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A special issue of Nutrients (ISSN 2072-6643). This special issue belongs to the section "Lipids".

Deadline for manuscript submissions: closed (15 February 2025) | Viewed by 13544

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Dr. Ernst J. Schaefer

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Guest Editor

1. Boston Heart Diagnostics/Eurofins Scientific Network, Framingham, MA, USA
2. Department of Medicine, Tufts University School of Medicine, Boston, MA, USA
Interests: lipids; lipoproteins; lipid disorders; cardiovascular health; obesity; diabetes; nutrition; lifestyle; genetics; disease prevention

Special Issue Information

Dear Colleagues,

Cardiovascular disease (CVD) is a leading cause of death and disability. CVD consists mainly of coronary heart disease and stroke. Major CVD risk factors include increased age, male sex, hypertension, diabetes, smoking, elevated total serum cholesterol due to elevated low density lipoprotein cholesterol (LDL-C), elevated lipoprotein(a) or Lp(a), increased homocysteine, decreased high density lipoprotein cholesterol (HDL-C), obesity, and decreased kidney function. The measurement of CVD risk factors and CVD risk assessment will be reviewed. Both lifestyle and genetics play important roles in the regulation of CVD risk and risk factors. Diets high in saturated fat, trans fats, cholesterol, and sugar and low in plant oils and omega-3 fatty acids have been associated with increased CVD risk. The measurement of biochemical risk factors will be reviewed. In addition, effective medications are available for the control of CVD risk factors, including hypertension, diabetes, smoking, and lipid abnormalities. All of these topics will be reviewed in this Special Issue.

Dr. Ernst J. Schaefer
Guest Editor

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Keywords

lipids
lipoproteins
lipid disorders
cardiovascular health
obesity
diabetes
nutrition
lifestyle
genetics
disease prevention

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Published Papers (8 papers)

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Research

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13 pages, 721 KiB

Open AccessArticle

Lifestyle Modification in Prediabetes and Diabetes: A Large Population Analysis

by Michael L. Dansinger, Joi A. Gleason, Julia Maddalena, Bela F. Asztalos and Margaret R. Diffenderfer

Nutrients 2025, 17(8), 1333; https://doi.org/10.3390/nu17081333 - 11 Apr 2025

Viewed by 1540

Abstract

Background/Aims: Diabetes mellitus is a major cause of atherosclerotic cardiovascular disease (ASCVD). We examined a large population and tested the efficacy of a voluntary lifestyle program in prediabetic and diabetic subjects. Methods: Of 133,764 subjects, 56.3% were healthy, 36.2% were prediabetic, and 7.5% were diabetic. Fasting serum measurements of glucose, insulin, adiponectin, glycosylated hemoglobin (HbA1c), high-sensitivity C-reactive protein (hs-CRP), glycated serum protein (GSP), fibrinogen, myeloperoxidase (MPO), lipoprotein-associated phospholipase A₂ (LpPLA₂), as well as standard lipids, direct low-density lipoprotein cholesterol (LDL-C), and small dense LDL-C (sdLDL-C) were performed using standard automated assays. Follow-up sampling at 6–12 months occurred in 20.1% of the prediabetic and 22.2% of the diabetic subjects; of these, 12.2% of the prediabetic and 9.7% of the diabetic subjects participated in a voluntary, real-world, digital dietitian-directed lifestyle-modification program with a 10-year diabetes risk being calculated using a biochemical model (Framingham). Results: Prediabetic and diabetic subjects had significantly elevated triglycerides, sdLDL-C, and hs-CRP and decreased HDL-C. They were insulin resistant as compared to healthy subjects, but only diabetics had significant reductions in insulin production. Lifestyle modification significantly reduced diabetes risk by 45.6% in prediabetics and significantly increased (2.4-fold) the percentage of diabetics that were in remission at follow-up (8.2% versus 3.4%) with increased weight loss (6.5 versus 2.0 pounds). Lifestyle intervention resulted in significant favorable effects on many metabolic markers. Conclusions: The measurement of fasting glucose and insulin is essential for the detection of decreased insulin production in diabetics. A digital lifestyle program can have favorable effects on ASCVD risk factors and diabetic status. Full article

(This article belongs to the Special Issue Impact of Lipids on Cardiovascular Health)

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19 pages, 11461 KiB

Open AccessArticle

Lipoprotein(a) and Risk of Incident Atherosclerotic Cardiovascular Disease: Impact of High-Sensitivity C-Reactive Protein and Risk Variability Among Human Clinical Subgroups

by Ron C. Hoogeveen, Margaret R. Diffenderfer, Elise Lim, Ching-Ti Liu, Hiroaki Ikezaki, Weihua Guan, Michael Y. Tsai and Christie M. Ballantyne

Nutrients 2025, 17(8), 1324; https://doi.org/10.3390/nu17081324 - 11 Apr 2025

Cited by 1 | Viewed by 1219

Abstract

Background/Objectives: Elevated lipoprotein(a) [Lp(a)] is associated with increased incidence of atherosclerotic cardiovascular disease (ASCVD). We aimed to assess the utility of Lp(a) as an ASCVD risk-enhancing factor, as recommended by the 2019 ACC/AHA guidelines on ASCVD primary prevention, and to determine whether C-reactive protein (CRP) modifies the association of elevated Lp(a) with ASCVD risk. Methods: Lp(a), high sensitivity CRP (hs-CRP), and other ASCVD risk factors, including blood lipids, blood pressure, diabetes status, body weight and height, and smoking, were measured in 15,933 participants (median age 61.7 years with 25th–75th percentiles 57–68 years, 56.7% female, 19.7% Black, free of ASCVD at baseline) in the Atherosclerosis Risk in Communities Study, Framingham Offspring Study, and Multi-Ethnic Study of Atherosclerosis. Participants were followed for 10 years for incident ASCVD (coronary heart disease (CHD) or stroke) and CHD (including angioplasty and/or coronary artery bypass but minus stroke). These endpoints occurred in 9.7% and 7.4% of subjects, respectively. Results: Compared with the lowest Lp(a) category (<10 mg/dL), the highest Lp(a) category (≥50 mg/dL) carried a significantly increased incidence of ASCVD (hazard ratio [HR] = 1.31; 95% confidence interval [CI] 1.15–1.50; p < 0.001) and CHD (HR = 1.49; 95%CI 1.27–1.75; p < 0.001). The association of elevated Lp(a) with incident ASCVD was stronger in males and non-Black individuals and was independent of diabetes status. Lp(a) levels ≥ 50 mg/dL predicted the 10-year ASCVD risk for those at intermediate risk (≥7.5%, HR = 1.32; 95%CI 1.15–1.52; p < 0.001). There was a significant interaction between Lp(a) and hs-CRP; individuals with concomitant elevated levels of Lp(a) and hs-CRP had the highest ASCVD risk. Conclusions: Elevated Lp(a) levels were associated with increased ASCVD risk, particularly in individuals with concomitantly elevated hs-CRP levels and those at intermediate 10-year ASCVD risk. Full article

(This article belongs to the Special Issue Impact of Lipids on Cardiovascular Health)

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18 pages, 680 KiB

Open AccessArticle

High-Density Lipoprotein Particles, Inflammation, and Coronary Heart Disease Risk

by Eveline O. Stock, Bela F. Asztalos, John M. Miller, Lihong He, Kate Townsend Creasy, Rachel Schwemberger, Alexander Quinn, Clive R. Pullinger, Mary J. Malloy, Margaret R. Diffenderfer and John P. Kane

Nutrients 2025, 17(7), 1182; https://doi.org/10.3390/nu17071182 - 28 Mar 2025

Cited by 2 | Viewed by 1163

Abstract

Background: Coronary heart disease (CHD) remains a leading cause of death and has been associated with alterations in plasma lipoprotein particles and inflammation markers. This study aimed to evaluate and compare standard and advanced lipid parameters and inflammatory biomarkers in CHD cases and matched control subjects. We hypothesized that incorporating advanced lipid and inflammatory biomarkers into risk models would improve CHD risk prediction beyond the standard lipid measures. Methods: CHD cases (n = 227, mean age 61 years, 47% female) and matched controls (n = 526) underwent fasting blood collection while off lipid-lowering medications. Automated chemistry analyses were performed to measure total cholesterol (TC), triglycerides (TGs), low-density lipoprotein-C (LDL-C), small dense LDL-C (sdLDL-C), apolipoproteins (apos) A-I and B, lipoprotein(a) (Lp(a)), high-sensitivity C-reactive protein (hsCRP), serum amyloid-A (SAA), myeloperoxidase (MPO), and apoA-I in HDL particles (via 2-dimensional electrophoresis and immunoblotting). Univariate, multivariate, and machine learning analyses compared the CHD cases with the controls. Results: The most significant percent differences between male and female cases versus controls were for hsCRP (+78%, +200%), MPO (+109%, +106%), SAA (+84%, +33%), sdLDL-C (+48%; +43%), Lp(a) (+43%,+70%), apoA-I in very large α-1 HDL (−34%, −26%), HDL-C (−24%, −27%), and apoA-I in very small preβ-1 HDL (+17%; +16%). Total C, non-HDL-C, and direct and calculated LDL-C levels were only modestly higher in the cases. Multivariate models incorporating advanced parameters were statistically superior to a standard model (C statistic: men: 0.913 vs. 0.856; women: 0.903 versus 0.838). Machine learning identified apoA-I in preβ-1-HDL, α-2-HDL, α-1-HDL, α-3-HDL, MPO, and sdLDL-C as the top predictors of CHD. Conclusions: This study introduces a novel approach to CHD risk assessment by integrating advanced HDL particle analysis and machine learning. By assessing HDL subpopulations (α-1, α-2, preβ-1 HDL), inflammatory biomarkers (MPO, SAA), and small dense LDL, we provide a more refined stratification model. Notably, preβ-1 HDL, an independent risk factor reflecting impaired cholesterol efflux from the artery wall, is highlighted as a critical marker of CHD risk. Our approach allows for earlier identification of high-risk individuals, particularly those with subtle lipid or inflammatory abnormalities, supporting more personalized interventions. These findings demonstrate the potential of advanced lipid profiling and machine learning to enhance CHD risk prediction. Full article

(This article belongs to the Special Issue Impact of Lipids on Cardiovascular Health)

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13 pages, 233 KiB

Open AccessArticle

Diabetes Mellitus Risk Prediction in the Framingham Offspring Study and Large Population Analysis

by Masumi Ai, Seiko Otokozawa, Ching-Ti Liu, Bela F. Asztalos, Julia Maddalena, Margaret R. Diffenderfer, Giuseppina Russo, Nuntakorn Thongtang and Michael L. Dansinger

Nutrients 2025, 17(7), 1117; https://doi.org/10.3390/nu17071117 - 24 Mar 2025

Cited by 1 | Viewed by 852

Abstract

Background: Diabetes mellitus is a major cause of death and a significant risk factor for cardiovascular disease, kidney failure, neuropathy, and retinopathy. Our objectives were to develop a diabetes risk model and apply it to a large population. Methods: Non-diabetic adults in the Framingham Offspring Study (n = 2416) were followed for 10 years for new diabetes. At baseline, the fasting serum glucose, adiponectin, insulin, glycated albumin, total cholesterol, triglycerides (TG), and high-density lipoprotein cholesterol (HDL-C) were measured using standardized automated assays. Standard health information was collected. Diabetes risk prediction models were developed using logistic regression analysis and applied to a large population (n = 133,764). Results: In this prospective study, 166 subjects (6.9%) developed new-onset diabetes. Glucose, body mass index (BMI), log adiponectin, % log glycated albumin, parental diabetes, TG, and the use of cholesterol-lowering medications entered the model (C statistic: 0.924; 0.898, biochemical variables: 0.898, and fasting glucose: only 0.876). In the population in non-diabetic subjects (56.3) and prediabetic subjects (36.2%), the predicted 10-year diabetes risk rates were 0.4% and 5.5% with the biochemical model, respectively. Prediabetic and diabetic subjects were insulin-resistant compared to non-diabetic subjects, but only those with diabetes had significant reductions in their insulin production. Conclusions: The 10-year risk of diabetes can be accurately predicted and applied to large populations. Fasting glucose alone is diagnostic for diabetes and is an excellent predictor of future diabetes, with having prediabetes increasing the risk 6-fold. Insulin and C-peptide measurements are useful in diabetic subjects to detect decreased insulin production and the need for insulin therapy. Full article

(This article belongs to the Special Issue Impact of Lipids on Cardiovascular Health)

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20 pages, 2401 KiB

Open AccessArticle

Precision Medicine in Cardiovascular Disease Prevention: Clinical Validation of Multi-Ancestry Polygenic Risk Scores in a U.S. Cohort

by Małgorzata Ponikowska, Paolo Di Domenico, Alessandro Bolli, George Bartholomew Busby, Emma Perez and Giordano Bottà

Nutrients 2025, 17(5), 926; https://doi.org/10.3390/nu17050926 - 6 Mar 2025

Viewed by 1574

Abstract

Background: Polygenic risk score (PRS) quantifies the cumulative effects of common genetic variants across the genome, including both coding and non-coding regions, to predict the risk of developing common diseases. In cardiovascular medicine, PRS enhances risk stratification beyond traditional clinical risk factors, offering a precision medicine approach to coronary artery disease (CAD) prevention. This study evaluates the predictive performance of a multi-ancestry PRS framework for cardiovascular risk assessment using the All of Us (AoU) short-read whole-genome sequencing dataset comprising over 225,000 participants. Methods: We developed PRSs for lipid traits (LDL-C, HDL-C, triglycerides) and cardiometabolic conditions (type 2 diabetes, hypertension, atrial fibrillation) and constructed two metaPRSs: one integrating lipid and cardiometabolic PRSs (risk factor metaPRS) and another incorporating CAD PRSs in addition to these risk factors (risk factor + CAD metaPRS). Predictive performance was evaluated separately for each trait-specific PRS and for both metaPRSs to assess their effectiveness in CAD risk prediction across diverse ancestries. Model predictive performance, including calibration, was assessed separately for each ancestry group, ensuring that all metrics were ancestry-specific and that PRSs remain generalizable across diverse populations Results: PRSs for lipids and cardiometabolic conditions demonstrated strong predictive performance across ancestries. The risk factors metaPRS predicted CAD risk across multiple ancestries. The addition of a CAD-specific PRS to the risk factors metaPRS improved predictive performance, highlighting a genetic component in CAD etiopathology that is not fully captured by traditional risk factors, whether clinically measured or genetically inferred. Model calibration and validation across ancestries confirmed the broad applicability of PRS-based approaches in multi-ethnic populations. Conclusion: PRS-based risk stratification provides a reliable, ancestry-inclusive framework for personalized cardiovascular disease prevention, enabling better targeted interventions such as pharmacological therapy and lifestyle modifications. By incorporating genetic information from both coding and non-coding regions, PRSs refine risk prediction across diverse populations, advancing the integration of genomics into precision medicine for common diseases Full article

(This article belongs to the Special Issue Impact of Lipids on Cardiovascular Health)

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15 pages, 1516 KiB

Open AccessArticle

Body Mass Index and Cardiovascular Risk Markers: A Large Population Analysis

by Bela F. Asztalos, Giuseppina Russo, Lihong He and Margaret R. Diffenderfer

Nutrients 2025, 17(5), 740; https://doi.org/10.3390/nu17050740 - 20 Feb 2025

Cited by 3 | Viewed by 1677

Abstract

Background/Objectives. An elevated body mass index (BMI) has been added to the new American Heart Association atherosclerotic cardiovascular disease (ASCVD) risk model. Our goal in this study was to examine the relationships between BMI and traditional and non-traditional ASCVD risk factors. Methods. We measured levels of blood glucose, insulin, lipids, lipoproteins, sterols, fatty acids, markers of inflammation and oxidative stress, and hormones in 226,000 middle-aged and elderly subjects (55% women) and associated those parameters to BMI in 5 groups (BMI 20–25, 25.1–30, 30.1–35, 35.1–40, and >40 kg/m²). Results. BMI and age were inversely correlated in both sexes. All of the traditional and non-traditional ASCVD risk markers, except low-density lipoprotein cholesterol (LDL-C), changed significantly in unfavorable ways in both sexes with increasing BMI. The largest changes were observed in the high sensitivity C-reactive protein, which increased 6- and 8-fold, and insulin, which increased 4- and 3-fold between the lowest and highest BMI groups in men and women, respectively. Although the LDL-C levels changed little, small dense LDL-C and triglyceride levels increased significantly with increasing BMI. Markers of cholesterol synthesis were positively associated with BMI, while markers of cholesterol absorption and omega-3 fatty acids were inversely associated with BMI. Concentrations of high-density lipoprotein cholesterol (HDL-C) and the athero-protective, large-size HDL particles were also inversely associated with BMI. Our analysis indicated that the associations between an elevated BMI and unfavorable changes in major ASCVD risk factors were independent of age in both sexes. Moreover, we observed that ASCVD risk factors started changing unfavorably with increasing BMI even in the normal weight range (BMI 20–25 kg/m²). Conclusions. An elevated BMI is associated with unfavorable changes in traditional and non-traditional ASCVD risk factors independent of age. Therefore, maintaining a normal BMI, preferably by an active lifestyle, and, if necessary, weight-managing medication, is very important to avoid developing conditions leading to ASCVD. Full article

(This article belongs to the Special Issue Impact of Lipids on Cardiovascular Health)

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14 pages, 1922 KiB

Open AccessArticle

Effect of Moderate Beer Intake on the Lipid Composition of Human Red Blood Cell Membranes

by Anallely López-Yerena, Natalia Muñoz-García, Victoria de Santisteban Villaplana, Teresa Padro and Lina Badimon

Nutrients 2024, 16(20), 3541; https://doi.org/10.3390/nu16203541 - 18 Oct 2024

Viewed by 2467

Abstract

Background/Objectives: Growing evidence suggests that erythrocyte membrane lipids are subject to changes during their lifespan. Factors such as the type of dietary intake and its composition contribute to the changes in red blood cell (RBC) membranes. Due to the high antioxidant content of beer, we aimed to investigate the effect of moderate beer consumption on the lipid composition of RBCs membranes from healthy overweight individuals. Methods: We conducted a four-weeks, prospective two-arm longitudinal crossed-over study, where participants (n = 36) were randomly assigned to alcohol-free beer group or traditional beer group. The lipids of RBCs membranes were assessed at the beginning and the end of the intervention by thin-layer chromatography. Results: Four-weeks of alcohol-free beer promoted changes in fatty acids (FA), free cholesterol (FC), phosphatidylethanolamine (PE) and phosphatidylcholine (PC) (p < 0.05). Meanwhile, traditional beer intake led to changes in FA, FC, phospholipids (PL), PE and PC (p < 0.05). The observed alterations in membrane lipids were found to be independent of sex and BMI as influencing factors. Conclusions: The lipid composition of erythrocyte membranes is distinctly but mildly influenced by the consumption of both non-alcoholic and conventional beer, with no effects on RBC membrane fluidity. Full article

(This article belongs to the Special Issue Impact of Lipids on Cardiovascular Health)

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Review

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24 pages, 2925 KiB

Open AccessReview

A Comprehensive Review of the Genetics of Dyslipidemias and Risk of Atherosclerotic Cardiovascular Disease

by Megan Kalwick and Mendel Roth

Nutrients 2025, 17(4), 659; https://doi.org/10.3390/nu17040659 - 12 Feb 2025

Cited by 1 | Viewed by 2305

Abstract

Dyslipidemias are often diagnosed based on an individual’s lipid panel that may or may not include Lp(a) or apoB. But these values alone omit key information that can underestimate risk and misdiagnose disease, which leads to imprecise medical therapies that reduce efficacy with unnecessary adverse events. For example, knowing whether an individual’s dyslipidemia is monogenic can granularly inform risk and create opportunities for precision therapeutics. This review explores the canonical and non-canonical causes of dyslipidemias and how they impact atherosclerotic cardiovascular disease (ASCVD) risk. This review emphasizes the multitude of genetic causes that cause primary hypercholesterolemia, hypertriglyceridemia, and low or elevated high-density lipoprotein (HDL)-cholesterol levels. Within each of these sections, this review will explore the evidence linking these genetic conditions with ASCVD risk. Where applicable, this review will summarize approved therapies for a particular genetic condition. Full article

(This article belongs to the Special Issue Impact of Lipids on Cardiovascular Health)

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