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OBJECTIVES: This study explored the association of deleterious variants in pharmacodynamics (PD) genes with statin response and adverse effects in patients with familial hypercholesterolemia (FH) and analyzed their potential effects on protein structure and stability. METHODS: Clinical and laboratory data were obtained from 144 adult FH patients treated with statins. A panel of 32 PD genes was analyzed by exon-targeted gene sequencing. Deleterious variants were identified using prediction algorithms and their structural effects were analyzed by molecular modeling studies. RESULTS: A total of 102 variants were predicted as deleterious (83 missense, 8 stop-gain, 4 frameshift, 1 indel, 6 splicing). The variants ABCA1 rs769705621 (indel), LPA rs41267807 (p.Tyr2023Cys) and KIF6 rs20455 (p.Trp719Arg) were associated with reduced low-density lipoprotein cholesterol (LDLc) response to statins, and the LPL rs1801177 (p.Asp36Asn) with increased LDLc response (P < 0.05). LPA rs3124784 (p.Arg2016Cys) was predicted to increase statin response (P = 0.022), and ABCA1 rs769705621 to increase the risk of statin-related adverse events (SRAE) (P = 0.027). LPA p.Arg2016Cys and LPL p.Asn36Asp maintained interactions with solvent, LPA p.Tyr2023Cys reduced intramolecular interaction with Gln1987, and KIF6 p.Trp719Arg did not affect intramolecular interactions. DDMut analysis showed that LPA p.Arg2016Cys and p.Tyr2023Cys and LPL p.Asp36Asn caused energetically favorable changes, and KIF6 p.Trp719Arg resulted in unfavorable energetic changes, affecting protein stability. CONCLUSION: Deleterious variants in ABCA1, LPA, LPL and KIF6 are associated with variability in LDLc response to statins, and ABCA1 rs769705621 is associated with SRAE risk in FH patients. Molecular modeling studies suggest that LPA p.Tyr2023Cys and KIF6 p.Trp719Arg disturb protein conformational structure and stability.

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AIM: Methylation of LDLR, PCSK9 and LDLRAP1 CpG sites was assessed in patients with familial hypercholesterolemia (FH). METHODS: DNA methylation of was analyzed by pyrosequencing in 131 FH patients and 23 normolipidemic (NL) subjects. RESULTS: LDLR, PCSK9 and LDLRP1 methylation was similar between FH patients positive (MD) and negative (non-MD) for pathogenic variants in FH-related genes. LDLR and PCSK9 methylation was higher in MD and non-MD groups than NL subjects (p < 0.05). LDLR, PCSK9 and LDLRAP1 methylation profiles were associated with clinical manifestations and cardiovascular events in FH patients (p < 0.05). CONCLUSION: Differential methylation of LDLR, PCSK9 and LDLRAP1 is associated with hypercholesterolemia and cardiovascular events. This methylation profile maybe useful as a biomarker and contribute to the management of FH.

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Aim: Methylation of LDLR, PCSK9 and LDLRAP1 CpG sites was assessed in patients with familial hypercholesterolemia (FH). Methods: DNA methylation of was analyzed by pyrosequencing in 131 FH patients and 23 normolipidemic (NL) subjects.Results:  LDLR, PCSK9 and LDLRP1 methylation was similar between FH patients positive (MD) and negative (non-MD) for pathogenic variants in FH-related genes. LDLR and PCSK9 methylation was higher in MD and non-MD groups than NL subjects (p < 0.05). LDLR, PCSK9 and LDLRAP1 methylation profiles were associated with clinical manifestations and cardiovascular events in FH patients (p < 0.05).Conclusion: Differential methylation of LDLR, PCSK9 and LDLRAP1 is associated with hypercholesterolemia and cardiovascular events. This methylation profile maybe useful as a biomarker and contribute to the management of FH.

[Box: see text].

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OBJECTIVES: This study explored the association of deleterious variants in pharmacodynamics (PD) genes with statin response and adverse effects in patients with familial hypercholesterolemia (FH) and analyzed their potential effects on protein structure and stability. METHODS: Clinical and laboratory data were obtained from 144 adult FH patients treated with statins. A panel of 32 PD genes was analyzed by exon-targeted gene sequencing. Deleterious variants were identified using prediction algorithms and their structural effects were analyzed by molecular modeling studies. RESULTS: A total of 102 variants were predicted as deleterious (83 missense, 8 stop-gain, 4 frameshift, 1 indel, 6 splicing). The variants ABCA1 rs769705621 (indel), LPA rs41267807 (p.Tyr2023Cys) and KIF6 rs20455 (p.Trp719Arg) were associated with reduced low-density lipoprotein cholesterol (LDLc) response to statins, and the LPL rs1801177 (p.Asp36Asn) with increased LDLc response (P < 0.05). LPA rs3124784 (p.Arg2016Cys) was predicted to increase statin response (P = 0.022), and ABCA1 rs769705621 to increase the risk of statin-related adverse events (SRAE) (P = 0.027). LPA p.Arg2016Cys and LPL p.Asn36Asp maintained interactions with solvent, LPA p.Tyr2023Cys reduced intramolecular interaction with Gln1987, and KIF6 p.Trp719Arg did not affect intramolecular interactions. DDMut analysis showed that LPA p.Arg2016Cys and p.Tyr2023Cys and LPL p.Asp36Asn caused energetically favorable changes, and KIF6 p.Trp719Arg resulted in unfavorable energetic changes, affecting protein stability. CONCLUSION: Deleterious variants in ABCA1, LPA, LPL and KIF6 are associated with variability in LDLc response to statins, and ABCA1 rs769705621 is associated with SRAE risk in FH patients. Molecular modeling studies suggest that LPA p.Tyr2023Cys and KIF6 p.Trp719Arg disturb protein conformational structure and stability.

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Familial Hypercholesterolemia (FH) is a genetic disorder associated with premature atherosclerosis and increased risk of cardiovascular diseases. LDLR deleterious mutations are associated with FH, however the role of some missense variants in FH pathogenicity remains to be elucidated. This study explored the predictive impact of LDLR missense variants on protein structure and investigated their functional effects on LDLR expression in HepG2 cells transfected with CRISPR/Cas9 constructs. FH (n = 287) and non-FH patients (n = 45) were selected, and lipid profile was obtained from medical records. LDLR variants were identified using an exon-targeted gene sequencing strategy, considering its cost-effective to increase accuracy in the identification step of the most likely FH-related variants in a less laborious process. LDLR variants were selected based on conflicting pathogenicity results found in Clinvar, in silico prediction tools, affected LDLR domains, and less common variants considering minor allele frequency < 0.05. Molecular modeling studies were used to predict the effects of LDLR missense variants on protein structure. Recombinant LDLR variants were constructed using CRISPR/Cas9 system and were used to transfect HepG2 cells. Functional assays in transfected cells were performed to assess LDLR expression using flow cytometry and western blotting, and LDLR activity using flow cytometry and confocal microscopy. The variants rs121908039 (c.551G>A, p.C184Y), rs879254797 (c.1118G>A, p.G373D), rs28941776 (c.1646G>A, p.G549D), rs750518671 (c.2389G>C, p.V797L), rs5928 (c.2441G>A, p.R814Q) and rs137853964 (c.2479G>A, p.V827I) were selected for molecular docking analysis. The p.C184Y exhibited a favorable energy change for protein stability due to its interaction with EGF-A/EGF-B regions; p.G373D and p.G549D displayed intermediate energy changes; and p.R814Q and p.V827I showed smaller energy changes. The results of functional assays showed that p.G373D, p.V797L and p.R814Q reduced LDLR expression and activity (p < 0.05). Microscopic analysis of the p.V797L and p.G373D variants revealed altered lipid localization and accumulation in transfected HepG2 cells. Carriers of p.G549D, p.V797L and p.R814Q had higher LDL cholesterol levels than non-FH group, and (p < 0.05). p.G373D and p.G549D were associated with clinical manifestations of FH. In conclusion, the p.C184Y, p.G373D, p.G549D and p.R814Q variants alter protein stability and intramolecular interactions, while p.V797L has a minimal impact on protein stability, and p.V827I has no significant intramolecular interactions. p.G373D, p.V767L and p.R814Q are associated with impaired LDLR expression and activity.

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Aim: Methylation of LDLR, PCSK9 and LDLRAP1 CpG sites was assessed in patients with familialhypercholesterolemia (FH). Methods: DNA methylation of was analyzed by pyrosequencing in 131FH patients and 23 normolipidemic (NL) subjects. Results: LDLR, PCSK9 and LDLRP1 methylationwas similar between FH patients positive (MD) and negative (non-MD) for pathogenic variantsin FH-related genes. LDLR and PCSK9 methylation was higher in MD and non-MD groups thanNL subjects (p < 0.05). LDLR, PCSK9 and LDLRAP1 methylation profiles were associated withclinical manifestations and cardiovascular events in FH patients (p < 0.05). Conclusion: Differentialmethylation of LDLR, PCSK9 and LDLRAP1 is associated with hypercholesterolemia and cardiovascularevents. This methylation profile maybe useful as a biomarker and contribute to the management ofFH.

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Familial hypercholesterolemia (FH) is a disorder of lipid metabolism that causes elevated low-density lipoprotein cholesterol (LDL-c) and increased premature atherosclerosis risk. Statins inhibit endogenous cholesterol biosynthesis, which reduces LDL-c plasma levels and prevent from cardiovascular events. This study aimed to explore the effects of statin treatment on serum lipidomic profile and to identify biomarkers of response in subjects with FH. Seventeen adult FH patients underwent a 6-week washout followed by 4-week treatment with atorvastatin (80 mg/day) or rosuvastatin (40 mg/day). LDL-c response was considered good (40­70 % reduction, n = 9) or poor (3­33 % reduction, n = 8). Serum lipidomic profile was analyzed by ultra-high-performance liquid chromatography combined with electrospray ionization tandem time-of-flight mass spectrometry, and data were analyzed using MetaboAnalyst v5.0. Lipidomic analysis identified 353 lipids grouped into 16 classes. Statin treatment reduced drastically 8 of 13 lipid classes, generating a characteristic lipidomic profile with a significant contribution of phosphatidylinositols (PI) 16:0/18:2, 18:0/18:1 and 18:0/18:2; and triacylglycerols (TAG) 18:2x2/18:3, 18:1/18:2/18:3, 16:1/18:2x2, 16:1/18:2/18:3 and 16:1/18:2/Arachidonic acid (p-adjusted <0.05). Biomarker analysis implemented in MetaboAnalyst subsequently identified PI 16:1/18:0, 16:0/18:2 and 18:0/18:2 as predictors of statin response with and receiver operating characteristic (ROC) areas under the curve of 0.98, 0.94 and 0.91, respectively. In conclusion, statins extensively modulate the overall serum lipid composition of FH individuals and these findings suggest that phosphatidyl-inositol molecules are potential predictive biomarkers of statin response.

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Polymorphisms in genes of leptin-melanocortin and insulin pathways have been associated with obesity and type 2 diabetes. We hypothesized that polymorphisms in IRS1, IRS2, MC3R, and MC4R influence metabolic and inflammatory markers and food intake composition in Brazilian subjects. This exploratory pilot study included 358 adult subjects. Clinical, anthropometric, and laboratory data were obtained through interview and access to medical records. The variants IRS1 rs2943634 A˃C, IRS2 rs1865434 C>T, MC3R rs3746619 C>A, and MC4R rs17782313 T>C were analyzed by real-time polymerase chain reaction. Food intake composition was assessed in a group of subjects with obesity (n = 84) before and after a short-term nutritional counseling program (9 weeks). MC4R rs17782313 was associated with increased risk of obesity (P = .034). Multivariate linear regression analysis adjusted by covariates indicated associations of IRS2 rs1865434 with reduced low-density lipoprotein cholesterol and resistin, MC3R rs3746619 with high glycated hemoglobin, and IRS1 rs2943634 and MC4R rs17782313 with increased high-sensitivity C-reactive protein (P < .05). Energy intake and carbohydrate and total fat intakes were reduced after the diet-oriented program (P < .05). Multivariate linear regression analysis showed associations of IRS2 rs1865434 with high basal fiber intake, IRS1 rs2943634 with low postprogram carbohydrate intake, and MC4R rs17782313 with low postprogram total fat and saturated fatty acid intakes (P < .05). Although significant associations did not survive correction for multiple comparisons using the Benjamini-Hochberg method in this exploratory study, polymorphisms in IRS1, IRS2, MC3R, and MC4R influence metabolic and inflammatory status in Brazilian adults. IRS1 and MC4R variants may influence carbohydrate, total fat, and saturated fatty acid intakes in response to a diet-oriented program in subjects with obesity.

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Familial hypercholesterolemia (FH) is a disorder of lipid metabolism that causes elevated low-density lipoprotein cholesterol (LDL-c) and increased premature atherosclerosis risk. Statins inhibit endogenous cholesterol biosynthesis, which reduces LDL-c plasma levels and prevent from cardiovascular events. This study aimed to explore the effects of statin treatment on serum lipidomic profile and to identify biomarkers of response in subjects with FH. Seventeen adult FH patients underwent a 6-week washout followed by 4-week treatment with atorvastatin (80 mg/day) or rosuvastatin (40 mg/day). LDL-c response was considered good (40-70 % reduction, n = 9) or poor (3-33 % reduction, n = 8). Serum lipidomic profile was analyzed by ultra-high-performance liquid chromatography combined with electrospray ionization tandem time-of-flight mass spectrometry, and data were analyzed using MetaboAnalyst v5.0. Lipidomic analysis identified 353 lipids grouped into 16 classes. Statin treatment reduced drastically 8 of 13 lipid classes, generating a characteristic lipidomic profile with a significant contribution of phosphatidylinositols (PI) 16:0/18:2, 18:0/18:1 and 18:0/18:2; and triacylglycerols (TAG) 18:2x2/18:3, 18:1/18:2/18:3, 16:1/18:2x2, 16:1/18:2/18:3 and 16:1/18:2/Arachidonic acid (p-adjusted <0.05). Biomarker analysis implemented in MetaboAnalyst subsequently identified PI 16:1/18:0, 16:0/18:2 and 18:0/18:2 as predictors of statin response with and receiver operating characteristic (ROC) areas under the curve of 0.98, 0.94 and 0.91, respectively. In conclusion, statins extensively modulate the overall serum lipid composition of FH individuals and these findings suggest that phosphatidyl-inositol molecules are potential predictive biomarkers of statin response.

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BACKGROUND: Familial hypercholesterolemia (FH) is caused by pathogenic variants in low-density lipoprotein (LDL) receptor (LDLR) or its associated genes, including apolipoprotein B (APOB), proprotein convertase subtilisin/kexin type 9 (PCSK9), and LDLR adaptor protein 1 (LDLRAP1). However, approximately 40% of the FH patients clinically diagnosed (based on FH phenotypes) may not carry a causal variant in a FH-related gene. Variants located at 3' untranslated region (UTR) of FH-related genes could elucidate mechanisms involved in FH pathogenesis. This study used a computational approach to assess the effects of 3'UTR variants in FH-related genes on miRNAs molecular interactions and to explore the association of these variants with molecular diagnosis of FH. METHODS AND RESULTS: Exons and regulatory regions of FH-related genes were sequenced in 83 FH patients using an exon-target gene sequencing strategy. In silico prediction tools were used to study the effects of 3´UTR variants on interactions between miRNAs and target mRNAs. Pathogenic variants in FH-related genes (molecular diagnosis) were detected in 44.6% FH patients. Among 59 3'UTR variants identified, LDLR rs5742911 and PCSK9 rs17111557 were associated with molecular diagnosis of FH, whereas LDLR rs7258146 and rs7254521 and LDLRAP1 rs397860393 had an opposite effect (p < 0.05). 3´UTR variants in LDLR (rs5742911, rs7258146, rs7254521) and PCSK9 (rs17111557) disrupt interactions with several miRNAs, and more stable bindings were found with LDLR (miR-4435, miR-509-3 and miR-502) and PCSK9 (miR-4796). CONCLUSION: LDLR and PCSK9 3´UTR variants disturb miRNA:mRNA interactions that could affect gene expression and are potentially associated with molecular diagnosis of FH.

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