ReviewNutrients2024
Emerging Biomarkers and Determinants of Lipoprotein Profiles to Predict CVD Risk: Implications for Precision Nutrition.
Review in Nutrients, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Novel Cerebrovascular Disease Blood Biomarkers Identified by Targeted Proteomics in a High-Risk Native American Population.World neurosurgery · 2026Article
- Do nutritional variables improve cardiovascular disease prediction? A comparative machine learning analysis.Frontiers in nutrition · 2026Article
- Review
- Article
- Association between fibrosis-4 index and coronary heart disease: a population-based study.BMC cardiovascular disorders · 2025Article
- Effects of a competitive season on the plasma lipid profile of soccer players.Physiological reports · 2025Article
- Nutrition and Lifestyle Interventions in Managing Dyslipidemia and Cardiometabolic Risk.Nutrients · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Biomarkers constitute a valuable tool to diagnose both the incidence and the prevalence of chronic diseases and may help to inform the design and effectiveness of precision nutrition interventions. Cardiovascular disease (CVD) continues to be the foremost cause of death all over the world. While the reasons that lead to increased risk for CVD are multifactorial, dyslipidemias, plasma concentrations of specific lipoproteins, and dynamic measures of lipoprotein function are strong biomarkers to predict and document coronary heart disease incidence. The aim of this review is to provide a comprehensive evaluation of the biomarkers and emerging approaches that can be utilized to characterize lipoprotein profiles as predictive tools for assessing CVD risk, including the assessment of traditional clinical lipid panels, measures of lipoprotein efflux capacity and inflammatory and antioxidant activity, and omics-based characterization of lipoprotein composition and regulators of lipoprotein metabolism. In addition, we discuss demographic, genetic, metagenomic, and lifestyle determinants of lipoprotein profiles-such as age, sex, gene variants and single-nucleotide polymorphisms, gut microbiome profiles, dietary patterns, physical inactivity, obesity status, smoking and alcohol intake, and stress-which are likely to be essential factors to explain interindividual responses to precision nutrition recommendations to mitigate CVD risk.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.