Cumulative Diastolic Blood Pressure Burden in Normal Systolic Blood Pressure and Cardiovascular Disease.

BACKGROUND: The clinical significance of isolated diastolic hypertension defined by the 2017 American College of Cardiology/American Heart Association blood pressure (BP) guidelines remains inconsistent. We examined whether long-term diastolic burden predicts the first major adverse cardiovascular event in participants with sustained and untreated normal systolic BP. METHODS: The Mass General Brigham Biobank is a New England health care-based cohort recruited between 2010 and 2021. A total of 15 979 participants aged 18 to 64 years and without prior cardiovascular disease, antihypertensives, or high systolic BP were studied. The cumulative diastolic burden was determined as the area under the curve for diastolic BP (DBP) ≥80 mm Hg over 5 years before enrollment. Major adverse cardiovascular event was defined as a composite of first incident ischemic heart disease, stroke, heart failure, or all-cause death. RESULTS: Of the 15 979 participants, mean (SD) age at enrollment was 47.6 (14.3) years, 11 950 (74.8%) were women, and the mean (SD) systolic BP and DBP were 118.0 (12.9) and 72.2 (9.3) mm Hg, respectively. Over a median (interquartile range) follow-up of 3.5 (1.8-5.4) years, 2467 (15.4%) major adverse cardiovascular events occurred. Using Cox proportional hazards regression, each SD increase in cumulative DBP was independently associated with a hazard ratio (95% CI) of 1.06 (1.02-1.10) without effect modification by sex (P=0.65), age (P=0.46), or race/ethnicity (P=0.24). In addition to traditional risk factors, cumulative DBP modestly improved the discrimination C index (95% CI) from 0.74 (0.72-0.75) to 0.75 (0.74-0.76; likelihood ratio test, P=0.037). CONCLUSIONS: Among individuals with normal systolic BP, cumulative DBP may augment cardiovascular disease risk stratification beyond a single DBP measure and traditional risk factors.

Long-term longitudinal analysis of 4,187 participants reveals new insights into determinants of incident clonal hematopoiesis.

Clonal hematopoiesis (CH), characterized by blood cells predominantly originating from a single mutated hematopoietic stem cell, is linked to diverse aging-related diseases, including hematologic malignancy and atherosclerotic cardiovascular disease (ASCVD). While CH is common among older adults, the underlying factors driving its development are largely unknown. To address this, we performed whole-exome sequencing on 8,374 blood DNA samples collected from 4,187 Atherosclerosis Risk in Communities Study (ARIC) participants over a median follow-up of 21 years. During this period, 735 participants developed incident CH. We found that age at baseline, sex, and dyslipidemia significantly influence the incidence of CH, while ASCVD and other traditional risk factors for ASCVD did not exhibit such associations. Our study also revealed associations between germline genetic variants and incident CH, prioritizing genes in CH development. Our comprehensive longitudinal assessment yields novel insights into the factors contributing to incident CH in older adults.

Genetic, sociodemographic, lifestyle, and clinical risk factors of recurrent coronary artery disease events: a population-based cohort study.

AIMS: Complications of coronary artery disease (CAD) represent the leading cause of death among adults globally. This study examined the associations and clinical utilities of genetic, sociodemographic, lifestyle, and clinical risk factors on CAD recurrence. METHODS AND RESULTS: Data were from 7024 UK Biobank middle-aged adults with established CAD at enrolment. Cox proportional hazards regressions modelled associations of age at enrolment, age at first CAD diagnosis, sex, cigarette smoking, physical activity, diet, sleep, Townsend Deprivation Index, body mass index, blood pressure, blood lipids, glucose, lipoprotein(a), C reactive protein, estimated glomerular filtration rate (eGFR), statin prescription, and CAD polygenic risk score (PRS) with first post-enrolment CAD recurrence. Over a median [interquartile range] follow-up of 11.6 [7.2-12.7] years, 2003 (28.5%) recurrent CAD events occurred. The hazard ratio (95% confidence interval [CI]) for CAD recurrence was the most pronounced with current smoking (1.35, 1.13-1.61) and per standard deviation increase in age at first CAD (0.74, 0.67-0.82). Additionally, age at enrolment, CAD PRS, C-reactive protein, lipoprotein(a), glucose, low-density lipoprotein cholesterol, deprivation, sleep quality, eGFR, and high-density lipoprotein (HDL) cholesterol also significantly associated with recurrence risk. Based on C indices (95% CI), the strongest predictors were CAD PRS (0.58, 0.57-0.59), HDL cholesterol (0.57, 0.57-0.58), and age at initial CAD event (0.57, 0.56-0.57). In addition to traditional risk factors, a comprehensive model improved the C index from 0.644 (0.632-0.654) to 0.676 (0.667-0.686). CONCLUSION: Sociodemographic, clinical, and laboratory factors are each associated with CAD recurrence with genetic risk, age at first CAD event, and HDL cholesterol concentration explaining the most.

Integrative proteomic analyses across common cardiac diseases yield new mechanistic insights and enhanced prediction.

Cardiac diseases represent common highly morbid conditions for which underlying molecular mechanisms remain incompletely understood. Here, we leveraged 1,459 protein measurements in 44,313 UK Biobank participants to characterize the circulating proteome associated with incident coronary artery disease, heart failure, atrial fibrillation, and aortic stenosis. Multivariable-adjusted Cox regression identified 820 protein-disease associations-including 441 proteins-at Bonferroni-adjusted P <8.6×10 -6 . Cis -Mendelian randomization suggested causal roles that aligned with epidemiological findings for 6% of proteins identified in primary analyses, prioritizing novel therapeutic targets for different cardiac diseases (e.g., interleukin-4 receptor for heart failure and spondin-1 for atrial fibrillation). Interaction analyses identified seven protein-disease associations that differed Bonferroni-significantly by sex. Models incorporating proteomic data (vs. clinical risk factors alone) improved prediction for coronary artery disease, heart failure, and atrial fibrillation. These results lay a foundation for future investigations to uncover novel disease mechanisms and assess the clinical utility of protein-based prevention strategies for cardiac diseases.