Kidney Volume and Risk of Incident Kidney Outcomes.

BACKGROUND: Low total kidney volume (TKV) is a risk factor for chronic kidney disease (CKD). However, evaluations of nonlinear relationships, incident events, causal inference, and prognostic utility beyond traditional biomarkers are lacking. METHODS: TKV, height-adjusted TKV, and body surface area-adjusted TKV (BSA-TKV) of 34,595 White British ancestry participants were derived from the UK Biobank. Association with incident CKD, acute kidney injury (AKI), and cardiovascular events were assessed with Cox proportional hazard models. Prognostic thresholds for CKD risk stratification were identified using a modified Mazumdar method with bootstrap resampling. Two-sample Mendelian randomization was performed to assess the bidirectional association of genetically predicted TKV with kidney and cardiovascular traits. RESULTS: Adjusted for eGFR and albuminuria, a lower TKV of 10 mL was associated with a 6% higher risk of incident CKD (hazard ratio [HR] 1.06, 95% confidence interval [CI] 1.03 to 1.08, P = 5.8 x 10-6) in contrast to no association with incident AKI (HR 1.00, 95% CI 0.98 to 1.02, P = 0.66). Comparison of nested models demonstrated improved accuracy over the CKD Prognosis Consortium Incident CKD Risk Score with the addition of BSA-TKV or prognostic thresholds at 119 (10th percentile) and 145 mL/m2 (50th percentile). In Mendelian randomization, a lower genetically predicted TKV by 10 mL was associated with 10% higher CKD risk (odds ratio [OR] 1.10, 95% CI 1.06 to 1.14, P = 1.3 x 10-7). Reciprocally, an elevated risk of genetically predicted CKD by 2-fold was associated with a lower TKV by 7.88 mL (95% CI -9.81 to -5.95, P = 1.2 x 10-15). There were no significant observational or Mendelian randomization associations of TKV with cardiovascular complications. CONCLUSIONS: Kidney volume was associated with incident CKD independent of traditional risk factors including baseline eGFR and albuminuria. Mendelian randomization demonstrated a bidirectional relationship between kidney volume and CKD.

The circulating proteome and brain health: Mendelian randomisation and cross-sectional analyses.

Decline in cognitive function is the most feared aspect of ageing. Poorer midlife cognitive function is associated with increased dementia and stroke risk. The mechanisms underlying variation in cognitive function are uncertain. Here, we assessed associations between 1160 proteins' plasma levels and two measures of cognitive function, the digit symbol substitution test (DSST) and the Montreal Cognitive Assessment in 1198 PURE-MIND participants. We identified five DSST performance-associated proteins (NCAN, BCAN, CA14, MOG, CDCP1), with NCAN and CDCP1 showing replicated association in an independent cohort, GS (N = 1053). MRI-assessed structural brain phenotypes partially mediated (8-19%) associations between NCAN, BCAN, and MOG, and DSST performance. Mendelian randomisation analyses suggested higher CA14 levels might cause larger hippocampal volume and increased stroke risk, whilst higher CDCP1 levels might increase intracranial aneurysm risk. Our findings highlight candidates for further study and the potential for drug repurposing to reduce the risk of stroke and cognitive decline.

Vaspin: A Novel Biomarker Linking Gluteofemoral Body Fat and Type 2 Diabetes Risk.

OBJECTIVE: To determine whether adiposity depots modulate vaspin levels and whether vaspin predicts type 2 diabetes (T2D) risk, through epidemiological and genetic analyses. RESEARCH DESIGN AND METHODS: We assessed the relationship of plasma vaspin concentration with incident and prevalent T2D and adiposity-related variables in 1) the Prospective Urban and Rural Epidemiology (PURE) biomarker substudy (N = 10,052) and 2) the Outcome Reduction with Initial Glargine Intervention (ORIGIN) trial (N = 7,840), using regression models. We then assessed whether vaspin is causally associated with T2D and whether genetic variants associated with MRI-measured adiposity depots modulate vaspin levels, using two-sample Mendelian randomization (MR). RESULTS: A 1-SD increase in circulating vaspin levels was associated with a 16% increase in incident T2D in the PURE cohort (hazard ratio 1.16; 95% CI 1.09-1.23; P = 4.26 × 10-7) and prevalent T2D in the ORIGIN cohort (odds ratio [OR] 1.16; 95% CI 1.07-1.25; P = 2.17 × 10-4). A 1-unit increase in BMI and triglyceride levels was associated with a 0.08-SD (95% CI 0.06-0.10; P = 2.04 × 10-15) and 0.06-SD (95% CI 0.04-0.08; P = 4.08 × 10-13) increase, respectively, in vaspin in the PURE group. Consistent associations were observed in the ORIGIN cohort. MR results reinforced the association between vaspin and BMI-adjusted T2D risk (OR 1.01 per 1-SD increase in vaspin level; 95% CI 1.00-1.02; P = 2.86 × 10-2) and showed that vaspin was increased by 0.10 SD per 1-SD decrease in genetically determined gluteofemoral adiposity (95% CI 0.02-0.18; P = 2.01 × 10-2). No relationships were found between subcutaneous or visceral adiposity and vaspin. CONCLUSIONS: These findings support that higher vaspin levels are related to increased T2D risk and reduced gluteofemoral adiposity, positioning vaspin as a promising clinical predictor for T2D.

A novel multi-ancestry proteome-wide Mendelian randomization study implicates extracellular proteins, tubular cells, and fibroblasts in estimated glomerular filtration rate regulation.

Estimated glomerular filtration rate (eGFR) impacts the concentration of plasma biomarkers confounding biomarker association studies of eGFR with reverse causation. To identify biomarkers causally associated with eGFR, we performed a proteome-wide Mendelian randomization study. Genetic variants nearby biomarker coding genes were tested for association with plasma concentration of 1,161 biomarkers in a multi-ancestry sample of 12,066 participants from the Prospective Urban and Rural Epidemiological (PURE) study. Using two-sample Mendelian randomization, individual variants' effects on biomarker concentration were correlated with their effects on eGFR and kidney traits from published genome-wide association studies (GWAS). Genetically altered concentrations of 22 biomarkers were associated with eGFR above a Bonferroni-corrected significance threshold. Five biomarkers were previously identified by GWAS (UMOD, FGF5, LGALS7, NINJ1, COL18A1). Nine biomarkers were within 1 Mb of the lead GWAS variant but the gene for the biomarker was unidentified as the candidate for the GWAS signal (INHBC, TNFRSF11A, TCN2, PXN1, PRTN3, PSMD9, TFPI, ITGB6, CA3). Single-cell transcriptomic data indicated the 22 biomarkers are expressed in kidney tubules, collecting duct, fibroblasts, and immune cells. Pathway analysis showed significant enrichment of identified biomarkers in the extracellular kidney parenchyma. Thus, using genetic regulators of biomarker concentration via proteome-wide Mendelian randomization, we identified 22 biomarkers that appear to causally impact eGFR in either a beneficial or adverse manner. The current study provides rationale for novel therapeutic targets for eGFR and emphasized a role for extracellular proteins produced by tubular cells and fibroblasts for impacting eGFR.

A versatile, fast and unbiased method for estimation of gene-by-environment interaction effects on biobank-scale datasets.

Identification of gene-by-environment interactions (GxE) is crucial to understand the interplay of environmental effects on complex traits. However, current methods evaluating GxE on biobank-scale datasets have limitations. We introduce MonsterLM, a multiple linear regression method that does not rely on model specification and provides unbiased estimates of variance explained by GxE. We demonstrate robustness of MonsterLM through comprehensive genome-wide simulations using real genetic data from 325,989 individuals. We estimate GxE using waist-to-hip-ratio, smoking, and exercise as the environmental variables on 13 outcomes (N = 297,529-325,989) in the UK Biobank. GxE variance is significant for 8 environment-outcome pairs, ranging from 0.009 - 0.071. The majority of GxE variance involves SNPs without strong marginal or interaction associations. We observe modest improvements in polygenic score prediction when incorporating GxE. Our results imply a significant contribution of GxE to complex trait variance and we show MonsterLM to be well-purposed to handle this with biobank-scale data.

Biomarkers Associated With Severe COVID-19 Among Populations With High Cardiometabolic Risk: A 2-Sample Mendelian Randomization Study.

Importance: Cardiometabolic parameters are established risk factors for COVID-19 severity. The identification of causal or protective biomarkers for COVID-19 severity may facilitate the development of novel therapies. Objective: To identify protein biomarkers that promote or reduce COVID-19 severity and that mediate the association of cardiometabolic risk factors with COVID-19 severity. Design, Setting, and Participants: This genetic association study using 2-sample mendelian randomization (MR) was conducted in 2022 to investigate associations among cardiometabolic risk factors, circulating biomarkers, and COVID-19 hospitalization. Inputs for MR included genetic and proteomic data from 4147 participants with dysglycemia and cardiovascular risk factors collected through the Outcome Reduction With Initial Glargine Intervention (ORIGIN) trial. Genome-wide association study summary statistics were obtained from (1) 3 additional independent plasma proteome studies, (2) genetic consortia for selected cardiometabolic risk factors (including body mass index [BMI], type 2 diabetes, type 1 diabetes, and systolic blood pressure; all n >10 000), and (3) the COVID-19 Host Genetics Initiative (n = 5773 hospitalized and 15 497 nonhospitalized case participants with COVID-19). Data analysis was performed in July 2022. Exposures: Genetically determined concentrations of 235 circulating proteins assayed with a multiplex biomarker panel from the ORIGIN trial for the initial analysis. Main Outcomes and Measures: Hospitalization status of individuals from the COVID-19 Host Genetics Initiative with a positive COVID-19 test result. Results: Among 235 biomarkers tested in samples totaling 22 101 individuals, MR analysis showed that higher kidney injury molecule-1 (KIM-1) levels reduced the likelihood of COVID-19 hospitalization (odds ratio [OR] per SD increase in KIM-1 levels, 0.86 [95% CI, 0.79-0.93]). A meta-analysis validated the protective association with no observed directional pleiotropy (OR per SD increase in KIM-1 levels, 0.91 [95% CI, 0.88-0.95]). Of the cardiometabolic risk factors studied, only BMI was associated with KIM-1 levels (0.17 SD increase in biomarker level per 1 kg/m2 [95% CI, 0.08-0.26]) and COVID-19 hospitalization (OR per 1-SD biomarker level, 1.33 [95% CI, 1.18-1.50]). Multivariable MR analysis also revealed that KIM-1 partially mitigated the association of BMI with COVID-19 hospitalization, reducing it by 10 percentage points (OR adjusted for KIM-1 level per 1 kg/m2, 1.23 [95% CI, 1.06-1.43]). Conclusions and Relevance: In this genetic association study, KIM-1 was identified as a potential mitigator of COVID-19 severity, possibly attenuating the increased risk of COVID-19 hospitalization among individuals with high BMI. Further studies are required to better understand the underlying biological mechanisms.

ACLY and CKD: A Mendelian Randomization Analysis.

Introduction: Adenosine triphosphate-citrate lyase (ACLY) inhibition is a therapeutic strategy under investigation for atherosclerotic cardiovascular disease, nonalcoholic steatohepatitis, and metabolic syndrome. Mouse models suggest that ACLY inhibition could reduce inflammation and kidney fibrosis. Genetic analysis of ACLY in chronic kidney disease (CKD) has not been performed. Methods: We constructed a genetic instrument by selecting variants associated with ACLY expression in the expression quantitative trait loci genetics consortium (eQTLGen) from blood samples from 31,684 participants. In a 2-sample Mendelian randomization analysis, we evaluated the effect of genetically predicted ACLY expression on the risk of CKD, estimated glomerular filtration rate (eGFR), and albumin-to-creatinine ratio (ACR) using the CKD Genetics (CKDGen) consortium, UK Biobank, and the Finnish Genetics (FinnGen) consortium totaling 66,396 CKD cases and 958,517 controls. Results: ACLY is constitutively expressed in all cell types including in whole blood. The genetic instrument included 13 variants and explained 1.5% of the variation in whole blood ACLY gene expression. A 34% reduction in ACLY expression score was associated with a 0.04 mmol/l reduced low-density lipoprotein (LDL) cholesterol (P = 3.4 × 10-4) and a 9% reduced risk of CKD (stages 3, 4, 5, dialysis, or eGFR < 60 ml/min per 1.73 m2) (odds ratio [OR] = 0.91, 95% CI: 0.85-0.98, P = 0.008), but no association was observed with either eGFR or ACR. Conclusion: Mendelian randomization analyses revealed that genetically reduced ACLY expression was associated with reduced risk of CKD but had no effect on either eGFR or ACR. Further evaluation of ACLY in kidney disease is warranted.

Elevated Lipoprotein(a) and Risk of Atrial Fibrillation: An Observational and Mendelian Randomization Study.

BACKGROUND: Atrial fibrillation (AF) is a cardiac arrhythmia associated with an elevated risk of stroke, heart failure, and mortality. However, preventative therapies are needed with ancillary benefits on its cardiovascular comorbidities. Lipoprotein(a) (Lp[a]) is a recognized risk factor for atherosclerotic cardiovascular disease (ASCVD), which itself increases AF risk, but it remains unknown whether Lp(a) is a causal mediator of AF independent of ASCVD. OBJECTIVES: This study investigated the role of Lp(a) in AF and whether it is independent of ASCVD. METHODS: Measured and genetically predicted Lp(a) levels were tested for association with 20,432 cases of incident AF in the UK Biobank (N = 435,579). Mendelian randomization analyses were performed by using summary-level data for AF from publicly available genome-wide association studies (N = 1,145,375). RESULTS: In the UK Biobank, each 50 nmol/L (23 mg/dL) increase in Lp(a) was associated with an increased risk of incident AF using measured Lp(a) (HR: 1.03; 95% CI: 1.02-1.04 ; P = 1.65 × 10-8) and genetically predicted Lp(a) (OR: 1.03; 95% CI: 1.02-1.05; P = 1.33 × 10-5). Mendelian randomization analyses using independent data replicated the effect (OR: 1.04 per 50 nmol/L Lp[a] increase; 95% CI: 1.03-1.05 per 50 nmol/L Lp[a] increase; P = 9.23 × 10-10). There was no evidence of risk-conferring effect from low-density lipoprotein cholesterol or triglycerides, and only 39% (95% CI: 27%-73%) of Lp(a) risk was mediated through ASCVD, suggesting that Lp(a) partly influences AF independent of its known effects on ASCVD. CONCLUSIONS: Our findings implicate Lp(a) as a potential causal mediator in the development of AF which show that the effects of Lp(a) extend across myocardial tissues. Ongoing clinical trials for Lp(a)-lowering therapies should evaluate effects on AF prevention.

GWAS and ExWAS of blood mitochondrial DNA copy number identifies 71 loci and highlights a potential causal role in dementia.

Background: Mitochondrial DNA copy number (mtDNA-CN) is an accessible blood-based measurement believed to capture underlying mitochondrial (MT) function. The specific biological processes underpinning its regulation, and whether those processes are causative for disease, is an area of active investigation. Methods: We developed a novel method for array-based mtDNA-CN estimation suitable for biobank-scale studies, called 'automatic mitochondrial copy (AutoMitoC).' We applied AutoMitoC to 395,781 UKBiobank study participants and performed genome- and exome-wide association studies, identifying novel common and rare genetic determinants. Finally, we performed two-sample Mendelian randomization to assess whether genetically low mtDNA-CN influenced select MT phenotypes. Results: Overall, genetic analyses identified 71 loci for mtDNA-CN, which implicated several genes involved in rare mtDNA depletion disorders, deoxynucleoside triphosphate (dNTP) metabolism, and the MT central dogma. Rare variant analysis identified SAMHD1 mutation carriers as having higher mtDNA-CN (beta = 0.23 SDs; 95% CI, 0.18-0.29; p=2.6 × 10-19), a potential therapeutic target for patients with mtDNA depletion disorders, but at increased risk of breast cancer (OR = 1.91; 95% CI, 1.52-2.40; p=2.7 × 10-8). Finally, Mendelian randomization analyses suggest a causal effect of low mtDNA-CN on dementia risk (OR = 1.94 per 1 SD decrease in mtDNA-CN; 95% CI, 1.55-2.32; p=7.5 × 10-4). Conclusions: Altogether, our genetic findings indicate that mtDNA-CN is a complex biomarker reflecting specific MT processes related to mtDNA regulation, and that these processes are causally related to human diseases. Funding: No funds supported this specific investigation. Awards and positions supporting authors include: Canadian Institutes of Health Research (CIHR) Frederick Banting and Charles Best Canada Graduate Scholarships Doctoral Award (MC, PM); CIHR Post-Doctoral Fellowship Award (RM); Wellcome Trust Grant number: 099313/B/12/A; Crasnow Travel Scholarship; Bongani Mayosi UCT-PHRI Scholarship 2019/2020 (TM); Wellcome Trust Health Research Board Irish Clinical Academic Training (ICAT) Programme Grant Number: 203930/B/16/Z (CJ); European Research Council COSIP Grant Number: 640580 (MO); E.J. Moran Campbell Internal Career Research Award (MP); CISCO Professorship in Integrated Health Systems and Canada Research Chair in Genetic and Molecular Epidemiology (GP).

Our cells are powered by small internal compartments known as mitochondria, which host several copies of their own 'mitochondrial' genome. Defects in these semi-autonomous structures are associated with a range of severe, and sometimes fatal conditions: easily checking the health of mitochondria through cheap, quick and non-invasive methods can therefore help to improve human health. Measuring the concentration of mitochondrial DNA molecules in our blood cells can help to estimate the number of mitochondrial genome copies per cell, which in turn act as a proxy for the health of the compartment. In fact, having lower or higher concentration of mitochondrial DNA molecules is associated with diseases such as cancer, stroke, or cardiac conditions. However, current approaches to assess this biomarker are time and resource-intensive; they also do not work well across people with different ancestries, who have slightly different versions of mitochondrial genomes. In response, Chong et al. developed a new method for estimating mitochondrial DNA concentration in blood samples. Called AutoMitoC, the automated pipeline is fast, easy to use, and can be used across ethnicities. Applying this method to nearly 400,000 individuals highlighted 71 genetic regions for which slight sequence differences were associated with changes in mitochondrial DNA concentration. Further investigation revealed that these regions contained genes that help to build, maintain, and organize mitochondrial DNA. In addition, the analyses yield preliminary evidence showing that lower concentration of mitochondrial DNA may be linked to a higher risk of dementia. Overall, the work by Chong et al. demonstrates that AutoMitoC can be used to investigate how mitochondria are linked to health and disease in populations across the world, potentially paving the way for new therapeutic approaches.

Blood Levels of the SMOC1 Hepatokine Are Not Causally Linked with Type 2 Diabetes: A Bidirectional Mendelian Randomization Study.

Hepatokines are liver-derived proteins that may influence metabolic pathways such as insulin sensitivity. Recently, Sparc-related modular calcium-binding protein 1 (SMOC1) was identified as glucose-responsive hepatokine that is dysregulated in the setting of non-alcoholic fatty liver disease (NAFLD). While SMOC1 may influence glucose-insulin homeostasis in rodents, it is unknown if SMOC1 is influenced by NAFLD in humans. It is also unknown if SMOC1 is causally associated with metabolic and disease traits in humans. Therefore, we aimed to determine the effect of NAFLD on SMOC1 gene expression in the liver and aimed to explore the potential causal associations of SMOC1 levels with NAFLD, T2D, and glycemic traits in humans. Using an RNA sequencing dataset from a cohort of 216 patients with NAFLD, we assessed SMOC1 expression levels across the NAFLD spectrum. We performed a series of bidirectional inverse-variance weighted Mendelian randomization (MR) analyses on blood SMOC1 levels using two sources of genome-wide association studies (GWAS) (Fenland study, n = 10,708 and INTERVAL study, n = 3301). We utilized GWAS summary statistics for NAFLD in 8434 cases and 770,180 controls, as well as publicly available GWAS for type 2 diabetes (T2D), body mass index (BMI), waist-to-hip ratio (WHR), fasting blood insulin (FBI), fasting blood glucose (FBG), homeostatic Model Assessment of Insulin Resistance (HOMA-B and HOMA-IR), and hemoglobin A1c (HbA1C). We found that SMOC1 expression showed no significant differences across NAFLD stages. We also identified that the top single-nucleotide polymorphism associated with blood SMOC1 levels, was associated with SMOC1 gene expression in the liver, but not in other tissues. Using MR, we did not find any evidence that genetically predicted NAFLD, T2D, and glycemic traits influenced SMOC1 levels. We also did not find evidence that blood SMOC1 levels were causally associated with T2D, NAFLD, and glycemic traits. In conclusion, the hepatokine SMOC1 does not appear to be modulated by the presence of NAFLD and may not regulate glucose-insulin homeostasis in humans. Results of this study suggest that blood factors regulating metabolism in rodents may not always translate to human biology.

Electronic health record-based genome-wide meta-analysis provides insights on the genetic architecture of non-alcoholic fatty liver disease.

Non-alcoholic fatty liver disease (NAFLD) is a complex disease linked to several chronic diseases. We aimed at identifying genetic variants associated with NAFLD and evaluating their functional consequences. We performed a genome-wide meta-analysis of 4 cohorts of electronic health record-documented NAFLD in participants of European ancestry (8,434 cases and 770,180 controls). We identify 5 potential susceptibility loci for NAFLD (located at or near GCKR, TR1B1, MAU2/TM6SF2, APOE, and PNPLA3). We also report a potentially causal effect of lower LPL expression in adipose tissue on NAFLD susceptibility and an effect of the FTO genotype on NAFLD. Positive genetic correlations between NAFLD and cardiometabolic diseases and risk factors such as body fat accumulation/distribution, lipoprotein-lipid levels, insulin resistance, and coronary artery disease and negative genetic correlations with parental lifespan, socio-economic status, and acetoacetate levels are observed. This large GWAS meta-analysis reveals insights into the genetic architecture of NAFLD.

Polygenic Risk Score for Coronary Artery Disease Improves the Prediction of Early-Onset Myocardial Infarction and Mortality in Men.

BACKGROUND: Several risk factors for coronary artery disease (CAD) have been described, some of which are genetically determined. The use of a polygenic risk score (PRS) could improve CAD risk assessment, but predictive accuracy according to age and sex is not well established. METHODS: A PRSCAD including the weighted effects of >1.14 million single nucleotide polymorphisms associated with CAD was calculated in UK Biobank (n=408 422), using LDpred. Cox regressions were performed, stratified by age quartiles and sex, for incident myocardial infarction (MI) and mortality, with a median follow-up of 11.0 years. Improvement in risk prediction of MI was assessed by comparing PRSCAD to the pooled cohort equation with categorical net reclassification index using a 2% threshold (NRI0.02) and continuous NRI (NRI>0). RESULTS: From 7746 incident MI cases and 393 725 controls, hazard ratio for MI reached 1.53 (95% CI, 1.49-1.56; P=2.69×10-296) per SD increase of PRSCAD. PRSCAD was significantly associated with MI in both sexes, with a stronger association in men (interaction P=0.002), particularly in those aged between 40 and 51 years (hazard ratio, 2.00 [95% CI, 1.86-2.16], P=1.93×10-72). This group showed the highest reclassification improvement, mainly driven by the up-classification of cases (NRI0.02, 0.199 [95% CI, 0.157-0.248] and NRI>0, 0.602 [95% CI, 0.525-0.683]). From 23 982 deaths, hazard ratio for mortality was 1.08 (95% CI, 1.06-1.09; P=5.46×10-30) per SD increase of PRSCAD, with a stronger association in men (interaction P=1.60×10-6). CONCLUSIONS: Our PRSCAD predicts MI incidence and all-cause mortality, especially in men aged between 40 and 51 years. PRS could optimize the identification and management of individuals at risk for CAD.

A trans-omic Mendelian randomization study of parental lifespan uncovers novel aging biology and therapeutic candidates for chronic diseases.

The study of parental lifespan has emerged as an innovative tool to advance aging biology and our understanding of the genetic architecture of human longevity and aging-associated diseases. Here, we leveraged summary statistics of a genome-wide association study including over one million parental lifespans to identify genetically regulated genes from the Genotype-Tissue Expression project. Through a combination of multi-tissue transcriptome-wide association analyses and genetic colocalization, we identified novel genes that may be associated with parental lifespan. Mendelian randomization (MR) analyses also identified circulating proteins and metabolites causally associated with parental lifespan and chronic diseases offering new drug repositioning opportunities such as those targeting apolipoprotein-B-containing lipoproteins. Liver expression of HP, the gene encoding haptoglobin, and plasma haptoglobin levels were causally linked with parental lifespan. Phenome-wide MR analyses were used to map genetically regulated genes, proteins and metabolites with other human traits as well as the disease-related phenome in the FinnGen cohorts (n = 135,638). Altogether, this study identified new candidate genes, circulating proteins and metabolites that may influence human aging as well as potential therapeutic targets for chronic diseases that warrant further investigation.

Lipoprotein Proteomics and Aortic Valve Transcriptomics Identify Biological Pathways Linking Lipoprotein(a) Levels to Aortic Stenosis.

Lipoprotein(a) (Lp(a)) is one of the most important risk factors for the development of calcific aortic valve stenosis (CAVS). However, the mechanisms through which Lp(a) causes CAVS are currently unknown. Our objectives were to characterize the Lp(a) proteome and to identify proteins that may be differentially associated with Lp(a) in patients with versus without CAVS. Our second objective was to identify genes that may be differentially regulated by exposure to high versus low Lp(a) levels in explanted aortic valves from patients with CAVS. We isolated Lp(a) from the blood of 21 patients with CAVS and 22 volunteers and performed untargeted label-free analysis of the Lp(a) proteome. We also investigated the transcriptomic signature of calcified aortic valves from patients who underwent aortic valve replacement with high versus low Lp(a) levels (n = 118). Proteins involved in the protein activation cascade, platelet degranulation, leukocyte migration, and response to wounding may be associated with Lp(a) depending on CAVS status. The transcriptomic analysis identified genes involved in cardiac aging, chondrocyte development, and inflammation as potentially influenced by Lp(a). Our multi-omic analyses identified biological pathways through which Lp(a) may cause CAVS, as well as key molecular events that could be triggered by Lp(a) in CAVS development.

Sex-Specific Associations of Genetically Predicted Circulating Lp(a) (Lipoprotein(a)) and Hepatic LPA Gene Expression Levels With Cardiovascular Outcomes: Mendelian Randomization and Observational Analyses.

BACKGROUND: Elevated Lp(a) (Lipoprotein(a)) levels are associated with coronary artery disease (CAD), ischemic stroke (IS), and calcific aortic valve stenosis (CAVS). Studies investigating the association between Lp(a) levels and these diseases in women have yielded inconsistent results. METHODS: To investigate the association of Lp(a) with sex-specific cardiovascular outcomes, we determined the association between genetically predicted Lp(a) levels (using 27 single nucleotide polymorphisms at the LPA locus) and hepatic LPA expression (using 80 single nucleotide polymorphisms at the LPA locus associated with LPA mRNA expression in liver samples from the Genotype-Tissue Expression dataset) on CAD, IS, and CAVS using individual participant data from the UK Biobank: 408 403 participants of European ancestry (37 102, 4283, and 2574 with prevalent CAD, IS, and CAVS, respectively). The long-term association between Lp(a) levels and incident CAD, IS, and CAVS was also investigated in European Prospective Investigation into Cancer and Nutrition-Norfolk: 18 721 participants (3964, 846, and 424 with incident CAD, IS, and CAVS, respectively). RESULTS: Genetically predicted plasma Lp(a) levels were positively and similarly associated with prevalent and incident CAD and CAVS in men and women. Genetically predicted plasma Lp(a) levels were associated with prevalent and incident IS when we studied men and women pooled together, and in men only. Genetically predicted LPA expression levels were associated with prevalent CAD and CAVS in men and women but not with IS. CONCLUSIONS: Genetically predicted blood Lp(a) and hepatic LPA gene expression as well as serum Lp(a) levels predict the risk of CAD and CAVS in men and in women. Whether RNA interference therapies aiming at lowering Lp(a) levels could be useful in reducing cardiovascular disease risk in both men and women with high Lp(a) levels needs to be determined in large-scale cardiovascular outcomes trials.

A Comparative Analysis of the Lipoprotein(a) and Low-Density Lipoprotein Proteomic Profiles Combining Mass Spectrometry and Mendelian Randomization.

BACKGROUND: Lipoprotein(a) (Lp[a]), which consists of a low-density lipoprotein (LDL) bound to apolipoprotein(a), is one of the strongest genetic risk factors for atherosclerotic cardiovascular diseases. Few studies have performed hypothesis-free direct comparisons of the Lp(a) and the LDL proteomes. Our objectives were to compare the Lp(a) and the LDL proteomic profiles and to evaluate the effect of lifelong exposure to elevated Lp(a) or LDL cholesterol levels on the plasma proteomic profile. METHODS: We performed a label-free analysis of the Lp(a) and LDL proteomic profiles of healthy volunteers in a discovery (n = 6) and a replication (n = 9) phase. We performed inverse variance weighted Mendelian randomization to document the effect of lifelong exposure to elevated Lp(a) or LDL cholesterol levels on the plasma proteomic profile of participants of the INTERVAL study. RESULTS: We identified 15 proteins that were more abundant on Lp(a) compared with LDL (serping1, pi16, itih1, itih2, itih3, pon1, podxl, cd44, cp, ptprg, vtn, pcsk9, igfals, vcam1, and ttr). We found no proteins that were more abundant on LDL compared with Lp(a). After correction for multiple testing, lifelong exposure to elevated LDL cholesterol levels was associated with the variation of 18 plasma proteins whereas Lp(a) did not appear to influence the plasma proteome. CONCLUSIONS: Results of this study highlight marked differences in the proteome of Lp(a) and LDL as well as in the effect of lifelong exposure to elevated LDL cholesterol or Lp(a) on the plasma proteomic profile.

CONTEXTE: La lipoprotéine(a) (Lp[a]), qui est constituée d'une lipoprotéine de basse densité (LDL) liée à une apolipoprotéine(a), est l'un des plus importants facteurs de risque génétiques de survenue d'une maladie cardiovasculaire athéroscléreuse. Peu d'études comparatives directes sans hypothèse ont porté sur le protéome de la Lp(a) et celui des LDL. Nos objectifs étaient de comparer les profils protéomiques de la Lp(a) et des LDL et d'évaluer l'effet d'une exposition à vie à un taux élevé de Lp(a) ou de cholestérol LDL sur le profil protéomique plasmatique. MÉTHODOLOGIE: Nous avons réalisé une analyse sans marquage des profils protéomiques de la Lp(a) et des LDL chez des volontaires en bonne santé dans le cadre d'une phase de découverte (n = 6) et d'une phase de réplication (n = 9). Pour rendre compte de l'effet d'une exposition à vie à un taux élevé de Lp(a) ou de cholestérol des LDL sur le profil protéomique plasmatique des participants de l'étude INTERVAL, nous avons utilisé une analyse de randomisation Mendélienne avec pondération par l'inverse de la variance. RÉSULTATS: Nous avons relevé 15 protéines associées en plus grande abondance à la Lp(a) qu'aux LDL (serping1, pi16, itih1, itih2, itih3, pon1, podxl, cd44, cp, ptprg, vtn, pcsk9, igfals, vcam1 et ttr). Nous n'avons noté aucune protéine associée en plus grande abondance aux LDL qu'à la Lp(a). Après correction pour tenir compte de la multiplicité des tests, l'exposition à vie à un taux élevé de cholestérol LDL a été associée à la variation de 18 protéines plasmatiques, tandis que le taux de Lp(a) ne semblait pas influencer le protéome plasmatique. CONCLUSIONS: Les résultats de notre étude font ressortir les différences marquées entre le protéome de la Lp(a) et celui des LDL, ainsi qu'entre l'effet sur le profil protéomique plasmatique de l'exposition à vie à un taux élevé de cholestérol LDL et celui de l'exposition à vie à un taux élevé de Lp(a).

Circulating Galectin-3 Levels Are Not Associated With Nonalcoholic Fatty Liver Disease: A Mendelian Randomization Study.

CONTEXT: The impact of galectin-3 inhibitors on nonalcoholic fatty liver diseases (NAFLD)-related outcomes is currently under investigation in randomized clinical trials. Whether there is a causal association between plasma galectin-3 levels and NAFLD is unknown. OBJECTIVE: To evaluate the causal effect of circulating galectin-3 levels on NAFLD as well as >800 other human diseases. DESIGN: Inverse variance-weighted (IVW) Mendelian randomization (MR) and phenome-wide MR. SETTING: Summary statistics of genome-wide association studies. PATIENTS: Participants of the UK Biobank, Electronic Medical Records and Genomics (eMERGE), FinnGen, Prevention of Renal and Vascular End-Stage Disease (PREVEND), and IMPROVE cohorts. INTERVENTION: Identification of independent single-nucleotide polymorphisms (SNPs) associated with galectin-3 levels (P < 5 × 10-8) in the PREVEND (14 SNPs) and IMPROVE (3 SNPs) cohorts. MAIN OUTCOME MEASURES: Presence of NAFLD in a meta-analysis of genome-wide association study of the eMERGE, UK Biobank, and FinnGen cohorts (3042 NAFLD cases and 504 853 controls), as well as >800 other human diseases in the UK Biobank and FinnGen. RESULTS: Using IVW-MR, we found no causal association between galectin-3 levels and NAFLD in the meta-analysis of the 3 cohorts or in each individual cohort. After correction for multiple testing, we found no causal association between galectin-3 levels and >800 human disease-related traits. CONCLUSIONS: This MR study revealed no causal associations between circulating galectin-3 levels and NAFLD or any other disease traits, suggesting that plasma galectin-3 levels may not be directly implicated in the pathogenesis of NAFLD or other human diseases.

Interaction of Autotaxin With Lipoprotein(a) in Patients With Calcific Aortic Valve Stenosis.

Our objectives were to determine whether autotaxin (ATX) is transported by lipoprotein(a) [Lp(a)] in human plasma and if could be used as a biomarker of calcific aortic valve stenosis (CAVS). We first found that ATX activity was higher in Lp(a) compared to low-density lipoprotein fractions in isolated fractions of 10 healthy participants. We developed a specific assay to measure ATX-Lp(a) in 88 patients with CAVS and 144 controls without CAVS. In a multivariable model corrected for CAVS risk factors, ATX-Lp(a) was associated with CAVS (p = 0.003). We concluded that ATX is preferentially transported by Lp(a) and might represent a novel biomarker for CAVS.

Genetic and In Vitro Inhibition of PCSK9 and Calcific Aortic Valve Stenosis.

The authors investigated whether PCSK9 inhibition could represent a therapeutic strategy in calcific aortic valve stenosis (CAVS). A meta-analysis of 10 studies was performed to determine the impact of the PCSK9 R46L variant on CAVS, and the authors found that CAVS was less prevalent in carriers of this variant (odds ratio: 0.80 [95% confidence interval: 0.70 to 0.91]; p = 0.0011) compared with noncarriers. PCSK9 expression was higher in the aortic valves of patients CAVS compared with control patients. In human valve interstitials cells submitted to a pro-osteogenic medium, PCSK9 levels increased and a PCSK9 neutralizing antibody significantly reduced calcium accumulation.

Lipoprotein-associated phospholipase A2 activity, genetics and calcific aortic valve stenosis in humans.

BACKGROUND: Lipoprotein-associated phospholipase A2 (Lp-PLA2) activity has been shown to predict calcific aortic valve stenosis (CAVS) outcomes. Our objective was to test the association between plasma Lp-PLA2 activity and genetically elevated Lp-PLA2 mass/activity with CAVS in humans. METHODS AND RESULTS: Lp-PLA2 activity was measured in 890 patients undergoing cardiac surgery, including 476 patients undergoing aortic valve replacement for CAVS and 414 control patients undergoing coronary artery bypass grafting. After multivariable adjustment, Lp-PLA2 activity was positively associated with the presence of CAVS (OR=1.21 (95% CI 1.04 to 1.41) per SD increment). We selected four single nucleotide polymorphisms (SNPs) at the PLA2G7 locus associated with either Lp-PLA2 mass or activity (rs7756935, rs1421368, rs1805017 and rs4498351). Genetic association studies were performed in eight cohorts: Quebec-CAVS (1009 cases/1017 controls), UK Biobank (1350 cases/349 043 controls), European Prospective Investigation into Cancer and Nutrition-Norfolk (504 cases/20 307 controls), Genetic Epidemiology Research on Aging (3469 cases/51 723 controls), Malmö Diet and Cancer Study (682 cases/5963 controls) and three French cohorts (3123 cases/6532 controls), totalling 10 137 CAVS cases and 434 585 controls. A fixed-effect meta-analysis using the inverse-variance weighted method revealed that none of the four SNPs was associated with CAVS (OR=0.99 (95% CI 0.96 to 1.02, p=0.55) for rs7756935, 0.97 (95% CI 0.93 to 1.01, p=0.11) for rs1421368, 1.00 (95% CI 1.00 to 1.01, p=0.29) for rs1805017, and 1.00 (95% CI 0.97 to 1.04, p=0.87) for rs4498351). CONCLUSIONS: Higher Lp-PLA2 activity is significantly associated with the presence of CAVS and might represent a biomarker of CAVS in patients with heart disease. Results of our genetic association study suggest that Lp-PLA2 is however unlikely to represent a causal risk factor or therapeutic target for CAVS.