A genetic variant in the LDLR promoter is responsible for part of the LDL-cholesterol variability in primary hypercholesterolemia

The efficacy and safety of proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors combined with statins in patients with hypercholesterolemia: a network meta-analysis

Background

In recent years, the position of PCSK9 inhibitors as adjuvant therapy to statins in guidelines has further improved. However, there remained a dearth of direct comparative studies among different PCSK9 inhibitors. Therefore, this study aimed to conduct a network meta-analysis to evaluate the efficacy and safety of different PCSK9 inhibitors combined with statins.

Methods

A comprehensive literature search was conducted from the study's inception to 12 November 2023, encompassing multiple online databases including PubMed, Embase, Cochrane Central, Web of Science, and ClinicalTrials.gov to obtain relevant randomized controlled trials. Frequentist network meta-analysis was employed to compare the efficacy and safety of different PCSK9 inhibitors. The efficacy endpoints were low-density lipoprotein cholesterol (LDL-C), apolipoprotein B (ApoB), and lipoprotein (a) (Lp(a)). The safety endpoints were any adverse events (AE), severe adverse events (SAE), AE leading to treatment discontinuation, and injection-site reaction.

Results

Compared with placebo and ezetimibe, all PCSK9 inhibitors demonstrated significant reductions in LDL-C levels. Notably, evolocumab exhibited the most pronounced effect with a treatment difference of -63.67% (-68.47% to -58.87%) compared with placebo. Regarding dosage selection for evolocumab, the regimen of 140 mg Q2W (-69.13%, -74.55% to -63.72%) was superior to 420 mg QM (-61.51%, -65.97% to -57.05%). Based on rankings and P-scores analysis, tafolecimab 150 mg Q2W demonstrated superior efficacy in reducing ApoB levels (-61.70%, -84.38% to -39.02%) and Lp(a) levels (-43%, 30%, -68%, 81% to -17%, 79%). Furthermore, the safety profile of PCSK9 inhibitors was favorable with no increase in the incidence of AE, SAE, or AE leading to treatment discontinuation; however, alirocumab, inclisiran, and tafolecimab may potentially entail a potential risk associated with injection-site reactions.

Conclusion

Compared with placebo and ezetimibe, PCSK9 inhibitors can significantly reduce LDL-C, ApoB, and Lp(a) when combined with statins to treat hypercholesterolemia. Furthermore, PCSK9 inhibitors and ezetimibe exhibit similar safety profiles.

Systematic Review Registration

[PROSPERO], identifier [CRD42023490506].

Large-scale genome-wide interaction analyses on multiple cardiometabolic risk factors to identify age-specific genetic risk factors

The genetic landscape of cardiometabolic risk factors has been explored extensively. However, insight in the effects of genetic variation on these risk factors over the life course is sparse. Here, we performed genome-wide interaction studies (GWIS) on different cardiometabolic risk factors to identify age-specific genetic risks. This study included 270,276 unrelated European-ancestry participants from the UK Biobank (54.2% women, a median age of 58 [interquartile range (IQR): 50, 63] years). GWIS models with interaction terms between genetic variants and age were performed on apolipoprotein B (ApoB), low-density lipoprotein-cholesterol (LDL-C), log-transformed triglycerides (TG), body mass index (BMI) and systolic blood pressure (SBP). Replication was subsequently performed in the Copenhagen General Population Study (CGPS) and the Estonian Biobank (EstBB). Multiple lead variants were identified to have genome-wide significant interactions with age (Pinteraction < 1e - 08). In detail, rs429358 (tagging APOE4) was identified for ApoB (Pinteraction = 9.0e - 14) and TG (Pinteraction = 5.4e - 16). Three additional lead variants were identified for ApoB: rs11591147 (R46L in PCSK9, Pinteraction = 3.9e - 09), rs34601365 (near APOB, Pinteraction = 8.4e - 09) and rs17248720 (near LDLR, Pinteraction = 2.0e - 09). Effect sizes of the identified lead variants were generally closer to the null with increasing age. No variant-age interactions were identified for LDL-C, SBP and BMI. The significant interactions of rs429358 with age on ApoB and TG were replicated in both CGPS and EstBB. The majority of genetic effects on cardiometabolic risk factors remain relatively constant over age, with the noted exceptions of specific genetic effects on ApoB and TG.

In silico analysis of upstream variants in Brazilian patients with Familial Hypercholesterolemia

Familial hypercholesterolemia (FH) is a prevalent autosomal genetic disease associated with increased risk of early cardiovascular events and death due to chronic exposure to very high levels of low-density lipoprotein cholesterol (LDL-c). Pathogenic variants in the coding regions of LDLR, APOB and PCSK9 account for most FH cases, and variants in non-coding regions maybe involved in FH as well. Variants in the upstream region of LDLR, APOB and PCSK9 were screened by targeted next-generation sequencing and their effects were explored using in silico tools. Twenty-five patients without pathogenic variants in FH-related genes were selected. 3 kb upstream regions of LDLR, APOB and PCSK9 were sequenced using the AmpliSeq (Illumina) and Miseq Reagent Nano Kit v2 (Illumina). Sequencing data were analyzed using variant discovery and functional annotation tools. Potentially regulatory variants were selected by integrating data from public databases, published data and context-dependent regulatory prediction score. Thirty-four single nucleotide variants (SNVs) in upstream regions were identified (6 in LDLR, 15 in APOB, and 13 in PCSK9). Five SNVs were prioritized as potentially regulatory variants (rs934197, rs9282606, rs36218923, rs538300761, g.55038486A>G). APOB rs934197 was previously associated with increased rate of transcription, which in silico analysis suggests that could be due to reducing binding affinity of a transcriptional repressor. Our findings highlight the importance of variant screening outside of coding regions of all relevant genes. Further functional studies are necessary to confirm that prioritized variants could impact gene regulation and contribute to the FH phenotype.

The landscape of GWAS validation; systematic review identifying 309 validated non-coding variants across 130 human diseases

Background

The remarkable growth of genome-wide association studies (GWAS) has created a critical need to experimentally validate the disease-associated variants, 90% of which involve non-coding variants.

Methods

To determine how the field is addressing this urgent need, we performed a comprehensive literature review identifying 36,676 articles. These were reduced to 1454 articles through a set of filters using natural language processing and ontology-based text-mining. This was followed by manual curation and cross-referencing against the GWAS catalog, yielding a final set of 286 articles.

Results

We identified 309 experimentally validated non-coding GWAS variants, regulating 252 genes across 130 human disease traits. These variants covered a variety of regulatory mechanisms. Interestingly, 70% (215/309) acted through cis-regulatory elements, with the remaining through promoters (22%, 70/309) or non-coding RNAs (8%, 24/309). Several validation approaches were utilized in these studies, including gene expression (n = 272), transcription factor binding (n = 175), reporter assays (n = 171), in vivo models (n = 104), genome editing (n = 96) and chromatin interaction (n = 33).

Conclusions

This review of the literature is the first to systematically evaluate the status and the landscape of experimentation being used to validate non-coding GWAS-identified variants. Our results clearly underscore the multifaceted approach needed for experimental validation, have practical implications on variant prioritization and considerations of target gene nomination. While the field has a long way to go to validate the thousands of GWAS associations, we show that progress is being made and provide exemplars of validation studies covering a wide variety of mechanisms, target genes, and disease areas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01216-w.

Evidence of association of circulating epigenetic-sensitive biomarkers with suspected coronary heart disease evaluated by Cardiac Computed Tomography

Circulating biomarkers available in clinical practice do not allow to stratify patients with coronary heart disease (CHD) prior the onset of a clinically relevant event. We evaluated the methylation status of specific genomic segments and gene expression in peripheral blood of patients undergoing Cardiac Computed Tomography (CCT) for CHD (n = 95).

We choose to investigate cholesterol metabolism. Methylation and gene expression of low density lipoprotein receptor (LDLR), sterol regulatory element-binding factor 2 (SREBF2) and ATP-binding cassette transporter 1 (ABCA1) were evaluated by qRT-PCR. Calcium score (CACS), stenosis degree, total plaque volume (TPV), calcified plaque volume (CPV), non-calcified plaque volume (NCPV) and plaque burden (PB) were assessed in all CHD patients (n = 65). The percentage of methylation at the specific analyzed segment of LDLR promoter was higher in CHD patients vs healthy subjects (HS) (n = 30) (p = 0.001). LDLR, SREBF2 and ABCA1 mRNAs were up-regulated in CHD patients vs HS (p = 0.02; p = 0.019; p = 0.008). SREBF2 was overexpressed in patients with coronary stenosis ≥50% vs subjects with stenosis <50% (p = 0.036). After adjustment for risk factors and clinical features, ABCA1 (p = 0.005) and SREBF2 (p = 0.010) gene expression were identified as independent predictors of CHD and severity. ROC curve analysis revealed a good performance of ABCA1 on predicting CHD (AUC = 0.768; p<0.001) and of SREBF2 for the prediction of disease severity (AUC = 0.815; p<0.001). Moreover, adjusted multivariate analysis demonstrated SREBF2 as independent predictor of CPV, NCPV and TPV (p = 0.022; p = 0.002 and p = 0.006) and ABCA1 as independent predictor of NCPV and TPV (p = 0.002 and p = 0.013).

CHD presence and characteristics are related to selected circulating transcriptional and epigenetic-sensitive biomarkers linked to cholesterol pathway. More extensive analysis of CHD phenotypes and circulating biomarkers might improve and personalize cardiovascular risk stratification in the clinical settings.

A renal genetic risk score (GRS) is associated with kidney dysfunction in people with type 2 diabetes

This study aims to investigate whether renal and cardiovascular phenotypes in Italian patients with type 2 diabetes (T2D) could be influenced by a number of disease risk SNPs recently found in genome-wide association studies (GWAS). In 1591 Italian subjects with T2D: (1) 47 SNPs associated to kidney function and/or chronic kidney disease (CKD) and 49 SNPs associated to cardiovascular disease (CVD) risk were genotyped; (2) urinary albumin/creatinine (A/C) ratio, glomerular filtration rate (eGFR) and lipid profile were assessed; (3) a standard electrocardiogram was performed; (4) two genotype risk scores (GRS) were computed (a renal GRS calculated selecting 39 SNPs associated with intermediate traits of kidney damage and a cardiovascular GRS determined selecting 42 SNPs associated to CVD risk phenotypes). After correction for multiple comparisons, the renal GRS was not associated to A/C ratio (p = 0.33), but it was significantly related to decreased eGFR (p = 0.005). No association between the cardiovascular GRS and electrocardiogram was detected. Thus, in Italian patients with T2D a renal GRS might predict the decline in glomerular function, suggesting that the clock of diabetes associated CKD starts ticking long before hyperglycemia. Our data support the feasibility of gene-based prediction of complications in people with T2D.

Pharmacogenetics and the treatment of HIV-/HCV-coinfected patients

This review will summarize the role of pharmacogenetics in the natural history of hepatitis C, particularly in patients with HIV/HCV and will take the perspective of pharmacogenetics and its influence on the response to antiviral therapy and the susceptibility to develop adverse effects. This review will also devote a section to host genetics in other clinical situations, such as disease progression and acute HCV infection, which may determine whether treatment of HIV-/HCV-coinfected patients is implemented or deferred.

LDLR rs688 TT Genotype and T Allele Are Associated with Increased Susceptibility to Coronary Artery Disease-A Case-Control Study

PURPOSE

The low-density lipoprotein receptor is responsible for the binding and uptake of plasma LDL particles and plays a critical role in maintaining cellular cholesterol homeostasis. LDLR gene SNP rs688 has been reported to be associated with increased plasma total and LDL cholesterol in several populations and can lead to elevated plasma LDL levels, resulting in an increased risk for atherosclerosis and coronary artery disease. This study aimed to explore genetic LDLR variant rs688 for its potential roles in coronary artery disease.

METHODOLOGY

This study recruited 200 coronary artery disease patients and 200 healthy individuals. Genotyping of LDLR-rs688C > T gene variations was performed using the allele specific PCR method. Correlation of LDLR-rs688C > T gene variants with different clinicopathological features of coronary artery disease patients was performed. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were applied to evaluate the correlation of this microRNA polymorphism with coronary artery disease risk.

RESULTS

A significant difference was observed in genotype distribution among the coronary artery disease and matched healthy controls (p = 0.003). The frequencies of all three genotypes CC, CT, TT reported in the patient samples were 14%, 65% and 21% and in the healthy controls samples were 18%, 73% and 9%, respectively. The increased risk of developing CAD in Indian patients was found to be associated with LDLR rs688 TT genotype (OR = 3.0, 95% CI, 1.43 × 6.2; p = 0.003) RR 1.87 (1.20⁻2.91) p = 0.0037) and also the increased risk of developing CAD was reported to be associated with LDLR rs688 T allele (OR = 0.74, 95% CI, 1.57⁻0.97; p = 0.03) RR 0.85 (0.73⁻0.99) p = 0.03) compared to the C allele. Therefore, it was observed that more than a 3.0- and 0.74-fold increase risk of developing CAD was associated with TT genotype and T allele in Indian coronary artery disease patients.

CONCLUSION

The findings indicated that LDLR rs688 TT genotype and T allele are associated with an increased susceptibility to coronary artery disease patients. LDLR-rs688C > T gene variation can be used as a predisposing genetic marker for coronary artery disease. Further studies with larger sample sizes are necessary to confirm our findings.

Identification of the Functional Variant(s) that Explain the Low-Density Lipoprotein Receptor (LDLR) GWAS SNP rs6511720 Association with Lower LDL-C and Risk of CHD

Background

The Low-Density Lipoprotein Receptor (LDLR) SNP rs6511720 (G>T), located in intron-1 of the gene, has been identified in genome-wide association studies (GWAS) as being associated with lower plasma levels of LDL-C and a lower risk of coronary heart disease (CHD). Whether or not rs6511720 is itself functional or a marker for a functional variant elsewhere in the gene is not known.

Methods

The association of LDLR SNP rs6511720 with incidence of CHD and levels of LDL-C was determined by reference to CARDIoGRAM, C4D and Global lipids genetics consortium (GLGC) data. SNP annotation databases were used to identify possible SNP function and prioritization. Luciferase reporter assays in the liver cell line Huh7 were used to measure the effect of variant genotype on gene expression. Electrophoretic Mobility Shift Assays (EMSAs) were used to identify the Transcription Factors (TFs) involved in gene expression regulation.

Results

The phenotype-genotype analysis showed that the rs6511720 minor allele is associated with lower level of LDL-C [beta = -0.2209, p = 3.85 x10^-262], and lower risk of CHD [log (OR) = 0.1155, p = 1.04 x10^-7]. Rs6511720 is in complete linkage. Rs6511720 is in complete linkage disequilibrium (LD) with three intron-1 SNPs (rs141787760, rs60173709, rs57217136). Luciferase reporter assays in Huh7 cells showed that the rare alleles of both rs6511720 and rs57217136 caused a significant increase in LDLR expression compared to the common alleles (+29% and +24%, respectively). Multiplex Competitor-EMSAs (MC-EMSA) identified that the transcription factor serum response element (SRE) binds to rs6511720, while retinoic acid receptor (RAR) and signal transducer and activator of transcription 1 (STAT1) bind to rs57217136.

Conclusion

Both LDLR rs6511720 and rs57217136 are functional variants. Both these minor alleles create enhancer-binding protein sites for TFs and may contribute to increased LDLR expression, which is consequently associated with reduced LDL-C levels and 12% lower CHD risk.

Rare genetic variants with large effect on triglycerides in subjects with a clinical diagnosis of familial vs nonfamilial hypertriglyceridemia

BACKGROUND

Most primary severe hypertriglyceridemias (HTGs) are diagnosed in adults, but their molecular foundations have not been completely elucidated.

OBJECTIVE

We aimed to identify rare dysfunctional mutations in genes encoding regulators of lipoprotein lipase (LPL) function in patients with familial and non-familial primary HTG.

METHODS

We sequenced promoters, exons, and exon-intron boundaries of LPL, APOA5, LMF1, and GPIHBP1 in 118 patients with severe primary HTG (triglycerides >500 mg/dL) and 53 normolipidemic controls. Variant functionality was analyzed using predictive software and functional assays for mutations in regulatory regions.

RESULTS

We identified 29 rare variants, 10 of which had not been previously described: c.(-16A>G), c.(1018+2G>A), and p.(His80Arg) in LPL; p.(Arg143Alafs*57) in APOA5; p.(Val140Ile), p.(Leu235Ile), p.(Lys520*), and p.(Leu552Arg) in LMF1; and c.(-83G>A) and c.(-192A>G) in GPIHBP1. The c.(1018+2G>A) variant led to deletion of exon 6 in LPL cDNA, whereas the c.(-16A>G) analysis showed differences in the affinity for nuclear proteins. Overall, 20 (17.0%) of the patients carried at least one allele with a rare pathogenic variant in LPL, APOA5, LMF1, or GPIHBP1. The presence of a rare pathogenic variant was not associated with lipid values, family history of HTG, clinical diagnosis, or previous pancreatitis.

CONCLUSIONS

Less than one in five subjects with triglycerides >500 mg/dL and no major secondary cause for HTG may carry a rare pathogenic mutation in LPL, APOA5, LMF1, or GPIHBP1. The presence of a rare pathogenic variant is not associated with a differential phenotype.

Low-density lipoprotein receptor genetic polymorphism in chronic hepatitis C virus Egyptian patients affects treatment response

AIM: To correlate a genetic polymorphism of the low-density lipoprotein (LDL) receptor with antiviral responses in Egyptian chronic hepatitis C virus (HCV) patients.

METHODS: Our study included 657 HCV-infected patients with genotype 4 who received interferon-based combination therapy. Patients were divided into two groups based on their response to therapy: 356 were responders, and 301 were non-responders. Patients were compared to 160 healthy controls. All patients and controls underwent a thorough physical examination, measurement of body mass index (BMI) and the following laboratory tests: serum alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, albumin, total bilirubin, direct bilirubin, prothrombin time, prothrombin concentration, INR, complete blood count, serum creatinine, fasting blood sugar, HCV antibody, and hepatitis B surface antigen. All HCV patients were further subjected to the following laboratory tests: HCV-RNA using quantitative polymerase chain reaction (PCR), antinuclear antibodies, thyroid-stimulating hormone, an LDL receptor (LDLR) genotype study of LDLR exon8c.1171G>A and exon10c.1413G>A using real-time PCR-based assays, abdominal ultrasonography, ultrasonographic-guided liver biopsy, and histopathological examination of liver biopsies. Correlations of LDL receptor polymorphisms with HAI, METAVIR score, presence of steatosis, and BMI were performed in all cases.

RESULTS: There were no statistically significant differences in response rates between the different types of interferon used or LDLR exon10c.1413G>A. However, there was a significant difference in the frequency of the LDL receptor exon8c.1171G>A genotype between cases (AA: 25.9%, GA: 22.2%, GG: 51.9%) and controls (AA: 3.8%, GA: 53.1% and GG: 43.1%) (P < 0.001). There was a statistically significant difference in the frequency of the LDLR exon 8C:1171 G>A polymorphism between responders (AA: 3.6%, GA: 15.2%, GG: 81.2%) and non-responders (AA: 52.2%, GA: 30.6%, GG: 17.2%) (P < 0.001). The G allele of LDL receptor exon8c.1171G>A predominated in cases and controls over the A allele, and a statistically significant association with response to interferon was observed. The frequency of the LDLR exon8c.1171G>A allele in non-responders was: A: 67.4% and G: 32.6 vs A: 11.2% and G: 88.8% in responders (P < 0.001). Therefore, carriers of the A allele exhibited a 16.4 times greater risk for non-response. There was a significant association between LDL receptors exon8 c.1171G>A and HAI (P < 0.011). There was a significant association between LDL receptors exon8c.1171G>A and BMI. The mean BMI level was highest in patients carrying the AA genotype (28.7 ± 4.7 kg/m²) followed by the GA genotype (28.1 ± 4.8 kg/m²). The lowest BMI was the GG genotype (26.6 ± 4.3 kg/m²) (P < 0.001). The only significant associations were found between LDL receptors exon8 c.1171G>A and METAVIR score or steatosis (P < 0.001).

CONCLUSION: LDL receptor gene polymorphisms play a role in the treatment response of HCV and the modulation of disease progression in Egyptians infected with chronic HCV.

Next-generation gene discovery for variants of large impact on lipid traits

PURPOSE OF REVIEW

Detection of high-impact variants on lipid traits is complicated by complex genetic architecture. Although genome-wide association studies (GWAS) successfully identified many novel genes associated with lipid traits, it was less successful in identifying variants with a large impact on the phenotype. This is not unexpected, as the more common variants detectable by GWAS typically have small effects. The availability of large familial datasets and sequence data has changed the paradigm for successful genomic discovery of the novel genes and pathogenic variants underlying lipid disorders.

RECENT FINDINGS

Novel loci with large effects have been successfully mapped in families, and next-generation sequencing allowed for the identification of the underlying lipid-associated variants of large effect size. The success of this strategy relies on the simplification of the underlying genetic variation by focusing on large single families segregating extreme lipid phenotypes.

SUMMARY

Rare, high-impact variants are expected to have large effects and be more relevant for medical and pharmaceutical applications. Family data have many advantages over population-based data because they allow for the efficient detection of high-impact variants with an exponentially smaller sample size and increased power for follow-up studies.

Single nucleotide variations: biological impact and theoretical interpretation

Genome-wide association studies (GWAS) and whole-exome sequencing (WES) generate massive amounts of genomic variant information, and a major challenge is to identify which variations drive disease or contribute to phenotypic traits. Because the majority of known disease-causing mutations are exonic non-synonymous single nucleotide variations (nsSNVs), most studies focus on whether these nsSNVs affect protein function. Computational studies show that the impact of nsSNVs on protein function reflects sequence homology and structural information and predict the impact through statistical methods, machine learning techniques, or models of protein evolution. Here, we review impact prediction methods and discuss their underlying principles, their advantages and limitations, and how they compare to and complement one another. Finally, we present current applications and future directions for these methods in biological research and medical genetics.