OptiMo-LDLr: An Integrated In Silico Model with Enhanced Predictive Power for LDL Receptor Variants, Unraveling Hot Spot Pathogenic Residues.

Familial hypercholesterolemia (FH) is an inherited metabolic disease affecting cholesterol metabolism, with 90% of cases caused by mutations in the LDL receptor gene (LDLR), primarily missense mutations. This study aims to integrate six commonly used predictive software to create a new model for predicting LDLR mutation pathogenicity and mapping hot spot residues. Six predictive-software are selected: Polyphen-2, SIFT, MutationTaster, REVEL, VARITY, and MLb-LDLr. Software accuracy is tested with the characterized variants annotated in ClinVar and, by bioinformatic and machine learning techniques all models are integrated into a more accurate one. The resulting optimized model presents a specificity of 96.71% and a sensitivity of 98.36%. Hot spot residues with high potential of pathogenicity appear across all domains except for the signal peptide and the O-linked domain. In addition, translating this information into 3D structure of the LDLr highlights potentially pathogenic clusters within the different domains, which may be related to specific biological function. The results of this work provide a powerful tool to classify LDLR pathogenic variants. Moreover, an open-access guide user interface (OptiMo-LDLr) is provided to the scientific community. This study shows that combination of several predictive software results in a more accurate prediction to help clinicians in FH diagnosis.

Predictive Modeling and Structure Analysis of Genetic Variants in Familial Hypercholesterolemia: Implications for Diagnosis and Protein Interaction Studies.

PURPOSE OF REVIEW: Familial hypercholesterolemia (FH) is a hereditary condition characterized by elevated levels of low-density lipoprotein cholesterol (LDL-C), which increases the risk of cardiovascular disease if left untreated. This review aims to discuss the role of bioinformatics tools in evaluating the pathogenicity of missense variants associated with FH. Specifically, it highlights the use of predictive models based on protein sequence, structure, evolutionary conservation, and other relevant features in identifying genetic variants within LDLR, APOB, and PCSK9 genes that contribute to FH. RECENT FINDINGS: In recent years, various bioinformatics tools have emerged as valuable resources for analyzing missense variants in FH-related genes. Tools such as REVEL, Varity, and CADD use diverse computational approaches to predict the impact of genetic variants on protein function. These tools consider factors such as sequence conservation, structural alterations, and receptor binding to aid in interpreting the pathogenicity of identified missense variants. While these predictive models offer valuable insights, the accuracy of predictions can vary, especially for proteins with unique characteristics that might not be well represented in the databases used for training. This review emphasizes the significance of utilizing bioinformatics tools for assessing the pathogenicity of FH-associated missense variants. Despite their contributions, a definitive diagnosis of a genetic variant necessitates functional validation through in vitro characterization or cascade screening. This step ensures the precise identification of FH-related variants, leading to more accurate diagnoses. Integrating genetic data with reliable bioinformatics predictions and functional validation can enhance our understanding of the genetic basis of FH, enabling improved diagnosis, risk stratification, and personalized treatment for affected individuals. The comprehensive approach outlined in this review promises to advance the management of this inherited disorder, potentially leading to better health outcomes for those affected by FH.

Age, Origin and Functional Study of the Prevalent LDLR Mutation Causing Familial Hypercholesterolaemia in Gran Canaria.

The p.(Tyr400_Phe402del) mutation in the LDL receptor (LDLR) gene is the most frequent cause of familial hypercholesterolaemia (FH) in Gran Canaria. The aim of this study was to determine the age and origin of this prevalent founder mutation and to explore its functional consequences. For this purpose, we obtained the haplotypic information of 14 microsatellite loci surrounding the mutation in one homozygous individual and 11 unrelated heterozygous family trios. Eight different mutation carrier haplotypes were identified, which were estimated to originate from a common ancestral haplotype 387 (110-1572) years ago. This estimation suggests that this mutation happened after the Spanish colonisation of the Canary Islands, which took place during the fifteenth century. Comprehensive functional studies of this mutation showed that the expressed LDL receptor was retained in the endoplasmic reticulum, preventing its migration to the cell surface, thus allowing us to classify this LDLR mutation as a class 2a, defective, pathogenic variant.

Cardiovascular Disease, Atherosclerosis and Familial Hypercholesterolemia: From Molecular Mechanisms Causing Pathogenicity to New Therapeutic Approaches.

This Special Issue, "Cardiovascular Disease, Atherosclerosis and Familial Hypercholesterolemia: From Molecular Mechanisms Causing Pathogenicity to New Therapeutic Approaches", contributes to advancing our knowledge of the molecular mechanisms that drive cardiovascular disease, atherosclerosis and familial hypercholesterolemia and the development of state-of-the-art research in the field [...].

Functional Characterization of p.(Arg160Gln) PCSK9 Variant Accidentally Found in a Hypercholesterolemic Subject.

Familial hypercholesterolaemia (FH) is an autosomal dominant dyslipidaemia, characterised by elevated LDL cholesterol (LDL-C) levels in the blood. Three main genes are involved in FH diagnosis: LDL receptor (LDLr), Apolipoprotein B (APOB) and Protein convertase subtilisin/kexin type 9 (PCSK9) with genetic mutations that led to reduced plasma LDL-C clearance. To date, several PCSK9 gain-of-function (GOF) variants causing FH have been described based on their increased ability to degrade LDLr. On the other hand, mutations that reduce the activity of PCSK9 on LDLr degradation have been described as loss-of-function (LOF) variants. It is therefore important to functionally characterise PCSK9 variants in order to support the genetic diagnosis of FH. The aim of this work is to functionally characterise the p.(Arg160Gln) PCSK9 variant found in a subject suspected to have FH. Different techniques have been combined to determine efficiency of the autocatalytic cleavage, protein expression, effect of the variant on LDLr activity and affinity of the PCSK9 variant for the LDLr. Expression and processing of the p.(Arg160Gln) variant had a result similar to that of WT PCSK9. The effect of p.(Arg160Gln) PCSK9 on LDLr activity is lower than WT PCSK9, with higher values of LDL internalisation (13%) and p.(Arg160Gln) PCSK9 affinity for the LDLr is lower than WT, EC50 8.6 ± 0.8 and 25.9 ± 0.7, respectively. The p.(Arg160Gln) PCSK9 variant is a LOF PCSK9 whose loss of activity is caused by a displacement of the PCSK9 P' helix, which reduces the stability of the LDLr-PCSK9 complex.

Leu22_Leu23 Duplication at the Signal Peptide of PCSK9 Promotes Intracellular Degradation of LDLr and Autosomal Dominant Hypercholesterolemia.

BACKGROUND: PCSK9 (Proprotein convertase subtilisin/kexin type 9) regulates LDL-C (low-density lipoprotein cholesterol) metabolism by targeting LDLr (LDL receptor) for lysosomal degradation. PCSK9 gain-of-function variants cause autosomal dominant hypercholesterolemia by reducing LDLr levels, the D374Y variant being the most severe, while loss-of-function variants are associated with low LDL-C levels. Gain-of-function and loss-of-function activities have also been attributed to variants occurring in the PCSK9 signal peptide. Among them, L11 is a very rare PCSK9 variant that seems to increase LDL-C values in a moderate way causing mild hypercholesterolemia. METHODS: Using molecular biology and biophysics methodologies, activities of L8 and L11 variants, both located in the leucine repetition stretch of the signal peptide, have been extensively characterized in vitro. RESULTS: L8 variant is not associated with increased LDLr activity, whereas L11 activity is increased by ≈20% compared with wt PCSK9. The results suggest that the L11 variant reduces LDLr levels intracellularly by a process resulting from impaired cleavage of the signal peptide. This would lead to less efficient LDLr transport to the cell membrane and promote LDLr intracellular degradation. CONCLUSIONS: Deletion of a leucine in the signal peptide in L8 variant does not affect PCSK9 activity, whereas the leucine duplication in the L11 variant enhances LDLr intracellular degradation. These findings highlight the importance of deep in vitro characterization of PCSK9 genetic variants to determine pathogenicity and improve clinical diagnosis and therapy of inherited familial hypercholesterolemia disease.

Pathophysiology of Atherosclerosis.

Atherosclerosis is the main risk factor for cardiovascular disease (CVD), which is the leading cause of mortality worldwide. Atherosclerosis is initiated by endothelium activation and, followed by a cascade of events (accumulation of lipids, fibrous elements, and calcification), triggers the vessel narrowing and activation of inflammatory pathways. The resultant atheroma plaque, along with these processes, results in cardiovascular complications. This review focuses on the different stages of atherosclerosis development, ranging from endothelial dysfunction to plaque rupture. In addition, the post-transcriptional regulation and modulation of atheroma plaque by microRNAs and lncRNAs, the role of microbiota, and the importance of sex as a crucial risk factor in atherosclerosis are covered here in order to provide a global view of the disease.

Boosting Cholesterol Efflux from Foam Cells by Sequential Administration of rHDL to Deliver MicroRNA and to Remove Cholesterol in a Triple-Cell 2D Atherosclerosis Model.

Cardiovascular disease, the leading cause of mortality worldwide, is primarily caused by atherosclerosis, which is characterized by lipid and inflammatory cell accumulation in blood vessels and carotid intima thickening. Although disease management has improved significantly, new therapeutic strategies focused on accelerating atherosclerosis regression must be developed. Atherosclerosis models mimicking in vivo-like conditions provide essential information for research and new advances toward clinical application. New nanotechnology-based therapeutic opportunities have emerged with apoA-I nanoparticles (recombinant/reconstituted high-density lipoproteins, rHDL) as ideal carriers to deliver molecules and the discovery that microRNAs participate in atherosclerosis establishment and progression. Here, a therapeutic strategy to improve cholesterol efflux is developed based on a two-step administration of rHDL consisting of a first dose of antagomiR-33a-loaded rHDLs to induce adenosine triphosphate-binding cassette transporters A1 overexpression, followed by a second dose of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine rHDLs, which efficiently remove cholesterol from foam cells. A triple-cell 2D-atheroma plaque model reflecting the cellular complexity of atherosclerosis is used to improve efficiency of the nanoparticles in promoting cholesterol efflux. The results show that sequential administration of rHDL potentiates cholesterol efflux indicating that this approach may be used in vivo to more efficiently target atherosclerotic lesions and improve prognosis of the disease.

MLb-LDLr: A Machine Learning Model for Predicting the Pathogenicity of LDLr Missense Variants.

Untreated familial hypercholesterolemia (FH) leads to atherosclerosis and early cardiovascular disease. Mutations in the low-density lipoprotein receptor (LDLr) gene constitute the major cause of FH, and the high number of mutations already described in the LDLr makes necessary cascade screening or in vitro functional characterization to provide a definitive diagnosis. Implementation of high-predicting capacity software constitutes a valuable approach for assessing pathogenicity of LDLr variants to help in the early diagnosis and management of FH disease. This work provides a reliable machine learning model to accurately predict the pathogenicity of LDLr missense variants with specificity of 92.5% and sensitivity of 91.6%.

Design and Validation of a Process Based on Cationic Niosomes for Gene Delivery into Novel Urine-Derived Mesenchymal Stem Cells.

BACKGROUND: Mesenchymal stem cells (MSCs) are stem cells present in adult tissues. They can be cultured, have great growth capacity, and can differentiate into several cell types. The isolation of urine-derived mesenchymal stem cells (hUSCs) was recently described. hUSCs present additional benefits in the fact that they can be easily obtained noninvasively. Regarding gene delivery, nonviral vectors based on cationic niosomes have been used and are more stable and have lower immunogenicity than viral vectors. However, their transfection efficiency is low and in need of improvement. METHODS: We isolated hUSCs from urine, and the cell culture was tested and characterized. Different cationic niosomes were elaborated using reverse-phase evaporation, and they were physicochemically characterized. Then, they were screened into hUSCs for transfection efficiency, and their internalization was evaluated. RESULTS: GPxT-CQ at a lipid/DNA ratio of 5:1 (w/w) had the best transfection efficiency. Intracellular localization studies confirmed that nioplexes entered mainly via caveolae-mediated endocytosis. CONCLUSIONS: In conclusion, we established a protocol for hUSC isolation and their transfection with cationic niosomes, which could have relevant clinical applications such as in gene therapy. This methodology could also be used for creating cellular models for studying and validating pathogenic genetic variants, and even for performing functional studies. Our study increases knowledge about the internalization of tested cationic niosomes in these previously unexplored cells.

Molecular mechanisms of lipotoxicity-induced pancreatic ß-cell dysfunction.

Type 2 diabetes (T2D), a heterogeneous disorder derived from metabolic dysfunctions, leads to a glucose overflow in the circulation due to both defective insulin secretion and peripheral insulin resistance. One of the critical risk factor for T2D is obesity, which represents a global epidemic that has nearly tripled since 1975. Obesity is characterized by chronically elevated free fatty acid (FFA) levels, which cause deleterious effects on glucose homeostasis referred to as lipotoxicity. Here, we review the physiological FFA roles onto glucose-stimulated insulin secretion (GSIS) and the pathological ones affecting many steps of the mechanisms and modulation of GSIS. We also describe in vitro and in vivo experimental evidences addressing lipotoxicity in ß-cells and the role of saturation and chain length of FFA on the potency of GSIS stimulation. The molecular mechanisms underpinning lipotoxic-ß-cell dysfunction are also reviewed. Among them, endoplasmic reticulum stress, oxidative stress and mitochondrial dysfunction, inflammation, impaired autophagy and ß-cell dedifferentiation. Finally therapeutic strategies for the ß-cells dysfunctions such as the use of metformin, glucagon-like peptide 1, thiazolidinediones, anti-inflammatory drugs, chemical chaperones and weight are discussed.

miR-27b Modulates Insulin Signaling in Hepatocytes by Regulating Insulin Receptor Expression.

Insulin resistance (IR) is one of the key contributing factors in the development of type 2 diabetes mellitus (T2DM). However, the molecular mechanisms leading to IR are still unclear. The implication of microRNAs (miRNAs) in the pathophysiology of multiple cardiometabolic pathologies, including obesity, atherosclerotic heart failure and IR, has emerged as a major focus of interest in recent years. Indeed, upregulation of several miRNAs has been associated with obesity and IR. Among them, miR-27b is overexpressed in the liver in patients with obesity, but its role in IR has not yet been thoroughly explored. In this study, we investigated the role of miR-27b in regulating insulin signaling in hepatocytes, both in vitro and in vivo. Therefore, assessment of the impact of miR-27b on insulin resistance through the hepatic tissue is of special importance due to the high expression of miR-27b in the liver together with its known role in regulating lipid metabolism. Notably, we found that miR-27b controls post-transcriptional expression of numerous components of the insulin signaling pathway including the insulin receptor (INSR) and insulin receptor substrate 1 (IRS1) in human hepatoma cells. These results were further confirmed in vivo showing that overexpression and inhibition of hepatic miR-27 enhances and suppresses hepatic INSR expression and insulin sensitivity, respectively. This study identified a novel role for miR-27 in regulating insulin signaling, and this finding suggests that elevated miR-27 levels may contribute to early development of hepatic insulin resistance.

Cholesterol Efflux Efficiency of Reconstituted HDL Is Affected by Nanoparticle Lipid Composition.

Cardiovascular disease (CVD), the leading cause of mortality worldwide is primarily caused by atherosclerosis, which is promoted by the accumulation of low-density lipoproteins into the intima of large arteries. Multiple nanoparticles mimicking natural HDL (rHDL) have been designed to remove cholesterol excess in CVD therapy. The goal of this investigation was to assess the cholesterol efflux efficiency of rHDLs with different lipid compositions, mimicking different maturation stages of high-density lipoproteins (HDLs) occurring in vivo. METHODS: the cholesterol efflux activity of soybean PC (Soy-PC), 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC), DPPC:Chol:1-palmitoyl-2-hydroxy-sn-glycero-3-phosphocholine (LysoPC) and DPPC:18:2 cholesteryl ester (CE):LysoPC rHDLs was determined in several cell models to investigate the contribution of lipid composition to the effectiveness of cholesterol removal. RESULTS: DPPC rHDLs are the most efficient particles, inducing cholesterol efflux in all cellular models and in all conditions the effect was potentiated when the ABCA1 transporter was upregulated. CONCLUSIONS: DPPC rHDLs, which resemble nascent HDL, are the most effective particles in inducing cholesterol efflux due to the higher physical binding affinity of cholesterol to the saturated long-chain-length phospholipids and the favored cholesterol transfer from a highly positively curved bilayer, to an accepting planar bilayer such as DPPC rHDLs. The physicochemical characteristics of rHDLs should be taken into consideration to design more efficient nanoparticles to promote cholesterol efflux.