@article {9637, title = {Development and Validation of the American Heart Association{\textquoteright}s PREVENT Equations.}, journal = {Circulation}, volume = {149}, year = {2024}, month = {2024 Feb 06}, pages = {430-449}, abstract = {

BACKGROUND: Multivariable equations are recommended by primary prevention guidelines to assess absolute risk of cardiovascular disease (CVD). However, current equations have several limitations. Therefore, we developed and validated the American Heart Association Predicting Risk of CVD EVENTs (PREVENT) equations among US adults 30 to 79 years of age without known CVD.

METHODS: The derivation sample included individual-level participant data from 25 data sets (N=3 281 919) between 1992 and 2017. The primary outcome was CVD (atherosclerotic CVD and heart failure). Predictors included traditional risk factors (smoking status, systolic blood pressure, cholesterol, antihypertensive or statin use, and diabetes) and estimated glomerular filtration rate. Models were sex-specific, race-free, developed on the age scale, and adjusted for competing risk of non-CVD death. Analyses were conducted in each data set and meta-analyzed. Discrimination was assessed using the Harrell C-statistic. Calibration was calculated as the slope of the observed versus predicted risk by decile. Additional equations to predict each CVD subtype (atherosclerotic CVD and heart failure) and include optional predictors (urine albumin-to-creatinine ratio and hemoglobin A1c), and social deprivation index were also developed. External validation was performed in 3 330 085 participants from 21 additional data sets.

RESULTS: Among 6 612 004 adults included, mean{\textpm}SD age was 53{\textpm}12 years, and 56\% were women. Over a mean{\textpm}SD follow-up of 4.8{\textpm}3.1 years, there were 211 515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval, 0.763-0.809) in female and 0.757 (0.727-0.778) in male participants. The calibration slopes were 1.03 (interquartile interval, 0.81-1.16) and 0.94 (0.81-1.13) among female and male participants, respectively. Similar estimates for discrimination and calibration were observed for atherosclerotic CVD- and heart failure-specific models. The improvement in discrimination was small but statistically significant when urine albumin-to-creatinine ratio, hemoglobin A1c, and social deprivation index were added together to the base model to total CVD (ΔC-statistic [interquartile interval] 0.004 [0.004-0.005] and 0.005 [0.004-0.007] among female and male participants, respectively). Calibration improved significantly when the urine albumin-to-creatinine ratio was added to the base model among those with marked albuminuria (>300 mg/g; 1.05 [0.84-1.20] versus 1.39 [1.14-1.65]; =0.01).

CONCLUSIONS: PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults by using routinely available clinical variables.

}, keywords = {Adult, Aged, Albumins, American Heart Association, Atherosclerosis, Cardiovascular Diseases, Creatinine, Female, Glycated Hemoglobin, Heart Failure, Humans, Male, Middle Aged, Risk Assessment, Risk Factors}, issn = {1524-4539}, doi = {10.1161/CIRCULATIONAHA.123.067626}, author = {Khan, Sadiya S and Matsushita, Kunihiro and Sang, Yingying and Ballew, Shoshana H and Grams, Morgan E and Surapaneni, Aditya and Blaha, Michael J and Carson, April P and Chang, Alexander R and Ciemins, Elizabeth and Go, Alan S and Gutierrez, Orlando M and Hwang, Shih-Jen and Jassal, Simerjot K and Kovesdy, Csaba P and Lloyd-Jones, Donald M and Shlipak, Michael G and Palaniappan, Latha P and Sperling, Laurence and Virani, Salim S and Tuttle, Katherine and Neeland, Ian J and Chow, Sheryl L and Rangaswami, Janani and Pencina, Michael J and Ndumele, Chiadi E and Coresh, Josef} } @article {9649, title = {Large-Scale Proteomics Identifies Novel Biomarkers and Circulating Risk Factors for Aortic Stenosis.}, journal = {J Am Coll Cardiol}, volume = {83}, year = {2024}, month = {2024 Feb 06}, pages = {577-591}, abstract = {

BACKGROUND: Limited data exist regarding risk factors for aortic stenosis (AS). The plasma proteome is a promising phenotype for discovery of novel biomarkers and potentially causative mechanisms.

OBJECTIVES: The aim of this study was to discover novel biomarkers with potentially causal associations with AS.

METHODS: We measured 4,877 plasma proteins (SomaScan aptamer-affinity assay) among ARIC (Atherosclerosis Risk In Communities) study participants in mid-life (visit 3 [V3]; n~=~11,430; age 60 {\textpm} 6 years) and in late-life (V5; n~=~4,899; age 76 {\textpm} 5 years). We identified proteins cross-sectionally associated with aortic valve (AV) peak velocity (AVmax) and dimensionless index by echocardiography at V5 and with incident AV-related hospitalization after V3 with the use of multivariable linear and Cox proportional hazard regression. We assessed associations of candidate proteins with changes in AVmax over 6 years and with AV calcification with the use of cardiac computed tomography, replicated analysis in an independent sample, performed Mendelian randomization, and evaluated gene expression in explanted human AV tissue.

RESULTS: Fifty-two proteins cross-sectionally were associated with AVmax and dimensionless index at V5 and with risk of incident AV-related hospitalization after V3. Among 3,413 participants in the Cardiovascular Health Study, 6 of those proteins were significantly associated with adjudicated moderate or severe AS, including matrix metalloproteinase 12 (MMP12), complement C1q tumor necrosis factor-related protein 1 (C1QTNF1), and growth differentiation factor-15. MMP12 was also associated with greater increase in AVmax over 6 years, greater degree of AV calcification, and greater expression in calcific compared with normal or fibrotic AV tissue. C1QTNF1 had consistent potential causal effects on both AS and AVmax according to Mendelian randomization analysis.

CONCLUSIONS: These findings identify MMP12 as a potential novel circulating biomarker of AS risk and C1QTNF1 as a new putative target to prevent AS progression.

}, keywords = {Aged, Aged, 80 and over, Aortic Valve, Aortic Valve Stenosis, Biomarkers, Calcinosis, Humans, Matrix Metalloproteinase 12, Middle Aged, Proteomics, Risk Factors}, issn = {1558-3597}, doi = {10.1016/j.jacc.2023.11.021}, author = {Shelbaya, Khaled and Arthur, Victoria and Yang, Yimin and Dorbala, Pranav and Buckley, Leo and Claggett, Brian and Skali, Hicham and Dufresne, Line and Yang, Ta-Yu and Engert, James C and Thanassoulis, George and Floyd, James and Austin, Thomas R and Bortnick, Anna and Kizer, Jorge and Freitas, Renata C C and Singh, Sasha A and Aikawa, Elena and Hoogeveen, Ron C and Ballantyne, Christie and Yu, Bing and Coresh, Josef and Blaha, Michael J and Matsushita, Kunihiro and Shah, Amil M} } @article {9917, title = {Association Between Cigarette Smoking~and Subclinical Markers of Cardiovascular Harm.}, journal = {J Am Coll Cardiol}, volume = {85}, year = {2025}, month = {2025 Mar 18}, pages = {1018-1034}, abstract = {

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.

}, keywords = {Aged, Atherosclerosis, Biomarkers, Cardiovascular Diseases, Carotid Intima-Media Thickness, Cigarette Smoking, Cohort Studies, Female, Humans, Male, Middle Aged, Risk Factors}, issn = {1558-3597}, doi = {10.1016/j.jacc.2024.12.032}, author = {Yao, Zhiqi and Tasdighi, Erfan and Dardari, Zeina A and Jha, Kunal K and Osuji, Ngozi and Rajan, Tanuja and Boakye, Ellen and Rodriguez, Carlos J and Matsushita, Kunihiro and Simonsick, Eleanor M and Lima, Jo{\~a}o A C and Widome, Rachel and Cohen, Debbie L and Appel, Lawrence J and Khera, Amit and Hall, Michael E and Judd, Suzanne E and Cole, Shelley A and Vasan, Ramachandran S and Benjamin, Emelia J and Lotufo, Paulo A and Bensenor, Isabela M and El Khoudary, Samar R and Barinas-Mitchell, Emma and Janssen, Imke and Psaty, Bruce M and Eaton, Charles B and Lamonte, Michael J and Cawthon, Peggy M and Orwoll, Eric S and Irvin, Marguerite R and Bhatnagar, Aruni and DeFilippis, Andrew P and El-Shahaway, Omar and Blaha, Michael J} }