Search Results (165)

Background: Heterozygous familial hypercholesterolemia (HeFH) is characterized by elevated low-density lipoprotein cholesterol (LDL-C) and increased cardiovascular risk, making early diagnosis essential; however, the diagnostic performance of pediatric criteria is heterogeneous. This study evaluated the effectiveness of different diagnostic criteria and scoring systems to select children for genetic testing. Materials and methods: A total of 214 pediatric subjects with suspected HeFH were included, recruited from patients followed at a tertiary care center, based on LDL-C levels ≥ 95th age- and sex-specific percentile in both the proband and one biological parent. All subjects underwent genetic analysis of the main FH-associated genes (LDLR, APOB, PCSK9). The following diagnostic criteria and scoring systems were retrospectively evaluated and compared with genetic findings: Simon Broome Register (SBR), Dutch Lipid Clinic Network (DLCN), European Atherosclerosis Society (EAS), American Heart Association (AHA), Familial Hypercholesterolemia Canada Network (FH-CAN), Japanese Atherosclerosis Society (JAS), Lipid TransPort Disorders Italian Genetic Network for Italian pediatric patients (LIPIGEN-FH-PED), and the Familial Hypercholesterolemia Pediatric Diagnostic Score (FH-PeDS). Results: Pathogenic variants were identified in 91.8% of subjects. Approaches using lower LDL-C thresholds minimized the loss of variant-positive individuals (particularly JAS and FH-PeDS, with a missed diagnoses rate of 1.6%), whereas more restrictive definitions excluded a substantial proportion of affected patients (10.5% SBR, 56.3% DLCN, 6.3% EAS, 6.3% AHA, 7.4% FH-CAN, and 6.3% LIPIGEN-FH-PED). The mutation detection rate (MDR) was >91% for all examined criteria. Conclusions: Several current diagnostic criteria may underestimate the true number of children carrying FH-associated variants. Less selective criteria enable the identification of a greater number of FH-positive individuals while maintaining a high MDR, thus supporting the prioritization of identifying as many affected children as possible in the pediatric setting. This cohort reflects a tertiary referral population rather than the general population; therefore, further studies are needed to evaluate the applicability of our findings to broader public health contexts and screening settings. Full article

Residual cardiovascular risk arises from dysregulated expression of genes encoding apolipoprotein(a) (LPA), apolipoprotein C-III (APOC3), angiopoietin-like gene 3 (ANGPTL3), and proprotein convertase subtilisin/kexin type 9 (PCSK9). RNA-based therapies, small interfering RNAs (siRNAs), and antisense oligonucleotides (ASOs) modulate these targets at the post-transcriptional level through RNA interference and RNase H-mediated degradation, respectively. This scoping review maps the molecular mechanisms, target involvement, and pharmacodynamic outcomes of RNA therapies for managing residual cardiovascular risk, with contextual comparison to traditional lipid-lowering agents. A systematic search of PubMed, Embase, Web of Science, and Scopus was performed from 2020 to February 2026. Of the 1088 records identified, 30 studies met the inclusion criteria. RNA therapies have demonstrated potential for engagement, with 80–98% reductions in Lp(a) (pelacarsen, olpasiran, zerlasiran, lepodisiran), 50–80% reductions in triglycerides (olezarsen, plozasiran, volanesorsen), and 36–44% reductions in low-density lipoprotein cholesterol (LDL-C). Mechanistically, siRNAs achieve gene silencing through RISC-mediated mRNA cleavage, with sustained pharmacodynamic effects (3–6 months) because of Argonaute-2 stability, while gapmer ASOs recruit RNase H1 for mRNA degradation. Conjugation with GalNAc allows for hepatocyte-specific delivery with a subcutaneous bioavailability of 70–85%. Safety profiles were favorable, with injection site reactions (4–12%) being the most common adverse event. This analysis maps the emerging molecular landscape of RNA therapies, highlighting their substantial precision for targeting residual cardiovascular risk pathways that cannot be addressed by traditional agents. Full article

In this paper, we review the literature regarding metformin’s action on blood lipid concentrations in metformin-treated diabetic patients. Published data indicate that metformin reduces serum total cholesterol (T-C), LDL-cholesterol (LDL-C) and triacylglycerol (TAG) concentrations and raises serum HDL-cholesterol (HDL-C) concentrations in diabetic patients. The beneficial effect of metformin on serum lipid profiles in diabetic patients can result from (a) its action on AMP-activated protein kinase, which inhibits lipogenesis and cholesterol synthesis and stimulates fatty acid oxidation; (b) decreased plasma TAG concentrations, via promoting VLDL-TAG clearance by brown adipose tissue; (c) the inhibition of nuclear factor erythroid 2-related factor 2 (Nrf2) gene expression, affecting lipid profile in diabetic patients; (d) the inhibition of the expression of genes encoding proprotein convertase subtilisin/kexin 9 (PCSK9) and lipogenic enzymes; (e) the downregulation of carbohydrate-response element-binding protein (ChREBP), which affects liver TAG and cholesterol synthesis from acetate formed by gut microbiota; (f) the inhibition of angiopoietin-like 3 protein (ANGPTL3) gene expression, and consequent effects on plasma TAG concentrations; (g) the activation of AMPK, which inhibits LXRα activity; and (h) reverse cholesterol transport. In conclusion, one can assume that beyond its primary antihyperglycemic effect, metformin exerts pleiotropic effects that modulate lipid metabolism and blood lipid profile in T2D patients. These beneficial effects of metformin on blood lipid profile may play a role in the reduction in cardiovascular risk in diabetic patients. Full article

PCSK9 is a gene associated with familial hypercholesterolemia and is involved in other biological processes such as apoptosis, autophagy, and inflammatory responses. This study aims to further validate whether PCSK9 inhibitors can improve diabetic cardiomyopathy and elucidate their mechanisms of action. This study utilized H9c2 cells and C57BL/6J mice to validate the efficacy of the PCSK9 inhibitor alirocumab through in vivo and in vitro experiments. In vitro, alirocumab was shown to enhance cell viability and reduce oxidative stress in H9c2 cells under high glucose stress. It can also decrease the expression levels of inflammatory reaction and mitochondrial apoptosis-related proteins. Through in vivo experiments, we demonstrated that alirocumab can reduce myocardial hypertrophy and improve cardiac function in diabetic cardiomyopathy mice. Meanwhile, alirocumab treatment increased mitochondrial size and quantity in the hearts of diabetic cardiomyopathy mice, promoted mitochondrial fusion, and reduced the number of damaged mitochondria. Alirocumab could also reduce the percentage of myocardial fibrosis and oxidative stress in mice. Finally, we found that alirocumab can improve cardiac function in diabetic cardiomyopathy through the ERK/p38 MAPK pathway. Our data demonstrate that the PCSK9 inhibitor alirocumab provides protective effects against diabetic cardiomyopathy, offering fundamental experimental support for its clinical application in this condition. Full article

Genetic factors are key determinants in the pathophysiology of obesity, regulating energy homeostasis. Monogenic non-syndromic obesity accounts for 2–3% of obesity in both children and adults and is most often attributable to mutations in genes encoding components of the leptin–melanocortin pathway. Genetic testing is indicated in children with severe obesity before age 5, hyperphagia, a family history of obesity, and neurodevelopmental delay or organ dysfunction. Mutations associated with monogenic obesity follow autosomal recessive (LEP, LEPR, POMC, and PCSK1) or autosomal dominant (MC4R, SH2B1, SIM1, GNAS) modes of inheritance. Other gene mutations in heterozygous states (MRAP2, MC3R, SRC1, KSR2) are associated with obesity and may exhibit autosomal dominant inheritance; however, the clinical phenotype depends on the degree of genetic penetrance and interactions with other genetic and/or environmental factors. No approved targeted pharmacotherapies are currently available for autosomal dominant monogenic obesity, and the frequent detection of variants of uncertain significance often hinders timely diagnostic confirmation. The review provides a comprehensive appraisal of autosomal dominant forms of monogenic non-syndromic obesity, analyzing genetic and molecular features, clinical presentations, and therapeutic strategies. Full article

The development and application of therapeutic oligonucleotides, such as siRNA, miRNA, ASOs and aptamers, is a rapidly growing field in biomedicine. These molecules are undergoing extensive preclinical and clinical testing, and the market for synthetic RNA drugs is expanding. However, several challenges remain, including targeted delivery and high costs associated with development, screening and production. One significant advance has been the creation of GalNAc-conjugates, which selectively target ASGPR and deliver oligonucleotides to hepatocytes. Although these conjugates have shown promising results, their widespread use is limited by the lack of effective synthesis methods. Thus, the development of new methods for the synthesis of ligand-oligonucleotide conjugates is an important task to which this study is devoted. In this study, we created a library of siRNA conjugates with the GalNAc L-96 ligand to suppress the expression of the PCSK9 gene associated with elevated LDL and an increased risk of developing cardiovascular diseases. The selection of the most effective siRNA molecules was carried out using an algorithm previously developed by our research group, which considers thermodynamic stability, predicted specificity and effectiveness. To experimentally confirm the effectiveness of conjugates, an in vitro model based on the cultivation of hepatocyte cells was developed. Optimization of the conjugate synthesis process has significantly reduced the cost of manufacturing technology, which creates the potential for efficient scaling of synthesis for transfer and application in the pharmaceutical industry. The results of the study showed that the development of the siRNA sequence optimized in silico resulted in a significant increase in the inhibitory effect of the GalNAc-siRNA conjugate compared to a compound similar to a commercial drug. Full article

Background/Objectives: Type 2 diabetes mellitus (T2DM) significantly elevates the risk of coronary artery disease (CAD), particularly in Asian populations where both conditions are epidemic. While shared genetic factors contribute to this comorbidity, evidence from Asian cohorts remains fragmented, with limited focus on population-specific variants. This meta-analysis synthesizes evidence on genetic variants associated with CAD risk in Asian patients with T2DM. Methods: We systematically searched several databases according to the PRISMA statement and checklist. Pooled odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were calculated using random-effects models, with heterogeneity assessed via I² and Cochran’s Q, and publication bias via funnel plots and Egger’s test. Results: In total, data on 11,268 subjects were reviewed, including 4668 cases and 6600 controls. Among 950 identified studies, 18 met eligibility criteria, and 14 studies provided sufficient data for the meta-analysis. The random-effects pooled estimate across all studied variants was not statistically significant (OR = 1.16 [95% CI: 0.68–2.00]; z = 0.56, p = 0.58). However, analysis of individual loci revealed gene-specific associations with CAD among this population: PCSK1 gene (OR = 2.12 [95% CI: 1.26–3.52]; p < 0.05; weight = 8.77%), GLP1R gene (OR = 2.25 [95% CI: 1.27–3.97]; p < 0.01; weight = 8.62%). ADIPOQ gene (OR = 8.00 [95% CI: 2.34–27.14]; p < 0.01; weight = 6.35%). Several genes were associated with an elevated risk of CAD: PCSK1 gene (OR = 2.12 [95% CI: 1.26–3.52]; p < 0.05; weight = 8.77%), GLP1R gene (OR = 2.25 [95% CI: 1.27–3.97]; p < 0.01; weight = 8.62%) and ADIPOQ gene (OR = 8.00 [95% CI: 2.34–27.14]; p < 0.01; weight = 6.35%). Several genes were associated with possible protective effects: ACE gene (OR = 0.41 [95% CI: 0.23–0.73]; p < 0.01; weight = 8.57%), Q192R gene (OR = 0.20 [95% CI: 0.08–0.52]; p < 0.001; weight = 7.41%). Heterogeneity was substantial (τ² = 0.78; I² = 81.95%; Q (13) = 64.67, p < 0.001). Conclusions: This first meta-analysis of genetic variants associated with CAD in Asian populations with T2DM identified specific locus-level associations implicating lipid metabolism, incretin signaling, and oxidative stress pathways. The lack of a significant pooled effect, alongside high heterogeneity, underscores the complexity and population-specific nature of this genetic architecture. These findings suggest that effective precision risk stratification may depend more on specific variants than on a broad polygenic signal, highlighting the need for further research in a larger, distinct sample size. Full article

Obesity is closely linked to dyslipidemia, hepatic injury, and chronic inflammation through disturbances in the gut–liver axis. Here, we evaluated the anti-obesity effects of L. rhamnosus (Lacticaseibacillus rhamnosus) CU262 in a high-fat diet (HFD) mouse model and elucidated mechanisms using an integrated multi-omics strategy. Male C57BL/6 mice received CU262 during 12 weeks of HFD feeding. Phenotypes, serum/liver biochemistry, gut microbiota (16S rRNA sequencing), fecal short-chain fatty acids (SCFAs), and hepatic transcriptomes (RNA-seq) were assessed. CU262 significantly attenuated weight gain and adiposity; improved serum TC, TG, LDL-C and HDL-C; lowered ALT/AST and FFA; and mitigated oxidative stress and inflammatory imbalance (↓ IL-6/TNF-α, ↑ IL-10). CU262 restored alpha diversity, reduced the Firmicutes/Bacteroidetes ratio, enriched beneficial taxa (e.g., Akkermansia), and increased acetate and butyrate. Liver transcriptomics showed CU262 reversed HFD-induced activation of cholesterol/steroid biosynthesis and endoplasmic reticulum stress, with downregulation of key genes (Mvk, Mvd, Fdps, Nsdhl, and Dhcr7) and Pcsk9, yielding negative enrichment of steroid and terpenoid backbone pathways and enhancement of oxidative phosphorylation and glutathione metabolism. Correlation analyses linked Akkermansia and SCFAs with improved lipid/inflammatory indices and repression of cholesterol-synthetic and stress-response genes. These findings demonstrate that CU262 alleviates HFD-induced metabolic derangements via microbiota-SCFA-hepatic gene network reprogramming along the gut–liver axis, supporting its potential as a functional probiotic for obesity management. Full article

Gene editing technologies have revolutionized therapeutic development, offering potentially curative and preventative strategies for cardiovascular disease (CVD), which remains a leading global cause of morbidity and mortality. This review provides an introduction to the state-of-the-art gene editing tools—including ZFNs, TALENs, CRISPR/Cas9 systems, base editors, and prime editors—and evaluates their application in lipid metabolic pathways central to CVD pathogenesis. Emphasis is placed on targets such as PCSK9, ANGPTL3, CETP, APOC3, ASGR1, LPA, and IDOL, supported by findings from human genetics, preclinical models, and recent first-in-human trials. Emerging delivery vehicles (AAVs, LNPs, lentivirus, virus-like particles) and their translational implications are discussed. The review highlights ongoing clinical trials employing liver-targeted in vivo editing modalities (LivGETx-CVD) and provides insights into challenges in delivery, off-target effects, genotoxicity, and immunogenicity. Collectively, this review captures the rapid progress of LivGETx-CVD from conceptual innovation to clinical application, and positions gene editing as a transformative, single-dose strategy with the potential to redefine prevention and long-term management of dyslipidemia and atherosclerotic cardiovascular disease. Full article

Atherosclerosis is a chronic, multifactorial vascular disease and the leading global cause of cardiovascular morbidity. Its development reflects interconnected disturbances in lipid metabolism, endothelial function, inflammation, smooth muscle cell (SMC) phenotypic switching, and extracellular matrix remodeling. Genetic predisposition, including monogenic disorders such as familial hypercholesterolemia and polygenic risk variants, modulates disease susceptibility by altering lipid homeostasis as well as inflammatory and thrombotic pathways. Epigenetic regulators and noncoding RNAs, such as histone modifications, microRNAs, and long noncoding RNAs, further shape gene expression and link environmental cues to vascular pathology. Endothelial injury promotes lipoprotein retention and oxidation, triggering monocyte recruitment and macrophage-driven foam cell formation, cytokine secretion, and necrotic core development. Persistent inflammation, macrophage heterogeneity, and SMC plasticity collectively drive plaque growth and destabilization. Emerging insights into immune cell metabolism, intracellular signaling networks, and novel regulatory RNAs are expanding therapeutic possibilities beyond lipid-lowering. Current and evolving treatments include statins, proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, anti-inflammatory agents targeting interleukin-1 beta (IL-1β) or NOD-, LRR-, and pyrin domain-containing protein 3 (NLRP3), and advanced approaches such as gene editing, siRNA, and nanoparticle-based delivery. Integrating multi-omics, biomarker-guided therapy, and precision medicine promises improved risk stratification and next-generation targeted interventions. This review summarizes recent molecular advances and highlights translational opportunities for enhancing atherosclerosis prevention and treatment. Full article

Therapeutic innovation in cardiovascular medicine is rapidly overcoming the limitations of conventional strategies, providing more targeted, durable, and multidimensional solutions. Key advances include next-generation lipid-lowering agents such as PCSK9 inhibitors, inclisiran, and bempedoic acid, as well as metabolic drugs like SGLT2 inhibitors, GLP-1 receptor agonists, and dual GIP/GLP-1 agonists, which offer cardiovascular and renal benefits beyond glucose control. At the same time, gene therapies, RNA-based interventions, genome editing tools, and nanocarriers are paving the way for precision medicine tailored to individual patient profiles. In parallel, digital innovations, including artificial intelligence, remote monitoring, and telehealth platforms, are transforming care delivery by enhancing adherence, enabling earlier intervention, and refining risk stratification. Collectively, these developments signify a paradigm shift toward a more personalized, proactive, and systems-based model of cardiovascular care. Full article

The dedifferentiation of smooth muscle cells (SMCs) is the main cause of atherosclerosis and vascular calcification. This study integrated the gene expression data of multiple microarrays to identify relevant marker molecules. A total of 72 Gene Expression Omnibus (GEO) samples (GSM) were collected from 10 gene expression data series (GSE) and divided into five groups: non-SMC, SMC, atherosclerotic SMC (SMC-ath), calcified SMC (SMC-calc), and treated SMC (SMC-t). The SMC-t group included synthetic SMCs that had undergone treatment to inhibit proliferation, migration, or inflammation. The gene expression data were merged, normalized, and batch effects were removed before differential gene expression (DGE) analysis was performed via linear models for microarray data (limma) and statistical analysis of metagenomic profiles (STAMPs). The genes with expressions that significantly differed were subsequently subjected to protein-protein interaction (PPI) and functional prediction analyses. In addition, the random forest method was used for classification. Twelve proteins that may be marker molecules for SMC differentiation and dedifferentiation were identified, namely, Proprotein convertase subtilisin/kexin type 1 (PCSK1), Transforming growth factor beta-induced (TGFBI), Complement C1s (C1S), Phosphomannomutase 1 (PMM1), Claudin 7 (CLDN7), Calcium binding and coiled-coil domain 2 (CALCOCO2), SAC3 domain-containing protein 1 (SAC3D1), Natriuretic peptide B (NPPB), Monoamine oxidase A (MAOA), Regulator of the Cell Cycle (RGCC), Alpha-crystallin B Chain (CRYAB), and Alcohol dehydrogenase 1B (ADH1B). Finally, their possible roles in SMCs are discussed. This study highlights the feasibility of bioinformatics analysis for studying SMC dedifferentiation. Full article

Familial Hypercholesterolemia (FH) is a common genetic disorder characterized by elevated LDL-cholesterol levels and an increased risk of premature cardiovascular disease. While pathogenic variants in LDLR, APOB, and PCSK9 are well-established causes, a substantial proportion of clinically suspected FH cases do not carry either pathogenic variants or rare variants of uncertain significance in these genes (FH/V−/USV−). This study aimed to characterize the metabolome/lipidome of genetically confirmed heterozygous FH (HeFH) patients compared to FH/V−/USV−, seeking to identify specific alterations associated with genetic status and phenotypic variability. Untargeted high-resolution mass spectrometry (UHPLC-Q-Exactive-MS)-based lipidomics and nuclear magnetic resonance-based metabolomics were performed on plasma samples of FH patients (n = 20 HeFH and n = 19 FH/V−/USV−) towards healthy controls (n = 22). PLS-DA analysis revealed group-level separation, suggesting differences in the circulating metabolome/lipidome. As expected, most of identified lipid classes were higher in both FH groups compared to normolipidemic controls. Notably, significant lipids (VIP > 1, p < 0.05) showed potential in distinguishing HeFH and FH/V−/USV− patients, particularly sphingomyelins. These data were confirmed by multivariable regression analysis controlling for age, sex, and lipid-lowering therapy as well as by ROC analysis. The evidence of a distinct lipidome signature in the HeFH subgroup may relate to the increased cardiovascular risk of HeFH patients compared to patients without pathogenic variants. Full article

Obesity is a highly complex, multifactorial disease influenced by dynamic interactions among genetic, epigenetic, environmental, and behavioral determinants that explicitly position genetics as the core. While advances in multi-omic integration have revolutionized our understanding of adiposity pathways, translation into personalized clinical nutrition remains a critical challenge. This review systematically consolidates emerging insights into the molecular and nutrigenomic architecture of obesity by integrating data from large-scale GWAS, functional epigenomics, nutrigenetic interactions, and microbiome-mediated metabolic programming. The primary aim is to systematically organize and synthesize recent genetic and genomic findings in obesity, while also highlighting how these discoveries can be contextualized within precision nutrition frameworks. A comprehensive literature search was conducted across PubMed, Scopus, and Web of Science up to July 2024 using MeSH terms, nutrigenomic-specific queries, and multi-omics filters. Eligible studies were classified into five domains: monogenic obesity, polygenic GWAS findings, epigenomic regulation, nutrigenomic signatures, and gut microbiome contributions. Over 127 candidate genes and 253 QTLs have been implicated in obesity susceptibility. Monogenic variants (e.g., LEP, LEPR, MC4R, POMC, PCSK1) explain rare, early-onset phenotypes, while FTO (polygenic) and MC4R (monogenic mutations as well as common polygenic variants) represent major loci across populations. Epigenetic mechanisms, dietary composition, physical activity, and microbial diversity significantly recalibrate obesity trajectories. Integration of genomics, functional epigenomics, precision nutrigenomics, and microbiome science presents transformative opportunities for personalized obesity interventions. However, translation into evidence-based clinical nutrition remains limited, emphasizing the need for functional validation, cross-ancestry mapping, and AI-driven precision frameworks. Specifically, this review systematically identifies and integrates evidence from genomics, epigenomics, nutrigenomics, and microbiome studies published between 2000 and 2024, applying structured inclusion/exclusion criteria and narrative synthesis to highlight translational pathways for precision nutrition. Full article