Inferring causal direction between two traits using R2 with application to transcriptome-wide association studies.

In Mendelian randomization, two single SNP-trait correlation-based methods have been developed to infer the causal direction between an exposure (e.g., a gene) and an outcome (e.g., a trait), called MR Steiger's method and its recent extension called Causal Direction-Ratio (CD-Ratio). Here we propose an approach based on R2, the coefficient of determination, to combine information from multiple (possibly correlated) SNPs to simultaneously infer the presence and direction of a causal relationship between an exposure and an outcome. Our proposed method generalizes Steiger's method from using a single SNP to multiple SNPs as IVs. It is especially useful in transcriptome-wide association studies (TWASs) (and similar applications) with typically small sample sizes for gene expression (or another molecular trait) data, providing a more flexible and powerful approach to inferring causal directions. It can be applied to GWAS summary data with a reference panel. We also discuss the influence of invalid IVs and introduce a new approach called R2S to select and remove invalid IVs (if any) to enhance the robustness. We compared the performance of the proposed method with existing methods in simulations to demonstrate its advantages. We applied the methods to identify causal genes for high/low-density lipoprotein cholesterol (HDL/LDL) using the individual-level GTEx gene expression data and UK Biobank GWAS data. The proposed method was able to confirm some well-known causal genes while identifying some novel ones. Additionally, we illustrated an application of the proposed method to GWAS summary to infer causal relationships between HDL/LDL and stroke/coronary artery disease (CAD).

Correlation-based tests for the formal comparison of polygenic scores in multiple populations.

Polygenic scores (PGS) are measures of genetic risk, derived from the results of genome wide association studies (GWAS). Previous work has proposed the coefficient of determination (R2) as an appropriate measure by which to compare PGS performance in a validation dataset. Here we propose correlation-based methods for evaluating PGS performance by adapting previous work which produced a statistical framework and robust test statistics for the comparison of multiple correlation measures in multiple populations. This flexible framework can be extended to a wider variety of hypothesis tests than currently available methods. We assess our proposed method in simulation and demonstrate its utility with two examples, assessing previously developed PGS for low-density lipoprotein cholesterol and height in multiple populations in the All of Us cohort. Finally, we provide an R package 'coranova' with both parametric and nonparametric implementations of the described methods.

Co-methylation analyses identify CpGs associated with lipid traits in Chinese discordant monozygotic twins.

To control genetic background and early life milieu in genome-wide DNA methylation analysis for blood lipids, we recruited Chinese discordant monozygotic twins to explore the relationships between DNA methylations and total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). 132 monozygotic (MZ) twins were included with discordant lipid levels and completed data. A linear mixed model was conducted in Epigenome-wide association study (EWAS). Generalized estimating equation model was for gene expression analysis. We conducted Weighted correlation network analysis (WGCNA) to build co-methylated interconnected network. Additional Qingdao citizens were recruited for validation. Inference about Causation through Examination of Familial Confounding (ICE FALCON) was used to infer the possible direction of these relationships. A total of 476 top CpGs reached suggestively significant level (P < 10-4), of which, 192 CpGs were significantly associated with TG (FDR < 0.05). They were used to build interconnected network and highlight crucial genes from WGCNA. Finally, four CpGs in GATA4 were validated as risk factors for TC; six CpGs at ITFG2-AS1 were negatively associated with TG; two CpGs in PLXND1 played protective roles in HDL-C. ICE FALCON indicated abnormal TC was regarded as the consequence of DNA methylation in CpGs at GATA4, rather than vice versa. Four CpGs in ITFG2-AS1 were both causes and consequences of modified TG levels. Our results indicated that DNA methylation levels of 12 CpGs in GATA4, ITFG2-AS1, and PLXND1 were relevant to TC, TG, and HDL-C, respectively, which might provide new epigenetic insights into potential clinical treatment of dyslipidemia.

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

BACKGROUND: Lipid-lowering drugs are widely used among the elderly, with some studies suggesting links to muscle-related symptoms. However, the causality remains uncertain. METHODS: Using 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. RESULTS: Using 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. CONCLUSIONS: Genetically 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.

Genetic testing for familial hypercholesterolemia.

PURPOSE OF REVIEW: Despite familial hypercholesterolemia (FH) being the most common genetic cause of cardiovascular disease (CVD), genetic testing is rarely utilized in the US. This review summarizes what is known about the clinical utility of genetic testing and its role in the diagnosis and screening of FH. RECENT FINDINGS: The presence of an FH-causative variant is associated with a substantially higher risk of CVD, even when low-density lipoprotein cholesterol (LDL-C) levels are only modestly elevated. Genetic testing can facilitate the identification of FH cases who may be missed by clinical diagnostic criteria, improve risk stratification beyond LDL-C and family history, guide treatment decisions, and improve treatment initiation and adherence. Genetic testing can be incorporated into FH screening and diagnosis algorithms, including cascade, targeted, and universal screening. Integrating genetic testing into cascade screening can enhance the effectiveness of the process. Several models of universal FH screening with coordinated genetic and lipid testing are feasible and effective. SUMMARY: More systematic integration of genetic testing into FH diagnosis and screening can significantly reduce the burden of this condition through early detection and treatment. Further pragmatic implementation studies are needed to determine how to more effectively and affordably integrate genetic testing into clinical lipid screening programs.

Unraveling the genetic background of individuals with a clinical familial hypercholesterolemia phenotype.

Familial hypercholesterolemia (FH) is a common genetic disorder of lipid metabolism caused by pathogenic/likely pathogenic variants in LDLR, APOB, and PCSK9 genes. Variants in FH-phenocopy genes (LDLRAP1, APOE, LIPA, ABCG5, and ABCG8), polygenic hypercholesterolemia, and hyperlipoprotein (a) [Lp(a)] can also mimic a clinical FH phenotype. We aim to present a new diagnostic tool to unravel the genetic background of clinical FH phenotype. Biochemical and genetic study was performed in 1,005 individuals with clinical diagnosis of FH, referred to the Portuguese FH Study. A next-generation sequencing panel, covering eight genes and eight SNPs to determine LDL-C polygenic risk score and LPA genetic score, was validated, and used in this study. FH was genetically confirmed in 417 index cases: 408 heterozygotes and 9 homozygotes. Cascade screening increased the identification to 1,000 FH individuals, including 11 homozygotes. FH-negative individuals (phenotype positive and genotype negative) have Lp(a) >50 mg/dl (30%), high polygenic risk score (16%), other monogenic lipid metabolism disorders (1%), and heterozygous pathogenic variants in FH-phenocopy genes (2%). Heterozygous variants of uncertain significance were identified in primary genes (12%) and phenocopy genes (7%). Overall, 42% of our cohort was genetically confirmed with FH. In the remaining individuals, other causes for high LDL-C were identified in 68%. Hyper-Lp(a) or polygenic hypercholesterolemia may be the cause of the clinical FH phenotype in almost half of FH-negative individuals. A small part has pathogenic variants in ABCG5/ABCG8 in heterozygosity that can cause hypercholesterolemia and should be further investigated. This extended next-generation sequencing panel identifies individuals with FH and FH-phenocopies, allowing to personalize each person's treatment according to the affected pathway.

Causal role of lipid metabolism in pulmonary alveolar proteinosis: an observational and mendelian randomisation study.

BACKGROUND: Pulmonary alveolar proteinosis (PAP) is a rare interstitial lung disease characterised by the accumulation of lipoprotein material in the alveoli. Although dyslipidaemia is a prominet feature, the causal effect of lipid traits on PAP remains unclear. This study aimed to explore the role of lipid traits in PAP and evaluate the potential of lipid-lowering drug targets in PAP. METHODS: Clinical outcomes, lipid profiles and lung function tests were analysed in a clinical cohort of diagnosed PAP patients and propensity score-matched healthy controls. Genome-wide association study data on PAP, lipid metabolism, blood cells and variants of genes encoding potential lipid-lowering drug targets were obtained for Mendelian randomisation (MR) and mediation analyses. FINDINGS: Observational results showed that higher levels of total cholesterol (TC), triglycerides and low-density lipoprotein (LDL) were associated with increased risks of PAP. Higher levels of TC and LDL were also associated with worse PAP severity. In MR analysis, elevated LDL was associated with an increased risk of PAP (OR: 4.32, 95% CI: 1.63 to 11.61, p=0.018). Elevated monocytes were associated with a lower risk of PAP (OR 0.34, 95% CI: 0.18 to 0.66, p=0.002) and mediated the risk impact of LDL on PAP. Genetic mimicry of PCSK9 inhibition was associated with a reduced risk of PAP (OR 0.03, p=0.007). INTERPRETATION: Our results support the crucial role of lipid and metabolism-related traits in PAP risk, emphasising the monocyte-mediated, causal effect of elevated LDL in PAP genetics. PCSK9 mediates the development of PAP by raising LDL. These finding provide evidence for lipid-related mechanisms and promising lipid-lowering drug target for PAP.

Genetic backgrounds and diagnosis of familial hypercholesterolemia.

Lipid disorders play a critical role in the intricate development of atherosclerosis and its clinical consequences, such as coronary heart disease and stroke. These disorders are responsible for a significant number of deaths in many adult populations worldwide. Familial hypercholesterolemia (FH) is a genetic disorder that causes extremely high levels of LDL cholesterol. The most common mutations occur in genes responsible for low-density lipoprotein receptor (LDLR), apolipoprotein B (APOB), or proprotein convertase subtilisin/kexin type 9 (PCSK9). While genetic testing is a dependable method for diagnosing the disease, it may not detect primary mutations in 20%-40% of FH cases.

Blood Lipid Metabolic Profiles and Causal Links to Site-Specific Cancer Risks: A Mendelian Randomization Study.

Observational and Mendelian randomization (MR) studies have established links between dyslipidemia and select cancer susceptibilities. However, there is a lack of comprehensive exploration of causal relationships spanning diverse cancer types. Here, we conducted a two-sample MR analysis to elucidate the causative connections between 9 blood lipid metabolic profiles (namely, adiponectin, leptin, lipoprotein A, apolipoprotein A1, apolipoprotein B, cholesterol, triglycerides, LDL-cholesterol, and HDL-cholesterol) and 21 site-specific cancer risks. Our findings reveal genetically predicted adiponectin levels to be associated with a reduced ovarian cancer risk, while genetically determined leptin increases bladder cancer risk but decreases prostate cancer risk. Lipoprotein A elevates risk of prostate cancer while diminishing risk of endometrial cancer, while apolipoprotein A1 heightens risks of breast and cervical cancers. Furthermore, elevated levels of cholesterol are positively correlated with kidney cancer, and triglycerides demonstrate a positive association with non-melanoma skin cancer but a negative association with breast cancer. Protective effects of genetically predicted LDL-cholesterol on endometrial cancer and adverse effects of HDL-cholesterol on breast cancer are also observed. Our study conclusively establishes that blood lipid metabolic profiles exert causal effects on cancer susceptibility, providing more robust evidence for cancer prevention and prompting contemplation regarding the future health of the human populace.

A regulatory element associated to NAFLD in the promoter of DIO1 controls LDL-C, HDL-C and triglycerides in hepatic cells.

BACKGROUND: Genome-wide association studies (GWAS) have identified genetic variants linked to fat metabolism and related traits, but rarely pinpoint causative variants. This limitation arises from GWAS not considering functional implications of noncoding variants that can affect transcription factor binding and potentially regulate gene expression. The aim of this study is to investigate a candidate noncoding functional variant within a genetic locus flagged by a GWAS SNP associated with non-alcoholic fatty liver disease (NAFLD), a condition characterized by liver fat accumulation in non-alcohol consumers. METHODS: CRISPR-Cas9 gene editing in HepG2 cells was used to modify the regulatory element containing the candidate functional variant linked to NAFLD. Global gene expression in mutant cells was assessed through RT-qPCR and targeted transcriptomics. A phenotypic assay measured lipid droplet accumulation in the CRISPR-Cas9 mutants. RESULTS: The candidate functional variant, rs2294510, closely linked to the NAFLD-associated GWAS SNP rs11206226, resided in a regulatory element within the DIO1 gene's promoter region. Altering this element resulted in changes in transcription factor binding sites and differential expression of candidate target genes like DIO1, TMEM59, DHCR24, and LDLRAD1, potentially influencing the NAFLD phenotype. Mutant HepG2 cells exhibited increased lipid accumulation, a hallmark of NAFLD, along with reduced LDL-C, HDL-C and elevated triglycerides. CONCLUSIONS: This comprehensive approach, that combines genome editing, transcriptomics, and phenotypic assays identified the DIO1 promoter region as a potential enhancer. Its activity could regulate multiple genes involved in the NAFLD phenotype or contribute to defining a polygenic risk score for enhanced risk assessment in NAFLD patients.

Novel loci linked to serum lipid traits are identified in a genome-wide association study of a highly admixed Brazilian population - the 2015 ISA Nutrition.

BACKGROUND: Cardiovascular diseases (CVDs) comprise major causes of death worldwide, leading to extensive burden on populations and societies. Alterations in normal lipid profiles, i.e., dyslipidemia, comprise important risk factors for CVDs. However, there is lack of comprehensive evidence on the genetic contribution to dyslipidemia in highly admixed populations. The identification of single nucleotide polymorphisms (SNPs) linked to blood lipid traits in the Brazilian population was based on genome-wide associations using data from the São Paulo Health Survey with Focus on Nutrition (ISA-Nutrition). METHODS: A total of 667 unrelated individuals had genetic information on 330,656 SNPs available, and were genotyped with Axiom™ 2.0 Precision Medicine Research Array. Genetic associations were tested at the 10- 5 significance level for the following phenotypes: low-density lipoprotein cholesterol (LDL-c), very low-density lipoprotein cholesterol (VLDL-c), high-density lipoprotein cholesterol (HDL-c), HDL-c/LDL-c ratio, triglycerides (TGL), total cholesterol, and non-HDL-c. RESULTS: There were 19 significantly different SNPs associated with lipid traits, the majority of which corresponding to intron variants, especially in the genes FAM81A, ZFHX3, PTPRD, and POMC. Three variants (rs1562012, rs16972039, and rs73401081) and two variants (rs8025871 and rs2161683) were associated with two and three phenotypes, respectively. Among the subtypes, non-HDL-c had the highest proportion of associated variants. CONCLUSIONS: The results of the present genome-wide association study offer new insights into the genetic structure underlying lipid traits in underrepresented populations with high ancestry admixture. The associations were robust across multiple lipid phenotypes, and some of the phenotypes were associated with two or three variants. In addition, some variants were present in genes that encode ncRNAs, raising important questions regarding their role in lipid metabolism.

Associations of ACE I/D and AGTR1 rs5182 polymorphisms with diabetes and their effects on lipids in an elderly Chinese population.

BACKGROUND: Diabetes mellitus is generally accompanied by dyslipidaemia, but inconsistent relationships between lipid profiles and diabetes are noted. Moreover, genetic variations in insertion/deletion (I/D) polymorphisms at angiotensin-converting enzyme gene (ACE) and T/C polymorphisms in the angiotensin type 1 receptor gene (AGTR1) are related to diabetes and lipid levels, but the associations are controversial. Thus, the current research aimed to explore the effects of ACE I/D, AGTR1 rs5182 and diabetes mellitus on serum lipid profiles in 385 Chinese participants with an average age of 75.01 years. METHODS: The ACE I/D variant was identified using the polymerase chain reaction (PCR) method, whereas the AGTR1 rs5182 polymorphism was identified using the PCR-based restriction fragment length polymorphism (PCR-RFLP) method and verified with DNA sequencing. Total cholesterol (TC), triglyceride (TG), apolipoprotein A (ApoA), apolipoprotein B (ApoB), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) levels were measured using routine methods, and the lipid ratios were calculated. RESULTS: ACE I/D, but not AGTR1 rs5182, was a predictor of TG/HDL-C for the whole study population. Both ACE I/D and AGTR1 rs5182 were predictors of HDL-C and LDL-C levels in females but not in males. Moreover, in females, diabetes mellitus and ACE I/D were identified as predictors of TG and TG/HDL-C, whereas AGTR1 rs5182 and diabetes mellitus were predictors of TG/HDL-C. Moreover, diabetes mellitus and the combination of ACE I/D and AGTR1 rs5182 variations were predictors of TG and TG/HDL-C exclusively in females. CONCLUSIONS: The results demonstrated the potential for gender-dependent interactions of ACE I/D, AGTR1 rs5182, and diabetes on lipid profiles. These findings may serve as an additional explanation for the inconsistent changes of blood lipids in individuals with diabetes mellitus, thereby offering a novel perspective for the clinical management of blood lipid levels in diabetic patients.

Discover QTLs for the level of blood components in Shaoxing duck using GWAS and haplotype sharing analysis.

Blood composition is indicative of health-related traits such as immunity and metabolism. The use of molecular genetics to investigate alterations in these attributes in laying ducks is a novel approach. Our objective was to employ genome - wide association studies (GWAS) and haplotype - sharing analysis to identify genomic regions and potential genes associated with 11 blood components in Shaoxing ducks. Our findings revealed 35 SNPs and 1 SNP associated with low-density lipoprotein cholesterol (LDL) and globulin (GLB), respectively. We identified 36 putative candidate genes for the LDL trait in close proximity to major QTLs and key loci. Based on their biochemical and physiological properties, TRA2A, NPY, ARHGEF26, DHX36, and AADAC are the strongest putative candidate genes. Through linkage disequilibrium analysis and haplotype sharing analysis, we identified three haplotypes and one haplotype, respectively, that were significantly linked with LDL and GLB. These haplotypes could be selected as potential candidate haplotypes for molecular breeding of Shaoxing ducks. Additionally, we utilized a bootstrap test to verify the reliability of GWAS with small experimental samples. The test can be accessed at https://github.com/xuwenwu24/Bootstrap-test.

Sex and statin-related genetic associations at the PCSK9 gene locus: results of genome-wide association meta-analysis.

BACKGROUND: Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key player of lipid metabolism with higher plasma levels in women throughout their life. Statin treatment affects PCSK9 levels also showing evidence of sex-differential effects. It remains unclear whether these differences can be explained by genetics. METHODS: We performed genome-wide association meta-analyses (GWAS) of PCSK9 levels stratified for sex and statin treatment in six independent studies of Europeans (8936 women/11,080 men respectively 14,825 statin-free/5191 statin-treated individuals). Loci associated in one of the strata were tested for statin- and sex-interactions considering all independent signals per locus. Independent variants at the PCSK9 gene locus were then used in a stratified Mendelian Randomization analysis (cis-MR) of PCSK9 effects on low-density lipoprotein cholesterol (LDL-C) levels to detect differences of causal effects between the subgroups. RESULTS: We identified 11 loci associated with PCSK9 in at least one stratified subgroup (p < 1.0 × 10-6), including the PCSK9 gene locus and five other lipid loci: APOB, TM6SF2, FADS1/FADS2, JMJD1C, and HP/HPR. The interaction analysis revealed eight loci with sex- and/or statin-interactions. At the PCSK9 gene locus, there were four independent signals, one with a significant sex-interaction showing stronger effects in men (rs693668). Regarding statin treatment, there were two significant interactions in PCSK9 missense mutations: rs11591147 had stronger effects in statin-free individuals, and rs11583680 had stronger effects in statin-treated individuals. Besides replicating known loci, we detected two novel genome-wide significant associations: one for statin-treated individuals at 6q11.1 (within KHDRBS2) and one for males at 12q24.22 (near KSR2/NOS1), both with significant interactions. In the MR of PCSK9 on LDL-C, we observed significant causal estimates within all subgroups, but significantly stronger causal effects in statin-free subjects compared to statin-treated individuals. CONCLUSIONS: We performed the first double-stratified GWAS of PCSK9 levels and identified multiple biologically plausible loci with genetic interaction effects. Our results indicate that the observed sexual dimorphism of PCSK9 and its statin-related interactions have a genetic basis. Significant differences in the causal relationship between PCSK9 and LDL-C suggest sex-specific dosages of PCSK9 inhibitors.

The protein "proprotein convertase subtilisin/kexin type 9" (PCSK9) regulates the levels of low-density lipoprotein cholesterol (LDL-C) in blood, and thus, contributes to the risk of cardio-vascular diseases. Women tend to have higher PCSK9 plasma levels throughout their life, although the difference is smaller in patients under LDL-C lowering medication (e.g., statins). We investigated the interplay of genetics, statin-treatment and sex, using combined data from six European studies. We detected 11 genetic regions associated with PCSK9 levels, of which one was specific for women (at SLCO1B3, a statin-transporter gene), and three were specific for men (e.g., ALOX5, encoding a protein linked to chronic inflammatory diseases such as atherosclerosis). We also tested if statin use changed the genetic effect and found five genes only associated with PCSK9 levels in untreated participants. Variants in the gene encoding PCSK9 were most strongly associated and had heterogeneous effects in dependence on statin treatment and sex: On one hand, there were genetic variants with stronger effects in men than women. Those variants are also linked to sex-differential gene expression of PCSK9. On the other hand, there were also variants with treatment-depending effects, linked to protein structure and functionality of PCSK9. This indicates that the observed sexual and treatment-related effects on PCSK9 levels have a genetic basis. In addition, we compared the causal effects of PCSK9 on LDL-C levels between men and women and found a different response to statin treatment. This highlights the need for sex-sensitive dosages of lipid-lowering medication.

Causal relationship between PCSK9 inhibitor and primary glomerular disease: a drug target Mendelian randomization study.

Background: Successive observational studies have highlighted low-density lipoprotein cholesterol (LDL-C) as a standalone risk factor for the progression of chronic kidney disease (CKD) to end-stage renal disease. Lowering LDL-C levels significantly reduces the incidence of atherosclerotic events in patients with progressive CKD. Recent research indicates that proprotein convertase subtilisin kexin 9 (PCSK9) inhibitors not only effectively lower LDL-C levels in CKD patients but also exhibit therapeutic potential for autoimmune diseases such as systemic lupus erythematosus, rheumatoid arthritis, and ulcerative colitis. However, the role of PCSK9 inhibitors (PCSK9i) in treating CKD beyond lowering LDL-C levels remains uncertain. Therefore, this study employs drug-targeted Mendelian randomization (MR) to investigate the causal impact of PCSK9i on primary glomerular diseases such as IgA nephropathy (IgAN), membranous nephropathy (MN), and nephrotic syndrome (NS). Methods: Single-nucleotide polymorphisms (SNPs) linked to LDL-C were sourced from the Global Lipids Genetics Consortium genome-wide association study (GWAS). Genes situated in proximity to 3-Hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR), and PCSK9 served as proxies for therapeutic inhibition of these targets. The causal link between PCSK9i and the risk of primary glomerular disorders was discovered using drug-target MR studies. The HMGCR inhibitor, a drug target of statins, was utilized for comparative analysis with PCSK9i. Primary outcomes included the risk assessment for IgAN, MN, and NS, using the risk of coronary heart disease as a positive control. Results: The inhibition of PCSK9, as proxied genetically, was found to significantly reduce the risk of IgAN [odds ratio, OR (95% confidence interval, CI) = 0.05 (-1.82 to 1.93), p = 2.10 × 10-3]. Conversely, this inhibition was associated with an increased risk of NS [OR (95% CI) = 1.78 (1.34-2.22), p = 0.01]. Similarly, HMGCR inhibitors (HMGCRi) demonstrated a potential reduction in the risk of IgAN [OR (95%CI) = 0.0032 (-3.58 to 3.59), p = 1.60 × 10-3). Conclusions: PCSK9i markedly decreased the risk of IgAN, suggesting a potential mechanism beyond their primary effect on LDL-C. However, these inhibitors were also associated with an increased risk of NS. On the other hand, HMGCRi appears to serve as a protective factor against IgAN. Conversely, PCSK9i may pose a risk factor for NS, suggesting the necessity for cautious application and further research into their impacts on various glomerular diseases.

Dose-Response Associations of Lipid Traits With Coronary Artery Disease and Mortality.

Importance: Apolipoprotein B (apoB), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG) are associated with coronary artery disease (CAD). However, trial evidence for the association of intensive LDL-C lowering and TG lowering with mortality is less definitive. Objectives: To investigate the associations of apoB, LDL-C, and TG with CAD and mortality, both overall and by sex and age, and to characterize the shapes of these associations. Design, Setting, and Participants: This genetic association study used linear and nonlinear mendelian randomization (MR) to analyze a population-based cohort of individuals of European ancestry from the UK Biobank, which recruited participants from 2006 to 2010 with follow-up information updated until September 2021. Data analysis occurred from December 2022 to November 2023. Exposures: Genetically predicted apoB, LDL-C, and TG. Main Outcomes and Measures: The primary outcomes were CAD, all-cause mortality, and cause-specific mortality. Genetic associations with CAD were calculated using logistic regression, associations with all-cause mortality using Cox proportional hazards regression, and associations with cause-specific mortality using cause-specific Cox proportional hazards regression with censoring for other causes of mortality. Results: This study included 347 797 participants (mean [SD] age, 57.2 [8.0] years; 188 330 female [54.1%]). There were 23 818 people who developed CAD and 23 848 people who died. Genetically predicted apoB was positively associated with risk of CAD (odds ratio [OR], 1.65 per SD increase; 95% CI 1.57-1.73), all-cause mortality (hazard ratio [HR], 1.11; 95% CI, 1.06-1.16), and cardiovascular mortality (HR, 1.36; 95% CI, 1.24-1.50), with some evidence for larger associations in male participants than female participants. Findings were similar for LDL-C. Genetically predicted TG was positively associated with CAD (OR, 1.60; 95% CI 1.52-1.69), all-cause mortality (HR, 1.08; 95% CI, 1.03-1.13), and cardiovascular mortality (HR, 1.21; 95% CI, 1.09-1.34); however, sensitivity analyses suggested evidence of pleiotropy. The association of genetically predicted TG with CAD persisted but it was no longer associated with mortality outcomes after controlling for apoB. Nonlinear MR suggested that all these associations were monotonically increasing across the whole observed distribution of each lipid trait, with no diminution at low lipid levels. Such patterns were observed irrespective of sex or age. Conclusions and relevance: In this genetic association study, apoB (or, equivalently, LDL-C) was associated with increased CAD risk, all-cause mortality, and cardiovascular mortality, all in a dose-dependent way. TG may increase CAD risk independent of apoB, although the possible presence of pleiotropy is a limitation. These insights highlight the importance of apoB (or, equivalently, LDL-C) lowering for reducing cardiovascular morbidity and mortality across its whole distribution.

The relationship between genetic liver fat and coronary heart disease is explained by apoB-containing lipoproteins.

BACKGROUND: The relationship between genetically-driven liver fat and coronary heart disease (CHD) remains unclear. ApoB-containing lipoproteins are known causal factors for CHD and may explain this relationship. METHODS AND RESULTS: We conducted a genome-wide association study (GWAS) in the UK Biobank to identify genetic variants associated with liver fat. We then investigated the effects that these genetic variants had on both apoB-containing lipoproteins and CHD. Using Mendelian Randomization (MR) analyses, we examined if the relationship between genetically-driven liver fat and CHD could be attributed to its effect on apoB-containing lipoproteins. We found 25 independent liver-fat associated single-nucleotide polymorphisms (SNPs) with differing effects on lipoprotein metabolism. The SNPs were classified into three groups/clusters. The first cluster (N = 3 SNPs) displayed lipoprotein-raising effects. The second cluster (N = 12 SNPs) displayed neutral effects on lipoproteins and the third cluster (N = 10 SNPs) displayed lipoprotein-lowering effects. For every 1% higher liver fat, the first cluster showed an increased risk of CHD (OR = 1.157 [95% CI: 1.108-1.208]). The second cluster showed a non-significant effect on CHD (OR = 0.988 [95% CI: 0.965-1.012], whereas the third cluster showed a protective effect of increased liver fat on CHD (OR = 0.942 [95% CI: 0.897-0.989]). When adjusting for apoB, the risk for CHD became null. CONCLUSIONS: Here, we identify 25 liver-fat associated SNPs. We find that SNPs that increase, decrease or have neutral effects on apoB-containing lipoproteins show increased, decreased or neutral effects on CHD, respectively. Therefore, the relationship between genetically-driven liver fat and CHD is mediated by the causal effect of apoB.

Genetic association of lipid-lowering drug target genes with erectile dysfunction and male reproductive health.

Objective: The effect of hypolipidemic drugs on male erectile function is still controversial. This Mendelian randomization (MR) study aimed to explore the potential impact of lipid-lowering drug targets on ED. Methods: We collected seven genetic variants encoding lipid-lowering drug targets (LDLR, HMGCR, NPC1L1, PCSK9, APOB, APOC3 and LPL) from published genome-wide association study (GWAS) statistics, and performed drug target MR analysis. The risk of ED was defined as the primary outcome, sex hormone levels and other diseases as the secondary outcomes. Mediation analyses were performed to explore potential mediating factors. Results: The results showed that LDLR, LPL agonists and APOC3 inhibitors were significantly associated with a reduced risk of ED occurrence. APOB inhibitors were associated with an increased risk of ED occurrence. In terms of sex hormone levels, LDLR and LPL agonists were significantly associated with increased TT levels, and HMGCR was associated with decreased TT and BT levels significantly. In terms of male-related disease, MR results showed that LDLR agonists and PCSK9 inhibitors were significantly associated with an elevated risk of PH; HMGCR, NPC1L1 inhibitors were associated with a reduced risk of PCa; and LDLR agonists were significantly associated with a reduced risk of AS and MI; in addition, HMGCR inhibitors were associated with a reduced risk of PCa. Conclusion: After performing drug-targeted MR analysis, we found that that there was a causal relationship between lipid-lowering drug targets and ED. APOC3, APOB, LDLR and LPL may be new candidate drug targets for the treatment of ED.

Association between high-density lipoprotein cholesterol and type 2 diabetes mellitus: dual evidence from NHANES database and Mendelian randomization analysis.

Background: Low levels of high-density lipoprotein cholesterol (HDL-C) are commonly seen in patients with type 2 diabetes mellitus (T2DM). However, it is unclear whether there is an independent or causal link between HDL-C levels and T2DM. This study aims to address this gap by using the The National Health and Nutrition Examination Survey (NHANES) database and Mendelian randomization (MR) analysis. Materials and methods: Data from the NHANES survey (2007-2018) with 9,420 participants were analyzed using specialized software. Logistic regression models and restricted cubic splines (RCS) were used to assess the relationship between HDL-C and T2DM incidence, while considering covariates. Genetic variants associated with HDL-C and T2DM were obtained from genome-wide association studies (GWAS), and Mendelian randomization (MR) was used to evaluate the causal relationship between HDL-C and T2DM. Various tests were conducted to assess pleiotropy and outliers. Results: In the NHANES study, all groups, except the lowest quartile (Q1: 0.28-1.09 mmol/L], showed a significant association between HDL-C levels and reduced T2DM risk (all P < 0.001). After adjusting for covariates, the Q2 [odds ratio (OR) = 0.67, 95% confidence interval (CI): (0.57, 0.79)], Q3 [OR = 0.51, 95% CI: (0.40, 0.65)], and Q4 [OR = 0.29, 95% CI: (0.23, 0.36)] groups exhibited average reductions in T2DM risk of 23%, 49%, and 71%, respectively. In the sensitivity analysis incorporating other lipid levels, the Q4 group still demonstrates a 57% reduction in the risk of T2DM. The impact of HDL-C levels on T2DM varied with age (P for interaction = 0.006). RCS analysis showed a nonlinear decreasing trend in T2DM risk with increasing HDL-C levels (P = 0.003). In the MR analysis, HDL-C levels were also associated with reduced T2DM risk (OR = 0.69, 95% CI = 0.52-0.82; P = 1.41 × 10-13), and there was no evidence of pleiotropy or outliers. Conclusion: This study provides evidence supporting a causal relationship between higher HDL-C levels and reduced T2DM risk. Further research is needed to explore interventions targeting HDL-C levels for reducing T2DM risk.

Lipid levels and risk of acute pancreatitis using bidirectional Mendelian randomization.

Previous studies found lipid levels, especially triglycerides (TG), are associated with acute pancreatitis, but their causalities and bi-directions were not fully examined. We determined whether abnormal levels of TG, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) are precursors and/or consequences of acute pancreatitis using bidirectional two-sample Mendelian randomization (MR) with two non-overlapping genome-wide association study (GWAS) summary statistics for lipid levels and acute pancreatitis. We found phenotypic associations that both higher TG levels and lower HDL-C levels contributed to increased risk of acute pancreatitis. Our GWAS meta-analysis of acute pancreatitis identified seven independent signals. Genetically predicted TG was positively associated with acute pancreatitis when using the variants specifically associated with TG using univariable MR [Odds ratio (OR), 95% CI 2.02, 1.22-3.31], but the reversed direction from acute pancreatitis to TG was not observed (mean difference = 0.003, SE = 0.002, P-value = 0.138). However, a bidirectional relationship of HDL-C and acute pancreatitis was observed: A 1-SD increment of genetically predicted HDL-C was associated with lower risk of acute pancreatitis (OR, 95% CI 0.84, 0.76-0.92) and genetically predisposed individuals with acute pancreatitis have, on average, 0.005 SD lower HDL-C (mean difference = - 0.005, SE = 0.002, P-value = 0.004). Our MR analysis confirms the evidence of TG as a risk factor of acute pancreatitis but not a consequence. A potential bidirectional relationship of HDL-C and acute pancreatitis occurs and raises the prospect of HDL-C modulation in the acute pancreatitis prevention and treatment.