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Purpose of Review: Preventive cardiology has an important role to play in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. The SARS-CoV-2 pandemic has been observed to have a greater mortality impact on subgroups of people in the population who are deemed to be at higher medical disease risk. Individuals with cardiovascular disorders are one such COVID-19-associated high-mortality risk group., Recent Findings: Evidence is accumulating that COVID-19 infection may worsen an individual's future cardiovascular health, and, preinfection/postinfection cardiovascular evaluation may be warranted to determine if progressive cardiovascular damage has occurred because of COVID-19 infection. In this study, we conducted a systematic review and meta-analysis, focusing on the association between COVID-19 severity and cardiac-specific biomarkers, including N-terminal pro-B-type natriuretic peptide (NT-proBNP), troponin T (TnT)/troponin I (TnI), lactate dehydrogenase (LDH), creatine kinase, and creatine kinase isoenzyme (CK-MB). TnT had the highest odds ratio or OR (11.83) indicating the greatest association with COVID-19 severity, followed by NT-proBNP (7.57), TnI (6.32), LDH (4.79), D-dimer (4.10), creatine kinase (3.43), and CK-MB (3.35). All of the biomarkers studied were significantly correlated with COVID-19 severity including severe symptoms, ICU care, and mortality (P < 0.0001, except P < 0.01 for CK-MB)., Summary: COVID-19 infection results in short-term and long-term disease risk that may involve adverse cardiovascular health issues including heart failure. Cardiac-specific biomarkers appear to identify a subset of COVID-19 patients who have the highest risk of an adverse medical outcome. Preventive cardiology has an important role to play in the COVID-19 pandemic.The risk/benefit analysis of maintaining or eliminating the use of the angiotensin receptor blockers (ARB) and angiotensin-converting enzyme inhibitor (ACE-I) medications deserves further investigation., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Background and Aims: Non-high-density (HDL)-cholesterol, low-density lipoprotein (LDL)-particle number, apolipoprotein B, lipoprotein(a) (Lp(a)), and small-dense (sdLDL) and large-buoyant (lbLDL) LDL-subfractions are emerging apo B-containing atherosclerotic cardiovascular disease (ASCVD) risk factors. Current guidelines emphasize lifestyle, including weight loss, for ASCVD risk management. Whether weight change affects these emerging risk factors beyond that predicted by traditional triglyceride and LDL-cholesterol measurements remains to be determined., Method: Regression analyses of fasting ∆apo B-containing lipoproteins vs. ∆BMI were examined in a large anonymized clinical laboratory database of 33,165 subjects who did not report use of lipid-lowering medications. Regression slopes (±SE) were estimated as: *∆mmol/L per ∆kg/m 2 , † ∆g/L per ∆kg/m 2 , ‡ ∆% per ∆kg/m 2 , and § ∆μmol/L per ∆kg/m 2 ., Results: When adjusted for age, ∆BMI was significantly related to ∆nonHDL-cholesterol (males: 0.0238 ± 0.0041, P = 7.9 × 10 - 9 ; females: 0.0330 ± 0.0037, P < 10 - 16 )*, ∆LDL-particles (males: 0.0128 ± 0.0024, P = 2.1 × 10 - 7 ; females: 0.0114 ± 0.0022, P = 3.2 × 10 - 7 ) * , ∆apo B (males: 0.0053 ± 0.0010, P = 7.9 × 10 - 8 ; females: 0.0073 ± 0.0009, P = 2.2 × 10 - 16 ) † , ∆sdLDL (males: 0.0125 ± 0.0015, P = 2.2 × 10 - 16 ; females: 0.0128 ± 0.0012, P < 10 - 16 )*, ∆percent LDL carried on small dense particles (%sdLDL, males: 0.296 ± 0.035, P < 10 - 16 ; females: 0.221 ± 0.023, P < 10 - 16 ) ‡ , ∆triglycerides (males: 0.0358 ± 0.0049, P = 2.0 × 10 - 13 ; females: 0.0304 ± 0.0029, P < 10 - 16 )*, and ∆LDL-cholesterol (males: 0.0128 ± 0.0034, P = 0.0002; females: 0.0232 ± 0.0031, P = 1.2 × 10 - 13 )* in both males and females. Age-adjusted ∆BMI was significantly related to ∆lbLDL in females (0.0098 ± 0.0024, P = 3.9 × 10 - 5 )* but not males (0.0007 ± 0.0026, P = 0.78)*. Female showed significantly greater increases in ∆LDL-cholesterol (P = 0.02) and ∆lbLDL (P = 0.008) per ∆BMI than males. ∆BMI had a greater effect on ∆LDL-cholesterol measured directly than indirect estimate of ∆LDL-cholesterol from the Friedewald equation. When sexes were combined and adjusted for age, sex, ∆triglycerides and ∆LDL-cholesterol, ∆BMI retained residual associations with ∆nonHDL-cholesterol (0.0019 ± 0.0009, P = 0.03)*, ∆LDL-particles (0.0032 ± 0.0010, P = 0.001)*, ∆apo B (0.0010 ± 0.0003, P = 0.0008) † , ∆Lp(a) (- 0.0091 ± 0.0021, P = 1.2 × 10 - 5 ) § , ∆sdLDL (0.0001 ± 0.0000, P = 1.6 × 10 - 11 ) * and ∆%sdLDL (0.151 ± 0.018, P < 10 - 16 ) ‡ ., Conclusions: Emerging apo B-containing risk factors show associations with weight change beyond those explained by the more traditional triglyceride and LDL-cholesterol measurements.

Heart attacks kill more Americans than all cancers combined. Fatal heart attack victims have no symptoms until minutes before they die, hence early detection of high-risk asymptomatic individuals is needed. Even though heart attacks kill and cost more than cancers, as a nation we spend over 20 times more on screening for asymptomatic cancer than for asymptomatic atherosclerotic cardiovascular disease (ASCVD), the underlying cause of heart attacks. Currently, payers only cover screening for risk factors of ASCVD such as blood pressure and blood cholesterol. This approach tends to miss high-risk and over-treat low-risk individuals. Although treadmill stress testing with ECG is not indicated for ASCVD detection in asymptomatic individuals, it is done often, and frequently leads to misleading conclusions or unnecessary downstream diagnostic procedures. For example, former President Clinton had passed his treadmill stress tests for several years during his presidential annual checkup but had a heart attack shortly after his presidency. This common practice is a waste of our limited resources. Instead, a more accurate risk assessment using coronary artery calcium (CAC) testing is available; and has just been adopted by ACC/AHA guidelines, however payers do not cover it. CAC is measured non-invasively with a 5-minute CT-scan of the heart, and costs less than $200, whereas cancer screening with colonoscopy and mammography costs over $3000. There is an opportunity to save lives and dollars if CAC testing is covered for appropriately selected individuals. Texas has already passed HB1290 to mandate CAC coverage. Other states must step up and take actions.

Under "treat to risk" goals, low-density (LDL)-cholesterol follow-up measurements monitor statin compliance rather than titration to target levels, however, there is little evidence showing that more-frequent monitoring reduces LDL-cholesterol. We therefore tested whether frequency of blood tests significantly predicted lipoprotein improvements in a large anonymized clinical laboratory database. Differences (∆ ± SE) in total cholesterol, triglycerides, and LDL-cholesterol between baseline and follow-up visits were calculated for 97,548 men and 110,424 women whose physicians sent blood to Boston Heart Diagnostics for analysis between 2010 and 2017. When adjusted for age and follow-up duration, plasma concentration changes per each follow-up measurement in men and women respectively were -2.84 ± 0.10 mg/dL and -3.03 ± 0.10 mg/dL for total cholesterol, -3.78 ± 0.30 mg/dL and -2.26 ± 0.19 mg/dL for triglycerides, and -2.54 ± 0.09 mg/dL and -3.06 ± 0.09 mg/dL for LDL-cholesterol (all P < 10 -16 ). Relative to baseline, significant decreases (P < 10 -16 ) were observed for the 1st, 2nd, and 3rd follow-up measurements for total cholesterol (mean ± SE, men: -9.4 ± 0.1, -11.9 ± 0.2, -13.7 ± 0.3; women: -8.0 ± 0.1, -10.5 ± 0.2, -12.6 ± 0.3 mg/dL, respectively), triglycerides (men: -10.3 ± 0.4, -12.8 ± 0.5, -13.4 ± 0.7; women: -6.4 ± 0.2, -8.8 ± 0.4, -10.1 ± 0.5 mg/dL, respectively) and LDL-cholesterol (men: -7.8 ± 0.1, -9.9 ± 0.2, -11.1 ± 0.2; women: -6.9 ± 0.1, -9.0 ± 0.2, -10.7 ± 0.2 mg/dL, respectively). When adjusted for regression to the mean, 6.9%, 9.9% and 11.8% of men, and 5.7%, 9.7% and 11.5% of women, went from having an LDL-cholesterol ≥160 to <160 mg/dL for their 1st, 2nd, and 3rd follow-up measurements, respectively. We conclude that under usual physician care, total cholesterol, triglyceride, and LDL-cholesterol concentrations decreased progressively with increased physician monitoring within a large patient population., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Background: Changes in body mass index (ΔBMI) have well-established relationships to changes in high-density lipoprotein (ΔHDL)-cholesterol concentrations; however, their relationships to ΔHDL subfractions are less well understood., Objective: Assess the associations between ΔHDL and ΔBMI in a very large cohort., Method: Age and sex-adjusted Δapo A1 concentrations were measured within 10 HDL subfractions in 14,121 women and 13,969 men using two-dimensional HDL-mapping. Significance was identified at .01 < P ≤ .05 (*), .001 < P ≤ .01 (†), .0001 < P ≤ .001 (‡), and P ≤ .0001 (§)., Results: ΔBMI was significantly associated with Δα-1 (very large HDL, slope ± SE, females: -0.39 ± 0.07 § ; males: -0.51 ± 0.05 § ), Δα-3 (medium HDL, females: 0.18 ± 0.04 § ; males: 0.19 ± 0.04 § ), and Δα-4 (small HDL, females: 0.14 ± 0.03 § ; males: 0.15 ± 0.04 § mg/dL per kg/m 2 ). As a percent of baseline, the changes in α-1 per ΔBMI were nearly twice as great as the changes in HDL-cholesterol per ΔBMI in both males (-1.53% vs -0.77%) and females (-0.79% vs -0.42%). HDL-cholesterol decreased significantly in healthy-weight patients who became overweight, overweight patients who became class I or class II obese, class I obese patients who became class II obese, and class II obese patients who became class III. In contrast, HDL-cholesterol increased in class III obese patients who became class II or class I, class II obese patients who became class I or overweight, class I patients who became overweight or healthy weight, overweight patients who became healthy weight, and healthy weight patients who became underweight., Conclusions: Weight change significantly affects HDL-cholesterol concentrations throughout the obesity spectrum. ΔBMI's effect on Δα-1 was nearly twice as great as its effect on HDL-cholesterol., (Copyright © 2018 National Lipid Association. Published by Elsevier Inc. All rights reserved.)

Objective: We tested the hypothesis that a lifestyle program would improve risk factors linked to cardiovascular disease (CVD) in first responders., Methods: A 1-year cluster-randomized controlled clinical trial in 10 cities. Participants were 175 first responders, with increased waist circumference and/or low levels of large (α1) high-density lipoprotein (HDL) particles. The intervention group received personalized online tools and access to telephonic coaching sessions., Results: At 1 year the intervention significantly reduced body weight (P = 0.004) and waist circumference (P = 0.002), increased α1 HDL (P = 0.01), and decreased triglyceride (P = 0.005) and insulin concentrations (P = 0.03). Program adherence was associated with weight loss (P = 0.0005) and increases in α1 HDL (P = 0.03)., Conclusions: In first responders, a personalized lifestyle intervention significantly improved CVD risk factors in proportion to program adherence. Changes in large HDL particles were more sensitive indicators of lifestyle changes than HDL-cholesterol measurement., Clinical Trial Registration Number: ClinicalTrials.gov: NCT03322046.

Background: Over a 14-year period, age-adjusted high total cholesterol (≥240 mg/dL) in the United States declined from 18.3% in 1999 to 2000 to 11.0% in 2013 to 2014, coinciding with the 2001 National Cholesterol Education Program Adult Treatment Panel (ATP)-III guidelines that endorsed low-density lipoprotein (LDL)-cholesterol blood value goals. Statin treatment recommendations were revised by the American College of Cardiology and the American Heart Association (ACC/AHA) in November 2013 to a "risk-based prescription" approach that did not utilize blood cholesterol values. This increased dosage and expanded the statin-eligible population by an estimated 12.8 million US adults. These changes should further lower total and LDL cholesterol concentrations nationally., Methods: We examined data from 507 752 patients nationally aged ≥16 years whose fasting bloods were sent to Boston Heart Diagnostics for direct LDL-cholesterol measurements. Between 2012 and 2017, age-adjusted concentrations were examined by analysis of covariance and LDL-cholesterol ≥160 mg/dL by logistic regression., Results: Contrary to expectations, age-adjusted mean LDL-cholesterol concentrations (±SE, mg/dL) increased significantly (P < 10 -16 ) in men (2012:113.8 ± 0.3; 2013:115.3 ± 0.2; 2014:114.7 ± 0.2; 2015:116.0 ± 0.2; 2016:117.6 ± 0.2; and 2017:117.1 ± 0.2 mg/dL) and women (2012:119.5 ± 0.3; 2013:120.7 ± 0.2; 2014:119.8 ± 0.02; 2015:120.8 ± 0.2; 2016:122.7 ± 0.1; and 2017:123.8 ± 0.2 mg/dL). The percentage with LDL-cholesterol ≥160 mg/dL also increased significantly (P < 10 -9 ) in men and women. Similar results were obtained for ages 40 to 75 years olds (corresponding to ACC/AHA guidelines)., Conclusion: These results provide additional evidence that declining blood LDL-cholesterol levels observed following the ATP-III recommendations, did not further decline (actually increased) following the 2013 ACC/AHA recommendations., (© 2018 Wiley Periodicals, Inc.)

Niacin (nicotinic acid) has been used for primary and secondary coronary heart disease prevention for over 40 years. Until recently clinical trials incorporating niacin as part of an intervention strategy consistently demonstrated reduction in clinical events and lesion improvement, including ≥6% absolute mortality reduction. Two large clinical event trials in 2011 (Atherothrombosis Intervention in Metabolic Syndrome With Low HDL/High Triglycerides and Impact on Global Health Outcomes) and 2014 (Heart Protection Study 2-Treatment of HDL to Reduce the Incidence of Vascular Events) concluded that niacin added to statin therapy did not provide clinical event benefit over statin alone. This has prompted some individuals to call for an end to the use of niacin in statin-treated patients and the US Food and Drug Administration to halt marketing of statin/niacin combination tablets. There are significant differences between the earlier clinical trials that revealed cardiovascular benefit of niacin and the 2 trials that failed to demonstrate a benefit. These differences include dyslipidemia types, niacin formulation, dosing, and timing. In general, the patient population that benefits the most from incorporating niacin in their treatment regimen can be defined by elevations in low-density lipoprotein cholesterol and triglycerides, and reduced high-density lipoprotein cholesterol. The niacin formulation and dose should be capable of achieving adequate lipoprotein change. Mealtime dosing of niacin, as opposed to bedtime dosing, may avoid a counter-regulatory hormone response, including catecholamines, because of altered fuel supply potentially leading to unexpected cardiovascular outcomes., (Copyright © 2017 National Lipid Association. Published by Elsevier Inc. All rights reserved.)

Context: Patients with nonalcoholic fatty liver disease (NAFLD) are at increased risk of cardiovascular disease, and atherogenic lipoproteins may play an important role., Objective: The objective of the study was to determine the contribution of the severity of steatohepatitis to atherogenic dyslipidemia in patients with NAFLD., Design: This was a cross-sectional study., Setting: The study was conducted at a university hospital., Patients: Patients were recruited from outpatient clinics or from the general population (n = 188)., Interventions: Measurement of hepatic triglyceride content by magnetic resonance spectroscopy, histology (liver biopsy), metabolic profile by means of an oral glucose tolerance test, and lipoprotein analyses were performed., Outcomes: Outcomes measured included standard lipids, lipoprotein subfraction analysis (apolipoprotein B/A1 levels, low-density lipoprotein (LDL) particle size/phenotype, and LDL/high-density lipoprotein subfractions), and insulin resistance., Results: Patients with NAFLD had severe insulin resistance, especially at the level of the adipose tissue, when compared with patients without NAFLD. Despite small differences in triglycerides and high-density lipoprotein-cholesterol, patients with NAFLD had a significantly higher plasma apolipoprotein B to apolipoprotein A1 ratio (0.66 ± 0.02 vs 0.58 ± 0.02, P = .01) and smaller LDL particle size (216.2 ± 0.7 vs 219.4 ± 1.1 Å, P = .01). Of note, these differences between patients with/without NAFLD were independent of the presence of obesity. Severity of steatohepatitis did not significantly influence the lipoprotein profile. Worse atherogenic dyslipidemia was best predicted by the degree of liver fat accumulation and adipose tissue and systemic insulin resistance., Conclusions: NAFLD was associated with a worse atherogenic lipoprotein profile, regardless of similar body mass index and other clinical parameters. We speculate that this lipoprotein profile is driven mostly by liver fat content and insulin resistance and appears not to be worsened by obesity or the severity of liver disease (nonalcoholic steatohepatitis).

Background: Cardiovascular disease (CVD) can occur in individuals with low low-density lipoprotein (LDL) cholesterol (LDL-C). We investigated whether detailed measures of LDL subfractions and other lipoproteins can be used to assess CVD risk in a population with both low LDL-C and high C-reactive protein who were randomized to high-intensity statin or placebo., Methods and Results: In 11 186 Justification for the Use of Statins in Prevention: An Intervention Trial Evaluating Rosuvastatin (JUPITER) participants, we tested whether lipids, apolipoproteins, and ion mobility-measured particle concentrations at baseline and after random allocation to rosuvastatin 20 mg/d or placebo were associated with first CVD events (n=307) or CVD/all-cause death (n=522). In placebo-allocated participants, baseline LDL-C was not associated with CVD (adjusted hazard ratio [HR] per SD, 1.03; 95% confidence interval [CI], 0.88-1.21). In contrast, associations with CVD events were observed for baseline non-high-density lipoprotein (HDL) cholesterol (HR, 1.18; 95% CI, 1.01-1.38), apolipoprotein B (HR, 1.28; 95% CI, 1.11-1.48), and ion mobility-measured non-HDL particles (HR, 1.19; 95% CI, 1.05-1.35) and LDL particles (HR, 1.21; 95% CI, 1.07-1.37). Association with CVD events was also observed for several LDL and very-low-density lipoprotein subfractions but not for ion mobility-measured HDL subfractions. In statin-allocated participants, CVD events were associated with on-treatment LDL-C, non-HDL cholesterol, and apolipoprotein B; these were also associated with CVD/all-cause death, as were several LDL and very-low-density lipoprotein subfractions, albeit with a pattern of association that differed from the baseline risk., Conclusions: In JUPITER, baseline LDL-C was not associated with CVD events, in contrast with significant associations for non-HDL cholesterol and atherogenic particles: apolipoprotein B and ion mobility-measured non-HDL particles, LDL particles, and select subfractions of very-low-density lipoprotein particles and LDL particles. During high-intensity statin therapy, on-treatment levels of LDL-C and atherogenic particles were associated with residual risk of CVD/all-cause death., Clinical Trial Registration: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00239681., (© 2015 American Heart Association, Inc.)

Statin-related myopathy (SRM) undermines drug adherence that is critical for achieving the benefits of lipid-lowering therapy. While the exact mechanism of SRM remains largely unknown, recent evidence supports specific genetic and immunologic influence on the development of intolerance. Genes of interest include those involved in the pharmacokinetics of statin response (i.e. drug metabolism, uptake transporters, and efflux transporters), pharmacodynamics (i.e. drug toxicity and immune-mediated myopathy), and gene expression. We examine the influence of genetic and immunologic variation on the pharmacokinetics, pharmacodynamics, and gene expression of SRM., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)