Dataset Information

Tweaking lentiviral vector design balances efficacy and safety in liver-directed gene therapy for familial hypercholesterolemia

ABSTRACT: Elevated low-density lipoprotein (LDL) cholesterol is the hallmark of familial hypercholesterolemia (FH), an inherited disease mostly due to mutations in the LDL receptor (LDLR)-encoding gene. Here we enforced overexpression of LDLR in hepatocytes by in vivo lentiviral vector (LV) gene therapy and normalized circulating LDL cholesterol in a mouse model of FH. One year after gene therapy we detected a high incidence of hepatic tumors in treated mice. Analysis of LV genomic integration sites in the liver tumors revealed expanded clones bearing LV insertions within the Fyn-related kinase (Frk) gene, a known hepatic oncogene, inducing the formation of aberrant LDLR-FRK transcripts. When we purposely overexpressed LDLR-FRK by LV gene transfer, we observed hepatocellular hyperplasia and hypertrophy, supporting a role of this chimeric protein in oncogenesis. Since high expression of this chimeric oncogene and the LDLR likely cooperated to cause liver toxicity, we reduced the strength of LDLR expression within LV. We achieved normalization of circulating LDL cholesterol in two FH mouse models and prevention of atherosclerosis, even under high-fat diet challenge, without any long-term liver tumorigenicity. Overall, our in-depth assessment of the efficacy and safety of in vivo gene therapy for FH provides new insights into mechanisms of action and potential vulnerabilities, with implications for future developments of lipid-lowering gene therapies.

ORGANISM(S): Mus musculus

PROVIDER: GSE315905 | GEO | 2026/04/15

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Inherited variants in the LDL receptor (LDLR) gene are the most common cause of familial hypercholesterolemia (FH), significantly increasing coronary artery disease risk. Early identification of pathogenic LDLR variants enables prompt intervention with lipid-lowering therapies; however, most LDLR variants observed in the population have uncertain or absent clinical classifications, limiting the clinical utility of genetic testing for definitive FH diagnosis, cascade testing of at-risk relatives, and timely lipid-lowering intervention. We developed an innovative, activity-normalized prime editing screening pipeline to measure the impact of 5,184 LDLR coding variants on LDL-cholesterol (LDL-C) uptake. Through pairing a genotypic outcome reporter with every prime editing guide RNA (pegRNA), we adjust phenotypic measurements to account for variable editing efficiency. Further, we use a statistical estimation approach that leverages measurements for all missense variants at a given position to denoise the resulting scores. We show that prime editing-mediated reporter editing correlates with endogenous variant installation frequency, allowing activity normalization to improve imputation of LDLR variant effect. Our optimized prime editing assay identifies a broad, continuous spectrum of variant functional effects. We achieve robust separation of pathogenic vs. benign ClinVar variants and concordance between experimentally derived functional scores and LDL-C levels measured in UK Biobank participants. Further, we calibrate the strength of this functional evidence to align with the ACMG/AMP variant interpretation guidelines. By integrating additional sources of evidence, a majority of currently unclassified rare LDLR variants appear to meet computational evidence thresholds for reclassification and can be prioritized for expert review. We use the broad coverage of this screen to gain insight into how apolipoproteins bind to LDLR. In particular, we identify and characterize rare LDLR variants that enhance LDL-C uptake through increased interaction with apolipoprotein B. Finally, we compare prime editing-based functional scores with those derived from recent base editing and cDNA-based LDLR variant screens, and find that all approaches show robust correlation with clinically observed LDL-C levels and computational scores, while prime editing identifies splice-altering coding variants that are not modeled by cDNA screening. Altogether, our approach demonstrates the power of prime editing to significantly improve understanding of how variants in LDLR impact function and contribute to FH.

Project description:Background: The low-density lipoprotein receptor (LDLR) in the liver plays a crucial role in clearing low-density lipoprotein cholesterol (LDL-C) from the bloodstream. This process takes place mainly in the liver. Under atherogenic conditions, Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9), secreted by the liver, binds to LDLR on hepatocytes, preventing its recycling and enhancing its lysosomal degradation. This process reduces LDL-C clearance, promoting hypercholesterolemia. Epsins, a family of ubiquitin-binding endocytic adaptors, are key regulators of atherogenesis in lesional cells, including endothelial cells and macrophages. Given epsins' canonical role in regulating endocytosis of cell surface receptors, we aimed to determine whether and how liver epsins contribute to PCSK9-mediated LDLR endocytosis and degradation, thereby impairing LDL-C clearance and accelerating atherosclerosis. Methods: Liver-specific epsin knockout (Liver-DKO) atherosclerotic models were generated in ApoE-/- and PCSK9-AAV8-induced atheroprone mice fed on a Western diet. We utilized single-cell RNA sequencing, along with molecular, cellular, and biochemical analyses, to investigate the physiological role of liver epsins in PCSK9-mediated LDLR degradation. Additionally, we explored the therapeutic potential of nanoparticle-encapsulated siRNAs targeting epsins 1 and 2 in ApoE-/- mice with established atherosclerosis. Results: Western diet (WD)-induced atherosclerosis was significantly attenuated in ApoE-/-/Liver-DKO mice compared with ApoE-/- controls, as well as in PCSK9-AAV8-induced Liver-DKO mice compared with PCSK9-AAV8-induced wild-type (WT) mice accompanied by reductions in blood cholesterol and triglyceride levels. Mechanistically, single-cell RNA sequencing of hepatocytes and aortas isolated from atherosclerotic ApoE-/- and ApoE-/-/Liver-DKO mice revealed epsin-deficient Ldlrhi hepatocytes with diminished lipogenic potential. Notably, pathway analysis of hepatocytes showed increased LDL particle clearance and enhanced LDLR-cholesterol interactions under WD treatment in ApoE-/-/Liver-DKO mice compared with ApoE-/- controls, correlating with decreased plasma LDL-C levels. Furthermore, pathway analysis of the aortas showed attenuated inflammation and endothelial activation, coupled with reduced lipid uptake, and enhanced cholesterol efflux under WD treatment in ApoE-/-/Liver-DKO mice compared with ApoE-/- controls. Moreover, the absence of liver epsins led to an upregulation of LDLR protein expression in hepatocytes. We further demonstrated that epsins bind LDLR via the ubiquitin-interacting motif (UIM), enabling PCSK9-mediated LDLR degradation. Depleting epsins abolished this degradation, thereby preventing atheroma progression. Lastly, targeting liver epsins with nanoparticle-encapsulated epsins siRNAs effectively ameliorates dyslipidemia and inhibits atherosclerosis progression. These results are consistent with findings showing an increased epsin1 and epsin2 expression in atherosclerotic cardiovascular disease patients. Conclusions: Liver epsins drive atherogenesis by promoting PCSK9-mediated LDLR degradation, thereby elevating circulating LDL-C levels and heightening lesional inflammation. As such, targeting epsins in the liver represents a promising therapeutic strategy to mitigate atherosclerosis by preserving LDLR and enhancing LDL-C clearance in the liver.

Project description:Background: Elevated plasma cholesterol promotes the formation of atherosclerotic lesions in which monocyte-derived lipid-laden macrophages are frequently found. To analyze, if circulating monocytes already show increased lipid content and differences in lipoprotein metabolism, we compared monocytes from patients with Familial Hypercholesterolemia (FH) with those from healthy individuals. Methods: Cholesterol and oxidized cholesterol metabolite serum levels of FH and of healthy, gender/age matched control subjects were measured by combined gas chromatography ? mass spectroscopy. Monocytes from patients with FH and from healthy subjects were isolated by antibody-assisted density centrifugation. Gene expression profiles of isolated monocytes were measured using Affymetrix HG-U 133 Plus 2.0 microarrays. We compared monocyte gene expression profiles from FH patients with healthy controls using a Welch T-test with correction for multiple testing (p < 0.05; Benjamini Hochberg correction, False Discovery Rate = 0.05). The differential expression of FH associated genes was validated at the mRNA level by qRT-PCR and/or at the protein level by Western Blot or flow cytometry. Functional validation of monocyte scavenger receptor activities were done by binding assays and dose/time dependent uptake analysis using native and oxidized LDL. Results: Using microarray analysis we found in FH patients a significant up-regulation of 1,617 genes and a down-regulation of 701 genes compared to monocytes from healthy individuals. These include genes of proteins that are involved in the uptake, biosynthesis, disposition, and cellular efflux of cholesterol. In addition, plasma from FH patients contains elevated amounts of sterols and oxysterols. An increased uptake of oxidized as well as of native LDL by FH monocytes combined with a down-regulation of NPC1 and ABCA1 explains the lipid accumulation observed in these cells. Conclusion: Our data demonstrate that circulating FH monocytes show differences in cell physiology that may contribute to the early onset of atherosclerosis in this disease. Keywords: Micro-array analysis, cell type comparison,

Dataset Information

Tweaking lentiviral vector design balances efficacy and safety in liver-directed gene therapy for familial hypercholesterolemia

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets