Chronic obstructive pulmonary disease (COPD) is associated with age and smoking, but other determinants of the disease are incompletely understood. Clonal hematopoiesis of indeterminate potential (CHIP) is a common, age-related state in which somatic mutations in clonal blood populations induce aberrant inflammatory responses. Patients with CHIP have an elevated risk for cardiovascular disease, but the association of CHIP with COPD remains unclear. We analyzed whole-genome sequencing and whole-exome sequencing data to detect CHIP in 48 835 patients, of whom 8444 had moderate to very severe COPD, from four separate cohorts with COPD phenotyping and smoking history. We measured emphysema in murine models in which Tet2 was deleted in hematopoietic cells. In the COPDGene cohort, individuals with CHIP had risks of moderate-to-severe, severe, or very severe COPD that were 1.6 (adjusted 95% confidence interval [CI], 1.1-2.2) and 2.2 (adjusted 95% CI, 1.5-3.2) times greater than those for noncarriers. These findings were consistently observed in three additional cohorts and meta-analyses of all patients. CHIP was also associated with decreased FEV1% predicted in the COPDGene cohort (mean between-group differences, −5.7%; adjusted 95% CI, −8.8% to −2.6%), a finding replicated in additional cohorts. Smoke exposure was associated with a small but significant increased risk of having CHIP (odds ratio, 1.03 per 10 pack-years; 95% CI, 1.01-1.05 per 10 pack-years) in the meta-analysis of all patients. Inactivation of Tet2 in mouse hematopoietic cells exacerbated the development of emphysema and inflammation in models of cigarette smoke exposure. Somatic mutations in blood cells are associated with the development and severity of COPD, independent of age and cumulative smoke exposure.

More reliable and faster prediction methods are needed to interpret enormous amounts of data generated by sequencing and genome projects. We have developed a new computational tool, PON-P2, for classification of amino acid substitutions in human proteins. The method is a machine learning-based classifier and groups the variants into pathogenic, neutral and unknown classes, on the basis of random forest probability score. PON-P2 is trained using pathogenic and neutral variants obtained from VariBench, a database for benchmark variation datasets. PON-P2 utilizes information about evolutionary conservation of sequences, physical and biochemical properties of amino acids, GO annotations and if available, functional annotations of variation sites. Extensive feature selection was performed to identify 8 informative features among altogether 622 features. PON-P2 consistently showed superior performance in comparison to existing state-of-the-art tools. In 10-fold cross-validation test, its accuracy and MCC are 0.90 and 0.80, respectively, and in the independent test, they are 0.86 and 0.71, respectively. The coverage of PON-P2 is 61.7% in the 10-fold cross-validation and 62.1% in the test dataset. PON-P2 is a powerful tool for screening harmful variants and for ranking and prioritizing experimental characterization. It is very fast making it capable of analyzing large variant datasets. PON-P2 is freely available at http://structure.bmc.lu.se/PON-P2/.

Background and Purpose: Clonal hematopoiesis of indeterminate potential (CHIP) is a novel age-related risk factor for cardiovascular disease–related morbidity and mortality. The association of CHIP with risk of incident ischemic stroke was reported previously in an exploratory analysis including a small number of incident stroke cases without replication and lack of stroke subphenotyping. The purpose of this study was to discover whether CHIP is a risk factor for ischemic or hemorrhagic stroke. Methods: We utilized plasma genome sequence data of blood DNA to identify CHIP in 78 752 individuals from 8 prospective cohorts and biobanks. We then assessed the association of CHIP and commonly mutated individual CHIP driver genes ( DNMT3A , TET2 , and ASXL1 ) with any stroke, ischemic stroke, and hemorrhagic stroke. Results: CHIP was associated with an increased risk of total stroke (hazard ratio, 1.14 [95% CI, 1.03–1.27]; P =0.01) after adjustment for age, sex, and race. We observed associations with CHIP with risk of hemorrhagic stroke (hazard ratio, 1.24 [95% CI, 1.01–1.51]; P =0.04) and with small vessel ischemic stroke subtypes. In gene-specific association results, TET2 showed the strongest association with total stroke and ischemic stroke, whereas DMNT3A and TET2 were each associated with increased risk of hemorrhagic stroke. Conclusions: CHIP is associated with an increased risk of stroke, particularly with hemorrhagic and small vessel ischemic stroke. Future studies clarifying the relationship between CHIP and subtypes of stroke are needed.

Osteoporosis is caused by an imbalance of osteoclasts and osteoblasts, occurring in close proximity to hematopoietic cells in the bone marrow. Recurrent somatic mutations that lead to an expanded population of mutant blood cells is termed clonal hematopoiesis of indeterminate potential (CHIP). Analyzing exome sequencing data from the UK Biobank, we found CHIP to be associated with increased incident osteoporosis diagnoses and decreased bone mineral density. In murine models, hematopoietic-specific mutations in Dnmt3a, the most commonly mutated gene in CHIP, decreased bone mass via increased osteoclastogenesis. Dnmt3a−/− demethylation opened chromatin and altered activity of inflammatory transcription factors. Bone loss was driven by proinflammatory cytokines, including Irf3-NF-κB–mediated IL-20 expression from Dnmt3a mutant macrophages. Increased osteoclastogenesis due to the Dnmt3a mutations was ameliorated by alendronate or IL-20 neutralization. These results demonstrate a novel source of osteoporosis-inducing inflammation.

Background: 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. Methods: 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. Results: 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 0.1: 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 0.1: 1.48 [95% CI, 1.13–1.94]; P =0.005). Conclusions: 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.