The power of genetic diversity in genome-wide association studies of lipids

Benchmarking Mendelian randomization methods for causal inference using genome-wide association study summary statistics

Mendelian randomization (MR), which utilizes genetic variants as instrumental variables (IVs), has gained popularity as a method for causal inference between phenotypes using genetic data. While efforts have been made to relax IV assumptions and develop new methods for causal inference in the presence of invalid IVs due to confounding, the reliability of MR methods in real-world applications remains uncertain. Instead of using simulated datasets, we conducted a benchmark study evaluating 16 two-sample summary-level MR methods using real-world genetic datasets to provide guidelines for the best practices. Our study focused on the following crucial aspects: type I error control in the presence of various confounding scenarios (e.g., population stratification, pleiotropy, and family-level confounders like assortative mating), the accuracy of causal effect estimates, replicability, and power. By comprehensively evaluating the performance of compared methods over one thousand exposure-outcome trait pairs, our study not only provides valuable insights into the performance and limitations of the compared methods but also offers practical guidance for researchers to choose appropriate MR methods for causal inference.

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.

Interpreting SNP heritability in admixed populations

SNP heritability is defined as the proportion of phenotypic variance explained by genotyped SNPs and is believed to be a lower bound of heritability ( h 2 ), being equal to it if all causal variants are known. Despite the simple intuition behind , its interpretation and equivalence to h 2 is unclear, particularly in the presence of population structure and assortative mating. It is well known that population structure can lead to inflation in estimates because of confounding due to linkage disequilibrium (LD) or shared environment. Here we use analytical theory and simulations to demonstrate that estimates can be biased in admixed populations, even in the absence of confounding and even if all causal variants are known. This is because admixture generates LD, which contributes to the genetic variance, and therefore to heritability. Genome-wide restricted maximum likelihood (GREML) does not capture this contribution leading to under-or over-estimates of relative to h 2 , depending on the genetic architecture. In contrast, Haseman-Elston (HE) regression exaggerates the LD contribution leading to biases in the opposite direction. For the same reason, GREML and HE estimates of local ancestry heritability are also biased. We describe this bias in and as a function of admixture history and the genetic architecture of the trait and show that it can be recovered under some conditions. We clarify the interpretation of in admixed populations and discuss its implication for genome-wide association studies and polygenic prediction.

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.

The Causal Effect of Serum Lipid Levels Mediated by Neuregulin 4 on the Risk of Four Atherosclerosis Subtypes: Evidence from Mendelian Randomization Analysis

Background

Neuregulin 4 (NRG4) was known to be associated with serum lipid levels and atherosclerosis. However, it is unknown whether the role of NRG4 in lipid homeostasis is causal to atherosclerosis and whether the effect is beneficial across different atherosclerosis subtypes.

Methods

We investigated the causal role of the levels of serum low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides regulated by NRG4 in subtypes of atherosclerosis through two sample Mendelian randomization. Aggregated genome-wide association study (GWAS) summary data for serum lipid level of 1.32 million individuals with European ancestry were obtained from the Global Lipids Genetics Consortium. GWAS summary data for four atherosclerosis subtypes (peripheral, coronary, cerebral and the other atherosclerosis) were obtained from FinnGen Consortium. Generalized inverse-variance-weighted Mendelian randomization and several sensitivity analyses were used to obtain the causal estimates.

Results

A 1-SD genetically elevated LDL-C level mediated by NRG4 was validated to be nominally associated with the risk of peripheral atherosclerosis (log (odds ratio)= 4.14, 95% confidence interval 0.11 to 8.17, P = 0.04), and the other associations were not significant or could not be validated by sensitivity analyses.

Conclusion

LDL-C lowering mediated by NRG4 is likely to prevent peripheral atherosclerosis.

A comprehensive multi-task deep learning approach for predicting metabolic syndrome with genetic, nutritional, and clinical data

Metabolic syndrome (MetS) is a complex disorder characterized by a cluster of metabolic abnormalities, including abdominal obesity, hypertension, elevated triglycerides, reduced high-density lipoprotein cholesterol, and impaired glucose tolerance. It poses a significant public health concern, as individuals with MetS are at an increased risk of developing cardiovascular diseases and type 2 diabetes. Early and accurate identification of individuals at risk for MetS is essential. Various machine learning approaches have been employed to predict MetS, such as logistic regression, support vector machines, and several boosting techniques. However, these methods use MetS as a binary status and do not consider that MetS comprises five components. Therefore, a method that focuses on these characteristics of MetS is needed. In this study, we propose a multi-task deep learning model designed to predict MetS and its five components simultaneously. The benefit of multi-task learning is that it can manage multiple tasks with a single model, and learning related tasks may enhance the model's predictive performance. To assess the efficacy of our proposed method, we compared its performance with that of several single-task approaches, including logistic regression, support vector machine, CatBoost, LightGBM, XGBoost and one-dimensional convolutional neural network. For the construction of our multi-task deep learning model, we utilized data from the Korean Association Resource (KARE) project, which includes 352,228 single nucleotide polymorphisms (SNPs) from 7729 individuals. We also considered lifestyle, dietary, and socio-economic factors that affect chronic diseases, in addition to genomic data. By evaluating metrics such as accuracy, precision, F1-score, and the area under the receiver operating characteristic curve, we demonstrate that our multi-task learning model surpasses traditional single-task machine learning models in predicting MetS.

Participant-derived cell line transcriptomic analyses and mouse studies reveal a role for ZNF335 in plasma cholesterol statin response

BACKGROUND

Statins lower circulating low-density lipoprotein cholesterol (LDLC) levels and reduce cardiovascular disease risk. Though highly efficacious in general, there is considerable inter-individual variation in statin efficacy that remains largely unexplained.

METHODS

To identify novel genes that may modulate statin-induced LDLC lowering, we used RNA-sequencing data from 426 control- and 2 µM simvastatin-treated lymphoblastoid cell lines (LCLs) derived from European and African American ancestry participants of the Cholesterol and Pharmacogenetics (CAP) 40 mg/day 6-week simvastatin clinical trial (ClinicalTrials.gov Identifier: NCT00451828). We correlated statin-induced changes in LCL gene expression with plasma LDLC statin response in the corresponding CAP participants. For the most correlated gene identified (ZNF335), we followed up in vivo by comparing plasma cholesterol levels, lipoprotein profiles, and lipid statin response between wild-type mice and carriers of a hypomorphic (partial loss of function) missense mutation in Zfp335 (the mouse homolog of ZNF335).

RESULTS

The statin-induced expression changes of 147 human LCL genes were significantly correlated to the plasma LDLC statin responses of the corresponding CAP participants in vivo (FDR = 5%). The two genes with the strongest correlations were zinc finger protein 335 (ZNF335 aka NIF-1, rho = 0.237, FDR-adj p = 0.0085) and CCR4-NOT transcription complex subunit 3 (CNOT3, rho = 0.233, FDR-adj p = 0.0085). Chow-fed mice carrying a hypomorphic missense (R1092W; aka bloto) mutation in Zfp335 had significantly lower non-HDL cholesterol levels than wild-type C57BL/6J mice in a sex combined model (p = 0.04). Furthermore, male (but not female) mice carrying the Zfp335R1092W allele had significantly lower total and HDL cholesterol levels than wild-type mice. In a separate experiment, wild-type mice fed a control diet for 4 weeks and a matched simvastatin diet for an additional 4 weeks had significant statin-induced reductions in non-HDLC (-43 ± 18% and -23 ± 19% for males and females, respectively). Wild-type male (but not female) mice experienced significant reductions in plasma LDL particle concentrations, while male mice carrying Zfp335R1092W allele(s) exhibited a significantly blunted LDL statin response.

CONCLUSIONS

Our in vitro and in vivo studies identified ZNF335 as a novel modulator of plasma cholesterol levels and statin response, suggesting that variation in ZNF335 activity could contribute to inter-individual differences in statin clinical efficacy.

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.

Genomic privacy preservation in genome-wide association studies: taxonomy, limitations, challenges, and vision

Genome-wide association studies (GWAS) serve as a crucial tool for identifying genetic factors associated with specific traits. However, ethical constraints prevent the direct exchange of genetic information, prompting the need for privacy preservation solutions. To address these issues, earlier works are based on cryptographic mechanisms such as homomorphic encryption, secure multi-party computing, and differential privacy. Very recently, federated learning has emerged as a promising solution for enabling secure and collaborative GWAS computations. This work provides an extensive overview of existing methods for GWAS privacy preserving, with the main focus on collaborative and distributed approaches. This survey provides a comprehensive analysis of the challenges faced by existing methods, their limitations, and insights into designing efficient solutions.

Regulation of Mitochondria-Derived Immune Activation by 'Antiviral' TRIM Proteins

Mitochondria are key orchestrators of antiviral responses that serve as platforms for the assembly and activation of innate immune-signaling complexes. In response to viral infection, mitochondria can be triggered to release immune-stimulatory molecules that can boost interferon production. These same molecules can be released by damaged mitochondria to induce pathogenic, antiviral-like immune responses in the absence of infection. This review explores how members of the tripartite motif-containing (TRIM) protein family, which are recognized for their roles in antiviral defense, regulate mitochondria-based innate immune activation. In antiviral defense, TRIMs are essential components of immune signal transduction pathways and function as directly acting viral restriction factors. TRIMs carry out conceptually similar activities when controlling immune activation related to mitochondria. First, they modulate immune-signaling pathways that can be activated by mitochondrial molecules. Second, they co-ordinate the direct removal of mitochondria and associated immune-activating factors through mitophagy. These insights broaden the scope of TRIM actions in innate immunity and may implicate TRIMs in diseases associated with mitochondria-derived inflammation.

Schizophrenia genomics: genetic complexity and functional insights

Determining the causes of schizophrenia has been a notoriously intractable problem, resistant to a multitude of investigative approaches over centuries. In recent decades, genomic studies have delivered hundreds of robust findings that implicate nearly 300 common genetic variants (via genome-wide association studies) and more than 20 rare variants (via whole-exome sequencing and copy number variant studies) as risk factors for schizophrenia. In parallel, functional genomic and neurobiological studies have provided exceptionally detailed information about the cellular composition of the brain and its interconnections in neurotypical individuals and, increasingly, in those with schizophrenia. Taken together, these results suggest unexpected complexity in the mechanisms that drive schizophrenia, pointing to the involvement of ensembles of genes (polygenicity) rather than single-gene causation. In this Review, we describe what we now know about the genetics of schizophrenia and consider the neurobiological implications of this information.

MRBEE: A bias-corrected multivariable Mendelian randomization method

Mendelian randomization (MR) is an instrumental variable approach used to infer causal relationships between exposures and outcomes, which is becoming increasingly popular because of its ability to handle summary statistics from genome-wide association studies. However, existing MR approaches often suffer the bias from weak instrumental variables, horizontal pleiotropy and sample overlap. We introduce MRBEE (MR using bias-corrected estimating equation), a multivariable MR method capable of simultaneously removing weak instrument and sample overlap bias and identifying horizontal pleiotropy. Our extensive simulations and real data analyses reveal that MRBEE provides nearly unbiased estimates of causal effects, well-controlled type I error rates and higher power than comparably robust methods and is computationally efficient. Our real data analyses result in consistent causal effect estimates and offer valuable guidance for conducting multivariable MR studies, elucidating the roles of pleiotropy, and identifying total 42 horizontal pleiotropic loci missed previously that are associated with myopia, schizophrenia, and coronary artery disease.

Epigenetic associations of GPNMB rs199347 variant with alcohol consumption in Parkinson's disease

Introduction

Alcohol consumption can induce a neuroinflammatory response and contribute to the progression of neurodegeneration. However, its association with Parkinson's disease (PD), the second most common neurodegenerative disorder, remains undetermined. Recent studies suggest that the glycoprotein non-metastatic melanoma protein B (GPNMB) is a potential biomarker for PD. We evaluated the association of rs199347, a variant of the GPNMB gene, with alcohol consumption and methylation upstream of GPNMB.

Methods

We retrieved genetic and DNA methylation data obtained from participants enrolled in the Taiwan Biobank (TWB) between 2008 and 2016. After excluding individuals with incomplete or missing information about potential PD risk factors, we included 1,357 participants in our final analyses. We used multiple linear regression to assess the association of GPNMB rs199347 and chronic alcohol consumption (and other potential risk factors) with GPNMB cg17274742 methylation.

Results

There was no difference between the distribution of GPNMB rs199347 genotypes between chronic alcohol consumers and the other study participants. A significant interaction was observed between the GPNMB rs199347 variant and alcohol consumption (p = 0.0102) concerning cg17274742 methylation. Compared to non-chronic alcohol consumers with the AA genotype, alcohol drinkers with the rs199347 GG genotype had significantly lower levels (hypomethylation) of cg17274742 (p = 0.0187).

Conclusion

Alcohol consumption among individuals with the rs199347 GG genotype was associated with lower levels of cg17274742 methylation, which could increase expression of the GPNMB gene, an important neuroinflammatory-related risk gene for PD.

Multi-biobank Mendelian randomization analyses identify opposing pathways in plasma low-density lipoprotein-cholesterol lowering and gallstone disease

Plasma low-density lipoprotein (LDL)-cholesterol is positively associated with coronary artery disease risk while biliary cholesterol promotes gallstone formation. Different plasma LDL-cholesterol lowering pathways may have distinct effects on biliary cholesterol and thereby gallstone disease risk. We conducted a Mendelian randomization (MR) study using data from the UK Biobank (30,547 gallstone disease cases/336,742 controls), FinnGen (34,461 cases/301,383 controls) and Biobank Japan (9,305 cases/168,253 controls). We first performed drug-target MR analyses substantiated by colocalization to investigate the effects of plasma LDL-cholesterol lowering therapies on gallstone disease risk. We then performed clustered MR analyses and pathway analyses to identify distinct mechanisms underlying the association of plasma LDL-cholesterol with gallstone disease risk. For a 1-standard deviation reduction in plasma LDL-cholesterol, genetic mimics of statins were associated with lower gallstone disease risk (odds ratio 0.72 [95% confidence interval 0.62, 0.83]), but genetic mimics of PCSK9 inhibitors and targeting apolipoprotein B were associated with higher risk (1.11 [1.03, 1.19] and 1.23 [1.13, 1.35]). The association for statins was supported by colocalization (posterior probability 98.7%). Clustered MR analyses identified variant clusters showing opposing associations of plasma LDL-cholesterol with gallstone disease risk, with some evidence for ancestry-and sex-specific associations. Among variants lowering plasma LDL-cholesterol, those associated with lower gallstone disease risk were mapped to glycosphingolipid biosynthesis pathway, while those associated with higher risk were mapped to pathways relating to plasma lipoprotein assembly, remodelling, and clearance and ATP-binding cassette transporters. This MR study provides genetic evidence that different plasma LDL-cholesterol lowering pathways have opposing effects on gallstone disease risk.

Fish oil supplementation modifies the associations between genetically predicted and observed concentrations of blood lipids: a cross-sectional gene-diet interaction study in UK Biobank

BACKGROUND

Dyslipidemia is a well-known risk factor for cardiovascular disease, the leading cause of mortality worldwide. Although habitual intake of fish oil is associated with cardioprotective effects through triglyceride reduction, the interactions of fish oil with the genetic predisposition to dysregulated lipids remain elusive.

OBJECTIVES

We examined whether fish oil supplementation modifies the association between genetically predicted and observed concentrations of total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, and triglycerides.

METHODS

A total of 441,985 participants with complete genetic and phenotypic data from the UK Biobank were included. Polygenic scores (PGS) of the 4 lipids were calculated in participants of diverse ancestries. For each lipid, multivariable linear regression models were used to assess if fish oil supplementation modified the association between PGS and the observed circulating concentration, with adjustment for relevant covariates.

RESULTS

Fish oil supplementation attenuates the associations between genetically predicted and observed circulating concentrations of total cholesterol, LDL cholesterol, and triglycerides while accentuating the corresponding association for HDL cholesterol among 424,090 participants of European ancestry. Consistent significant findings were obtained using PGS calculated based on multiple genome-wide association studies or alternative PGS methods. For triglycerides, each standard deviation (SD) increment in PGS is associated with 0.254 [95% confidence interval (CI): 0.248, 0.259] SD increase in the observed concentration among European-ancestry participants who reported fish oil usage. In contrast, a stronger association was observed in nonusers (0.267; 95% CI: 0.263, 0.270). Consistently, we showed that fish oil significantly attenuates the association between genetically predicted and observed concentrations of triglycerides in African-ancestry participants.

CONCLUSIONS

Fish oil supplementation attenuates the association between genetically predicted and observed circulating concentrations of total cholesterol, LDL cholesterol, and triglycerides while accentuating the corresponding association for HDL cholesterol in individuals of European ancestry. Further research is needed to understand the clinical implications of these findings.

Multi-omics characterization of type 2 diabetes associated genetic variation

Discerning the mechanisms driving type 2 diabetes (T2D) pathophysiology from genome-wide association studies (GWAS) remains a challenge. To this end, we integrated omics information from 16 multi-tissue and multi-ancestry expression, protein, and metabolite quantitative trait loci (QTL) studies and 46 multi-ancestry GWAS for T2D-related traits with the largest, most ancestrally diverse T2D GWAS to date. Of the 1,289 T2D GWAS index variants, 716 (56%) demonstrated strong evidence of colocalization with a molecular or T2D-related trait, implicating 657 cis-effector genes, 1,691 distal-effector genes, 731 metabolites, and 43 T2D-related traits. We identified 773 of these cis- and distal-effector genes using either expression QTL data from understudied ancestry groups or inclusion of T2D index variants enriched in underrepresented populations, emphasizing the value of increasing population diversity in functional mapping. Linking these variants, genes, metabolites, and traits into a network, we elucidated mechanisms through which T2D-associated variation may impact disease risk. Finally, we showed that drugs targeting effector proteins were enriched in those approved to treat T2D, highlighting the potential of these results to prioritize drug targets for T2D. These results represent a leap in the molecular characterization of T2D-associated genetic variation and will aid in translating genetic findings into novel therapeutic strategies.

Lipidome changes due to improved dietary fat quality inform cardiometabolic risk reduction and precision nutrition

Current cardiometabolic disease prevention guidelines recommend increasing dietary unsaturated fat intake while reducing saturated fats. Here we use lipidomics data from a randomized controlled dietary intervention trial to construct a multilipid score (MLS), summarizing the effects of replacing saturated fat with unsaturated fat on 45 lipid metabolite concentrations. In the EPIC-Potsdam cohort, a difference in the MLS, reflecting better dietary fat quality, was associated with a significant reduction in the incidence of cardiovascular disease (-32%; 95% confidence interval (95% CI): -21% to -42%) and type 2 diabetes (-26%; 95% CI: -15% to -35%). We built a closely correlated simplified score, reduced MLS (rMLS), and observed that beneficial rMLS changes, suggesting improved dietary fat quality over 10 years, were associated with lower diabetes risk (odds ratio per standard deviation of 0.76; 95% CI: 0.59 to 0.98) in the Nurses' Health Study. Furthermore, in the PREDIMED trial, an olive oil-rich Mediterranean diet intervention primarily reduced diabetes incidence among participants with unfavorable preintervention rMLS levels, suggestive of disturbed lipid metabolism before intervention. Our findings indicate that the effects of dietary fat quality on the lipidome can contribute to a more precise understanding and possible prediction of the health outcomes of specific dietary fat modifications.

Genetic Architecture and Clinical Outcomes of Combined Lipid Disturbances

BACKGROUND

Dyslipoproteinemia often involves simultaneous derangements of multiple lipid traits. We aimed to evaluate the phenotypic and genetic characteristics of combined lipid disturbances in a general population-based cohort.

METHODS

Among UK Biobank participants without prevalent coronary artery disease, we used blood lipid and apolipoprotein B concentrations to ascribe individuals into 1 of 6 reproducible and mutually exclusive dyslipoproteinemia subtypes. Incident coronary artery disease risk was estimated for each subtype using Cox proportional hazards models. Phenome-wide analyses and genome-wide association studies were performed for each subtype, followed by in silico causal gene prioritization and heritability analyses. Additionally, the prevalence of disruptive variants in causal genes for Mendelian lipid disorders was assessed using whole-exome sequence data.

RESULTS

Among 450 636 UK Biobank participants: 63 (0.01%) had chylomicronemia; 40 005 (8.9%) had hypercholesterolemia; 94 785 (21.0%) had combined hyperlipidemia; 13 998 (3.1%) had remnant hypercholesterolemia; 110 389 (24.5%) had hypertriglyceridemia; and 49 (0.01%) had mixed hypertriglyceridemia and hypercholesterolemia. Over a median (interquartile range) follow-up of 11.1 (10.4-11.8) years, incident coronary artery disease risk varied across subtypes, with combined hyperlipidemia exhibiting the largest hazard (hazard ratio, 1.92 [95% CI, 1.84-2.01]; P=2×10-16), even when accounting for non-HDL-C (hazard ratio, 1.45 [95% CI, 1.30-1.60]; P=2.6×10-12). Genome-wide association studies revealed 250 loci significantly associated with dyslipoproteinemia subtypes, of which 72 (28.8%) were not detected in prior single lipid trait genome-wide association studies. Mendelian lipid variant carriers were rare (2.0%) among individuals with dyslipoproteinemia, but polygenic heritability was high, ranging from 23% for remnant hypercholesterolemia to 54% for combined hyperlipidemia.

CONCLUSIONS

Simultaneous assessment of multiple lipid derangements revealed nuanced differences in coronary artery disease risk and genetic architectures across dyslipoproteinemia subtypes. These findings highlight the importance of looking beyond single lipid traits to better understand combined lipid and lipoprotein phenotypes and implications for disease risk.

Bidirectional causality between the levels of blood lipids and endometriosis: a two-sample mendelian randomization study

BACKGROUND

Observational studies have found a correlation between the levels of blood lipids and the development and progression of endometriosis (EM). However, the causality and direction of this correlation is unclear. This study aimed to examine the bidirectional connection between lipid profiles and the risk of EM using publicly available genome-wide association study (GWAS) summary statistics.

METHODS

Eligible exposure variables such as levels of triglycerides (TG), total cholesterol (TC), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) were selected using a two-sample Mendelian randomization (MR) analysis method following a series of quality control procedures. Data on EM were obtained from the publicly available Finnish database of European patients. Inverse variance weighted (IVW), MR Egger, weighted median, and weighted mode methods were used to analyze the causal relationship between lipid exposure and EM, exclude confounders, perform sensitivity analyses, and assess the stability of the results. Reverse MR analyses were performed with EM as exposure and lipid results as study outcomes.

RESULTS

IVW analysis results identified HDL as a protective factor for EM, while TG was shown to be a risk factor for EM. Subgroup analyses based on the site of the EM lesion identified HDL as a protective factor for EM of the uterus, while TG was identified a risk factor for the EM of the fallopian tube, ovary, and pelvic peritoneum. Reverse analysis did not reveal any effect of EM on the levels of lipids.

CONCLUSION

Blood lipids, such as HDL and TG, may play an important role in the development and progression of EM. However, EM does not lead to dyslipidemia.

PON1 rs662, rs854560 and TRIB1 rs17321515, rs2954029 Gene Polymorphisms Are Associated with Lipid Parameters in Patients with Unstable Angina

Acute coronary heart disease (CHD) is mainly caused by the rupture of an unstable atherosclerotic plaque. Many different factors can cause stenosis or even occlusion of the coronary artery lumen, such as vasculitis and platelet aggregation. Our study was performed to assess the association between PON1 rs662, rs854560 and TRIB1 rs17321515, rs2954029 polymorphisms and the risk of CHD, as well as the association between studied polymorphisms and selected clinical parameters affecting the risk of developing ischemic heart disease. A total of 232 patients with unstable angina were enrolled in this study. There were no statistically significant differences in the PON1 rs662, rs854560 and TRIB1 rs17321515, rs2954029 polymorphism distributions between the total study and control groups. Total cholesterol plasma levels were significantly higher in patients with the PON1 rs662 TT genotype compared to those with the CC+TC genotypes, as well as in patients with the PON1 rs854560 TT genotype compared to those with the AA+AT genotypes. LDL plasma levels were significantly increased in patients with the PON1 rs854560 TT genotype compared to those with the AA+AT genotypes. Plasma levels of HDL were significantly decreased in patients with the TRIB1 rs17321515 AA+AG genotypes compared to those with the GG genotype, as well as in patients with the TRIB1 rs2954029 AA+AT genotypes compared to those with the TT genotype. Our results suggest that the analysed polymorphisms are not risk factors for unstable angina in the Polish population. However, the results of this study indicate an association between the PON1 rs662, rs854560 and TRIB1 rs17321515, rs2954029 polymorphisms with lipid parameters in patients with coronary artery disease.

Mendelian randomization study of lipid metabolism characteristics and migraine risk

BACKGROUND

The association between serum lipids and migraine is controversial. However, randomized controlled trials have suggested that statins may be efficacious for the prevention of migraine. In this study, we aim to investigate the relationship between lipids metabolism and migraine risk.

METHODS

Single-nucleotide polymorphisms (SNPs), relating to the serum lipid traits and the effect of lipid-lowering drugs that target APOB, CETP, HMGCR, NPC1L1, and PCSK9, were extracted from genome-wide association studies (GWAS) summary data. The GWAS summary data were obtained from the Global Lipids Genetic Consortium (GLGC), the UK Biobank, and the FinnGen study, respectively. Mendelian randomization (MR) analysis was performed to evaluate the association between serum lipid traits and lipid-lowering drugs with migraine risk.

RESULTS

Regarding serum lipids, it was found that SNPs related to high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), total cholesterol (TC), or triglycerides (TG) levels were not associated with migraine, migraine with aura (MA) or migraine without aura (MO). In addition, genotypes of HMGCR related to higher LDL-C levels were associated with increased risk of migraine (OR = 1.46, p = 0.035) and MA (OR = 2.03, p = 0.008); However, genotypes of PCSK9 related to higher LDL-C levels were associated with decreased risk of migraine (OR = 0.75, p = 0.001) and MA (OR = 0.69, p = 0.004); And genotypes of APOB related to higher LDL-C levels were associated with decreased risk of MO (OR = 0.62, p = 0.000).

CONCLUSIONS

There is a relationship between lipid metabolism characteristics and migraine risk.

SIGNIFICANCE

Based on the genome-wide association summary data, single-nucleotide polymorphisms (SNPs) related to high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), total cholesterol (TC), or triglycerides (TG) level were not associated with risk of migraine, migraine with aura (MA) or migraine without aura (MO). However, genotypes of HMGCR related to higher LDL-C levels have shown an increased risk on migraine and MA. And genotypes of APOB or PCSK9 related to higher LDL-C levels have shown a decreased risk on MO, or migraine and MA, respectively. These results suggested that there may be a relationship between lipid metabolism characteristics and the risk for migraine development.

Relationship of Fat Mass Ratio, a Biomarker for Lipodystrophy, With Cardiometabolic Traits

Familial partial lipodystrophy (FPLD) is a heterogenous group of syndromes associated with a high prevalence of cardiometabolic diseases. Prior work has proposed DEXA-derived fat mass ratio (FMR), defined as trunk fat percentage divided by leg fat percentage, as a biomarker of FPLD, but this metric has not previously been characterized in large cohort studies. We set out to 1) understand the cardiometabolic burden of individuals with high FMR in up to 40,796 participants in the UK Biobank and 9,408 participants in the Fenland study, 2) characterize the common variant genetic underpinnings of FMR, and 3) build and test a polygenic predictor for FMR. Participants with high FMR were at higher risk for type 2 diabetes (odds ratio [OR] 2.30, P = 3.5 × 10-41) and metabolic dysfunction-associated liver disease or steatohepatitis (OR 2.55, P = 4.9 × 10-7) in UK Biobank and had higher fasting insulin (difference 19.8 pmol/L, P = 5.7 × 10-36) and fasting triglycerides (difference 36.1 mg/dL, P = 2.5 × 10-28) in the Fenland study. Across FMR and its component traits, 61 conditionally independent variant-trait pairs were discovered, including 13 newly identified pairs. A polygenic score for FMR was associated with an increased risk of cardiometabolic diseases. This work establishes the cardiometabolic significance of high FMR, a biomarker for FPLD, in two large cohort studies and may prove useful in increasing diagnosis rates of patients with metabolically unhealthy fat distribution to enable treatment or a preventive therapy.

ARTICLE HIGHLIGHTS

Integrative regulation of hLMR1 by dietary and genetic factors in nonalcoholic fatty liver disease and hyperlipidemia

Long non-coding RNA (lncRNA) genes represent a large class of transcripts that are widely expressed across species. As most human lncRNAs are non-conserved, we recently employed a unique humanized liver mouse model to study lncRNAs expressed in human livers. We identified a human hepatocyte-specific lncRNA, hLMR1 (human lncRNA metabolic regulator 1), which is induced by feeding and promotes hepatic cholesterol synthesis. Recent genome-wide association studies (GWAS) found that several single-nucleotide polymorphisms (SNPs) from the hLMR1 gene locus are associated with blood lipids and markers of liver damage. These results suggest that dietary and genetic factors may regulate hLMR1 to affect disease progression. In this study, we first screened for nutritional/hormonal factors and found that hLMR1 was robustly induced by insulin/glucose in cultured human hepatocytes, and this induction is dependent on the transcription factor SREBP1. We then tested if GWAS SNPs genetically linked to hLMR1 could regulate hLMR1 expression. We found that DNA sequences flanking rs9653945, a SNP from the last exon of the hLMR1 gene, functions as an enhancer that can be robustly activated by SREBP1c depending on the presence of rs9653945 major allele (G). We further performed CRISPR base editing in human HepG2 cells and found that rs9653945 major (G) to minor (A) allele modification resulted in blunted insulin/glucose-induced expression of hLMR1. Finally, we performed genotyping and gene expression analyses using a published human NAFLD RNA-seq dataset and found that individuals homozygous for rs9653945-G have a higher expression of hLMR1 and risk of NAFLD. Taken together, our data support a model that rs9653945-G predisposes individuals to insulin/glucose-induced hLMR1, contributing to the development of hyperlipidemia and NAFLD.

Influence of Polygenic Background on the Clinical Presentation of Familial Hypercholesterolemia

BACKGROUND

Heterozygous familial hypercholesterolemia (FH) is among the most common genetic conditions worldwide that affects ≈ 1 in 300 individuals. FH is characterized by increased levels of low-density lipoprotein cholesterol (LDL-C) and increased risk of coronary artery disease (CAD), but there is a wide spectrum of severity within the FH population. This variability in expression is incompletely explained by known risk factors. We hypothesized that genome-wide genetic influences, as represented by polygenic risk scores (PRSs) for cardiometabolic traits, would influence the phenotypic severity of FH.

METHODS

We studied individuals with clinically diagnosed FH (n=1123) from the FH Canada National Registry, as well as individuals with genetically identified FH from the UK Biobank (n=723). For all individuals, we used genome-wide gene array data to calculate PRSs for CAD, LDL-C, lipoprotein(a), and other cardiometabolic traits. We compared the distribution of PRSs in individuals with clinically diagnosed FH, genetically diagnosed FH, and non-FH controls and examined the association of the PRSs with the risk of atherosclerotic cardiovascular disease.

RESULTS

Individuals with clinically diagnosed FH had higher levels of LDL-C, and the incidence of atherosclerotic cardiovascular disease was higher in individuals with clinically diagnosed compared with genetically identified FH. Individuals with clinically diagnosed FH displayed enrichment for higher PRSs for CAD, LDL-C, and lipoprotein(a) but not for other cardiometabolic risk factors. The CAD PRS was associated with a risk of atherosclerotic cardiovascular disease among individuals with an FH-causing genetic variant.

CONCLUSIONS

Genetic background, as expressed by genome-wide PRSs for CAD, LDL-C, and lipoprotein(a), influences the phenotypic severity of FH, expanding our understanding of the determinants that contribute to the variable expressivity of FH. A PRS for CAD may aid in risk prediction among individuals with FH.

Discovering mechanisms of human genetic variation and controlling cell states at scale

Population-scale sequencing efforts have catalogued substantial genetic variation in humans such that variant discovery dramatically outpaces interpretation. We discuss how single-cell sequencing is poised to reveal genetic mechanisms at a rate that may soon approach that of variant discovery. The functional genomics toolkit is sufficiently modular to systematically profile almost any type of variation within increasingly diverse contexts and with molecularly comprehensive and unbiased readouts. As a result, we can construct deep phenotypic atlases of variant effects that span the entire regulatory cascade. The same conceptual approach to interpreting genetic variation should be applied to engineering therapeutic cell states. In this way, variant mechanism discovery and cell state engineering will become reciprocating and iterative processes towards genomic medicine.

Calibrated prediction intervals for polygenic scores across diverse contexts

Polygenic scores (PGS) have emerged as the tool of choice for genomic prediction in a wide range of fields. We show that PGS performance varies broadly across contexts and biobanks. Contexts such as age, sex and income can impact PGS accuracy with similar magnitudes as genetic ancestry. Here we introduce an approach (CalPred) that models all contexts jointly to produce prediction intervals that vary across contexts to achieve calibration (include the trait with 90% probability), whereas existing methods are miscalibrated. In analyses of 72 traits across large and diverse biobanks (All of Us and UK Biobank), we find that prediction intervals required adjustment by up to 80% for quantitative traits. For disease traits, PGS-based predictions were miscalibrated across socioeconomic contexts such as annual household income levels, further highlighting the need of accounting for context information in PGS-based prediction across diverse populations.

Rare variants at KCNJ2 are associated with LDL-cholesterol levels in a cross-population study

Leveraging whole genome sequencing data of 1751 individuals from the UK and 2587 Qatari subjects, we suggest here an association of rare variants mapping to the sour taste-associated gene KCNJ2 with reduced low-density lipoprotein cholesterol (LDL-C, P = 2.10 × 10-12) and with a 22% decreased dietary trans-fat intake. This study identifies a novel candidate rare locus for LDL-C, adding insights into the genetic architecture of a complex trait implicated in cardiovascular disease.

Statin use and fall risk in adults: a cross-sectional survey and mendelian randomization analysis

Background and Objective

The issue of falls poses a significant threat to the health of the elderly population. Although statins can cause myopathy, which implies that they may cause balance problems and increase the risk of falling, this has not been tested. Our objective was to assess whether the use of statins is linked to a higher risk of falls.

Methods

A cross-sectional survey study and Mendelian randomization (MR) study were conducted to examine whether the use of statins was associated with an increased risk of falling and balance problems. The cross-sectional study included 2,656 participants from the US population (NHANES) who reported information on balance and falling problems in the past year and their use of statins. Univariate and multivariate logistic regression models were used to investigate the association between statin use and the likelihood of falling or experiencing balance problems. The MR study identified five Single Nucleotide Polymorphisms (SNPs) that predict statin use across five ancestry groups: Admixed African or African, East Asian, European, Hispanic, and South Asian. Additionally, SNPs predicting the risk of falls were acquired from the UK Biobank population. A two-sample MR analysis was performed to examine whether genetically predicted statin use increased the risk of falls.

Results

The use of statins was found to be associated with an increased likelihood of balance and falling problems (balance problem, OR 1.25, 95%CI 1.02 to 1.55; falling problem, OR 1.27, 95%CI 1.03-1.27). Subgroup analysis revealed that patients under the age of 65 were more susceptible to these issues when taking statins (balance problem, OR 3.42, 95%CI 1.40 to 9.30; falling problem, OR 5.58, 95%CI 2.04-15.40). The MR analysis indicated that the use of statins, as genetically proxied, resulted in an increased risk of falling problems (OR 1.21, 95% CI 1.1-1.33).

Conclusion

Our study found an association between the use of statins and an increased risk of balance problems and falls in adults over 40 years old, and the MR study result suggested statin use increased risk of falls. The risk was higher in participants under 65 years old compared to those over 65 years old.

Obstructive Sleep Apnea Syndrome Exacerbates NASH Progression via Selective Autophagy-Mediated Eepd1 Degradation

Obstructive sleep apnea syndrome (OSAS), characterized by chronic intermittent hypoxia (CIH), is an independent risk factor for aggravating non-alcoholic steatohepatitis (NASH). The prevailing mouse model employed in CIH research is inadequate for the comprehensive exploration of the impact of CIH on NASH development due to reduced food intake observed in CIH-exposed mice, which deviates from human responses. To address this issue, a pair-feeding investigation with CIH-exposed and normoxia-exposed mice is conducted. It is revealed that CIH exposure aggravates DNA damage, leading to hepatic fibrosis and inflammation. The analysis of genome-wide association study (GWAS) data also discloses the association between Eepd1, a DNA repair enzyme, and OSAS. Furthermore, it is revealed that CIH triggered selective autophagy, leading to the autophagic degradation of Eepd1, thereby exacerbating DNA damage in hepatocytes. Notably, Eepd1 liver-specific knockout mice exhibit aggravated hepatic DNA damage and further progression of NASH. To identify a therapeutic approach for CIH-induced NASH, a drug screening is conducted and it is found that Retigabine dihydrochloride suppresses CIH-mediated Eepd1 degradation, leading to alleviated DNA damage in hepatocytes. These findings imply that targeting CIH-mediated Eepd1 degradation can be an adjunctive approach in the treatment of NASH exacerbated by OSAS.

Comparing the effects of CETP in East Asian and European ancestries: a Mendelian randomization study

CETP inhibitors are a class of lipid-lowering drugs in development for treatment of coronary heart disease (CHD). Genetic studies in East Asian ancestry have interpreted the lack of CETP signal with low-density lipoprotein cholesterol (LDL-C) and lack of drug target Mendelian randomization (MR) effect on CHD as evidence that CETP inhibitors might not be effective in East Asian participants. Capitalizing on recent increases in sample size of East Asian genetic studies, we conducted a drug target MR analysis, scaled to a standard deviation increase in high-density lipoprotein cholesterol. Despite finding evidence for possible neutral effects of lower CETP levels on LDL-C, systolic blood pressure and pulse pressure in East Asians (interaction p-values < 1.6 × 10-3), effects on cardiovascular outcomes were similarly protective in both ancestry groups. In conclusion, on-target inhibition of CETP is anticipated to decrease cardiovascular disease in individuals of both European and East Asian ancestries.

Shared genetics between breast cancer and predisposing diseases identifies novel breast cancer treatment candidates

Background

Current effective breast cancer treatment options have severe side effects, highlighting a need for new therapies. Drug repurposing can accelerate improvements to care, as FDA-approved drugs have known safety and pharmacological profiles. Some drugs for other conditions, such as metformin, an antidiabetic, have been tested in clinical trials for repurposing for breast cancer. Here, we exploit the genetics of breast cancer and linked predisposing diseases to propose novel drug repurposing. We hypothesize that if a predisposing disease contributes to breast cancer pathology, identifying the pleiotropic genes related to the risk of cancer could prioritize drug targets, among all drugs treating a predisposing disease. We aim to develop a method to not only prioritize drug repurposing, but also to highlight shared etiology explaining repurposing.

Methods

We compile breast cancer's predisposing diseases from literature. For each predisposing disease, we use GWAS summary statistics to identify genes in loci showing genetic correlation with breast cancer. Then, we use a network approach to link these shared genes to canonical pathways, and similarly for all drugs treating the predisposing disease, we link their targets to pathways. In this manner, we are able to prioritize a list of drugs based on each predisposing disease, with each drug linked to a set of implicating pathways. Finally, we evaluate our recommendations against drugs currently under investigation for breast cancer.

Results

We identify 84 loci harboring mutations with positively correlated effects between breast cancer and its predisposing diseases; these contain 194 identified shared genes. Out of the 112 drugs indicated for the predisposing diseases, 76 drugs can be linked to shared genes via pathways (candidate drugs for repurposing). Fifteen out of these candidate drugs are already in advanced clinical trial phases or approved for breast cancer (OR = 9.28, p = 7.99e-03, one-sided Fisher's exact test), highlighting the ability of our approach to identify likely successful candidate drugs for repurposing.

Conclusions

Our novel approach accelerates drug repurposing for breast cancer by leveraging shared genetics with its known risk factors. The result provides 59 novel candidate drugs alongside biological insights supporting each recommendation.

Generation Scotland: an update on Scotland's longitudinal family health study

PURPOSE

Generation Scotland (GS) is a large family-based cohort study established as a longitudinal resource for research into the genetic, lifestyle and environmental determinants of physical and mental health. It comprises extensive genetic, sociodemographic and clinical data from volunteers in Scotland.

PARTICIPANTS

A total of 24 084 adult participants, including 5501 families, were recruited between 2006 and 2011. Within the cohort, 59% (approximately 14 209) are women, with an average age at recruitment of 49 years. Participants completed a health questionnaire and attended an in-person clinic visit, where detailed baseline data were collected on lifestyle information, cognitive function, personality traits and mental and physical health. Genotype array data are available for 20 026 (83%) participants, and blood-based DNA methylation (DNAm) data for 18 869 (78%) participants. Linkage to routine National Health Service datasets has been possible for 93% (n=22 402) of the cohort, creating a longitudinal resource that includes primary care, hospital attendance, prescription and mortality records. Multimodal brain imaging is available in 1069 individuals.

FINDINGS TO DATE

GS has been widely used by researchers across the world to study the genetic and environmental basis of common complex diseases. Over 350 peer-reviewed papers have been published using GS data, contributing to research areas such as ageing, cancer, cardiovascular disease and mental health. Recontact studies have built on the GS cohort to collect additional prospective data to study chronic pain, major depressive disorder and COVID-19.

FUTURE PLANS

To create a larger, richer, longitudinal resource, 'Next Generation Scotland' launched in May 2022 to expand the existing cohort by a target of 20 000 additional volunteers, now including anyone aged 12+ years. New participants complete online consent and questionnaires and provide postal saliva samples, from which genotype and salivary DNAm array data will be generated. The latest cohort information and how to access data can be found on the GS website (www.generationscotland.org).

Major Psychiatric Disorders, Substance Use Behaviors, and Longevity

Importance

Observational studies suggest that major psychiatric disorders and substance use behaviors reduce longevity, making it difficult to disentangle their relationships with aging-related outcomes.

Objective

To evaluate the associations between the genetic liabilities for major psychiatric disorders, substance use behaviors (smoking and alcohol consumption), and longevity.

Design, Settings, and Participants

This 2-sample mendelian randomization (MR) study assessed associations between psychiatric disorders, substance use behaviors, and longevity using single-variable and multivariable models. Multiomics analyses were performed elucidating transcriptomic underpinnings of the MR associations and identifying potential proteomic therapeutic targets. This study sourced summary-level genome-wide association study (GWAS) data, gene expression, and proteomic data from cohorts of European ancestry. Analyses were performed from May 2022 to November 2023.

Exposures

Genetic susceptibility for major depression (n = 500 199), bipolar disorder (n = 413 466), schizophrenia (n = 127 906), problematic alcohol use (n = 435 563), weekly alcohol consumption (n = 666 978), and lifetime smoking index (n = 462 690).

Main Outcomes and Measures

The main outcome encompassed aspects of health span, lifespan, and exceptional longevity. Additional outcomes were epigenetic age acceleration (EAA) clocks.

Results

Findings from multivariable MR models simultaneously assessing psychiatric disorders and substance use behaviorsm suggest a negative association between smoking and longevity in cohorts of European ancestry (n = 709 709; 431 503 [60.8%] female; β, -0.33; 95% CI, -0.38 to -0.28; P = 4.59 × 10-34) and with increased EAA (n = 34 449; 18 017 [52.3%] female; eg, PhenoAge: β, 1.76; 95% CI, 0.72 to 2.79; P = 8.83 × 10-4). Transcriptomic imputation and colocalization identified 249 genes associated with smoking, including 36 novel genes not captured by the original smoking GWAS. Enriched pathways included chromatin remodeling and telomere assembly and maintenance. The transcriptome-wide signature of smoking was inversely associated with longevity, and estimates of individual smoking-associated genes, eg, XRCC3 and PRMT6, aligned with the smoking-longevity MR analyses, suggesting underlying transcriptomic mediators. Cis-instrument MR prioritized brain proteins associated with smoking behavior, including LY6H (β, 0.02; 95% CI, 0.01 to 0.03; P = 2.37 × 10-6) and RIT2 (β, 0.02; 95% CI, 0.01 to 0.03; P = 1.05 × 10-5), which had favorable adverse-effect profiles across 367 traits evaluated in phenome-wide MR.

Conclusions

The findings suggest that the genetic liability of smoking, but not of psychiatric disorders, is associated with longevity. Transcriptomic associations offer insights into smoking-related pathways, and identified proteomic targets may inform therapeutic development for smoking cessation strategies.

Distinct biological signature and modifiable risk factors underlie the comorbidity between major depressive disorder and cardiovascular disease

Major depressive disorder (MDD) and cardiovascular disease (CVD) are often comorbid, resulting in excess morbidity and mortality. Here we show that CVDs share most of their genetic risk factors with MDD. Multivariate genome-wide association analysis of shared genetic liability between MDD and atherosclerotic CVD revealed seven loci and distinct patterns of tissue and brain cell-type enrichments, suggesting the involvement of the thalamus. Part of the genetic overlap was explained by shared inflammatory, metabolic and psychosocial or lifestyle risk factors. Our data indicated causal effects of genetic liability to MDD on CVD risk, but not from most CVDs to MDD, and showed that the causal effects were partly explained by metabolic and psychosocial or lifestyle factors. The distinct signature of MDD-atherosclerotic CVD comorbidity suggests an immunometabolic subtype of MDD that is more strongly associated with CVD than overall MDD. In summary, we identified biological mechanisms underlying MDD-CVD comorbidity and modifiable risk factors for prevention of CVD in individuals with MDD.

Genetic variations of low-density lipoprotein cholesterol on metabolic disorders in obstructive sleep apnea

BACKGROUND

The study aimed to explore the relationship between low-density lipoprotein cholesterol (LDL-C) genetic variants and obstructive sleep apnea (OSA) and its complications, including cardiovascular diseases (CVD), insulin resistance (IR), and metabolic syndrome (MS).

METHOD

4329 individuals with suspected OSA who underwent a comprehensive assessment of anthropometric, biochemical, and polysomnography (PSG) data, along with 30 LDL-C single nucleotide polymorphisms (SNPs) were enrolled. The 10-year Framingham CVD risk score (FRS), IR and MS were evaluated for each subject. Linear regression and logistic regression were utilized to examine the correlations among these variables.

RESULTS

After the Benjamini-Hochberg correction, linear regression results indicated positive correlations between variants rs3741297 and rs629301 with FRS (β = 0.031, PBH=0.002; β = 0.026, PBH=0.015). Logistic regression revealed that rs3741297 increased MS risk among total subjects [OR = 1.67 (95% CI:1.369-2.038), PBH=1.32 × 10- 5] and increased IR risk in females [OR = 3.475 (95% CI:1.653-7.307), PBH=0.03]. In males, rs2642438 decreased MS risk [OR = 0.81 (95% CI:0.703-0.933), PBH=0.045].

CONCLUSIONS

The rs3741297 variant correlated with susceptibility to CVD, IR, and MS in the OSA population. OSA, CVD, IR and MS share a potentially common genetic background, which may promote precision medicine.

CINICAL TRIAL REGISTRATION

The study protocol was registered with the Chinese Clinical Trial Registry (ChiCTR1900025714).

Associations of lipids and lipid-modifying drug target genes with atrial fibrillation risk based on genomic data

BACKGROUND

The causal associations of lipids and the drug target genes with atrial fibrillation (AF) risk remain obscure. We aimed to investigate the causal associations using genetic evidence.

METHODS

Mendelian randomization (MR) analyses were conducted using summary-level genome-wide association studies (GWASs) in European and East Asian populations. Lipid profiles (low-density lipoprotein cholesterol, triglyceride, and lipoprotein[a]) and lipid-modifying drug target genes (3-hydroxy-3-methylglutaryl-CoA reductase, proprotein convertase subtilisin/kexin type 9, NPC1-like intracellular cholesterol transporter 1, apolipoprotein C3, angiopoietin-like 3, and lipoprotein[a]) were used as exposures. AF was used as an outcome. The inverse variance weighted method was applied as the primary method. Summary-data-based Mendelian randomization analyses were performed for further validation using expression quantitative trait loci data. Mediation analyses were conducted to explore the indirect effect of coronary heart disease.

RESULTS

In the European population, MR analyses demonstrated that elevated levels of lipoprotein(a) increased AF risk. Moreover, analyses focusing on drug targets revealed that the genetically proxied target gene LPA, which simulates the effects of drug intervention by reducing lipoprotein(a), exhibited an association with AF risk. This association was validated in independent datasets. There were no consistent and significant associations observed for other traits when analyzed in different datasets. This finding was also corroborated by Summary-data-based Mendelian randomization analyses between LPA and AF. Mediation analyses revealed that coronary heart disease plays a mediating role in this association. However, in the East Asian population, no statistically significant evidence was observed to support these associations.

CONCLUSIONS

This study provided genetic evidence that Lp(a) may be a causal factor for AF and that LPA may represent a promising pharmacological target for preventing AF in the European population.

PCSK9 genetic variants and risk of vascular and non-vascular diseases in Chinese and UK populations

AIMS

Lowering low-density lipoprotein cholesterol (LDL-C) through PCSK9 inhibition represents a new therapeutic approach to preventing and treating cardiovascular disease (CVD). Phenome-wide analyses of PCSK9 genetic variants in large biobanks can help to identify unexpected effects of PCSK9 inhibition.

METHODS AND RESULTS

In the prospective China Kadoorie Biobank, we constructed a genetic score using three variants at the PCSK9 locus associated with directly measured LDL-C [PCSK9 genetic score (PCSK9-GS)]. Logistic regression gave estimated odds ratios (ORs) for PCSK9-GS associations with CVD and non-CVD outcomes, scaled to 1 SD lower LDL-C. PCSK9-GS was associated with lower risks of carotid plaque [n = 8340 cases; OR = 0.61 (95% confidence interval: 0.45-0.83); P = 0.0015], major occlusive vascular events [n = 15 752; 0.80 (0.67-0.95); P = 0.011], and ischaemic stroke [n = 11 467; 0.80 (0.66-0.98); P = 0.029]. However, PCSK9-GS was also associated with higher risk of hospitalization with chronic obstructive pulmonary disease [COPD: n = 6836; 1.38 (1.08-1.76); P = 0.0089] and with even higher risk of fatal exacerbations amongst individuals with pre-existing COPD [n = 730; 3.61 (1.71-7.60); P = 7.3 × 10-4]. We also replicated associations for a PCSK9 variant, reported in UK Biobank, with increased risks of acute upper respiratory tract infection (URTI) [pooled OR after meta-analysis of 1.87 (1.38-2.54); P = 5.4 × 10-5] and self-reported asthma [pooled OR of 1.17 (1.04-1.30); P = 0.0071]. There was no association of a polygenic LDL-C score with COPD hospitalization, COPD exacerbation, or URTI.

CONCLUSION

The LDL-C-lowering PCSK9 genetic variants are associated with lower risk of subclinical and clinical atherosclerotic vascular disease but higher risks of respiratory diseases. Pharmacovigilance studies may be required to monitor patients treated with therapeutic PCSK9 inhibitors for exacerbations of respiratory diseases or respiratory tract infections.

LAY SUMMARY

Genetic analyses of over 100 000 participants of the China Kadoorie Biobank, mimicking the effect of new drugs intended to reduce cholesterol by targeting the PCSK9 protein, have identified potential severe effects of lower PCSK9 activity in patients with existing respiratory disease.PCSK9 genetic variants that are associated with lower cholesterol and reduced rates of cardiovascular disease are also associated with increased risk of a range of respiratory diseases, including asthma, upper respiratory tract infections, and hospitalization with chronic obstructive pulmonary disease (COPD).These genetic variants are not associated with whether or not individuals have COPD; instead, they are specifically associated with an increase in the chance of those who already have COPD being hospitalized and even dying, suggesting that careful monitoring of such patients should be considered during development of and treatment with anti-PCSK9 medication.

Genetically proxied low-density lipoprotein cholesterol lowering via PCSK9-inhibitor drug targets and risk of congenital malformations

AIMS

Current guidelines advise against the use of lipid-lowering drugs during pregnancy. This is based only on previous observational evidence demonstrating an association between statin use and congenital malformations, which is increasingly controversial. In the absence of clinical trial data, we aimed to use drug-target Mendelian randomization to model the potential impact of fetal LDL-lowering, overall and through PCSK9 drug targets, on congenital malformations.

METHODS AND RESULTS

Instrumental variants influencing LDL levels overall and through PCSK9-inhibitor drug targets were extracted from genome-wide association study (GWAS) summary data for LDL on 1 320 016 individuals. Instrumental variants influencing circulating PCSK9 levels (pQTLs) and liver PCSK9 gene expression levels (eQTLs) were extracted, respectively, from a GWAS on 10 186 individuals and from the genotype-tissue expression project. Gene-outcome association data was extracted from the 7th release of GWAS summary data on the FinnGen cohort (n = 342 499) for eight categories of congenital malformations affecting multiple systems. Genetically proxied LDL-lowering through PCSK9 was associated with higher odds of malformations affecting multiple systems [OR 2.70, 95% confidence interval (CI) 1.30-5.63, P = 0.018], the skin (OR 2.23, 95% CI 1.33-3.75, P = 0.007), and the vertebral, anorectal, cardiovascular, tracheo-esophageal, renal, and limb association (VACTERL) (OR 1.51, 95% CI 1.16-1.96, P = 0.007). An association was also found with obstructive defects of the renal pelvis and ureter, but this association was suggestive of horizontal pleiotropy. Lower PCSK9 pQTLs were associated with the same congenital malformations.

CONCLUSION

These data provide genetic evidence supporting current manufacturer advice to avoid the use of PCSK9 inhibitors during pregnancy.

Cross-ancestry genome-wide association studies of brain imaging phenotypes

Genome-wide association studies of brain imaging phenotypes are mainly performed in European populations, but other populations are severely under-represented. Here, we conducted Chinese-alone and cross-ancestry genome-wide association studies of 3,414 brain imaging phenotypes in 7,058 Chinese Han and 33,224 white British participants. We identified 38 new associations in Chinese-alone analyses and 486 additional new associations in cross-ancestry meta-analyses at P < 1.46 × 10-11 for discovery and P < 0.05 for replication. We pooled significant autosomal associations identified by single- or cross-ancestry analyses into 6,443 independent associations, which showed uneven distribution in the genome and the phenotype subgroups. We further divided them into 44 associations with different effect sizes and 3,557 associations with similar effect sizes between ancestries. Loci of these associations were shared with 15 brain-related non-imaging traits including cognition and neuropsychiatric disorders. Our results provide a valuable catalog of genetic associations for brain imaging phenotypes in more diverse populations.

Ancestry, ethnicity, and race: explaining inequalities in cardiometabolic disease

Population differences in cardiometabolic disease remain unexplained. Misleading assumptions over genetic explanations are partly due to terminology used to distinguish populations, specifically ancestry, race, and ethnicity. These terms differentially implicate environmental and biological causal pathways, which should inform their use. Genetic variation alone accounts for a limited fraction of population differences in cardiometabolic disease. Research effort should focus on societally driven, lifelong environmental determinants of population differences in disease. Rather than pursuing population stratifiers to personalize medicine, we advocate removing socioeconomic barriers to receipt of and adherence to healthcare interventions, which will have markedly greater impact on improving cardiometabolic outcomes. This requires multidisciplinary collaboration and public and policymaker engagement to address inequalities driven by society rather than biology per se.

G protein-coupled receptor 146: new insights from genetics and model systems

PURPOSE OF REVIEW

Atherosclerotic cardiovascular diseases continue to be a significant global cause of death. Despite the availability of efficient treatments, there is an ongoing need for innovative strategies to lower lipid levels, especially for individuals experiencing refractory dyslipidemias or intolerable adverse effects. Based on human genetic findings and on mouse studies, the G protein-coupled receptor 146 (GPR146) emerges as a promising target against hypercholesterolemia and atherosclerosis. The present review aims at providing a thorough summary of the latest information acquired regarding GPR146, encompassing genetic evidence, functional insights, and its broader implications for cardiometabolic health.

RECENT FINDINGS

Human genetic studies uncovered associations between GPR146 variants, plasma lipid levels and metabolic parameters. Additionally, GPR146's influence extends beyond lipid regulation, impacting adipocyte differentiation, lipolysis, and inflammation pathways. Despite GPR146's orphan status, ongoing efforts to deorphanize it, suggest a potential ligand with downstream effects involving Gαi coupling.

SUMMARY

Here, we outline and deliberate on recent progress focused on: enhancing comprehension of the effects of inhibiting GPR146 in humans through genetic instruments, evaluating the extra-hepatic functions of GPR146, and discovering its natural ligand(s). Grasping these biological parameters and mechanisms is crucial in the exploration of GPR146 as a prospective therapeutic target.

LDL-c Lowering, Ischemic Stroke, and Small Vessel Disease Brain Imaging Biomarkers: A Mendelian Randomization Study

BACKGROUND

The effects of lipid-lowering drug targets on different ischemic stroke subtypes are not fully understood. We aimed to explore the mechanisms by which lipid-lowering drug targets differentially affect the risk of ischemic stroke subtypes and their underlying pathophysiology.

METHODS

Using a 2-sample Mendelian randomization approach, we assessed the effects of genetically proxied low-density lipoprotein cholesterol (LDL-c) and 3 clinically approved LDL-lowering drugs (HMGCR [3-hydroxy-3-methylglutaryl-CoA reductase], PCSK9 [proprotein convertase subtilisin/kexin type 9], and NPC1L1 [Niemann-Pick C1-Like 1]) on stroke subtypes and brain imaging biomarkers associated with small vessel stroke (SVS), including white matter hyperintensity volume and perivascular spaces.

RESULTS

In genome-wide Mendelian randomization analyses, lower genetically predicted LDL-c was significantly associated with a reduced risk of any stroke, ischemic stroke, and large artery stroke, supporting previous findings. Significant associations between genetically predicted LDL-c and cardioembolic stroke, SVS, and biomarkers, perivascular space and white matter hyperintensity volume, were not identified in this study. In drug-target Mendelian randomization analysis, genetically proxied reduced LDL-c through NPC1L1 inhibition was associated with lower odds of perivascular space (odds ratio per 1-mg/dL decrease, 0.79 [95% CI, 0.67-0.93]) and with lower odds of SVS (odds ratio, 0.29 [95% CI, 0.10-0.85]).

CONCLUSIONS

This study provides supporting evidence of a potentially protective effect of LDL-c lowering through NPC1L1 inhibition on perivascular space and SVS risk, highlighting novel therapeutic targets for SVS.

Associations of Dietary Cholesterol Consumption With Incident Diabetes and Cardiovascular Disease: The Role of Genetic Variability in Cholesterol Absorption and Disease Predisposition

OBJECTIVE

Whether genetic susceptibility to disease and dietary cholesterol (DC) absorption contribute to inconsistent associations of DC consumption with diabetes and cardiovascular disease (CVD) remains unclear.

RESEARCH DESIGN AND METHODS

DC consumption was assessed by repeated 24-h dietary recalls in the UK Biobank. A polygenetic risk score (PRS) for DC absorption was constructed using genetic variants in the Niemann-Pick C1-Like 1 and ATP Binding Cassettes G5 and G8 genes. PRSs for diabetes, coronary artery disease, and stroke were also created. The associations of DC consumption with incident diabetes (n = 96,826) and CVD (n = 94,536) in the overall sample and by PRS subgroups were evaluated using adjusted Cox models.

RESULTS

Each additional 300 mg/day of DC consumption was associated with incident diabetes (hazard ratio [HR], 1.17 [95% CI, 1.07-1.27]) and CVD (HR, 1.09 [95% CI, 1.03-1.17]), but further adjusting for BMI nullified these associations (HR for diabetes, 0.99 [95% CI, 0.90-1.09]; HR for CVD, 1.04 [95% CI, 0.98-1.12]). Genetic susceptibility to the diseases did not modify these associations (P for interaction ≥0.06). The DC-CVD association appeared to be stronger in people with greater genetic susceptibility to cholesterol absorption assessed by the non-high-density lipoprotein cholesterol-related PRS (P for interaction = 0.04), but the stratum-level association estimates were not statistically significant.

CONCLUSIONS

DC consumption was not associated with incident diabetes and CVD, after adjusting for BMI, in the overall sample and in subgroups stratified by genetic predisposition to cholesterol absorption and the diseases. Nevertheless, whether genetic predisposition to cholesterol absorption modifies the DC-CVD association requires further investigation.

Body mass index stratification optimizes polygenic prediction of type 2 diabetes in cross-biobank analyses

Type 2 diabetes (T2D) shows heterogeneous body mass index (BMI) sensitivity. Here, we performed stratification based on BMI to optimize predictions for BMI-related diseases. We obtained BMI-stratified datasets using data from more than 195,000 individuals (nT2D = 55,284) from BioBank Japan (BBJ) and UK Biobank. T2D heritability in the low-BMI group was greater than that in the high-BMI group. Polygenic predictions of T2D toward low-BMI targets had pseudo-R2 values that were more than 22% higher than BMI-unstratified targets. Polygenic risk scores (PRSs) from low-BMI discovery outperformed PRSs from high BMI, while PRSs from BMI-unstratified discovery performed best. Pathway-specific PRSs demonstrated the biological contributions of pathogenic pathways. Low-BMI T2D cases showed higher rates of neuropathy and retinopathy. Combining BMI stratification and a method integrating cross-population effects, T2D predictions showed greater than 37% improvements over unstratified-matched-population prediction. We replicated findings in the Tohoku Medical Megabank (n = 26,000) and the second BBJ cohort (n = 33,096). Our findings suggest that target stratification based on existing traits can improve the polygenic prediction of heterogeneous diseases.

Multi-Ancestry Polygenic Risk Score for Coronary Heart Disease Based on an Ancestrally Diverse Genome-Wide Association Study and Population-Specific Optimization

BACKGROUND

Predictive performance of polygenic risk scores (PRS) varies across populations. To facilitate equitable clinical use, we developed PRS for coronary heart disease (CHD; PRSCHD) for 5 genetic ancestry groups.

METHODS

We derived ancestry-specific and multi-ancestry PRSCHD based on pruning and thresholding (PRSPT) and ancestry-based continuous shrinkage priors (PRSCSx) applied to summary statistics from the largest multi-ancestry genome-wide association study meta-analysis for CHD to date, including 1.1 million participants from 5 major genetic ancestry groups. Following training and optimization in the Million Veteran Program, we evaluated the best-performing PRSCHD in 176,988 individuals across 9 diverse cohorts.

RESULTS

Multi-ancestry PRSPT and PRSCSx outperformed ancestry-specific PRSPT and PRSCSx across a range of tuning values. Two best-performing multi-ancestry PRSCHD (ie, PRSPTmult and PRSCSxmult) and 1 ancestry-specific (PRSCSxEUR) were taken forward for validation. PRSPTmult demonstrated the strongest association with CHD in individuals of South Asian ancestry and European ancestry (odds ratio per 1 SD [95% CI, 2.75 [2.41-3.14], 1.65 [1.59-1.72]), followed by East Asian ancestry (1.56 [1.50-1.61]), Hispanic/Latino ancestry (1.38 [1.24-1.54]), and African ancestry (1.16 [1.11-1.21]). PRSCSxmult showed the strongest associations in South Asian ancestry (2.67 [2.38-3.00]) and European ancestry (1.65 [1.59-1.71]), lower in East Asian ancestry (1.59 [1.54-1.64]), Hispanic/Latino ancestry (1.51 [1.35-1.69]), and the lowest in African ancestry (1.20 [1.15-1.26]).

CONCLUSIONS

The use of summary statistics from a large multi-ancestry genome-wide meta-analysis improved the performance of PRSCHD in most ancestry groups compared with single-ancestry methods. Despite the use of one of the largest and most diverse sets of training and validation cohorts to date, improvement of predictive performance was limited in African ancestry. This highlights the need for larger genome-wide association study datasets of underrepresented populations to enhance the performance of PRSCHD.

Genetic liability to elevated circulating IP-10, IFNγ and SCGFβ levels in relation to thoracic aortic aneurysm: A mendelian randomization study

Inflammation is associated with thoracic aortic aneurysm (TAA) but the effects of each circulating inflammatory factor on TAA remain unclear. In this study, we explored the relationship between circulating inflammatory factors and TAA risk using Mendelian randomization (MR) approach based on summary statistics from the latest genome-wide association study (GWAS) of 41 circulating inflammatory factors in 8293 Finns and a GWAS involving 1351 TAA cases and 18,295 controls of European ancestry. In univariable MR, higher interferon gamma-induced protein 10 (IP-10) levels, higher interferon gamma (IFNγ) levels and higher stem cell growth factor beta (SCGFβ) levels were associated with an increased risk of TAA (OR = 1.37, 95 % CI = 1.17-1.59, p = 7.42 × 10-5; OR = 1.43, 95 % CI = 1.19-1.74, p = 2.04 × 10-4; OR = 1.27, 95 % CI = 1.09-1.48, p = 2.40 × 10-3, respectively). In multivariable MR, the patterns of associations for the three cytokines remained adjusting for each other or smoking, but were attenuated differently with adjustment for other cardiovascular risk factors, especially for lipids and body mass index. Bidirectional MR approach did not identify any significant associations between cytokines and risk factors. Our results indicated that circulating cytokines may play mediation roles in the pathogenesis of TAA. Further studies are needed to determine whether these biomarkers can be used to prevent and treat TAA.

Impact of loss-of-function in angiopoietin-like 4 on the human phenome

BACKGROUND

Carriers of the E40K loss-of-function variant in Angiopoietin-like 4 (ANGPTL4), have lower plasma triglyceride levels as well as lower rates of coronary artery disease (CAD) and type 2 diabetes (T2D). These genetic data suggest ANGPTL4 inhibition as a potential therapeutic target for cardiometabolic diseases. However, it is unknown whether the association between E40K and human diseases is due to linkage disequilibrium confounding. The broader impact of genetic ANGPTL4 inhibition is also unknown, raising uncertainties about the safety and validity of this target.

METHODS

To assess the impact of ANGPLT4 inhibition, we evaluated whether E40K and other loss-of-function variants in ANGPTL4 influenced a wide range of health markers and diseases using 29 publicly available genome-wide association meta-analyses of cardiometabolic traits and diseases, as well as 1589 diseases assessed in electronic health records within FinnGen (n = 309,154). To determine whether these relationships were likely causal, and not driven by other correlated variants, we used the Bayesian fine mapping algorithm CoPheScan.

RESULTS

The CoPheScan posterior probability of E40K being the causal variant for triglyceride levels was 99.99 %, validating the E40K to proxy lifelong lower activity of ANGPTL4. The E40K variant was associated with lower risk of CAD (odds ratio [OR] = 0.84, 95 % CI = 0.81 to 0.87, p=3.6e-21) and T2D (OR = 0.91, 95 % CI = 0.87 to 0.95, p=2.8e-05) in GWAS meta-analyses, with results replicated in FinnGen. These significant results were also replicated using other rare loss-of-function variants identified through whole exome sequencing in 488,278 participants of the UK Biobank. Using a Mendelian randomization study design, the E40K variant effect on cardiometabolic diseases was concordant with lipoprotein lipase enhancement (r = 0.82), but not hepatic lipase enhancement (r = -0.10), suggesting that ANGPTL4 effects on cardiometabolic diseases are potentially mainly mediated through lipoprotein lipase. After correction for multiple testing, the E40K variant did not significantly increase the risk of any of the 1589 diseases tested in FinnGen.

CONCLUSIONS

ANGPTL4 inhibition may represent a potentially safe and effective target for cardiometabolic diseases prevention or treatment.

Genetic association of serum lipids and lipid-modifying targets with endometriosis: Trans-ethnic Mendelian-randomization and mediation analysis

BACKGROUND

Prior observational research identified dyslipidemia as a risk factor for endometriosis (EMS) but the causal relationship remains unestablished due to inherent study limitations.

METHODS

Genome-wide association study data for high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), and total cholesterol (TC) from European (EUR) and East Asian (EAS) ancestries were sourced from the Global Lipids Genetics Consortium. Multi-ancestry EMS data came from various datasets. Univariable Mendelian randomization (MR) examined causal links between serum lipids and EMS. Multivariable and mediation MR explored the influence of seven confounding factors and mediators. Drug-target MR investigates the association between lipid-lowering target genes identified in positive results and EMS. The primary method was inverse-variance weighted (IVW), with replication datasets and meta-analyses reinforcing causal associations. Sensitivity analyses included false discovery rate (FDR) correction, causal analysis using summary effect estimates (CAUSE), and colocalization analysis.

RESULTS

IVW analysis in EUR ancestry showed a significant causal association between TG and increased EMS risk (OR = 1.112, 95% CI 1.033-1.198, P = 5.03×10-3, PFDR = 0.03), supported by replication and meta-analyses. CAUSE analysis confirmed unbiased results (P < 0.05). Multivariable and mediation MR revealed that systolic blood pressure (Mediation effect: 7.52%, P = 0.02) and total testosterone (Mediation effect: 10.79%, P = 0.01) partly mediated this relationship. No causal links were found between other lipid traits and EMS (P > 0.05 & PFDR > 0.05). In EAS ancestry, no causal relationships with EMS were detected (P > 0.05 & PFDR > 0.05). Drug-target MR indicated suggestive evidence for the influence of ANGPTL3 on EMS mediated through TG (OR = 0.798, 95% CI 0.670-0.951, P = 0.01, PFDR = 0.04, PP.H4 = 0.85%).

CONCLUSIONS

This MR study in EUR ancestry indicated an increased EMS risk with higher serum TG levels.