Discovery and refinement of loci associated with lipid levels

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

BACKGROUND AND OBJECTIVES

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

METHODS

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

RESULTS

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

DISCUSSION

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

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

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

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

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

Mapping biological influences on the human plasma proteome beyond the genome

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

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

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

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

Novel insights into the association between genetically proxied inhibition of proprotein convertase subtilisin/kexin type 9 and risk of sarcopenia

BACKGROUND

The effects of lipid-lowering drugs [including statins, ezetimibe, and proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors] on hyperlipidaemia have been established. Some may have treatment effects beyond their reported properties, offering potential opportunities for drug repurposing. Epidemiological studies have reported conflicting findings on the relationship between lipid-lowering medication use and sarcopenia risk.

METHODS

We performed a two-sample Mendelian randomization (MR) study to investigate the causal association between the use of genetically proxied lipid-lowering drugs (including statins, ezetimibe, and PCSK9 inhibitors, which use low-density lipoprotein as a biomarker), and sarcopenia risk. The inverse-variance weighting method was used with pleiotropy-robust methods (MR-Egger regression and weighted median) and colocalization as sensitivity analyses.

RESULTS

According to the positive control analysis, genetically proxied inhibition in lipid-lowering drug targets was associated with a lower risk of coronary heart disease [PCSK9 (OR, 0.67; 95% CI, 0.61 to 0.72; P = 7.7E-21); 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR; OR, 0.68; 95% CI, 0.57 to 0.82; P = 4.6E-05), and Niemann-Pick C1-like 1 (NPC1L1; OR, 0.53; 95% CI, 0.40 to 0.69; P = 3.3E-06)], consistent with drug mechanistic actions and previous trial evidence. Genetically proxied inhibition of PCSK9 (beta, -0.040; 95% CI, -0.068 to -0.012; P = 0.005) and circulating PCSK9 levels (beta, -0.019; 95% CI, -0.033 to -0.005; P = 0.006) were associated with reduced appendicular lean mass (ALM) with concordant estimates in terms of direction and magnitude. Validation analyses using a second instrument for PCSK9 yielded consistent results in terms of direction and magnitude [(PCSK9 to ALM; beta, -0.052; 95% CI, -0.074 to -0.032; P = 7.1E-7); (PCSK9 protein to ALM; beta, -0.060; 95% CI, -0.106 to -0.014; P = 0.010)]. Genetically proxied inhibition of PCSK9 gene expression in the liver may be associated with reduced ALM (beta, -0.013; 95% CI, -0.035 to 0.009; P = 0.25), consistent with the results of PCSK9 drug-target and PCSK9 protein MR analyses, but the magnitude was less precise. No robust association was found between HMGCR inhibition (beta, 0.048; 95% CI, -0.015 to 0.110; P = 0.14) or NPC1L1 (beta, 0.035; 95% CI, -0.074 to 0.144; P = 0.53) inhibition and ALM, and validation and sensitivity MR analyses showed consistent estimates.

CONCLUSIONS

This MR study suggested that PCSK9 is involved in sarcopenia pathogenesis and that its inhibition is associated with reduced ALM. These findings potentially pave the way for future studies that may allow personalized selection of lipid-lowering drugs for those at risk of sarcopenia.

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

BACKGROUND

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

METHOD

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

RESULTS

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

CONCLUSION

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

Heritability and genetic correlations of obesity indices and cardiometabolic traits in the Northern Chinese families

OBJECTIVE

This study aimed to investigate the heritability of various obesity indices and their shared genetic factors with cardiometabolic traits in the Chinese nuclear family.

METHODS

A total of 1270 individuals from 538 nuclear families were included in this cross-sectional study. Different indices were used to quantify fat mass and distribution, including body index mass (BMI), visceral fat index (VFI), and body fat percent (BFP). Heritability and genetic correlations for all quantitative traits were estimated using variance component models. The susceptibility-threshold model was utilized to estimate the heritability for binary traits.

RESULTS

Heritability estimates for obesity indices were highest for BMI (59%), followed by BFP (49%), and VFI (40%). Heritability estimates for continuous cardiometabolic traits varied from 24% to 50%. All obesity measures exhibited consistently significant positive genetic correlations with blood pressure, fasting blood glucose, and uric acid (rG range: 0.26-0.57). However, diverse genetic correlations between various obesity indices and lipid profiles were observed. Significant genetic correlations were limited to specific pairs: BFP and total cholesterol (rG = 0.24), BFP and low-density lipoprotein cholesterol (rG = 0.25), and VFI and triglyceride (rG = 0.33).

CONCLUSION

The genetic overlap between various obesity indices and cardiometabolic traits underscores the importance of pleiotropic genes. Further studies are warranted to investigate specific shared genetic and environmental factors between obesity and cardiometabolic diseases.

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

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

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

Background

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

Working hypothesis and methods

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

Results

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

Conclusions

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

Supplementary Information

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

Profiling of differentially expressed MicroRNAs in familial hypercholesterolemia via direct hybridization

Background

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

Methods

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

Results

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

Conclusions

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

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

BACKGROUND & AIMS

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

Backgrounds and aims

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

Methods and findings

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

Conclusion

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

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

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

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

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

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

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

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

Background

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

Methods

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

Results

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

Conclusions

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

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

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

The plasma lipids with different fatty acid chains are associated with the risk of hemorrhagic stroke: a Mendelian randomization study

Background and objective

Hemorrhagic stroke, characterized by acute bleeding due to cerebrovascular lesions, is associated with plasma lipids and endothelial damage. The causal relationship between genetic plasma lipid levels and hemorrhagic stroke remains unclear. This study employs a two-sample Mendelian randomization (MR) analysis to explore the causal relationship between plasma lipid profiles with different fatty acid chains and the risk of intracerebral and subarachnoid hemorrhage, the two main subtypes of hemorrhagic stroke.

Methods

The datasets for exposure and outcome summary statistics were obtained from publicly available sources such as the GWAS Catalog, IEU OpenGWAS project, and FinnGen. The two-sample MR analysis was employed to initially assess the causal relationship between 179 plasma lipid species and the risk of intracerebral and subarachnoid hemorrhage in the Finnish population, leading to the identification of candidate lipids. The same methods were applied to reanalyze data from European populations and conduct a meta-analysis of the candidate lipids. The Inverse Variance Weighting (IVW) method served as the primary analysis for causal inference, with additional methods used for complementary analyses. Sensitivity analysis was conducted to clarify causal relationships and reduce biases.

Results

Two analyses using Mendelian randomization were performed, followed by meta-analyses of the results. A causal relationship was established between 11 specific lipid species and the occurrence of intracerebral hemorrhage within the European population. Additionally, 5 distinct lipid species were associated with subarachnoid hemorrhage. Predominantly, lipids with linoleic acid and arachidonic acid side chains were identified. Notably, lipids containing arachidonic acid chains (C20:4) such as PC 18:1;0_20:4;0 consistently showed a decreased risk of both intracerebral hemorrhage [p < 0.001; OR(95% CI) = 0.892(0.835-0.954)] and subarachnoid hemorrhage [p = 0.002; OR(95% CI) = 0.794(0.689-0.916)]. Conversely, lipids with linoleic acid chains (C18:2) were associated with an increased risk of intracerebral hemorrhage.

Conclusion

This study identifies a potential causal relationship between lipids with different fatty acid side chains and the risk of intracerebral and subarachnoid hemorrhagic stroke, improving the understanding of the mechanisms behind the onset and progression of hemorrhagic stroke.

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

BACKGROUND

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

AIMS

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

The impact of statin use on sepsis mortality

BACKGROUND

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

METHODS

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

MAIN RESULTS

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

CONCLUSIONS

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

Novel loci linked to serum lipid traits are identified in a genome-wide association study of a highly admixed Brazilian population - the 2015 ISA Nutrition

BACKGROUND

Cardiovascular diseases (CVDs) comprise major causes of death worldwide, leading to extensive burden on populations and societies. Alterations in normal lipid profiles, i.e., dyslipidemia, comprise important risk factors for CVDs. However, there is lack of comprehensive evidence on the genetic contribution to dyslipidemia in highly admixed populations. The identification of single nucleotide polymorphisms (SNPs) linked to blood lipid traits in the Brazilian population was based on genome-wide associations using data from the São Paulo Health Survey with Focus on Nutrition (ISA-Nutrition).

METHODS

A total of 667 unrelated individuals had genetic information on 330,656 SNPs available, and were genotyped with Axiom™ 2.0 Precision Medicine Research Array. Genetic associations were tested at the 10- 5 significance level for the following phenotypes: low-density lipoprotein cholesterol (LDL-c), very low-density lipoprotein cholesterol (VLDL-c), high-density lipoprotein cholesterol (HDL-c), HDL-c/LDL-c ratio, triglycerides (TGL), total cholesterol, and non-HDL-c.

RESULTS

There were 19 significantly different SNPs associated with lipid traits, the majority of which corresponding to intron variants, especially in the genes FAM81A, ZFHX3, PTPRD, and POMC. Three variants (rs1562012, rs16972039, and rs73401081) and two variants (rs8025871 and rs2161683) were associated with two and three phenotypes, respectively. Among the subtypes, non-HDL-c had the highest proportion of associated variants.

CONCLUSIONS

The results of the present genome-wide association study offer new insights into the genetic structure underlying lipid traits in underrepresented populations with high ancestry admixture. The associations were robust across multiple lipid phenotypes, and some of the phenotypes were associated with two or three variants. In addition, some variants were present in genes that encode ncRNAs, raising important questions regarding their role in lipid metabolism.

The role of coffee and potential mediators in subclinical atherosclerosis: insights from Mendelian randomization study

Background and aims

Coffee contains many bioactive compounds, and its inconsistent association with subclinical atherosclerosis has been reported in observational studies. In this Mendelian randomization study, we investigated whether genetically predicted coffee consumption is associated with subclinical atherosclerosis, as well as the role of potential mediators.

Methods

We first conducted a two-sample Mendelian randomization analysis to examine the causal effect of coffee and its subtypes on subclinical atherosclerosis inferred from coronary artery calcification (CAC). Next, the significant results were validated using another independent dataset. Two-step Mendelian randomization analyses were utilized to evaluate the causal pathway from coffee to subclinical atherosclerosis through potential mediators, including blood pressure, blood lipids, body mass index, and glycated hemoglobin. Mendelian randomization analyses were performed using the multiplicative random effects inverse-variance weighted method as the main approach, followed by a series of complementary methods and sensitivity analyses.

Results

Coffee, filtered coffee, and instant coffee were associated with the risk of CAC (β = 0.79, 95% CI: 0.12 to 1.47, p = 0.022; β = 0.66, 95% CI: 0.17 to 1.15, p = 0.008; β = 0.66, 95% CI: 0.20 to 1.13, p = 0.005; respectively). While no significant causal relationship was found between decaffeinated coffee and CAC (β = -1.32, 95% CI: -2.67 to 0.04, p = 0.056). The association between coffee and CAC was validated in the replication analysis (β = 0.27, 95% CI: 0.07 to 0.48, p = 0.009). Body mass index mediated 39.98% of the effect of coffee on CAC (95% CI: 9.78 to 70.19%, p = 0.009), and 5.79% of the effect of instant coffee on CAC (95% CI: 0.54 to 11.04%, p = 0.030).

Conclusion

Our study suggests that coffee other than decaffeinated coffee increases the risk of subclinical atherosclerosis inferred from CAC. Body mass index mediated 39.98 and 5.79% of the causal effects of coffee and instant coffee on CAC, respectively. Coffee should be consumed with caution, especially in individuals with established cardiovascular risk factors, and decaffeinated coffee appears to be a safer choice.

Association between walking pace and heart failure: A Mendelian randomization analysis

BACKGROUND AND AIM

The relationship between walking pace and heart failure (HF) has been recognized, yet the directionality and underlying mediating risk factors remain unclear.

METHODS AND RESULTS

This study utilized bidirectional two-sample Mendelian randomization (MR) with genome-wide association studies (GWAS) summary statistics to assess the causal relationships between walking pace and HF. Additionally, we employed a two-step Multivariable Mendelian Randomization (MVMR) to explore potential mediating factors. We further validated our findings by conducting two-sample MR with another available GWAS summary data on heart failure. Results indicated that genetically predicted increases in walking pace were associated with a reduced risk of HF (odds ratio (OR), 0.589, 95% confidence interval (CI): 0.417-0.832). Among the considered mediators, the waist-to-hip ratio (WHR) accounts for the largest proportion of the effect (45.7%, 95% CI: 13.2%, 78.2%). This is followed by type 2 diabetes at 24.4% (95% CI: 6.7%, 42.0%) and triglycerides at 18.6% (95% CI: 4.5%, 32.7%). Furthermore, our findings reveal that genetically predicted HF risk (OR, 0.975, 95% CI: 0.960-0.991) is associated with a slower walking pace. Validated findings were consistent with the main results.

CONCLUSIONS

In conclusion, MR analysis demonstrates that a slow walking pace is a reliable indicator of an elevated risk of HF, and the causal relationship is bidirectional. Interventions focusing on waist-to-hip ratio, type 2 diabetes, and triglycerides may provide valuable strategies for HF prevention in individuals with a slow walking pace.

Lipids, lipid-modified drug target genes, and the risk of male infertility: a Mendelian randomization study

Background

Previous observational studies have reported a possible association between circulating lipids and lipid-lowering drugs and male infertility (MIF), as well as the mediating role of circulating vitamin D. Then, due to issues such as bias, reverse causality, and residual confounding, inferring causal relationships from these studies may be challenging. Therefore, this study aims to explore the effects of circulating lipids and lipid-lowering drugs on MIF through Mendelian randomization (MR) analysis and evaluate the mediating role of vitamin D.

Method

Genetic variations related to lipid traits and the lipid-lowering effect of lipid modification targets are extracted from the Global Alliance for Lipid Genetics Genome-Wide Association Study. The summary statistics for MIF are from the FinnGen 9th edition. Using quantitative expression feature loci data from relevant organizations to obtain genetic variations related to gene expression level, further to explore the relationship between these target gene expression levels and MIF risk. Two-step MR analysis is used to explore the mediating role of vitamin D. Multiple sensitivity analysis methods (co-localization analysis, Egger intercept test, Cochrane's Q test, pleiotropy residuals and outliers (MR-PRESSO), and the leave-one-out method) are used to demonstrate the reliability of our results.

Result

In our study, we observed that lipid modification of four lipid-lowering drug targets was associated with MIF risk, the LDLR activator (equivalent to a 1-SD decrease in LDL-C) (OR=1.94, 95% CI 1.14-3.28, FDR=0.040), LPL activator (equivalent to a 1-SD decrease in TG) (OR=1.86, 95% CI 1.25-2.76, FDR=0.022), and CETP inhibitor (equivalent to a 1-SD increase in HDL-C) (OR=1.28, 95% CI 1.07-1.53, FDR=0.035) were associated with a higher risk of MIF. The HMGCR inhibitor (equivalent to a 1-SD decrease in LDL-C) was associated with a lower risk of MIF (OR=0.38, 95% CI 0.17-0.83, FDR=0.39). Lipid-modifying effects of three targets were partially mediated by serum vitamin D levels. Mediation was 0.035 (LDLR activator), 0.012 (LPL activator), and 0.030 (CETP inhibitor), with mediation ratios of 5.34% (LDLR activator), 1.94% (LPL activator), and 12.2% (CETP inhibitor), respectively. In addition, there was no evidence that lipid properties and lipid modification effects of six other lipid-lowering drug targets were associated with MIF risk. Multiple sensitivity analysis methods revealed insignificant evidence of bias arising from pleiotropy or genetic confounding.

Conclusion

This study did not support lipid traits (LDL-C, HDL-C, TG, Apo-A1, and Apo-B) as pathogenic risk factors for MIF. It emphasized that LPL, LDLR, CETP, and HMGCR were promising drug targets for improving male fertility.

The role of hypertension in the relationship between leisure screen time, physical activity and migraine: a 2-sample Mendelian randomization study

BACKGROUND

The relationship between lifestyle and migraine is complex, as it remains uncertain which specific lifestyle factors play the most prominent role in the development of migraine, or which modifiable metabolic traits serve as mediators in establishing causality.

METHODS

Independent genetic variants strongly associated with 20 lifestyle factors were selected as instrumental variables from corresponding genome-wide association studies (GWASs). Summary-level data for migraine were obtained from the FinnGen consortium (18,477 cases and 287,837 controls) as a discovery set and the GWAS meta-analysis data (26,052 cases and 487,214 controls) as a replication set. Estimates derived from the two datasets were combined using fixed-effects meta-analysis. Two-step univariable MR (UVMR) and multivariable Mendelian randomization (MVMR) analyses were conducted to evaluate 19 potential mediators of association and determine the proportions of these mediators.

RESULTS

The combined effect of inverse variance weighted revealed that a one standard deviation (SD) increase in genetically predicted Leisure screen time (LST) was associated with a 27.7% increase (95% CI: 1.14-1.44) in migraine risk, while Moderate or/and vigorous physical activity (MVPA) was associated with a 26.9% decrease (95% CI: 0.61-0.87) in migraine risk. The results of the mediation analysis indicated that out of the 19 modifiable metabolic risk factors examined, hypertension explains 24.81% of the relationship between LST and the risk of experiencing migraine. Furthermore, hypertension and diastolic blood pressure (DBP) partially weaken the association between MVPA and migraines, mediating 4.86% and 4.66% respectively.

CONCLUSION

Our research findings indicated that both LST and MVPA in lifestyle have independent causal effects on migraine. Additionally, we have identified that hypertension and DBP play a mediating role in the causal pathway between these two factors and migraine.

Effects of genetically proxied statins on diabetic nephropathy and retinopathy: a Mendelian randomization study

There is no reliable causal evidence for the effect of statins on diabetic nephropathy (DN) and diabetic retinopathy (DR), and the results of previous observational studies are contradictory. Genetic variants linked to low-density lipoprotein cholesterol (LDL-C) from a UK biobank genome-wide association study and located within a 100kb window around HMGCR were used to proxy statins, comparing with PCSK9 inhibitors (control). DN and DR genome-wide association study summary statistics were obtained from the FinnGen study. Secondary MR analyses and NHANES cross-sectional data were used for validation. Drug-target Mendelian randomization (MR) was applied to investigate the association between the genetically proxied inhibition of HMGCR and PCSK9 with DN and DR, p < 0.0125 was considered significant after Bonferroni Correction. To triangulate the findings, genetic variants of whole blood-derived targets gene expression (cis-eQTL) and plasma-derived protein (cis-pQTL) levels were used to perform secondary MR analyses and data from the National Health and Nutrition Examination Survey were used for cross-sectional analysis. Genetically proxied inhibition of HMGCR was associated with higher risks of DN and DR (DN: OR = 1.79, p = 0.01; DR: OR = 1.41, p = 0.004), while no such association was found for PCSK9. Secondary MR analyses confirmed these associations. Cross-sectional analysis revealed a positive link between statin use and DR incidence (OR = 1.26, p = 0.03) and a significant negative association with glomerular filtration rate (Beta = - 1.9, p = 0.03). This study provides genetic evidence that genetically proxied inhibition of HMGCR is associated with increased risks of DN/DR, and this effect may not be attributed to their LDL-C-lowering properties. For patients with diabetic dyslipidemia, PCSK9 inhibitors may be a preferable alternative.

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

AIMS

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

METHODS AND RESULTS

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

CONCLUSION

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

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

Background

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

Methods

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

Results

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

Conclusion

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

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

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

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

BACKGROUND

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

AIM

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

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

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

Background

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

Methods

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

Results

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

Conclusion

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

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

Background

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

Objective

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

Methods

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

Results

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

Conclusions

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

A new era in the science and care of kidney diseases

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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