA performed and analysed error-corrected sequencing (ECS) experiments. FG-R interpreted the single-cell proteogenomic DNA results. AIJ, CR and KAS performed functional experiments. RTC provided healthy controls data for ECS analysis. KVW, AIJ, KAQ and PCG performed statistical analysis for clinical outcomes. KAQ and PCG provided clinical care. PCG accepts full responsibility for the work and conduct of the study, had access to the data, and controlled the decision to publish.
Funding This research was funded by the Intramural Research Program of the National Heart, Lung, and Blood Institute and the National Institute of Arthritis and Musculoskeletal and Skin Diseases.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
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