Background Laboratory studies suggest that urinary uromodulin, the most common protein in the urine of healthy adults, may protect against urinary tract infection (UTI). Epidemiologic studies ...evaluating this relationship in humans are lacking. Study Design Prospective longitudinal cohort study. Setting & Participants 953 participants enrolled in the Cardiovascular Health Study. Predictor Uromodulin assayed using enzyme-linked immunosorbent assay in spot urine samples. Outcomes Composite of outpatient UTI events or UTI-related hospitalizations and each of them individually identified using International Classification of Diseases, Ninth Revision ( ICD-9 ) codes using negative binomial regression with robust standard errors adjusted for age, race, sex, body mass index, diabetes, estimated glomerular filtration rate, and urinary albumin and urinary creatinine excretion. Results Median uromodulin level was 25.9 (IQR, 17.3-38.9) μg/mL, mean age of participants was 78 years, 61% were women, and 15% were black. There were 331 outpatient UTI events and 87 UTI-related hospitalizations among 186 participants during a median 9.9 years of follow-up. Persons in the highest quartile (>38.93 μg/mL) of uromodulin concentration had a significantly lower risk for the composite outcome (incidence rate ratio IRR, 0.47; 95% CI, 0.29-0.79) compared with those in the lowest quartile (≤17.26 μg/mL). This association remained significant for outpatient UTI events (highest vs lowest quartile even after excluding those with prior UTI: IRR, 0.42; 95% CI, 0.23-0.77). The direction of association with UTI hospitalization was similar, but not statistically significant (IRR, 0.78; 95% CI, 0.39-1.58). Limitations Use of ICD-9 codes to identify outcomes and lack of generalizability to younger populations. Conclusions High urinary uromodulin levels are associated with lower risk for UTI in older community-dwelling adults independent of traditional UTI risk factors. This finding supports prior laboratory data indicating a protective role of uromodulin against UTI. Further research is needed to understand if this may lead to new treatments to prevent or treat UTI.
Emerging evidence suggests that an underlying atrial cardiopathy may result in thromboembolism before atrial fibrillation (AF) develops. We examined the association between various markers of atrial ...cardiopathy and the risk of ischemic stroke.
The CHS (Cardiovascular Health Study) prospectively enrolled community-dwelling adults ≥65 years of age. For this study, we excluded participants diagnosed with stroke or AF before baseline. Exposures were several markers of atrial cardiopathy: baseline P-wave terminal force in ECG lead V
, left atrial dimension on echocardiogram, and N terminal pro B type natriuretic peptide (NT-proBNP), as well as incident AF. Incident AF was ascertained from 12-lead electrocardiograms at annual study visits for the first decade after study enrollment and from inpatient and outpatient Medicare data throughout follow-up. The primary outcome was incident ischemic stroke. We used Cox proportional hazards models that included all 4 atrial cardiopathy markers along with adjustment for demographic characteristics and established vascular risk factors.
Among 3723 participants who were free of stroke and AF at baseline and who had data on all atrial cardiopathy markers, 585 participants (15.7%) experienced an incident ischemic stroke during a median 12.9 years of follow-up. When all atrial cardiopathy markers were combined in 1 Cox model, we found significant associations with stroke for P-wave terminal force in ECG lead V
(hazard ratio per 1000 μV*ms 1.04; 95% confidence interval, 1.001-1.08), log-transformed NT-proBNP (hazard ratio per doubling of NT-proBNP, 1.09; 95% confidence interval, 1.03-1.16), and incident AF (hazard ratio, 2.04; 95% confidence interval, 1.67-2.48) but not left atrial dimension (hazard ratio per cm, 0.96; 95% confidence interval, 0.84-1.10).
In addition to clinically apparent AF, other evidence of abnormal atrial substrate is associated with subsequent ischemic stroke. This finding is consistent with the hypothesis that thromboembolism from the left atrium may occur in the setting of several different manifestations of atrial disease.
Mitochondrial DNA copy number (mtDNA-CN) has been associated with a variety of aging-related diseases, including all-cause mortality. However, the mechanism by which mtDNA-CN influences disease is ...not currently understood. One such mechanism may be through regulation of nuclear gene expression via the modification of nuclear DNA (nDNA) methylation.
To investigate this hypothesis, we assessed the relationship between mtDNA-CN and nDNA methylation in 2507 African American (AA) and European American (EA) participants from the Atherosclerosis Risk in Communities (ARIC) study. To validate our findings, we assayed an additional 2528 participants from the Cardiovascular Health Study (CHS) (N = 533) and Framingham Heart Study (FHS) (N = 1995). We further assessed the effect of experimental modification of mtDNA-CN through knockout of TFAM, a regulator of mtDNA replication, via CRISPR-Cas9.
Thirty-four independent CpGs were associated with mtDNA-CN at genome-wide significance (P < 5 × 10
). Meta-analysis across all cohorts identified six mtDNA-CN-associated CpGs at genome-wide significance (P < 5 × 10
). Additionally, over half of these CpGs were associated with phenotypes known to be associated with mtDNA-CN, including coronary heart disease, cardiovascular disease, and mortality. Experimental modification of mtDNA-CN demonstrated that modulation of mtDNA-CN results in changes in nDNA methylation and gene expression of specific CpGs and nearby transcripts. Strikingly, the "neuroactive ligand receptor interaction" KEGG pathway was found to be highly overrepresented in the ARIC cohort (P = 5.24 × 10
), as well as the TFAM knockout methylation (P = 4.41 × 10
) and expression (P = 4.30 × 10
) studies.
These results demonstrate that changes in mtDNA-CN influence nDNA methylation at specific loci and result in differential expression of specific genes that may impact human health and disease via altered cell signaling.
Recent evidence indicates that our understanding of the relationship between cardiac function and ischemic stroke remains incomplete. The Cardiovascular Health Study enrolled community-dwelling ...adults ≥ 65 years old. We included participants with speckle-tracking data from digitized baseline study echocardiograms. Exposures were left atrial reservoir strain (primary), left ventricular longitudinal strain, left ventricular early diastolic strain rate, septal e' velocity, and lateral e' velocity. The primary outcome was incident ischemic stroke. Cox proportional hazards models were adjusted for demographics, image quality, and risk factors including left ventricular ejection fraction and incident atrial fibrillation. Among 4,000 participants in our analysis, lower (worse) left atrial reservoir strain was associated with incident ischemic stroke (HR per SD absolute decrease, 1.14; 95% CI 1.04-25). All secondary exposure variables were significantly associated with the outcome. Left atrial reservoir strain was associated with cardioembolic stroke (HR per SD absolute decrease, 1.42; 95% CI 1.21-1.67) and cardioembolic stroke related to incident atrial fibrillation (HR per SD absolute decrease, 1.60; 1.32-1.95). Myocardial dysfunction that can ultimately lead to stroke may be identifiable at an early stage. This highlights opportunities to identify cerebrovascular risk earlier and improve stroke prevention via therapies for early myocardial dysfunction.
Abstract Background and Aims Understanding contributions of lean and fat tissue to cardiovascular and non-cardiovascular mortality may help clarify areas of prevention in older adults. We aimed to ...define distributions of lean and fat tissue in older adults and their contributions to cause-specific mortality. Methods and Results A total of 1335 participants of the Cardiovascular Health Study (CHS) who underwent dual-energy x-ray absorptiometry (DEXA) scans were included. We used principal components analysis (PCA) to define two independent sources of variation in DEXA-derived body composition, corresponding to principal components composed of lean (“lean PC”) and fat (“fat PC”) tissue. We used Cox proportional hazards regression using these PCs to investigate the relationship between body composition with cardiovascular and non-cardiovascular mortality. Mean age was 76.2±4.8 years (56% women) with mean body mass index 27.1±4.4 kg/m2 . A greater lean PC was associated with lower all-cause (HR=0.91, 95% CI 0.84-0.98, P=0.01) and cardiovascular mortality (HR=0.84, 95% CI 0.74-0.95, P=0.005). The lowest quartile of the fat PC (least adiposity) was associated with a greater hazard of all-cause mortality (HR = 1.24, 95% CI 1.04-1.48, P=0.02) relative to fat PCs between the 25th -75th percentile, but the highest quartile did not have a significantly greater hazard (P=0.70). Conclusion Greater lean tissue mass is associated with improved cardiovascular and overall mortality in the elderly. The lowest levels of fat tissue mass are linked with adverse prognosis, but the highest levels show no significant mortality protection. Prevention efforts in the elderly frail may be best targeted toward improvements in lean muscle mass.
This study evaluated the associations of obesity and cardiometabolic traits with incident heart failure with preserved versus reduced ejection fraction (HFpEF vs. HFrEF). Given known sex differences ...in HF subtype, we examined men and women separately.
Recent studies suggest that obesity confers greater risk of HFpEF versus HFrEF. Contributions of associated metabolic traits to HFpEF are less clear.
We studied 22,681 participants from 4 community-based cohorts followed for incident HFpEF versus HFrEF (ejection fraction ≥50% vs. <50%). We evaluated the association of body mass index (BMI) and cardiometabolic traits with incident HF subtype using Cox models.
The mean age was 60 ± 13 years, and 53% were women. Over a median follow-up of 12 years, 628 developed incident HFpEF and 835 HFrEF. Greater BMI portended higher risk of HFpEF compared with HFrEF (hazard ratio HR: 1.34 per 1-SD increase in BMI; 95% confidence interval CI: 1.24 to 1.45 vs. HR: 1.18; 95% CI: 1.10 to 1.27). Similarly, insulin resistance (homeostatic model assessment of insulin resistance) was associated with HFpEF (HR: 1.20 per 1-SD; 95% CI: 1.05 to 1.37), but not HFrEF (HR: 0.99; 95% CI: 0.88 to 1.11; p < 0.05 for difference HFpEF vs. HFrEF). We found that the differential association of BMI with HFpEF versus HFrEF was more pronounced among women (p for difference HFpEF vs. HFrEF = 0.01) when compared with men (p = 0.34).
Obesity and related cardiometabolic traits including insulin resistance are more strongly associated with risk of future HFpEF versus HFrEF. The differential risk of HFpEF with obesity seems particularly pronounced among women and may underlie sex differences in HF subtypes.
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Left ventricular (LV) mass and geometry are associated with risk of cardiovascular disease (CVD). We sought to determine whether LV mass and geometry contribute to risk prediction for CVD in adults ...aged ≥65 years of the Cardiovascular Health Study. We indexed LV mass to body size, denoted as LV mass index (echo-LVMI), and we defined LV geometry as normal, concentric remodeling, and eccentric or concentric LV hypertrophy. We added echo-LVMI and LV geometry to separate 10-year risk prediction models containing traditional risk factors and determined the net reclassification improvement (NRI) for incident coronary heart disease (CHD), CVD (CHD, heart failure HF, and stroke), and HF alone. Over 10 years of follow-up in 2,577 participants (64% women, 15% black, mean age 72 years) for CHD and CVD, the adjusted hazards ratios for a 1-SD higher echo-LVMI were 1.25 (95% CI 1.14 to 1.37), 1.24 (1.15 to 1.33), and 1.51 (1.40 to 1.62), respectively. Addition of echo-LVMI to the standard model for CHD resulted in an event NRI of −0.011 (95% CI −0.037 to 0.028) and nonevent NRI of 0.034 (95% CI 0.008 to 0.076). Addition of echo-LVMI and LV geometry to the standard model for CVD resulted in an event NRI of 0.013 (95% CI −0.0335 to 0.0311) and a nonevent NRI of 0.043 (95% CI 0.011 to 0.09). The nonevent NRI was also significant with addition of echo-LVMI for HF risk prediction (0.10, 95% CI 0.057 to 0.16). In conclusion, in adults aged ≥65 years, echo-LVMI improved risk prediction for CHD, CVD, and HF, driven primarily by improved reclassification of nonevents.
Heart failure (HF) is a prevalent and deadly disease, and preventive strategies focused on at-risk individuals are needed. Current HF prediction models have not examined HF subtypes. We sought to ...develop and validate risk prediction models for HF with preserved and reduced ejection fraction (HFpEF, HFrEF).
Of 28,820 participants from 4 community-based cohorts, 982 developed incident HFpEF and 909 HFrEF during a median follow-up of 12 years. Three cohorts were combined, and a 2:1 random split was used for derivation and internal validation, with the fourth cohort as external validation. Models accounted for multiple competing risks (death, other HF subtype, and unclassified HF). The HFpEF-specific model included age, sex, systolic blood pressure, body mass index, antihypertensive treatment, and previous myocardial infarction; it had good discrimination in derivation (c-statistic 0.80; 95% confidence interval CI, 0.78-0.82) and validation samples (internal: 0.79; 95% CI, 0.77-0.82 and external: 0.76; 95% CI: 0.71-0.80). The HFrEF-specific model additionally included smoking, left ventricular hypertrophy, left bundle branch block, and diabetes mellitus; it had good discrimination in derivation (c-statistic 0.82; 95% CI, 0.80-0.84) and validation samples (internal: 0.80; 95% CI, 0.78-0.83 and external: 0.76; 95% CI, 0.71-0.80). Age was more strongly associated with HFpEF, and male sex, left ventricular hypertrophy, bundle branch block, previous myocardial infarction, and smoking with HFrEF (P value for each comparison ≤0.02).
We describe and validate risk prediction models for HF subtypes and show good discrimination in a large sample. Some risk factors differed between HFpEF and HFrEF, supporting the notion of pathogenetic differences among HF subtypes.
Whether cardiovascular (CV) disease risk factors and biomarkers associate differentially with heart failure (HF) risk in men and women is unclear.
The purpose of this study was to evaluate ...sex-specific associations of CV risk factors and biomarkers with incident HF.
The analysis was performed using data from 4 community-based cohorts with 12.5 years of follow-up. Participants (recruited between 1989 and 2002) were free of HF at baseline. Biomarker measurements included natriuretic peptides, cardiac troponins, plasminogen activator inhibitor-1, D-dimer, fibrinogen, C-reactive protein, sST2, galectin-3, cystatin-C, and urinary albumin-to-creatinine ratio.
Among 22,756 participants (mean age 60 ± 13 years, 53% women), HF occurred in 2,095 participants (47% women). Age, smoking, type 2 diabetes mellitus, hypertension, body mass index, atrial fibrillation, myocardial infarction, left ventricular hypertrophy, and left bundle branch block were strongly associated with HF in both sexes (p < 0.001), and the combined clinical model had good discrimination in men (C-statistic = 0.80) and in women (C-statistic = 0.83). The majority of biomarkers were strongly and similarly associated with HF in both sexes. The clinical model improved modestly after adding natriuretic peptides in men (ΔC-statistic = 0.006; likelihood ratio chi-square = 146; p < 0.001), and after adding cardiac troponins in women (ΔC-statistic = 0.003; likelihood ratio chi-square = 73; p < 0.001).
CV risk factors are strongly and similarly associated with incident HF in both sexes, highlighting the similar importance of risk factor control in reducing HF risk in the community. There are subtle sex-related differences in the predictive value of individual biomarkers, but the overall improvement in HF risk estimation when included in a clinical HF risk prediction model is limited in both sexes.
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The most prominent risk factor for atrial fibrillation (AF) is chronological age; however, underlying mechanisms are unexplained. Algorithms using epigenetic modifications to the human genome ...effectively predict chronological age. Chronological and epigenetic predicted ages may diverge in a phenomenon referred to as epigenetic age acceleration (EAA), which may reflect accelerated biological aging. We sought to evaluate for associations between epigenetic age measures and incident AF.
Measures for 4 epigenetic clocks (Horvath, Hannum, DNA methylation DNAm PhenoAge, and DNAm GrimAge) and an epigenetic predictor of PAI-1 (plasminogen activator inhibitor-1) levels (ie, DNAm PAI-1) were determined for study participants from 3 population-based cohort studies. Cox models evaluated for associations with incident AF and results were combined via random-effects meta-analyses. Two-sample summary-level Mendelian randomization analyses evaluated for associations between genetic instruments of the EAA measures and AF.
Among 5600 participants (mean age, 65.5 years; female, 60.1%; Black, 50.7%), there were 905 incident AF cases during a mean follow-up of 12.9 years. Unadjusted analyses revealed all 4 epigenetic clocks and the DNAm PAI-1 predictor were associated with statistically significant higher hazards of incident AF, though the magnitudes of their point estimates were smaller relative to the associations observed for chronological age. The pooled EAA estimates for each epigenetic measure, with the exception of Horvath EAA, were associated with incident AF in models adjusted for chronological age, race, sex, and smoking variables. After multivariable adjustment for additional known AF risk factors that could also potentially function as mediators, pooled EAA measures for 2 clocks remained statistically significant. Five-year increases in EAA measures for DNAm GrimAge and DNAm PhenoAge were associated with 19% (adjusted hazard ratio HR, 1.19 95% CI, 1.09-1.31;
<0.01) and 15% (adjusted HR, 1.15 95% CI, 1.05-1.25;
<0.01) higher hazards of incident AF, respectively. Mendelian randomization analyses for the 5 EAA measures did not reveal statistically significant associations with AF.
Our study identified adjusted associations between EAA measures and incident AF, suggesting that biological aging plays an important role independent of chronological age, though a potential underlying causal relationship remains unclear. These aging processes may be modifiable and not constrained by the immutable factor of time.