Discovery and refinement of loci associated with lipid levels

Genetic association of lipid-lowering drugs with aortic aneurysms: a Mendelian randomization study

AIMS

The lack of effective pharmacotherapies for aortic aneurysms (AA) is a persistent clinical challenge. Lipid metabolism plays an essential role in AA. However, the impact of lipid-lowering drugs on AA remains controversial. The study aimed to investigate the genetic association between lipid-lowering drugs and AA.

METHODS AND RESULTS

Our research used publicly available data on genome-wide association studies (GWASs) and expression quantitative trait loci (eQTL) studies. Genetic instruments, specifically eQTLs related to drug-target genes and SNPs (single nucleotide polymorphisms) located near or within the drug-target loci associated with low-density lipoprotein cholesterol (LDL-C), have been served as proxies for lipid-lowering medications. Drug-Target Mendelian Randomization (MR) study is used to determine the causal association between lipid-lowering drugs and different types of AA. The MR analysis revealed that higher expression of HMGCR (3-hydroxy-3-methylglutaryl coenzyme A reductase) was associated with increased risk of AA (OR = 1.58, 95% CI = 1.20-2.09, P = 1.20 × 10-03) and larger lumen size (aortic maximum area: OR = 1.28, 95% CI = 1.13-1.46, P = 1.48 × 10-04; aortic minimum area: OR = 1.26, 95% CI = 1.21-1.42, P = 1.78 × 10-04). PCSK9 (proprotein convertase subtilisin/kexin type 9) and CETP (cholesteryl ester transfer protein) show a suggestive relationship with AA (PCSK9: OR = 1.34, 95% CI = 1.10-1.63, P = 3.07 × 10-03; CETP: OR = 1.38, 95% CI = 1.06-1.80, P = 1.47 × 10-02). No evidence to support genetically mediated NPC1L1 (Niemann-Pick C1-Like 1) and LDLR (low-density lipoprotein cholesterol receptor) are associated with AA.

CONCLUSION

This study provides causal evidence for the genetic association between lipid-lowering drugs and AA. Higher gene expression of HMGCR, PCSK9, and CETP increases AA risk. Furthermore, HMGCR inhibitors may link with smaller aortic lumen size.

New target-HMGCR inhibitors for the treatment of primary sclerosing cholangitis: A drug Mendelian randomization study

Background

No intervention definitively extends transplant-free survival in primary sclerosing cholangitis (PSC). Statins, inhibitors of 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR), may enhance PSC prognosis, but their efficacy is debated.

Methods

We analyzed HMGCR single-nucleotide polymorphisms from published genome-wide association studies using Mendelian randomization to assess the causal relationship between HMGCR and PSC risk. Effects of HMGCR were compared with proprotein convertase subtilisin kexin 9 (PCSK9) inhibitors, common lipid-lowering drugs, using coronary heart disease risk as a positive control. The inverse-variance weighted (IVW) method was the primary analysis, complemented by the weighted median method. Heterogeneity analysis, examination of horizontal pleiotropy, and leave-one-out sensitivity analysis were conducted for result robustness.

Results

Genetically predicted HMGCR exhibited a pronounced detrimental effect on PSC in both the IVW method (odds ratio [OR] [95%] = 2.43 [1.23-4.78], P = 0.010) and the weighted median method (OR [95%] = 2.36 [1.02-5.45], P = 0.044). However, PCSK9 did not reach statistical significance. Moreover, all analyses passed through heterogeneity analysis, horizontal pleiotropy analysis, and leave-one-out sensitivity analysis.

Conclusion

This study has confirmed a causal relationship between HMGCR and PSC risk, suggesting statins targeting HMGCR could enhance PSC patient outcomes.

Integrated single cell-RNA sequencing and Mendelian randomization for ischemic stroke and metabolic syndrome

Although more and more evidence has supported that metabolic syndrome (MS) is linked to ischemic stroke (IS), the molecular mechanism and genetic association between them has not been investigated. Here, we combined the existing single-cell RNA sequencing (scRNA-seq) data and mendelian randomization (MR) for stroke to understand the role of dysregulated metabolism in stroke. The shared hub genes were identified with machine learning and WGCNA. A total of six upregulated DEGs and five downregulated genes were selected for subsequent analyses. Nine genes were finally identified with random forest, Lasso regression, and XGBoost method as a potential diagnostic model. scRNA-seq also show the abnormal glycolysis level in most cell clusters in stroke and associated with the expression level of hub genes. The genetic relationship between IS and MS was verified with MR analysis. Our study reveals the common molecular profile and genetic association between ischemic stroke and metabolic syndrome.

Association of education with cholelithiasis and mediating effects of cardiometabolic factors: A Mendelian randomization study

BACKGROUND

Education, cognition, and intelligence are associated with cholelithiasis occurrence, yet which one has a prominent effect on cholelithiasis and which cardiometabolic risk factors mediate the causal relationship remain unelucidated.

AIM

To explore the causal associations between education, cognition, and intelligence and cholelithiasis, and the cardiometabolic risk factors that mediate the associations.

METHODS

Applying genome-wide association study summary statistics of primarily European individuals, we utilized two-sample multivariable Mendelian randomization to estimate the independent effects of education, intelligence, and cognition on cholelithiasis and cholecystitis (FinnGen study, 37041 and 11632 patients, respectively; n = 486484 participants) and performed two-step Mendelian randomization to evaluate 21 potential mediators and their mediating effects on the relationships between each exposure and cholelithiasis.

RESULTS

Inverse variance weighted Mendelian randomization results from the FinnGen consortium showed that genetically higher education, cognition, or intelligence were not independently associated with cholelithiasis and cholecystitis; when adjusted for cholelithiasis, higher education still presented an inverse effect on cholecystitis [odds ratio: 0.292 (95%CI: 0.171-0.501)], which could not be induced by cognition or intelligence. Five out of 21 cardiometabolic risk factors were perceived as mediators of the association between education and cholelithiasis, including body mass index (20.84%), body fat percentage (40.3%), waist circumference (44.4%), waist-to-hip ratio (32.9%), and time spent watching television (41.6%), while time spent watching television was also a mediator from cognition (20.4%) and intelligence to cholelithiasis (28.4%). All results were robust to sensitivity analyses.

CONCLUSION

Education, cognition, and intelligence all play crucial roles in the development of cholelithiasis, and several cardiometabolic mediators have been identified for prevention of cholelithiasis due to defects in each exposure.

Lipoprotein lipase as a target for obesity/diabetes related cardiovascular disease

Worldwide, the prevalence of obesity and diabetes have increased, with heart disease being their leading cause of death. Traditionally, the management of obesity and diabetes has focused mainly on weight reduction and controlling high blood glucose. Unfortunately, despite these efforts, poor medication management predisposes these patients to heart failure. One instigator for the development of heart failure is how cardiac tissue utilizes different sources of fuel for energy. In this regard, the heart switches from using various substrates, to predominantly using fatty acids (FA). This transformation to using FA as an exclusive source of energy is helpful in the initial stages of the disease. However, over the progression of diabetes this has grave end results. This is because toxic by-products are produced by overuse of FA, which weaken heart function (heart disease). Lipoprotein lipase (LPL) is responsible for regulating FA delivery to the heart, and its function during diabetes has not been completely revealed. In this review, the mechanisms by which LPL regulates fuel utilization by the heart in control conditions and following diabetes will be discussed in an attempt to identify new targets for therapeutic intervention. Currently, as treatment options to directly target diabetic heart disease are scarce, research on LPL may assist in drug development that exclusively targets fuel utilization by the heart and lipid accumulation in macrophages to help delay, prevent, or treat cardiac failure, and provide long-term management of this condition during diabetes.

Genetic proxy of lipid-lowering drugs and calcific aortic valve stenosis: A Mendelian randomization study

Background

Lipid metabolism plays an important role in the pathogenesis and development of calcific aortic valve stenosis. Our aim was to evaluate the causal effect of lipid-lowering drugs, such as low-density lipoprotein cholesterol (LDL-C) lowering and triglyceride lowering drugs, on the outcome of aortic valve stenosis using a two-sample Mendelian randomization (MR) study.

Methods

We used two genetic tools to represent the exposure of lipid-lowering drugs, including expression quantitative trait loci for the expression of drug target genes, and genetic variants within or near drug target genes that are associated with LDL-C and triglyceride concentrations from Genome-Wide Association Studies (GWAS). Effect estimates were calculated using summary-data-based MR (SMR) and inverse-variance-weighted MR (IVW-MR) analysis.

Results

Based on the results of SMR and IVW-MR analysis, LDL-C-lowering PCSK9 inhibitors have potential in reducing the risk of aortic valve stenosis (for SMR, OR: 1.044; 95%CI: 1.002-1.404; P = 0.047; for IVW-MR, OR: 1.647, 95%CI: 1.316-2.062, P < 0.001). However, no significant association was observed between triglyceride target gene expression, as well as triglyceride-lowering drugs, and aortic valve stenosis.

Conclusion

This two-sample drug-targeted MR study suggests a potential causal relationship between PCSK9 inhibitors and the reduction of calcific aortic valve stenosis risk.

Genetic Correlates of Treatment-Resistant Depression: Insights from Polygenic Scores Across Cognitive, Temperamental, and Sleep Traits in the All of US cohort

Background

Treatment-resistant depression (TRD) is a major challenge in mental health, affecting a significant number of patients and leading to considerable economic and social burdens. The etiological factors contributing to TRD are complex and not fully understood.

Objective

To investigate the genetic factors associated with TRD using polygenic scores (PGS) across various traits, and to explore their potential role in the etiology of TRD using large-scale genomic data from the All of Us Research Program (AoU).

Methods

Data from 292,663 participants in the AoU were analyzed using a case-cohort design. Treatment resistant depression (TRD), treatment responsive Major Depressive Disorder (trMDD), and all others who have no formal diagnosis of Major Depressive Disorder (non-MDD) were identified through diagnostic codes and prescription patterns. Polygenic scores (PGS) for 61 unique traits from seven domains were used and logistic regressions were conducted to assess associations between PGS and TRD. Finally, Cox proportional hazard models were used to explore the predictive value of PGS for progression rate from the diagnostic event of Major Depressive Disorder (MDD) to TRD.

Results

In the discovery set (104128 non-MDD, 16640 trMDD, and 4177 TRD), 44 of 61 selected PGS were found to be significantly associated with MDD, regardless of treatment responsiveness. Eleven of them were found to have stronger associations with TRD than with trMDD, encompassing PGS from domains in education, cognition, personality, sleep, and temperament. Genetic predisposition for insomnia and specific neuroticism traits were associated with increased TRD risk (OR range from 1.05 to 1.15), while higher education and intelligence scores were protective (ORs 0.88 and 0.91, respectively). These associations are consistent across two other independent sets within AoU (n = 104,388 and 63,330). Among 28,964 individuals tracked over time, 3,854 developed TRD within an average of 944 days (95% CI: 883 ~ 992 days) after MDD diagnosis. All eleven previously identified and replicated PGS were found to be modulating the conversion rate from MDD to TRD. Thus, those having higher education PGS would experiencing slower conversion rates than those who have lower education PGS with hazard ratios in 0.79 (80th versus 20th percentile, 95% CI: 0.74 ~ 0.85). Those who had higher insomnia PGS experience faster conversion rates than those who had lower insomnia PGS, with hazard ratios in 1.21 (80th versus 20th percentile, 95% CI: 1.13 ~ 1.30).

Conclusions

Our results indicate that genetic predisposition related to neuroticism, cognitive function, and sleep patterns play a significant role in the development of TRD. These findings underscore the importance of considering genetic and psychosocial factors in managing and treating TRD. Future research should focus on integrating genetic data with clinical outcomes to enhance our understanding of pathways leading to treatment resistance.

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

BACKGROUND

Lipid-lowering drugs are widely used among the elderly, with some studies suggesting links to muscle-related symptoms. However, the causality remains uncertain.

METHODS

Using the Mendelian randomization (MR) approach, we assessed the causal effects of genetically proxied reduced low-density lipoprotein cholesterol (LDL-C) through inhibitions of hydroxy-methyl-glutaryl-CoA reductase (HMGCR), proprotein convertase subtilisin/kexin type 9 (PCSK9), and Niemann-Pick C1-like 1 (NPC1L1) on sarcopenia-related traits, including low hand grip strength, appendicular lean mass, and usual walking pace. A meta-analysis was conducted to combine the causal estimates from different consortiums.

RESULTS

Using LDL-C pooled data predominantly from UK Biobank, genetically proxied inhibition of HMGCR was associated with higher appendicular lean mass (beta = 0.087, P = 7.56 × 10- 5) and slower walking pace (OR = 0.918, P = 6.06 × 10- 9). In contrast, inhibition of PCSK9 may reduce appendicular lean mass (beta = -0.050, P = 1.40 × 10- 3), while inhibition of NPC1L1 showed no causal impact on sarcopenia-related traits. These results were validated using LDL-C data from Global Lipids Genetics Consortium, indicating that HMGCR inhibition may increase appendicular lean mass (beta = 0.066, P = 2.17 × 10- 3) and decelerate walking pace (OR = 0.932, P = 1.43 × 10- 6), whereas PCSK9 inhibition could decrease appendicular lean mass (beta = -0.048, P = 1.69 × 10- 6). Meta-analysis further supported the robustness of these causal associations.

CONCLUSIONS

Genetically proxied HMGCR inhibition may increase muscle mass but compromise muscle function, PCSK9 inhibition could result in reduced muscle mass, while NPC1L1 inhibition is not associated with sarcopenia-related traits and this class of drugs may serve as viable alternatives to sarcopenia individuals or those at an elevated risk.

The Causal Relationship between PCSK9 Inhibitors and Osteoporosis Based on Drug-Targeted Mendelian Combined Mediation Analysis

PCSK9 inhibitors have been shown to lower serum low density lipoprotein cholesterol (LDL-C) levels and are considered integral in the treatment of cardiovascular diseases. However, the potential association between PCSK9 inhibitors and osteoporosis is unclear now. In this study, drug-targeted mendelian randomization (MR) was utilized in conjunction with mediation analysis including bone mineral density (BMD), total 25-hydroxyvitamin D (T25(OH)D) levels and calcium supplementation to investigate the causal relationship between PCSK9 inhibitors and osteoporosis. The LDL-C level was chosen as the exposure variable in a sample size of 173,082 individuals. We conducted a MR analysis on the relationship between PCSK9 inhibitors and osteoporosis, elucidating the mediators involved. Utilizing the inverse variance weighted (IVW) method, we found the risk of osteoporosis was reduced by 0.6% in those who used PCSK9 inhibitors compared with non-users (OR: 0.994, 95%CI: 0.991-0.998, P < 0.001). In people aged 30-45 years, the risk of low BMD was 1.176 times higher among PCSK9 inhibitor users compared to non-users (OR: 1.176, 95%CI: 1.017-1.336, P = 0.045). Conversely, people aged 45-60 years who used PCSK9 inhibitors had a 14.9% lower risk of low BMD compared to non-users (OR: 0.851, 95%CI: 0.732-0.968, P = 0.007). Mediation analysis revealed that 43.33% of the impact of PCSK9 inhibitors on osteoporosis was mediated through BMD levels, with the remaining 56.67% being a direct effect. Effects of PCSK9 inhibitors on BMD levels varied in different ages. In addition, the risk of high serum T25(OH)D levels were 1.091 times among PCSK9 inhibitor users compared to non-users (OR: 1.091, 95%CI: 1.065-1.112, P < 0.001), providing valuable insights for clinicians.

A new era in the science and care of kidney diseases

Notable progress in basic, translational and clinical nephrology research has been made over the past five decades. Nonetheless, many challenges remain, including obstacles to the early detection of kidney disease, disparities in access to care and variability in responses to existing and emerging therapies. Innovations in drug development, research technologies, tissue engineering and regenerative medicine have the potential to improve patient outcomes. Exciting prospects include the availability of new drugs to slow or halt the progression of chronic kidney disease, the development of bioartificial kidneys that mimic healthy kidney functions, and tissue engineering techniques that could enable transplantable kidneys to be created from the cells of the recipient, removing the risk of rejection. Cell and gene therapies have the potential to be applied for kidney tissue regeneration and repair. In addition, about 30% of kidney disease cases are monogenic and could potentially be treated using these genetic medicine approaches. Systemic diseases that involve the kidney, such as diabetes mellitus and hypertension, might also be amenable to these treatments. Continued investment, communication, collaboration and translation of innovations are crucial to realize their full potential. In addition, increasing sophistication in exploring large datasets, implementation science, and qualitative methodologies will improve the ability to deliver transformational kidney health strategies.

The role of genetically-influenced phospholipid transfer protein activity in lipoprotein metabolism and coronary artery disease

BACKGROUND

Phospholipid transfer protein (PLTP) transfers surface phospholipids between lipoproteins and as such plays a role in lipoprotein metabolism, but with unclear effects on coronary artery disease (CAD) risk. We aimed to investigate the associations of genetically-influenced PLTP activity with 1-H nuclear magnetic resonance (1H-NMR) metabolomic measures and with CAD. Furthermore, using factorial Mendelian randomization (MR), we examined the potential additional effect of genetically-influenced PLTP activity on CAD risk on top of genetically-influenced low-density lipoprotein-cholesterol (LDL-C) lowering.

METHODS

Using data from UK Biobank, genetic scores for PLTP activity and LDL-C were calculated and dichotomised based on the median, generating four groups with combinations of high/low PLTP activity and high/low LDL-C levels for the factorial MR. Linear and logistic regressions were performed on 168 metabolomic measures (N = 58,514) and CAD (N = 318,734, N-cases=37,552), respectively, with results expressed as β coefficients (in standard deviation units) or odds ratios (ORs) and 95% confidence interval (CI).

RESULTS

Irrespective of the genetically-influenced LDL-C, genetically-influenced low PLTP activity was associated with a higher high-density lipoprotein (HDL) particle concentration (β [95% CI]: 0.03 [0.01, 0.05]), smaller HDL size (-0.14 [-0.15, -0.12]) and higher triglyceride (TG) concentration (0.04 [0.02, 0.05]), but not with CAD (OR 0.99 [0.97, 1.02]). In factorial MR analyses, genetically-influenced low PLTP activity and genetically-influenced low LDL-C had independent associations with metabolomic measures, and genetically-influenced low PLTP activity did not show an additional effect on CAD risk.

CONCLUSIONS

Low PLTP activity associates with higher HDL particle concentration, smaller HDL particle size and higher TG concentration, but no association with CAD risk was observed.

Genetic effects of inflammatory cytokines on coronary artery disease and myocardial infarction and the mediating roles of lipid traits

BACKGROUND

Chronic inflammation has been connected by epidemiological evidence to coronary artery disease (CAD) along with myocardial infarction (MI). Nevertheless, it is still unclear whether reverse causality or confounders account for these connections. Our objectives are to examine the causality between inflammatory cytokines and CAD/MI as well as the potential mediating influence of lipid characteristics.

METHODS

We acquired instrumental variables through genome-wide association studies meta-analyses of 41 inflammatory cytokines (8293 individuals). Genetic associations with CAD (122 733 cases and 424 528 controls), MI (~61 505 cases and 577 716 controls) and five candidate lipid mediators were obtained from the corresponding genome-wide association studies. A two-step, two-sample Mendelian randomization analysis was applied, followed with comprehensive sensitivity analyses.

RESULTS

Genetically determined growth regulated oncogene-α was causally linked to a decreased incidence of CAD [odds ratio (OR), 0.97; 95% confidence interval (CI), 0.95-0.99; P = .007] and MI (OR, 0.95; 95% CI, 0.92-0.98; P = .002). There is suggestive evidence indicating a causal impact of macrophage inflammatory protein-1β upon CAD (OR, 1.04; 95% CI, 1.01-1.07; P = .010) and MI (OR, 1.07; 95% CI, 1.02-1.11; P = .002). Furthermore, we discovered suggestive causal connections between tumor necrosis factor-related apoptosis-inducing ligand and CAD (OR, 0.97; 95% CI, 0.95-1.00; P = .020). Two-step Mendelian randomization analysis revealed that triglycerides partially mediate the effect of growth regulated oncogene-α on CAD (proportion-mediated: 13.28%) and MI (8.05%).

CONCLUSIONS

We provided novel genetic evidence supporting the causality of inflammatory cytokines on CAD/MI and elucidate the mediating effect of triglycerides in the causal pathways linking inflammatory cytokines and CAD/MI.

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

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

A Mendelian randomization study between metabolic syndrome and its components with prostate cancer

Previous research has produced inconsistent findings concerning the connection between metabolic syndrome and prostate cancer. It is challenging for observational studies to establish a conclusive causal relationship between the two. However, Mendelian randomization can provide stronger evidence of causality in this context. To examine the causal link between a metabolic composite and its components with prostate cancer, we performed a two-sample Mendelian randomization (MR) study utilizing aggregated data from genome-wide association studies, followed by meta-analyses. In our study, we employed inverse variance weighting as the primary method for MR analysis. Additionally, we assessed potential sources of heterogeneity and horizontal pleiotropy through the Cochran's Q test and MR-Egger regression. Moreover, we used multivariate MR to determine whether smoking versus alcohol consumption had an effect on the outcomes. We found no causal relationship between metabolic syndrome and its components and prostate cancer(MetS, odds ratio [OR] = 0.95, 95% confidence interval [CI] = 0.738-1.223, p = 0.691; TG, [OR] = 1.02, 95%[CI] = 0.96-1.08, p = 0.59); HDL, [OR] = 1.02, 95% [CI] = 0.97-1.07, p = 0.47; DBP, [OR] = 1.00, 95%[CI] = 0.99-1.01, p = 0.87; SBP, [OR] = 1.00, 95%[CI] = 0.99-1.00, p = 0.26; FBG [OR] = 0.92, 95%[CI] = 0.81-1.05, p = 0.23; WC, [OR] = 0.93, 95%[CI] = 0.84-1.03, p = 0.16). Finally, the MVMR confirms that the metabolic syndrome and its components are independent of smoking and alcohol consumption in prostate cancer. We didn't find significant evidence to determine a causal relationship between the metabolic syndrome and its components and prostate cancer through MR analysis. Further research is necessary to explore the potential pathogenesis between the two diseases.

Lipid-lowering medications and risk of malignant melanoma: a Mendelian randomization study

Background

The relationship between blood lipids, lipid-modifying medications, and cancer risk has been under investigation for some time. Recent studies suggest that lipid-lowering medications might influence melanoma outcomes, though findings remain controversial. Our study aims to clarify the potential causal relationship between lipid-lowering drugs commonly used and melanoma incidence through a comprehensive Mendelian randomization (MR) analysis.

Methods

Genetic variations within an LDL-related drug target gene (LDL-cholesterol from a genome-wide association study) served as proxies for exposure to lipid-lowering drugs. We conducted a two-sample Mendelian randomization analysis using inverse variance weighting (IVW), MR-Egger, and weighted median approaches. The MR-PRESSO test and pleiotropy_test were utilized to identify and adjust for horizontal pleiotropy. Stability and reliability of the Mendelian randomization findings were assessed using the leave-one-out method, Cochran's Q test, and funnel plot analysis. Odds ratios (OR) were employed to evaluate the causal relationship between genetic proxies of lipid-lowering drugs and melanoma risk.

Results

IVW analysis revealed that HMGCR gene expression is linked to a decreased risk of melanoma [OR: 0.624(0.439-0.888); p = 0.008]. Conversely, PCSK9 gene expression is tied to an elevated risk of melanoma [OR: 1.233(1.026-1.484); p = 0.025]. No significant association was observed between NPC1L1 and melanoma.

Conclusions

HMGCR inhibitors (statins) may increase melanoma risk, while PCSK9 inhibitors (evolocumab, alirocumab) could potentially decrease melanoma risk.

Assessing causality between obstructive sleep apnea with the dyslipidemia and osteoporosis: a Mendelian randomization study

Purpose

This study aims to assess the causal relationship between Obstructive Sleep Apnea (OSA), dyslipidemia, and osteoporosis using Mendelian Randomization (MR) techniques.

Methods

Utilizing a two-sample MR approach, the study examines the causal relationship between dyslipidemia and osteoporosis. Multivariable MR analyses were used to test the independence of the causal association of dyslipidemia with OSA. Single nucleotide polymorphisms (SNPs) were selected as instrumental variables based on genome-wide significance, independence, and linkage disequilibrium criteria. The data were sourced from publicly available Genome-Wide Association Studies (GWAS) of OSA (n = 375,657) from the FinnGen Consortium, the Global Lipids Genetics Consortium of dyslipidemia (n = 188,577) and the UK Biobank for osteoporosis (n = 456,348).

Results

The MR analysis identified a significant positive association between genetically predicted OSA and triglyceride levels (OR: 1.15, 95% CI: 1.04-1.26, p = 0.006) and a negative correlation with high-density lipoprotein cholesterol (HDL-C) (OR: 0.84, 95% CI: 0.77-0.93, p = 0.0003). Conversely, no causal relationship was found between dyslipidemia (total cholesterol, triglycerides, HDL-C, and low-density lipoprotein cholesterol) and OSA or the relationship between OSA and osteoporosis.

Conclusion

The study provides evidence of a causal relationship between OSA and dyslipidemia, highlighting the need for targeted prevention and management strategies for OSA to address lipid abnormalities. The absence of a causal link with osteoporosis and in the reverse direction emphasizes the need for further research in this area.

Sex differences in risk factor relationships with subarachnoid haemorrhage and intracranial aneurysms: A Mendelian Randomisation 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 randomisation 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.

A mendelian randomization study revealing that metabolic syndrome is causally related to renal failure

Background

The onset and progression of chronic kidney disease (CKD) has been linked to metabolic syndrome (MetS), with the results of recent observational studies supporting a potential link between renal failure and MetS. The causal nature of this relationship, however, remains uncertain. This study thus leveraged a Mendelian Randomization (MR) approach to probe the causal link of MetS with renal failure.

Methods

A genetic database was initially used to identify SNPs associated with MetS and components thereof, after which causality was evaluated through the inverse variance weighted (IVW), MR-Egger regression, and weighted media techniques. Results were subsequently validated through sensitivity analyses.

Results

IVW (OR = 1.48, 95% CI = 1.21-1.82, P =1.60E-04) and weighted median (OR = 1.58, 95% CI =1.15-2.17, P = 4.64E-03) analyses revealed that MetS was linked to an elevated risk of renal failure. When evaluating the specific components of MetS, waist circumference was found to be causally related to renal failure using the IVW (OR= 1.58, 95% CI = 1.39-1.81, P = 1.74e-11), MR-Egger (OR= 1.54, 95% CI = 1.03-2.29, P = 0.036), and weighted median (OR= 1.82, 95% CI = 1.48-2.24, P = 1.17e-8). The IVW method also revealed a causal association of hypertension with renal failure (OR= 1.95, 95% CI = 1.34-2.86, P = 5.42e-04), while renal failure was not causally related to fasting blood glucose, triglyceride levels, or HDL-C levels.

Conclusion

These data offer further support for the existence of a causal association of MetS with kidney failure. It is thus vital that MetS be effectively managed in patients with CKD in clinical settings, particularly for patients with hypertension or a high waist circumference who are obese. Adequate interventions in these patient populations have the potential to prevent or delay the development of renal failure.

shaPRS: Leveraging shared genetic effects across traits or ancestries improves accuracy of polygenic scores

We present shaPRS, a method that leverages widespread pleiotropy between traits or shared genetic effects across ancestries, to improve the accuracy of polygenic scores. The method uses genome-wide summary statistics from two diseases or ancestries to improve the genetic effect estimate and standard error at SNPs where there is homogeneity of effect between the two datasets. When there is significant evidence of heterogeneity, the genetic effect from the disease or population closest to the target population is maintained. We show via simulation and a series of real-world examples that shaPRS substantially enhances the accuracy of polygenic risk scores (PRSs) for complex diseases and greatly improves PRS performance across ancestries. shaPRS is a PRS pre-processing method that is agnostic to the actual PRS generation method, and as a result, it can be integrated into existing PRS generation pipelines and continue to be applied as more performant PRS methods are developed over time.

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

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

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

Background

Acne vulgaris, a chronic inflammatory skin condition predominantly seen in teenagers, impacts more than 640 million people worldwide. The potential use of lipid-lowering medications as a treatment for acne vulgaris remains underexplored. This study seeks to investigate the impact of lipid-lowering therapies on the risk of developing acne vulgaris using two-sample Mendelian randomization (MR) analysis.

Method

The two-sample MR method was employed for analysis, and information on lipid-lowering drugs was obtained from the DrugBank and ChEMBL databases. The summary data for blood low-density lipoprotein (LDL) and triglycerides were sourced from the Global Lipids Genetics Consortium, while genome-wide association studies (GWAS) summary data for acne vulgaris were obtained from the FinnGen database. Heterogeneity was examined using the Q-test, horizontal pleiotropy was assessed using MR-Presso, and the robustness of analysis results was evaluated using leave-one-out analysis.

Results

The MR analysis provided robust evidence for an association between lowering LDL cholesterol through two drug targets and acne vulgaris, with PCSK9 showing an odds ratio (OR) of 1.782 (95%CI: 1.129-2.812, p = 0.013) and LDL receptor (LDLR) with an OR of 1.581 (95%CI: 1.071-2.334, p = 0.021). Similarly, targeting the lowering of triglycerides through lipoprotein lipase (LPL) was significantly associated with an increased risk of acne vulgaris, indicated by an OR of 1.607 (95%CI: 1.124-2.299, p = 0.009).

Conclusion

The current MR study presented suggestive evidence of a positive association between drugs targeting three genes (PCSK9, LDLR, and LPL) to lower lipids and a reduced risk of acne vulgaris.

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 proproteinconvertase subtilisin/kexin type 9 (PCSK9) inhibitors, Niemann-Pick C1-like 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.

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

AIMS

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

METHODS AND RESULTS

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

CONCLUSION

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

LAY SUMMARY

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

Unveiling Statins and Genetics in Age-Related Macular Degeneration: The Coimbra Eye Study-Report 9

Purpose

To assess the association of age-related macular degeneration (AMD) progression and statins, connected with AMD genetic risk, and if there is an interplay between statins and genetics.

Methods

In this analysis, 682 subjects made two visits (6.5-year follow-up) of the Coimbra Eye Study. Subjects who started taking statins at any time point between the two visits were considered. Progressors were defined as not having AMD at baseline and having any AMD at follow-up. Genetic risk scores (GRSs) were calculated individually with 52 independent variants associated with AMD. Time to progression was estimated using unadjusted Kaplan-Meier curves. An extended Cox model was used for the association between statins and GRS with the risk for AMD progression. Multiplicative and additive interactions were assessed.

Results

Median survival time was 7.50 years for subjects not taking statins and 7.62 for subjects taking statins (P < 0.001). Statin intake reduced the risk for progression to AMD in 48%, adjusting for age, sex, body mass index, smoking, and diabetes (model 1) and GRS (model 2). The combined effects of not taking statins and having high GRS increased the progression risk fourfold compared to taking statins and having low GRS (hazard ratio [HR] = 4.25; 95% confidence interval [CI], 1.62-11.16; P = 0.003). For subjects not taking statins, an increased risk of progression was found for those subjects with high GRS compared to subjects with low GRS (HR = 1.80; 95% CI, 1.13-2.85; P = 0.013). No statistically significant multiplicative or additive interactions were found.

Conclusions

Statins seem to be protective against AMD progression, and genetics may play a role in treatment response.

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

OBJECTIVE

High low-density-lipoprotein (LDL) cholesterol has been associated with an increased risk of coronary artery diseases (CAD) including acute myocardial infarction (AMI). However, whether lipids lowering drug treatment is causally associated with decreased risk of AMI remains largely unknown. We used Mendelian randomization (MR) to evaluate the influence of genetic variation affecting the function of lipid-lowering drug targets on AMI.

METHODS

Single-nucleotide polymorphisms (SNPs) associated with lipids as instruments were extracted from the Global Lipids Genetics Consortium (GLGC). The genome-wide association study (GWAS) data for AMI were obtained from UK Biobank. Two sample MR analysis was used to study the associations between high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and triglycerides (TG) with AMI (n = 3,927). Genetic variants associated with LDL cholesterol at or near drug target gene were used to mimic drug effects on the AMI events in drug target MR.

RESULTS

Genetically predicted higher LDL-C (per one SD increase in LDL-C of 38.67 mg/dL, OR 1.006, 95% CI 1.004-1.007) and TG (per one SD increase in TG of 90.72 mg/dL, 1.004, 1.002-1.006) was associated with increased risk of AMI, but decreased risk for higher HDL-C (per one SD increase in HDL-C of 15.51 mg/dL, 0.997, 0.995-0.999) in univariable MR. Association remained significant for LDL-C, but attenuated toward the null for HDL-C and TG in multivariable MR. Genetically proxied lower LDL-C with genetic variants at or near the PCSK9 region (drug target of evolocumab) and NPC1L1 (drug target of ezetimibe) were associated with decreased risk of AMI (0.997, 0.994-0.999 and 0.986, 0.975-0.998, respectively), whereas genetic variants at HMGCR region (drug target of statin) showed marginal association with AMI (0.995, 0.990-1.000). After excluding drug target-related SNPs, LDL-C related SNPs outside the drug target region remained a causal effect on AMI (0.994, 0.993-0.996).

CONCLUSIONS

The findings suggest that genetically predicted LDL-C may play a predominant role in the development of AMI. The drug MR results imply that ezetimibe and evolocumab may decrease the risk of AMI due to their LDL-C lowering effect, and there are other non-drug related lipid lowering pathways that may be causally linked to AMI.

Causal effects of inflammatory bowel disease on risk of type 2 diabetes: a two-sample multivariable Mendelian randomization study

AIM

This study aimed to explore the causal association between inflammatory bowel disease (IBD) and the risk of type 2 diabetes (T2D) based on a two-sample Mendelian randomization (MR) study.

METHODS

Summary single nucleotide polymorphism (SNP)-phenotype association data were obtained from published two genome-wide association studies (GWAS) including SNPs related to IBD, UC, or CD in European participants (n = 71,997) and East Asian participants (n = 16,805). Two GWAS including SNPs associated with T2D included 655,666 Europeans and 433,540 East Asians. A series of screening processes were performed to select qualified instrumental SNPs strongly related to exposure. We applied the inverse variance weighted (IVW), the MR-Egger regression, and the weighted median to estimate the causal effects of IBD, ulcerative colitis (UC) or Crohn' disease (CD) on T2D. Cochran's Q test was conducted to evaluate the statistical heterogeneity between SNPs in the IVW method. The leave-one-out analysis was employed to assess whether the results were caused by any single SNP associated with IBD, UC, or CD. Odds ratio (OR) and 95% confidence interval (CI) were calculated.

RESULTS

The IVW results demonstrated that IBD could increase the risk of T2D in the European population (OR = 1.0230, 95%CI: 1.0073-1.0390). UC was positively associated with the risk of T2D according to the weighted median (OR = 1.0274, 95%CI: 1.0009-1.0546) and IVW (OR = 1.0244, 95%CI: 1.0071-1.0421) results in the European population. The IVW results indicated that the CD was positively associated with the risk of T2D in the European population (OR = 1.0187, 95%CI: 1.0045-1.0330). In the East Asian population, there are no associations between the IBD, UC, or CD and the risk of T2D (all P > 0.05). MVMR results revealed that the causal effect UC on T2D was still statistically significant after including body mass index (BMI) or low-density lipoprotein (LDL).

CONCLUSION

IBD, UC, or CD had causal effects on the risk of T2D in the European population, which might provide evidence for the prevention of T2D in patients with IBD, UC, or CD.

New approaches to triglyceride reduction: Is there any hope left?

Triglycerides play a crucial role in the efficient storage of energy in the body. Mild and moderate hypertriglyceridemia (HTG) is a heterogeneous disorder with significant association with atherosclerotic cardiovascular disease (ASCVD), including myocardial infarction, ischemic stroke, and peripheral artery disease and represents an important component of the residual ASCVD risk in statin treated patients despite optimal low-density lipoprotein cholesterol reduction. Individuals with severe HTG (>1,000 mg/dL) rarely develop atherosclerosis but have an incremental incidence of acute pancreatitis with significant morbidity and mortality. HTG can occur from a combination of genetic (both mono and polygenic) and environmental factors including poor diet, low physical activity, obesity, medications, and diseases like insulin resistance and other endocrine pathologies. HTG represents a potential target for ASCVD risk and pancreatitis risk reduction, however data on ASCVD reduction by treating HTG is still lacking and HTG-associated acute pancreatitis occurs too rarely to effectively demonstrate treatment benefit. In this review, we address the key aspects of HTG pathophysiology and examine the mechanisms and background of current and emerging therapies in the management of HTG.

Differential age-specific associations of LDL cholesterol and body mass index with coronary heart disease

BACKGROUND AND AIMS

Low-density lipoprotein cholesterol (LDLc) and body mass index (BMI) are not always correlated and their relationship is probably dependent on age, indicating differential age-specific associations of these factors with health outcomes. We aim to discriminate the roles of LDLc and BMI in coronary heart disease (CHD) across different age groups.

METHODS

This is a prospective cohort study of 368,274 participants aged 38-73 years and free of CHD at baseline. LDLc and BMI were measured at baseline, and incident CHD was the main outcome. Cox proportional hazards model and restricted cubic spline (RCS) regression were used to estimate hazard ratio (HR) and 95% confidence interval (CI) of exposure on CHD.

RESULTS

After a mean of 12 years of follow-up, similar relationships of LDLc and BMI with CHD risk were observed in the overall population but in differential age-specific patterns. Across the age groups of <50, 50-54, 55-59, 60-64 and ≥ 65 years, the LDLc-CHD association diminished with the adjusted HRs decreasing from 1.35, 1.26, 1.19, 1.11 to 1.08; while no declining trend was found in BMI-CHD relationship with the adjusted HRs of 1.15, 1.11, 1.12, 1.13 and 1.15, respectively. The interaction and mediation between LDLc and BMI on CHD risk were more pronounced at young-age groups. LDLc-CHD but not BMI-CHD association was dependent on sex, metabolic syndrome and lipid-lowering drugs use.

CONCLUSIONS

There were differential age-specific associations of LDLc and BMI with the risk of developing CHD, calling for future efforts to discriminate the age-different benefits from lipids management or weight control on the primary prevention for CHD.

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

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

SUMMARY

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

Genetically predicted mood swings increased risk of cardiovascular disease: Evidence from a Mendelian randomization analysis

BACKGROUND

Mood swings is linked to a higher risk of cardiovascular diseases (CVDs). However, the causal relationships between them remain unknown.

METHODS

We conducted this Mendelian randomization (MR) analysis to evaluate the causal associations between mood swings (n = 373,733) and 5 CVDs, including CAD, MI, HF, AF, and stroke using summary data of large-scale genome-wide association studies (GWAS). FinnGen datasets validated the results. Various MR approaches, sensitivity analyses, multivariable MR (MVMR), and two-step MR mediation analyses were applied.

RESULTS

The MR analysis revealed significant causal effects of mood swings on CAD (OR = 1.45, 95 % CI 1.24-1.71; P = 5.52e-6), MI (OR = 1.60, 95 % CI 1.32-1.95; P = 1.77e-6), HF (OR = 1.42, 95 % CI 1.18-1.71; P = 2.32e-4), and stroke (OR = 1.48, 95 % CI 1.19-1.83; P = 3.46e-4), excluding AF (P = 0.16). In the reverse MR analysis, no causal relationships were observed. The results were reproducible using FinnGen data. In the MVMR analysis, the causal effects of mood swings on CAD, MI, HF and stroke still remain significant after adjusting potential confounding factors including BMI, smoking and T2DM, but not for LDL and hypertension. Further mediation analysis indicated hypertension may mediate the causal pathways from mood swings to CAD (18.11 %, 95 % CI: 8.83 %-27.39 %), MI (16.40 %, 95 % CI: 7.93 %-24.87 %), HF (13.06 %, 95 % CI: 6.25 %-19.86 %), and stroke (18.04 %, 95 % CI: 8.73 %-27.34 %).

CONCLUSION

Mood swings has a significant causal impact on the development of CAD, MI, HF, and stroke, partly mediated by hypertension.

Genetically predicted high serum sex hormone-binding globulin levels are associated with lower ischemic stroke risk: A sex-stratified Mendelian randomization study

OBJECTIVE

Cross-sectional and cohort studies have found insufficient evidence of a causal relationship between sex hormone-binding globulin and ischemic stroke, only associations. Here, we performed a sex-stratified, bidirectional, two-sample Mendelian randomization analysis to evaluate whether a causal relationship exists between sex hormone-binding globulin and ischemic stroke.

METHODS

Single-nucleotide polymorphisms associated with sex hormone-binding globulin and ischemic stroke were screened from genome-wide association studies summary data as instrumental variables to enable a bidirectional, two-sample Mendelian randomization study design. Inverse-variance weighted analysis was used as the main method to evaluate potential causality, and additional methods, including the weighted median and MR-Egger tests, were used to validate the Mendelian randomization results. Cochran's Q statistic, MR-Egger intercept test, and Mendelian Randomization-Pleiotropy Residual Sum and Outlier global test were used as sensitivity analysis techniques to assure the reliability of the results. Multivariable analysis was used to show the robustness of the results with key theorized confounders.

RESULTS

Inverse-variance weighted analysis showed that genetically predicted higher serum sex hormone-binding globulin levels were associated with significantly decreased risk of ischemic stroke in males (odds radio = 0.934, 95 % confidence interval = 0.885-0.985, P = 0.012) and females (odds radio = 0.924, 95 % confidence interval = 0.868-0.983, P = 0.013). In an analysis of ischemic stroke subtypes, genetically predicted higher serum sex hormone-binding globulin levels were also associated with significantly decreased risk of small-vessel occlusion in both males (odds radio = 0.849, 95 % confidence interval = 0.759-0.949, P = 0.004) and females (odds radio = 0.829, 95 % confidence interval = 0.724-0.949, P = 0.006). The association remained in sensitivity analyses and multivariable analyses. The reverse analysis suggested an association between genetically predicted risk of cardioembolism and increased serum sex hormone-binding globulin in females (Beta = 0.029 nmol/L, Standard Error = 0.010, P = 0.003).

CONCLUSION

Our findings provide new insight into the etiology of ischemic stroke and suggest that modulating serum sex hormone-binding globulin may be a therapeutic strategy to protect against ischemic stroke.

An overview of detecting gene-trait associations by integrating GWAS summary statistics and eQTLs

Detecting genes that affect specific traits (such as human diseases and crop yields) is important for treating complex diseases and improving crop quality. A genome-wide association study (GWAS) provides new insights and directions for understanding complex traits by identifying important single nucleotide polymorphisms. Many GWAS summary statistics data related to various complex traits have been gathered recently. Studies have shown that GWAS risk loci and expression quantitative trait loci (eQTLs) often have a lot of overlaps, which makes gene expression gradually become an important intermediary to reveal the regulatory role of GWAS. In this review, we review three types of gene-trait association detection methods of integrating GWAS summary statistics and eQTLs data, namely colocalization methods, transcriptome-wide association study-oriented approaches, and Mendelian randomization-related methods. At the theoretical level, we discussed the differences, relationships, advantages, and disadvantages of various algorithms in the three kinds of gene-trait association detection methods. To further discuss the performance of various methods, we summarize the significant gene sets that influence high-density lipoprotein, low-density lipoprotein, total cholesterol, and triglyceride reported in 16 studies. We discuss the performance of various algorithms using the datasets of the four lipid traits. The advantages and limitations of various algorithms are analyzed based on experimental results, and we suggest directions for follow-up studies on detecting gene-trait associations.

Exploring the Relationship Between Atorvastatin and Memory Loss: A Comprehensive Analysis Integrating Real-World Pharmacovigilance and Mendelian Randomization

BACKGROUND AND OBJECTIVE

Atorvastatin is a drug widely used to prevent cardiovascular and cerebrovascular diseases. Current observational studies suggest that atorvastatin may be associated with cognitive dysfunction (especially memory loss). However, some studies have suggested that dyslipidemia may be an important factor in cognitive dysfunction. The purpose of this study was to perform a pharmacovigilance analysis using real-world data from the US Food and Drug Administration's Adverse Event Reporting System (FAERS) to assess whether memory loss is an adverse effect of atorvastatin and to further clarify its causality through Mendelian randomization (MR).

METHODS

We extracted real-world data from the FAERS database (Quarter 1 2004 to Quarter 1 2023). Disproportionality analysis methods and measures of association such as the reporting odds ratio (OR), proportional reporting ratio, Bayesian confidence interval progressive neural network, and polynomial Gamma Poisson distribution reduction were used to assess whether memory loss was an adverse effect of atorvastatin. In addition, we used MR to evaluate causality in depth.

RESULTS

In the pharmacovigilance analysis of atorvastatin, we extracted four datasets of clinical symptoms associated with memory loss from the FAERS database [Amnesia (n = 1196), Memory impairment (n = 840), Transient global amnesia (n = 38), and Retrograde amnesia (n = 9)]. The reporting OR, proportional reporting ratio, Bayesian confidence interval progressive neural network, and Gamma Poisson distribution reduction all showed positive results for amnesia, transient global amnesia, and retrograde amnesia, while the reporting OR and Bayesian confidence interval progressive neural network also showed positive results for memory disorders. Thus, memory loss was a frequent side effect of atorvastatin. The MR analyses were used to further evaluate the association between statins and memory loss. The results of the MR analysis (statins and memory loss) are as follows: Ivw (mre) (β = 0.11 [OR = 1.11], P = 0.01 < 0.05) and the OR and β directions of MR-Egger and weighted mode were the same. The results of the MR analysis (statins and mitochondrial DNA copy number) are as follows: Ivw(mre) (β = -0.03 [OR = 0.96], P < 0.01) and the OR and β direction of MR-Egger and weighted mode are the same. The results of the MR analysis (DNA copy number and memory loss) are as follows: Ivw(β = - 0.06 [OR = 0.94], P = 0.04 < 0.05) and the OR and β direction of MR-Egger and weighted mode were the same. The pleiotropy test did not find horizontal diversity in our results.

CONCLUSIONS

This study suggests that memory loss is a notable adverse event associated with atorvastatin and provides evidence indicating a potential causal relationship between atorvastatin and memory loss. We also found that statins may further affect memory by affecting mitochondrial function. Therefore, in the clinical use of atorvastatin, it is important to carefully monitor the changes in cognitive function of patients. Second, a pharmacovigilance analysis combined with MR was used in this study to provide a new approach for the study of adverse drug reactions. This comprehensive analysis method helps to evaluate the safety of drugs and the risk of adverse reactions more comprehensively and provides doctors with a more accurate clinical decision-making basis.

Causal effects of sleep traits on metabolic syndrome and its components: a Mendelian randomization study

PURPOSE

Previous observational studies have suggested an association between sleep disturbance and metabolic syndrome (MetS). However, it remains unclear whether this association is causal. This study aims to investigate the causal effects of sleep-related traits on MetS using Mendelian randomization (MR).

METHODS

Single-nucleotide polymorphisms strongly associated with daytime napping, insomnia, chronotype, short sleep, and long sleep were selected as genetic instruments from the corresponding genome-wide association studies (GWAS). Summary-level data for MetS were obtained from two independent GWAS datasets. Univariable and multivariable MR analyses were conducted to investigate and verify the causal effects of sleep traits on MetS.

RESULTS

The univariable MR analysis demonstrated that genetically predicted daytime napping and insomnia were associated with increased risk of MetS in both discovery dataset (OR daytime napping = 1.630, 95% CI 1.273, 2.086; OR insomnia = 1.155, 95% CI 1.108, 1.204) and replication dataset (OR daytime napping = 1.325, 95% CI 1.131, 1.551; OR insomnia = 1.072, 95% CI 1.046, 1.099). For components, daytime napping was positively associated with triglycerides (beta = 0.383, 95% CI 0.160, 0.607) and waist circumference (beta = 0.383, 95% CI 0.184, 0.583). Insomnia was positively associated with hypertension (OR = 1.101, 95% CI 1.042, 1.162) and waist circumference (beta = 0.067, 95% CI 0.031, 0.104). The multivariable MR analysis indicated that the adverse effect of daytime napping and insomnia on MetS persisted after adjusting for BMI, smoking, drinking, and another sleep trait.

CONCLUSION

Our study supported daytime napping and insomnia were potential causal factors for MetS characterized by central obesity, hypertension, or elevated triglycerides.

Causal relationship between lipid-lowering drugs and ovarian cancer, cervical cancer: a drug target mendelian randomization study

BACKGROUND

The causal impact of lipid-lowering drugs on ovarian cancer (OC) and cervical cancer (CC) has received considerable attention, but its causal relationship is still a subject of debate. Hence, the objective of this study is to evaluate the impact of lipid-lowering medications on the occurrence risk of OC and CC through Mendelian randomization (MR) analysis of drug targets.

METHODS

This investigation concentrated on the primary targets of lipid-lowering medications, specifically, 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) and proprotein convertase kexin 9 (PCSK9). Genetic variations associated with HMGCR and PCSK9 were derived from published genome-wide association study (GWAS) findings to serve as substitutes for HMGCR and PCSK9 inhibitors. Employing a MR approach, an analysis was conducted to scrutinize the impact of inhibitors targeting HMGCR and PCSK9 on the occurrence of OC and CC. Coronary heart disease (CHD) risk was utilized as a positive control, and the primary outcomes encompassed OC and CC.

RESULTS

The findings of the study suggest a notable elevation in the risk of OC among patients treated with HMGCR inhibitors (OR [95%CI] = 1.815 [1.316, 2.315], p = 0.019). In contrast, no significant correlation was observed between PCSK9 inhibitors and the occurrence of OC. Additionally, the analysis did not reveal any noteworthy connection between HMGCR inhibitors, PCSK9 inhibitors, and CC.

CONCLUSION

HMGCR inhibitors significantly elevate the risk of OC in patients, but their mechanism needs further investigation, and no influence of PCSK9 inhibitors on OC has been observed. There is no significant relationship between HMGCR inhibitors, PCSK9 inhibitors, and CC.

Mediation Mendelian randomisation study on the effects of shift work on coronary heart disease and traditional risk factors via gut microbiota

Background

Epidemiological evidence suggests that there is an increased risk of coronary heart disease (CHD) related to jobs involving shift work (JSW), but the causality of and mechanism underlying such a relationship remain unclear. Therefore, we aimed to explore the relationship between JSW and CHD, investigating both causality and potential mediating factors.

Methods

We performed univariate, multivariate, and mediation Mendelian randomisation (MR) analyses using data from large genome-wide association studies focussed on JSW and CHD, as well as data on some CHD risk factors (type 2 diabetes, hypertension, obesity, and lipids measurement) and 196 gut microbiota taxa. Single-nucleotide polymorphisms significantly associated with JSW acted as instrument variables. We used inverse-variance weighting as the primary method of analysis.

Results

Bidirectional MR analysis indicated a robust effect of JSW on increased CHD risk; however, the existence of CHD did not affect the choice of JSW. We identified a mediating effects of type 2 diabetes and hypertension in this relationship, accounting for 11.89% and 14.80% of the total effect of JSW on CHD, respectively. JSW were also causally associated with the risk of type 2 diabetes and hypertension and had an effect on nine microbial taxa. The mediating influence of the Eubacterium brachy group at the genus level explained 16.64% of the total effect of JSW on hypertension. We found limited evidence for the causal effect of JSW on obesity and lipids measurements.

Conclusions

Our findings suggest a causal effect of JSW on CHD, diabetes, and hypertension. We also found evidence for a significant connection between JSW and alterations in the gut microbiota. Considering that certain microbial taxa mediated the effect of JSW on hypertension risk, targeting gut microbiota through therapeutics could potentially mitigate high risks of hypertension and CHD associated with JSW.

Epigenetic age acceleration is associated with blood lipid levels in a multi-ancestry sample of older U.S. adults

BACKGROUND

Dyslipidemia, which is characterized by an unfavorable lipid profile, is a key risk factor for cardiovascular disease (CVD). Understanding the relationships between epigenetic aging and lipid levels may help guide early prevention and treatment efforts for dyslipidemia.

METHODS

We used weighted linear regression to cross-sectionally investigate the associations between five measures of epigenetic age acceleration estimated from whole blood DNA methylation (HorvathAge Acceleration, HannumAge Acceleration, PhenoAge Acceleration, GrimAge Acceleration, and DunedinPACE) and four blood lipid measures (total cholesterol (TC), LDL-C, HDL-C, and triglycerides (TG)) in 3,813 participants (mean age = 70 years) from the Health and Retirement Study (HRS). As a sensitivity analysis, we examined the same associations in participants who fasted prior to the blood draw (n = 2,531) and in participants who did not take lipid-lowering medication (n = 1,869). Using interaction models, we also examined whether demographic factors including age, sex, and educational attainment modified the relationships between epigenetic age acceleration and blood lipids.

RESULTS

After adjusting for age, race/ethnicity, sex, fasting status, and lipid-lowering medication use, greater epigenetic age acceleration was associated with lower TC, HDL-C, and LDL-C, and higher TG (p < 0.05), although the effect sizes were relatively small (e.g., < 7 mg/dL of TC per standard deviation in epigenetic age acceleration). GrimAge acceleration and DunedinPACE associations with all lipids remained significant after further adjustment for body mass index, smoking status, and educational attainment. These associations were stronger in participants who fasted and who did not use lipid-lowering medication, particularly for LDL-C. We observed the largest number of interactions between DunedinPACE and demographic factors, where the associations with lipids were stronger in younger participants, females, and those with higher educational attainment.

CONCLUSION

Multiple measures of epigenetic age acceleration are associated with blood lipid levels in older adults. A greater understanding of how these associations differ across demographic groups can help shed light on the relationships between aging and downstream cardiovascular diseases. The inverse associations between epigenetic age and TC and LDL-C could be due to sample limitations or non-linear relationships between age and these lipids, as both TC and LDL-C decrease faster at older ages.

PCSK9 inhibitors ameliorate arterial stiffness in ACS patients: evidences from Mendelian randomization, a retrospective study and basic experiments

Background

Current evidences suggest that Proprotein Convertase Subtilisin/kexin Type 9 inhibitors (PCSK9i) exhibit a protective influence on acute coronary syndrome (ACS). Nevertheless, further investigation is required to comprehend the impact and mechanisms of these pharmaceutical agents on inflammatory factors and arterial stiffness (AS) in patients with ACS. Consequently, the objective of this study is to ascertain the influence of PCSK9i on arterial stiffness in ACS patients and elucidate the underlying mechanisms behind their actions.

Methods

This study employed Mendelian randomization (MR) analysis to examine the association between genetic prediction of PCSK9 inhibition and arterial stiffness. Data of 71 patients with ACS were retrospectively collected, including PCSK9i group (n = 36, PCSK9 inhibitors combined with statins) and control group (n = 35, statins only). Blood lipid levels, inflammatory markers and pulse wave velocity (PWV) data were collected before treatment and at 1 and 6 months after treatment for analysis. Additionally, cell experiments were conducted to investigate the impact of PCSK9i on osteogenesis of vascular smooth muscle cells (VSMCs), utilizing western blot (WB), enzyme-linked immunosorbent assay (ELISA), and calcification index measurements.

Results

The results of the MR analysis suggest that genetic prediction of PCSK9 inhibition has potential to reduce the PWV. Following treatment of statins combined with PCSK9 inhibitors for 1 and 6 months, the PCSK9i group exhibited significantly lower levels of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), C-reactive protein (CRP), interleukin-6 (IL-6), fibrinogen (FIB) and procalcitonin (PCT) compared to the control group (p < 0.05). Additionally, PWV in the PCSK9i group demonstrated significant reduction after 6 months of treatment and was found to be associated with the circulating CRP level. In cell experiments, PCSK9i pretreatment ameliorated osteogenesis of VSMCs through reducing the deposition of calcium ions, alkaline phosphatase (ALP) activity, and expression of runt-related transcription factor 2 (RUNX2).

Conclusion

PCSK9i have potential to enhance arterial stiffness in ACS patients. Specifically, at the clinical level, this impact may be attributed to alterations in circulating CRP levels. At the cellular level, it is associated with the signaling pathway linked to RUNX2.

Blood lipid levels mediating the effects of sex hormone-binding globulin on coronary heart disease: Mendelian randomization and mediation analysis

Observational studies indicate that serum sex hormone-binding globulin (SHBG) levels are inversely correlated with blood lipid levels and coronary heart disease (CHD) risk. Given that dyslipidemia is an established risk factor for CHD, we aim to employ Mendelian randomization (MR) in conjunction with mediation analysis to confirm the mediating role of blood lipid levels in the association between SHBG and CHD. First, we assessed the causality between serum SHBG levels and five cardiovascular diseases using univariable MR. The results revealed causality between SHBG levels and reduced risk of CHD, myocardial infarction, as well as hypertension. Specifically, the most significant reduction was observed in CHD risk, with an odds ratio of 0.73 (95% CI 0.63-0.86) for each one-standard-deviation increase in SHBG. The summary-level data of serum SHBG levels and CHD are derived from a sex-specific genome-wide association study (GWAS) conducted by UK Biobank (sample size = 368,929) and a large-scale GWAS meta-analysis (60,801 cases and 123,504 controls), respectively. Subsequently, we further investigated the mediating role of blood lipid level in the association between SHBG and CHD. Mediation analysis clarified the mediation proportions for four mediators: high cholesterol (48%), very low-density lipoprotein cholesterol (25.1%), low-density lipoprotein cholesterol (18.5%), and triglycerides (44.3%). Summary-level data for each mediator were sourced from the UK Biobank and publicly available GWAS. The above results confirm negative causality between serum SHBG levels and the risk of CHD, myocardial infarction, and hypertension, with the causal effect on reducing CHD risk largely mediated by the improvement of blood lipid profiles.

Proteome-wide Mendelian randomization identifies potential therapeutic targets for nonalcoholic fatty liver diseases

Nonalcoholic fatty liver disease (NAFLD) is the predominant cause of liver pathology. Current evidence highlights plasma proteins as potential therapeutic targets. However, their mechanistic roles in NAFLD remain unclear. This study investigated the involvement of specific plasma proteins and intermediate risk factors in NAFLD progression. Two-sample Mendelian randomization (MR) analysis was conducted to examine the association between plasma proteins and NAFLD. Colocalization analysis determined the shared causal variants between the identified proteins and NAFLD. The MR analysis was applied separately to proteins, risk factors, and NAFLD. Mediator shares were computed by detecting the correlations among these elements. Phenome-wide association studies (phewas) were utilized to assess the safety implications of targeting these proteins. Among 1,834 cis-protein quantitative trait loci (cis-pQTLs), after-FDR correction revealed correlations between the plasma levels of four gene-predicted proteins (CSPG3, CILP2, Apo-E, and GCKR) and NAFLD. Colocalization analysis indicated shared causal variants for CSPG3 and GCKR in NAFLD (posterior probability > 0.8). Out of the 22 risk factors screened for MR analysis, only 8 showed associations with NAFLD (p ≤ 0.05), while 4 linked to CSPG3 and GCKR. The mediator shares for these associations were calculated separately. Additionally, reverse MR analysis was performed on the pQTLs, risk factors, and NAFLD, which exhibited a causal relationship with forward MR analysis. Finally, phewas summarized the potential side effects of associated-targeting proteins, including CSPG3 and GCKR. Our research emphasized the potential therapeutic targets for NAFLD and provided modifiable risk factors for preventing NAFLD.

Association of genetic variants related to combined lipid-lowering and antihypertensive therapies with risk of cardiovascular disease: 2 × 2 factorial Mendelian randomization analyses

BACKGROUND

Lipid-lowering drugs and antihypertensive drugs are commonly combined for cardiovascular disease (CVD). However, the relationship of combined medications with CVD remains controversial. We aimed to explore the associations of genetically proxied medications of lipid-lowering and antihypertensive drugs, either alone or both, with risk of CVD, other clinical and safety outcomes.

METHODS

We divided 423,821 individuals in the UK Biobank into 4 groups via median genetic scores for targets of lipid-lowering drugs and antihypertensive drugs: lower low-density lipoprotein cholesterol (LDL-C) mediated by targets of statins or proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, lower systolic blood pressure (SBP) mediated by targets of β-blockers (BBs) or calcium channel blockers (CCBs), combined genetically lower LDL-C and SBP, and reference (genetically both higher LDL-C and SBP). Associations with risk of CVD and other clinical outcomes were explored among each group in factorial Mendelian randomization.

RESULTS

Independent and additive effects were observed between genetically proxied medications of lipid-lowering and antihypertensive drugs with CVD (including coronary artery disease, stroke, and peripheral artery diseases) and other clinical outcomes (ischemic stroke, hemorrhagic stroke, heart failure, diabetes mellitus, chronic kidney disease, and dementia) (P > 0.05 for interaction in all outcomes). Take the effect of PCSK9 inhibitors and BBs on CVD for instance: compared with the reference, PCSK9 group had a 4% lower risk of CVD (odds ratio [OR], 0.96; 95%CI, 0.94-0.99), and a 3% lower risk was observed in BBs group (OR, 0.97; 95%CI, 0.94-0.99), while combined both were associated with a 6% additively lower risk (OR, 0.94; 95%CI, 0.92-0.97; P = 0.87 for interaction).

CONCLUSIONS

Genetically proxied medications of combined lipid-lowering and antihypertensive drugs have an independent and additive effects on CVD, other clinical and safety outcomes, with implications for CVD clinical practice, subsequent trials as well as drug development of polypills.

A statistical approach for identifying single nucleotide variants that affect transcription factor binding

Non-coding variants located within regulatory elements may alter gene expression by modifying transcription factor (TF) binding sites, thereby leading to functional consequences. Different TF models are being used to assess the effect of DNA sequence variants, such as single nucleotide variants (SNVs). Often existing methods are slow and do not assess statistical significance of results. We investigated the distribution of absolute maximal differential TF binding scores for general computational models that affect TF binding. We find that a modified Laplace distribution can adequately approximate the empirical distributions. A benchmark on in vitro and in vivo datasets showed that our approach improves upon an existing method in terms of performance and speed. Applications on eQTLs and on a genome-wide association study illustrate the usefulness of our statistics by highlighting cell type-specific regulators and target genes. An implementation of our approach is freely available on GitHub and as bioconda package.

Genetic variations in anti-diabetic drug targets and COPD risk: evidence from mendelian randomization

BACKGROUND

Previous research has emphasized the potential benefits of anti-diabetic medications in inhibiting the exacerbation of Chronic Obstructive Pulmonary Disease (COPD), yet the role of anti-diabetic drugs on COPD risk remains uncertain.

METHODS

This study employed a Mendelian randomization (MR) approach to evaluate the causal association of genetic variations related to six classes of anti-diabetic drug targets with COPD. The primary outcome for COPD was obtained from the Global Biobank Meta-analysis Initiative (GBMI) consortium, encompassing a meta-analysis of 12 cohorts with 81,568 cases and 1,310,798 controls. Summary-level data for HbA1c was derived from the UK Biobank, involving 344,182 individuals. Positive control analysis was conducted for Type 2 Diabetes Mellitus (T2DM) to validate the choice of instrumental variables. The study applied Summary-data-based MR (SMR) and two-sample MR for effect estimation and further adopted colocalization analysis to verify evidence of genetic variations.

RESULTS

SMR analysis revealed that elevated KCNJ11 gene expression levels in blood correlated with reduced COPD risk (OR = 0.87, 95% CI = 0.79-0.95; p = 0.002), whereas an increase in DPP4 expression corresponded with an increased COPD incidence (OR = 1.18, 95% CI = 1.03-1.35; p = 0.022). Additionally, the primary method within MR analysis demonstrated a positive correlation between PPARG-mediated HbA1c and both FEV1 (OR = 1.07, 95% CI = 1.02-1.13; P = 0.013) and FEV1/FVC (OR = 1.08, 95% CI = 1.01-1.14; P = 0.007), and a negative association between SLC5A2-mediated HbA1c and FEV1/FVC (OR = 0.86, 95% CI = 0.74-1.00; P = 0.045). No colocalization evidence with outcome phenotypes was detected (all PP.H4 < 0.7).

CONCLUSION

This study provides suggestive evidence for anti-diabetic medications' role in improving COPD and lung function. Further updated MR analyses are warranted in the future, following the acquisition of more extensive and comprehensive data, to validate our results.

Genotype-based "virtual" metabolomics in a clinical biobank identifies novel metabolite-disease associations

Introduction: Circulating metabolites act as biomarkers of dysregulated metabolism and may inform disease pathophysiology. A portion of the inter-individual variability in circulating metabolites is influenced by common genetic variation. We evaluated whether a genetics-based "virtual" metabolomics approach can identify novel metabolite-disease associations. Methods: We examined the association between polygenic scores for 724 metabolites with 1,247 clinical phenotypes in the BioVU DNA biobank, comprising 57,735 European ancestry and 15,754 African ancestry participants. We applied Mendelian randomization (MR) to probe significant relationships and validated significant MR associations using independent GWAS of candidate phenotypes. Results and Discussion: We found significant associations between 336 metabolites and 168 phenotypes in European ancestry and 107 metabolites and 56 phenotypes in African ancestry. Of these metabolite-disease pairs, MR analyses confirmed associations between 73 metabolites and 53 phenotypes in European ancestry. Of 22 metabolitephenotype pairs evaluated for replication in independent GWAS, 16 were significant (false discovery rate p < 0.05). These included associations between bilirubin and X-21796 with cholelithiasis, phosphatidylcholine (16:0/22:5n3,18:1/20:4) and arachidonate with inflammatory bowel disease and Crohn's disease, and campesterol with coronary artery disease and myocardial infarction. These associations may represent biomarkers or potentially targetable mediators of disease risk.

Genetic Association between Lipid-Regulating Drug Targets and Diabetic Retinopathy: A Drug Target Mendelian Randomization Study

Background

Diabetic retinopathy (DR) is a diabetic microvascular complication and a leading cause of vision loss. However, there is a lack of effective strategies to reduce the risk of DR currently. The present study is aimed at assessing the causal effect of lipid-regulating targets on DR risk using a two-sample Mendelian randomization (MR) study.

Method

Genetic variants within or near drug target genes, including eight lipid-regulating targets for LDL-C (HMGCR, PCSK9, and NPC1L1), HDL-C (CETP, SCARB1, and PPARG), and TG (PPARA and LPL), were selected as exposures. The exposure data were obtained from the IEU OpenGWAS project. The outcome dataset related to DR was obtained from the FinnGen research project. Inverse-variance-weighted MR (IVW-MR) was used to calculate the effect estimates by each target. Sensitivity analyses were performed to verify the robustness of the results.

Results

There was suggestive evidence that PCSK9-mediated LDL-C levels were positively associated with DR, with OR (95% CI) of 1.34 (1.02-1.77). No significant association was found between the expression of HMGCR- and NPC1L1-mediated LDL-C levels; CETP-, SCARB1-, and PPARG-mediated HDL-C levels; PPARA- and LPL-mediated TG levels; and DR risk.

Conclusions

This is the first study to reveal a genetically causal relationship between lipid-regulating drug targets and DR risk. PCSK9-mediated LDL-C levels maybe positively associated with DR risk at the genetic level. This study provides suggestive evidence that PCSK9 inhibition may reduce the risk of DR.

Beyond guilty by association at scale: searching for causal variants on the basis of genome-wide summary statistics

Understanding the causal genetic architecture of complex phenotypes is essential for future research into disease mechanisms and potential therapies. Here, we present a novel framework for genome-wide detection of sets of variants that carry non-redundant information on the phenotypes and are therefore more likely to be causal in a biological sense. Crucially, our framework requires only summary statistics obtained from standard genome-wide marginal association testing. The described approach, implemented in open-source software, is also computationally efficient, requiring less than 15 minutes on a single CPU to perform genome-wide analysis. Through extensive genome-wide simulation studies, we show that the method can substantially outperform usual two-stage marginal association testing and fine-mapping procedures in precision and recall. In applications to a meta-analysis of ten large-scale genetic studies of Alzheimer's disease (AD), we identified 82 loci associated with AD, including 37 additional loci missed by conventional GWAS pipeline. The identified putative causal variants achieve state-of-the-art agreement with massively parallel reporter assays and CRISPR-Cas9 experiments. Additionally, we applied the method to a retrospective analysis of 67 large-scale GWAS summary statistics since 2013 for a variety of phenotypes. Results reveal the method's capacity to robustly discover additional loci for polygenic traits and pinpoint potential causal variants underpinning each locus beyond conventional GWAS pipeline, contributing to a deeper understanding of complex genetic architectures in post-GWAS analyses.

The causal relationship between sarcopenia-related traits and ischemic stroke: Insights from univariable and multivariable Mendelian randomization analyses

AIMS

The causal relationship between sarcopenia-related traits and ischemic stroke (IS) remains poorly understood. This study aimed to explore the causal impact of sarcopenia-related traits on IS and to identify key mediators of this association.

METHODS

We conducted univariable, multivariable two-sample, and two-step Mendelian randomization (MR) analyses using genome-wide association study (GWAS) data. This included data for appendicular lean mass (ALM), hand grip strength (HGS), and usual walking pace (UWP) from the UK Biobank, and IS data from the MEGASTROKE consortium. Additionally, 21 candidate mediators were analyzed based on their respective GWAS data sets.

RESULTS

Each 1-SD increase in genetically proxied ALM was associated with a 7.5% reduction in the risk of IS (95% CI: 0.879-0.974), and this correlation remained after controlling for levels of physical activity and adiposity-related indices. Two-step MR identified that six mediators partially mediated the protective effect of higher ALM on IS, with the most significant being coronary heart disease (CHD, mediating proportion: 39.94%), followed by systolic blood pressure (36.51%), hypertension (23.87%), diastolic blood pressure (15.39%), type-2 diabetes mellitus (T2DM, 12.71%), and low-density lipoprotein cholesterol (7.97%).

CONCLUSION

Our study revealed a causal protective effect of higher ALM on IS, independent of physical activity and adiposity-related indices. Moreover, we found that higher ALM could reduce susceptibility to IS partially by lowering the risk of vascular risk factors, including CHD, hypertension, T2DM, and hyperlipidemia. In brief, we elucidated another modifiable factor for IS and implied that maintaining sufficient muscle mass may reduce the risk of such disease.

Joint genotypic and phenotypic outcome modeling improves base editing variant effect quantification

CRISPR base editing screens enable analysis of disease-associated variants at scale; however, variable efficiency and precision confounds the assessment of variant-induced phenotypes. Here, we provide an integrated experimental and computational pipeline that improves estimation of variant effects in base editing screens. We use a reporter construct to measure guide RNA (gRNA) editing outcomes alongside their phenotypic consequences and introduce base editor screen analysis with activity normalization (BEAN), a Bayesian network that uses per-guide editing outcomes provided by the reporter and target site chromatin accessibility to estimate variant impacts. BEAN outperforms existing tools in variant effect quantification. We use BEAN to pinpoint common regulatory variants that alter low-density lipoprotein (LDL) uptake, implicating previously unreported genes. Additionally, through saturation base editing of LDLR, we accurately quantify missense variant pathogenicity that is consistent with measurements in UK Biobank patients and identify underlying structural mechanisms. This work provides a widely applicable approach to improve the power of base editing screens for disease-associated variant characterization.

Integrated analysis of single cell-RNA sequencing and Mendelian randomization identifies lactate dehydrogenase B as a target of melatonin in ischemic stroke

AIMS

Despite the success of single-cell RNA sequencing in identifying cellular heterogeneity in ischemic stroke, clarifying the mechanisms underlying these associations of differently expressed genes remains challenging. Several studies that integrate gene expression and gene expression quantitative trait loci (eQTLs) with genome wide-association study (GWAS) data to determine their causal role have been proposed.

METHODS

Here, we combined Mendelian randomization (MR) framework and single cell (sc) RNA sequencing to study how differently expressed genes (DEGs) mediating the effect of gene expression on ischemic stroke. The hub gene was further validated in the in vitro model.

RESULTS

We identified 2339 DEGs in 10 cell clusters. Among these DEGs, 58 genes were associated with the risk of ischemic stroke. After external validation with eQTL dataset, lactate dehydrogenase B (LDHB) is identified to be positively associated with ischemic stroke. The expression of LDHB has also been validated in sc RNA-seq with dominant expression in microglia and astrocytes, and melatonin is able to reduce the LDHB expression and activity in vitro ischemic models.

CONCLUSION

Our study identifies LDHB as a novel biomarker for ischemic stroke via combining the sc RNA-seq and MR analysis.

Factors associated with genetic markers for rotator cuff disease in patients with atraumatic rotator cuff tears

For atraumatic rotator cuff tears, genetics contributes to symptomatic tear risk and may influence rotator cuff healing after surgical repair. But little is known about how genetic factors influence rotator cuff tear patient characteristics at presentation. We collected saliva samples for genotyping from atraumatic rotator cuff tear patients. We examined nine single nucleotide polymorphisms (SNPs) associated with cuff tears in prior literature. We estimated associations of SNP dosage with (1) age at tear diagnosis, (2) bilateral atraumatic tear prevalence, and (3) tear size. Linear regression was used to estimate associations with diagnosis age adjusted for sex and principal components. Logistic regression and ordinal logistic regression were used to estimate associations with bilateral tear prevalence and tear size category, respectively, adjusting for age, sex, and principal components. Of 344 eligible patients, 336 provided sufficient samples for genotyping. Median age at tear diagnosis was 61, 22% (N = 74) had bilateral atraumatic tears, and 9% (N = 29) had massive tears. SNP rs13107325 in the SLC39A8 gene and rs11850957 in the STXBP6 gene were associated with younger diagnosis age even after accounting for multiple comparisons (rs13107325: -4 years, 95% CI = -6.5, -1.4; rs11850957: -2.7 years, 95% CI = -4.3, -1.1). No other significant associations were observed with diagnosis age, tear size, or bilateral tear prevalence. SLC39A8 encodes a Mn transporter. STXBP6 may play a role in inflammatory responses by altering phagocytosis and antigen presentation of monocytes and macrophages. Further research is needed to determine if genetic markers can be used alongside patient characteristics to aid in identifying optimal surgical repair candidates.