03863nas a2200397 4500008004100000022001400041245014600055210006900201260001600270520264500286100001902931700003002950700001802980700002002998700001903018700001803037700002203055700002003077700001903097700001903116700001803135700001903153700002003172700001803192700002403210700002303234700002503257700002103282700002003303700002403323700002103347700001503368700002403383700002203407856003603429 2017 eng d a2380-659100aAssociation of Coronary Artery Calcium Score vs Age With Cardiovascular Risk in Older Adults: An Analysis of Pooled Population-Based Studies.0 aAssociation of Coronary Artery Calcium Score vs Age With Cardiov c2017 Jul 263 a

Importance: Besides age, other discriminators of atherosclerotic cardiovascular disease (ASCVD) risk are needed in older adults.

Objectives: To examine the predictive ability of coronary artery calcium (CAC) score vs age for incident ASCVD and how risk prediction changes by adding CAC score and removing only age from prediction models.

Design, Setting, and Participants: We conducted an analysis of pooled US population-based studies, including the Framingham Heart Study, the Multi-Ethnic Study of Atherosclerosis, and the Cardiovascular Health Study. Results were compared with 2 European cohorts, the Rotterdam Study and the Heinz Nixdorf Recall Study. Participants underwent CAC scoring between 1998 and 2006 using cardiac computed tomography. The participants included adults older than 60 years without known ASCVD at baseline.

Exposures: Coronary artery calcium scores.

Main Outcomes and Measures: Incident ASCVD events including coronary heart disease (CHD) and stroke.

Results: The study included 4778 participants from 3 US cohorts, with a mean age of 70.1 years; 2582 (54.0%) were women, and 2431 (50.9%) were nonwhite. Over 11 years of follow-up (44 152 person-years), 405 CHD and 228 stroke events occurred. Coronary artery calcium score (vs age) had a greater association with incident CHD (C statistic, 0.733 vs 0.690; C statistics difference, 0.043; 95% CI of difference, 0.009-0.075) and modestly improved prediction of incident stroke (C statistic, 0.695 vs 0.670; C statistics difference, 0.025; 95% CI of difference, -0.015 to 0.064). Adding CAC score to models including traditional cardiovascular risk factors, with only age being removed, provided improved discrimination for incident CHD (C statistic, 0.735 vs 0.703; C statistics difference, 0.032; 95% CI of difference, 0.002-0.062) but not for stroke. Coronary artery calcium score was more likely than age to provide higher category-free net reclassification improvement among participants who experienced an ASCVD event (0.390; 95% CI, 0.312-0.467 vs 0.08; 95% CI -0.001 to 0.181) and to result in more accurate reclassification of risk for ASCVD events among these individuals. The findings were similar in the 2 European cohorts (n = 4990).

Conclusions and Relevance: Coronary artery calcium may be an alternative marker besides age to better discriminate between lower and higher CHD risk in older adults. Whether CAC score can assist in guiding the decision to initiate statin treatment for primary prevention in older adults requires further investigation.

1 aYano, Yuichiro1 aO'Donnell, Christopher, J1 aKuller, Lewis1 aKavousi, Maryam1 aErbel, Raimund1 aNing, Hongyan1 aD'Agostino, Ralph1 aNewman, Anne, B1 aNasir, Khurram1 aHofman, Albert1 aLehmann, Nils1 aDhana, Klodian1 aBlankstein, Ron1 aHoffmann, Udo1 aMöhlenkamp, Stefan1 aMassaro, Joseph, M1 aMahabadi, Amir-Abbas1 aLima, João, A C1 aIkram, Arfan, M1 aJöckel, Karl-Heinz1 aFranco, Oscar, H1 aLiu, Kiang1 aLloyd-Jones, Donald1 aGreenland, Philip uhttps://chs-nhlbi.org/node/744204686nas a2200541 4500008004100000022001400041245011900055210006900174260001600243520308900259100002303348700001903371700003003390700002203420700002203442700002003464700002203484700002303506700001803529700002103547700002103568700001503589700002003604700002303624700002103647700002103668700001903689700001503708700002703723700002003750700002003770700002103790700002003811700002403831700001903855700002103874700002203895700002203917700002003939700001703959700002503976700002204001700001904023700002404042700002204066700002004088856003604108 2018 eng d a2380-659100aAssociation of Cardiovascular Biomarkers With Incident Heart Failure With Preserved and Reduced Ejection Fraction.0 aAssociation of Cardiovascular Biomarkers With Incident Heart Fai c2018 Jan 103 a

Importance: Nearly half of all patients with heart failure have preserved ejection fraction (HFpEF) as opposed to reduced ejection fraction (HFrEF), yet associations of biomarkers with future heart failure subtype are incompletely understood.

Objective: To evaluate the associations of 12 cardiovascular biomarkers with incident HFpEF vs HFrEF among adults from the general population.

Design, Setting, and Participants: This study included 4 longitudinal community-based cohorts: the Cardiovascular Health Study (1989-1990; 1992-1993 for supplemental African-American cohort), the Framingham Heart Study (1995-1998), the Multi-Ethnic Study of Atherosclerosis (2000-2002), and the Prevention of Renal and Vascular End-stage Disease study (1997-1998). Each cohort had prospective ascertainment of incident HFpEF and HFrEF. Data analysis was performed from June 25, 2015, to November 9, 2017.

Exposures: The following biomarkers were examined: N-terminal pro B-type natriuretic peptide or brain natriuretic peptide, high-sensitivity troponin T or I, C-reactive protein (CRP), urinary albumin to creatinine ratio (UACR), renin to aldosterone ratio, D-dimer, fibrinogen, soluble suppressor of tumorigenicity, galectin-3, cystatin C, plasminogen activator inhibitor 1, and interleukin 6.

Main Outcomes and Measures: Development of incident HFpEF and incident HFrEF.

Results: Among the 22 756 participants in these 4 cohorts (12 087 women and 10 669 men; mean [SD] age, 60 [13] years) in the study, during a median follow-up of 12 years, 633 participants developed incident HFpEF, and 841 developed HFrEF. In models adjusted for clinical risk factors of heart failure, 2 biomarkers were significantly associated with incident HFpEF: UACR (hazard ratio [HR], 1.33; 95% CI, 1.20-1.48; P < .001) and natriuretic peptides (HR, 1.27; 95% CI, 1.16-1.40; P < .001), with suggestive associations for high-sensitivity troponin (HR, 1.11; 95% CI, 1.03-1.19; P = .008), plasminogen activator inhibitor 1 (HR, 1.22; 95% CI, 1.03-1.45; P = .02), and fibrinogen (HR, 1.12; 95% CI, 1.03-1.22; P = .01). By contrast, 6 biomarkers were associated with incident HFrEF: natriuretic peptides (HR, 1.54; 95% CI, 1.41-1.68; P < .001), UACR (HR, 1.21; 95% CI, 1.11-1.32; P < .001), high-sensitivity troponin (HR, 1.37; 95% CI, 1.29-1.46; P < .001), cystatin C (HR, 1.19; 95% CI, 1.11-1.27; P < .001), D-dimer (HR, 1.22; 95% CI, 1.11-1.35; P < .001), and CRP (HR, 1.19; 95% CI, 1.11-1.28; P < .001). When directly compared, natriuretic peptides, high-sensitivity troponin, and CRP were more strongly associated with HFrEF compared with HFpEF.

Conclusions and Relevance: Biomarkers of renal dysfunction, endothelial dysfunction, and inflammation were associated with incident HFrEF. By contrast, only natriuretic peptides and UACR were associated with HFpEF. These findings highlight the need for future studies focused on identifying novel biomarkers of the risk of HFpEF.

1 ade Boer, Rudolf, A1 aNayor, Matthew1 adeFilippi, Christopher, R1 aEnserro, Danielle1 aBhambhani, Vijeta1 aKizer, Jorge, R1 aBlaha, Michael, J1 aBrouwers, Frank, P1 aCushman, Mary1 aLima, João, A C1 aBahrami, Hossein1 aHarst, Pim1 aWang, Thomas, J1 aGansevoort, Ron, T1 aFox, Caroline, S1 aGaggin, Hanna, K1 aKop, Willem, J1 aLiu, Kiang1 aVasan, Ramachandran, S1 aPsaty, Bruce, M1 aLee, Douglas, S1 aHillege, Hans, L1 aBartz, Traci, M1 aBenjamin, Emelia, J1 aChan, Cheeling1 aAllison, Matthew1 aGardin, Julius, M1 aJanuzzi, James, L1 aShah, Sanjiv, J1 aLevy, Daniel1 aHerrington, David, M1 aLarson, Martin, G1 aGilst, Wiek, H1 aGottdiener, John, S1 aBertoni, Alain, G1 aHo, Jennifer, E uhttps://chs-nhlbi.org/node/760304780nas a2200697 4500008004100000022001400041245009100055210006900146260001600215300001400231490000700245520282300252653000903075653002003084653001503104653002803119653003503147653002203182653001903204653001103223653001103234653000903245653001603254653001703270100001503287700002003302700002203322700001803344700001703362700001803379700001803397700002503415700002503440700002603465700002103491700001903512700002103531700002303552700001603575700002103591700002103612700002103633700002703654700002403681700002103705700002503726700002603751700002703777700001803804700002003822700002203842700002403864700002203888700002003910700002503930700002103955700002603976700002204002700002204024856003604046 2025 eng d a1558-359700aAssociation Between Cigarette Smoking and Subclinical Markers of Cardiovascular Harm.0 aAssociation Between Cigarette Smoking and Subclinical Markers of c2025 Mar 18 a1018-10340 v853 a

BACKGROUND: Cigarette smoking is a strong risk factor for cardiovascular harm.

OBJECTIVES: The study sought to explore the detailed relationships between smoking intensity, pack-years, and time since cessation with inflammation, thrombosis, and subclinical atherosclerosis markers of cardiovascular harm.

METHODS: We included 182,364 participants (mean age 58.2 years, 69.0% female) from 22 cohorts of the Cross Cohort Collaboration with self-reported smoking status, including smoking intensity and/or pack-years, and concurrent subclinical marker measurements. Markers were categorized into 3 domains: inflammation (high-sensitivity C-reactive protein, interleukin-6, glycoprotein acetylation), thrombosis (fibrinogen, D-dimer), and subclinical atherosclerosis (coronary artery calcium, carotid intima-media thickness, carotid plaque, and ankle-brachial index). Utilizing multivariate regression models and restricted cubic splines, we assessed associations of smoking status, intensity, pack-years, time since cessation, and subclinical markers.

RESULTS: A total of 15.3% of participants currently smoke (mean 16.7 cigarettes/day, mean 30.0 pack-years), and 34.6% of participants formerly smoked (median 19.0 years since quitting, mean 22.4 pack-years). Participants with a history of smoking showed higher levels of all subclinical markers compared with those who have never smoked, with stronger associations observed in those currently smoke. Among participants who currently smoke, smoking intensity showed a clear dose-response relationship with all markers, except for D-dimer, specifically with incremental 1% to 9% higher levels of subclinical markers per 10 cigarettes. After 20 cigarettes, the patterns appeared to plateau for blood markers, while they continued to increase for atherosclerosis markers. Among those who have ever smoked, robust dose-response relationships were observed for pack-years with all subclinical markers, with incremental 1% to 9% higher levels per 10 pack-years. The dose-response effects persisted after 20 pack-years for all markers, though with a milder slope. Among participants who smoked formerly, there were substantially lower levels of biomarkers with longer time since quitting, and most markers were not different compared with those who have never smoked by 30 years, except for the coronary artery calcium score, which remained 19% higher even beyond quitting after 30 years.

CONCLUSIONS: Smoking-relevant parameters show strong and dose-response relationships across 3 domains of subclinical markers of cardiovascular harm. The sensitivity of the tested subclinical markers to small increments in cigarette exposure suggests potential value in the regulation of new and existing tobacco products.

10aAged10aAtherosclerosis10aBiomarkers10aCardiovascular Diseases10aCarotid Intima-Media Thickness10aCigarette Smoking10aCohort Studies10aFemale10aHumans10aMale10aMiddle Aged10aRisk Factors1 aYao, Zhiqi1 aTasdighi, Erfan1 aDardari, Zeina, A1 aJha, Kunal, K1 aOsuji, Ngozi1 aRajan, Tanuja1 aBoakye, Ellen1 aRodriguez, Carlos, J1 aMatsushita, Kunihiro1 aSimonsick, Eleanor, M1 aLima, João, A C1 aWidome, Rachel1 aCohen, Debbie, L1 aAppel, Lawrence, J1 aKhera, Amit1 aHall, Michael, E1 aJudd, Suzanne, E1 aCole, Shelley, A1 aVasan, Ramachandran, S1 aBenjamin, Emelia, J1 aLotufo, Paulo, A1 aBensenor, Isabela, M1 aKhoudary, Samar, R El1 aBarinas-Mitchell, Emma1 aJanssen, Imke1 aPsaty, Bruce, M1 aEaton, Charles, B1 aLamonte, Michael, J1 aCawthon, Peggy, M1 aOrwoll, Eric, S1 aIrvin, Marguerite, R1 aBhatnagar, Aruni1 aDeFilippis, Andrew, P1 aEl-Shahaway, Omar1 aBlaha, Michael, J uhttps://chs-nhlbi.org/node/9917