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- Arnold, Natalie, et al.
(author)
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Impact of lipoprotein(a) level on low-density lipoprotein cholesterol– or apolipoprotein B–related risk of coronary heart disease
- 2024
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In: Journal of the American College of Cardiology. - : Elsevier. - 0735-1097 .- 1558-3597. ; 84:2, s. 165-177
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Journal article (peer-reviewed)abstract
- Background: Conventional low-density lipoprotein cholesterol (LDL-C) quantification includes cholesterol attributable to lipoprotein(a) (Lp(a)-C) due to their overlapping densities.Objectives: The purposes of this study were to compare the association between LDL-C and LDL-C corrected for Lp(a)-C (LDLLp(a)corr) with incident coronary heart disease (CHD) in the general population and to investigate whether concomitant Lp(a) values influence the association of LDL-C or apolipoprotein B (apoB) with coronary events.Methods: Among 68,748 CHD-free subjects at baseline LDLLp(a)corr was calculated as “LDL-C—Lp(a)-C,” where Lp(a)-C was 30% or 17.3% of total Lp(a) mass. Fine and Gray competing risk-adjusted models were applied for the association between the outcome incident CHD and: 1) LDL-C and LDLLp(a)corr in the total sample; and 2) LDL-C and apoB after stratification by Lp(a) mass (≥/<90th percentile).Results: Similar risk estimates for incident CHD were found for LDL-C and LDL-CLp(a)corr30 or LDL-CLp(a)corr17.3 (subdistribution HR with 95% CI) were 2.73 (95% CI: 2.34-3.20) vs 2.51 (95% CI: 2.15-2.93) vs 2.64 (95% CI: 2.26-3.10), respectively (top vs bottom fifth; fully adjusted models). Categorization by Lp(a) mass resulted in higher subdistribution HRs for uncorrected LDL-C and incident CHD at Lp(a) ≥90th percentile (4.38 [95% CI: 2.08-9.22]) vs 2.60 [95% CI: 2.21-3.07]) at Lp(a) <90th percentile (top vs bottom fifth; Pinteraction0.39). In contrast, apoB risk estimates were lower in subjects with higher Lp(a) mass (2.43 [95% CI: 1.34-4.40]) than in Lp(a) <90th percentile (3.34 [95% CI: 2.78-4.01]) (Pinteraction0.49).Conclusions: Correction of LDL-C for its Lp(a)-C content provided no meaningful information on CHD-risk estimation at the population level. Simple categorization of Lp(a) mass (≥/<90th percentile) influenced the association between LDL-C or apoB with future CHD mostly at higher Lp(a) levels.
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- Batra, Gorav, et al.
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Biomarker-Based Prediction of Recurrent Ischemic Events in Patients With Acute Coronary Syndromes
- 2022
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In: Journal of the American College of Cardiology. - : Elsevier. - 0735-1097 .- 1558-3597. ; 80:18, s. 1735-1747
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Journal article (peer-reviewed)abstract
- BACKGROUND: In patients with acute coronary syndrome (ACS), there is residual and variable risk of recurrent ischemic events.OBJECTIVES: This study aimed to develop biomarker-based prediction models for 1-year risk of cardiovascular (CV) death and myocardial infarction (MI) in patients with ACS undergoing percutaneous coronary intervention.METHODS: We included 10,713 patients from the PLATO (A Comparison of Ticagrelor [AZD6140] and Clopidogrel in Patients With Acute Coronary Syndrome) trial in the development cohort and externally validated in 3,508 patients from the TRACER (Thrombin Receptor Antagonist for Clinical Event Reduction in Acute Coronary Syndrome) trial. Variables contributing to risk of CV death/MI were assessed using Cox regression models, and a score was derived using subsets of variables approximating the full model.RESULTS: There were 632 and 190 episodes of CV death/MI in the development and validation cohorts. The most important predictors of CV death/MI were the biomarkers, growth differentiation factor 15, and N-terminal pro-B-type natriuretic peptide, which had greater prognostic value than all candidate variables. The final model included 8 items: age (A), biomarkers (B) (growth differentiation factor 15 and N-terminal pro-B-type natriuretic peptide), and clinical variables (C) (extent of coronary artery disease, previous vascular disease, Killip class, ACS type, P2Y12 inhibitor). The model, named ABC-ACS ischemia, was well calibrated and showed good discriminatory ability for 1-year risk of CV death/MI with C-indices of 0.71 and 0.72 in the development and validation cohorts, respectively. For CV death, the score performed better, with C-indices of 0.80 and 0.84 in the development and validation cohorts, respectively.CONCLUSIONS: An 8-item score for the prediction of CV death/MI was developed and validated for patients with ACS undergoing percutaneous coronary intervention. The ABC-ACS ischemia score showed good calibration and discrimination and might be useful for risk prediction and decision support in patients with ACS. (A Comparison of Ticagrelor [AZD6140] and Clopidogrel in Patients With Acute Coronary Syndrome [PLATO]; NCT00391872; Trial to Assess the Effects of Vorapaxar [SCH 530348; MK-5348] in Preventing Heart Attack and Stroke in Participants With Acute Coronary Syndrome [TRACER]; NCT00527943)
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- Behrouzi, Bahar, et al.
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Influenza Vaccination to Reduce Cardiovascular Morbidity and Mortality in Patients With COVID-19 : JACC State-of-the-Art Review
- 2020
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In: Journal of the American College of Cardiology. - : Elsevier. - 0735-1097 .- 1558-3597. ; 76:15, s. 1777-1794
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Research review (peer-reviewed)abstract
- Viral respiratory infections are risk factors for cardiovascular disease (CVD). Underlying CVD is also associated with an increased risk of complications following viral respiratory infections, including increased morbidity, mortality, and health care utilization. Globally, these phenomena are observed with seasonal influenza and with the current coronavirus disease 2019 (COVID-19) pandemic. Persons with CVD represent an important target population for respiratory virus vaccines, with capacity developed within 3 large ongoing influenza vaccine cardiovascular outcomes trials to determine the potential cardioprotective effects of influenza vaccines. In the context of COVID-19, these international trial networks may be uniquely positioned to redeploy infrastructure to study therapies for primary and secondary prevention of COVID-19. Here, we describe mechanistic links between influenza and COVID-19 infection and the risk of acute cardiovascular events, summarize the data to date on the potential cardioprotective effects of influenza vaccines, and describe the ongoing influenza vaccine cardiovascular outcomes trials, highlighting important lessons learned that are applicable to COVID-19.
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- Björnson, Elias, 1988, et al.
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Lipoprotein(a) Is Markedly More Atherogenic Than LDL: An Apolipoprotein B-Based Genetic Analysis
- 2024
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In: Journal of the American College of Cardiology. - 0735-1097 .- 1558-3597. ; 83:3, s. 385-395
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Journal article (peer-reviewed)abstract
- Background: Lipoprotein(a) (Lp(a)) is recognized as a causal factor for coronary heart disease (CHD) but its atherogenicity relative to that of low-density lipoprotein (LDL) on a per-particle basis is indeterminate. Objectives: The authors addressed this issue in a genetic analysis based on the fact that Lp(a) and LDL both contain 1 apolipoprotein B (apoB) per particle. Methods: Genome-wide association studies using the UK Biobank population identified 2 clusters of single nucleotide polymorphisms: one comprising 107 variants linked to Lp(a) mass concentration, the other with 143 variants linked to LDL concentration. In these Lp(a) and LDL clusters, the relationship of genetically predicted variation in apoB with CHD risk was assessed. Results: The Mendelian randomization-derived OR for CHD for a 50 nmol/L higher Lp(a)-apoB was 1.28 (95% CI: 1.24-1.33) compared with 1.04 (95% CI: 1.03-1.05) for the same increment in LDL-apoB. Likewise, use of polygenic scores to rank subjects according to difference in Lp(a)-apoB vs difference in LDL-apoB revealed a greater HR for CHD per 50 nmol/L apoB for the Lp(a) cluster (1.47; 95% CI: 1.36-1.58) compared with the LDL cluster (1.04; 95% CI: 1.02-1.05). From these data, we estimate that the atherogenicity of Lp(a) is approximately 6-fold (point estimate of 6.6; 95% CI: 5.1-8.8) greater than that of LDL on a per-particle basis. Conclusions: We conclude that the atherogenicity of Lp(a) (CHD risk quotient per unit increase in particle number) is substantially greater than that of LDL. Therefore, Lp(a) represents a key target for drug-based intervention in a significant proportion of the at-risk population.
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