Global Lipid Research Articles

Loss of peroxiredoxin 6 (PRDX6) alters lipid composition and distribution resulting in increased sensitivity to ferroptosis.

Peroxiredoxin 6 (PRDX6) is a multifunctional enzyme involved in phospholipid peroxide repair and metabolism. In this study we investigated the global lipid composition of a human hepatocarcinoma cell line SNU475 lacking PRDX6 and lipid related cellular processes. There was a general decrease in multiple lipids species upon loss of PRDX6, in particular sphingomyelins and acylcarnitines, consistent with previously observed alterations in cell signaling pathways and mitochondrial dysfunction. Deprivation of docosahexaenoic acid and related species was also evident. However, a few striking exceptions are worth highlighting: 1) Three specific arachidonic acid (AA) containing phophatidylcholines (PC) increased significantly. The increase of sn1-stearic/sn2-PUFA containing PC and sn2-AA containing plasmenyls are indicative of a preference of PRDX6 iPLA2 activity for these AA storage glycerophospholipids. 2) Several polyunsaturated fatty acids (PUFA) and PUFA containing triacylglycerols accumulated together with increased formation of lipid droplets, an indication of altered FA flux and PUFA sequestration in PRDX6 knockout cells. Loss of PRDX6 resulted in increased sensitivity to erastin-induced ferroptosis, independent of selenium and GPX4, as a consequence of increased levels of lipid hydroperoxides, that reverted to normal levels upon rescue with PRDX6. <SPAN style="font-weight: 400;">The results presented demonstrate that all three enzymatic activities of PRDX6 contribute to the role of this multifunctional enzyme in diverse cellular processes, including membrane phospholipid remodeling and glycerophospholipid functional diversity, resulting in altered lipid peroxides and modulation of AA disposition and traffic. These contributions highlight the complexity of the changes that loss of PRDX6 exerts on cell functionality.</SPAN>.

Polyamines mediate cellular energetics and lipid metabolism through mitochondrial respiration to facilitate virus replication.

Polyamines are critical cellular components that regulate a variety of processes, including translation, cell cycling, and nucleic acid metabolism. The polyamines, putrescine, spermidine, and spermine, are found abundantly within cells and are positively-charged at physiological pH. Polyamine metabolism is connected to distinct other metabolic pathways, including nucleotide and amino acid metabolism. However, the breadth of the effect of polyamines on cellular metabolism remains to be fully understood. We recently demonstrated a role for polyamines in cholesterol metabolism, and following these studies, we measured the impact of polyamines on global lipid metabolism. We find that lipid droplets increase in number and size with polyamine depletion. We further demonstrate that lipid anabolism is markedly decreased, and lipid accumulation is due to reduced mitochondrial fatty acid oxidation. In fact, mitochondrial structure and function are largely ablated with polyamine depletion. To compensate, cells depleted of polyamines switch from aerobic respiration to glycolysis in a polyamine depletion-mediated Warburg-like effect. Finally, we show that inhibitors of lipid metabolism are broadly antiviral, suggesting that polyamines and lipids are promising antiviral targets. Together, these data demonstrate a novel role for polyamines in mitochondrial function, lipid metabolism, and cellular energetics.

Random Forest Analysis of Out-of-Pocket Health Expenditures Associated with Cardiometabolic Diseases, Lifestyle, Lipid Profile, and Genetic Information in São Paulo, Brazil.

Background/Objectives: There is a lack of empirical studies of out-of-pocket health expenditures associated with dyslipidemias, which are major cardiovascular risk factors, especially in underrepresented admixed populations. The study investigates associations of health costs with lipid traits, GWAS-derived genetic risk scores (GRSs), and other cardiometabolic risk factors. Methods: Data from the observational cross-sectional 2015 ISA-Nutrition comprised lifestyle, environmental factors, socioeconomic and demographic variables, and biochemical and genetic markers related to the occurrence of cardiometabolic diseases. GWAS-derived genetic risk scores were estimated from SNPs previously associated with lipid traits. There was phenotypic and genetic information available for 490 independent individuals, which was used as inputs for random forests and logistic regression to explain private quantitative and categorical health costs. Results: There were significant correlations between GRSs and their respective lipid phenotypes. The main relevant variables across techniques and outcome variables comprised income per capita, principal components of ancestry, diet quality, global physical activity, inflammatory and lipid markers, and LDL-c GRS and non-HDL-c GRS. The area under the ROC curve (AUC) of quartile-based categorical health expenditure without GRSs was 0.76. GRSs were not significant for this categorical outcome. Conclusions: We present an original contribution to the investigation of determinants of private health expenditures in a highly admixed population, providing insights on associations between genetic and socioeconomic dimensions of health in Brazil. Ancestry information was also among the main factors contributing to health expenses, providing a novel view of the role of genetic ancestry on cardiometabolic risk factors and its potential impact on health costs.

Proteome-wide association studies for blood lipids and comparison with transcriptome-wide association studies

Blood lipid traits are treatable and heritable risk factors for heart disease, a leading cause of mortality worldwide. Although genome-wide association studies (GWASs) have discovered hundreds of variants associated with lipids in humans, most of the causal mechanisms of lipids remain unknown. To better understand the biological processes underlying lipid metabolism, we investigated the associations of plasma protein levels with total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol in blood. We trained protein prediction models based on samples in the Multi-Ethnic Study of Atherosclerosis (MESA) and applied them to conduct proteome-wide association studies (PWASs) for lipids using the Global Lipids Genetics Consortium (GLGC) data. Of the 749 proteins tested, 42 were significantly associated with at least one lipid trait. Furthermore, we performed transcriptome-wide association studies (TWASs) for lipids using 9,714 gene expression prediction models trained on samples from peripheral blood mononuclear cells (PBMCs) in MESA and 49 tissues in the Genotype-Tissue Expression (GTEx) project. We found that although PWASs and TWASs can show different directions of associations in an individual gene, 40 out of 49 tissues showed a positive correlation between PWAS and TWAS signed p values across all the genes, which suggests high-level consistency between proteome-lipid associations and transcriptome-lipid associations.

A global lipid map of severe fever with thrombocytopenia syndrome virus infection reveals glycerophospholipids as novel prognosis biomarkers.

This study systematically investigated the lipid landscape profile of SFTS-infected patients with different clinical outcomes. Our results revealed a global alteration in the lipid signature, particularly the glycerophospholipid metabolic pathway, induced by SFTSV infection. Notably, LysoPC (20:0) and LysoPC (P-16:0) presented remarkable prognostic value as novel biomarkers for SFTSV infection and may contribute to the prognosis of SFTS progression and appropriate interventions.

Association between lipid-lowering agents with intervertebral disc degeneration, sciatica and low back pain: a drug-targeted mendelian randomized study and cross-sectional observation

BackgroundAbnormal lipid metabolism is linked to intervertebral disc degeneration (IVDD), sciatica, and low back pain (LBP), but it remains unclear whether targeted interventions can prevent these issues. This study investigated the causal effects of lipid-lowering drug use on IVDD, sciatica, and LBP development.MethodsSingle-nucleotide polymorphisms (SNPs) linked to total cholesterol (TC), low-density-lipoprotein cholesterol (LDL-C), and non-high-density-lipoprotein cholesterol (non-HDL-C) were obtained from the Global Lipids Genetics Consortium’s genome-wide association study (GWAS). Genes near HMGCR, PCSK9, and NPC1L1 were selected to represent therapeutic inhibition targets. Using Mendelian randomization (MR) focusing on these drug targets, we identified causal effects of PCSK9, HMGCR, and NPC1L1 on the risk of developing IVDD, sciatica, and LBP, with coronary heart disease risk serving as a positive control. Using summary data from Mendelian randomization (SMR) analysis, we evaluated potential therapeutic targets for IVDD, sciatica, and LBP through protein quantitative trait loci (pQTL). The genetic associations with IVDD, sciatica, LBP, and coronary heart disease were derived from FinnGen (discovery) and UK Biobank (replication). Additionally, a cross-sectional observational study was performed using data from the National Health and Nutrition Examination Survey (NHANES) to further investigate the connection between LBP and statin use, with a sample size of 4343 participants. Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were calculated to assess the outcomes.ResultsThe NHANES-based cross-sectional study indicated that non-statin use was associated with an increased risk of developing LBP (OR = 1.29, 95% CI [1.04, 1.59], P = 0.019). Moreover, Inverse-variance weighting (IVW) analysis revealed that NPC1L1-mediated reductions in TC, LDL-C, and non-HDL-C concentrations were associated with a decreased risk of developing IVDD (P = 9.956E-03; P = 3.516E-02; P = 1.253E-04). Similarly, PCSK9-mediated reductions in LDL-C and TC concentrations were linked to a lower risk of developing sciatica (P = 3.825E-02; P = 2.709E-02). Sensitivity analysis confirmed the stability and reliability of the MR results. MST1 (macrophage stimulating 1) levels was inversely associated with IVDD, sciatica, and LBP risks.ConclusionThe results of cross-sectional study suggested that non-use of statins was positively correlated with LBP. The results of Mendelian randomization study suggest that NPC1L1 could lower the risk of developing IVDD by reducing TC, LDL-C, and non-HDL-C levels. Additionally, PCSK9 may reduce the risk of developing sciatica by lowering LDL-C and TC levels. In contrast, HMGCR appears to have no significant effect on IVDD, sciatica, or LBP development. Nonetheless, further research is needed to verify these preliminary results. MST1 warrants further exploration as a potential therapeutic target. It is necessary to do further research to validate these findings.

Genetic Associations of Lipids and Lipid-Modifying Drug Targets With Type 2 Diabetes in the Chinese Population

BackgroundDyslipidemia is a recognized risk factor for type 2 diabetes (T2D), yet the genetic basis and causal nature remain unclear, particularly in Chinese populations. ObjectivesThe authors investigated the causal effects of genetically predicted lipid levels on T2D risk and explored the potential effects of lipid-modifying drugs. MethodsLeveraging data from the Kunshan Community cohort in China, we analyzed the associations between low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides (TGs) with T2D risk using genetic risk scores, 1-sample univariable, multivariable, and nonlinear Mendelian randomization (MR) analyses. Two-sample MR using summary-level data from Global Lipid Genetics Consortium and Biobank Japan was used for validation. Drug-target MR was used to examine the impact of lipid-modifying drug targets on T2D. ResultsLower genetic risk scores of LDL-C (OR per SD: 0.97 [95% CI: 0.95-0.99]; P = 0.010) and TGs (0.96 [95%CI: 0.94-0.98]; P = 0.002) were associated with increased T2D risk. Univariable MR revealed that genetically predicted lower LDL-C (0.78 [95% CI: 0.65-0.93]; P = 0.006) and TG levels (0.76 [95% CI: 0.66-0.89]; P < 0.001) were linked to a higher T2D risk, validated by 2-sample MR. Multivariable MR demonstrated a direct inverse association between LDL-C (0.80 [95% CI: 0.66-0.97]; P = 0.020) and TG (0.80 [95% CI: 0.66-0.97]; P = 0.022) with T2D. No evidence was found for nonlinearity. Among lipid-modifying drugs, genetic mimicry of apolipoprotein C3 (APOC3) inhibition increased T2D risk (OR per 1 mmol/L reduction in TG: 1.38 [95% CI: 1.10-1.75]; P = 0.007). ConclusionsOur findings suggested potential adverse effects of lower LDL-C, TG levels, as well as long-term use of APOC3 inhibitors on T2D risk in Chinese populations. These findings highlight the need for cautious lipid management strategies in T2D prevention.

Lipids, lipid-lowering drugs and lateral epicondylitis of the humerus: a drug-targeted Mendelian randomization study.

Clinical observations indicate that blood lipids may be risk factors for lateral epicondylitis (LE) of the humerus, and lipid-lowering drugs are also used for the prevention and treatment of tendon diseases, but these lack high-quality clinical trial evidence and remain inconclusive. Mendelian randomization (MR) analyses can overcome biases in traditional observational studies and offer more accurate inference of causal relationships. Therefore, we employed this approach to investigate whether blood lipids are risk factors for LE and if lipid-lowering drugs can prevent it. Genetic variations associated with lipid traits, including low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), and total cholesterol (TC), were obtained from the UK Biobank and the Global Lipids Genetics Consortium (GLGC). Data on genetic variation in LE were sourced from FinnGen, including 24,061 patients and 275,212 controls. Subsequently, MR analyses were conducted to assess the potential correlation between lipid traits and LE. Additionally, drug-target Mendelian randomization analyses were performed on 10 drug targets relevant to LE. For those drug targets that yielded significant results, further analysis was conducted using colocalization techniques. No correlation was found between three blood lipid traits and LE. Lipoprotein lipase (LPL) enhancement is significantly associated with a decreased risk of LE (OR = 0.76, [95% CI, 0.65-0.90], p = 0.001). The expression of LPL in the blood is associated with LE and shares a single causal variant (12.07%), greatly exceeding the probability of different causal variations (1.93%), with a colocalization probability of 86.2%. The three lipid traits are not risk factors for lateral epicondylitis. LPL is a potential drug target for the prevention and treatment of LE.

Effects of ACLY Inhibition on Body Weight Distribution: A Drug Target Mendelian Randomization Study.

Background: Adenosine triphosphate-citrate lyase (ACLY) inhibition has proven clinically efficacious for low-density lipoprotein cholesterol (LDL-c) lowering and cardiovascular disease (CVD) risk reduction. Clinical and genetic evidence suggests that some LDL-c lowering strategies, such as 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) inhibition with statin therapy increase body weight and the risk of developing type 2 diabetes mellitus (T2DM). However, whether ACLY inhibition affects metabolic risk factors is currently unknown. We aimed to investigate the effects of ACLY inhibition on glycaemic and anthropometric traits using Mendelian randomization (MR). Methods: As genetic instruments for ACLY inhibition, we selected weakly correlated single-nucleotide polymorphisms at the ACLY gene associated with lower ACLY gene expression in the eQTLGen study (N = 31,684) and lower LDL-c levels in the Global Lipid Genetic Consortium study (N = 1.65 million). Two-sample Mendelian randomization was employed to investigate the effects of ACLY inhibition on T2DM risk, and glycaemic and anthropometric traits using summary data from large consortia, with sample sizes ranging from 151,013 to 806,834 individuals. Findings for genetically predicted ACLY inhibition were compared to those obtained for genetically predicted HMGCR inhibition using the same instrument selection strategy and outcome data. Results: Primary MR analyses showed that genetically predicted ACLY inhibition was associated with lower waist-to-hip ratio (β per 1 standard deviation lower LDL-c: -1.17; 95% confidence interval (CI): -1.61 to -0.73; p < 0.001) but not with risk of T2DM (odds ratio (OR) per standard deviation lower LDL-c: 0.74, 95% CI = 0.25 to 2.19, p = 0.59). In contrast, genetically predicted HMGCR inhibition was associated with higher waist-to-hip ratio (β = 0.15; 95%CI = 0.04 to 0.26; p = 0.008) and T2DM risk (OR = 1.73, 95% CI = 1.27 to 2.36, p < 0.001). The MR analyses considering secondary outcomes showed that genetically predicted ACLY inhibition was associated with a lower waist-to-hip ratio adjusted for body mass index (BMI) (β = -1.41; 95%CI = -1.81 to -1.02; p < 0.001). In contrast, genetically predicted HMGCR inhibition was associated with higher HbA1c (β = 0.19; 95%CI = 0.23 to 0.49; p < 0.001) and BMI (β = 0.36; 95%CI = 0.23 to 0.49; p < 0.001). Conclusions: Human genetic evidence supports the metabolically favourable effects of ACLY inhibition on body weight distribution, in contrast to HMGCR inhibition. These findings should be used to guide and prioritize ongoing clinical development efforts.

Fast and scalable ensemble learning method for versatile polygenic risk prediction

Polygenic risk scores (PRS) enhance population risk stratification and advance personalized medicine, but existing methods face several limitations, encompassing issues related to computational burden, predictive accuracy, and adaptability to a wide range of genetic architectures. To address these issues, we propose Aggregated L0Learn using Summary-level data (ALL-Sum), a fast and scalable ensemble learning method for computing PRS using summary statistics from genome-wide association studies (GWAS). ALL-Sum leverages a L0L2 penalized regression and ensemble learning across tuning parameters to flexibly model traits with diverse genetic architectures. In extensive large-scale simulations across a wide range of polygenicity and GWAS sample sizes, ALL-Sum consistently outperformed popular alternative methods in terms of prediction accuracy, runtime, and memory usage by 10%, 20-fold, and threefold, respectively, and demonstrated robustness to diverse genetic architectures. We validated the performance of ALL-Sum in real data analysis of 11 complex traits using GWAS summary statistics from nine data sources, including the Global Lipids Genetics Consortium, Breast Cancer Association Consortium, and FinnGen Biobank, with validation in the UK Biobank. Our results show that on average, ALL-Sum obtained PRS with 25% higher accuracy on average, with 15 times faster computation and half the memory than the current state-of-the-art methods, and had robust performance across a wide range of traits and diseases. Furthermore, our method demonstrates stable prediction when using linkage disequilibrium computed from different data sources. ALL-Sum is available as a user-friendly R software package with publicly available reference data for streamlined analysis.

Genetic association of lipid and lipid-lowering drug target genes with atopic dermatitis: a drug target Mendelian randomization study

Observational studies suggest dyslipidemia as an atopic dermatitis (AD) risk factor and posit that lipid-lowering drugs may influence AD risk, but the causal link remains elusive. Mendelian randomization was applied to elucidate the causal role of serum lipids in AD and assess the therapeutic potential of lipid-lowering drug targets. Genetic variants related to serum lipid traits and lipid-lowering drug targets were sourced from the Global Lipid Genetics Consortium GWAS data. Comprehensive AD data were collated from the UK Biobank, FinnGen, and Biobank Japan. Colocalization, Summary-data-based Mendelian Randomization (SMR), and mediation analyses were utilized to validate the results and pinpoint potential mediators. Among assessed targets, only Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) was significantly linked to a reduced AD risk, corroborated across three separate AD cohorts. No association between serum lipid concentrations or other lipid-lowering drug targets and diminished AD risk was observed. Mediation analysis revealed that beta nerve growth factor (b-NGF) might mediate approximately 12.8% of PCSK9's influence on AD susceptibility. Our findings refute dyslipidemia's role in AD pathogenesis. Among explored lipid-lowering drug targets, PCSK9 stands out as a promising therapeutic agent for AD.

PCSK9 Inhibitors and the Risk of Vitiligo: A Mendelian Randomization Study

Lipid-lowering agents have been suggested as a therapeutic option for vitiligo based on the potential pathogenic role of lipid metabolism abnormalities. We aimed to explore the impact of genetically proxied lipid-lowering agents on the risk of vitiligo and potentially associated mediators.Genome-wide association study summary statistics for European ancestry were extracted from the largest available meta-analysis for vitiligo, the Global Lipids Genetics Consortium for seven lipid profiles, and two large biobanks, UKB and deCODE, for 4,719 proteins. After identifying lipid-lowering agents with genetically proxied protective effects against vitiligo using lipid-lowering and protein-inhibition Mendelian randomization (MR) analyses, multivariable and two-step MR analyses were conducted to identify potential mediators between lipid-lowering agents and vitiligo.Lipid-lowering MR indicated a potential role of PCSK9 in reducing the vitiligo risk (OR[95%CI] = 0.71[0.52-0.95]), which was replicated in PCSK9-inhibition MR analyses across two separate biobanks (UKB: OR[95%CI]=0.82[0.71-0.96]; deCODE: OR[95%CI]=0.78[0.67-0.91]). Multivariable MR suggested that well-known lipid profiles do not mediate the relationship between PCSK9 and vitiligo, while two-step MR analyses identified five potential protein mediators (CCN5, CXCL12, FCRL1, LGMN, and FGF2).Hence, PCSK9 inhibitor may attenuate the vitiligo risk; PCSK9 and the potential protein mediators can serve as promising novel therapeutic targets for its effective treatment.

Lipidomics in Plants Under Abiotic Stress Conditions: An Overview

Lipids are ubiquitous macromolecules that play essential roles in several metabolic processes in plants, such as primary and secondary metabolism, energy storage, and lipid signaling, also being major constituents of membranes. Considering their importance, lipid contents, proportion, and composition are widely modulated in response to environmental conditions, which is even more important under unfavorable conditions such as abiotic stresses. In recent years, technological advances have allowed for the analysis of the global lipid profile, also known as lipidomics, which has emerged as a powerful tool for the comprehensive analysis of the modulation and roles of lipids under different conditions. This review provides a current overview of plant lipidomics research, covering the different lipid classes found in plants, analytical techniques, and the main lipid-related responses under temperature, water, salt, alkali, heavy metal, nutrient deficiency, light, and oxidative stress.

Impact of the Deletion of Genes of the Nitrogen Metabolism on Triacylglycerol, Cardiolipin and Actinorhodin Biosynthesis in Streptomyces coelicolor.

Since nitrogen limitation is known to be an important trigger of triacylglycerol (TAG) accumulation in most microorganisms, we first assessed the global lipid content of 21 strains derived from Streptomyces coelicolor M145 deleted for genes involved in nitrogen metabolism. Seven of these strains deleted for genes encoding proteins involved in polyamine (GlnA2/SCO2241, GlnA3/SCO6962, GlnA4/SCO1613), or protein (Pup/SCO1646) degradation, in the regulation of nitrogen metabolism (GlnE/SCO2234 and GlnK/SCO5584), or the global regulator DasR/SCO5231 that controls negatively the degradation of N-acetylglucosamine, a constituent of peptidoglycan, had a higher TAG content than the original strain, whereas five of these strains (except the glnA2 and pup mutants) had a lower cardiolipin (CL) content. The production of the blue polyketide actinorhodin (ACT) was totally abolished in the dasR mutant in both Pi conditions, whereas the deletion of pup, glnA2, glnA3, and glnA4 was correlated with a significant increase in total ACT production, but mainly in Pi limitation. Unexpectedly, ACT production was strongly reduced in the glnA3 mutant in Pi proficiency. Altogether, our data suggest that high TAG and ACT biosynthesis and low CL biosynthesis might all contribute to the lowering of oxidative stress resulting from nitrogen limitation or from other causes.

Association of lipid-lowering drugs with risk of sarcopenia: a drug target mendelian randomization study and meta-analysis

BackgroundLipid-lowering drugs are widely used among the elderly, with some studies suggesting links to muscle-related symptoms. However, the causality remains uncertain.MethodsUsing the Mendelian randomization (MR) approach, we assessed the causal effects of genetically proxied reduced low-density lipoprotein cholesterol (LDL-C) through inhibitions of hydroxy-methyl-glutaryl-CoA reductase (HMGCR), proprotein convertase subtilisin/kexin type 9 (PCSK9), and Niemann-Pick C1-like 1 (NPC1L1) on sarcopenia-related traits, including low hand grip strength, appendicular lean mass, and usual walking pace. A meta-analysis was conducted to combine the causal estimates from different consortiums.ResultsUsing LDL-C pooled data predominantly from UK Biobank, genetically proxied inhibition of HMGCR was associated with higher appendicular lean mass (beta = 0.087, P = 7.56 × 10− 5) and slower walking pace (OR = 0.918, P = 6.06 × 10− 9). In contrast, inhibition of PCSK9 may reduce appendicular lean mass (beta = -0.050, P = 1.40 × 10− 3), while inhibition of NPC1L1 showed no causal impact on sarcopenia-related traits. These results were validated using LDL-C data from Global Lipids Genetics Consortium, indicating that HMGCR inhibition may increase appendicular lean mass (beta = 0.066, P = 2.17 × 10− 3) and decelerate walking pace (OR = 0.932, P = 1.43 × 10− 6), whereas PCSK9 inhibition could decrease appendicular lean mass (beta = -0.048, P = 1.69 × 10− 6). Meta-analysis further supported the robustness of these causal associations.ConclusionsGenetically proxied HMGCR inhibition may increase muscle mass but compromise muscle function, PCSK9 inhibition could result in reduced muscle mass, while NPC1L1 inhibition is not associated with sarcopenia-related traits and this class of drugs may serve as viable alternatives to sarcopenia individuals or those at an elevated risk.

Identification of lipid-modifying drug targets for autoimmune diseases: insights from drug target mendelian randomization

BackgroundsA growing body of evidence has highlighted the interactions of lipids metabolism and immune regulation. Nevertheless, there is still a lack of evidence regarding the causality between lipids and autoimmune diseases (ADs), as well as their possibility as drug targets for ADs.ObjectivesThis study was conducted to comprehensively understand the casual associations between lipid traits and ADs, and evaluate the therapeutic possibility of lipid-lowering drug targets on ADs.MethodsGenetic variants for lipid traits and variants encoding targets of various lipid-lowering drugs were derived from Global Lipid Genetics Consortium (GLGC) and verified in Drug Bank. Summary data of ADs were obtained from MRC Integrative Epidemiology Unit (MER-IEU) database and FinnGen consortium, respectively. The causal inferences between lipid traits/genetic agents of lipid-lowering targets and ADs were evaluated by Mendelian randomization (MR), summary data-based MR (SMR), and multivariable MR (MVMR) analyses. Enrichment analysis and protein interaction network were employed to reveal the functional characteristics and biological relevance of potential therapeutic lipid-lowering targets.ResultsThere was no evidence of causal effects regarding 5 lipid traits and 9 lipid-lowering drug targets on ADs. Genetically proxied 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) inhibition was associated with a reduced risk of rheumatoid arthritis (RA) in both discovery (OR [odds ratio] = 0.45, 95%CI: 0.32, 0.63, P = 6.79 × 10− 06) and replicate datasets (OR = 0.37, 95%CI: 0.23, 0.61, P = 7.81 × 10− 05). SMR analyses supported that genetically proxied HMGCR inhibition had causal effects on RA in whole blood (OR = 0.48, 95%CI: 0.29, 0.82, P = 6.86 × 10− 03) and skeletal muscle sites (OR = 0.75, 95%CI: 0.56, 0.99, P = 4.48 × 10− 02). After controlling for blood pressure, body mass index (BMI), smoking and drinking alchohol, HMGCR suppression showed a direct causal effect on a lower risk of RA (OR = 0.33, 95%CI: 0.40, 0.96, P = 0.042).ConclusionsOur study reveals causal links of genetically proxied HMGCR inhibition (lipid-lowering drug targets) and HMGCR expression inhibition with a decreased risk of RA, suggesting that HMGCR may serve as candidate drug targets for the treatment and prevention of RA.

Repurposing lipid-lowering drugs as potential treatment for acne vulgaris: a Mendelian randomization study.

Acne vulgaris, a chronic inflammatory skin condition predominantly seen in teenagers, impacts more than 640 million people worldwide. The potential use of lipid-lowering medications as a treatment for acne vulgaris remains underexplored. This study seeks to investigate the impact of lipid-lowering therapies on the risk of developing acne vulgaris using two-sample Mendelian randomization (MR) analysis. The two-sample MR method was employed for analysis, and information on lipid-lowering drugs was obtained from the DrugBank and ChEMBL databases. The summary data for blood low-density lipoprotein (LDL) and triglycerides were sourced from the Global Lipids Genetics Consortium, while genome-wide association studies (GWAS) summary data for acne vulgaris were obtained from the FinnGen database. Heterogeneity was examined using the Q-test, horizontal pleiotropy was assessed using MR-Presso, and the robustness of analysis results was evaluated using leave-one-out analysis. The MR analysis provided robust evidence for an association between lowering LDL cholesterol through two drug targets and acne vulgaris, with PCSK9 showing an odds ratio (OR) of 1.782 (95%CI: 1.129-2.812, p = 0.013) and LDL receptor (LDLR) with an OR of 1.581 (95%CI: 1.071-2.334, p = 0.021). Similarly, targeting the lowering of triglycerides through lipoprotein lipase (LPL) was significantly associated with an increased risk of acne vulgaris, indicated by an OR of 1.607 (95%CI: 1.124-2.299, p = 0.009). The current MR study presented suggestive evidence of a positive association between drugs targeting three genes (PCSK9, LDLR, and LPL) to lower lipids and a reduced risk of acne vulgaris.

A causal association between lipid-lowering medications and rotator cuff syndrome: a drug-targeted mendelian randomization study.

Background: Previous research has suggested that dyslipidemia may be a risk factor for rotator cuff syndrome (RCS), and lipid-lowering drugs may aid in its treatment, though conclusions have not been definitive. Mendelian randomization is a statistical method that explores the causal relationships between exposure factors and diseases. It overcomes the confounding issues inherent in traditional observational studies, thereby providing more reliable causal inferences. We employed this method to investigate whether hyperlipidemia is a risk factor for rotator cuff syndrome and whether lipid-lowering drugs can effectively treat this condition. Methods: Genetic variations linked to lipid traits low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), and total cholesterol (TC) were acquired from the UK Biobank and the Global Lipids Genetics Consortium (GLGC). Data on genetic variation in rotator cuff syndrome were obtained from FinnGen, including 24,061 patients and 275,212 controls. In the next step, we carried out two-sample Mendelian randomization analyses to determine whether lipid traits correlate with rotator cuff syndrome risk. Additionally, we performed drug-target Mendelian randomization (MR) analyses on 10 drug targets related to rotator cuff syndrome. For the drug targets that showed significant results, further analysis was done using Summary-data-based Mendelian Randomization (SMR) and colocalization techniques. We performed a mediation analysis to identify potential mediators between HMG-CoA reductase (HMGCR) and RCS. Results: No causative link was established between these lipid traits and rotator cuff syndrome. However, a significant association has been identified where HMGCR inhibition corresponds to a reduced risk of rotator cuff disease (OR = 0.68, [95% CI, 0.56-0.83], p = 1.510 × 10-4). Additionally, enhanced expression of HMGCR in muscle tissues is also linked to a decreased risk of rotator cuff syndrome (OR = 0.88, [95% CI, 0.76-0.99], p = 0.03). Body mass index (BMI) mediated 22.97% of the total effect of HMGCR on RCS. Conclusion: This study does not support low-density LDL-C, TG, and TC as risk factors for rotator cuff syndrome. HMGCR represents a potential pharmaceutical target for preventing and treating rotator cuff syndrome. The protective action of statins on the rotator cuff syndrome might not be associated with their lipid-lowering properties.

Effects of genetically proxied lipid-lowering drugs on acute myocardial infarction: a drug-target mendelian randomization study

ObjectiveHigh low-density-lipoprotein (LDL) cholesterol has been associated with an increased risk of coronary artery diseases (CAD) including acute myocardial infarction (AMI). However, whether lipids lowering drug treatment is causally associated with decreased risk of AMI remains largely unknown. We used Mendelian randomization (MR) to evaluate the influence of genetic variation affecting the function of lipid-lowering drug targets on AMI.MethodsSingle-nucleotide polymorphisms (SNPs) associated with lipids as instruments were extracted from the Global Lipids Genetics Consortium (GLGC). The genome-wide association study (GWAS) data for AMI were obtained from UK Biobank. Two sample MR analysis was used to study the associations between high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and triglycerides (TG) with AMI (n = 3,927). Genetic variants associated with LDL cholesterol at or near drug target gene were used to mimic drug effects on the AMI events in drug target MR.ResultsGenetically predicted higher LDL-C (per one SD increase in LDL-C of 38.67 mg/dL, OR 1.006, 95% CI 1.004–1.007) and TG (per one SD increase in TG of 90.72 mg/dL, 1.004, 1.002–1.006) was associated with increased risk of AMI, but decreased risk for higher HDL-C (per one SD increase in HDL-C of 15.51 mg/dL, 0.997, 0.995–0.999) in univariable MR. Association remained significant for LDL-C, but attenuated toward the null for HDL-C and TG in multivariable MR. Genetically proxied lower LDL-C with genetic variants at or near the PCSK9 region (drug target of evolocumab) and NPC1L1 (drug target of ezetimibe) were associated with decreased risk of AMI (0.997, 0.994–0.999 and 0.986, 0.975–0.998, respectively), whereas genetic variants at HMGCR region (drug target of statin) showed marginal association with AMI (0.995, 0.990-1.000). After excluding drug target-related SNPs, LDL-C related SNPs outside the drug target region remained a causal effect on AMI (0.994, 0.993–0.996).ConclusionsThe findings suggest that genetically predicted LDL-C may play a predominant role in the development of AMI. The drug MR results imply that ezetimibe and evolocumab may decrease the risk of AMI due to their LDL-C lowering effect, and there are other non-drug related lipid lowering pathways that may be causally linked to AMI.

Statins inhibit paclitaxel-induced PD-L1 expression and increase CD8+ T cytotoxicity for better prognosis in breast cancer.

In recent years, the widespread use of lipid-lowering drugs, especially statins, has attracted people's attention. Statin use may be potentially associated with a reduced risk of breast cancer. To explore the relationship between statin use and cancer risk. And further explore the potential role of statins in the adjuvant treatment of breast cancer. Data for the Mendelian randomization portion of the study were obtained from genome-wide association studies of common cancers in the UK Biobank and FinnGen studies and from the Global Lipid Genetics Consortium's low density lipoprotein (LDL). In addition, the impacts of statins and chemotherapy drugs on breast cancer were examined using both in vitro and in vivo models, with particular attention to the expression levels of the immune checkpoint protein PD-L1 and its potential to suppress tumor growth. Data from about 3.8 million cancer patients and ~1.3 million LDL-measuring individuals were analyzed. Genetically proxied HMGCR inhibition (statins) was associated with breast cancer risk reduction (P=0.0005). In vitro experiments showed that lovastatin significantly inhibited paclitaxel-induced PD-L1 expression and assisted paclitaxel in suppressing tumor cell growth. Furthermore, the combination therapy involving lovastatin and paclitaxel amplified CD8+ T-cell infiltration, bolstering their tumor-killing capacity and enhancing in vivo efficacy. The utilization of statins is correlated with improved prognoses for breast cancer patients and may play a role in facilitating the transition from cold to hot tumors. Combination therapy with lovastatin and paclitaxel enhances CD8+ T-cell activity and leads to better prognostic characteristics.