Background: Apolipoprotein (apo) C-III is involved in several processes that increase triglyceride levels, inflammation, and insulin resistance. Four of its proteoforms have been the focus of several studies and have shown differential associations with cardiovascular risk biomarkers, mostly lipids. However, there are other proteoforms of apoC-III that have not yet been investigated in detail. The aim of this study was to evaluate the associations of seven apoC-III proteoforms with a comprehensive set of biomarkers, including lipid metabolism, inflammation, and glucose homeostasis.
Methods: Seven apoC-III proteoforms (apoC-III0a, apoC-III0b, apoC-III1, apoC-III1d, apoC-III2, apoC-III2d, and apoC-III0f) were measured using a mass spectrometry immunoassay in 875 participants from the cross-sectional study of the Di@bet.es cohort. The complete lipoprotein profile was obtained via the Liposcale test, and the proton nuclear magnetic resonance (1H-NMR)-assessed glycoprotein signals were also obtained as biomarkers of inflammation.
Results: Three proteoform ratios (apoC-III2d, apoC-III2, and apoC-III0f normalized to apoC-III1) showed protective associations with most of the cardiovascular risk biomarkers in comparison with total apoC-III in linear regression models and were negatively associated with triglycerides (β=-0.173, p < 0.001; β=-0.297, p < 0.001; β=-0.223, p = 0.002), very low-density (VLDL) particle concentration (β=-0.133, p < 0.001; β=-0.265, p < 0.001; β=-0.203, p < 0.001), GlycA (β=-0.148, p < 0.001; β=-0.263, p < 0.001; β=-0.211, p < 0.001) and homeostatic model assessment of insulin resistance (HOMA-IR) (β=-0.096, p = 0.003; β=-0.199, p < 0.001; β=-0.114, p = 0.002). These associations were partly independent of total apoC-III concentrations. Participants with high levels of these proteoforms had a lower prevalence of cardiometabolic disorders, such as type 2 diabetes (p = 0.022), obesity (p = 0.001), and metabolic syndrome (p = 0.013).
Conclusions: While apoC-III is positively associated with biomarkers of cardiometabolic risk, the proportions of three apoC-III proteoforms show opposite associations, independent of total apoC-III concentrations. Measuring not only apoC-III but also the proportions of apoC-III proteoforms can provide valuable information since individuals with similar levels of total apoC-III could display opposite lipid profiles depending on the proportion of apoC-III proteoforms.
Background: Increased whole blood viscosity (WBV) was associated with impaired peripheral glucose metabolism, type 2 diabetes, and cardiovascular disease (CVD). Impaired myocardial glucose metabolism is a risk factor for CVD. Whether an increased WBV is associated with impaired myocardial glucose metabolism is still undefined.
Methods: To elucidate this issue, we evaluated the association between WBV and myocardial glucose metabolic rate (MRGlu) in 57 individuals with different glucose tolerance status. Myocardial MRGlu was assessed using dynamic cardiac 18F-FDG PET combined with euglycemic hyperinsulinemic clamp. WBV was calculated using a validated equation including hematocrit and plasma proteins: WBV = [0.12 × h] + [0.17 × (p - 2.07)], where h is the hematocrit (%) and p the plasma proteins (g/dl). The subjects were stratified into tertiles according to their myocardial MrGlu values.
Results: As compared with individuals in the highest myocardial MrGlu tertile, those in the lowest tertile showed an age-adjusted increase in WBV (5.54 ± 0.3 cP vs. 6.13 ± 0.4 cP respectively; P = 0.001), hematocrit (39.1 ± 3.1% vs. 43.2 ± 3.7% respectively; P = 0.004), and total proteins (7.06 ± 0.3 g/l vs. 7.60 ± 0.3 g/l respectively; P < 0.0001). WBV was negatively correlated with myocardial MRGlu (r = - 0.416, P = 0.001). In a stepwise multivariate regression analysis, including several cardiovascular risk factors, the only variables significantly associated with myocardial MrGlu were WBV (β - 0.505; P < 0.0001), fasting insulin (β - 0.346; P = 0.004), fasting plasma glucose (β - 0.287; P = 0.01), and sex (β 0.280; P = 0.003) explaining the 69.6% of its variation.
Conclusions: The current study showed a strongly association between an increase of WBV and an impaired myocardial glucose metabolism in individuals with a broad spectrum of glucose tolerance.
Background: Adipsin (complement factor D, CFD), as the first described adipokine, is well-known for its regulatory effects in diabetic cardiovascular complications. However, its role in diabetic hind-limb ischemia was not clarified. This study aimed to evaluate the possible therapeutic effect of Adipsin in hind-limb ischemia in type 2 diabetic mice and to elucidate the molecular mechanisms involved.
Methods: A high-fat diet and streptozotocin (HFD/STZ)-induced diabetic mouse model, and a transgenic mouse model with adipose tissue-specific overexpression of Adipsin (Adipsin-Tg) were employed. Hindlimb ischemia was established by femoral artery ligation, and blood flow recovery was monitored using Laser Doppler perfusion imaging. Molecular mechanisms underlying Adipsin-potentiated angiogenesis were examined using RNA sequencing and co-immunoprecipitation/mass spectrometry (Co-IP/MS) analyses.
Results: Adipsin expression was upregulated in non-diabetic mice following HLI, while suppressed in diabetic mice, indicating its potential role in ischemic recovery which is impaired in diabetes. Adipsin-Tg mice exhibited significantly improved blood flow recovery, increased capillary density, and enhanced muscle regeneration in comparison with non-transgenic (NTg) diabetic mice. Adipsin facilitated proliferation, migration, and tube formation of human umbilical vein endothelial cells (HUVECs) under hyperglycemic and hypoxic conditions. Additionally, it enhanced phosphorylation of AKT, ERK, and eNOS pathways both in vivo and in vitro. RNA sequencing and co-immunoprecipitation/mass spectrometry (Co-IP/MS) analyses identified that Adipsin promoted angiogenesis by interacting with SERBP1, which disrupted the binding of SERBP1 to SERPINE1 mRNA, resulting in reduced SERPINE1 expression and the subsequent activation of the VEGFR2 signaling cascade.
Conclusions: Adipsin promotes angiogenesis and facilitates blood perfusion recovery in diabetic mice with HLI by downregulating SERPINE1 through interaction with SERBP1. These findings elucidate a novel therapeutic potential for Adipsin in the management of PAD in diabetic patients, highlighting its role in enhancing angiogenesis and tissue repair.
The asialoglycoprotein receptor 1 (ASGR1), a multivalent carbohydrate-binding receptor that primarily is responsible for recognizing and eliminating circulating glycoproteins with exposed galactose (Gal) or N-acetylgalactosamine (GalNAc) as terminal glycan residues, has been implicated in modulating the lipid metabolism and reducing cardiovascular disease burden. In this study, we investigated the impact of ASGR1 deficiency (ASGR1-/-) on atherosclerosis by evaluating its effects on plaque formation, lipid metabolism, circulating immunoinflammatory response, and circulating N-glycome under the hypercholesterolemic condition in ApoE-deficient mice. After 16 weeks of a western-type diet, ApoE-/-/ASGR1-/- mice presented lower plasma cholesterol and triglyceride levels compared to ApoE-/-. This was associated with reduced atherosclerotic plaque area and necrotic core formation. Interestingly, ApoE-/-/ASGR1-/- mice showed increased levels of circulating immune cells, increased AST/ALT ratio, and no changes in the N-glycome profile and liver morphology. The liver of ApoE-/-/ASGR1-/- mice, however, presented alterations in the metabolism of lipids, xenobiotics, and bile secretion, indicating broader alterations in liver homeostasis beyond lipids. These data suggest that improvements in circulating lipid metabolism and atherosclerosis in ASGR1 deficiency is paralleled by a deterioration of liver injury. These findings point to the need for additional evaluation before considering ASGR1 as a pharmacological target for dyslipidemia and cardiovascular disorders.
Background: Globally, cardiovascular disease (CVD) constitutes the primary cause of death, with insulin resistance (IR), measured by the triglyceride-glucose (TyG) index, and visceral obesity, reflected by the Chinese Visceral Adiposity Index (CVAI), as key contributors. However, the relationship between the TyG index and CVAI regarding CVD risk remains insufficiently understood. This research investigates the interactive impact of the TyG index and CVAI on the risk of cardiovascular disease.
Methods: We analyzed data from 8,358 participants from the China Health and Retirement Longitudinal Study (CHARLS) over a 9-year follow-up period. Participants were classified into four groups based on median TyG index (8.59) and CVAI values (101.26), and baseline characteristics were summarized. Missing data were addressed using multiple imputation by chained equations (MICE). Cox proportional hazards models assessed associations between TyG index, CVAI, CVD, coronary heart disease (CHD), and stroke risks, with Kaplan-Meier analysis used for cumulative hazard. Interaction effects were evaluated using both multiplicative and additive measures. Subgroup analyses by age, gender, and clinical conditions were conducted to explore interaction effects across different populations. Sensitivity analyses re-tested models, excluding the covariates BMI and diabetes, using tertiles for classification, and re-evaluating imputed data.
Results: Over the 9-year follow-up, 1,240 participants (14.8%) developed CVD, including 896 cases of CHD and 475 strokes. Kaplan-Meier curves indicated that participants with low TyG index but high CVAI had the highest cumulative hazard of CVD. Cox regression showed that this group had the highest CVD risk (HR = 1.87, 95% CI: 1.57-2.24), followed by those with both high TyG index and high CVAI (HR = 1.75, 95% CI: 1.49-2.06). Interaction analysis revealed a negative interaction effect between high TyG and high CVAI on CVD and CHD risks, with no significant effect on stroke. Subgroup and sensitivity analyses further confirmed these findings, showing consistent results across demographic groups and under various analytical conditions.
Conclusion: This study suggests that the interaction between IR (TyG index) and visceral fat accumulation (CVAI) plays a complex role in CVD risk, with a potential antagonistic effect observed between high TyG and high CVAI on CVD events. These findings highlight the importance of considering both IR and visceral adiposity in CVD risk assessments to improve the identification of high-risk individuals.
Background: The burden of atrial fibrillation (AF) in the intensive care unit (ICU) remains heavy. Glycaemic control is important in the AF management. Glycaemic variability (GV), an emerging marker of glycaemic control, is associated with unfavourable prognosis, and abnormal GV is prevalent in ICUs. However, the impact of GV on the prognosis of AF patients in the ICU remains uncertain. This study aimed to evaluate the relationship between GV and all-cause mortality after ICU admission at short-, medium-, and long-term intervals in AF patients.
Methods: Data was obtained from the Medical Information Mart for Intensive Care IV 3.0 database, with admissions (2008-2019) as primary analysis cohort and admissions (2020-2022) as external validation cohort. Multivariate Cox proportional hazards models, and restricted cubic spline analyses were used to assess the associations between GV and mortality outcomes. Subsequently, GV and other clinical features were used to construct machine learning (ML) prediction models for 30-day all-cause mortality after ICU admission.
Results: The primary analysis cohort included 8989 AF patients (age 76.5 [67.7-84.3] years; 57.8% male), while the external validation cohort included 837 AF patients (age 72.9 [65.3-80.2] years; 67.4% male). Multivariate Cox proportional hazards models revealed that higher GV quartiles were associated with higher risk of 30-day (Q3: HR 1.19, 95%CI 1.04-1.37; Q4: HR 1.33, 95%CI 1.16-1.52), 90-day (Q3: HR 1.25, 95%CI 1.11-1.40; Q4: HR 1.34, 95%CI 1.29-1.50), and 360-day (Q3: HR 1.21, 95%CI 1.09-1.33; Q4: HR 1.33, 95%CI 1.20-1.47) all-cause mortality, compared with lowest GV quartile. Moreover, our data suggests that GV needs to be contained within 20.0%. Among all ML models, light gradient boosting machine had the best performance (internal validation: AUC [0.780], G-mean [0.551], F1-score [0.533]; external validation: AUC [0.788], G-mean [0.578], F1-score [0.568]).
Conclusion: GV is a significant predictor of ICU short-term, mid-term, and long-term all-cause mortality in patients with AF (the potential risk stratification threshold is 20.0%). ML models incorporating GV demonstrated high efficiency in predicting short-term mortality and GV was ranked anterior in importance. These findings underscore the potential of GV as a valuable biomarker in guiding clinical decisions and improving patient outcomes in this high-risk population.
Background: Type 1 diabetes increases the risk of coronary artery disease (CAD). High-throughput metabolomics may be utilized to identify metabolites associated with disease, thus, providing insight into disease pathophysiology, and serving as predictive markers in clinical practice. Urine is less tightly regulated than blood, and therefore, may enable earlier discovery of disease-associated markers. We studied urine metabolomics in relation to incident CAD in individuals with type 1 diabetes.
Methods: We prospectively studied CAD in 2501 adults with type 1 diabetes from the Finnish Diabetic Nephropathy Study. 209 participants experienced incident CAD within the 10-year follow-up. We analyzed the baseline urine samples with a high-throughput targeted urine metabolomics platform, which yielded 54 metabolites. With the data, we performed metabolome-wide survival analyses, correlation network analyses, and metabolomic state profiling for prediction of incident CAD.
Results: Urinary 3-hydroxyisobutyrate was associated with decreased 10-year incident CAD, which according to the network analysis, likely reflects younger age and improved kidney function. Urinary xanthosine was associated with 10-year incident CAD. In the network analysis, xanthosine correlated with baseline urinary allantoin, which is a marker of oxidative stress. In addition, urinary trans-aconitate and 4-deoxythreonate were associated with decreased 5-year incident CAD. Metabolomic state profiling supported the usage of CAD-associated urinary metabolites to improve prediction accuracy, especially during shorter follow-up. Furthermore, urinary trans-aconitate and 4-deoxythreonate were associated with decreased 5-year incident CAD. The network analysis further suggested glomerular filtration rate to influence the urinary metabolome differently between individuals with and without future CAD.
Conclusions: We have performed the first high-throughput urinary metabolomics analysis on CAD in individuals with type 1 diabetes and found xanthosine, 3-hydroxyisobutyrate, trans-aconitate, and 4-deoxythreonate to be associated with incident CAD. In addition, metabolomic state profiling improved prediction of incident CAD.
Diabetic cardiomyopathy (DCM) is a severe cardiovascular complication of diabetes characterized by myocardial hypertrophy, fibrosis, and impaired cardiac function. Fibroblast growth factor 21 (FGF21) has emerged as a promising therapeutic target due to its antifibrotic, antioxidant, and anti-inflammatory properties. Our commentary summarizes and affirms the recent study by Wang et al., which demonstrates the significant role of ferroptosis in DCM pathogenesis. FGF21 has shown promise as a therapeutic target for DCM, potentially inhibiting ferroptosis, mitigating oxidative damage, and protecting cardiomyocyte function. Mechanistically, the study identified ATF4 as an upstream regulator of FGF21 in DCM, revealing that FGF21 directly interacts with ferritin and extends its half-life, thus inhibiting ferroptosis in DCM. These findings provide a theoretical basis for understanding the pathogenesis and treatment of DCM. Our commentary suggests that future studies should explore the role of non-cardiomyocyte cell types in DCM, verify findings with clinical samples, and address comprehensive methods for ferroptosis detection. Additionally, we discuss the clinical application and future potential of FGF21-based therapies for DCM. Such efforts may contribute to advancing DCM diagnosis and treatment, fostering the development of innovative therapeutic strategies.
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