Premature Menopause, Clonal Hematopoiesis, and Coronary Artery Disease in Postmenopausal Women
Premature menopause is an independent risk factor for cardiovascular disease in women, but mechanisms underlying this association remain unclear. Clonal hematopoiesis of indeterminate potential (CHIP), the age-related expansion of hematopoietic cells with leukemogenic mutations without detectable malignancy, is associated with accelerated atherosclerosis. Whether premature menopause is associated with CHIP is unknown.
We included postmenopausal women from the UK Biobank (n=11 495) aged 40 to 70 years with whole exome sequences and from the Women’s Health Initiative (n=8111) aged 50 to 79 years with whole genome sequences. Premature menopause was defined as natural or surgical menopause occurring before age 40 years. Co–primary outcomes were the presence of any CHIP and CHIP with variant allele frequency >0.1. Logistic regression tested the association of premature menopause with CHIP, adjusted for age, race, the first 10 principal components of ancestry, smoking, diabetes, and hormone therapy use. Secondary analyses considered natural versus surgical premature menopause and gene-specific CHIP subtypes. Multivariable-adjusted Cox models tested the association between CHIP and incident coronary artery disease.
The sample included 19 606 women, including 418 (2.1%) with natural premature menopause and 887 (4.5%) with surgical premature menopause. Across cohorts, CHIP prevalence in postmenopausal women with versus without a history of premature menopause was 8.8% versus 5.5% (P<0.001), respectively. After multivariable adjustment, premature menopause was independently associated with CHIP (all CHIP: odds ratio, 1.36 [95% 1.10–1.68]; P=0.004; CHIP with variant allele frequency >0.1: odds ratio, 1.40 [95% CI, 1.10–1.79]; P=0.007). Associations were larger for natural premature menopause (all CHIP: odds ratio, 1.73 [95% CI, 1.23–2.44]; P=0.001; CHIP with variant allele frequency >0.1: odds ratio, 1.91 [95% CI, 1.30–2.80]; P<0.001) but smaller and nonsignificant for surgical premature menopause. In gene-specific analyses, only DNMT3A CHIP was significantly associated with premature menopause. Among postmenopausal middle-aged women, CHIP was independently associated with incident coronary artery disease (hazard ratio associated with all CHIP: 1.36 [95% CI, 1.07–1.73]; P=0.012; hazard ratio associated with CHIP with variant allele frequency >0.1: 1.48 [95% CI, 1.13–1.94]; P=0.005).
Premature menopause, especially natural premature menopause, is independently associated with CHIP among postmenopausal women. Natural premature menopause may serve as a risk signal for predilection to develop CHIP and CHIP-associated cardiovascular disease.
What Is New?
We tested whether premature menopause (before age 40 years) overall and stratified by mechanism of menopause (natural versus surgical premature menopause) was associated with clonal hematopoiesis of indeterminate potential (CHIP), the expansion of hematopoietic stem cells with somatic mutations in leukemia-associated genes, among postmenopausal women with next-generation genomic sequencing in the UK Biobank and Women’s Health Initiative.
Premature menopause, especially natural premature menopause, was independently associated with increased odds of CHIP; no significant association with surgical premature menopause was observed.
CHIP was associated with incident coronary artery disease events in postmenopausal middle-aged women independent of conventional coronary artery disease risk factors.
What Are the Clinical Implications?
Natural premature menopause may represent a risk signal for latent genomic instability and predilection to develop CHIP and CHIP-associated cardiovascular disease.
Women with premature menopause may be particularly well-suited to CHIP screening and surveillance and to precision medicine approaches to mitigate CHIP-associated cardiovascular disease risk, such as interleukin-1β/interleukin-6 inhibition.
Editorial, see p 424
Cardiovascular disease is the leading cause of death among women in the United States and globally,1 and cardiovascular risk increases substantially after menopause.2 The mean age at menopause in Western nations is ≈51 years, but ≈10% of women undergo menopause before age 45 years, and at least 1% experience menopause before age 40 years.3,4 Premature menopause, defined as menopause onset before age 40, is associated with accelerated biological aging,5,6 cardiovascular disease, and all-cause mortality,7 with higher cardiovascular risks observed at progressively earlier menopausal age.8,9 Because the association between premature menopause and cardiovascular disease appears partially independent of traditional cardiovascular risk factors,9–11 multisociety cardiovascular guidelines now classify premature menopause as a “risk-enhancing factor” to guide allocation of primary-prevention statin therapy for women otherwise at intermediate risk of atherosclerotic cardiovascular disease.12,13
Despite the well-described cardiovascular risks associated with premature menopause, the responsible mechanisms remain unclear. Historically, increased cardiovascular risks were attributed to loss of cardioprotective estrogen effects; however, in a recent study, hormone therapy did not lower cardiovascular risks associated with premature menopause,9 and randomized trials of postmenopausal hormone replacement therapy have not specifically targeted women with premature menopause.14 Relevant mechanisms may extend beyond estrogen deficiency. In the largest genome-wide association study of age at natural (ie, nonsurgical) menopause to date, roughly two-thirds of genetic associations mapped to DNA damage repair pathways,15 implying that women with natural premature menopause may be predisposed to accumulate genetic damage; such damage or its downstream consequences may represent one mechanism of accelerated aging in women with natural premature menopause that may heighten cardiovascular disease risk.
Clonal hematopoiesis of indeterminate potential (CHIP) is the expansion of hematopoietic stem cells with somatic mutations in leukemia-associated genes, typically defined as a variant allele prevalence among circulating blood cells (ie, variant allele frequency [VAF]) >2% in the absence of detectable hematologic cytopenia, dysplasia, or malignancy.16,17 CHIP is a relatively common age-associated phenomenon, affecting 10% of individuals older than 70 years.18–20 CHIP-associated mutations occur most commonly in 1 of 3 genes: DNMT3A and TET2, both of which function as tumor suppressor genes through DNA methylation and demethylation, and ASXL1, a chromatin-binding transcriptional regulator.17 CHIP is associated with elevation in inflammatory cytokines and accelerated atherosclerosis in animal21,22 and human23,24 studies. Whether a history of premature menopause is associated with CHIP is unknown.
This study tested whether premature menopause overall and stratified by mechanism of menopause (natural and surgical premature menopause) was associated with elevated risk of CHIP among postmenopausal women in the UK Biobank and Women’s Health Initiative (WHI). We also investigated the association of CHIP with incident coronary artery disease (CAD) events in these cohorts.
Researchers may apply for UK Biobank data access (https://www.ukbiobank.ac.uk/). WHI data are available to investigators in dbGaP (accession number phs001237.v2.p1). The UK Biobank is a population-based cohort of >500 000 UK adult residents recruited between 2006 and 2010 and followed prospectively by linkage to national health records.25 At baseline, participants underwent phlebotomy and provided detailed information about medical history, medication use including previous and current hormone therapy, and reproductive history, including history of menarche, menopause, parity, and gynecologic surgery. In the present study, the UK Biobank cohort included postmenopausal women aged 40 to 70 years at blood draw with complete reproductive history data and available whole exome sequences. As described previously,24 the UK Biobank cohort was restricted to unrelated women of European ancestry. Follow-up in the UK Biobank occurred through March 2020 for inpatient diagnosis codes and May 2020 for the death register.
The WHI (URL: https://www.clinicaltrials.gov; Unique identifier: NCT00000611) is a prospective, multicenter study of women recruited at 40 centers throughout the United States between 1993 and 1998.26 Participants enrolled in a clinical trial (hormone therapy, calcium/vitamin D supplementation, or dietary modification) or in an observational study. A subsample of unrelated WHI women who were 50 to 79 years old at the time of phlebotomy and underwent whole genome sequencing as part of the National Heart, Lung, and Blood Institute TOPMed program (Trans-Omics for Precision Medicine; total n=11 023) were included in the present analysis.27 To avoid effects of study treatments on outcomes, women in the WHI hormone therapy trial with blood draw ≥2 years after the screening visit (n=486) were excluded. Follow-up in the WHI occurred through March 2019.
In both cohorts, related women within 3 degrees of relatedness were identified using the Kinship-Based Inference for Genome-Wide Association Studies tool28 and excluded. Women with incomplete, unknown, or discordant reproductive history data were also excluded (Figure 1). This research was conducted under UK Biobank application number 7089. All participants provided informed consent. The Massachusetts General Hospital Institutional Review Board approved secondary use of these data.
The primary exposure was premature menopause, defined as natural or surgical menopause occurring before age 40 years, for consistency with cardiovascular society guidelines,12,13 as ascertained by participant self-report. Natural premature menopause was defined as any menopause occurring before age 40 years not resulting from surgery. Natural premature menopause, surgical premature menopause, surgical menopause with bilateral oophorectomy versus hysterectomy only (to enable comparisons in women with ovarian conservation versus removal), age at menarche, parity, and nulliparity constituted secondary exposures. Reproductive history, medical conditions, medication use, and health habits were systematically ascertained at study enrollment in both cohorts, and anthropomorphic data and vital signs were measured by study staff.25,26
Sequencing and CHIP Detection
UK Biobank exomes were sequenced from whole blood–derived DNA at the Regeneron Sequencing Center (Tarrytown, NY).29 MuTect2 software30 analyzed exomes to detect somatic mutations in DNMT3A and TET2, using a predefined list of preleukemic CHIP driver mutations, in the UK Biobank (Table I in the Data Supplement).24 WHI whole genomes were sequenced from whole blood–derived DNA at the Broad Institute of Harvard and MIT (Cambridge, MA). MuTect2 software analyzed genomes for the presence of CHIP driver mutations in 74 genes in WHI (Table II in the Data Supplement).31 In both cohorts, common germline variants and sequencing artifacts were excluded as reported previously.24,31 Compared with whole genome sequencing (>30× sequencing depth), the greater depth of whole exome sequencing (>50×) affords greater sensitivity to detect CHIP clones with VAF ≤0.1.31 In the <1% of women with >1 CHIP mutation, the CHIP gene and VAF used in analyses were assigned based on the CHIP mutation with the largest VAF. Mosaic chromosomal alterations (mCAs) were generated from genotype array data among UK Biobank participants as previously described.32,33 Mutational signature analysis was performed using the MutationalPatterns package in R version 184.108.40.206
The co–primary study outcomes were the presence of any CHIP and CHIP with VAF >0.1, because larger CHIP clones above this threshold have previously been more strongly associated with adverse clinical outcomes.18,24 The 3 most commonly mutated CHIP drivers (DNMT3A, TET2, and ASXL1) were each tested as separate secondary outcomes.
Additional models tested the association of CHIP with incident CAD. Incident CAD was defined in the UK Biobank by the appearance of a qualifying International Classification of Diseases code in the study record as used previously9,35 with International Classification of Diseases codes corresponding to acute myocardial infarction and coronary artery revascularization (Table III in the Data Supplement) and in WHI as a composite of fatal and nonfatal myocardial infarction or coronary artery revascularization using standardized physician review, classification, and adjudication as previously described.36
Participant characteristics were compared between women with versus without a history of premature menopause for continuous variables using the Student t test or Wilcoxon rank-sum test, as appropriate, and for categorical variables using the Pearson χ2 test or Fisher exact test. Primary analyses tested the association of premature menopause with CHIP, for both UK Biobank and WHI, using multivariable logistic regression models, adjusted for age, the first 10 principal components of ancestry, current or former tobacco use, diabetes, and a history of current or previous hormone therapy use. Models testing associations among WHI participants were also adjusted for race/ethnicity, enrollment in the WHI observational study versus clinical trial, and whether women were randomized to hormone therapy versus placebo. To account for diabetes status, models of UK Biobank participants were adjusted for type 2 diabetes; because diabetes subtypes were not available in WHI, models of WHI participants were adjusted for any treated diabetes. For primary analyses, models were run separately in each cohort and meta-analyzed with fixed effects models using the rmeta package in R 3.6.0. We conducted a variety of sensitivity analyses, including adjusting for body mass index; excluding women with history of cancer, women with history of gynecologic surgery, and women enrolled in the WHI hormone therapy trial; and stratifying by age <70 years (middle age) versus ≥70 years at blood draw. In exploratory analyses, we tested the association of hormone therapy use with CHIP using logistic regression with the same covariates as the primary analyses, stratified by age at menopause.
Additional models tested the association of CHIP with incident CAD using Cox proportional hazard models, adjusted for age, the first 10 principal components of ancestry, current or former tobacco use, prevalent diabetes, systolic blood pressure, antihypertensive medication use, cholesterol-lowering medication use, body mass index, previous hysterectomy, and a history of previous hormone therapy use; WHI models were further adjusted for race/ethnicity, enrollment in the WHI observational study versus clinical trial, whether women were randomized to hormone therapy, and an inverse probability weight37 (to account for the nonrandom selection of women for whole genome sequencing in WHI). Follow-up began at blood draw and women with CAD diagnosed before blood draw were excluded from incident CAD analyses. Incident CAD models for WHI participants were also stratified by age <70 years versus ≥70 years at blood draw. The proportional hazards assumption was tested using Schoenfeld residuals. Analyses were performed separately in each cohort and meta-analyzed using fixed effects models.
Given 2 primary outcomes in prevalent CHIP analyses and 2 primary exposures in incident CAD analyses, 2-sided P<0.05/4=0.0125 was considered statistically significant. Findings of secondary analyses should be considered exploratory. Analyses were conducted using R 3.6.0 (R Foundation for Statistical Computing, Vienna, Austria).
Description of the Study Cohort
The final study sample included 19 606 postmenopausal women across both cohorts, including 418 (2.1%) with natural premature menopause and 887 (4.5%) with surgical premature menopause. The UK Biobank cohort included 11 495 postmenopausal women aged 40 to 70 years at blood draw with complete reproductive history data and available whole exome sequences (Figure 1). The WHI cohort included 8111 postmenopausal women with available whole genome sequences from peripheral blood DNA using blood drawn at age 50 to 79 years. Mean (SD) age at blood draw for whole exome and whole genome sequencing was 60.1 (5.2) years in the UK Biobank and 68.3 (6.6) years in WHI, respectively. The WHI cohort included 6733 (83.0%) White, 918 (11.3%) Black, 217 (2.7%) Hispanic, and 157 (1.9%) Asian/Pacific Islander women.
In the UK Biobank, 390 women (3.4%) had a history of premature menopause, of whom 178 (1.5%) had natural premature menopause and 212 (1.8%) had surgical premature menopause (46 [0.4%] with bilateral oophorectomy ± hysterectomy versus 166 [1.4%] with hysterectomy alone). In WHI, 915 women (11.3%) had a history of premature menopause, of whom 240 (3.0%) had natural premature menopause and 675 (8.3%) had surgical premature menopause (511 [6.3%] with bilateral oophorectomy ± hysterectomy versus 164 [2.0%] with hysterectomy alone). In both cohorts, compared with women without a history of premature menopause, women with a history of premature menopause were 1.2 years younger at blood draw on average, were more likely to be current or former tobacco users, were more likely to be taking antihypertensive medications, and had higher baseline prevalence of diabetes and CAD (Table 1).
|Characteristics||UK Biobank (n=11 495)||Women’s Health Initiative (n=8111)|
|Menopause at age <40 y (n=390)||Menopause at age ≥40 y (n=11 105)||P value||Menopause at age <40 y (n=915)||Menopause at age ≥40 y (n=7196)||P value|
|Age at blood draw, y||58.9 (6.6)||60.1 (5.2)||<0.001||67.3 (6.5)||68.5 (6.5)||<0.001|
|White||390 (100)||11 105 (100)||681 (74.4)||6052 (84.1)|
|Black||0 (0)||0 (0)||180 (19.7)||738 (10.3)|
|Hispanic||0 (0)||0 (0)||22 (2.4)||195 (2.7)|
|Asian||0 (0)||0 (0)||12 (1.3)||145 (2.0)|
|American Indian/Alaskan Native||0 (0)||0 (0)||11 (1.2)||17 (0.2)|
|Unknown||0 (0)||0 (0)||9 (1.0)||49 (0.7)|
|Age at menarche, y||12.8 (1.8)||12.9 (1.6)||0.19||12.5 (1.5)||12.7 (1.3)||0.008|
|Age at menopause, y||35.1 (4.1)||50.5 (4.2)||<0.001||34.3 (3.6)||49.8 (1.9)||<0.001|
|Parity||2 (1, 2)||2 (1, 2)||0.77||3 (2, 4)||3 (2, 4)||<0.001|
|Nulliparity||63 (16.2)||1913 (17.2)||0.63||38 (4.8)||138 (2.1)||<0.001|
|History of hysterectomy||225 (57.7)||921 (8.3)||<0.001||770 (84.2)||2402 (33.4)||<0.001|
|History of bilateral oophorectomy||64 (16.4)||543 (4.9)||<0.001||498 (54.4)||1428 (19.8)||<0.001|
|Ever use of hormone therapy||300 (76.9)||5009 (45.2)||<0.001||701 (78.9)||4169 (59.2)||<0.001|
|Current use of hormone therapy||59 (15.1)||692 (6.2)||<0.001||365 (41.1)||2238 (31.8)||<0.001|
|Duration of hormone therapy use (among hormone therapy users)||9.1 (6.7)||5.6 (4.5)||<0.001||15.3 (12.5)||8.8 (8.1)||<0.001|
|Current or former smoking||203 (52.1)||4578 (41.2)||<0.001||483 (53.1)||3464 (48.8)||0.01|
|Type 2 diabetes mellitus||15 (3.8)||177 (1.6)||0.001||92 (10.1)||452 (6.3)||<0.001|
|Coronary artery disease||19 (4.9)||281 (2.5)||0.007||127 (13.9)||728 (10.1)||<0.001|
|History of cancer||70 (18.1)||1197 (10.8)||<0.001||98 (10.8)||467 (6.5)||<0.001|
|Antihypertensive medication use||98 (25.1)||2125 (19.1)||0.004||388 (42.4)||2350 (32.6)||<0.001|
|Cholesterol-lowering medication use||88 (22.6)||1673 (15.1)||<0.001||152 (16.6)||1063 (14.8)||0.16|
|Body mass index, kg/m2||28.5 (6.3)||26.9 (4.9)||<0.001||29.9 (6.3)||28.5 (6.0)||<0.001|
|Systolic blood pressure, mm Hg||139.7 (20.1)||140.5 (20.1)||0.46||133.6 (19.0)||132.0 (18.3)||0.02|
|Low-density lipoprotein cholesterol, mg/dL||142.8 (34.6)||144.6 (33.3)||0.34||140.3 (39.4)||142.9 (37.2)||0.14|
|High-density lipoprotein cholesterol, mg/dL||61.3 (15.3)||64.0 (14.7)||0.001||55.4 (15.7)||56.2 (15.3)||0.25|
|Triglycerides, mg/dL||134.5 (93.7, 186.5)||122.0 (89.9, 168.9)||0.001||140.0 (100.0, 195.0)||135.0 (95.0, 185.0)||0.17|
|C-reactive protein, mg/L||2.1 (0.9, 4.1)||1.4 (0.7, 2.8)||<0.001||—||—||—|
|Women’s Health Initiative observational study||—||—||—||399 (43.6)||3222 (44.8)||0.53|
|Any Women’s Health Initiative clinical trial||—||—||—||516 (56.4)||3974 (55.2)||0.53|
|Women’s Health Initiative hormone trial||—||—||—||301 (32.9)||2348 (32.6)||0.90|
Prevalence of CHIP
Consistent with the older age of women enrolled and greater number of CHIP drivers ascertained in WHI, CHIP prevalence was greater in WHI compared with the UK Biobank: 698 (8.6%; including 533 of 698 [76.4%] with DNMT3A or TET2 mutations) in WHI had CHIP versus 415 (3.6%) in the UK Biobank (P<0.001; Table IV in the Data Supplement). In the UK Biobank, 172 women with CHIP (41.4% of 415) had large clones (ie, VAF >0.1). By contrast, 598 women with CHIP (85.7% of 698) in WHI had large CHIP clones, likely because of older age and decreased sensitivity of whole genome sequencing (compared with whole exome sequencing) for detecting smaller clones. The most commonly mutated CHIP driver gene was DNMT3A in both cohorts, accounting for 342 (82.4% of 415) CHIP cases in the UK Biobank and 404 (57.9% of 698) CHIP cases in WHI. After DNMT3A, the most common CHIP drivers in WHI were TET2 (129 [18.5%]), ASXL1 (51 [7.3%]), and JAK2 (26 [3.7%]). CHIP prevalence increased progressively with older chronologic age (Figure 2). In WHI, American Indian/Alaskan Native women had 2.56-fold adjusted prevalence of CHIP versus White women, although this association was not statistically significant (95% CI, 0.86–7.67; P=0.09); no other significant associations with race/ethnicity were observed (Table V in the Data Supplement).
Premature Menopause and Clonal Hematopoiesis
The overall pooled prevalence of CHIP across cohorts was 8.8% (115/1305) among women with a history of premature menopause and 5.5% (998/18 301) among women without a history of premature menopause (P<0.001). Crude CHIP prevalence progressively increased with earlier age at menopause (Figure I in the Data Supplement). CHIP prevalence was greater in women with versus without premature menopause irrespective of age at blood draw (Figure 2); differences in CHIP prevalence were more pronounced for CHIP with VAF >0.1 (Figure II in the Data Supplement).
Multivariable-adjusted associations between premature menopause and CHIP were similar in the UK Biobank and WHI (Figure 3). Premature menopause was associated with all CHIP with an odds ratio (OR) of 1.35 (95% CI, 0.83–2.17; P=0.22) in the UK Biobank and an OR of 1.36 (95% CI, 1.07–1.73; P=0.01) in WHI, yielding a meta-analyzed OR of 1.36 (95% CI, 1.10–1.68; P=0.004; P [heterogeneity]=0.97) in our primary analysis. This association appeared to be driven primarily by a stronger association between natural premature menopause and CHIP (meta-analyzed OR, 1.73 [95% CI, 1.23–2.44]; P=0.001; P [heterogeneity]=0.86) compared with the observed relationship between surgical premature menopause and CHIP (meta-analyzed OR, 1.21 [95% CI, 0.93–1.57]; P=0.15; P [heterogeneity]=0.81). For CHIP with VAF >0.1, the association with natural premature menopause appeared even stronger (UK Biobank: OR, 2.72 [95% CI, 1.17–6.29]; P=0.02; WHI: OR, 1.75 [95% CI, 1.13–2.69]; P=0.01; meta-analyzed OR, 1.91 [95% CI, 1.30–2.80]; P<0.001; P [heterogeneity]=0.26), whereas there was no evidence of association with surgical premature menopause.
Among women with a history of surgical premature menopause, associations with CHIP were similar and nonsignificant among women who underwent bilateral oophorectomy with or without hysterectomy versus those who underwent hysterectomy alone (Table VI in the Data Supplement). Age at menarche, parity, and nulliparity were not significantly associated with CHIP in either cohort. Associations were not materially changed after further adjustment for body mass index (Table VII in the Data Supplement). Sensitivity analyses excluding women with cancer showed results consistent with the primary analyses (Table VIII in the Data Supplement). Sensitivity analyses excluding women with any history of gynecologic surgery and women enrolled in the WHI hormone therapy trial also yielded similar results. When the WHI cohort was stratified by age at blood draw <70 years versus ≥70 years, associations among women <70 years were stronger and more closely resembled those observed in the UK Biobank cohort (all <70 years old at blood draw), while associations among older women in WHI were attenuated (Table IX in the Data Supplement).
We next compared patterns of somatic mutations among women with CHIP by premature menopause status in the UK Biobank using the Catalogue of Somatic Mutations in Cancer mutational signatures.38,39 Among those with CHIP, mutational signatures were similar among women with natural premature menopause, surgical premature menopause, and no premature menopause; the most common mutational signatures across all 3 groups were defective homologous recombination DNA damage repair, age-related spontaneous deamination of 5-methylcytosine, and defective DNA mismatch repair (Figure III in the Data Supplement).39
Having established an association between premature menopause and CHIP, we next assessed whether premature menopause was associated more strongly with specific CHIP genes (Table X in the Data Supplement). Women with natural premature menopause had particular enrichment in DNMT3A CHIP (all DNMT3A CHIP: meta-analyzed OR, 1.97 [95% CI, 1.34–2.92]; P<0.001; P [heterogeneity]=0.78; DNMT3A CHIP with VAF >0.1: meta-analyzed OR, 2.28 [95% CI, 1.45–3.56]; P<0.001; P [heterogeneity]=0.48), but DNMT3A CHIP showed no evidence of association with surgical premature menopause. Natural premature menopause was not associated with TET2 or ASXL1 CHIP. Consistent with known selection from chemotherapy, PPM1D and TP53 CHIP were enriched among women with CHIP with versus without a history of cancer in WHI (8.8% versus 3.9%; P=0.06). Among women without previous cancer, no women with premature menopause had TP53 CHIP; no women with natural premature menopause had PPM1D CHIP; and 2 women with surgical premature menopause (3.8% of 53 with CHIP) had PPM1D CHIP, similar to the proportion of women without premature menopause with PPM1D CHIP (17 [3.1%] of 549).
Women with premature menopause and CHIP had higher red blood cell distribution width and lower platelet counts compared with other women (Table XI in the Data Supplement). C-reactive protein levels were higher in women with premature menopause irrespective of CHIP status. Among women in the UK Biobank, in an exploratory model adjusted for age, the first 10 principal components of ancestry, and smoking status, premature menopause was associated with 3-fold risk for myeloid dysplasia and neoplasia (hazard ratio [HR], 2.98 [95% CI, 1.06–8.38]; P=0.04).
Given observed associations between premature menopause and CHIP, we tested whether premature menopause was associated with other clonal somatic phenomena. Mosaic chromosomal alterations (mCAs) were previously ascertained among UK Biobank participants using single nucleotide polymorphism array data.32,33 Among 147 573 genotyped postmenopausal women in the UK Biobank with complete reproductive history data, premature menopause was associated with 1.3-fold risk of mCA with cell fraction >0.1 (OR, 1.31 [95% CI, 1.01–1.70]; P=0.04), driven by a 2-fold increase in chromosome X mCA with cell fraction >0.1 among women with natural premature menopause (OR, 2.07 [95% CI, 1.06–4.04]; P=0.03; Table XII in the Data Supplement). The proportion of women with mCAs was similar among those with CHIP (3.9%) and without CHIP (3.5%; P=0.57).
Association of Hormone Therapy Use With CHIP
In multivariable-adjusted models, ever use and current use of hormone therapy at study enrollment were associated with increased odds of CHIP in the UK Biobank (ever use: OR, 1.26 [95% CI, 1.03–1.54]; P=0.03; current use: OR, 1.88 [95% CI, 1.33–2.59]; P<0.001), but neither was significantly associated with CHIP in WHI (ever use: OR, 1.08 [95% CI, 0.91–1.26]; P=0.36; current use: OR, 0.96 [95% CI, 0.81–1.14]; P=0.99). Because women with premature menopause are more likely to use hormone therapy than other women, we assessed whether the association with hormone therapy observed in the UK Biobank reflected residual confounding by an indication of premature menopause and whether the association of hormone therapy with CHIP differed by menopausal age. In the UK Biobank, multivariable-adjusted analyses stratified by age at menopause suggested that current or previous use of hormone therapy at study enrollment were associated with increased in risk of CHIP only among women without premature menopause (Table XIII in the Data Supplement), and specifically among women with menopause after age 50 years. WHI participants had no increased or decreased risk of CHIP associated with previous or current hormone therapy use at study enrollment in any age stratum.
Association Between CHIP and Incident CAD
Follow-up for incident CAD events (myocardial infarction or coronary revascularization) occurred over a median (interquartile range) 10.0 (9.8 to 10.2) years in the UK Biobank and 13.1 (6.8 to 18.8) years in WHI. There were 473 incident CAD cases in the UK Biobank and 1146 incident CAD cases in WHI.
After multivariable adjustment, estimated associations between CHIP and incident CAD were similar among women in the UK Biobank (for all CHIP: HR 1.31 [95% CI, 0.87–1.99]; P=0.20; for CHIP with VAF >0.1: HR 1.56 [95% CI, 0.88–2.78]; P=0.13) and among middle-aged women (<70 years old at blood draw) in WHI (for all CHIP: HR 1.38 [95% CI, 1.03–1.86]; P=0.03; for CHIP with VAF >0.1: HR 1.45 [95% CI, 1.07–1.98]; P=0.02). By contrast, no association for CHIP with incident CAD was present among women ≥70 years old at blood draw (Table XIV in the Data Supplement; P [interaction] for age <70 versus ≥70 years × CHIP with VAF >0.1=0.06). In meta-analyzed models of women in the UK Biobank and women <70 years old in WHI, all CHIP was associated with an HR of 1.36 (95% CI, 1.07–1.73; P=0.012; P [heterogeneity]=0.85) and CHIP with VAF >0.1 with an HR of 1.48 (95% CI, 1.13–1.94; P=0.005; P [heterogeneity]=0.83; Figure 4). The association between CHIP and incident CAD was attenuated for VAF <0.1 (Figure IV in the Data Supplement).
In models for incident CAD that were further adjusted for premature menopause status, the association with incident CAD was unchanged (meta-analyzed HR, 1.36 [95% CI, 1.07–1.73]; P=0.01; P [heterogeneity]=0.84). Across cohorts, cumulative CAD incidence (among women without prevalent CAD) was 8.3% (1352/16 376) in women without premature menopause or CHIP, 12.5% (132/1056) in women with premature menopause only, 13.0% (119/916) in women with CHIP only, 15.4% (97/629) in women with CHIP with VAF >0.1 only, 15.5% (16/103) in women with premature menopause and any CHIP, and 17.3% (14/81) in women with premature menopause and CHIP with VAF >0.1 (P<0.001; Table 2). Compared with women without premature menopause or CHIP, women with both (n=103 without prevalent CAD) had a meta-analyzed adjusted HR for incident CAD of 1.57 (95% CI, 0.83–2.97; P=0.17; P [heterogeneity]=0.49), and women with premature menopause and CHIP with VAF >0.1 (n=81) had a meta-analyzed HR of 1.87 (95% CI, 0.99–3.53; P=0.053; P [heterogeneity]=0.87). Sensitivity analysis in WHI restricted to women who were <70 years old at blood draw and not enrolled in the hormone trial (n=2669) confirmed that study treatments did not drive the observed associations with CHIP: all CHIP was associated with an HR of 1.48 (95% CI, 1.00–2.18; P=0.05) and CHIP with VAF >0.1 was associated with an HR of 1.54 (95% CI, 1.02–2.33; P=0.04). Mosaic chromosomal alterations were not associated with incident CAD (all mCAs: HR, 0.84 [95% CI, 0.61–1.14]; P=0.25; mCAs with cell fraction >0.1: HR, 1.04 [95% CI, 0.39–2.78]; P=0.95). CHIP was associated with all-cause mortality (all CHIP: meta-analyzed HR, 1.18 [95% CI, 1.06–1.31]; P=0.003, P [heterogeneity]=0.29; CHIP with VAF >0.1: HR, 1.20 [95% CI, 1.07–1.34]; P=0.001, P [heterogeneity]=0.31).
|History of premature menopause||No CHIP||Any CHIP||CHIP with VAF >0.1|
|No||8.3% (1352/16 376)||13.0% (119/916)||15.4% (97/629)|
|Yes||12.5% (132/1056)||15.5% (16/103)||17.3% (14/81)|
A history of premature menopause, especially natural premature menopause, was independently associated with increased odds of CHIP, a recently recognized risk factor for cardiovascular disease, in 2 large cohorts of postmenopausal women with whole exome or genome sequencing of blood DNA. The risks of developing CHIP and specific CHIP driver mutations appeared to differ in women with natural versus surgical premature menopause, implying that postmenopausal reductions in estrogen and other sex steroid hormones alone may not explain the relationship between menopause and CHIP. Premature menopause was more strongly associated with CHIP with VAF >0.1, which was more strongly linked to adverse clinical outcomes in this and previous studies compared with smaller CHIP clones. Furthermore, CHIP was associated with incident CAD in postmenopausal middle-aged women independent of conventional risk factors, extending CHIP’s role as an atherosclerotic cardiovascular disease risk factor to postmenopausal women.
These findings have several key implications for understanding the biological relevance of CHIP in postmenopausal women. First, menopausal age represents a novel risk signal for development of CHIP beyond chronologic age. Independent of established CHIP risk factors, premature menopause was associated with 1.4-fold odds—and natural premature menopause with 1.7-fold odds—of CHIP. Chronologic age, tobacco smoking, and previous exposure to chemotherapy and radiation represent the strongest risk factors for CHIP,18,40 but our understanding of clinical factors predisposing to CHIP development is otherwise limited. As evidence-based strategies for mitigation of CHIP-associated cardiovascular and cancer risks emerge, and as genomic sequencing becomes increasingly accessible, identification of individuals suitable for CHIP screening will become increasingly clinically relevant.41,42 History of premature menopause may help identify individuals for CHIP screening and surveillance. Although the present analysis is cross-sectional, previous studies have found very low CHIP prevalence (<0.1%) among individuals younger than age 40 years18–20—substantially lower than the prevalence of premature menopause in the present cohort and previous cohorts of postmenopausal women8,9,43—suggesting that premature menopause likely occurs antecedent to CHIP development. However, the differential association of premature natural versus premature surgical menopause with CHIP lends to the possibility of CHIP occurring before premature menopause. Future studies with premenopausal CHIP ascertainment will better clarify this temporal relationship.
The association between premature menopause and CHIP provides insights into potential mechanisms of CHIP development in women. Previous work shows that hematopoietic stem cells possess receptors for sex hormones, including estrogen,44,45 and that estrogen signaling promotes stem cell renewal46 and exhibits anti-leukemogenic properties.47,48 We observed that women with natural premature menopause had consistently higher risk of CHIP in both cohorts. However, women with or without bilateral oophorectomy (ie, removal of the primary source of estrogen) at the time of surgical premature menopause had similar risk of CHIP, suggesting that hormonal deficiency alone does not account for the mechanism of CHIP development. DNA damage repair pathways account for two-thirds of identified genetic determinants of age at natural menopause.15 Genome-wide association studies of age at natural menopause15 have implicated loss-of-function variants in CHEK2, a DNA damage checkpoint kinase.31 Furthermore, genetic variants in TERT, which encodes telomerase, associate strongly with CHIP31,49 as well as other cancers. Telomeres are key regulators of genomic stability and cellular senescence. TERT variants also link to accelerated epigenetic aging and earlier age at natural menopause.50 Natural premature menopause may reflect a latent predisposition to accumulation of somatic mutations or attrition of stem cells in both the ovaries and the bone marrow, in turn enabling selective advantage of CHIP clones. In other words, natural premature menopause may serve as a risk signal for predilection to CHIP development. We also observed enrichment of mosaic chromosomal alterations in women with natural premature menopause, suggesting natural premature menopause may be associated with a variety of clonal somatic phenomena not limited to CHIP and further supporting that natural premature menopause may indicate genomic instability more broadly. Fanconi anemia, a Mendelian syndrome attributable to defects in DNA damage repair, is characterized by infertility and extremely premature spontaneous menopause,51 accelerated development of hematologic and solid malignancy, and predilection to atherosclerosis.
We found that exogenous postmenopausal hormone use was associated with increased risk of CHIP among women in the UK Biobank who experienced menopause later in life. Compared with younger women using hormone therapy after early menopause, older women may have accumulated a greater burden of somatic mutations that may be positively selected in the setting of continued estrogen exposure. This premise represents one potential explanation for the timing hypothesis of hormone therapy, whereby increased cardiovascular risk associated with exogenous hormone therapy primarily affects women >60 years old and >10 years beyond menopause,52 although this possibility requires further testing in human cohorts and animal models. Our observation of DNMT3A CHIP predilection agrees with previous work demonstrating an inverse relationship between DNMT3A gene expression and cellular activation by estrogen in normal and tumor tissues.53–58
CHIP represents an independent risk factor for incident CAD events among postmenopausal women. An association between CHIP and incident cardiovascular events was recently demonstrated for a composite outcome of myocardial infarction, coronary artery revascularization, stroke, and death among 35 000 male and female individuals in the UK Biobank,24 but whether this association was relevant among women, who have a lower absolute risk of cardiovascular disease, was unclear. Here, we find an association with incident CAD among postmenopausal middle-aged women. Although CHIP is strongly associated with chronologic age, we did not observe an independent association between CHIP and incident CAD among elderly women (≥70 years old); this finding may reflect a greater relative effect of CHIP compared with other conventional risk factors for earlier-onset CAD as suggested by previous cross-sectional analyses,23 exclusion of women with prevalent CAD (which was more common in women with CHIP) from incident disease models, or survival bias, as is commonly observed in epidemiologic cohort studies. Much mechanistic work linking CHIP to atherothrombotic events has focused on TET2 CHIP and resultant interleukin-1β/interleukin-6 pathway activation predisposing to atherosclerosis.21,23 However, recent studies implicate the same atherogenic inflammatory cytokines with DNMT3A CHIP as well.59,60 A stratified human genetic analysis recently showed that individuals with CHIP are more likely to derive clinical cardiovascular benefit with interleukin-1β/interleukin-6 pathway inhibition.24 Therefore, women with premature menopause may particularly benefit from earlier CHIP screening with the prospect of a novel molecularly guided preventive strategy. Affirmation of this hypothesis will require prospective randomized controlled trials.
Our study has several limitations. Whereas CHIP was ascertained only in DNMT3A and TET2 in the UK Biobank, these genes constituted the majority (76%) of CHIP drivers in the WHI cohort and in previous analyses.18,23 The UK Biobank study cohort included women of European ancestry only. Although the UK Biobank and WHI differed with respect to age, racial/ethnic composition, the era during which women experienced menopause, associated practices surrounding gynecologic surgery and use of hormone therapy, DNA sequencing methods, and CHIP drivers queried, associations between premature menopause and CHIP and between CHIP and incident CAD were nonetheless highly consistent between the cohorts. Age at menopause was ascertained by participant self-report in both cohorts, which may be inaccurate, particularly among older women who are further from menopause; however, such misclassification would be expected to minimize observed differences and bias results toward the null. Doses and preparations of hormone therapy used before study enrollment were not available; differences in these aspects of hormone therapy use may explain differential associations between hormone therapy and CHIP observed between cohorts. Finally, although multiple previous studies have shown that premature and early menopause independently associate with elevated risk of CAD,7,9,61,62 premature menopause was not independently associated with CAD after covariate adjustment in the present dataset, precluding formal mediation analysis. This is likely because of reduced sample size of women with next-generation sequencing compared with previous larger epidemiologic studies. However, given the observed enrichment for CHIP among women with premature menopause, CHIP-associated CAD risk may be particularly important among some women with premature menopause.
Premature menopause, especially natural premature menopause, is independently associated with CHIP among postmenopausal women. CHIP may contribute to the excess cardiovascular risk associated with premature menopause. These findings should stimulate further research to elucidate mechanisms of CHIP development in this population.
The Women’s Health Initiative program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, US Department of Health and Human Services through contracts HHSN268201600018C, HHSN268201600001C, HHSN268201600002C, HHSN268201600003C, and HHSN268201600004C. Molecular data gathering for the TOPMed program (Trans-Omics for Precision Medicine) was supported by the National Heart, Lung, and Blood Institute. Genome sequencing for the National Heart, Lung, and Blood Institute TOPMed: Women’s Health Initiative (phs001237.v2.p1) was performed at the Broad Institute Genomics Platform (contract HHSN268201500014C). Core support including centralized genomic read mapping and genotype calling, along with variant quality metrics and filtering, were provided by the TOPMed Informatics Research Center (grant 3R01HL-117626-02S1; contract HHSN268201800002I). Core support including phenotype harmonization, data management, sample-identity quality control, and general program coordination were provided by the TOPMed Data Coordinating Center (grant R01HL-120393; grant U01HL-120393; contract HHSN268201800001I). The authors thank the studies and participants who provided biological samples and data for TOPMed.
Sources of Funding
Dr Honigberg is supported by the National Institutes of Health (grant T32HL094301-07). Dr Pirruccello is supported by a John S. LaDue Memorial Fellowship in Cardiovascular Research. Dr Reiner, Dr Whitsel, and Dr Natarajan are supported by the National Heart, Lung, and Blood Institute (grant R01 HL148565). Dr Natarajan is supported by grants from the National Heart, Lung, and Blood Institute (grants R01HL142711, R01HL148565, and R01HL148050), Fondation Leducq (grant TNE-18CVD04), and a Hassenfeld award from the Massachusetts General Hospital. Dr Libby receives funding support from the National Heart, Lung, and Blood Institute (grant R01 HL134892), the American Heart Association (grant 18CSA34080399), the RRM Charitable Fund, and the Simard Fund.
Data Supplement Figures I–IV
Data Supplement Tables I–XIV
Disclosures Dr Natarajan reports grant support from Amgen, Apple, and Boston Scientific; consulting income from Apple; and spousal employment and equity in Vertex, all unrelated to this work. Dr Libby is an unpaid consultant to, or involved in clinical trials for, Amgen, AstraZeneca, Baim Institute, Beren Therapeutics, Esperion, Therapeutics, Genentech, Kancera, Kowa Pharmaceuticals, Medimmune, Merck, Norvo Nordisk, Merck, Novartis, Pfizer, and Sanofi-Regeneron. Dr Libby is a member of scientific advisory boards for Amgen, Corvidia Therapeutics, DalCor Pharmaceuticals, Kowa Pharmaceuticals, Olatec Therapeutics, Medimmune, Novartis, and XBiotech, Inc. Dr Libby’s laboratory has received research funding in the last 2 years from Novartis. Dr Libby is on the Board of Directors of XBiotech, Inc. Dr. Libby has a financial interest in XBiotech, a company developing therapeutic human antibodies. Dr. Libby’s interests were reviewed and are managed by Brigham and Women’s Hospital and Partners HealthCare in accordance with their conflict of interest policies. The other authors report no conflicts.
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