Discovery and refinement of loci associated with lipid levels

Genetically Proxied Therapeutic Effect of Lipid-Lowering Drugs Use, Breast Cancer, and Endometrial Cancer's Risk: A Drug Target-Based Mendelian Randomization Study

Background

Observational studies have investigated the association between lipid-lowering drugs and breast cancer (BC) and endometrial cancer (EC), but some controversy remains.

Objective

This paper aims to explore the causal relationship between genetic proxies for lipid-lowering drugs and breast and endometrial cancers using drug-target Mendelian randomization (MR).

Methods

Analyses were mainly performed using inverse variance weighted (IVW), heterogeneity and horizontal pleiotropy tests, and sensitivity analysis to assess the robustness of the results and causal relationship.

Results

HMGCR, APOB, and NPC1L1 increased the risk of breast cancer, LPL increased the risk of endometrial cancer, and APOC3 decreased the risk of breast and endometrial cancer. No heterogeneity or horizontal pleiotropy was detected, and nor was there any evidence of an association between other lipid-lowering drugs and breast and endometrial cancer.

Conclusion

Our study demonstrated genetically that HMGCR inhibition, APOB inhibition, and NPC1L1 inhibition decrease the risk of breast cancer, LPL agonist increases the risk of endometrial cancer, and APOC3 inhibition decreases the risk of breast cancer and endometrial cancer, and these findings provide genetic insights into the potential risks of lipid-lowering drug therapy.

Nutritional Genomics: Implications for Age-Related Macular Degeneration

Background: Age-related macular degeneration (AMD) is a leading cause of vision loss in older individuals, driven by a multifactorial etiology involving genetic, environmental, and dietary factors. Nutritional genomics, which studies gene-nutrient interactions, has emerged as a promising field for AMD prevention and management. Genetic predispositions, such as variants in CFH, C3, C2/CFB, APOE, and oxidative stress pathways, significantly affect the risk and progression of AMD. Methods: This narrative review synthesizes findings from randomized controlled trials and recent advances in nutritional genomics research. It examines the interplay between genetic predispositions and dietary interventions, exploring how personalized nutritional strategies can optimize AMD management. Results and Discussion: The AREDS and AREDS2 trials demonstrated that supplements, including vitamins C, E, zinc, copper, lutein, and zeaxanthin, can reduce the progression to advanced AMD. Nutritional interventions tailored to genetic profiles show promise: CFH risk alleles may enhance zinc supplementation's anti-inflammatory effects, while APOE variants influence the response to omega-3 fatty acids. Adjusting carotenoid intake, such as lutein and zeaxanthin, based on genetic susceptibility exemplifies emerging precision nutritional approaches. Ongoing research seeks to integrate nutrigenomic testing into clinical settings, enabling clinicians to tailor interventions to individual genetic profiles. Conclusions: Further studies are needed to assess the long-term effects of personalized interventions, investigate additional genetic variants, and develop tools for clinical implementation of nutrigenomics. Advancing these strategies holds the potential to improve patient outcomes, optimize AMD management, and pave the way for precision nutrition in ophthalmology.

Novel Insights into Causal Effects of Lipid and Lipid-Lowering Targets with Autoimmune Thyroid Disease: A Mendelian Randomization Study

Background

Dyslipidemia has been implicated in the pathogenesis of several diseases, including thyroid dysfunction and immune disorders. However, whether circulating lipids and long-term use of lipid-lowering drugs influence the development of autoimmune thyroid disease (AITD) remains unclear. This study aims to evaluate the effects of lipid-lowering drugs on AITD and explore their potential mechanisms.

Methods

Two-sample and two-step Mendelian randomization (MR) studies were performed to assess the causal relationships between circulating lipids (LDL-C, TC, TG, and ApoB) and seven lipid-lowering drug targets (ApoB, CETP, HMGCR, LDLR, NPC1L1, PCSK9, and PPARα) with AITD. Mediation analyses were conducted to explore potential mediating factors.

Results

There was no clear causality between circulating lipids (ApoB, LDL-C, TC, and TG) and AITD (p > 0.05). ApoB inhibition is related to a reduced risk of autoimmune thyroiditis (AT) (OR = 0.462, p= 0.046), while PCSK9 inhibition is related to reduced Graves' disease (GD) risk (OR = 0. 551, p = 0.033). Moreover, PCSK9 inhibition (OR = 0.735, p = 0.003), LDLR inhibition (OR = 0.779, p = 0.027), and NPC1L1 inhibition (OR = 0.599, p = 0.016) reduced the risk of autoimmune hypothyroidism (AIH). Mediation analysis showed that NPC1L1 inhibition and PCSK9 inhibition exerted effects on AIH through IL-4 and FGF-19 levels. And the effect of PCSK9 inhibition on GD through TNF-β levels.

Conclusion

There was no clear causality between circulating lipids (ApoB, LDL-C, TC, and TG) and AITD. Lipid-lowering drug target gene inhibitors reduced the AITD risk by modulating inflammatory factors.

Evidence of a Causal Relationship Between Body Mass Index and Immune-Mediated and Inflammatory Skin Diseases and Biomarkers: A Mendelian Randomization Study

Aim

Increasing observational studies are revealing a positive correlation between body mass index (BMI) and the risk of Immune-mediated and Inflammatory Skin Diseases (IMID), however the causal relationship is not yet definite.

Objective

The aim of the study was to conduct a two-sample Mendelian randomization (TSMR) to explore the potential causality between BMI, and IMID and biomarkers.

Methods

The summary statistics for BMI (n = 322,154), at genome-wide significant level, were derived from the Genetic Investigation of Anthropometric Traits consortium (GIANT). The outcome data for IMID (Psoriasis, vitiligo, Atopic dermatitis (AD), acne, Bullous diseases, Dermatitis herpetiformis, Systemic lupus erythematosus (SLE), Alopecia Areata (AA), Hidradenitis suppurativa (HS) and Systemic sclerosis), and biomarkers were obtained from genome-wide association studies (GWAS). The TSMR analyses were performed in four methods, including inverse variance weighted (IVW) method, MR-Egger regression, the weighted median estimator (WME) and simple mode.

Results

The IVW analysis showed that the per standard deviation (SD) increase in BMI increased a 57% risk of psoriasis. We also observed the suggestive evidence of a causal relationship between BMI and AD and HS. This analysis did not support causality of Vitiligo, Acne, Bullous pemphigoid, Dermatitis herpetiformis, SLE, AA and Systemic sclerosis. The higher risk of BMI may be explained by higher levels of Triglycerides, C-reactive protein (CRP), Interleukin 6, Erythrocyte sedimentation rate (ESR) and Neutrophil count. The high-density lipoprotein (HDL) has an inverse relationship with BMI. No influences were defined for Total cholesterol, low-density lipoprotein (LDL), Rheumatoid factor (RF), Basophil count and Eosinophil count.

Conclusion

Our two-sample MR analysis proved the causal evidence for the associations between BMI and IMID, including psoriasis, AD and HS, which might be related to the elevated expression of biomarkers, including Triglycerides, CRP, Interleukin 6, ESR and neutrophil count.

Associations Between Gene Variants of Lipid-Lowering Drug Targets and Adverse Outcomes After Ischemic Stroke

BACKGROUND

The association of lipid-lowering drug targets and their gene variants with cardiovascular diseases has been previously clarified. However, the relationship between gene variants of lipid-lowering drug targets and the adverse prognosis of ischemic stroke patients remains unclear.

METHODS AND RESULTS

Multiple single-nucleotide polymorphisms associated with 6 lipid-lowering drug targets were genotyped for patients with ischemic stroke. The primary outcome was death or major disability within 2 years after ischemic stroke. Genetic risk score was constructed from significant single-nucleotide polymorphisms identified via additive models, which was calculated by multiplying the number of risk alleles at each locus by the corresponding beta coefficient and then summing the products. The rs2006760-C of the HMGCR, rs11206510-T of PCSK9, and rs1864163-G and rs9929488-G of CETP were associated with increased odds of adverse outcomes within 2 years after ischemic stroke. Each additional risk allele was associated with higher odds of adverse outcomes. Genetic risk score was positively associated with the odds of primary outcome (odds ratio [OR], 1.48 [95% CI, 1.15-1.90]; Ptrend = 0.001), major disability (OR, 1.56 [95% CI, 1.16-2.08]; Ptrend = 0.002), death (hazard ratio [HR], 1.58 [95% CI, 1.12-2.25]; Ptrend = 0.011), and the composite outcome of death or cardiovascular events (HR, 1.41 [95% CI, 1.08-1.85]; Ptrend = 0.010) when 2 extreme quartiles were compared.

CONCLUSIONS

rs2006760-C of HMGCR, rs11206510-T of PCSK9, and rs1864163-G and rs9929488-G of CETP were associated with increased odds of adverse outcomes within 2 years after ischemic stroke. Furthermore, higher GRS was positively related to the odds of poor outcomes in patients with ischemic stroke. Registration: URL: https://www.clinicaltrials.gov; Identifier: NCT01840072.

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

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

Causal Pathways Between Breast Cancer and Cardiovascular Disease Through Mediator Factors: A Two-Step Mendelian Randomization Analysis

Background

The causal relationship of breast cancer (BC) with cardiovascular disease (CVD) and the underlying mediating pathways remains elusive. Our study endeavors to investigate the causal association between BC and CVD, with a focus on identifying potential metabolic mediators and elucidating their mediation effects in this causality.

Methods

In this study, we conducted two-sample Mendelian randomization (MR) to estimate the causal effect of BC (overall BC, ER+ BC, ER- BC) from the Breast Cancer Association Consortium (BCAC) on CVD including coronary heart disease (CHD), hypertensive heart disease (HHD), ischaemic heart disease (IHD), and heart failure (HF) from the FinnGen consortium. Then, we used two-step MR to evaluate 18 metabolic mediators of the association and calculate the mediated proportions.

Results

Genetically predicted ER+ BC was causally associated with an increased risk of CVD including CHD (OR = 1.034, 95% CI: 1.004-1.065, p = 0.026), HHD (OR = 1.061, 95% CI: 1.002-1.124, p = 0.041), IHD (OR = 1.034, 95% CI: 1.007-1.062, p=0.013), and HF (OR = 1.055, 95% CI: 1.013-1.099, p = 0.010), while no causality was observed for overall BC and ER- BC. Furthermore, high-density lipoprotein cholesterol (HDL-C) was identified as a mediator of the association between ER+BC and CVD, including CHD (with 15.2% proportion)) and IHD (with 15.5% proportion), respectively.

Conclusion

This study elucidates the potential causal impact of ER+ BC on subsequent risk of CVD, including CHD, HHD, IHD, and HF. We also outline the metabolic mediator HDL-C as a priority target for preventive measures to reduce excessive risk of CVD among patients diagnosed with ER+BC.

Lipid-associated GWAS loci as important markers of the risk, severity, and clinical course of peripheral artery disease

BACKGROUND

This study investigated the relationship between lipid-associated loci identified through genome-wide association studies (GWAS) and the risk of peripheral artery disease (PAD), its severity, as well as clinical and laboratory features.

RESEARCH DESIGN AND METHODS

A study included 1263 unrelated Russian subjects, consisting of 620 patients diagnosed with PAD and 643 healthy controls. Thirteen single nucleotide polymorphisms (SNP) were genotyped using the MassArray-4 system.

RESULTS

Polymorphisms rs1689800, rs55730499 and rs881844 were found to be associated with an increased risk of PAD, whereas SNPs rs1883025, rs3136441, rs3764261 and rs6065906 showed protective effects against disease (Pperm ≤ 0.05). SNPs rs1689800, rs217406, rs1883025, and rs3136441 exhibited combined effects with cigarette smoking on the PAD risk (Pperm ≤ 0.05). Polymorphisms rs55730499 (beta = 0.124, Pperm = 0.04), rs9987289 (beta = 0.558, Pperm = 0.03), and rs881844 beta = -0.171, Pperm = 0.03) correlated with the ankle-brachial index. Multiple associations have been found between the SNPs and clinically significant characteristics, including disease severity, risk of gangrene, early disease onset, plasma procoagulant and atherogenic lipid changes (Pperm ≤ 0.05).

CONCLUSIONS

We identified novel genetic markers associated with PAD susceptibility and disease-related clinical and laboratory features. The identified biomarkers enhance the potential for predictive genetic testing related to the risk and progression of PAD, facilitating the integration of molecular diagnostics into clinical decision-making processes.

The impact of statin use on sepsis mortality

BACKGROUND

Statins exert pleiotropic anti-inflammatory and antioxidant effects in addition to their cholesterol-lowering properties. This study aimed to investigate whether statin use is associated with improved outcomes of sepsis.

METHODS

Data from patients with sepsis were extracted from the Medical Information Mart for Intensive Care IV database. Patients with a history of receiving prescriptions for statins (i.e., atorvastatin, lovastatin, pitavastatin, pravastatin, rosuvastatin, or simvastatin) were matched with non-users using propensity-score matching, to balance confounding factors between the groups. Mendelian randomization (MR) analyses were performed using information from the UK Biobank dataset to explore the potential causal link between low-density lipoprotein cholesterol (LDL-C) levels and LDL-C lowering effects via genetically inhibiting β‑hydroxy β-methylglutaryl-coenzyme A reductase and the susceptibility to sepsis, and the sepsis-related 28-day mortality.

MAIN RESULTS

90-day mortality rate was lower among the 10,323 statin users when compared to matched non-users [hazard ratio (HR): 0.612, 95% CI: 0.571 to 0.655]. In-hospital mortality was also lower for statin users compared to non-users (11.3% vs. 17.8%, p < 0.0001, HR: 0.590, 95% CI: 0.548 to 0.634). Statin use was associated with better outcome in all investigated subpopulations apart from patients with severe liver disease. MR analyses further pointed toward pleiotropic effects beyond lipid-lowering effects of statins on sepsis-related outcomes.

CONCLUSIONS

Statin use is associated with improved outcomes following sepsis-related intensive care unit (ICU) admission, most likely from its pleiotropic properties, characterized by lower 90-day and in-hospital mortality among statin users.

MR Corge: sensitivity analysis of Mendelian randomization based on the core gene hypothesis for polygenic exposures

SUMMARY

Mendelian randomization is being utilized to assess causal effects of polygenic exposures, where many genetic instruments are subject to horizontal pleiotropy. Existing methods for detecting and correcting for horizontal pleiotropy have important assumptions that may not be fulfilled. Built upon the core gene hypothesis, we developed MR Corge for performing sensitivity analysis of Mendelian randomization. MR Corge identifies a small number of putative core instruments that are more likely to affect genes with a direct biological role in an exposure and obtains causal effect estimates based on these instruments, thereby reducing the risk of horizontal pleiotropy. Using positive and negative controls, we demonstrated that MR Corge estimates aligned with established biomedical knowledge and the results of randomized controlled trials. MR Corge may be widely applied to investigate polygenic exposure-outcome relationships.

AVAILABILITY AND IMPLEMENTATION

An open-sourced R package is available at https://github.com/zhwm/MRCorge.

Beyond conventional treatment: ASGR1 Leading the new era of hypercholesterolemia management

Cardiovascular disease (CVD) remains a leading cause of mortality worldwide, with hypercholesterolemia being a major risk factor. Although various lipid-lowering therapies exist, many patients fail to achieve optimal cholesterol control, highlighting the need for novel therapeutic approaches. ASGR1 (asialoglycoprotein receptor 1), predominantly expressed on hepatocytes, has emerged as a key regulator of cholesterol metabolism and low-density lipoprotein (LDL) clearance. This receptor's ability to regulate lipid homeostasis positions it as a promising target for therapeutic intervention in hypercholesterolemia and related cardiovascular diseases. This review critically examines the biological functions and regulatory mechanisms of ASGR1 in cholesterol metabolism, with a focus on its potential as a therapeutic target for hypercholesterolemia and related cardiovascular diseases. By analyzing recent advances in ASGR1 research, this article explores its role in liver-specific pathways, the implications of ASGR1 variants in CVD risk, and the prospects for developing ASGR1-targeted therapies. This review aims to provide a foundation for future research and clinical applications in hypercholesterolemia management.

TM6SF2 -rs58542926 Genotype Has Opposing Effects on Incidence of Hepatic and Cardiac Events in a Community Cohort

INTRODUCTION

TM6SF2 -rs58542926-T is associated with increased cirrhosis and modestly decreased coronary artery disease prevalence. However, relative effects of TM6SF2 genotype on major adverse cardiovascular events (MACE) vs liver-related events (LRE) are not known.

METHODS

We used the UK Biobank, a prospective cohort with genetic and inpatient diagnosis data. The primary predictor was TM6SF2 -rs58542926 genotype, and the primary outcomes were MACE and LRE. Effects were reported as subhazard ratios (sHRs) and 10-year cumulative incidence by Fine-Gray competing risk analyses.

RESULTS

More than 430,000 individuals met inclusion criteria. TM6SF2 -rs58542926-TT genotype (vs CC) was associated with higher incidence of LRE (adjusted sHR 3.16, 95% confidence interval 1.86-5.37) and lower incidence of MACE (adjusted sHR for TT vs CC genotype 0.76, 95% confidence interval 0.63-0.91). In individuals with fibrosis-4 (FIB4) < 1.3, 1.3-2.67, and > 2.67, 10-year LRE incidence in TM6SF2 -rs58542926-TT vs CC individuals was 0.08% vs 0.06% ( P > 0.05), 0.81% vs 0.20% ( P < 0.0001), and 10.5% vs 3.4% ( P = 0.00094), respectively. The corresponding values for MACE were 3.8% vs 5.1% ( P = 0.032), 6.4% vs 8.2% ( P = 0.040), and 17.1% vs 12.4% ( P > 0.05). The absolute decrease in MACE with rs58542926-TT (vs CC) genotype exceeded the absolute increase in LRE in all groups but FIB4 > 2.67. Associations of TM6SF2 genotype with LRE/MACE were significant in men but not women. TM6SF2 -rs58542926-T allele was also associated with increased hepatic steatosis and corrected T1 time by magnetic resonance imaging, with greater effect sizes in men than women.

DISCUSSION

TM6SF2 genotype has opposite effects on LRE vs MACE incidence, and absolute effects on MACE were greater except in those with highest FIB4 scores. Effects were strongest in men. These findings clarify implications of TM6SF2 genotype based on personalized clinical risk.

Association of lipid levels, adipokines and multiple myeloma: a two-sample multivariate Mendelian randomization study

Many observational studies and experiments have found a strong association between lipid levels and adipokines and multiple myeloma (MM), but the causal relationship between lipid levels, adipokines and MM remains to be determined. We performed a two-sample and multivariate MR analysis to investigate the causal relationship between lipid levels, adipokines and MM. Total cholesterol(TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG) were used to represent lipid levels, and adiponectin, leptin, and resistin were used to represent adipokines. Genetic data for each index and MM were obtained from the Integrated Epidemiology Unit (IEU) Genome-Wide Association Study (GWAS) database, and two-sample MR analyses were performed, as well as multivariate MR analyses of adipokines for causality of MM using BMI as an adjusting factor. In the analyzed results, no significant causal association was found between adipokines, lipid levels and multiple myeloma, and after adjusting for BMI, an association between adipokines and MM was still not found. The results of this MR study do not support an association between genetically predicted adipokines, lipid levels, and risk of MM, but we cannot rule out the existence of a weak association. The mechanisms need to be further investigated.

Leisure screen time and diabetic retinopathy risk: A Mendelian randomization study

The aim of this study was to investigate whether leisure screen time (LST) increases the risk of diabetic retinopathy (DR) using the Mendelian randomization (MR). This study employed a two-sample MR analysis, utilizing 63 single-nucleotide polymorphisms as instrumental variables (IVs) to assess the causal relationship between LST and the risk of Dr. To ensure the robustness of the results, a multi-effect test was conducted to evaluate the validity of the IVs. Additionally, heterogeneity tests were performed to explore differences among sub-samples. Sensitivity analyses were also conducted to further validate our findings. The impact of LST on the risk of DR was observed in both inverse variance weighted (odds ratio [OR]: 1.22, 95% confidence interval [CI]: 1.04-1.43, P = 1.38 × 10-2) and weighted median (OR: 1.30, 95% CI: 1.05-1.61, P = 1.46 × 10-2) analyses. However, the MR-Egger method (OR: 0.66, 95% CI: 0.32-1.36, P = .273) did not find an increased risk of DR with increased LST. The pleiotropy test yielded a P-value of P = .09. Heterogeneity tests showed that the Q value for the inverse variance weighted method was 71.39 with a P-value of 0.17, indicating no significant heterogeneity. These results suggest that the IVs might be appropriate, and the analysis results could be robust. A large-scale MR analysis suggests a causal relationship between LST and the risk of Dr.

Assessing the effects of HMGCR, LPL, and PCSK9 inhibition on sleep apnea: Mendelian randomization analysis of drug targets

To investigate the use of lipid-lowering drugs and abnormal serum lipid levels in patients at risk of sleep apnea syndrome. Three types of Mendelian randomization (MR) analyses were used. First, a 2-sample Mendelian randomization (TSMR) analysis was used to investigate the association between sleep apnea syndrome risk and serum lipid levels. Multivariate Mendelian randomization (MVMR) analysis was subsequently used to investigate the effects of confounding variables on SAS incidence of sleep apnea syndrome. Finally, drug-target Mendelian randomization (DMR) analysis was used to analyze the association between lipid-lowering drug use and sleep apnea syndrome risk. According to the TSMR analysis, the serum HDL-C concentration was negatively correlated with sleep apnea syndrome (OR = 0.904; 95% CI = 0.845-0.967; P = .003). Serum TG levels were positively correlated with sleep apnea syndrome (OR = 1.081; 95% CI = 1.003-1.163; P = .039). The association between serum HDL-C levels and sleep apnea syndrome in patients with MVMR was consistent with the results in patients with TSMR (OR = 0.731; 95% CI = 0.500-1.071; P = 3.94E-05). According to our DMR analysis, HMGCR and PCSK9, which act by lowering serum LDL-C levels, were inversely associated with the risk of sleep apnea syndrome (OR = 0.627; 95% CI = 0.511-0.767; P = 6.30E-06) (OR = 0.775; 95% CI = 0.677-0.888; P = .0002). LPL, that lowered serum TG levels, was positively associated with the risk of sleep apnea syndrome (OR = 1.193; 95% CI = 1.101-1.294; P = 1.77E-05). Our analysis suggested that high serum HDL-C levels may reduce the risk of sleep apnea syndrome. Low serum TG levels have a protective effect against sleep apnea syndrome. The DMR results suggested that the use of HMGCR lipid-lowering drugs (such as statins) and PCSK9 inhibitors has a protective effect against sleep apnea syndrome. However, LPL-based lipid-lowering drugs may increase the risk of sleep apnea syndrome.

Identification of Genetic Loci Associated With Intracerebral Hemorrhage Using a Multitrait Analysis Approach

BACKGROUND AND OBJECTIVES

Genome-wide association studies (GWASs) have only 2 loci associated with spontaneous intracerebral hemorrhage (ICH): APOE for lobar and 1q22 for nonlobar ICH. We aimed to discover new loci through an analysis that combines correlated traits (multi-trait analysis of GWAS [MTAG]) and explore a gene-based analysis, transcriptome-wide association study (TWAS), and proteome-wide association study (PWAS) to understand the biological mechanisms of spontaneous ICH providing potential therapeutic targets.

METHODS

We use the published MTAG of ICH (patients with spontaneous intraparenchymal bleeding) and small-vessel ischemic stroke. For all ICH, lobar ICH, and nonlobar ICH, a pairwise MTAG combined ICH with traits related to cardiovascular risk factors, cerebrovascular diseases, or Alzheimer disease (AD). For the analysis, we assembled those traits with a genetic correlation ≥0.3. A new MTAG combining multiple traits was performed with those traits whose pairwise MTAG yielded new GWAS-significant single nucleotide polymorphisms (SNPs), with a posterior-probability of model 3 (GWAS-pairwise) ≥0.6. We perform TWAS and PWAS that correlate the genetic component of expression or protein levels with the genetic component of a trait. We use the ICH cohort from UK Biobank as replication.

RESULTS

For all ICH (1,543 ICH, 1,711 controls), the mean age was 72 ± 2 in cases and 70 ± 2 in controls, and half of them were women. Replication cohort: 700 ICH and 399,717 controls. Novel loci were found only for all ICH (the trait containing lobar and nonlobar ICH), combining data of ICH and small vessel stroke, white matter hyperintensities volume, fractional anisotropy, mean diffusivity, and AD. We replicated 6 SNPs belonging to 2q33.2 (ICA1L, β = 0.20, SE = 0.03, p value = 8.91 × 10-12), 10q24.33 (OBFC1, β = -0.12, SE = 0.02, p value = 1.67 × 10-8), 13q34 (COL4A2, β = 0.02, SE = 0.02, p value = 2.34 × 10-11), and 19q13.32 (APOC1, β = -0.19, SE = 0.03, p value = 1.38 × 10-12; APOE, β = 0.21, SE = 0.03, p value = 2.70 × 10-11; PVRL2:CTB-129P6.4, β = 0.15, SE = 0.03, p value = 1.38 × 10-8); 2 genes (SH3PXD2A, Z-score = 4.83, p value = 6.67 × 10-7; and APOC1, Z-score: = 5.11, p value = 1.60 × 10-7); and ICA1L transcript (Z-score = 6.8, p value = 9.1 × 10-12) and protein levels (Z-score = -5.8, p value = 6.7 × 10-9).

DISCUSSION

Our results reinforce the role of APOE in ICH risk, replicate previous ICH-associated loci (2q33 and 13q34), and point to new ICH associations with OBFC1, PVRL2:CTB-129P6.4, APOC1, and SH3PXD2A. Our study used data from European subjects, our main limitation. These molecules could be potential targets for future studies for modulating ICH risk.

Analyses of GWAS signal using GRIN identify additional genes contributing to suicidal behavior

Genome-wide association studies (GWAS) identify genetic variants underlying complex traits but are limited by stringent genome-wide significance thresholds. We present GRIN (Gene set Refinement through Interacting Networks), which increases confidence in the expanded gene set by retaining genes strongly connected by biological networks when GWAS thresholds are relaxed. GRIN was validated on both simulated interrelated gene sets as well as multiple GWAS traits. From multiple GWAS summary statistics of suicide attempt, a complex phenotype, GRIN identified additional genes that replicated across independent cohorts and retained biologically interrelated genes despite a relaxed significance threshold. We present a conceptual model of how these retained genes interact through neurobiological pathways that may influence suicidal behavior, and identify existing drugs associated with these pathways that would not have been identified under traditional GWAS thresholds. We demonstrate GRIN's utility in boosting GWAS results by increasing the number of true positive genes identified from GWAS results.

GWAS-by-subtraction reveals an IOP-independent component of primary open angle glaucoma

The etiology of primary open angle glaucoma is constituted by both intraocular pressure-dependent and intraocular pressure-independent mechanisms. However, GWASs of traits affecting primary open angle glaucoma through mechanisms independent of intraocular pressure remains limited. Here, we address this gap by subtracting the genetic effects of a GWAS for intraocular pressure from a GWAS for primary open angle glaucoma to reveal the genetic contribution to primary open angle glaucoma via intraocular pressure-independent mechanisms. Seventeen independent genome-wide significant SNPs were associated with the intraocular pressure-independent component of primary open angle glaucoma. Of these, 7 are located outside known normal tension glaucoma loci, 11 are located outside known intraocular pressure loci, and 2 are novel primary open angle glaucoma loci. The intraocular pressure-independent genetic component of primary open angle glaucoma is associated with glaucoma endophenotypes, while the intraocular pressure-dependent component is associated with blood pressure and vascular permeability. A genetic risk score for the intraocular pressure-independent component of primary open angle glaucoma is associated with 26 different retinal micro-vascular features, which contrasts with the genetic risk score for the intraocular pressure-dependent component. Increased understanding of these intraocular pressure-dependent and intraocular pressure-independent components provides insights into the pathogenesis of glaucoma.

HMGCR as a promising molecular target for therapeutic intervention in aortic aneurisms: a mendelian randomization study

BACKGROUND

Despite the exploration of the connections between serum low-density lipoprotein cholesterol (LDL-C) levels and aneurisms in epidemiological studies, causality remains unclear. Therefore, this study aimed to assess the causal impact of LDL-C-lowering targets (HMGCR, PCSK9, NPC1L1, CETP, APOB, and LDLR) on various forms of aneurisms using Mendelian Randomization (MR) analysis.

METHODS

Two genetic instruments acted as proxies for exposure to LDL-C-lowering drugs: expression quantitative trait loci of drug target genes and genetic variants linked to LDL-C near drug target genes. Summary-data-based MR (SMR), inverse-variance-weighted MR (IVW-MR), and multivariable MR (MVMR) methods were employed to compute the effect estimates.

RESULTS

The SMR analysis revealed substantial associations between increased HMGCR expression and a heightened risk of aortic aneurism (odds ratio [OR] = 1.603, 95% confidence interval [CI] = 1.209-2.124), thoracic aortic aneurism (OR = 1.666, 95% CI = 1.122-2.475), and abdominal aortic aneurism (OR = 1.910, 95% CI = 1.278-2.856). Likewise, IVW-MR analysis demonstrated positive correlations between HMGCR-mediated LDL-C and aortic aneurism (OR = 2.228, 95% CI = 1.702-2.918), thoracic aortic aneurism (OR = 1.751, 95% CI = 1.191-2.575), abdominal aortic aneurism (OR = 4.784, 95% CI = 3.257-7.028), and cerebral aneurism (OR = 1.993, 95% CI = 1.277-3.110). Furthermore, in the MVMR analysis, accounting for body mass index, smoking, and hypertension, a significant positive relationship was established between HMGCR-mediated LDL-C levels and the development of aortic aneurisms, encompassing both thoracic and abdominal subtypes. Similarly, consistent positive associations were observed for PCSK9 and CETP genes, as well as PCSK9-mediated and CETP-mediated LDL-C levels, with the occurrence of aortic aneurism and abdominal aortic aneurism. Nonetheless, the evidence for potential associations between APOB, NPC1L1 and LDLR with specific subtypes of aortic aneurisms lacked consistent support from both SMR and IVW-MR analyses.

CONCLUSIONS

Our MR analysis offered compelling evidence of a plausible causal link between HMGCR and an increased risk of aortic aneurism, encompassing both thoracic and abdominal types. These groundbreaking findings further bolster the case for the deployment of HMGCR inhibitors in the treatment of aortic aneurisms, including both thoracic and abdominal variants.

Genetic analyses of 104 phenotypes in 20,900 Chinese pregnant women reveal pregnancy-specific discoveries

Monitoring biochemical phenotypes during pregnancy is vital for maternal and fetal health, allowing early detection and management of pregnancy-related conditions to ensure safety for both. Here, we conducted a genetic analysis of 104 pregnancy phenotypes in 20,900 Chinese women. The genome-wide association study (GWAS) identified a total of 410 trait-locus associations, with 71.71% reported previously. Among the 116 novel hits for 45 phenotypes, 83 were successfully replicated. Among them, 31 were defined as potentially pregnancy-specific associations, including creatine and HELLPAR and neutrophils and ESR1, with subsequent analysis revealing enrichments in estrogen-related pathways and female reproductive tissues. The partitioning heritability underscored the significant roles of fetal blood, embryoid bodies, and female reproductive organs in pregnancy hematology and birth outcomes. Pathway analysis confirmed the intricate interplay of hormone and immune regulation, metabolism, and cell cycle during pregnancy. This study contributes to the understanding of genetic influences on pregnancy phenotypes and their implications for maternal health.

Mapping biological influences on the human plasma proteome beyond the genome

Broad-capture proteomic platforms now enable simultaneous assessment of thousands of plasma proteins, but most of these are not actively secreted and their origins are largely unknown. Here we integrate genomic with deep phenomic information to identify modifiable and non-modifiable factors associated with 4,775 plasma proteins in ~8,000 mostly healthy individuals. We create a data-driven map of biological influences on the human plasma proteome and demonstrate segregation of proteins into clusters based on major explanatory factors. For over a third (N = 1,575) of protein targets, joint genetic and non-genetic factors explain 10-77% of the variation in plasma (median 19.88%, interquartile range 14.01-31.09%), independent of technical factors (median 2.48%, interquartile range 0.78-6.41%). Together with genetically anchored causal inference methods, our map highlights potential causal associations between modifiable risk factors and plasma proteins for hundreds of protein-disease associations, for example, COL6A3, which possibly mediates the association between reduced kidney function and cardiovascular disease. We provide a map of biological and technical influences on the human plasma proteome to help contextualize findings from proteomic studies.

Hierarchical joint analysis of marginal summary statistics-Part II: High-dimensional instrumental analysis of omics data

Instrumental variable (IV) analysis has been widely applied in epidemiology to infer causal relationships using observational data. Genetic variants can also be viewed as valid IVs in Mendelian randomization and transcriptome-wide association studies. However, most multivariate IV approaches cannot scale to high-throughput experimental data. Here, we leverage the flexibility of our previous work, a hierarchical model that jointly analyzes marginal summary statistics (hJAM), to a scalable framework (SHA-JAM) that can be applied to a large number of intermediates and a large number of correlated genetic variants-situations often encountered in modern experiments leveraging omic technologies. SHA-JAM aims to estimate the conditional effect for high-dimensional risk factors on an outcome by incorporating estimates from association analyses of single-nucleotide polymorphism (SNP)-intermediate or SNP-gene expression as prior information in a hierarchical model. Results from extensive simulation studies demonstrate that SHA-JAM yields a higher area under the receiver operating characteristics curve (AUC), a lower mean-squared error of the estimates, and a much faster computation speed, compared to an existing approach for similar analyses. In two applied examples for prostate cancer, we investigated metabolite and transcriptome associations, respectively, using summary statistics from a GWAS for prostate cancer with more than 140,000 men and high dimensional publicly available summary data for metabolites and transcriptomes.

NPC1L1 rs217434 A > G as a Novel Single Nucleotide Polymorphism Related to Dyslipidemia in a Korean Population

A relationship between cholesterol levels and Niemann-Pick C1-Like 1 (NPC1L1) polymorphisms in diverse populations was found in previous studies. However, relevant research on this association in the Korean population is relatively scarce. Therefore, the current study sought to examine the correlation between the NPC1L1 rs217434 A > G polymorphism and clinical as well as biochemical variables pertaining to dyslipidemia in the Korean population. This cross-sectional single-center study included 1404 Korean subjects aged 20-86 years, grouped based on dyslipidemia presence (normal and dyslipidemia) and genotype (AA or AG). After adjusting for sex and age, it was discovered that the dyslipidemia group's BMI, diastolic blood pressure, glucose-related indicators, lipid profile, high-sensitivity C-reactive protein (hs-CRP), and parameters of oxidative stress were considerably different from the normal group's values. When grouped according to genotype, individuals in the AG group exhibited greater total cholesterol, low-density lipoprotein cholesterol, hs-CRP, and 8-epi-prostaglandin F2α in comparison to those in the AA group. Moreover, individuals with dyslipidemia and the AG genotype exhibited unfavorable outcomes for lipid profiles, markers related to glucose and inflammation, and markers of oxidative stress. This study provided evidence for a relationship between the NPC1L1 rs217434 A > G genotype and dyslipidemia in the Korean population, which highlights the potential of the NPC1L1 rs217434 A > G genotype as an early predictor of dyslipidemia.

Causal effects of cardiovascular health on five epigenetic clocks

BACKGROUND

This work delves into the relationship between cardiovascular health (CVH) and aging. Previous studies have shown an association of ideal CVH with a slower aging rate, measured by epigenetic age acceleration (EAA). However, the causal relationship between CVH and EAA has remained unexplored.

METHODS AND RESULTS

We performed genome-wide association studies (GWAS) on the (12-point) CVH score and its components using the Taiwan Biobank data, in which weighted genetic risk scores were treated as instrumental variables. Subsequently, we conducted a one-sample Mendelian Randomization (MR) analysis with the two-stage least-squares method on 2383 participants to examine the causal relationship between the (12-point) CVH score and EAA. As a result, we observed a significant causal effect of the CVH score on GrimAge acceleration (GrimEAA) (β [SE]: - 0.993 [0.363] year; p = 0.0063) and DNA methylation-based plasminogen activator inhibitor-1 (DNAmPAI-1) (β [SE]: - 0.294 [0.099] standard deviation (sd) of DNAmPAI-1; p = 0.0030). Digging individual CVH components in depth, the ideal total cholesterol score (0 [poor], 1 [intermediate], or 2 [ideal]) was causally associated with DNAmPAI-1 (β [SE]: - 0.452 [0.150] sd of DNAmPAI-1; false discovery rate [FDR] q = 0.0102). The ideal body mass index (BMI) score was causally associated with GrimEAA (β [SE]: - 2.382 [0.952] years; FDR q = 0.0498) and DunedinPACE (β [SE]: - 0.097 [0.030]; FDR q = 0.0044). We also performed a two-sample MR analysis using the summary statistics from European GWAS. We observed that the (12-point) CVH score exhibits a significant causal effect on Horvath's intrinsic epigenetic age acceleration (β [SE]: - 0.389 [0.186] years; p = 0.036) and GrimEAA (β [SE]: - 0.526 [0.244] years; p = 0.031). Furthermore, we detected causal effects of BMI (β [SE]: 0.599 [0.081] years; q = 2.91E-12), never smoking (β [SE]: - 2.981 [0.524] years; q = 1.63E-7), walking (β [SE]: - 4.313 [1.236] years; q = 0.004), and dried fruit intake (β [SE]: - 1.523 [0.504] years; q = 0.013) on GrimEAA in the European population.

CONCLUSIONS

Our research confirms the causal link between maintaining an ideal CVH and epigenetic age. It provides a tangible pathway for individuals to improve their health and potentially slow aging.

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

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

Lipid levels and multiple myeloma risk: insights from Meta-analysis and mendelian randomization

BACKGROUND

Lipid levels have been suggset to be correlated with multiple myeloma (MM) risk, though causality remains unconfirmed. To explore this further, a detailed study combining meta-analysis and Mendelian randomization (MR) was conducted.

METHODS

Literature searches were performed on PubMed and Embase; summary data for plasma lipid traits were extracted from the IEU and MM data from the FinnGen database. Meta-analysis and MR were utilized to analyze the link of lipids with MM risk, including mediator MR to identify potential mediators. The study was conducted in accordance with PRISMA and STROBE-MR guidelines.

RESULTS

Observational studies analyzed through meta-analysis showed that elevated levels of LDL, HDL, total cholesterol (TC), and triglycerides correlate with a lower risk of MM, with HRs of 0.73, 0.59, 0.60, and 0.84, respectively. MR analysis confirmed a potential causal link of triglyceride with a reduced MM risk (OR: 0.67, 95% CI: 0.46-0.98), independent of BMI. Mediation analysis pointed to X-11,423-O-sulfo-L-tyrosine and neuropilin-2 as potential mediators.

CONCLUSIONS

The findings suggest that higher lipid levels (LDL, HDL, TC, and triglycerides) are linked with a reduced MM risk, and higher triglyceride levels are causally associated with a reduced MM risk. This suggests new avenues for therapeutic interventions targeting MM.

SCAMPI: A scalable statistical framework for genome-wide interaction testing harnessing cross-trait correlations

Family-based heritability estimates of complex traits are often considerably larger than their single-nucleotide polymorphism (SNP) heritability estimates. This discrepancy may be due to non-additive effects of genetic variation, including variation that interacts with other genes or environmental factors to influence the trait. Variance-based procedures provide a computationally efficient strategy to screen for SNPs with potential interaction effects without requiring the specification of the interacting variable. While valuable, such variance-based tests consider only a single trait and ignore likely pleiotropy among related traits that, if present, could improve power to detect such interaction effects. To fill this gap, we propose SCAMPI (Scalable Cauchy Aggregate test using Multiple Phenotypes to test Interactions), which screens for variants with interaction effects across multiple traits. SCAMPI is motivated by the observation that SNPs with pleiotropic interaction effects induce genotypic differences in the patterns of correlation among traits. By studying such patterns across genotype categories among multiple traits, we show that SCAMPI has improved performance over traditional univariate variance-based methods. Like those traditional variance-based tests, SCAMPI permits the screening of interaction effects without requiring the specification of the interaction variable and is further computationally scalable to biobank data. We employed SCAMPI to screen for interacting SNPs associated with four lipid-related traits in the UK Biobank and identified multiple gene regions missed by existing univariate variance-based tests. SCAMPI is implemented in software for public use.

Interaction between genetic risk score and dietary fat intake on lipid-related traits in Brazilian young adults

The occurrence of dyslipidaemia, which is an established risk factor for cardiovascular diseases, has been attributed to multiple factors including genetic and environmental factors. We used a genetic risk score (GRS) to assess the interactions between genetic variants and dietary factors on lipid-related traits in a cross-sectional study of 190 Brazilians (mean age: 21 ± 2 years). Dietary intake was assessed by a trained nutritionist using three 24-h dietary recalls. The high GRS was significantly associated with increased concentration of TAG (beta = 0·10 mg/dl, 95 % CI 0·05-0·16; P < 0·001), LDL-cholesterol (beta = 0·07 mg/dl, 95 % CI 0·04, 0·11; P < 0·0001), total cholesterol (beta = 0·05 mg/dl, 95 % CI: 0·03, 0·07; P < 0·0001) and the ratio of TAG to HDL-cholesterol (beta = 0·09 mg/dl, 95 % CI: 0·03, 0·15; P = 0·002). Significant interactions were found between the high GRS and total fat intake on TAG:HDL-cholesterol ratio (Pinteraction = 0·03) and between the high GRS and SFA intake on TAG:HDL-cholesterol ratio (Pinteraction = 0·03). A high intake of total fat (>31·5 % of energy) and SFA (>8·6 % of energy) was associated with higher TAG:HDL-cholesterol ratio in individuals with the high GRS (beta = 0·14, 95 % CI: 0·06, 0·23; P < 0·001 for total fat intake; beta = 0·13, 95 % CI: 0·05, 0·22; P = 0·003 for SFA intake). Our study provides evidence that the genetic risk of high TAG:HDL-cholesterol ratio might be modulated by dietary fat intake in Brazilians, and these individuals might benefit from limiting their intake of total fat and SFA.

Genetic estimation of causalities between educational attainment with common digestive tract diseases and the mediating pathways

BACKGROUND

The association between education, intelligence, and cognition with digestive tract diseases has been established. However, the specific contribution of each factor in the pathogenesis of these diseases are still uncertain.

METHOD

This study employed multivariable Mendelian randomization (MR) to assess the independent effects of education, intelligence, and cognition on gastrointestinal conditions in the FinnGen and UK Biobank European-ancestry populations. A two-step MR approach was employed to assess the mediating effects of the association.

RESULTS

Meta-analysis of MR estimates from FinnGen and UK Biobank showed that 1- SD (4.2 years) higher education was causally associated with lower risks of gastroesophageal reflux (OR: 0.58; 95% CI: 0.50, 0.66), peptic ulcer (OR: 0.57; 95% CI: 0.47, 0.69), irritable bowel syndrome (OR: 0.70; 95% CI: 0.56, 0.87), diverticular disease (OR: 0.69; 95% CI: 0.61, 0.78), cholelithiasis (OR: 0.68; 95% CI: 0.59, 0.79) and acute pancreatitis (OR: 0.54; 95% CI: 0.41, 0.72), independently of intelligence and cognition. These causal associations were mediating by body mass index (3.7-22.3%), waist-to-hip ratio (8.3-11.9%), body fat percentage (4.1-39.8%), fasting insulin (1.4-5.5%) and major depression (6.0-12.4%).

CONCLUSION

Our findings demonstrate a causal and independent association between education and six common digestive tract diseases. Additionally, our study highlights five mediators as crucial targets for preventing digestive tract diseases associated with lower education levels.

A Large-Scale Genome-Wide Gene-Sleep Interaction Study in 732,564 Participants Identifies Lipid Loci Explaining Sleep-Associated Lipid Disturbances

We performed large-scale genome-wide gene-sleep interaction analyses of lipid levels to identify novel genetic variants underpinning the biomolecular pathways of sleep-associated lipid disturbances and to suggest possible druggable targets. We collected data from 55 cohorts with a combined sample size of 732,564 participants (87% European ancestry) with data on lipid traits (high-density lipoprotein [HDL-c] and low-density lipoprotein [LDL-c] cholesterol and triglycerides [TG]). Short (STST) and long (LTST) total sleep time were defined by the extreme 20% of the age- and sex-standardized values within each cohort. Based on cohort-level summary statistics data, we performed meta-analyses for the one-degree of freedom tests of interaction and two-degree of freedom joint tests of the main and interaction effect. In the cross-population meta-analyses, the one-degree of freedom variant-sleep interaction test identified 10 loci (P int <5.0e-9) not previously observed for lipids. Of interest, the ASPH locus (TG, LTST) is a target for aspartic and succinic acid metabolism previously shown to improve sleep and cardiovascular risk. The two-degree of freedom analyses identified an additional 7 loci that showed evidence for variant-sleep interaction (P joint <5.0e-9 in combination with P int <6.6e-6). Of these, the SLC8A1 locus (TG, STST) has been considered a potential treatment target for reduction of ischemic damage after acute myocardial infarction. Collectively, the 17 (9 with STST; 8 with LTST) loci identified in this large-scale initiative provides evidence into the biomolecular mechanisms underpinning sleep-duration-associated changes in lipid levels. The identified druggable targets may contribute to the development of novel therapies for dyslipidemia in people with sleep disturbances.

The impact of sex hormones on metabolic syndrome: univariable and multivariable Mendelian randomization studies

BACKGROUND

Observational studies have found associations between sex hormones and metabolic syndrome(Mets), but the causal relationships remains unclear. This study utilizes univariable and multivariable Mendelian randomization (MR) to elucidate the associations between sex hormones (including sex hormone-binding globulin(SHBG), estradiol(E2), testosterone(T)) and Mets and its subtypes (including waist circumference(WC), fasting blood glucose(FBG), high blood pressure(HBP), high-density lipoprotein(HDL-C), triglycerides(TG)).

METHODS

We utilized summary data from large-scale genome-wide association studies. Univariable Mendelian randomization (UMVMR) analysis was primarily conducted using the inverse variance weighted method (IVW), with secondary analyses employing the weighted median, MR-Egger regression, simple mode method, and weighted mode method. Subsequently, multivariable Mendelian randomization (MVMR) was employed to assess the causal relationships between SHBG, T, E2, and MetS and its components: WC, FPG, HBP, HDL-C, and TG. Sensitivity analyses were conducted to assess result reliability.

RESULTS

Genetically predicted SHBG was significantly negatively associated with MetS (UMVMR: β=-0.72; 95% CI = 0.41 to 0.57; P = 1.28e-17; MVMR: β=-0.60; 95% CI=-0.83 to -0.38; P < 0.001). Positive causal relationships were observed between SHBG and WC(MVMR: β = 0.10; 95% CI = 0.03 to 0.17; P = 0.01) and HDL-C (MVMR: β = 0.41; 95% CI = 0.21 to 0.60; P < 0.001), while negative causal relationships were found between SHBG and HBP (MVMR: β=-0.02; 95% CI=-0.04 to -0.00; P = 0.02), TG (MVMR: β=-0.48; 95% CI=-0.70 to -0.26; P < 0.001). Genetically predicted E2 exhibited a negative association with TG (MVMR: β=-1.49; 95% CI=-2.48 to -0.50; P = 0.003). Genetically predicted T was negatively associated with TG (MVMR: β=-0.36; 95% CI=-0.71 to -0.00; P = 0.049) and WC (MVMR: β=-0.13; 95% CI=-0.24 to -0.02; P = 0.02), with inconsistent sensitivity analyses. Additionally, No other causal associations were found.

CONCLUSION

Our study indicates that SHBG is a protective factor for MetS, potentially delaying its onset and progression through improvements in HBP and TG. Furthermore, T and E2 may improve TG levels, with T also reducing WC levels. Importantly, our study provides new insights for the prevention and treatment of MetS.

Genetic Association of Lipids and Lipid-Lowering Drug Target Genes With Attention Deficit Hyperactivity Disorder

BACKGROUND

Lipid metabolism plays an essential role in nervous system development. Cholesterol deficiency leads to a variety of neurodevelopmental disorders, such as autism spectrum disorder and fragile X syndrome. There have been a lot of efforts to search for biological markers associated with and causal to ADHD, among which lipid is one possible etiological factor that is quite widely studied. We aimed to evaluate the causal relationship between lipids traits, lipid-lowering drugs, and attention deficit hyperactivity disorder (ADHD) outcomes using Mendelian randomization (MR) studies.

METHODS

We used summary data from genome-wide association studies to explore the causal relationships between circulating lipid-related traits and ADHD. Then, quantitative trait loci for the expression of lipid-lowering drug target genes and genetic variants associated with lipid traits were extracted. Summary-data-based MR and inverse-variance-weighted MR (IVW-MR) were used to investigate the correlation between the expression of these drug-target genes and ADHD.

RESULTS

After rigorous screening, 939 instrumental variables were finally included for univariable mendelian randomization analysis. However, there is no correlation between lipid profile and ADHD risk. Drug target analysis by IVW-MR method observed that APOB-mediated low-density lipoprotein cholesterol was associated with lower ADHD risk (odds ratio [OR] = 0.90, 95% confidence interval [CI] [0.84, 0.97]; p = .007), whereas LPL-mediated triglycerides levels were associated with a higher risk of ADHD (OR = 1.13, 95% CI [1.06, 1.21]; p < .001).

CONCLUSION

Our results suggest that APOB gene and LPL gene may be candidate drug target genes for the treatment of ADHD.

Association of lipid-lowering drugs with gut microbiota: A Mendelian randomization study

BACKGROUND

The gut microbiota can be influenced by lipid metabolism. We aimed to evaluate the impact of lipid-lowering medications, such as proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, Niemann-Pick C1-Like 1 protein (NPC1L1) inhibitors, and 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) inhibitors, on gut microbiota through drug target Mendelian randomization (MR) investigation.

METHODS

We used genetic variants that were associated with low-density lipoprotein cholesterol (LDL-C) in genome-wide association studies and located within or near drug target genes as proxies for lipid-lowering drug exposure. In addition, expression trait loci in drug target genes were used as complementary genetic tools. We used effect estimates calculated using inverse variance weighted MR (IVW-MR) and summary data-based MR (SMR). Multiple sensitivity analyses were performed.

RESULTS

Genetic proxies for lipid-lowering drugs broadly affected the abundance of gut microbiota. High expression of NPC1L1 was significantly associated with an increase in the genus Eggerthella (β = 1.357, SE = 0.337, P = 5.615 × 10-5). An HMGCR-mediated increase in LDL-C was significantly associated with the order Pasteurellales (β = 0.489, SE = 0.123, P = 6.955 × 10-5) and the genus Haemophilus (β = 0.491, SE = 0.125, P = 8.379 × 10-5), whereas a PCSK9-mediated increase in LDL-C was associated with the genus Terrisporobacter (β = 0.666, SE = 0.127, P = 1.649 × 10-5). No pleiotropy was detected.

CONCLUSIONS

This drug target MR highlighted the potential interventional effects of lipid-lowering drugs on the gut microbiota and separately revealed the possible effects of different types of lipid-lowering drugs on specific gut microbiota.

Myelinated peripheral axons are more vulnerable to mechanical trauma in a model of enlarged axonal diameters

The velocity of axonal impulse propagation is facilitated by myelination and axonal diameters. Both parameters are frequently impaired in peripheral nerve disorders, but it is not known if the diameters of myelinated axons affect the liability to injury or the efficiency of functional recovery. Mice lacking the adaxonal myelin protein chemokine-like factor-like MARVEL-transmembrane domain-containing family member-6 (CMTM6) specifically from Schwann cells (SCs) display appropriate myelination but increased diameters of peripheral axons. Here we subjected Cmtm6-cKo mice as a model of enlarged axonal diameters to a mild sciatic nerve compression injury that causes temporarily reduced axonal diameters but otherwise comparatively moderate pathology of the axon/myelin-unit. Notably, both of these pathological features were worsened in Cmtm6-cKo compared to genotype-control mice early post-injury. The increase of axonal diameters caused by CMTM6-deficiency thus does not override their injury-dependent decrease. Accordingly, we did not detect signs of improved regeneration or functional recovery after nerve compression in Cmtm6-cKo mice; depleting CMTM6 in SCs is thus not a promising strategy toward enhanced recovery after nerve injury. Conversely, the exacerbated axonal damage in Cmtm6-cKo nerves early post-injury coincided with both enhanced immune response including foamy macrophages and SCs and transiently reduced grip strength. Our observations support the concept that larger peripheral axons are particularly susceptible toward mechanical trauma.

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.

Genetic association of lipid traits and lipid-related drug targets with normal tension glaucoma: a Mendelian randomization study for predictive preventive and personalized medicine

Background

Glaucoma is the leading cause of irreversible blindness worldwide. Normal tension glaucoma (NTG) is a distinct subtype characterized by intraocular pressures (IOP) within the normal range (< 21 mm Hg). Due to its insidious onset and optic nerve damage, patients often present with advanced conditions upon diagnosis. NTG poses an additional challenge as it is difficult to identify with normal IOP, complicating its prediction, prevention, and treatment. Observational studies suggest a potential association between NTG and abnormal lipid metabolism, yet conclusive evidence establishing a direct causal relationship is lacking. This study aims to explore the causal link between serum lipids and NTG, while identifying lipid-related therapeutic targets. From the perspective of predictive, preventive, and personalized medicine (PPPM), clarifying the role of dyslipidemia in the development of NTG could provide a new strategy for primary prediction, targeted prevention, and personalized treatment of the disease.

Working hypothesis and methods

In our study, we hypothesized that individuals with dyslipidemia may be more susceptible to NTG due to a dysregulation of microvasculature in optic nerve head. To verify the working hypothesis, univariable Mendelian randomization (UVMR) and multivariable Mendelian randomization (MVMR) were utilized to estimate the causal effects of lipid traits on NTG. Drug target MR was used to explore possible target genes for NTG treatment. Genetic variants associated with lipid traits and variants of genes encoding seven lipid-related drug targets were extracted from the Global Lipids Genetics Consortium genome-wide association study (GWAS). GWAS data for NTG, primary open angle glaucoma (POAG), and suspected glaucoma (GLAUSUSP) were obtained from FinnGen Consortium. For apolipoproteins, we used summary statistics from a GWAS study by Kettunen et al. in 2016. For metabolic syndrome, summary statistics were extracted from UK Biobank participants. In the end, these findings could help identify individuals at risk of NTG by screening for lipid dyslipidemia, potentially leading to new targeted prevention and personalized treatment approaches.

Results

Genetically assessed high-density cholesterol (HDL) was negatively associated with NTG risk (inverse-variance weighted [IVW] model: OR per SD change of HDL level = 0.64; 95% CI, 0.49-0.85; P = 1.84 × 10-3), and the causal effect was independent of apolipoproteins and metabolic syndrome (IVW model: OR = 0.29; 95% CI, 0.14-0.60; P = 0.001 adjusted by ApoB and ApoA1; OR = 0.70; 95% CI, 0.52-0.95; P = 0.023 adjusted by BMI, HTN, and T2DM). Triglyceride (TG) was positively associated with NTG risk (IVW model: OR = 1.62; 95% CI, 1.15-2.29; P = 6.31 × 10-3), and the causal effect was independent of metabolic syndrome (IVW model: OR = 1.66; 95% CI, 1.18-2.34; P = 0.003 adjusted by BMI, HTN, and T2DM), but not apolipoproteins (IVW model: OR = 1.71; 95% CI, 0.99-2.95; P = 0.050 adjusted by ApoB and ApoA1). Genetic mimicry of apolipoprotein B (APOB) enhancement was associated with lower NTG risks (IVW model: OR = 0.09; 95% CI, 0.03-0.26; P = 9.32 × 10-6).

Conclusions

Our findings supported dyslipidemia as a predictive causal factor for NTG, independent of other factors such as metabolic comorbidities. Among seven lipid-related drug targets, APOB is a potential candidate drug target for preventing NTG. Personalized health profiles can be developed by integrating lipid metabolism with life styles, visual quality of life such as reading, driving, and walking. This comprehensive approach will aid in shifting from reactive medical services to PPPM in the management of NTG.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00373-5.

Profiling of differentially expressed MicroRNAs in familial hypercholesterolemia via direct hybridization

Background

Individuals with homozygous familial hypercholesterolemia (HoFH) have a severe clinical problem in their first decade of life, which is not usually present in heterozygous FH (HeFH) individuals. For this latter group of patients, FH diagnosis is mostly severely delayed with a significant increase in the risk of angina, myocardial infarction, peripheral artery disease, stroke, and cardiovascular and all-cause mortality.

Methods

This study used various bioinformatics tools to analyze microarray data and identify critical miRNAs and their target genes associated with FH and its severity. Differentially expressed serum miRNAs from direct hybridization microarray data in three groups of subjects: healthy, HeFH, and HoFH. The differential expressed miRNAs were determined according to a log of fold-change (LFC) <-0.5 or >0.5 and of p < 0.05. Then, we assessed their target genes in silico. Gene ontology (GO) enrichment was applied by Cytoscape. The protein-protein interaction and co-expression network were analyzed by the STRING and GeneMANIA plugins of Cytoscape, respectively.

Results

We identified increased expression of circulating hsa-miR-604, hsa-miR-652-5p, and hsa-miR-4451 as well as reduced expression of hsa-miR-3140-3p, hsa-miR-550a-5p, and hsa-miR-363-3p in both group of FH vs. healthy subjects. Higher levels of hsa-miR-1183, hsa-miR-1185-1-3p, hsa-miR-122-5p, hsa-miR-19a-3p, hsa-miR-345-3p, and hsa-miR-34c-5p were detected in HeFH in respect to HoFH when compared to healthy subjects. Most upregulated miRNAs mainly affected gene related to cardiac myofibrillogenesis, cholesterol synthesis, RNA editing for apolipoprotein B, and associated with LDL-cholesterol levels. In contrast, down-regulated miRNAs mainly affected gene related to plasma biomarker for coronary artery disease, lipids metabolism, cell adhesion and migration, genetic predictors of type 2 diabetes and cholesterol metabolism. The essential genes were primarily enriched in GO regarding biological regulation, intracellular nucleic acid binding, and the KEGG pathway of TGF-β signaling.

Conclusions

The case-control nature of this study precluded the possibility of assessing the predictive role of the identified differentially expressed miRNAs for cardiovascular events. Therefore, the signature of miRNAs reflecting the pathogenesis of both HeFH and HoFH.

Can NPC1L1 inhibitors reduce the risk of biliary tract cancer? Evidence from a mendelian randomization study

BACKGROUND & AIMS

Oxysterols have been implicated in biliary tract cancer (BTC), and Niemann-Pick C1-like 1 (NPC1L1) has been associated with oxysterol uptake in biliary and intestinal cells. Thus, our study aims to investigate the potential causal link between genetically proxied NPC1L1 inhibitors and the risk of BTC.

METHODS

In this study, we employed two genetic instruments as proxies for NPC1L1 inhibitors, which included LDL cholesterol-associated genetic variants located within or in close proximity to the NPC1L1 gene, as well as expression quantitative trait loci (eQTLs) of the NPC1L1 gene. Effect estimates were calculated using the Inverse-variance-weighted MR (IVW-MR) and summary-data-based MR (SMR) methods.

RESULTS

In MR analysis using the IVW method, both proxy instruments from the UK Biobank and the GLGC demonstrated a positive association between NPC1L1-mediated LDL cholesterol and BTC risk, with odds ratios (OR) of 10.30 (95% CI = 1.51-70.09; P = 0.017) and 5.61 (95% CI = 1.43-21.91; P = 0.013), respectively. Moreover, SMR analysis revealed a significant association between elevated NPC1L1 expression and increased BTC risk (OR = 1.19, 95% CI = 1.04-1.37; P = 0.014).

CONCLUSIONS

This MR study suggests a causal link between NPC1L1 inhibition and reduced BTC risk. NPC1L1 inhibitors, like ezetimibe, show potential for chemoprevention in precancerous BTC patients, requiring further clinical investigation.

Causal effects of lipid-lowering drugs on inflammatory skin diseases: Evidence from drug target Mendelian randomisation

Clinical research has revealed that inflammatory skin diseases are associated with dyslipidaemia. Modulating lipids is also a rising potential treatment option. However, there is heterogeneity in the existing evidence and a lack of large-scale clinical trials. Observational research is prone to bias, making it difficult to determine causality. This study aimed to evaluate the causal association between lipid-lowering drugs and inflammatory skin diseases. A drug target Mendelian randomisation (MR) analysis was conducted. Genetic targets of lipid-lowering drugs, including proprotein convertase subtilis kexin 9 (PCSK9) and 3-hydroxy-3-methylglutaryl-assisted enzyme A reductase (HMGCR) inhibitor, were screened. Common inflammatory skin diseases, including psoriasis, allergic urticaria, rosacea, atopic dermatitis, systemic sclerosis and seborrhoeic dermatitis, were considered as outcomes. Gene-predicted inhibition of PCSK9 was causally associated with a decreased risk of psoriasis (ORIVW [95%CI] = 0.600 [0.474-0.761], p = 2.48 × 10-5) and atopic dermatitis (ORIVW [95%CI] = 0.781 [0.633-0.964], p = 2.17 × 10-2). Gene-predicted inhibition of HMGCR decreased the risk of seborrhoeic dermatitis (ORIVW [95%CI] = 0.407 [0.168-0.984], p = 4.61 × 10-2) but increased the risk of allergic urticaria (ORIVW [95%CI] = 3.421 [1.374-8.520], p = 8.24 × 10-3) and rosacea (ORIVW [95%CI] = 3.132 [1.260-7.786], p = 1.40 × 10-2). Among all causal associations, only PCSK9 inhibition demonstrated a robust causal effect on psoriasis after a more rigorous Bonferroni test (p < 4.17 × 10-3, which is 0.05/12). Modulating lipids via PCSK9 inhibition may offer potential therapeutic targets for psoriasis and atopic dermatitis. Given the potential cutaneous side effects associated with HMGCR inhibitors, PCSK9 inhibitors could be considered viable alternatives in lipid-lowering medication.

Multipartite network analysis to identify environmental and genetic associations of metabolic syndrome in the Korean population

Network analysis has become a crucial tool in genetic research, enabling the exploration of associations between genes and diseases. Its utility extends beyond genetics to include the assessment of environmental factors. Unipartite network analysis is commonly used in genomics to visualize initial insights and relationships among variables. Syndromic diseases, such as metabolic syndrome, are characterized by the simultaneous occurrence of various signs, symptoms, and clinicopathological features. Metabolic syndrome encompasses hypertension, diabetes, obesity, and dyslipidemia, and both genetic and environmental factors contribute to its development. Given that relevant data often consist of distinct sets of variables, a more intuitive visualization method is needed. This study applied multipartite network analysis as an effective method to understand the associations among genetic, environmental, and disease components in syndromic diseases. We considered three distinct variable sets: genetic factors, environmental factors, and disease components. The process involved projecting a tripartite network onto a two-mode bipartite network and then simplifying it into a one-mode network. This approach facilitated the visualization of relationships among factors across different sets and within individual sets. To transition from multipartite to unipartite networks, we suggest both sequential and concurrent projection methods. Data from the Korean Association Resource (KARE) project were utilized, including 352,228 SNPs from 8840 individuals, alongside information on environmental factors such as lifestyle, dietary, and socioeconomic factors. The single-SNP analysis step filtered SNPs, supplemented by reference SNPs reported in a genome-wide association study catalog. The resulting network patterns differed significantly by sex: demographic factors and fat intake were crucial for women, while alcohol consumption was central for men. Indirect relationships were identified through projected bipartite networks, revealing that SNPs such as rs4244457, rs2156552, and rs10899345 had lifestyle interactions on metabolic components. Our approach offers several advantages: it simplifies the visualization of complex relationships among different datasets, identifies environmental interactions, and provides insights into SNP clusters sharing common environmental factors and metabolic components. This framework provides a comprehensive approach to elucidate the mechanisms underlying complex diseases like metabolic syndrome.

Causal relationships between GLP1 receptor agonists, blood lipids, and heart failure: a drug-target mendelian randomization and mediation analysis

BACKGROUND

Glucagon-like peptide-1 receptor (GLP1R) agonists have been shown to reduce major cardiovascular events in diabetic patients, but their role in heart failure (HF) remains controversial. Recent evidence implies their potential benefits on cardiometabolism such as lipid metabolism, which may contribute to lowering the risk of HF. Consequently, we designed a Mendelian randomization (MR) study to investigate the causal relationships of circulating lipids mediating GLP1R agonists in HF.

METHODS

The available cis-eQTLs for GLP1R target gene were selected as instrumental variables (IVs) of GLP1R agonism. Positive control analyses of type 2 diabetes mellitus (T2DM) and body mass index (BMI) were conducted to validate the enrolled IVs. Two-sample MR was performed to evaluate the associations between GLP1R agonism and HF as well as left ventricular ejection fraction (LVEF). Summary data for HF and LVEF were obtained from two genome-wide association studies (GWASs), which included 977,323 and 40,000 individuals of European ancestry, respectively. The primary method employed was the random-effects inverse variance weighted, with several other methods used for sensitivity analyses, including MR-Egger, MR PRESSO, and weighted median. Additionally, multivariable MR and mediation MR were applied to identify potentially causal lipid as mediator.

RESULTS

A total of 18 independent IVs were included. The positive control analyses showed that GLP1R agonism significantly reduced the risk of T2DM (OR = 0.79, 95% CI = 0.75-0.85, p < 0.0001) and decreased BMI (OR = 0.95, 95% CI = 0.93-0.96, p < 0.0001), ensuring the effectiveness of selected IVs. We found favorable evidence to support the protective effect of GLP1R agonism on HF (OR = 0.75, 95% CI = 0.71-0.79, p < 0.0001), but there was no obvious correlation with increased LVEF (OR = 1.01, 95% CI = 0.95-1.06, p = 0.8332). Among the six blood lipids, only low-density lipoprotein cholesterol (LDL-C) was both associated with GLP1R agonism and HF. The causal effect of GLP1R agonism on HF was partially mediated through LDL-C by 4.23% of the total effect (95% CI = 1.04-7.42%, p = 0.0093).

CONCLUSIONS

This study supported the causal relationships of GLP1R agonists with a reduced risk of HF. LDL-C might be the mediator in this association, highlighting the cardiometabolic benefit of GLP1R agonists on HF.

The relationship between lipoproteins and the risk of esophageal cancer: a Mendelian randomization study

Backgrounds and aims

Esophageal cancer (EC) causes approximately 508,000 deaths annually, making it a significant cause of cancer-related mortality. While previous studies have suggested an association between lipoprotein levels and EC risk, the causal relationship remains unexplored. This study aims to investigate the causal link between lipoproteins and EC using Mendelian randomization (MR).

Methods and findings

This study employed MR to determine the causal effect between lipoproteins and EC risk, with body mass index (BMI) used as a confounder in multivariable MR (MVMR) analysis. Sensitivity analyses were conducted to assess the reliability of the results. Univariable MR (UVMR) analysis indicated that low-density lipoprotein (LDL) had a significant inverse association with EC risk (p = 0.03; OR = 0.89; 95%CI, 0.73-0.98), while high-density lipoprotein (HDL) and triglycerides showed no significant association. In the synthesis of findings across diverse datasets, LDL maintained a notable inverse association with the likelihood of EC (p < 0.001; OR = 0.89; 95%CI, 0.84-0.94). Triglyceride levels indicated a potential trend toward an adverse correlation with EC susceptibility (p = 0.03; OR = -0.94; 95%CI, 0.89-0.99), whereas HDL levels did not establish a definitive causal link with the occurrence of EC. MVMR analysis, adjusting for BMI, confirmed these findings.

Conclusion

LDL exhibits a clear inverse causal relationship with EC risk, regardless of BMI adjustment. No causal effects were observed for HDL in relation to EC risk. Meanwhile, there is a small but statistically significant causal relationship between triglycerides and EC risk.

Investigating Genetic Overlap between Alzheimer's Disease, Lipids, and Coronary Artery Disease: A Large-Scale Genome-Wide Cross Trait Analysis

There is evidence to support a link between abnormal lipid metabolism and Alzheimer's disease (AD) risk. Similarly, observational studies suggest a comorbid relationship between AD and coronary artery disease (CAD). However, the intricate biological mechanisms of AD are poorly understood, and its relationship with lipids and CAD traits remains unresolved. Conflicting evidence further underscores the ongoing investigation into this research area. Here, we systematically assess the cross-trait genetic overlap of AD with 13 representative lipids (from eight classes) and seven CAD traits, leveraging robust analytical methods, well-powered large-scale genetic data, and rigorous replication testing. Our main analysis demonstrates a significant positive global genetic correlation of AD with triglycerides and all seven CAD traits assessed-angina pectoris, cardiac dysrhythmias, coronary arteriosclerosis, ischemic heart disease, myocardial infarction, non-specific chest pain, and coronary artery disease. Gene-level analyses largely reinforce these findings and highlight the genetic overlap between AD and three additional lipids: high-density lipoproteins (HDLs), low-density lipoproteins (LDLs), and total cholesterol. Moreover, we identify genome-wide significant genes (Fisher's combined p value [FCPgene] < 2.60 × 10-6) shared across AD, several lipids, and CAD traits, including WDR12, BAG6, HLA-DRA, PHB, ZNF652, APOE, APOC4, PVRL2, and TOMM40. Mendelian randomisation analysis found no evidence of a significant causal relationship between AD, lipids, and CAD traits. However, local genetic correlation analysis identifies several local pleiotropic hotspots contributing to the relationship of AD with lipids and CAD traits across chromosomes 6, 8, 17, and 19. Completing a three-way analysis, we confirm a strong genetic correlation between lipids and CAD traits-HDL and sphingomyelin demonstrate negative correlations, while LDL, triglycerides, and total cholesterol show positive correlations. These findings support genetic overlap between AD, specific lipids, and CAD traits, implicating shared but non-causal genetic susceptibility. The identified shared genes and pleiotropic hotspots are valuable targets for further investigation into AD and, potentially, its comorbidity with CAD traits.

Causal Association of Golgi Protein 73 With Coronary Artery Disease: Evidence from Proteomics and Mendelian Randomization

Background: Identification of the unknown pathogenic factor driving atherosclerosis not only enhances the development of disease biomarkers but also facilitates the discovery of new therapeutic targets, thus contributing to the improved management of coronary artery disease (CAD). We aimed to identify causative protein biomarkers in CAD etiology based on proteomics and 2-sample Mendelian randomization (MR) design. Methods: Serum samples from 33 first-onset CAD patients and 31 non-CAD controls were collected and detected using protein array. Differentially expressed analyses were used to identify candidate proteins for causal inference. We used 2-sample MR to detect the causal associations between the candidate proteins and CAD. Network MR was performed to explore whether metabolic risk factors for CAD mediated the risk of identified protein. Vascular expression of candidate protein in situ was also detected. Results: Among the differentially expressed proteins identified utilizing proteomics, we found that circulating Golgi protein 73 (GP73) was causally associated with incident CAD and other atherosclerotic events sharing similar etiology. Network MR approach showed low-density lipoprotein cholesterol and glycated hemoglobin serve as mediators in the causal pathway, transmitting 42.1% and 8.7% effects from GP73 to CAD, respectively. Apart from the circulating form of GP73, both mouse model and human specimens imply that vascular GP73 expression was also upregulated in atherosclerotic lesions and concomitant with markers of macrophage and phenotypic switching of vascular smooth muscle cells (VSMCs). Conclusions: Our study supported GP73 as a biomarker and causative for CAD. GP73 may involve in CAD pathogenesis mainly via dyslipidemia and hyperglycemia, which may enrich the etiological information and suggest future research direction on CAD.

Leisure television watching exerts a causal effect on gastroesophageal reflux disease: evidence from a two-step mendelian randomization study

BACKGROUND

Previous studies have shown that physical activity (PA) and leisure sedentary behaviors (LSB, including leisure television watching) are linked to gastroesophageal reflux disease (GERD). However, the associations between PA/LSB and GERD remain controversial. In this study, we aimed to reveal whether these associations reflect causal relationships and reveal the potential mechanisms of these relationships using bidirectional and two-step Mendelian randomization (MR) analyses.

METHODS

We obtained genome-wide association study (GWAS) summary statistics for PA/LSB, four common risk factors (including cigarettes smoked per day, alcoholic drinks per week, triglycerides, total cholesterol) and GERD from published GWASs. A bidirectional MR analysis was performed to identify causal relationships between PA/LSB and GERD. Then, a series of sensitivity analyses were performed to verify the robustness of the results. Finally, a mediation analysis via two-step MR was conducted to investigate any effects explained by common risk factors in these relationships.

RESULTS

Genetically predicted per 1-SD increase in leisure time television watching significantly increased the risk of GERD in the bidirectional MR analysis (OR = 1.33; 95% CI: 1.14-1.56; P = 2.71 × 10- 4). Sensitivity analyses successfully verified the robustness of the causal relationship. Further mediation analysis showed that this effect was partly mediated by increasing cigarettes smoked per day, with mediated proportions of 18.37% (95% CI: 11.94-39.79%).

CONCLUSION

Our findings revealed a causal relationship between leisure television watching and an increased risk of GERD, notably, the causal effect was partially mediated by cigarettes smoked per day. These findings may inform prevention and management strategies directed toward GERD.

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.

Unveiling the association between HMG-CoA reductase inhibitors and bladder cancer: a comprehensive analysis using Mendelian randomization, animal models, and transcriptomics

This study utilized Mendelian randomization (MR) analysis and genome-wide association study (GWAS) data to investigate the association between commonly prescribed drugs and bladder cancer (BLCA) risk. Our results revealed that HMG CoA reductase (HMGCR) inhibitors, specifically simvastatin, are significantly associated with reduced BLCA risk. We further showed that simvastatin could significantly inhibit BLCA proliferation and epithelial-mesenchymal transition in animal models, with transcriptomic data identifying several pathways associated with these processes. Higher expression of HMGCR were linked with BLCA development and progression, and certain blood lipids, such as lipoprotein particles and very low density lipoprotein (VLDL) cholesterol, might influence BLCA risk. These findings suggested that HMGCR inhibitors, particularly simvastatin, could be potential treatment options or adjuvant therapies for BLCA.

Human genetic variation determines 24-hour rhythmic gene expression and disease risk

24-hour biological rhythms are essential to maintain physiological homeostasis. Disruption of these rhythms increases the risks of multiple diseases. The biological rhythms are known to have a genetic basis formed by core clock genes, but how individual genetic variation shapes the oscillating transcriptome and contributes to human chronophysiology and disease risk is largely unknown. Here, we mapped interactions between temporal gene expression and genotype to identify quantitative trait loci (QTLs) contributing to rhythmic gene expression. These newly identified QTLs were termed as rhythmic QTLs (rhyQTLs), which determine previously unappreciated rhythmic genes in human subpopulations with specific genotypes. Functionally, rhyQTLs and their associated rhythmic genes contribute extensively to essential chronophysiological processes, including bile acid and lipid metabolism. The identification of rhyQTLs sheds light on the genetic mechanisms of gene rhythmicity, offers mechanistic insights into variations in human disease risk, and enables precision chronotherapeutic approaches for patients.

Causal Relationships between Lipid-Lowering Drug Target and Aortic Disease and Calcific Aortic Valve Stenosis: A Two-Sample Mendelian Randomization

Background

Proprotein convertase subtilisin/kexin type 9 (PCSK9), 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR), cholesteryl ester transfer protein (CETP) and apolipoprotein C3 (APOC3) are pivotal regulators of lipid metabolism, with licensed drugs targeting these genes. The use of lipid-lowering therapy via the inhibition of these genes has demonstrated a reduction in the risk of cardiovascular disease. However, concerns persist regarding their potential long-term impact on aortic diseases and calcific aortic valve disease (CAVS). This study aims to investigate causal relationships between genetic variants resembling these genes and aortic disease, as well as calcific aortic valve disease using Mendelian randomization (MR).

Methods

We conducted drug-target Mendelian randomization employing summary-level statistics of low-density lipoprotein cholesterol (LDL-C) to proxy the loss-of-function of PCSK9, HMGCR, CETP and APOC3. Subsequently, we investigated the association between drug-target genetic variants and calcific aortic valve stenosis and aortic diseases, including thoracic aortic aneurysm (TAA), abdominal aortic aneurysm (AAA), and aortic dissection (AD).

Results

The genetically constructed variants mimicking lower LDL-C levels were associated with a decreased risk of coronary artery disease, validating their reliability. Notably, HMGCR inhibition exhibited a robust protective effect against TAA (odds ratio (OR): 0.556, 95% CI: 0.372-0.831, p = 0.004), AAA (OR: 0.202, 95% CI: 0.107-0.315, p = 4.84 × 10-15), and AD (OR: 0.217, 95% CI: 0.098-0.480, p = 0.0002). Similarly, PCSK9, CETP and APOC3 inhibition proxies reduced the risk of AAA (OR: 0.595, 95% CI: 0.485-0.730, p = 6.75 × 10-7, OR: 0.127, 95% CI: 0.066-0.243, p = 4.42 × 10-10, and OR: 0.387, 95% CI: 0.182-0.824, p = 0.014, respectively) while showing a neutral impact on TAA and AD. Inhibition of HMGCR, PCSK9, and APOC3 showed promising potential in preventing CAVS with odds ratios of 0.554 (OR: 0.554, 95% CI: 0.433-0.707, p = 2.27 × 10-6), 0.717 (95% CI: 0.635-0.810, p = 9.28 × 10-8), and 0.540 (95% CI: 0.351-0.829, p = 0.005), respectively. However, CETP inhibition did not demonstrate any significant benefits in preventing CAVS (95% CI: 0.704-1.544, p = 0.836). The consistency of these findings across various Mendelian randomization methods, accounting for different assumptions concerning genetic pleiotropy, enhances the causal inference.

Conclusions

Our MR analysis reveals that genetic variants resembling statin administration are associated with a reduced risk of AAA, TAA, AD and CAVS. HMGCR, PCSK9 and APOC3 inhibitors but not CETP inhibitors have positive benefits of reduced CAVS. Notably, PCSK9, CETP and APOC3 inhibitors exhibit a protective impact, primarily against AAA, with no discernible benefits extending to TAA or AD.

Principled distillation of UK Biobank phenotype data reveals underlying structure in human variation

Data within biobanks capture broad yet detailed indices of human variation, but biobank-wide insights can be difficult to extract due to complexity and scale. Here, using large-scale factor analysis, we distill hundreds of variables (diagnoses, assessments and survey items) into 35 latent constructs, using data from unrelated individuals with predominantly estimated European genetic ancestry in UK Biobank. These factors recapitulate known disease classifications, disentangle elements of socioeconomic status, highlight the relevance of psychiatric constructs to health and improve measurement of pro-health behaviours. We go on to demonstrate the power of this approach to clarify genetic signal, enhance discovery and identify associations between underlying phenotypic structure and health outcomes. In building a deeper understanding of ways in which constructs such as socioeconomic status, trauma, or physical activity are structured in the dataset, we emphasize the importance of considering the interwoven nature of the human phenome when evaluating public health patterns.