Discovery and refinement of loci associated with lipid levels

Association between lipid-lowering drug targets and the risk of cystic kidney disease: a drug-target Mendelian randomization analysis

BACKGROUND

Evidence regarding the causal relationship between lipid-lowering drugs and cystic kidney disease, including polycystic kidney disease (PKD), was limited. This study aimed to evaluate the causal relationship between lipid phenotypes mediated by lipid-lowering drug targets-3-hydroxy-3-methyl glutaryl coenzyme A reductase (HMGCR), proprotein convertase subtilisin/kexin type-9 (PCSK9), and Niemann-Pick C1-like 1 (NPC1L1)-and the risk of cystic kidney disease and PKD.

METHODS

Genetic variants encoding lipid-lowering drug targets-HMGCR, PCSK9, and NPC1L1-from published genome-wide association study (GWAS) statistics were collected to perform drug target Mendelian randomization (MR) analysis. Summary statistics for the GWAS of cystic kidney disease and PKD were obtained from the FinnGen consortium and the European Bioinformatics Institute. Inverse variance weighting (IVW) was used as the primary MR analysis method, with sensitivity analyses conducted to ensure the robustness of the results.

RESULTS

Increased gene expression of HMGCR was associated with an elevated risk of cystic kidney disease (IVW-MR: odds ratio [OR] = 3.05, 95% confidence interval [CI] = 1.19-7.84, p = 0.02) and PKD (IVW-MR: OR = 2.13, 95% CI = 1.01-4.46; p = 0.045). There was no evidence of causal effects of PCSK9 and NPC1L1 targets on cystic kidney disease and PKD. Cochran's Q test, MR-PRESSO, and MR-Egger intercept tests showed no heterogeneity or horizontal pleiotropy among the instrumental variables.

CONCLUSIONS

This study supported that increased HMGCR expression was associated with an increased risk of cystic kidney disease and PKD, suggesting potential benefits of statin therapy for cystic kidney disease and PKD. Further research is necessary to elucidate specific mechanisms and potential therapeutic applications of HMGCR inhibitors.

GPR146 regulates CYP7A1 transcription in cells and in vivo of mice

G protein-coupled receptor 146 (GPR146) plays a significant role in cholesterol metabolism in both humans and mice. Previous studies have shown that Gpr146 in mouse liver regulates cholesterol metabolism during long-term starvation, short-term starvation, and feeding conditions. Specifically, Gpr146 suppresses endogenous cholesterol synthesis and very-low-density lipoprotein secretion following feeding. However, its role in cholesterol metabolism under other feeding conditions remains unclear. The conversion of cholesterol to bile acids represents the primary pathway of cholesterol metabolism, with cytochrome P450 family 7 subfamily A member 1 (CYP7A1) serving as the critical rate-limiting enzyme. Studies have indicated that overexpression of Cyp7a1 can lower blood cholesterol levels. In this study, we systematically identified CYP7A1 as a target gene of GPR146 both in vivo and in cultured hepatocytes. Our findings revealed that silencing the expression of gpr146 in the mouse liver significantly reduced total blood cholesterol levels while markedly upregulating liver cyp7a1 expression during a 2-h fasting period. Importantly, this regulation occurs independently of farnesoid X-activated receptor (FXR)-dependent and FXR-independent cytokine pathways. These results strongly suggest that CYP7A1 is a crucial endogenous mediator of GPR146 in cholesterol metabolism both in vitro and in vivo.

Lipoprotein(a) in familial dyslipidemias: The effect on cardiovascular prognosis in patients with familial hypercholesterolemia or familial combined hyperlipidemia

BACKGROUND AND AIMS

Familial dyslipidemias are associated with increased cardiovascular risk. Increased lipoprotein(a) [Lp(a)] is considered as the most prevalent monogenic lipid disorder. The objective of the study was to identify the cardiovascular prognosis of patients with familial dyslipidemias (heterozygous familial hypercholesterolemia (FH) or familial combined hyperlipidemia (FCH)), without cardiovascular disease at baseline, investigating in parallel the effect of Lp(a).

METHODS AND RESULTS

909 patients with FH (n = 433, mean age 44.2 ± 12.8 years) or FCH (n = 476, mean age 49.0 ± 11.1 years) were evaluated during a mean period of 10 years. The main endpoint was the composite of major cardiovascular events. The incidence of major cardiovascular events in the total population was 6.6 %, while greater in patients with FH compared to patients with FCH (8.1 % vs 5.5 %, p = 0.03). Multiple Cox regression analysis revealed that FH patients had greater cardiovascular risk compared to FCH patients (HR 2.17, 95 % CI 1.10-4.26, p = 0.02). In FH patients, increased baseline Lp(a) (≥30 mg/dl) was an independent predictor of adverse cardiovascular events (HR 2.37 95 % CI 1.41-4.90, p = 0.02), whereas in FCH patients was not. In FCH patients the presence of diabetes at baseline was a strong independent prognosticator of adverse cardiovascular events (HR 3.56 95 % CI 1.19-11.33, p = 0.03), after adjustment for confounders.

CONCLUSIONS

FH patients demonstrate double cardiovascular risk compared to FCH patients. In FH patients increased Lp(a) doubles the cardiovascular risk, beyond low density lipoprotein cholesterol. In FCH patients the presence of diabetes triples the cardiovascular risk, beyond Lp(a) which does not seem to convey an independent prognostic value.

Three Loci Affecting Variance of Body Mass Index in African Americans and Sub-Saharan Africans

Conventional genome-wide association studies (GWAS) are designed to assess the effect of a genetic locus on phenotypic mean by genotype. Such loci explain a proportion of phenotypic variance known as narrow-sense heritability. In contrast, variance quantitative trait loci (vQTL) are associated with the phenotypic variance by genotype. These loci explain an additional proportion of phenotypic variance and contribute to broad-sense heritability but not to narrow-sense heritability. Here, a genome-wide vQTL analysis in 22,805 African Americans yielded eight loci for body mass index (BMI). Of these loci, three were replicated in 6002 sub-Saharan Africans. No locus reached genome-wide significance using the standard additive model. Furthermore, no locus showed evidence for natural selection, haplotype effects, or gene × sex or gene × study interactions. Two loci showed evidence for an effect of locus-specific ancestry resulting from admixture and for a gene × gene interaction. One locus showed evidence for interaction with diastolic blood pressure, consistent with this vQTL capturing an unmodeled gene × covariate interaction. These analyses demonstrate that relevant BMI loci can be detected by evaluating vQTL and that these loci contribute to the underexplored broad-sense heritability for this trait.

Examining socioeconomic differences in sepsis risk and mediation by modifiable factors: a Mendelian randomization study

BACKGROUND

Educational attainment is inversely related to sepsis risk, but the causal nature is still unclear. We therefore conducted the first Mendelian randomization (MR) study of genetically predicted educational attainment on sepsis that also uses a within-family genetic instrument for education. To further explore possible mechanistic pathways that can inform strategies to reduce sepsis risk, we examined the mediating effects of factors that are modifiable or can be prevented.

METHODS

The association between genetically predicted educational attainment and sepsis was estimated using summary-level data from recent genome-wide association studies. Possible bias due to population stratification, dynastic effects, and assortative mating in the genetic instrument for education was evaluated using summary-level data from a within-sibship genome-wide association study. We used inverse variance weighted MR analysis to estimate the effect of one standard deviation increase in years of education on sepsis risk. The robustness of the findings was assessed in sensitivity analyses, applying weighted median, weighted mode, and MR Egger regression. Finally, we applied multivariable MR analyses to estimate the mediating effects of smoking initiation, alcohol consumption, body mass index, high-density lipoprotein (HDL)-cholesterol, systolic blood pressure and type 2 diabetes.

RESULTS

For each standard deviation increase in genetically predicted educational attainment (3.4 years), the odds ratio (OR) for sepsis was 0.72 (95% confidence interval (CI) 0.66 to 0.78). The results of the analysis using the within-sibship genetic instrument and other sensitivity analyses were in line with this finding: within-sibship OR 0.88 (95% CI 0.64 to 1.18), weighted median OR 0.70 (95% CI 0.62 to 0.80), weighted mode OR 0.70 (95% CI 0.43 to 1.13), and MR Egger OR 0.65 (95% CI 0.50 to 0.85). The mediation analysis showed that 56% of the effect of educational attainment on sepsis risk can be explained by modifiable or preventable factors.

CONCLUSIONS

Higher educational attainment is strongly associated with a reduced risk of sepsis, pointing to important socioeconomic differences in this disease. The results also suggest that interventions targeting modifiable or preventable factors could contribute to reducing the socioeconomic differences in sepsis risk.

Association between metabolic syndrome and low back pain: a two-sample Mendelian randomization study

This study uses two-sample MR analysis with GWAS summary statistics to evaluate the causal relationship between metabolic syndrome and low back pain. A two-sample Mendelian randomization analysis used GWAS summary statistics for low back pain from the FinnGen database and metabolic syndrome data, including waist circumference, hypertension, fasting blood glucose, HDL cholesterol, and triglyceride levels. Various methods like inverse variance weighted, MR-Egger, weighted median, and mode assessed the causal relationship, with sensitivity analyses addressing heterogeneity and pleiotropy. Our analysis found a statistically significant causal association between essential hypertension (OR  2.38, 95% CI 1.42-3.96; Padj = 0.002), metabolic syndrome (OR  1.05, 95% CI 1.01-1.10; Padj = 0.023) and waist circumference (OR   49, 95% CI 1.32-1.68; Padj < 0.001) and low back pain (OR  1.41, 95% CI 1.30-1.53, Padj < 0.001). In contrast, fasting blood glucose (FBG), HDL cholesterol, and triglycerides showed no significant associations with low back pain across all MR methods. The results of sensitivity analyses indicated that the heterogeneity and pleiotropy were unlikely to disturb the causal estimate. Our study indicates that increased essential hypertension, metabolic syndrome and waist circumference is causally associated with a higher risk of low back pain. Interventions targeting metabolic syndrome components, particularly blood pressure control and weight management, could help reduce the risk of low back pain. Further research is needed to explore the underlying biological pathways linking these metabolic factors to low back pain.

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. 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.

EHBP1 suppresses liver fibrosis in metabolic dysfunction-associated steatohepatitis

Excess cholesterol accumulation contributes to fibrogenesis in metabolic dysfunction-associated steatohepatitis (MASH), but how hepatic cholesterol metabolism becomes dysregulated in MASH is not completely understood. We show that human fibrotic MASH livers have decreased EH-domain-binding protein 1 (EHBP1), a genome-wide association study (GWAS) locus associated with low-density lipoprotein (LDL) cholesterol, and that EHBP1 loss- and gain-of-function increase and decrease MASH fibrosis in mice, respectively. Mechanistic studies reveal that EHBP1 promotes sortilin-mediated PCSK9 secretion, leading to LDL receptor (LDLR) degradation, decreased LDL uptake, and reduced TAZ, a fibrogenic effector. At a cellular level, EHBP1 deficiency affects the intracellular localization of retromer, a protein complex required for sortilin stabilization. Our therapeutic approach to stabilizing retromer is effective in mitigating MASH fibrosis. Moreover, we show that the tumor necrosis factor alpha (TNF-α)/peroxisome proliferator-activated receptor alpha (PPARα) pathway suppresses EHBP1 in MASH. These data not only provide mechanistic insights into the role of EHBP1 in cholesterol metabolism and MASH fibrosis but also elucidate an interplay between inflammation and EHBP1-mediated cholesterol metabolism.

Comparing the impacts of different exercise interventions on patients with type 2 diabetes mellitus: a literature review and meta-analysis

Objective

Exercise interventions are a recommended method of diabetes management through which patients can achieve blood glucose control, increase muscle volume, and improve insulin sensitivity, while also improving blood lipids, blood pressure, and cardiovascular health. A few studies on the effects of physical exercise on diabetic patients have been published in recent years. This article focuses on exploring evidence on which exercise interventions generate which effects in diabetic patients, namely, high-intensity interval training (HIIT), method training (MT), aerobic exercise training (AET), resistance training (RT), and combined training (CBT).

Methods

Randomized controlled trials (RCTs) that focused on the effects of exercise interventions on blood glucose and blood lipids of patients with type 2 diabetes mellitus were reviewed. A network meta-analysis was performed to compare the effects of the five exercise interventions in diabetic patients, namely the impacts on glycosylated hemoglobin (HbA1c), fasting blood glucose (FBG), total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL), and low-density lipoprotein (LDL). The study was strictly conducted following the PRISMA Protocol, and the Cochrane Risk of Bias Assessment Tool 2.0 was used to objectively evaluate the risk of bias in the implementation of the study.

Results

This review included 25 RCTs in total, with 1,711 subjects. Meta-analysis suggests that, compared with conventional therapeutic treatment, exercise interventions can reduce blood glucose indexes, namely HbA1c, FBG, TC, TG, HDL, and LDL. RT and AET have been shown to reduce TC; HIIT, MT, AET, and CBT have been shown to improve HDL; and HIIT, MT, AET, and CBT have been shown to improve HDL. The MT and RT exercise types can reduce LDL. Evidence also suggests that MT can lower HbA1c, TG, and LDL levels, and RT lowers cholesterol levels. HIIT exercise appears to improve FBG and HDL levels.

Conclusion

The five types of exercise generate different effects on the key clinical dimensions of diabetes. MT seems to be the optimal choice to improve HbA1c, TG levels, and LDL, while HIIT improves FBG and HDL levels, whereas RT exercise appears to be the optimal exercise to lower cholesterol levels.

Expanding the Use of SGLT2 Inhibitors in T2D Patients Across Clinical Settings

Sodium-glucose cotransporter-2 inhibitors (SGLT2i) are currently recommended in patients with type 2 diabetes (T2D) to reduce serum glucose levels. Moreover, robust evidence has clearly demonstrated their beneficial cardiovascular and renal effects, making this class of drugs pivotal for the treatment of T2D, especially when complicated by diabetic kidney disease or heart failure. However, several other comorbidities are frequently encountered in T2D patients beyond these long-term diabetes complications, especially in the internal medicine setting. For some of these comorbidities, such as MAFLD and cognitive impairment, the association with diabetes is increasingly recognized, with the hypothesis of a common pathophysiologic background, whereas, for others, a coincident epidemiology linked to the ageing of populations, including that of T2D subjects, may be advocated. In the effort of personalizing T2D treatment, evidence on the potential effects of SGLT2i in these different clinical conditions is accumulating. The purpose of this narrative review is to update current literature on the effects of SGLT2i for the treatment of T2D in different clinical settings beyond glycaemic control, and to elucidate potential molecular mechanisms by which they exert these effects.

HDL Cholesterol Is Remarkably Cardioprotective Against Coronary Artery Disease in Native Hawaiians and Pacific Islanders

BACKGROUND

High-density lipoprotein cholesterol (HDL-C) is inversely associated with cardiometabolic risk and exhibits nonlinear effects at extreme levels. Cardiometabolic diseases are a leading cause of death and are particularly prevalent among Native Hawaiian and Pacific Islanders (NHPIs).

OBJECTIVES

This study characterizes HDL-C's association with coronary artery disease (CAD), major adverse cardiovascular events (MACE), and type 2 diabetes (T2D) in NHPIs compared to the general population.

METHODS

Using electronic health record data from the National Institutes of Health All of Us Research Program, we applied Cox proportional hazards models to compare HDL-C's protective effects on CAD, MACE, and T2D between 261 NHPIs and the remaining cohort (n = 188,802). Models were adjusted for key confounders, and restricted cubic splines were used to assess nonlinear risk dynamics.

RESULTS

Tracking individuals across 10,534,661 person-years (mean age 55.7 ± 15.8 years, 38% male), HDL-C was more strongly associated with reduced CAD risk in NHPIs (HR: 0.32; 95% CI: 0.19-0.54) than in the general cohort (HR: 0.57; 95% CI: 0.56-0.58). A marginally stronger association was observed for MACE (NHPI HR: 0.40; 95% CI: 0.23-0.71 vs general HR: = 0.54; 95% CI: 0.53-0.56), while T2D associations were similar. Spline analysis indicated that low HDL-C increases risk for both CAD and T2D in NHPIs.

CONCLUSIONS

HDL-C's protective role against cardiometabolic diseases is more pronounced in NHPIs, particularly for CAD. These findings support further investigation into tailored clinical assessments for this population.

TEX10: A Novel Drug Target and Potential Therapeutic Direction for Sleep Apnea Syndrome

Background

Sleep apnea syndrome (SAS) is a prevalent sleep disorder strongly associated with obesity, metabolic dysregulation, and cardiovascular diseases. While its underlying pathophysiological mechanisms remain incompletely understood, genetic factors likely play a pivotal role in SAS pathogenesis. This study investigates the causal relationships between potential drug target genes and SAS using multiple statistical approaches, aiming to provide novel insights for targeted therapeutic development.

Methods

We conducted a comprehensive genetic analysis integrating multiple methodologies to investigate gene-SAS relationships. Using publicly available GWAS and eQTL databases, we performed Mendelian Randomization (MR) analysis with the inverse variance weighted (IVW) method, validated by weighted median and MR-Egger approaches. Summary-data-based MR (SMR) analysis, coupled with HEIDI testing, assessed direct gene expression-SAS associations while controlling for linkage disequilibrium (LD). Colocalization analysis evaluated the probability of shared causal variants between SNPs, gene expression, and SAS. Statistical significance was determined using Benjamini-Hochberg multiple testing correction (FDR < 0.05). Additionally, mediation analysis explored TEX10's influence on SAS through metabolic intermediates including BMI, waist circumference, and HDL cholesterol.

Results

We identified 18 candidate drug target genes significantly associated with SAS, with MAPKAPK3, TNXB, MPHOSPH8, and TEX10 showing consistent associations across multiple analyses. TEX10, in particular, exhibited significant associations with SAS risk in blood, cerebral cortex, hippocampus, and basal ganglia (PP.H4 > 0.9). Mediation analysis suggested that TEX10 might influence SAS risk indirectly through BMI, waist circumference, and HDL cholesterol levels.

Conclusion

Our study identified multiple potential therapeutic targets causally linked to SAS, with TEX10 emerging as a key candidate gene. These findings advance our understanding of SAS pathogenesis and offer promising directions for personalized diagnostics and targeted therapies.

Mendelian Randomization Assessment of the Genetic Effects of Lipid-Lowering Drugs on Digestive System Cancers

The relationship between lipid-lowering drugs and the risk of digestive system cancers remains unclear. This study aims to assess the risk association between lipid-lowering drugs and digestive system cancers through mendelian randomization (MR) analysis. We utilized genetic instruments to substitute for the exposure to lipid-lowering drugs, including expression quantitative trait loci (eQTL) for HMGCR, PCSK9, and NPC1L1, as well as genetic variants associated with low-density lipoprotein (LDL) from the Global Lipids Genetics Consortium's genome-wide association study (GWAS) data for target genes. We used MR and SMR methods to assess the risk estimates of lipid-lowering drug target genes on digestive system tumors. The MR analysis indicated a negative association between HMGCR-mediated LDL and hepatocellular carcinoma (OR = 0.06, 95% CI: 0.00-0.81, p = 0.03), and a positive association between NPC1L1-mediated LDL and gastric cancer risk (OR = 15.45, 95% CI: 5.96-40.56, p < 0.01). In the SMR analysis, it was observed that HMGCR expression decreased the risk of hepatocellular carcinoma (OR = 0.11, 95% CI: 0.02-0.68, p = 0.02), while NPC1L1 expression increased the risk of gastric cancer (OR = 1.33, 95% CI: 1.08-1.64, p < 0.01). Our study results suggested a potential risk association between HMGCR inhibitors and NPC1L1 with hepatocellular carcinoma and gastric cancer.

Exploring lipid-modifying therapies for sepsis through the modulation of circulating inflammatory cytokines: a Mendelian randomization study

BACKGROUND

Whether lipid-modifying drugs directly impact the outcome of sepsis remains uncertain. Therefore, systematic investigations are needed to explore the potential impact of lipid-related therapies on sepsis outcomes and to elucidate the underlying mechanisms involving circulating inflammatory cytokines, which may play critical roles in the pathogenesis of sepsis. This study aimed to utilize drug-target Mendelian randomization to assess the direct causal effects of genetically proxied lipid-modifying therapies on sepsis outcomes.

METHODS

First, a two-sample Mendelian randomization study was conducted to validate the causal associations among high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and sepsis. A subsequent drug-target Mendelian randomization study assessed the direct causal effects of genetically proxied lipid-modifying therapies on the risk of sepsis, sepsis-related critical care admission, and sepsis-related death. The identified lipid-modifying drug targets were subsequently explored for direct causal relationships with 36 circulating inflammatory cytokines. Finally, enrichment analyses of the identified cytokines were conducted to explore the potential relationships of lipid-modifying drugs with the inflammatory response.

RESULTS

Genetically proxied cholesteryl ester transfer protein (CETP) inhibitors were significantly associated with sepsis-related critical care admission (OR=0.84, 95% CI [0.74, 0.95], P=0.008,) and sepsis-related death (OR=0.68, 95% CI [0.52, 0.88], P=0.004). The genetically proxied CETP inhibitors were strongly associated with the levels of 15 circulating inflammatory cytokines. Enrichment analyses indicated that CETP inhibitors may modulate inflammatory cytokines and influence the inflammatory response pathway.

CONCLUSION

This study supports a causal effect of genetically proxied CETP inhibitors in reducing the risk of sepsis-related critical care admission and death. These findings suggest that the underlying mechanism may involve the modulation of some circulating inflammatory cytokines, influencing the inflammatory response pathway.

A latent outcome variable approach for Mendelian randomization using the stochastic expectation maximization algorithm

Mendelian randomization (MR) is a widely used tool to uncover causal relationships between exposures and outcomes. However, existing MR methods can suffer from inflated type I error rates and biased causal effects in the presence of invalid instruments. Our proposed method enhances MR analysis by augmenting latent phenotypes of the outcome, explicitly disentangling horizontal and vertical pleiotropy effects. This allows for explicit assessment of the exclusion restriction assumption and iteratively refines causal estimates through the expectation-maximization algorithm. This approach offers a unique and potentially more precise framework compared to existing MR methods. We rigorously evaluate our method against established MR approaches across diverse simulation scenarios, including balanced and directional pleiotropy, as well as violations of the Instrument Strength Independent of Direct Effect (InSIDE) assumption. Our findings consistently demonstrate superior performance of our method in terms of controlling type I error rates, bias, and robustness to genetic confounding, regardless of whether individual-level or summary data is used. Additionally, our method facilitates testing for directional horizontal pleiotropy and outperforms MR-Egger in this regard, while also effectively testing for violations of the InSIDE assumption. We apply our method to real data, demonstrating its effectiveness compared to traditional MR methods. This analysis reveals the causal effects of body mass index (BMI) on metabolic syndrome (MetS) and a composite MetS score calculated by the weighted sum of its component factors. While the causal relationship is consistent across most methods, our proposed method shows fewer violations of the exclusion restriction assumption, especially for MetS scores where horizontal pleiotropy persists and other methods suffer from inflation.

Genetically determined increase in apolipoprotein C-III (APOC3 gain-of-function) delays very low-density lipoprotein clearance in humans

AIM

Apolipoprotein C-III (apoC-III) is an important regulator of triglyceride (TG) metabolism and a target for intervention. The present study examined the effects of gain-of-function (GOF) variants in APOC3 on apolipoprotein B kinetics to understand further how changes in the synthesis of this apolipoprotein impact triglyceride-rich lipoprotein (TRL) metabolism.

METHODS

Two groups of subjects were recruited by population screening, 9 carriers of known APOC3 GOF variants and 9 age-, sex- and BMI-matched non-carriers. The kinetics of TRL were determined using stable isotope tracers of apoprotein and triglyceride metabolism in a non-steady-state protocol involving administration of a fat-rich meal.

RESULTS

APOC3 GOF carriers had 47 % higher plasma apoC-III levels compared to non-carriers (P = 0.022) and higher production rates for the apolipoprotein. Post-prandial response (total area-under-curve) for plasma TG was 108 % greater in GOF carriers compared to non-carriers (P = 0.002) due specifically to higher levels of VLDL1. In contrast, no difference was seen in the chylomicron apoB48 response. Comparison of TRL kinetics between groups showed that APOC3 GOF carriers had lower fractional clearance rates for VLDL1-apoB100 and VLDL1-apoB48-containing particles (P < 0.02), but no difference in VLDL1-apoB100 or chylomicron apoB48 production rates. Both the rate of VLDL lipolysis and the rate of clearance of VLDL particles from the circulation were lower in APOC3 GOF carriers than in non-carriers. In contrast, chylomicron apoB clearance rates did not differ between APOC3 GOF carriers and non-carriers.

CONCLUSION

APOC3 GOF carriers showed specific alterations in TRL metabolism (compared to matched non-carriers), namely slower lipolysis and delayed clearance of VLDL1-sized particles, but no difference in chylomicron metabolism. Our findings suggest that intervention to reduce apoC-III production can be modelled as a reduction in TRL, particularly VLDL particle levels, without deleterious effects on fat absorption or hepatic VLDL production.

Causal Associations Between Lipids, NPC1L1, and Liver Cancer Risk: Insights From Mendelian Randomization and Bioinformatics

BACKGROUND AND AIM

The study aims to investigate the potential causal effects of lipids on liver cancer risk and to analyze the possible impact of lipid-lowering drug targets on liver cancer.

METHODS

Genetic variants linked to lipid traits and drug targets were obtained from the Global Lipids Genetics Consortium and DrugBank. Liver cancer data were sourced from FinnGen. Mendelian randomization (MR) was used to assess causal relationships between lipid traits and liver cancer. Functional analyses included protein-protein interaction (PPI), KEGG pathway enrichment, transcription factor (TF) network analysis, and survival analysis. NPC1L1 expression, DNA methylation, and immune infiltration were analyzed using UALCAN, TCGA-LIHC, and TIMER, respectively.

RESULTS

MR analysis showed higher genetically predicted LDL-C levels reduced liver cancer risk (OR = 0.5981, p = 0.034). Drug target MR indicated that NPC1L1 inhibition (OR = 1.0638, p = 0.0311) and elevated PPARɑ levels (OR = 1.1339, p < 0.01) increased liver cancer risk. Functional analysis revealed NPC1L1 was highly expressed in liver cancer tissues due to hypomethylation and linked to immune cell infiltration, indicating its role in immune evasion and tumor progression.

CONCLUSION

The study demonstrates that elevated LDL-C levels are associated with a reduced risk of liver cancer and NPC1L1 plays a key role in regulating lipid metabolism and influencing immune evasion.

Drug-targeted Mendelian randomization analysis combined with transcriptome sequencing to explore the molecular mechanisms associated with cognitive impairment

BackgroundCurrent therapies for cognitive impairment, including Alzheimer's disease (AD) and mild cognitive impairment, are limited by a lack of universal treatment and adverse effects associated with polypharmacy. Investigating genetic and molecular mechanisms underlying cognitive decline is critical for the development of targeted therapeutics.ObjectiveTo identify causal genes and potential therapeutic targets for cognitive impairment through integrative genomic analyses.MethodsGenome-wide association study data on cognitive impairment were combined with the expression quantitative trait loci (eQTL) data from the eQTLGen consortium. Mendelian randomization (MR) and colocalization analyses were employed to infer causal relationships. Gene Set Enrichment Analysis and Gene Set Variation Analysis evaluated the pathway and functional differences. Immune cell infiltration patterns and the immunometabolic pathways were assessed, followed by drug target prediction.ResultsMR analysis identified seven gene-eQTL pairs significantly associated with cognitive impairment. SMR colocalization prioritized three key genes: HNMT (histamine metabolism), TNFSF8 (inflammatory signaling), and S1PR5 (sphingolipid signaling). HNMT, TNFSF8, and S1PR5 had 39, 24, and 30 predicted targeted drugs, respectively, including arsenic trioxide, aspirin, and immunomodulators.ConclusionsThis study implicates HNMT, TNFSF8, and S1PR5 as potential therapeutic targets for cognitive impairment. Further validation is required to confirm their clinical relevance.

Evaluating lipid-lowering drug targets for full-course diabetic retinopathy

BACKGROUND

Implementing lipid control in patients with diabetes is regarded as a potential strategy for halting the advancement of diabetic retinopathy (DR). This study seeks to use Mendelian randomisation (MR) to assess the causal relationship between lipid traits and lipid-lowering drug targets and full-course DR (background DR, severe non-proliferative DR (NPDR) and proliferative DR (PDR)).

METHODS

A two-sample MR and drug target MR to decipher the causal effects of lipid traits and lipid-lowering drug targets on full-course DR, including background DR, severe NPDR and PDR, was conducted in the study. Genetic variants associated with lipid traits and genes encoding the protein targets of lipid-lowering drugs were extracted from the Global Lipids Genetics Consortium and UK Biobank. Summary-level data of full-course DR are obtained from FinnGen.

RESULTS

No significant causal relationship was found between lipid traits and full-course DR. However, in drug target MR analysis, peroxisome proliferator-activated receptor gamma (PPARG) enhancement was associated with lower risks of background DR (OR=0.12, p=0.005) and PDR (OR=0.25, p=0.006). Additionally, mediation MR analysis showed that lowering fasting insulin (p=0.015) and HbA1c (p=0.005) levels mediated most of the association between PPARG and full-course DR.

CONCLUSIONS

This study reveals PPARG may be a promising drug target for full-course DR. The activation of PPARG could reduce the risk of full-course DR, especially background DR and PDR. The mechanism of the PPARG agonists' protection of full-course DR may be dependent on the glucose-lowering effect.

A Bayesian approach to correcting the attenuation bias of regression using polygenic risk score

Polygenic risk score has become increasingly popular for predicting the value of complex traits. In many settings, polygenic risk score is used as a covariate in regression analysis to study the association between different phenotypes. However, measurement error in polygenic risk score causes attenuation bias in the estimation of regression coefficients. In this paper, we employ a Bayesian approach to accounting for the measurement error of polygenic risk score and correcting the attenuation bias in linear and logistic regression. Through simulation, we show that our approach is able to obtain approximately unbiased estimation of coefficients and credible intervals with correct coverage probability. We also empirically compare our Bayesian measurement error model with the conventional regression model by analyzing real traits in the UK Biobank. The results demonstrate the effectiveness of our approach as it significantly reduces the error in coefficient estimates.

Pathways and Molecular Mechanisms Governing LDL Receptor Regulation

Clearance of circulating plasma LDL (low-density lipoprotein) cholesterol by the liver requires hepatic LDLR (low-density lipoprotein receptor). Complete absence of functional LDLR manifests in severe hypercholesterolemia and premature atherosclerotic cardiovascular disease. Since the discovery of the LDLR 50 years ago by Brown and Goldstein, all approved lipid-lowering medications have been aimed at increasing the abundance and availability of LDLR on the surface of hepatocytes to promote the removal of LDL particles from the circulation. As such a critical regulator of circulating and cellular cholesterol, it is not surprising that LDLR activity is tightly regulated. Despite over half a century's worth of study, there are still many facets of LDLR biology that remain unexplored. This review will focus on pathways that regulate the LDLR and emerging concepts of LDLR biology.

Whole genome sequencing analysis of body mass index identifies novel African ancestry-specific risk allele

Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals (P < 5 × 10-9), including two secondary signals. Notably, we identified and replicated a novel low-frequency single nucleotide polymorphism (SNP) in MTMR3 that was common in individuals of African descent. Using a diverse study population, we further identified two novel secondary signals in known BMI loci and pinpointed two likely causal variants in the POC5 and DMD loci. Our work demonstrates the benefits of combining WGS and diverse cohorts in expanding current catalog of variants and genes confer risk for obesity, bringing us one step closer to personalized medicine.

Large-scale multi-omics analyses in Hispanic/Latino populations identify genes for cardiometabolic traits

Here, we present a multi-omics study of type 2 diabetes and quantitative blood lipid and lipoprotein traits conducted to date in Hispanic/Latino populations (nmax = 63,184). We conduct a meta-analysis of 16 type 2 diabetes and 19 lipid trait GWAS, identifying 20 genome-wide significant loci for type 2 diabetes, including one novel locus and novel signals at two known loci, based on fine-mapping. We also identify sixty-one genome-wide significant loci across the lipid/lipoprotein traits, including nine novel loci, and novel signals at 19 known loci through fine-mapping. Next, we analyze genetically regulated expression, perform Mendelian randomization, and analyze association with transcriptomic and proteomic measure using multi-omics data from a Hispanic/Latino population. Using this approach, we identify genes linked to type 2 diabetes and lipid/lipoprotein traits, including TMEM205 and NEDD9 for HDL cholesterol, TREH for triglycerides, and ANXA4 for type 2 diabetes.

Glucosamine supplementation contributes to reducing the risk of type 2 diabetes: Evidence from Mendelian randomization combined with a meta-analysis

ObjectiveObservational studies on glucosamine supplementation and type 2 diabetes risk have shown inconsistent results, necessitating the use of Mendelian randomization to clarify the true causal relationship.MethodsThe glucosamine supplementation-related genome-wide association study dataset was obtained from the MRC Integrative Epidemiology Unit consortium, whereas type 2 diabetes-related genome-wide association study datasets were obtained from the FinnGen consortium (discovery) and Xue et al.'s meta-analysis (validation). Two-sample Mendelian randomization analyses were performed separately in the discovery and validation datasets, followed by meta-analysis and multivariable Mendelian randomization analyses to verify the robustness of the results of two-sample Mendelian randomization. The estimation of the causal relationship was conducted through the inverse variance weighted method.ResultsGlucosamine supplementation exhibited a significant protective effect against type 2 diabetes, as identified by two-sample Mendelian randomization analysis in the FinnGen consortium (odds ratio: 0.13, 95% confidence interval: 0.02-0.89) and validated in Xue et al.'s meta-analysis (odds ratio: 0.06, 95%; confidence interval: 0.01-0.29). A combined meta-analysis (odds ratio: 0.08, 95%; confidence interval: 0.02-0.27) of the results of two-sample Mendelian randomization confirmed the robustness of these findings. Additionally, multivariable Mendelian randomization analysis (odds ratio: 0.12, 95%; confidence interval: 0.02-0.94), after adjusting for confounding factors, supported the results of two-sample Mendelian randomization. No evidence of heterogeneity or pleiotropy was observed.ConclusionOverall, our results revealed that genetically predicted glucosamine supplementation was inversely associated with the risk of type 2 diabetes, highlighting the potential importance of glucosamine supplementation in preventing type 2 diabetes.

Associations of Lipid-Lowering Drugs With Blood Pressure and Fasting Glucose: A Mendelian Randomization Study

BACKGROUND

Observational studies have linked LDL-C (low-density lipoprotein-cholesterol)-lowering drugs with lower blood pressure (BP) and higher fasting glucose, but the causality remains unclear. We conducted a drug target Mendelian randomization study to assess the causal associations of genetically proxied inhibition of HMGCR (3-hydroxy-3-methylglutaryl coenzyme A reductase), PCSK9 (proprotein convertase subtilisin/kexin type 9), and NPC1L1 (Niemann-Pick C1-Like 1) with BP and fasting glucose.

METHODS

Single-nucleotide polymorphisms in HMGCR, NPC1L1, and PCSK9 associated with LDL-C in a genome-wide association study meta-analysis from the Global Lipid Genetics Consortium (173 082 European individuals) were used to proxy LDL-C-lowering drug targets. BP and fasting glucose data were obtained from genome-wide association studies conducted by the International Consortium of Blood Pressure (757 601 European participants) and the Glucose and Insulin-related Traits Consortium (58 074 European participants). We used the inverse-variance weighted method and a series of sensitivity analyses for assessment.

RESULTS

Genetically proxied inhibition of HMGCR was negatively associated with systolic BP (β, -0.81 [95% CI, -1.26 to -0.37 mm Hg]; P=3.72×10-4) and diastolic BP (β, -1.58 [95% CI, -2.24 to -0.91 mm Hg]; P=3.23×10-6). Conversely, we observed a positive association between genetically proxied inhibition of HMGCR and high fasting glucose (β, 0.13 [95% CI, 0.08-0.17 mmol/L]; P=4.25×10-8). However, there was no association of PCSK9 and NPC1L1 inhibition with BP or fasting glucose.

CONCLUSIONS

Genetically proxied inhibition of HMGCR was significantly associated with low BP and high fasting glucose, while there was no effect of PCSK9 and NPC1L1 inhibition on BP or fasting glucose.

A study into rare GPR146 gene variants in humans and mice

BACKGROUND AND AIMS

G-protein coupled receptor 146 (GPR146)-deficient mice exhibit a moderate 21 % reduction in plasma cholesterol. This is associated with decreased phosphorylation of ERK1/2 and reduced SREBP2 activity in the liver, which leads to lower VLDL secretion. Insight into the role of GPR146 in humans is however limited. We therefore set out to study rare genetic variants in GPR146 to improve our understanding of this new player in lipid metabolism.

METHODS

We used whole genome sequencing data from UK Biobank participants to search for rare coding variants in GPR146. We first carried out gene-based burden tests (using SAIGE-GENE-framework) and examined the association of individual variants with plasma cholesterol levels. One of the variants (P62L) was also studied using the Global Lipids Genetics Consortium (GLGC) data set and in a knock-in mouse model.

RESULTS

We found that the combination of rare genetic variants identified in GPR146 is significantly associated with plasma cholesterol levels. Three rare variants, i.e. P62L, I129I, and A175T were individually associated with reduced plasma cholesterol. In the GLGC cohort, the P62L variant was associated with reductions in both HDL and LDL cholesterol. Follow-up experiments show lower plasma cholesterol levels in GPR146P61L male and female mice (-13 %, p < 0.05 and -15 %, p < 0.005, respectively) when compared to controls due to a reduction in HDL cholesterol. The GPR146P61L mice did not exhibit a change in VLDL secretion. In line, the ERK1/2 signalling pathway and Srebp2 mRNA expression in liver homogenates, and the secretion of apoB by primary hepatocytes of GPR146P61L and wild-type mice were unchanged.

CONCLUSIONS

This study shows that rare GPR146 gene variants are associated with lower plasma cholesterol levels in humans. One of these variants, P62L is associated with reductions of HDL cholesterol and LDL cholesterol in humans while the ortholog in mice confers a loss of GPR146 function leading to only reduced HDL cholesterol. How GPR146 affects HDL metabolism in humans and mice remains to be resolved.

The breadth and impact of the Global Lipids Genetics Consortium

PURPOSE OF REVIEW

This review highlights contributions of the Global Lipids Genetics Consortium (GLGC) in advancing the understanding of the genetic etiology of blood lipid traits, including total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, and non-HDL cholesterol. We emphasize the consortium's collaborative efforts, discoveries related to lipid and lipoprotein biology, methodological advancements, and utilization in areas extending beyond lipid research.

RECENT FINDINGS

The GLGC has identified over 923 genomic loci associated with lipid traits through genome-wide association studies (GWASs), involving more than 1.65 million individuals from globally diverse populations. Many loci have been functionally validated by individuals inside and outside the GLGC community. Recent GLGC studies show increased population diversity enhances variant discovery, fine-mapping of causal loci, and polygenic score prediction for blood lipid levels. Moreover, publicly available GWAS summary statistics have facilitated the exploration of lipid-related genetic influences on cardiovascular and noncardiovascular diseases, with implications for therapeutic development and drug repurposing.

SUMMARY

The GLGC has significantly advanced the understanding of the genetic basis of lipid levels and serves as the leading resource of GWAS summary statistics for these traits. Continued collaboration will be critical to further understand lipid and lipoprotein biology through large-scale genetic assessments in diverse populations.

Genetic association of circulating lipids and lipid-lowering drug targets with vascular calcification

BACKGROUND AND AIMS

Vascular calcification (VC) significantly increases the incidence and mortality of many diseases. The causal relationships of dyslipidaemia and lipid-lowering drug use with VC severity remain unclear. This study explores the genetic causal associations of different circulating lipids and lipid-lowering drug targets with coronary artery calcification (CAC) and abdominal aortic artery calcification (AAC).

METHODS

We obtained single-nucleotide polymorphisms (SNPs) and expression quantitative trait loci (eQTLs) associated with seven circulating lipids and 13 lipid-lowering drug targets from publicly available genome-wide association studies and eQTL databases. Causal associations were investigated by univariable, multivariable, drug-target, and summary data-based Mendelian randomization (MR) analyses. Potential mediation effects of metabolic risk factors were evaluated.

RESULTS

MR analysis revealed that genetic proxies for low-density lipoprotein cholesterol (LDL-C), triglycerides (TC) and Lipoprotein (a) (Lp(a)) were causally associated with CAC severity, and apolipoprotein B (apoB) level was causally associated with AAC severity. A significant association was detected between hepatic Lipoprotein(A) (LPA) gene expression and CAC severity. Colocalisation analysis supported the hypothesis that the association between LPA expression and CAC quantity is driven by different causal variant sites within the ±1 Mb flanking region of LPA. Serum calcium and phosphorus had causal associations with CAC severity.

CONCLUSIONS

Inhibitors targeting LPA might represent CAC drug candidates. Moreover, T2DM, hypercalcemia, and hyperphosphatemia are positively causally associated with CAC severity, while chronic kidney disease and estimated glomerular filtration rate are not.

Potential Causal Relationship Between Extensive Lipid Profiles and Various Hair Loss Diseases: Evidence From Univariable and Multivariable Mendelian Randomization Analyses

BACKGROUND

Hair loss disorders, including non-cicatricial forms such as alopecia areata (AA) and androgenetic alopecia (AGA), as well as cicatricial forms, represent significant dermatological concerns influenced by various factors, including lipid metabolism. While observational studies and clinical trials have suggested a link between lipid levels and hair loss, the causal relationship remains unclear.

METHODS

We conducted a comprehensive analysis of 983 lipid variables [including triglycerides (TG), fatty acids, cholesterol, cholesterol esters, phospholipids, and lipoproteins] and 4 hair loss disorders. Two-sample univariable Mendelian randomization (UVMR) and multivariable Mendelian randomization (MVMR) analyses were employed to investigate the causal effects of lipids on hair loss disorders. Sensitivity analyses were performed to ensure the robustness of our findings.

RESULTS

The UVMR analysis identified 56 significant causal associations between lipid levels and hair loss disorders, with cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), TG, apolipoprotein A1, apolipoprotein B, and lipoprotein(a) emerging as key contributors. The MVMR analysis evaluated the independent effects of HDL-C, LDL-C, and TG on alopecia disorders, identifying significant associations only between HDL-C, TG, and AA. Sensitivity analyses confirmed the consistency and robustness of these results.

CONCLUSION

This study provides strong evidence for potential causal associations between lipids and hair loss disorders, highlighting potential therapeutic targets and the importance of lipid management in affected patients.

Inhibition of Putative Ibrutinib Targets Promotes Atrial Fibrillation, Conduction Blocks, and Proarrhythmic Electrocardiogram Indices: A Mendelian Randomization Analysis

Background

The mechanism by which ibrutinib, a Bruton's tyrosine kinase inhibitor, can elevate the risk of arrhythmias is not fully elucidated. In this study, we explored how inhibition of off-target kinases can contribute to this phenomenon.

Methods

We performed a Mendelian randomization analysis to examine the causal associations between genetically proxied inhibition of six putative ibrutinib drug targets (ErbB2/HER2, CSK, JAK3, TEC, BLK, and PLCG2) and the atrial fibrillation (AF) risk, proarrhythmic ECG indices, and cardiometabolic traits and diseases. Inverse-variance weighted random-effects models and Wald ratio were used to examine the associations between genetically proxied inhibition of these drug targets and the risk of outcomes. Colocalization analyses were employed to examine the robustness of the causally significant findings. ELISAs were used to measure ErbB2 levels in intracardiac plasma samples.

Results

Genetically proxied ErbB2 inhibition was associated with an increased AF risk, higher P wave terminal force, and prolonged QTc interval. Patients with AF had significantly higher intracardiac ErbB2 levels compared with patients with paroxysmal supraventricular tachycardia. CSK inhibition prolonged the QRS duration, decreased the QTc interval, and was potentially linked to conduction blocks. PLCG2 inhibition led to decreased P wave terminal force, shorter QTc interval, and increased risk of left bundle branch block. BLK inhibition shortened the QTc interval and was also associated with atrioventricular block.

Conclusion

The off-target effects and downstream targets of ibrutinib, including CSK, PLCG2, ERBB2, TEC, and BLK, may lead to cardiac electrical homeostasis imbalances and lethal cardiovascular diseases. Using drugs that inhibit these targets should be given extra caution.

Genome Wide Association Study (GWAS) Identifies Novel Genetic Loci for Second-Generation Antipsychotics (SGA)-Induced Metabolic Syndrome (MetS)

Second-generation antipsychotics (SGA) are widely used for treating psychiatric disorders; however, their use is associated with an increased risk of metabolic syndrome (MetS). To identify common genetic associations of SGA-induced metabolic syndrome (SGA-MetS), we conducted a genome-wide association study (GWAS) in a diverse patient population within the BioVU and BioMe electronic health records (EHRs)-linked biobanks. Additionally, we performed Mendelian Randomization (MR) analysis to investigate the association between the individual metabolic parameters comprising MetS (body mass index [BMI], fasting glucose, blood pressure, HDL, and triglycerides) and SGA-MetS. The meta-analysis of European ancestry GWAS from BioVU and BioMe (N = 9248) identified a genome-wide signal (rs61900075, β = -0.27, SE = 0.05, p = 1.6 × 10-8) on chromosome 11. Multiple associated variants met the suggestive level of association (p ≤ 10-5) in the PELO-ITGA1 locus on chromosome 5 and were associated among the Hispanic Ancestry within BioMe. The meta-analysis of the African Ancestry patients of BioVU and BioMe (N = 2018) identified multiple genome-wide signals that were functionally mapped to NPPC-DIS3L2 in chromosome 2. Finally, the inverse-variance weighted average MR (BMI: OR = 1.2, 95% CI: 1.1-1.4, p = 0.002) showed that genetically predicted, higher BMI was associated with an increased risk of SGA-MetS. Similar results were seen in the sensitivity analyses using the weighted median and Egger MR. This study identified novel variants for SGA-MetS and suggested a role of BMI in increasing the risk of SGA-MetS. The findings highlight the value of EHR biobanks for identifying the genetics underlying SGA-MetS. The associations in chromosome 2 and 5 will need further replication.

Statins' protective effects on focal epilepsy are independent of LDL-C

OBJECTIVE

This study evaluates the potential protective effects of statins against epilepsy, focusing on their differential impacts on focal and generalized epilepsy. It investigates the role of statins through the HMGCR gene and associated low-density lipoprotein (LDL) cholesterol levels.

METHODS

A two-sample Mendelian randomization (MR) and summary-data-based MR (SMR) approach were employed using genetic instruments from genome-wide association studies (GWASs) and expression quantitative trait loci (eQTLs). Subgroup analyses examined focal and generalized epilepsy, with sensitivity tests, including MR-Egger regression and MR-PRESSO, to assess horizontal pleiotropy and robustness.

RESULTS

SMR analysis found no significant association between HMGCR expression and epilepsy risk across subtypes (p > 0.05). However, inverse-variance-weighted MR (IVW-MR) showed that elevated LDL cholesterol mediated by HMGCR was linked to an increased risk of focal epilepsy (OR = 1.251, 95% CI = 1.135-1.378). No such association was observed for generalized epilepsy. Statins showed promise in reducing post-stroke epilepsy risk, likely through anti-inflammatory and neuroprotective effects.

SIGNIFICANCE

The findings suggest that statins' protective effects may be subtype-specific, particularly in post-stroke focal epilepsy. Further research is needed to elucidate underlying mechanisms and optimize their therapeutic potential in epilepsy management.

PLAIN LANGUAGE SUMMARY

Statins, drugs typically used to manage cholesterol, may also lower the risk of developing certain types of epilepsy, especially post-stroke focal epilepsy, by reducing inflammation and protecting brain cells. The research found no clear effect of statins on generalized epilepsy or epilepsy caused by other factors. These results could aid in creating better treatments for epilepsy in the future.

Examining the link between 179 lipid species and 7 diseases using genetic predictors

BACKGROUND

Genome-wide association studies of lipid species have identified several loci shared with various diseases, however, the relationship between lipid species and disease risk remains poorly understood. Here we investigated whether the plasma levels of lipid species are causally linked to disease risk.

METHODS

We built genetic predictors of 179 lipid species, measured in 7174 Finnish individuals, by utilising either 11 high-impact genomic loci or genome-wide polygenic scores (PGS). We assessed the impact of the lipid species on seven diseases by performing disease association across FinnGen (n = 500,348), UK Biobank (n = 420,531), and Generation Scotland (n = 20,032). We performed univariable Mendelian randomisation (MR) and multivariable MR (MVMR) analyses to examine whether lipid species impact disease risk independently of standard lipids.

FINDINGS

PGS explained >4% of the variance for 34 lipid species but variants outside the high-impact loci had only a marginal contribution. Variants within the high-impact loci showed association with all seven diseases. MVMR supported a causal role of ApoB in ischaemic heart disease after accounting for lipid species. Phosphatidylethanolamine-increasing LIPC variants seemed to lower age-related macular degeneration risk independently of HDL-cholesterol. MVMR suggested a protective effect of four lipid species containing arachidonic acid on cholelithiasis risk independently of Total Cholesterol.

INTERPRETATION

Our study demonstrates how genetic predictors of lipid species can be utilised to gain insights into disease risk. We report potential links between lipid species and age-related macular degeneration and cholelithiasis risk, which can be explored for their utility in disease risk prediction and therapy.

FUNDING

The funders had no role in the study design, data analyses, interpretation, or writing of this article.

Assessing the effect of modifiable risk factors on hepatocellular carcinoma: evidence from a bidirectional Mendelian randomization analysis

BACKGROUND

The pathogenesis of hepatocellular carcinoma (HCC) involves a variety of environmental risk factors, some of which have yet to be fully clarified. Using the Mendelian randomization (MR) approach, this study comprehensively investigates the causal effect of genetically predicted modifiable risk factors on HCC.

METHODS

Genetic variants related to the 50 risk factors that had been identified in previous research were derived from genome-wide association studies. Summary statistics for the discovery cohort and validation cohort of HCC were sourced from the FinnGen consortium and the UK Biobank, respectively. Bidirectional MR analysis and sensitivity analysis were performed to establish causative risk factors for HCC.

RESULTS

Through the inverse variance weighted method, the results of the discovery cohort indicated that waist circumference, nonalcoholic fatty liver disease (NAFLD), alanine aminotransferase (ALT) levels, and aspartate aminotransferase (AST) levels were significantly linked to HCC occurrence risk. Furthermore, body fat percentage, glycated hemoglobin (HbA1c), obesity class 1-3, waist-to-hip ratio, iron, ferritin, transferrin saturation, and urate had suggestive associations with HCC. The validation cohort further confirmed that NAFLD and ALT levels were strongly related to HCC. Reverse MR indicated that genetic susceptibility to HCC was connected to NAFLD and transferrin saturation. Sensitivity analyses showed that most of the findings were robust.

CONCLUSION

This MR study delivers evidence of the complex causal relationship between modifiable risk factors and HCC. These findings offer new insights into potential prevention and treatment strategies for HCC.

Epigenome-wide methylation analysis shows phosphonoethylamine alleviates aberrant DNA methylation in NASH caused by Pcyt2 deficiency

BACKGROUND

Aberrant DNA methylation can lead to the onset of pathological phenotypes and is increasingly being implicated in age-related metabolic diseases. In our preceding study we show that the heterozygous ablation of Pcyt2, the rate limiting enzyme in phosphatidylethanolamine (PE) synthesis, causes an age-dependent development of non-alcoholic steatohepatitis (NASH), and that treatment with the Pcyt2 substrate phosphonoethylamine (PEA) can attenuate phenotypic NASH pathologies. Here, we hypothesize that abnormal DNA methylation patterns underly the development of Pcyt2 + /- NASH. In this study, we conduct an epigenome-wide methylation analysis to characterize the differential methylation of Pcyt2 + /- livers and investigate whether the attenuation of NASH with PEA treatment is associated with changes in DNA methylation.

RESULTS

Pcyt2 + /- NASH liver experiences significant alterations in DNA methylation pattens relative to Pcyt2 + / + . Differentially methylated genes belong to pathways including PI3K-Akt signalling pathway, Foxo signalling pathway, oxidative phosphorylation and insulin signalling/secretion, indicating that epigenetic regulation underlies many of our previously established functional pathological mechanisms of Pcyt2 + /- NASH. Previously unidentified pathways during Pcyt2 deficiency are highlighted, such as cell cycle regulation and cellular senescence that may contribute to NASH development. Treatment with PEA dramatically attenuates aberrant total and protein-coding DNA methylation patterns by 96%. PEA treatment restored the methylation status of key genes involved in epigenetic modifications and induced differential methylation of genes associated with obesity and T2DM such as Adyc3, Celsr2, Fam63b.

CONCLUSION

The Pcyt2 + /- liver methylome and transcriptome is altered and likely underlies much of the pathology in Pcyt2 + /- NASH phenotype. The treatment with PEA significantly attenuates aberrant DNA methylation in Pcyt2 + /- liver and corrects the DNA methylation of genes involved in the pathogenesis of NASH, indicating its therapeutic potential. This analysis provides critical insight into the epigenetic basis of NASH pathophysiology and suggests diagnostic markers and therapeutic targets.

Druggable genome-wide Mendelian randomization identifies therapeutic targets for metabolic dysfunction-associated steatotic liver disease

BACKGROUND

Metabolic dysfunction-associated steatotic liver disease (MASLD) affects > 25% of the global population, potentially leading to severe hepatic and extrahepatic complications, including metabolic dysfunction-associated steatohepatitis. Given that the pathophysiology of MASLD is incompletely understood, identifying therapeutic targets and optimizing treatment strategies are crucial for addressing this severe condition.

METHODS

Mendelian randomization (MR) analysis was conducted using two genome-wide association study datasets: a European meta-analysis (8,434 cases; 770,180 controls) and an additional study (3,954 cases; 355,942 controls), identifying therapeutic targets for MASLD. Of 4302 drug-target genes, 2,664 genetic instrument variables were derived from cis-expression quantitative trait loci (cis-eQTLs). Colocalization analyses assessed shared causal variants between MASLD-associated single nucleotide polymorphisms and eQTLs. Using the drug target gene cis-eQTL of liver tissue from the genotype-tissue expression project, we performed MR and summary MR to validate the significance of the gene results of the blood eQTL MR. RNA-sequencing data from liver biopsies were validated using immunohistochemistry and quantitative polymerase chain reaction (qPCR) tests to confirm gene expression findings.

RESULT

MR analysis across both datasets identified significant MR associations between MASLD and two drug targets-milk fat globule-EGF factor 8 (MFGE8) (odds ratio [OR] 0.89, 95% confidence interval [CI] 0.85-0.94; P = 2.15 × 10-6) and cluster of differentiation 33 (CD33) (OR 1.17, 95% CI 1.10-1.25; P = 1.39 × 10-6). Both targets exhibited strong colocalization with MASLD. Genetic manipulation indicating MFGE8 activation and CD33 inhibition did not increase the risk for other metabolic disorders. RNA-sequencing, qPCR, and immunohistochemistry validation demonstrated consistent differential expressions of MFGE8 and CD33 in MASLD.

CONCLUSION

CD33 inhibition can reduce MASLD risk, while MFGE8 activation may offer therapeutic benefits for MASLD treatment.

Leveraging pleiotropic clustering to address high proportion correlated horizontal pleiotropy in Mendelian randomization studies

Mendelian randomization harnesses genetic variants as instrumental variables to infer causal relationships between exposures and outcomes. However, certain genetic variants can affect both the exposure and the outcome through a shared factor. This phenomenon, called correlated horizontal pleiotropy, may result in false-positive causal findings. Here, we propose a Pleiotropic Clustering framework for Mendelian randomization, PCMR. PCMR detects correlated horizontal pleiotropy and extends the zero modal pleiotropy assumption to enhance causal inference in trait pairs with correlated horizontal pleiotropic variants. Simulations show that PCMR can effectively detect correlated horizontal pleiotropy and avoid false positives in the presence of correlated horizontal pleiotropic variants, even when they constitute a high proportion of the variants connecting both traits (e.g., 30-40%). In datasets consisting of 48 exposure-common disease pairs, PCMR detects horizontal correlated pleiotropy in 7 out of the exposure-common disease pairs, and avoids detecting false positive causal links. Additionally, PCMR can facilitate the integration of biological information to exclude correlated horizontal pleiotropic variants, enhancing causal inference. We apply PCMR to study causal relationships between three common psychiatric disorders as examples.

Comparison of Patients With Familial Chylomicronemia Syndrome and Multifactorial Chylomicronemia Syndrome

CONTEXT

Patients with rare familial chylomicronemia syndrome (FCS) and relatively common multifactorial chylomicronemia syndrome (MCS) both express severe hypertriglyceridemia, defined as plasma triglyceride concentration ≥10 mmol/L (≥885 mg/dL). Clinically there can be confusion between the 2 conditions.

OBJECTIVE

To compare clinical and biochemical phenotypes in patients with genotypically characterized FCS and MCS.

METHODS

We performed targeted sequencing of DNA from 193 patients with severe hypertriglyceridemia, classified them as having either FCS or MCS, and compared clinical and biochemical characteristics.

RESULTS

Patients with FCS were significantly younger than patients with MCS (31.4 ± 16.7 vs 51.0 ± 11.3 years; P = .003), with earlier age at symptom onset (15.0 ± 15.8 vs 37.8 ± 8.8 years; P = .00066), lower body mass index (23.3 ± 3.1 vs 30.7 ± 5.0 kg/m2; P = .000016), and higher prevalence of pancreatitis events (81.8% vs 35.2%; P = .003). Furthermore, patients with FCS had a higher ratio of triglyceride to total cholesterol (ie, 4.18 ± 0.92 vs 1.08 ± 0.51; P < .0001) and lower plasma apolipoprotein B (ie, 0.56 ± 0.15 vs 1.02 ± 0.43 g/L; P < .0001) than patients with MCS. Patients with MCS with heterozygous pathogenic variants had a relatively more severe clinical presentation than other MCS genetic subgroups.

CONCLUSION

Patients with FCS have notable phenotypic differences from patients with MCS, although there is overlap. While genetic analysis of patients with persistent severe hypertriglyceridemia can definitively diagnose FCS, 8.8% of patients with MCS with sustained refractory hypertriglyceridemia behave functionally as if they have FCS, which should influence their eligibility for novel therapies for severe hypertriglyceridemia.

Genetic association of lipids and lipid-lowering drug target genes with breast cancer

BACKGROUND

Although several preclinical and epidemiological studies have shown that blood lipids and lipid-lowering drugs can reduce the risk of breast cancer, this finding remains controversial. This study aimed to explore the causal relationship between dyslipidemia,lipid-lowering drugs, and breast cancer. We also aimed to evaluate the potential impact of lipid-lowering drug targets on breast cancer.

METHOD

Data of 431 lipid- and lipid-related phenotypes were obtained from genome-wide association study (GWAS), and mendelian randomization (MR) analyses were performed using two independent breast cancer datasets as endpoints. Genetic variants associated with genes encoding lipid-lowering drug targets were extracted from the Global Lipid Genetics Consortium. Expression quantitative trait loci data in relevant tissues were used to further validate lipid-lowering drug targets that reached significance and combined with bioinformatics approaches for molecular expression and prognostic exploration. Further mediation analyses were performed to explore potential mediators.

RESULT

In two independent datasets, phosphatidylcholine (18:1_0:0 levels) was associated with breast cancer risk (discovery: odds ratio (OR) = 1.255 [95% confidence interval (CI) 1.120-1.406]; p = 8.936 × 10-5, replication: OR = 1.016 [95% CI, 1.003-1.030]; p = 0.017), HMG- CoA reductase (HMGCR) inhibition was genetically modeled and associated with a reduced risk of breast cancer (discovery: OR = 0.833 [95% CI 0.752-0.923], p = 5.12 × 10-4; replication: OR = 0.975 [95% CI 0.960-0.990], p = 1.65 × 10-3). There was a significant MR correlation between HMGCR expression in whole blood and breast cancer (OR = 1.11 [95% 1.01-1.22] p = 0.04). Bioinformatics analysis revealed that HMGCR expression higher in breast cancer tissues than in normal tissues, along with poor overall survival and relapse-free survival, and was associated with multiple immune cell infiltration. Finally, the mediation analysis showed that HMGCR inhibitors affected breast cancer through different immune cell phenotypes and C-reactive protein levels.

CONCLUSION

In this study, we found for the first time that phosphatidylcholine (18:1_0:0) levels are associated with breast cancer risk. We found that HMGCR inhibitors are associated with a reduced risk of breast cancer, and part of their action may be through pathways other than lipid-lowering, including modulation of immune function and reduction of inflammation represented by C-reactive protein levels.

Systematic interrogation of functional genes underlying cholesterol and lipid homeostasis

BACKGROUND

Dyslipidemia or hypercholesterolemia are among the main risk factors for cardiovascular diseases. Unraveling the molecular basis of lipid or cholesterol homeostasis would help to identify novel drug targets and develop effective therapeutics.

RESULTS

Here, we adopt a systematic approach to catalog the genes underlying lipid and cholesterol homeostasis by combinatorial use of high-throughput CRISPR screening, RNA sequencing, human genetic variant association analysis, and proteomic and metabolomic profiling. Such integrative multi-omics efforts identify gamma-glutamyltransferase GGT7 as an intriguing potential cholesterol and lipid regulator. As a SREBP2-dependent target, GGT7 positively regulates cellular cholesterol levels and affects the expression of several cholesterol metabolism genes. Furthermore, GGT7 interacts with actin-dependent motor protein MYH10 to control low-density lipoprotein cholesterol (LDL-C) uptake into the cells. Genetic ablation of Ggt7 in mice leads to reduced serum cholesterol levels, supporting an in vivo role of Ggt7 during cholesterol homeostasis.

CONCLUSIONS

Our study not only provides a repertoire of lipid or cholesterol regulatory genes from multiple angles but also reveals a causal link between a gamma-glutamyltransferase and cholesterol metabolism.

Causal association between metabolic syndrome and ovarian dysfunction: a bidirectional two-sample mendelian randomization

BACKGROUND

The relationship between Metabolic Syndrome (MetS) and ovarian dysfunction has been widely reported in observational studies, yet it remains not fully understood. This study employs genetic prediction methods and utilizes summary data from genome-wide association studies (GWAS) to investigate this causal link.

METHODS

We employed a bidirectional two-sample Mendelian Randomization (MR) analysis utilizing MetS and ovarian dysfunction summary data from GWAS. Inverse variance weighted (IVW) was employed as the primary MR method, supplemented by Weighted Median, Weighted Mode, and MR-Egger methods. The robustness of the results was further assessed through sensitivity analyses including MR-Egger regression, MR-PRESSO, Cochran's Q, and leave-one-out test.

RESULTS

Our MR analysis identified a causal relationship between genetically determined insulin resistance (OR = 0.26, 95% CI: 0.08-0.89, P = 0.03), waist circumference (OR = 2.14, 95% CI: 1.45-3.15, P < 0.001), BMI (OR = 2.1, 95% CI: 1.56-2.83, P < 0.001) and ovarian dysfunction. Conversely, reverse MR analysis confirmed causal effects of ovarian dysfunction on metabolic syndrome (OR = 0.98, 95% CI: 0.97-0.99, P < 0.001) and waist circumference (OR = 0.99, 95% CI: 0.98-0.99, P = 0.02). The results of MR-Egger regression test indicated that the whole analysis was not affected by horizontal pleiotropy. Additionally, the MR-PRESSO test identified outliers in SNPs, but after removal of outliers, results remained unchanged.

CONCLUSION

This study reveals a bidirectional causal connection between metabolic syndrome and ovarian dysfunction via genetic prediction methods. These findings are crucial for advancing our understanding of the interactions between these conditions and developing strategies for prevention and treatment.

Mendelian randomization-based observational cohort study on drug targets: Impact of antihypertensive and lipid-lowering therapies on inflammatory cytokines

This study assesses the causal effects of antihypertensive and lipid-lowering drugs on inflammatory cytokines using a Mendelian randomization (MR) approach. We conducted a drug-targeted MR analysis using data from large-scale genome-wide association studies and eQTL datasets. SNPs near drug target genes served as instrumental variables to investigate the impact of antihypertensive (angiotensin-converting enzyme inhibitors [ACEIs], ARBs) and lipid-lowering drugs (HMGCR inhibitors, proprotein convertase subtilisin/Kexin type 9 [PCSK9] inhibitors, Niemann-Pick C1-like 1 inhibitors) on inflammatory cytokines. Sensitivity analyses, including leave-one-out and MR-Egger tests, were performed to confirm the robustness of the findings. ACEIs were associated with decreased levels of IL-1β, TNF-α, and CRP. ARBs did not show significant effects on inflammatory cytokines. HMGCR inhibitors significantly reduced MCP-1, MIP-1β, TNF-α, and IFN-γ, while PCSK9 inhibitors were linked to reductions in IL-1β and IL-6. Sensitivity analyses supported the reliability of these findings. The study demonstrated distinct anti-inflammatory effects of ACEIs, HMGCR inhibitors, and PCSK9 inhibitors. These findings support the potential use of these drugs to mitigate inflammation-related complications in patients with chronic conditions.

Cholesterol 7 alpha-hydroxylase (CYP7A1) gene polymorphisms are associated with increased LDL-cholesterol levels and the incidence of subclinical atherosclerosis

The cholesterol 7 alpha-hydroxylase (CYP7A1) enzyme plays an important role in the conversion of cholesterol to bile acid, contributing to the reduction of cholesterol plasma levels in normal conditions. Nonetheless, recent studies have shown that some genetic variants in the enhancer and promoter regions of the CYP7A1 gene reduce the expression of the CYP7A1 enzyme, increasing plasma lipid levels, as well as the risk of developing coronary heart disease. The aim of this work was to explore whether the genetic variants (rs2081687, rs9297994, rs10107182, rs10504255, rs1457043, rs8192870, and rs3808607) of the CYP7A1 gene are involved in subclinical atherosclerosis and plasma lipid levels. We included 416 patients with subclinical atherosclerosis (SA) with coronary artery calcium (CAC) greater than zero, and 1046 controls with CAC = 0. According to the inheritance models (co-dominant, dominant, recessive, over-dominant and additive), the homozygosity of the minor allele frequencies of 7 analyzed polymorphisms showed a high incidence of SA (P < 0.05). In a sub-analysis performed including only the patients with SA, the same SNPs were associated with increased low-density lipoprotein cholesterol (LDL-C) levels. On the other hand, our findings showed that the haplotype (TGCGCTG) increases the risk of developing SA (P < 0.05). In conclusion, the rs2081687, rs9297994, rs10107182, rs10504255, rs1457043, rs8192870, and rs3808607 polymorphisms of CYP7A1 confer a risk of developing SA and elevated LDL-C levels. Our results suggest that the CYP7A1 is involved in the incidence of SA through the increase in the plasma lipid profile.

Causal Relationship Between Intelligence, Noncognitive Education, Cognition and Urinary Tract or Kidney Infection: A Mendelian Randomization Study

Background

The occurrence of urinary tract or kidney infection is correlated with intelligence, noncognitive education and cognition, but the causal relationship between them remains uncertain, and which risk factors mediate this causal relationship remains unknown.

Methods

The intelligence (n=269,867), noncognitive education (n=510,795) and cognition data (n=257,700) were obtained from genome-wide association studies (GWAS) conducted in individuals of European ethnicities. The genetic associations between these factors and urinary tract or kidney infection (UK Biobank, n=397,867) were analyzed using linkage disequilibrium score regression. We employed a two-sample univariate and multivariate Mendelian randomization to evaluate the causal relationship, and utilized a two-step Mendelian randomization to examine the involvement of 28 potential mediators and their respective mediating proportions.

Results

The genetic correlation coefficients of intelligence, noncognitive education, cognition, and urinary tract or kidney infection were -0.338, -0.218, and -0.330. The Mendelian randomization using the inverse variance weighted method revealed each 1-SD increase in intelligence, the risk of infection decreased by 15.9%, while after adjusting for noncognitive education, the risk decreased by 20%. For each 1-SD increase in noncognitive education, the risk of infection decreased by 8%, which further reduced to 7.1% after adjusting for intelligence and to 6.7% after adjusting for cognition. For each 1-SD increase in cognition, the risk of infection decreased by 10.8%, increasing to 11.9% after adjusting for noncognitive education. The effects of intelligence and cognition are interdependent. 2 out of 28 potential mediating factors exhibited significant mediation effects in the causal relationship between noncognitive education and urinary tract or kidney infection, with body mass index accounting for 12.1% of the mediation effect and smoking initiation accounting for 14.7%.

Conclusion

Enhancing intelligence, noncognitive education, and cognition can mitigate the susceptibility to urinary tract or kidney infection. Noncognitive education exhibited independent effect, while body mass index and smoking initiation assuming a mediating role.

Sex differences in predicting dyslipidemia using polygenic risk score with fatty liver index and fibrotic nonalcoholic steatohepatitis index

Non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) are recognized risk factors for dyslipidemia. Current prediction models that rely solely on dyslipidemia polygenic risk score (PRS) have certain limitations. We aimed to validate simple indexes for NAFLD and NASH as predictors of dyslipidemia using the PRS. This study utilized cohort data from an urban population-based dataset comprising 48,263 South Koreans. The incidence of dyslipidemia was higher in men than in women (32.4% and 27.8%; p < 0.001). The PRS model predicted dyslipidemia more accurately in men (AUROC [95% confidence intervals]: 0.645 [0.636-0.754]). Notably, integrating the fatty liver index (FLI) and fibrotic NASH index (FNI) with the PRS model resulted in the highest accuracy in diagnosing dyslipidemia, particularly in men (AUROC [95% confidence intervals]: 0.704 [0.698-0.711]). In conclusion, a predictive model combining the PRS with FLI and FNI was validated. This model offers more accurate predictive value for diagnosing dyslipidemia, particularly in East Asian men. Thus, our study has the clinical potential for identifying high-risk individuals and determining preventive measures for dyslipidemia in a sex-specific manner.

Precision Medicine in Cardiovascular Disease Prevention: Clinical Validation of Multi-Ancestry Polygenic Risk Scores in a U.S. Cohort

BACKGROUND

Polygenic risk score (PRS) quantifies the cumulative effects of common genetic variants across the genome, including both coding and non-coding regions, to predict the risk of developing common diseases. In cardiovascular medicine, PRS enhances risk stratification beyond traditional clinical risk factors, offering a precision medicine approach to coronary artery disease (CAD) prevention. This study evaluates the predictive performance of a multi-ancestry PRS framework for cardiovascular risk assessment using the All of Us (AoU) short-read whole-genome sequencing dataset comprising over 225,000 participants.

METHODS

We developed PRSs for lipid traits (LDL-C, HDL-C, triglycerides) and cardiometabolic conditions (type 2 diabetes, hypertension, atrial fibrillation) and constructed two metaPRSs: one integrating lipid and cardiometabolic PRSs (risk factor metaPRS) and another incorporating CAD PRSs in addition to these risk factors (risk factor + CAD metaPRS). Predictive performance was evaluated separately for each trait-specific PRS and for both metaPRSs to assess their effectiveness in CAD risk prediction across diverse ancestries. Model predictive performance, including calibration, was assessed separately for each ancestry group, ensuring that all metrics were ancestry-specific and that PRSs remain generalizable across diverse populations Results: PRSs for lipids and cardiometabolic conditions demonstrated strong predictive performance across ancestries. The risk factors metaPRS predicted CAD risk across multiple ancestries. The addition of a CAD-specific PRS to the risk factors metaPRS improved predictive performance, highlighting a genetic component in CAD etiopathology that is not fully captured by traditional risk factors, whether clinically measured or genetically inferred. Model calibration and validation across ancestries confirmed the broad applicability of PRS-based approaches in multi-ethnic populations.

CONCLUSION

PRS-based risk stratification provides a reliable, ancestry-inclusive framework for personalized cardiovascular disease prevention, enabling better targeted interventions such as pharmacological therapy and lifestyle modifications. By incorporating genetic information from both coding and non-coding regions, PRSs refine risk prediction across diverse populations, advancing the integration of genomics into precision medicine for common diseases.

Systematic Evaluation of the Impact of a Wide Range of Dietary Habits on Myocardial Infarction: A Two-Sample Mendelian Randomization Analysis

BACKGROUND

Myocardial infarction is a cardiovascular disease that significantly contributes to global morbidity and disability. Given the significant role of diet in the pathogenesis and prevention of cardiovascular diseases, this study rigorously investigates the causal relationship between dietary habits and myocardial infarction.

METHODS AND RESULTS

This study used large-scale genome-wide association studies with pooled UK Biobank data to explore associations between 9 dietary categories (83 types) and myocardial infarction. A 2-sample Mendelian randomization approach was applied to assess these associations, while multivariate Mendelian randomization and mediation analyses investigated the role of lipids in mediating the effects of diet on myocardial infarction. Univariate Mendelian analyses revealed genetic associations among 9 categories of dietary habits (83 types) and myocardial infarction. Notably, robust evidence indicates the "tablespoons of cooked vegetables per day" as the most significant risk factor for myocardial infarction development. "Coffee consumption(cups per day)" and "frequency of adding salt to food" were also identified as supplementary risk factors. In contrast, "overall alcohol intake" showed a protective effect, potentially by increasing high-density lipoprotein cholesterol (4.48% mediation) and reducing triglycerides (6.24% mediation). Cereal category, particularly "cereal consumption (bowls per week)" was associated with reduced myocardial infarction risk, contributing by raising high-density lipoprotein cholesterol (3.69% mediation) and lowering total cholesterol (8.33% mediation). Additionally, "overall cheese consumption" was also protective against myocardial infarction.

CONCLUSIONS

Our findings elucidate the influence of dietary habits on myocardial infarction, showing underlying genetic mechanisms and emphasizing the regulatory role of lipids as an intermediate.

Sirolimus as a repurposed drug for tendinopathy: A systems biology approach combining computational and experimental methods

BACKGROUND

Effective drugs for tendinopathy are lacking, resulting in significant morbidity and re-tearing rate after operation. Applying systems biology to identify new applications for current pharmaceuticals can decrease the duration, expenses, and likelihood of failure associated with the development of new drugs.

METHODS

We identify tendinopathy signature genes employing a transcriptomics database encompassing 154 clinical tendon samples. We then proposed a systems biology based drug prediction strategy that encompassed multiplex transcriptional drug prediction, systematic review assessment, deep learning based efficacy prediction and Mendelian randomization (MR). Finally, we evaluated the effects of drug target using gene knockout mice.

RESULTS

We demonstrate that sirolimus is a repurposable drug for tendinopathy, supported by: 1) Sirolimus achieves top ranking in drug-gene signature-based multiplex transcriptional drug efficacy prediction, 2) Consistent evidence from systematic review substantiates the efficacy of sirolimus in the management of tendinopathy, 3) Genetic prediction indicates that plasma proteins inhibited by mTOR (the target of sirolimus) are associated with increased tendinopathy risk. The effectiveness of sirolimus is further corroborated through in vivo testing utilizing tendon tissue-specific mTOR gene knockout mice. Integrative pathway enrichment analysis suggests that mTOR inhibition can regulate heterotopic ossification-related pathways to ameliorate clinical tendinopathy.

CONCLUSIONS

Our study assimilates knowledge of system-level responses to identify potential drugs for tendinopathy, and suggests sirolimus as a viable candidate. A systems biology approach could expedite the repurposing of drugs for human diseases that do not have well-defined targets.

Evaluation of polygenic scores for hypertrophic cardiomyopathy in the general population and across clinical settings

Hypertrophic cardiomyopathy (HCM) is an important cause of morbidity and mortality, with pathogenic variants found in about a third of cases. Large-scale genome-wide association studies (GWAS) demonstrate that common genetic variation contributes to HCM risk. Here we derive polygenic scores (PGS) from HCM GWAS and genetically correlated traits and test their performance in the UK Biobank, 100,000 Genomes Project, and clinical cohorts. We show that higher PGS significantly increases the risk of HCM in the general population, particularly among pathogenic variant carriers, where HCM penetrance differs 10-fold between those in the highest and lowest PGS quintiles. Among relatives of HCM probands, PGS stratifies risks of developing HCM and adverse outcomes. Finally, among HCM cases, PGS strongly predicts the risk of adverse outcomes and death. These findings support the broad utility of PGS across clinical settings, enabling tailored screening and surveillance and stratification of risk of adverse outcomes.

Sex differences in risk factor relationships with subarachnoid haemorrhage and intracranial aneurysms: A Mendelian randomization study

Background

The prevalence of intracranial aneurysms (IAs) and incidence of aneurysmal subarachnoid haemorrhage (aSAH) is higher in women than in men. Although several cardiometabolic and lifestyle factors have been related to the risk of IAs or aSAH, it is unclear whether there are sex differences in causal relationships of these risk factors.

Aims

The aim of this study was to determine sex differences in causal relationships between cardiometabolic and lifestyle factors and risk of aSAH and IA.

Methods

We conducted a sex-specific two-sample Mendelian randomization study using summary-level data from genome-wide association studies. We analysed low-density lipoprotein cholesterol, high-density lipoprotein cholesterol [HDL-C], triglycerides, non-HDL-C, total cholesterol, fasting glucose, systolic and diastolic blood pressure, smoking initiation, and alcohol use as exposures, and aSAH and IA (i.e. aSAH and unruptured IA combined) as outcomes.

Results

We found statistically significant sex differences in the relationship between genetically proxied non-HDL-C and aSAH risk, with odds ratios (ORs) of 0.72 (95% confidence interval 0.58, 0.88) in women and 1.01 (0.77, 1.31) in men (p-value for sex difference 0.044). Moreover, genetic liability to smoking initiation was related to a statistically significantly higher risk of aSAH in men compared to women (p-value for sex difference 0.007) with ORs of 3.81 (1.93, 7.52) and 1.12 (0.63, 1.99), respectively, and to a statistically significantly higher IA risk in men compared to women (p-value for sex difference 0.036) with ORs of 3.58 (2.04, 6.27) and 1.61 (0.98, 2.64), respectively. In addition, higher genetically proxied systolic and diastolic blood pressure were related to a higher risk of aSAH and IA in both women and men.

Conclusions

Higher genetically proxied non-HDL-C was related to a lower risk of aSAH in women compared to men. Moreover, genetic liability to smoking initiation was associated with a higher risk for aSAH and IA in men compared to women. These findings may help improve understanding of sex differences in the development of aSAH and IA.