PSRC1 May Affect Coronary Artery Disease Risk by Altering CELSR2, PSRC1, and SORT1 Gene Expression and Circulating Granulin and Apolipoprotein B Protein Levels

Genetic Variants, Bioactive Compounds, and PCSK9 Inhibitors in Hyper-LDL-Cholesterolemia: A GWAS and In Silico Study on Cardiovascular Disease Risk

Background: Hyper-LDL-cholesterolemia is a key contributor to cardiovascular diseases (CVDs), and both genetic predisposition and lifestyle influence it. This study aimed to develop personalized strategies for managing hyper-LDL-cholesterolemia by integrating polygenic risk scores (PRSs), genetic variants, and bioactive compound interactions, leveraging a precision medicine approach. Methods: A cohort of 58,701 Korean adults, including 8966 individuals with hyper-LDL-cholesterolemia (LDL ≥ 160 mg/dL) or undergoing treatment with hypocholesterolemic agents, was analyzed to investigate the interplay between genetic risk and lifestyle factors. The PRS was constructed using three key variants: PCSK9 (rs151193009), CELSR2 (rs11102967), and APOE (rs7412). Gene-lifestyle interactions were assessed, focusing on energy intake and physical activity. Computational molecular docking was utilized to investigate how bioactive compounds differentially interact with the wild-type and mutant forms of PCSK9 (Arg93Cys) and APOE (Arg176Cys), focusing on variations in binding affinity. Results: Hyper-LDL-cholesterolemia was associated with a 1.3-fold increased risk of CVD. The PRS showed a significant association with a 3.45-fold higher likelihood of developing both elevated LDL cholesterol and reduced HDL cholesterol levels. Lifestyle interactions revealed that high energy intake and physical inactivity significantly amplified the genetic risk (p < 0.05). In silico analysis demonstrated that bioactive compounds, notably prodelphinidin trimer, exhibited enhanced binding affinity with wild-type PCSK9 (Arg93Cys), while several compounds preferentially targeted the mutated PCSK9, suggesting potential avenues for genotype-specific therapies. Conclusions: This study emphasizes the combined influence of genetic predispositions and lifestyle behaviors on developing hyper-LDL-cholesterolemia, and highlights potential bioactive compounds as personalized therapeutic targets. By integrating genomic data, lifestyle analysis, and molecular docking, this research provides a foundation for precision interventions tailored to an individual's genetic and metabolic profile, paving the way for more effective and personalized management of dyslipidemia and associated CVD risk.

Genetic Overlap Between Obstructive Sleep Apnea and Ischemic Stroke: A Large-Scale Genome-Wide Cross-Trait Analysis

Background

To further understand the complex relationship between Obstructive Sleep Apnea (OSA) and ischemic stroke, this study explores the role of genetic factors in the comorbidity of these two conditions.

Methods

Based on large-scale available Genome-Wide Association Studies (GWAS) for OSA and ischemic stroke, we conducted a multi-level cross-trait analysis. First, we utilized Linkage Disequilibrium Score Regression (LDSC) to analyze the genetic correlation between the two diseases. Subsequently, we performed cross-trait analysis to identify pleiotropic Single Nucleotide Polymorphisms (SNPs) associated with both OSA and ischemic stroke. On this basis, we applied annotation and Multi-marker Analysis of GenoMic Annotation (MAGMA) analysis to examine results at the gene level. Finally, we conducted Transcriptome-Wide Association Studies (TWAS) to analyze gene expressions significantly related to both traits.

Results

The LDSC analysis revealed a significant positive genetic correlation between OSA and ischemic stroke. Cross-trait analysis identified a total of 90 pleiotropic SNPs, with rs78581380 being the most significant. Combining Functional Mapping and Annotation (FUMA) annotation and MAGMA analysis, we identified 83 genes in total. TWAS analysis discovered 23 gene expressions that were significantly associated with both OSA and ischemic stroke traits.

Conclusion

This study elucidates the shared genetic architecture between OSA and ischemic stroke, emphasizing the crucial role of genetic factors in the comorbidity of these two conditions.

SPTLC3 regulates plasma membrane sphingolipid composition to facilitate hepatic gluconeogenesis

SPTLC3, an inducible subunit of the serine palmitoyltransferase (SPT) complex, causes production of alternative sphingoid bases, including a 16-carbon dihydrosphingosine, whose biological function is only beginning to emerge. High-fat feeding induced SPTLC3 in the liver, prompting us to produce a liver-specific knockout mouse line. Following high-fat feeding, knockout mice showed decreased fasting blood glucose, and knockout primary hepatocytes showed suppressed glucose production, a core function of hepatocytes. Stable isotope tracing revealed suppression of the gluconeogenic pathway, finding that SPTLC3 was required to maintain expression of key gluconeogenic genes via adenylate cyclase/cyclic AMP (cAMP)/cAMP response element binding protein (CREB) signaling. Additionally, by employing a combination of a recently developed lipidomics methodology, exogenous C14/C16 fatty acid treatment, and in situ adenylate cyclase activity, we implicated a functional interaction between sphingomyelin with a d16 backbone and adenylate cyclase at the plasma membrane. This work pinpoints a specific sphingolipid-protein functional interaction with broad implications for understanding sphingolipid signaling and metabolic disease.

Multiomic integration analysis identifies atherogenic metabolites mediating between novel immune genes and cardiovascular risk

BACKGROUND

Understanding genetic-metabolite associations has translational implications for informing cardiovascular risk assessment. Interrogating functional genetic variants enhances our understanding of disease pathogenesis and the development and optimization of targeted interventions.

METHODS

In this study, a total of 187 plasma metabolite levels were profiled in 4974 individuals of European ancestry of the GCAT| Genomes for Life cohort. Results of genetic analyses were meta-analysed with additional datasets, resulting in up to approximately 40,000 European individuals. Results of meta-analyses were integrated with reference gene expression panels from 58 tissues and cell types to identify predicted gene expression associated with metabolite levels. This approach was also performed for cardiovascular outcomes in three independent large European studies (N = 700,000) to identify predicted gene expression additionally associated with cardiovascular risk. Finally, genetically informed mediation analysis was performed to infer causal mediation in the relationship between gene expression, metabolite levels and cardiovascular risk.

RESULTS

A total of 44 genetic loci were associated with 124 metabolites. Lead genetic variants included 11 non-synonymous variants. Predicted expression of 53 fine-mapped genes was associated with 108 metabolite levels; while predicted expression of 6 of these genes was also associated with cardiovascular outcomes, highlighting a new role for regulatory gene HCG27. Additionally, we found that atherogenic metabolite levels mediate the associations between gene expression and cardiovascular risk. Some of these genes showed stronger associations in immune tissues, providing further evidence of the role of immune cells in increasing cardiovascular risk.

CONCLUSIONS

These findings propose new gene targets that could be potential candidates for drug development aimed at lowering the risk of cardiovascular events through the modulation of blood atherogenic metabolite levels.

Sex differences in the genetic and molecular mechanisms of coronary artery disease

Sex differences in coronary artery disease (CAD) presentation, risk factors and prognosis have been widely studied. Similarly, studies on atherosclerosis have shown prominent sex differences in plaque biology. Our understanding of the underlying genetic and molecular mechanisms that drive these differences remains fragmented and largely understudied. Through reviewing genetic and epigenetic studies, we identified more than 40 sex-differential candidate genes (13 within known CAD loci) that may explain, at least in part, sex differences in vascular remodeling, lipid metabolism and endothelial dysfunction. Studies with transcriptomic and single-cell RNA sequencing data from atherosclerotic plaques highlight potential sex differences in smooth muscle cell and endothelial cell biology. Especially, phenotypic switching of smooth muscle cells seems to play a crucial role in female atherosclerosis. This matches the known sex differences in atherosclerotic phenotypes, with men being more prone to lipid-rich plaques, while women are more likely to develop fibrous plaques with endothelial dysfunction. To unravel the complex mechanisms that drive sex differences in CAD, increased statistical power and adjustments to study designs and analysis strategies are required. This entails increasing inclusion rates of women, performing well-defined sex-stratified analyses and the integration of multi-omics data.

Exploring the genetic basis of coronary artery disease using functional genomics

Genome-wide Association Studies (GWAS) have identified more than 300 loci associated with coronary artery disease (CAD), defining the genetic risk map of the disease. However, the translation of the association signals into biological-pathophysiological mechanisms constitute a major challenge. Through a group of examples of studies focused on CAD, we discuss the rationale, basic principles and outcomes of the main methodologies implemented to prioritize and characterize causal variants and their target genes. Additionally, we highlight the strategies as well as the current methods that integrate association and functional genomics data to dissect the cellular specificity underlying the complexity of disease mechanisms. Despite the limitations of existing approaches, the increasing knowledge generated through functional studies helps interpret GWAS maps and opens novel avenues for the clinical usability of association data.

Sorting through the extensive and confusing roles of sortilin in metabolic disease

Sortilin is a post-Golgi trafficking receptor homologous to the yeast vacuolar protein sorting receptor 10 (VPS10). The VPS10 motif on sortilin is a 10-bladed β-propeller structure capable of binding more than 50 proteins, covering a wide range of biological functions including lipid and lipoprotein metabolism, neuronal growth and death, inflammation, and lysosomal degradation. Sortilin has a complex cellular trafficking itinerary, where it functions as a receptor in the trans-Golgi network, endosomes, secretory vesicles, multivesicular bodies, and at the cell surface. In addition, sortilin is associated with hypercholesterolemia, Alzheimer's disease, prion diseases, Parkinson's disease, and inflammation syndromes. The 1p13.3 locus containing SORT1, the gene encoding sortilin, carries the strongest association with LDL-C of all loci in human genome-wide association studies. However, the mechanism by which sortilin influences LDL-C is unclear. Here, we review the role sortilin plays in cardiovascular and metabolic diseases and describe in detail the large and often contradictory literature on the role of sortilin in the regulation of LDL-C levels.