Discovery and refinement of loci associated with lipid levels

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.

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.

Association between atorvastatin and erectile dysfunction: a comprehensive analysis incorporating real-world pharmacovigilance and Mendelian randomization

Background

Atorvastatin is a commonly prescribed medication for the prevention of cardiovascular diseases. Recent observational studies have suggested a potential association between atorvastatin use and the occurrence of Erectile Dysfunction (ED). In this study, we aimed to explore the relationship between atorvastatin and ED using real-world data from the FAERS database and employed Mendelian randomization to assess causality.

Methods

To evaluate the disproportionality of atorvastatin in relation to ED, we conducted several pharmacovigilance analyses, including odds ratio (ROR), proportional reporting ratio (PRR), Bayesian Confidence propagation neural network (BCPNN), and gamma-Poisson contractile apparatus (GPS). Additionally, we employed Mendelian randomization to investigate the causal relationship between atorvastatin and ED.

Results

Pharmacovigilance disproportionality analysis revealed a significant association between atorvastatin and ED, as indicated by the following results: ROR [3.707078559, 95% CI (3.33250349, 4.123756054)], PRR [3.702969038, χ2 (669.2853829)], IC [1.870490139, IC025 (1.702813857)], and EBGM [3.656567867, EBGM05 (3.28709656)]. Furthermore, the two-sample Mendelian randomization analysis provided evidence supporting a causal relationship between atorvastatin use and ED, with an inverse variance weighted estimate of β = 3.17 (OR = 23.91, p = 0.02 < 0.05).

Conclusion

Based on comprehensive analyses incorporating pharmacovigilance and Mendelian randomization, our findings suggest that atorvastatin use is associated with an increased risk of ED and indicate a causal relationship. These results emphasize the importance of considering potential adverse effects, such as ED, when prescribing atorvastatin for cardiovascular disease prevention. Further research and clinical monitoring are warranted to better understand the underlying mechanisms and develop appropriate strategies to mitigate this side effect.

Metabolic Traits and Risk of Ischemic Stroke in Japanese and European Populations: A Two-Sample Mendelian Randomization Study

The role of metabolic traits in ischemic stroke (IS) has been explored through observational studies and a few Mendelian randomization (MR) studies employing limited methods in European populations. This study aimed to investigate the causal effects of metabolic traits on IS in both East Asian and European populations utilizing multiple MR methods based on genetic insights. Two-sample and multivariable MR were performed, and MR estimates were calculated as inverse-variance weighted (IVW), weighted median, and penalized weighted median. Pleiotropy was assessed by MR-Egger and Mendelian randomization pleiotropy residual sum and outlier tests. Systolic blood pressure (SBP) was associated with an increased risk of IS by IVW in both European (ORIVW: 1.032, 95% CI: 1.026-1.038, p < 0.001) and Japanese populations (ORIVW: 1.870, 95% CI: 1.122-3.116, p = 0.016), which was further confirmed by other methods. Unlike the European population, the evidence for the association of diastolic blood pressure (DBP) with IS in the Japanese population was not stable. No evidence supported an association between the other traits and IS (all Ps > 0.05) in both races. A positive association was found between SBP and IS in two races, while the results of DBP were only robust in Europeans.

Aminotransferases as causal factors for metabolic syndrome: A bidirectional Mendelian randomization study

BACKGROUND

Circulating aminotransferases (ALT and AST) have been used as biomarkers for liver injury. The causal relationships between aminotransferases and metabolic syndrome remain ambiguous.

METHODS

We conducted bidirectional and multivariable Mendelian randomization (MR) analyses between aminotransferases and traits related to metabolic syndrome using genetic variants obtained from genome-wide association studies (GWASs). MR-PRESSO tests were adopted to remove outliers and eliminate pleiotropy. MR steiger tests were conducted to ensure the correct direction of the causal effects.

RESULTS

Both aminotransferases were risk factors for essential hypertension. ALT is a risk factor for type 2 diabetes. The bidirectional causal relationship between ALT and hyperglycemia, serum lipids, and obesity was demonstrated. The effect of fasting glucose on AST was demonstrated, while type 2 diabetes did not affect AST. The effect of HDL-C on ALT and the effect of triglycerides on AST were found in multivariable MR analyses.

CONCLUSIONS

Our bidirectional MR analyses suggest that ALT and AST are causally associated with several metabolic syndrome-related traits, especially hypertension and type 2 diabetes. These findings highlight the potential role of aminotransferases as biomarkers and therapeutic targets for metabolic syndrome.

The causal associations of circulating lipids with Barrett's Esophagus and Esophageal Cancer: a bi-directional, two sample mendelian randomization analysis

OBJECTIVE

The causal associations of circulating lipids with Barrett's Esophagus (BE) and Esophageal Cancer (EC) has been a topic of debate. This study sought to elucidate the causality between circulating lipids and the risk of BE and EC.

METHODS

We conducted two-sample Mendelian randomization (MR) analyses using single nucleotide polymorphisms (SNPs) of circulating lipids (n = 94,595 - 431,167 individuals), BE (218,792 individuals), and EC (190,190 individuals) obtained from the publicly available IEU OpenGWAS database. The robustness and reliability of the results were ensured by employing inverse-variance weighted (IVW), weighted median, MR-Egger, and MR-PRESSO methods. The presence of horizontal pleiotropy, heterogeneities, and stability of instrumental variables were assessed through MR-Egger intercept test, Cochran's Q test, and leave-one-out sensitivity analysis. Additionally, bidirectional MR and multivariable MR (MVMR) were performed to explore reverse causality and adjust for known confounders, respectively.

RESULTS

None of the testing methods revealed statistically significant horizontal pleiotropy, directional pleiotropy, or heterogeneity. Univariate MR analyses using IVW indicated a robust causal relationship between increased triglycerides and BE (odds ratio [OR] = 1.79, p-value = 0.009), while no significant association with EC was observed. Inverse MR analysis indicated no evidence of reverse causality in the aforementioned outcomes. In MVMR analyses, elevated triglycerides (TRG) were significantly and positively associated with BE risk (OR = 1.79, p-value = 0.041).

CONCLUSION

This MR study suggested that genetically increased triglycerides were closely related to an elevated risk of BE, potentially serving as a biomarker for the diagnosis of BE in the future.

Association between dyslipidemia and the risk of incident chronic kidney disease affected by genetic susceptibility: Polygenic risk score analysis

BACKGROUND

The effect of dyslipidemia on kidney disease outcomes has been inconclusive, and it requires further clarification. Therefore, we aimed to investigate the effects of genetic factors on the association between dyslipidemia and the risk of chronic kidney disease (CKD) using polygenic risk score (PRS).

METHODS

We analyzed data from 373,523 participants from the UK Biobank aged 40-69 years with no history of CKD. Baseline data included plasma levels of total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride, as well as genome-wide genotype data for PRS. Our primary outcome, incident CKD, was defined as a composite of estimated glomerular filtration rate < 60 ml/min/1.73 m2 and CKD diagnosis according to International Classification of Disease-10 codes. The effects of the association between lipid levels and PRS on incident CKD were assessed using the Cox proportional hazards model. To investigate the effect of this association, we introduced multiplicative interaction terms into a multivariate analysis model and performed subgroup analysis stratified by PRS tertiles.

RESULTS

In total, 4,424 participants developed CKD. In the multivariable analysis, PRS was significantly predictive of the risk of incident CKD as both a continuous variable and a categorized variable. In addition, lower total cholesterol, LDL-C, HDL-C, and higher triglyceride levels were significantly associated with the risk of incident CKD. There were interactions between triglycerides and intermediate and high PRS, and the interactions were inversely associated with the risk of incident CKD.

CONCLUSIONS

This study showed that PRS presented significant predictive power for incident CKD and individuals in the low-PRS group had a higher risk of triglyceride-related incident CKD.

Clinically relevant plasma proteome for adiposity depots: evidence from systematic mendelian randomization and colocalization analyses

BACKGROUND

The accumulation of visceral and ectopic fat comprise a major cause of cardiometabolic diseases. However, novel drug targets for reducing unnecessary visceral and ectopic fat are still limited. Our study aims to provide a comprehensive investigation of the causal effects of the plasma proteome on visceral and ectopic fat using Mendelian randomization (MR) approach.

METHODS

We performed two-sample MR analyses based on five large genome-wide association study (GWAS) summary statistics of 2656 plasma proteins, to screen for causal associations of these proteins with traits of visceral and ectopic fat in over 30,000 participants of European ancestry, as well as to assess mediation effects by risk factors of outcomes. The colocalization analysis was conducted to examine whether the identified proteins and outcomes shared casual variants.

RESULTS

Genetically predicted levels of 14 circulating proteins were associated with visceral and ectopic fat (P < 4.99 × 10- 5, at a Bonferroni-corrected threshold). Colocalization analysis prioritized ten protein targets that showed effect on outcomes, including FST, SIRT2, DNAJB9, IL6R, CTSA, RGMB, PNLIPRP1, FLT4, PPY and IL6ST. MR analyses revealed seven risk factors for visceral and ectopic fat (P < 0.0024). Furthermore, the associations of CTSA, DNAJB9 and IGFBP1 with primary outcomes were mediated by HDL-C and SHBG. Sensitivity analyses showed little evidence of pleiotropy.

CONCLUSIONS

Our study identified candidate proteins showing putative causal effects as potential therapeutic targets for visceral and ectopic fat accumulation and outlined causal pathways for further prevention of downstream cardiometabolic diseases.

Autoimmune diseases and their genetic link to bronchiectasis: insights from a genetic correlation and Mendelian randomization study

Background

Previous studies have demonstrated that autoimmune diseases are closely associated with bronchiectasis (BE). However, the causal effects between autoimmune diseases and BE remain elusive.

Methods

All summary-level data were obtained from large-scale Genome-Wide Association Studies (GWAS). The univariate Mendelian randomization (UVMR) was utilized to investigate the genetic causal correlation (rg) of 12 autoimmune diseases and bronchiectasis, The Multivariable Mendelian Randomization (MVMR) method was used to explore the effects of the confounding factors. Further investigation was conducted to identify potential intermediate factors using mediation analysis. Finally, the linkage disequilibrium score regression (LDSC) method was used to identify genetic correlations among complex traits. A series of sensitivity analyses was performed to validate the robustness of the results.

Results

The LDSC analysis revealed significant genetic correlations between BE and Crohn's disease (CD) (rg = 0.220, P = 0.037), rheumatoid arthritis (RA) (rg = 0.210, P = 0.021), and ulcerative colitis (UC) (rg = 0.247, P = 0.023). However, no genetic correlation was found with other autoimmune diseases (P > 0.05). The results of the primary IVW analysis suggested that for every SD increase in RA, there was a 10.3% increase in the incidence of BE (odds ratio [OR] = 1.103, 95% confidence interval [CI] 1.055-1.154, P = 1.75×10-5, FDR = 5.25×10-5). Furthermore, for every standard deviation (SD) increase in celiac disease (CeD), the incidence of BE reduced by 5.1% (OR = 0.949, 95% CI 0.902-0.999, P = 0.044, FDR = 0.044). We also observed suggestive evidence corresponding to a 3% increase in BE incidence with T1DM (OR = 1.033, 95% CI 1.001-1.066, P = 0.042, FDR = 0.063). Furthermore, MVMR analysis showed that RA was an independent risk factor for BE, whereas mediator MR analysis did not identify any mediating factors. The sensitivity analyses corroborated the robustness of these findings.

Conclusion

LDSC analysis revealed significant genetic correlations between several autoimmune diseases and BE, and further MVMR analysis showed that RA is an independent risk factor for BE.

MUSSEL: Enhanced Bayesian polygenic risk prediction leveraging information across multiple ancestry groups

Polygenic risk scores (PRSs) are now showing promising predictive performance on a wide variety of complex traits and diseases, but there exists a substantial performance gap across populations. We propose MUSSEL, a method for ancestry-specific polygenic prediction that borrows information in summary statistics from genome-wide association studies (GWASs) across multiple ancestry groups via Bayesian hierarchical modeling and ensemble learning. In our simulation studies and data analyses across four distinct studies, totaling 5.7 million participants with a substantial ancestral diversity, MUSSEL shows promising performance compared to alternatives. For example, MUSSEL has an average gain in prediction R2 across 11 continuous traits of 40.2% and 49.3% compared to PRS-CSx and CT-SLEB, respectively, in the African ancestry population. The best-performing method, however, varies by GWAS sample size, target ancestry, trait architecture, and linkage disequilibrium reference samples; thus, ultimately a combination of methods may be needed to generate the most robust PRSs across diverse populations.

Associations between lipid-lowering drugs and pregnancy and perinatal outcomes: a Mendelian randomization study

INTRODUCTION

Mounting evidence has indicated that maternal dyslipidemia is associated with adverse obstetric outcomes, and the actions of lipid-lowering drugs in pregnant women remain controversial. Hence, this study aimed to appraise the causal relationship of lipid-lowering drugs [hydroxymethylglutaryl-coenzyme reductase (HMGCR) inhibitors, PCSK9 inhibitors, and NPC1L1 inhibitors] with pregnancy and perinatal outcomes using drug-targeting Mendelian randomization analysis.

METHODS

As a proxy for lipid-lowering drug exposure, two genetic instruments were used: genetic variants within or near the gene linked to low-density lipoprotein cholesterol (LDL-C) and the expression of quantitative trait loci of the drug target gene. Effect estimates were calculated using the inverse variance weighting (IVW) method and summary data-based Mendelian randomization (SMR) method. Heterogeneity and pleiotropy were assessed by Mendelian randomization-Egger regression, the Cochran Q test, and MR-PRESSO analysis.

RESULTS

HMGCR inhibitors were ascribed to a reduced risk of preeclampsia in both the IVW-MR method [odds ratio (OR) 0.583; 95% confidence interval (CI) 0.418-0.812; P  = 0.001] and SMR analysis (OR 0.816; 95% CI 0.675-0.986; P  = 0.036). The causal link between HMGCR inhibitors and offspring birthweight was statistically significant only in the analysis using the IVW method (OR, 0.879; 95% CI, 0.788-0.980; P  = 0.020), and the combined results of the OR values supported the potential inhibitory effect of HMGCR inhibitors on offspring birthweight. Causal associations between lipid-lowering drugs and gestational diabetes, preterm birth, and congenital anomalies were not detected in either analysis.

CONCLUSION

No causal associations were observed between lipid-lowering drugs and gestational diabetes, preterm birth or congenital anomalies, whereas genetically predicted HMGCR inhibition dramatically reduced the risk of preeclampsia but attenuated offspring birthweight.

Association between fatty liver index and controlled attenuation parameters as markers of metabolic dysfunction-associated fatty liver disease and bone mineral density: observational and two-sample Mendelian randomization studies

Previously observational studies did not draw a clear conclusion on the association between fatty liver diseases and bone mineral density (BMD). Our large-scale studies revealed that MAFLD and hepatic steatosis had no causal effect on BMD, while some metabolic factors were correlated with BMD. The findings have important implications for the relationship between fatty liver diseases and BMD, and may help direct the clinical management of MAFLD patients who experience osteoporosis and osteopenia.

PURPOSE

Liver and bone are active endocrine organs with several metabolic functions. However, the link between metabolic dysfunction-associated fatty liver disease (MAFLD) and bone mineral density (BMD) is contradictory.

METHODS

Using the UK Biobank and National Health and Nutrition Examination Survey (NHANES) dataset, we investigated the association between MAFLD, steatosis, and BMD in the observational analysis. We performed genome-wide association analysis to identify single-nucleotide polymorphisms associated with MAFLD. Large-scale two-sample Mendelian randomization (TSMR) analyses examined the potential causal relationship between MAFLD, hepatic steatosis, or major comorbid metabolic factors, and BMD.

RESULTS

After adjusting for demographic factors and body mass index, logistic regression analysis demonstrated a significant association between MAFLD and reduced heel BMD. However, this association disappeared after adjusting for additional metabolic factors. MAFLD was not associated with total body, femur neck, and lumbar BMD in the NHANES dataset. Magnetic resonance imaging-measured steatosis did not show significant associations with reduced total body, femur neck, and lumbar BMD in multivariate analysis. TSMR analyses indicated that MAFLD and hepatic steatosis were not associated with BMD. Among all MAFLD-related comorbid factors, overweight and type 2 diabetes showed a causal relationship with increased BMD, while waist circumference and hyperlipidemia had the opposite effect.

CONCLUSION

No causal effect of MAFLD and hepatic steatosis on BMD was observed in this study, while some metabolic factors were correlated with BMD. This has important implications for understanding the relationship between fatty liver disease and BMD, which may help direct the clinical management of MAFLD patients with osteoporosis.

Genome-wide characterization of circulating metabolic biomarkers

Genome-wide association analyses using high-throughput metabolomics platforms have led to novel insights into the biology of human metabolism1-7. This detailed knowledge of the genetic determinants of systemic metabolism has been pivotal for uncovering how genetic pathways influence biological mechanisms and complex diseases8-11. Here we present a genome-wide association study for 233 circulating metabolic traits quantified by nuclear magnetic resonance spectroscopy in up to 136,016 participants from 33 cohorts. We identify more than 400 independent loci and assign probable causal genes at two-thirds of these using manual curation of plausible biological candidates. We highlight the importance of sample and participant characteristics that can have significant effects on genetic associations. We use detailed metabolic profiling of lipoprotein- and lipid-associated variants to better characterize how known lipid loci and novel loci affect lipoprotein metabolism at a granular level. We demonstrate the translational utility of comprehensively phenotyped molecular data, characterizing the metabolic associations of intrahepatic cholestasis of pregnancy. Finally, we observe substantial genetic pleiotropy for multiple metabolic pathways and illustrate the importance of careful instrument selection in Mendelian randomization analysis, revealing a putative causal relationship between acetone and hypertension. Our publicly available results provide a foundational resource for the community to examine the role of metabolism across diverse diseases.

The association of Sort1 expression with LDL subfraction and inflammation in patients with coronary artery disease

BACKGROUND

Controversial effect of sortilin on lipoprotein metabolism in the development of atherosclerosis reveals the need for more extensive research.

OBJECTIVES

The aim of this study was to investigate the association between Sort1 gene expression and lipids, lipoprotein subfractions, and inflammation in CAD.

METHODS

The study population included 162 subjects with CAD and 49 healthy individuals. The Sort1 gene expression level was determined by qRT-PCR using Human Sortilin TaqMan Gene Expression Assays. Lipoprotein subclasses were analysed by the Lipoprint system. Serum levels of apolipoprotein and CRP were measured by autoanalyzer.

RESULTS

Sort1 gene expression and atherogenic subfraction (SdLDL) levels were significantly higher (p < 0.001) while atheroprotective subfraction (LbLDL) was lower in the subjects with CAD (p < 0.050). Also, increased Sort1 gene expression levels were observed in those with higher CRP values.

CONCLUSIONS

Our findings reveal that the high Sort1 gene expression has a prominent linear relationship with both the atherogenic LDL phenotype and proinflammation, thereby might contribute to the occurrence of CAD.

Novel functions of Tribbles-homolog 1 in liver, adipocytes and atherosclerosis

PURPOSE OF REVIEW

Human genetics studies have sparked great interest in the pseudokinase Tribbles homolog 1, as variant at the TRIB1 gene locus were robustly linked to several cardiometabolic traits, including plasma lipids and coronary artery disease. In this review, we summarize recent findings from mouse models that investigated the function of hepatic and adipocyte Trib1 in lipid metabolism and its role in atherosclerosis.

RECENT FINDINGS

Studies in atherosclerosis prone low-density lipoprotein (LDL)-receptor knockout mice suggested that systemic Trib1 -deficiency promotes atherosclerotic lesion formation through the modulation of plasma lipids and inflammation. Further, investigations in mice with hepatocyte specific deletion of Trib1 identified a novel role in the catabolism of apoB-containing lipoproteins via regulation of the LDL-receptor. Moreover, recent studies on Trib1 in adipocytes uncovered critical functions in adipose tissue biology, including the regulation of plasma lipid and adiponectin levels and the response to β3-adrenergic receptor activation.

SUMMARY

Functional studies in mice have expanded our understanding of how Trib1 contributes to various aspects of cardiometabolic diseases. They support the notion that Trib1 exerts tissue-specific effects, which can result in opposing effects on cardiometabolic traits. Additional studies are required to fully elucidate the molecular mechanisms underlying the cellular and systemic effects of Trib1 .

Association between genetically proxied lipid-lowering drug targets, lipid traits, and amyotrophic lateral sclerosis: a mendelian randomization study

BACKGROUND

The use of circulating lipid traits as biomarkers to predict the risk of amyotrophic lateral sclerosis (ALS) is currently controversial, and the evidence-based medical evidence for the use of lipid-lowering agents, especially statins, on ALS risk remains insufficient. Our aim was to apply a Mendelian randomization (MR) approach to assess the causal impact of lipid-lowering agents and circulating lipid traits on ALS risk.

MATERIALS AND METHODS

Our study included primary and secondary analyses, in which the risk associations of lipid-lowering gene inhibitors, lipid traits, and ALS were assessed by the inverse variance weighting method as the primary approach. The robustness of the results was assessed using LDSC assessment, conventional MR sensitivity analysis, and used Mediating MR to explore potential mechanisms of occurrence. In the secondary analysis, the association of lipid-lowering genes with ALS was validated using the Summary data-based Mendelian Randomization (SMR) method.

RESULTS

Our results showed strong evidence between genetic proxies for Apolipoprotein B (ApoB) inhibitor (OR = 0.76, 95% CI = 0.68 - 0.86; P = 5.58 × 10-6) and reduced risk of ALS. Additionally, 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) inhibitor (OR = 1.06, 95% CI = 0. 85-1.33) was not found to increase ALS risk. SMR results suggested that ApoB expression was associated with increased ALS risk, and colocalization analysis did not support a significant common genetic variation between ApoB and ALS. Mediator MR analysis suggested a possible mediating role for interleukin-6 and low-density lipoprotein cholesterol (LDL-C). While elevated LDL-C was significantly associated with increased risk of ALS among lipid traits, total cholesterol (TC) and ApoB were weakly associated with ALS. LDSC results suggested a potential genetic correlation between these lipid traits and ALS.

CONCLUSIONS

Using ApoB inhibitor can lower the risk of ALS, statins do not trigger ALS, and LDL-C, TC, and ApoB levels can predict the risk of ALS.

Association of lipid-modifying therapy with risk of obstructive sleep apnea: A drug-target mendelian randomization study

BACKGROUND

Obstructive sleep apnea (OSA) is considered to be an important contributor of dyslipidemia. However, there lacks observational studies focusing on the potential effect of lipid management on OSA risk. Thus, we aimed to investigate the genetic association of lipid-modifying therapy with risk of OSA.

METHODS

A drug-target mendelian randomization (MR) study using both cis-variants and cis-expression quantitative trait loci (eQTLs) of lipid-modifying drug targets was performed. The MR analyses used summary-level data of genome wide association studies (GWAS). Primary MR analysis was conducted using inverse-variance-weighted (IVW) method. Sensitivity analysis was performed using weighted median (WM) and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods.

RESULTS

Genetically proxied low-density lipoprotein cholesterol (LDL-C)-lowering effect of cholesteryl ester transfer protein (CETP) was associated with reduced risk of OSA (odds ratio [OR] =0.75, 95% confidence interval [CI]: 0.60-0.94, false discovery rate [FDR] q value = 0.046). A significant MR association with risk of OSA was observed for CETP expression in subcutaneous adipose tissue (OR = 0.94, 95%CI: 0.89-1.00, FDR q value = 0.049), lung (OR = 0.94, 95%CI: 0.89-1.00, FDR q value = 0.049) and small intestine (OR = 0.96, 95%CI: 0.93-1.00, FDR q value = 0.049). No significant effects of high-density lipoprotein cholesterol (HDL-C)-raising effect of CETP inhibition, LDL-C-lowering and triglycerides-lowering effect of other drug targets on OSA risk were observed.

CONCLUSIONS

The present study presented genetic evidence supporting the association of LDL-C-lowering therapy by CETP inhibition with reduced risk of OSA. These findings provided novel insights into the role of lipid management in patients with OSA and encouraged further clinical validations and mechanistic investigations.

To explore the causal association between the serum lipid profile and inflammatory bowel disease using bidirectional Mendelian randomisation analysis

Background

Despite studies confirming that patients with inflammatory bowel disease (IBD) present with dyslipidaemia, the associations between IBD and the serum lipid profile have not been determined. The present study aimed to investigate the causal relationship between the serum lipid profile and IBD risk and elucidate the nature of the interactions between them.

Methods

Two-sample Mendelian randomisation (MR) analysis was performed to investigate the causal links between total cholesterol (TC), total triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A (Apo A), apolipoprotein B (Apo B) and lipoprotein (a) (Lp(a)) and IBD. The study was carried out using the R TwoSampleMR and Mendelian randomisation packages.

Results

All MR methods, including the weighted median, weighted mode, inverse-variance weighted model, MR-PRESSO, contamination mixture and MR Egger, supported a null causal relationship between TG, TC, HDL-C, LDL-C, Apo A, Apo B and Lp(a) and between IBD, Crohn's disease and ulcerative colitis. Null causal effects of lipid indices on IBD were validated through independent genome-wide association studies (GWAS), indicating that the findings are robust.

Conclusion

Our findings suggest that none of the seven lipid indices may be a potential risk factor for the onset of IBD. However, additional research is needed since our MR analyses cannot assess the potential non-linear causal relationship between serum lipids and IBD.

Association between genetically proxied PCSK9 inhibition and systemic lupus erythematosus risk: A mendelian randomization study

BACKGROUND

Preclinical and epidemiological studies suggest that proprotein convertase subtilisin/kexin type 9 (PCSK9) had a potential effect on the development of SLE, but it was unclear whether a causal relationship exists. We aimed to investigate the association between genetically proxied inhibition of PCSK9 and the risk of SLE using a two-sample Mendelian randomization (MR) approach.

METHODS

Single nucleotide polymorphisms (SNPs) associated with PCSK9 were extracted from pooled data obtained from the Global Lipid Genetics Consortium (GLGC) Genome-wide Association Study (GWAS) related to LDL-c levels, which was used as a proxy for PCSK9 inhibition. Pooled statistics for SLE were obtained from an independent GWAS dataset including 5201 SLE patients and 9066 controls. Inverse variance-weighted random-effects models were used to examine the association between genetically proxied inhibition of PCSK9 and the risk of SLE. MR-Egger, weighted median, weighted mode, Simple mode, and co-location analyses were used as sensitivity analyses to test the robustness of the analyses.

RESULTS

Genetically proxied inhibition of PCSK9 was associated with a reduced risk of SLE (OR = 0.51, 95% CI = 0.34 to 0.77, p = .001). This finding was replicated in an earlier GLGC GWAS analysis (OR = 0.59, 95% CI = 0.40 to 0.87, p = .007). Sensitivity analysis ensured that the results were robust. Co-localization analysis did not find evidence of shared causal variation between PCSK9 and SLE.

CONCLUSIONS

This Mendelian randomization study showed that PCSK9 was associated with SLE pathogenesis, and its inhibition was associated with a reduced risk of SLE. This study has offered a prospective therapeutic avenue for intervening in the progression of SLE by inhibiting PCSK9 levels.

A gut-derived hormone regulates cholesterol metabolism

The reciprocal coordination between cholesterol absorption in the intestine and de novo cholesterol synthesis in the liver is essential for maintaining cholesterol homeostasis, yet the mechanisms governing the opposing regulation of these processes remain poorly understood. Here, we identify a hormone, Cholesin, which is capable of inhibiting cholesterol synthesis in the liver, leading to a reduction in circulating cholesterol levels. Cholesin is encoded by a gene with a previously unknown function (C7orf50 in humans; 3110082I17Rik in mice). It is secreted from the intestine in response to cholesterol absorption and binds to GPR146, an orphan G-protein-coupled receptor, exerting antagonistic downstream effects by inhibiting PKA signaling and thereby suppressing SREBP2-controlled cholesterol synthesis in the liver. Therefore, our results demonstrate that the Cholesin-GPR146 axis mediates the inhibitory effect of intestinal cholesterol absorption on hepatic cholesterol synthesis. This discovered hormone, Cholesin, holds promise as an effective agent in combating hypercholesterolemia and atherosclerosis.

Drug Target Mendelian Randomization Study of PCSK9 and HMG-CoA Reductase Inhibition and Atrial Fibrillation

INTRODUCTION

Atrial fibrillation (AF) is a prevalent cardiac arrhythmia with significant clinical implications. The potential influence of lipid-lowering therapies, specifically PCSK9 inhibitors (PCSK9i) and HMG-CoA reductase inhibitors (statins), on AF risk remains a topic of interest. This mendelian randomization (MR) study aimed to elucidate the causal relationship between genetically predicted inhibition of PCSK9 and HMG-CoA reductase and the risk of AF.

METHODS

Utilizing publicly available, summary-level genome-wide association study data, we employed single-nucleotide polymorphisms associated with lower LDL-C levels as instruments for gene-simulated inhibition of PCSK9 and HMG-CoA reductase. Multiple MR techniques were applied to estimate the causal effects, and sensitivity analyses were conducted to validate the results.

RESULTS

Genetically predicted inhibition of PCSK9 demonstrated a reduced risk of AF, with an odds ratio (OR) of 0.92 (95% CI: 0.85-0.99, p = 0.01) using the inverse variance-weighted (IVW) method. In contrast, the inhibition of HMG-CoA reductase did not exhibit a statistically significant association with AF risk (IVW: OR = 1.11, 95% CI: 1.00-1.22, p = 0.05).

CONCLUSION

Our MR study suggests that genetically predicted inhibition of PCSK9, but not HMG-CoA reductase, is associated with a lower risk of AF. These findings provide evidence for a causal protective effect of PCSK9i on AF and support the use of PCSK9i for AF prevention in patients with dyslipidemia. Further studies are needed to elucidate the mechanisms underlying the differential effects of PCSK9i and statins on AF and to confirm the clinical implications of our findings.

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

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

Advancements in elucidating the pathogenesis of actinic keratosis: present state and future prospects

Solar keratosis, also known as actinic keratosis (AK), is becoming increasingly prevalent. It is a benign tumor that develops in the epidermis. Individuals with AK typically exhibit irregular, red, scaly bumps or patches as a result of prolonged exposure to UV rays. These growths primarily appear on sun-exposed areas of the skin such as the face, scalp, and hands. Presently, dermatologists are actively studying AK due to its rising incidence rate in the United States. However, the underlying causes of AK remain poorly understood. Previous research has indicated that the onset of AK involves various mechanisms including UV ray-induced inflammation, oxidative stress, complex mutagenesis, resulting immunosuppression, inhibited apoptosis, dysregulated cell cycle, altered cell proliferation, tissue remodeling, and human papillomavirus (HPV) infection. AK can develop in three ways: spontaneous regression, persistence, or progression into invasive cutaneous squamous cell carcinoma (cSCC). Multiple risk factors and diverse signaling pathways collectively contribute to its complex pathogenesis. To mitigate the risk of cancerous changes associated with long-term UV radiation exposure, prompt identification, management, and prevention of AK are crucial. The objective of this review is to elucidate the primary mechanisms underlying AK malignancy and identify potential treatment targets for dermatologists in clinical settings.

The protective role of oily fish intake against type 2 diabetes: insights from a genetic correlation and Mendelian randomization study

Background and aims

Previous research has underscored the association between oily fish intake and type 2 diabetes (T2DM), yet the causality remains elusive.

Methods

A bidirectional univariable Mendelian Randomization (MR) analysis was employed to evaluate the causal effects of oily fish and non-oily fish intake on T2DM. Replication analysis and meta-analysis were conducted to ensure robust results. Multivariable MR analysis was utilized to assess confounders, and further mediation MR analysis discerned mediating effects. Linkage Disequilibrium Score (LDSC) analysis was undertaken to compute genetic correlations. Inverse variance weighted (IVW) was the primary method, complemented by a series of sensitivity analyses.

Results

The LDSC analysis unveiled a significant genetic correlation between oily fish intake and T2DM (Genetic correlation: -0.102, p = 4.43 × 10-4). For each standard deviation (SD) increase in genetically predicted oily fish intake, the risk of T2DM was reduced by 38.6% (OR = 0.614, 95% CI 0.504 ~ 0.748, p = 1.24 × 10-6, False Discovery Rate (FDR) = 3.72 × 10-6). The meta-analysis across three data sources highlighted a persistent causal association (OR = 0.728, 95% CI 0.593 ~ 0.895, p = 0.003). No other causal effects were identified (all p > 0.5, FDR > 0.5). The main outcomes remained consistent in most sensitivity analyses. Both MVMR and mediation MR analyses emphasized the mediating roles of triglycerides (TG), body mass index (BMI), and 25-hydroxyvitamin D (25OHD) levels.

Conclusion

To encapsulate, there's an inverse association between oily fish intake and T2DM risk, suggesting potential benefits of oily fish intake in T2DM prevention.

Mendelian randomization study on insulin resistance and risk of hypertension and cardiovascular disease

Observational studies have suggested that insulin resistance (IR) is associated with hypertension and various cardiovascular diseases. However, the presence of a causal relationship between IR and cardiovascular disease remains unclear. Here, we applied Mendelian randomization (MR) approaches to address the causal association between genetically determined IR and the risk of cardiovascular diseases. Our primary genetic instruments comprised 53 SNPs associated with IR phenotype from a GWAS of up to 188,577 participants. Genetic association estimates for hypertension and venous thromboembolism (VTE) were extracted from UK Biobank, estimates for atrial fibrillation (AF) were extracted from the hitherto largest GWAS meta-analysis on AF, estimates for heart failure were extracted from HERMES Consortium, estimates for peripheral artery disease (PAD) and aortic aneurysm were extracted from the FinnGen Study. The main analyses were performed using the random-effects inverse-variance weighted approach, and complemented by sensitivity analyses and multivariable MR analyses. Corresponding to 55% higher fasting insulin adjusted for body mass index, 0.46 mmol/L lower high-density lipoprotein cholesterol and 0.89 mmol/L higher triglyceride, one standard deviation change in genetically predicted IR was associated with increased risk of hypertension (odds ratio (OR) 1.06, 95% CI 1.04-1.08; P = 1.91 × 10-11) and PAD (OR 1.90, 95% CI 1.43-2.54; P = 1.19 × 10-5). Suggestive evidence was obtained for an association between IR and heart failure (OR per SD change in IR: 1.19, 95% CI 1.01-1.41, P = 0.041). There was no MR evidence for an association between genetically predicted IR and atrial fibrillation, VTE, and aortic aneurysm. Results were widely consistent across all sensitivity analyses. In multivariable MR, the association between IR and PAD was attenuated after adjustment for lipids (P = 0.347) or BMI (P = 0.163). Our findings support that genetically determined IR increases the risk of hypertension and PAD.

Analyzing the causal relationship between lipid-lowering drug target genes and epilepsy: a Mendelian randomization study

Background

Previous research has yielded conflicting results on the link between epilepsy risk and lipid-lowering medications. The aim of this study is to determine whether the risk of epilepsy outcomes is causally related to lipid-lowering medications predicted by genetics.

Methods

We used genetic instruments as proxies to the exposure of lipid-lowering drugs, employing variants within or near genes targeted by these drugs and associated with low-density lipoprotein cholesterol (LDL cholesterol) from a genome-wide association study. These variants served as controlling factors. Through drug target Mendelian randomization, we systematically assessed the impact of lipid-lowering medications, including HMG-CoA reductase (HMGCR) inhibitors, proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, and Niemann-Pick C1-like 1 (NPC1L1) inhibitors, on epilepsy.

Results

The analysis demonstrated that a higher expression of HMGCR was associated with an elevated risk of various types of epilepsy, including all types (OR = 1.17, 95% CI:1.03 to 1.32, p = 0.01), focal epilepsy (OR = 1.24, 95% CI:1.08 to 1.43, p = 0.003), and focal epilepsy documented with lesions other than hippocampal sclerosis (OR = 1.05, 95% CI: 1.01 to 1.10, p = 0.02). The risk of juvenile absence epilepsy (JAE) was also associated with higher expression of PCSK9 (OR = 1.06, 95% CI: 1.02 to 1.09, p = 0.002). For other relationships, there was no reliable supporting data available.

Conclusion

The drug target MR investigation suggests a possible link between reduced epilepsy vulnerability and HMGCR and PCSK9 inhibition.

Associations between type 1 diabetes and pulmonary tuberculosis: a bidirectional mendelian randomization study

BACKGROUND

Type 1 diabetes mellitus (T1DM) has been associated with higher pulmonary tuberculosis (PTB) risk in observational studies. However, the causal relationship between them remains unclear. This study aimed to assess the causal effect between T1DM and PTB using bidirectional Mendelian randomization (MR) analysis.

METHODS

Single nucleotide polymorphisms (SNPs) of T1DM and PTB were extracted from the public genetic variation summary database. In addition, GWAS data were collected to explore the causal relationship between PTB and relevant clinical traits of T1DM, including glycemic traits, lipids, and obesity. The inverse variance weighting method (IVW), weighted median method, and MR‒Egger regression were used to evaluate the causal relationship. To ensure the stability of the results, sensitivity analyses assess the robustness of the results by estimating heterogeneity and pleiotropy.

RESULTS

IVW showed that T1DM increased the risk of PTB (OR = 1.07, 95% CI: 1.03-1.12, P < 0.001), which was similar to the results of MR‒Egger and weighted median analyses. Moreover, we found that high-density lipoprotein cholesterol (HDL-C; OR = 1.28, 95% CI: 1.03-1.59, P = 0.026) was associated with PTB. There was no evidence of an effect of glycemic traits, remaining lipid markers, or obesity on the risk of PTB. In the reverse MR analysis, no causal relationships were detected for PTB on T1DM and its relevant clinical traits.

CONCLUSION

This study supported that T1DM and HDL-C were risk factors for PTB. This implies the effective role of treating T1DM and managing HDL-C in reducing the risk of PTB, which provides an essential basis for the prevention and comanagement of concurrent T1DM and PTB in clinical practice.

Uncovering genetic associations in the human diseasome using an endophenotype-augmented disease network

MOTIVATION

Many diseases, particularly cardiometabolic disorders, exhibit complex multimorbidities with one another. An intuitive way to model the connections between phenotypes is with a disease-disease network (DDN), where nodes represent diseases and edges represent associations, such as shared single-nucleotide polymorphisms (SNPs), between pairs of diseases. To gain further genetic understanding of molecular contributors to disease associations, we propose a novel version of the shared-SNP DDN (ssDDN), denoted as ssDDN+, which includes connections between diseases derived from genetic correlations with intermediate endophenotypes. We hypothesize that a ssDDN+ can provide complementary information to the disease connections in a ssDDN, yielding insight into the role of clinical laboratory measurements in disease interactions.

RESULTS

Using PheWAS summary statistics from the UK Biobank, we constructed a ssDDN+ revealing hundreds of genetic correlations between diseases and quantitative traits. Our augmented network uncovers genetic associations across different disease categories, connects relevant cardiometabolic diseases, and highlights specific biomarkers that are associated with cross-phenotype associations. Out of the 31 clinical measurements under consideration, HDL-C connects the greatest number of diseases and is strongly associated with both type 2 diabetes and heart failure. Triglycerides, another blood lipid with known genetic causes in non-mendelian diseases, also adds a substantial number of edges to the ssDDN. This work demonstrates how association with clinical biomarkers can better explain the shared genetics between cardiometabolic disorders. Our study can facilitate future network-based investigations of cross-phenotype associations involving pleiotropy and genetic heterogeneity, potentially uncovering sources of missing heritability in multimorbidities.

AVAILABILITY AND IMPLEMENTATION

The generated ssDDN+ can be explored at https://hdpm.biomedinfolab.com/ddn/biomarkerDDN.

Maternal history of Alzheimer's disease predisposes to altered serum cholesterol levels in adult offspring

Controversial findings regarding the association between serum cholesterol levels and Alzheimer's disease (AD) have been identified through observational studies. The genetic basis shared by both factors and the causality between them remain largely unknown. The objective of this study is to examine the causal impact of maternal history of AD on changes in serum cholesterol levels in adult offspring. By retrieving genetic variants from summary statistics of large-scale genome-wide association study of maternal history of AD (European-based: Ncase = 27 696, Ncontrol = 260 980). The causal association between genetically predicted maternal history of AD and changes in serum cholesterol levels in adult offspring was examined using the two-sample Mendelian randomization (MR) method. Causal impact estimates were calculated using single-nucleotide polymorphisms in both univariable MR (UMR) and multivariable MR (MVMR) analyses. Additionally, other approaches, such as Cochran's Q test and leave-one-out variant analysis, were employed to correct for potential biases. The results of UMR presented that genetically predicted maternal history of AD was positively associated with hypercholesterolemia (OR = 1.014; 95% CI: 1.009-1.018; p < 0.001), total cholesterol (OR = 1.29; 95% CI: 1.134-1.466; p < 0.001) and low-density lipoprotein (OR = 1.525; 95% CI: 1.272-1.828; p < 0.001) among adult offspring. Genetic predisposition for maternal history of AD to be negatively associated with high-density lipoprotein (OR = 0.889; 95% CI: 0.861-0.917; p < 0.001). The MVMR analysis remained robust and significant after adjusting for diabetes and obesity in offspring. Sufficient evidence was provided in this study to support the putative causal impact of maternal history of AD on the change of serum cholesterol profile in adult offspring. In clinical practice, priority should be given to the detection and monitoring of cholesterol levels in individuals with a maternal history of AD, particularly in the early stages.

Polygenic Risk Associations with Clinical Characteristics and Recurrence of Dupuytren Disease

BACKGROUND

Dupuytren disease (DD) is a common complex trait, with varying severity and incompletely understood cause. Genome-wide association studies (GWAS) have identified risk loci. In this article, we examine whether genetic risk profiles of DD in patients are associated with clinical variation and disease severity and with patient genetic risk profiles of genetically correlated traits, including body mass index (BMI), triglycerides, high-density lipoproteins, type 2 diabetes mellitus, and endophenotypes fasting glucose and glycated hemoglobin.

METHODS

The authors used a well-characterized cohort of 1461 DD patients with available phenotypic and genetic data. Phenotype data include age at onset, recurrence, and family history of disease. Polygenic risk scores (PRSs) of DD, BMI, triglycerides, high-density lipoprotein, type 2 diabetes, fasting glucose, and hemoglobin A1c using various significance thresholds were calculated with PRSice using the most recent GWAS summary statistics. Control data from LifeLines were used to determine P value cutoffs for PRS generation explaining most variance.

RESULTS

The PRS for DD was significantly associated with a positive family history for DD, age at onset, disease onset before the age of 50, and recurrence. We also found a significant negative correlation between the PRSs for DD and BMI.

CONCLUSIONS

Although GWAS studies of DD are designed to identify genetic risk factors distinguishing case/control status, we show that the genetic risk profile for DD also explains part of its clinical variation and disease severity. The PRS may therefore aid in accurate prognostication, choosing initial treatment and in personalized medicine in the future.

CLINICAL QUESTION/LEVEL OF EVIDENCE

Risk, III.

Leveraging electronic health records and knowledge networks for Alzheimer's disease prediction and sex-specific biological insights

Identification of Alzheimer's disease (AD) onset risk can facilitate interventions before irreversible disease progression. We demonstrate that electronic health records from the University of California, San Francisco, followed by knowledge networks (for example, SPOKE) allow for (1) prediction of AD onset and (2) prioritization of biological hypotheses, and (3) contextualization of sex dimorphism. We trained random forest models and predicted AD onset on a cohort of 749 individuals with AD and 250,545 controls with a mean area under the receiver operating characteristic of 0.72 (7 years prior) to 0.81 (1 day prior). We further harnessed matched cohort models to identify conditions with predictive power before AD onset. Knowledge networks highlight shared genes between multiple top predictors and AD (for example, APOE, ACTB, IL6 and INS). Genetic colocalization analysis supports AD association with hyperlipidemia at the APOE locus, as well as a stronger female AD association with osteoporosis at a locus near MS4A6A. We therefore show how clinical data can be utilized for early AD prediction and identification of personalized biological hypotheses.

Mining cholesterol genes from thousands of mouse livers identifies aldolase C as a regulator of cholesterol biosynthesis

The availability of genome-wide transcriptomic and proteomic datasets is ever-increasing and often not used beyond initial publication. Here, we applied module-based coexpression network analysis to a comprehensive catalog of 35 mouse genome-wide liver expression datasets (encompassing more than 3800 mice) with the goal of identifying and validating unknown genes involved in cholesterol metabolism. From these 35 datasets, we identified a conserved module of genes enriched with cholesterol biosynthetic genes. Using a systematic approach across the 35 datasets, we identified three genes (Rdh11, Echdc1, and Aldoc) with no known role in cholesterol metabolism. We then performed functional validation studies and show that each gene is capable of regulating cholesterol metabolism. For the glycolytic gene, Aldoc, we demonstrate that it contributes to de novo cholesterol biosynthesis and regulates cholesterol and triglyceride levels in mice. As Aldoc is located within a genome-wide significant genome-wide association studies locus for human plasma cholesterol levels, our studies establish Aldoc as a causal gene within this locus. Through our work, we develop a framework for leveraging mouse genome-wide liver datasets for identifying and validating genes involved in cholesterol metabolism.

Effect of Household Income on Cardiovascular Diseases, Cardiovascular Biomarkers, and Socioeconomic Factors

PURPOSE

To examine whether household income is causally related to cardiovascular diseases and investigate the potential reasons.

METHODS

Using 2-sample Mendelian randomization analyses, we obtained summary statistics from genome-wide association studies of household income and a range of cardiovascular diseases, biomarkers, and socioeconomic factors.

FINDINGS

Higher household income was causally associated with lower risks of coronary heart disease (odd ratio [OR] = 0.63; 95% CI: 0.49-0.79; P = 0.0001), myocardial infarction (OR = 0.64; 95% CI: 0.50-0.82; P = 0.0003), and hypertension (OR = 0.71; 95% CI: 0.58-0.88; P = 0.0015). With increasing household income, the cardiovascular biomarkers including triglycerides, C-reactive protein, body mass index, fasting glucose were decreased whereas telomere length and high-density lipoprotein cholesterol were increased. Besides, individuals with higher household income were less likely to smoke (β = -0.34; 95% CI: -0.47 to -0.21; P = 1.91×10-07), intake salt (β = -0.14; 95% CI: -0.21 to -0.07; P = 0.0001), or be exposed to air pollution (β = -0.10; 95% CI: -0.15 to -0.06; P = 8.81×10-06) or depression state (β = -0.03; 95% CI: -0.04 to -0.02; P = 5.16×10-07). They were more likely to take physical activity (β = 0.06; 95% CI: 0.02 to 010; P = 0.0016) and have long years of schooling (β = 0.70; 95% CI: 0.62 to 0.78; P = 5.32×10-67).

IMPLICATIONS

Higher household income is causally associated with better socioeconomic factors and improved cardiovascular biomarkers, which translates into a reduced prevalence of cardiovascular diseases. Policies to improve income equality may result in a reduced burden of cardiovascular diseases.

Genetically proxied therapeutic inhibition of lipid-lowering drug targets and risk of rheumatoid arthritis disease: a Mendelian randomization study

OBJECTIVE

To evaluate the potential impact of consistent use of similar treatments over a long period; it is essential to investigate the potential correlation between genetic variations that influence the expression or function of pharmacological targets for reducing lipid levels and the risk of developing rheumatoid arthritis.

METHODS

We used variants in the following genes to conduct Mendelian randomization analyses: HMGCR (encoding the target for statins), PCSK9 (encoding the target for PCSK9 inhibitors, such as evolocumab and alirocumab), and NPC1L1 (encoding the target for ezetimibe). Data from lipid genetics consortia (173,082 sample size) were used to weight variations according to their correlations with low-density lipoprotein cholesterol (LDL-C). In two large datasets (total n = 19,562 cases, 501,655 controls). We conducted a meta-analysis of Mendelian randomization estimates, weighted by LDL-C levels, on the regional differences in the risk of rheumatoid arthritis using data from two large databases.

RESULTS

We approached SMR and IVW-MR analyses to examine the relationship between target gene expression (including HMGCR, PCSK9, and NPC1L1) and LDL-C levels mediated by these genes with RA. The IVW-MR analysis revealed no significant association between genetically predicted LDL-C concentration and the risk of RA (OR = 0.88, 95% CI = 0.59-1.29; OR = 0.91, 95% CI = 0.67-1.23; OR = 0.81, 95% CI = 0.49-1.36; all p > 0.05). Similarly, our findings from the SMR approach provided no evidence to suggest that gene expression of HMGCR, PCSK9, and NPC1L1 was associated with the risk of RA (OR = 0.91, 95% CI = 0.79-1.05, p = 0.207; OR = 0.96, 95% CI = 0.85-1.09, p = 0.493).

CONCLUSIONS

Our results do not provide evidence to support the hypothesis that reducing LDL-C levels with statins, alirocumab, or ezetimibe effectively prevents the risk of developing RA. However, our study provides valuable insights into the assessment of lipid-lowering agents in RA, which can enhance our understanding of the condition and assist in clinical practice by aiding in the determination and monitoring of RA status to clinical response.

Investigating the causal relationship between human blood/urine metabolites and periodontal disease using two-sample Mendelian randomization

Background and Aims

The aim is to investigate the cause-and-effect connection between metabolites found in blood/urine and the likelihood of developing periodontal disease (PD) through the utilization of a two-sample Mendelian randomization (MR) method.

Methods

Using an inverse variance weighted (IVW) method and two additional two-sample MR models, we examined the relationship between blood/urine metabolites and PD by analyzing data from a comprehensive metabolome-based genome-wide association study and the Genome-Wide Association Studies (GWAS) of PD. To assess the consistency and dependability of the findings, diversity, cross-effects, and sensitivity analyses were conducted.

Results

Out of the 35 metabolites found in blood and urine, a total of eight metabolites (C-reactive protein, Potassium in urine, Urea, Cystatin C, Non-albumin protein, Creatinine, estimated Glomerular Filtration Rate, and Phosphate) displayed a possible causal connection with the risk of dental caries/PD using the inverse variance weighted (IVW) method (p < 0.05). This includes five metabolites in the blood and three in the urine. No metabolites were statistically significant in IVW MR models (p < 3.68 × 10- 4). Even after conducting sensitivity analysis with the leave-one-out method and removing the confounding instrumental variables, the impact of these factors on dental caries/PD remained significant.

Conclusion

Based on the available evidence, it is not possible to establish a significant causal link between the 35 blood metabolites and the likelihood of developing dental caries and PD.

Potential association of genetically predicted lipid and lipid-modifying drugs with rheumatoid arthritis: A Mendelian randomization study

BACKGROUND

Past studies have demonstrated that patients diagnosed with rheumatoid arthritis (RA) often exhibit abnormal levels of lipids. Furthermore, certain lipid-modifying medications have shown effectiveness in alleviating clinical symptoms associated with RA. However, the current understanding of the causal relationship between lipids, lipid-modifying medications, and the risk of developing RA remains inconclusive. This study employed Mendelian randomization (MR) to investigate the causal connection between lipids, lipid-modifying drugs, and the occurrence of RA.

METHODS

We obtained genetic variation for lipid traits and drug targets related to lipid modification from three sources: the Global Lipids Genetics Consortium (GLGC), UK Biobank, and Nightingale Health 2020. The genetic data for RA were acquired from two comprehensive meta-analyses and the R8 of FINNGEN, respectively. These variants were employed in drug-target MR analyses to establish a causal relationship between genetically predicted lipid-modifying drug targets and the risk of RA. For suggestive lipid-modified drug targets, we conducted Summary-data-based Mendelian Randomization (SMR) analyses and using expression quantitative trait loci (eQTL) data in relevant tissues. In addition, we performed co-localization analyses to assess genetic confounders.

RESULTS

Our analysis revealed no significant causal relationship between lipid and RA. We observed that the genetically predicted 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) -mediated low density lipoprotein cholesterol (LDL-C) (OR 0.704; 95% CI 0.56, 0.89; P = 3.43×10-3), Apolipoprotein C-III (APOC3) -mediated triglyceride (TG) (OR 0.844; 95% CI 0.77, 0.92; P = 1.50×10-4) and low density lipoprotein receptor (LDLR) -mediated LDL-C (OR 0.835; 95% CI 0.73, 0.95; P = 8.81×10-3) were significantly associated with a lowered risk of RA. while Apolipoprotein B-100 (APOB) -mediated LDL-C (OR 1.212; 95%CI 1.05,1.40; P = 9.66×10-3) was significantly associated with an increased risk of RA.

CONCLUSIONS

Our study did not find any supporting evidence to suggest that lipids are a risk factor for RA. However, we observed significant associations between HMGCR, APOC3, LDLR, and APOB with the risk of RA.

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 = and f) and in participants who did not take lipid-lowering medication (n = 1,869). Using interaction models, we also examined whether the relationships between epigenetic age acceleration and blood lipids differ by demographic factors including age, sex, and educational attainment.

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). GrimAge acceleration and DunedinPACE associations with all lipids remained significant after further adjusting 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

Epigenetic age acceleration, a powerful biomarker of cellular aging, is highly 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 the non-linear relationship between age and these lipids, as both TC and LDL-C decrease faster at older ages. More studies are needed to further understand the temporal relationships between epigenetic age acceleration on blood lipids and other health outcomes.

Maternal Age at Menarche Genes Determines Fetal Growth Restriction Risk

We aimed to explore the potential link of maternal age at menarche (mAAM) gene polymorphisms with risk of the fetal growth restriction (FGR). This case (FGR)-control (FGR free) study included 904 women (273 FGR and 631 control) in the third trimester of gestation examined/treated in the Departments of Obstetrics. For single nucleotide polymorphism (SNP) multiplex genotyping, 50 candidate loci of mAAM were chosen. The relationship of mAAM SNPs and FGR was appreciated by regression procedures (logistic/model-based multifactor dimensionality reduction [MB-MDR]) with subsequent in silico assessment of the assumed functionality pithy of FGR-related loci. Three mAAM-appertain loci were FGR-linked to genes such as KISS1 (rs7538038) (effect allele G-odds ratio (OR)allelic = 0.63/pperm = 0.0003; ORadditive = 0.61/pperm = 0.001; ORdominant = 0.56/pperm = 0.001), NKX2-1 (rs999460) (effect allele A-ORallelic = 1.37/pperm = 0.003; ORadditive = 1.45/pperm = 0.002; ORrecessive = 2.41/pperm = 0.0002), GPRC5B (rs12444979) (effect allele T-ORallelic = 1.67/pperm = 0.0003; ORdominant = 1.59/pperm = 0.011; ORadditive = 1.56/pperm = 0.009). The haplotype ACA FSHB gene (rs555621*rs11031010*rs1782507) was FRG-correlated (OR = 0.71/pperm = 0.05). Ten FGR-implicated interworking models were founded for 13 SNPs (pperm ≤ 0.001). The rs999460 NKX2-1 and rs12444979 GPRC5B interplays significantly influenced the FGR risk (these SNPs were present in 50% of models). FGR-related mAAM-appertain 15 polymorphic variants and 350 linked SNPs were functionally momentous in relation to 39 genes participating in the regulation of hormone levels, the ovulation cycle process, male gonad development and vitamin D metabolism. Thus, this study showed, for the first time, that the mAAM-appertain genes determine FGR risk.

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

Background

Low levels of high-density lipoprotein cholesterol (HDL-C) are commonly seen in patients with type 2 diabetes mellitus (T2DM). However, it is unclear whether there is an independent or causal link between HDL-C levels and T2DM. This study aims to address this gap by using the The National Health and Nutrition Examination Survey (NHANES) database and Mendelian randomization (MR) analysis.

Materials and methods

Data from the NHANES survey (2007-2018) with 9,420 participants were analyzed using specialized software. Logistic regression models and restricted cubic splines (RCS) were used to assess the relationship between HDL-C and T2DM incidence, while considering covariates. Genetic variants associated with HDL-C and T2DM were obtained from genome-wide association studies (GWAS), and Mendelian randomization (MR) was used to evaluate the causal relationship between HDL-C and T2DM. Various tests were conducted to assess pleiotropy and outliers.

Results

In the NHANES study, all groups, except the lowest quartile (Q1: 0.28-1.09 mmol/L], showed a significant association between HDL-C levels and reduced T2DM risk (all P < 0.001). After adjusting for covariates, the Q2 [odds ratio (OR) = 0.67, 95% confidence interval (CI): (0.57, 0.79)], Q3 [OR = 0.51, 95% CI: (0.40, 0.65)], and Q4 [OR = 0.29, 95% CI: (0.23, 0.36)] groups exhibited average reductions in T2DM risk of 23%, 49%, and 71%, respectively. In the sensitivity analysis incorporating other lipid levels, the Q4 group still demonstrates a 57% reduction in the risk of T2DM. The impact of HDL-C levels on T2DM varied with age (P for interaction = 0.006). RCS analysis showed a nonlinear decreasing trend in T2DM risk with increasing HDL-C levels (P = 0.003). In the MR analysis, HDL-C levels were also associated with reduced T2DM risk (OR = 0.69, 95% CI = 0.52-0.82; P = 1.41 × 10-13), and there was no evidence of pleiotropy or outliers.

Conclusion

This study provides evidence supporting a causal relationship between higher HDL-C levels and reduced T2DM risk. Further research is needed to explore interventions targeting HDL-C levels for reducing T2DM risk.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Genetic influences on circulating retinol and its relationship to human health

Retinol is a fat-soluble vitamin that plays an essential role in many biological processes throughout the human lifespan. Here, we perform the largest genome-wide association study (GWAS) of retinol to date in up to 22,274 participants. We identify eight common variant loci associated with retinol, as well as a rare-variant signal. An integrative gene prioritisation pipeline supports novel retinol-associated genes outside of the main retinol transport complex (RBP4:TTR) related to lipid biology, energy homoeostasis, and endocrine signalling. Genetic proxies of circulating retinol were then used to estimate causal relationships with almost 20,000 clinical phenotypes via a phenome-wide Mendelian randomisation study (MR-pheWAS). The MR-pheWAS suggests that retinol may exert causal effects on inflammation, adiposity, ocular measures, the microbiome, and MRI-derived brain phenotypes, amongst several others. Conversely, circulating retinol may be causally influenced by factors including lipids and serum creatinine. Finally, we demonstrate how a retinol polygenic score could identify individuals more likely to fall outside of the normative range of circulating retinol for a given age. In summary, this study provides a comprehensive evaluation of the genetics of circulating retinol, as well as revealing traits which should be prioritised for further investigation with respect to retinol related therapies or nutritional intervention.

Genetic insights into repurposing statins for hyperthyroidism prevention: a drug-target Mendelian randomization study

Background

Current therapeutic measures for thyroid dysfunction are limited and often accompanied by adverse effects. The use of lipid-lowering drugs like statins has recently been associated with lower thyroid eye diseases risk.

Objective

To investigate the implications of genetically proxied lipid-lowering drugs on thyroid dysfunction.

Methods

In this drug-target Mendelian randomization (MR) study, we utilized genetic variants within drug target genes associated with low-density lipoprotein (LDL) or triglyceride (TG), derived from a genome-wide association study (GWAS) meta-analysis (N ≤ 188,577), to simulate lifelong drug interventions. Genetic summary statistics for thyroid dysfunction outcomes were retrieved from GWAS datasets of Thyroid Omics Consortium (N ≤ 54,288) and UK Biobank (N = 484,598). Inverse-variance-weighted MR (IVW-MR) method was performed as primary analysis, followed by validation in colocalization analysis. A subsequent two-step MR analysis was conducted to identify biomarkers mediating the identified drug-outcome association.

Results

In IVW-MR analysis, genetic mimicry of 3-hydroxy-3-methylglutarylcoenzyme reductase (HMGCR) inhibitors (e.g. statins) was significantly associated with lower risk of hyperthyroidism in two independent datasets (OR1, 0.417 per 1-mmol/L lower in LDL-C; 95% CI 0.262 to 0.664; P1 = 2.262 × 10-4; OR2 0.996; 95% CI 0.993-0.998; P2 = 0.002). Two-step MR analysis revealed eighteen biomarkers linked to genetic mimicry of HMGCR inhibition, and identified insulin-like growth factor 1 (IGF-1) levels mediating 2.108% of the negative causal relationship between HMGCR inhibition and hyperthyroidism.

Conclusion

This study supports HMGCR inhibition as a promising therapeutic strategy for hyperthyroidism and suggests its underlying mechanisms may extend beyond lipid metabolism. Further investigations through laboratory studies and clinical trials are necessary to confirm and elucidate these findings.

Causal Associations of Education Level With Cardiovascular Diseases, Cardiovascular Biomarkers, and Socioeconomic Factors

An inverse association of education level with cardiovascular diseases has been documented in observational studies, yet the causality and potential mechanisms remain to be determined. To systematically investigate the causal associations of education level with cardiovascular diseases, cardiovascular biomarkers, and socioeconomic factors, a 2-sample Mendelian randomization was performed. The results revealed that higher genetically determined education level was associated with lower risks of type 2 diabetes mellitus (odds ratio [OR] 0.54, 95% confidence interval [CI] 0.47 to 0.61, p = 3.04 × 10-23), peripheral artery disease (OR 0.62, 95% CI 0.51 to 0.76, p = 2.14 × 10-06), hypertension (OR 0.62, 95% CI 0.56 to 0.70, p = 4.22 × 10-16), coronary heart disease (OR 0.62, 95% CI 0.56 to 0.69, p = 3.50 × 10-19), myocardial infarction (OR 0.62, 95% CI 0.55 to 0.69, p = 2.58 × 10-16), ischemic stroke (OR 0.67, 95% CI 0.62 to 0.74, p = 6.00 × 10-19), deep vein thrombosis (OR 0.69, 95% CI 0.55 to 0.87, p = 0.0017), atrial fibrillation (OR 0.70, 95% CI 0.57 to 0.86, p = 0.0007), cardiac death (OR 0.71, 95% CI 0.60 to 0.86, p = 0.0003), heart failure (OR 0.72, 95% CI 0.65 to 0.79, p = 6.37 × 10-12), transient ischemic attack (OR 0.76, 95% CI 0.64 to 0.90, p = 0.0010), and venous thromboembolism (OR 0.79, 95% CI 0.67 to 0.92, p = 0.0028). Systolic blood pressure, diastolic blood pressure, C-reactive protein, body mass index, waist circumference, and triglycerides were decreased, whereas telomere length was increased. Subjects with higher education were less likely to smoke, intake salt, or be exposed to air pollution and depression state. They were more likely to take physical activity and possess more household income. In conclusion, higher education may causally decrease cardiovascular diseases through socioeconomic factors and cardiovascular biomarkers. Reducing education inequality is important in the management of cardiovascular diseases.

Novel genetic markers for chronic kidney disease in a geographically isolated population of Indigenous Australians: Individual and multiple phenotype genome-wide association study

BACKGROUND

Chronic kidney disease (CKD) is highly prevalent among Indigenous Australians, especially those in remote regions. The Tiwi population has been isolated from mainland Australia for millennia and exhibits unique genetic characteristics that distinguish them from other Indigenous and non-Indigenous populations. Notably, the rate of end-stage renal disease is up to 20 times greater in this population compared to non-Indigenous populations. Despite the identification of numerous genetic loci associated with kidney disease through GWAS, the Indigenous population such as Tiwi remains severely underrepresented and the increased prevalence of CKD in this population may be due to unique disease-causing alleles/genes.

METHODS

We used albumin-to-creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) to estimate the prevalence of kidney disease in the Tiwi population (N = 492) in comparison to the UK Biobank (UKBB) (N = 134,724) database. We then performed an exploratory factor analysis to identify correlations among 10 CKD-related phenotypes and identify new multi-phenotype factors. We subsequently conducted a genome-wide association study (GWAS) on all single and multiple phenotype factors using mixed linear regression models, adjusted for age, sex, population stratification, and genetic relatedness between individuals.

RESULTS

Based on ACR, 20.3% of the population was at severely increased risk of CKD progression and showed elevated levels of ACR compared to the UKBB population independent of HbA1c. A GWAS of ACR revealed novel association loci in the genes MEG3 (chr14:100812018:T:A), RAB36 (rs11704318), and TIAM2 (rs9689640). Additionally, multiple phenotypes GWAS of ACR, eGFR, urine albumin, and serum creatinine identified a novel variant that mapped to the gene MEIS2 (chr15:37218869:A:G). Most of the identified variants were found to be either absent or rare in the UKBB population.

CONCLUSIONS

Our study highlights the Tiwi population's predisposition towards elevated ACR, and the collection of novel genetic variants associated with kidney function. These associations may prove valuable in the early diagnosis and treatment of renal disease in this underrepresented population. Additionally, further research is needed to comprehensively validate the functions of the identified variants/genes.

Incorporating functional annotation with bilevel continuous shrinkage for polygenic risk prediction

BACKGROUND

Genetic variants can contribute differently to trait heritability by their functional categories, and recent studies have shown that incorporating functional annotation can improve the predictive performance of polygenic risk scores (PRSs). In addition, when only a small proportion of variants are causal variants, PRS methods that employ a Bayesian framework with shrinkage can account for such sparsity. It is possible that the annotation group level effect is also sparse. However, the number of PRS methods that incorporate both annotation information and shrinkage on effect sizes is limited. We propose a PRS method, PRSbils, which utilizes the functional annotation information with a bilevel continuous shrinkage prior to accommodate the varying genetic architectures both on the variant-specific level and on the functional annotation level.

RESULTS

We conducted simulation studies and investigated the predictive performance in settings with different genetic architectures. Results indicated that when there was a relatively large variability of group-wise heritability contribution, the gain in prediction performance from the proposed method was on average 8.0% higher AUC compared to the benchmark method PRS-CS. The proposed method also yielded higher predictive performance compared to PRS-CS in settings with different overlapping patterns of annotation groups and obtained on average 6.4% higher AUC. We applied PRSbils to binary and quantitative traits in three real world data sources (the UK Biobank, the Michigan Genomics Initiative (MGI), and the Korean Genome and Epidemiology Study (KoGES)), and two sources of annotations: ANNOVAR, and pathway information from the Kyoto Encyclopedia of Genes and Genomes (KEGG), and demonstrated that the proposed method holds the potential for improving predictive performance by incorporating functional annotations.

CONCLUSIONS

By utilizing a bilevel shrinkage framework, PRSbils enables the incorporation of both overlapping and non-overlapping annotations into PRS construction to improve the performance of genetic risk prediction. The software is available at https://github.com/styvon/PRSbils .

Aminopeptidase O Protein mediates the association between Lachnospiraceae and appendicular lean mass

Objective

Investigating the causal relationship between Lachnospiraceae and Appendicular lean mass (ALM) and identifying and quantifying the role of Aminopeptidase O Protein (AOPEP) as a potential mediator.

Methods

The summary statistics data of gut microbiota composition from the largest available genome-wide association study (GWAS) meta-analysis conducted by the MiBioGen Consortium (n = 13,266). Appendicular lean mass data were obtained from the UK-Biobank (n = 450,243). We conducted bidirectional two-sample Mendelian randomization (MR) analysis using summary-level data from GWAS to investigate the causal relationship between Lachnospiraceae and ALM. Additionally, we employed a drug-targeted MR approach to assess the causal relationship between AOPEP and ALM. Finally, a two-step MR was employed to quantitatively estimate the proportion of the effect of Lachnospiraceae on ALM that is mediated by AOPEP. Cochran's Q statistic was used to quantify heterogeneity among instrumental variable estimates.

Results

In the MR analysis, it was found that an increase in genetically predicted Lachnospiraceae [OR = 1.031, 95% CI (1.011-1.051), P = 0.002] is associated with an increase in ALM. There is no strong evidence to suggest that genetically predicted ALM has an impact on Lachnospiraceae genus [OR = 1.437, 95% CI (0.785-2.269), P = 0.239]. The proportion of genetically predicted Lachnospiraceae mediated by AOPEP was 34.2% [95% CI (1.3%-67.1%)].

Conclusion

Our research reveals that increasing Lachnospiraceae abundance in the gut can directly enhance limb muscle mass and concurrently suppress AOPEP, consequently mitigating limb muscle loss. This supports the potential therapeutic modulation of gut microbiota for sarcopenia. Interventions such as drug treatments or microbiota transplantation, aimed at elevating Lachnospiraceae abundance and AOPEP inhibition, synergistically improve sarcopenia in the elderly, thereby enhancing the overall quality of life for older individuals.