Meta-GWAS of PCSK9 levels detects two novel loci at APOB and TM6SF2.

BACKGROUND: Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key player in lipid metabolism, as it degrades low-density lipoprotein (LDL) receptors from hepatic cell membranes. So far, only variants of the PCSK9 gene locus were found to be associated with PCSK9 levels. Here we aimed to identify novel genetic loci that regulate PCSK9 levels and how they relate to other lipid traits. Additionally, we investigated to what extend the causal effect of PCSK9 on coronary artery disease (CAD) is mediated by low-density lipoprotein-cholesterol (LDL-C). METHODS AND RESULTS: We performed a genome-wide association study meta-analysis of PCSK9 levels in up to 12 721 samples of European ancestry. The estimated heritability was 10.3%, which increased to 12.6% using only samples from patients without statin treatment. We successfully replicated the known PCSK9 hit consisting of three independent signals. Interestingly, in a study of 300 African Americans, we confirmed the locus with a different PCSK9 variant. Beyond PCSK9, our meta-analysis detected three novel loci with genome-wide significance. Co-localization analysis with cis-eQTLs and lipid traits revealed biologically plausible candidate genes at two of them: APOB and TM6SF2. In a bivariate Mendelian Randomization analysis, we detected a strong effect of PCSK9 on LDL-C, but not vice versa. LDL-C mediated 63% of the total causal effect of PCSK9 on CAD. CONCLUSION: Our study identified novel genetic loci with plausible candidate genes affecting PCSK9 levels. Ethnic heterogeneity was observed at the PCSK9 locus itself. Although the causal effect of PCSK9 on CAD is mainly mediated by LDL-C, an independent direct effect also occurs.

Sex and statin-related genetic associations at the PCSK9 gene locus: results of genome-wide association meta-analysis.

BACKGROUND: Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key player of lipid metabolism with higher plasma levels in women throughout their life. Statin treatment affects PCSK9 levels also showing evidence of sex-differential effects. It remains unclear whether these differences can be explained by genetics. METHODS: We performed genome-wide association meta-analyses (GWAS) of PCSK9 levels stratified for sex and statin treatment in six independent studies of Europeans (8936 women/11,080 men respectively 14,825 statin-free/5191 statin-treated individuals). Loci associated in one of the strata were tested for statin- and sex-interactions considering all independent signals per locus. Independent variants at the PCSK9 gene locus were then used in a stratified Mendelian Randomization analysis (cis-MR) of PCSK9 effects on low-density lipoprotein cholesterol (LDL-C) levels to detect differences of causal effects between the subgroups. RESULTS: We identified 11 loci associated with PCSK9 in at least one stratified subgroup (p < 1.0 × 10-6), including the PCSK9 gene locus and five other lipid loci: APOB, TM6SF2, FADS1/FADS2, JMJD1C, and HP/HPR. The interaction analysis revealed eight loci with sex- and/or statin-interactions. At the PCSK9 gene locus, there were four independent signals, one with a significant sex-interaction showing stronger effects in men (rs693668). Regarding statin treatment, there were two significant interactions in PCSK9 missense mutations: rs11591147 had stronger effects in statin-free individuals, and rs11583680 had stronger effects in statin-treated individuals. Besides replicating known loci, we detected two novel genome-wide significant associations: one for statin-treated individuals at 6q11.1 (within KHDRBS2) and one for males at 12q24.22 (near KSR2/NOS1), both with significant interactions. In the MR of PCSK9 on LDL-C, we observed significant causal estimates within all subgroups, but significantly stronger causal effects in statin-free subjects compared to statin-treated individuals. CONCLUSIONS: We performed the first double-stratified GWAS of PCSK9 levels and identified multiple biologically plausible loci with genetic interaction effects. Our results indicate that the observed sexual dimorphism of PCSK9 and its statin-related interactions have a genetic basis. Significant differences in the causal relationship between PCSK9 and LDL-C suggest sex-specific dosages of PCSK9 inhibitors.

The protein "proprotein convertase subtilisin/kexin type 9" (PCSK9) regulates the levels of low-density lipoprotein cholesterol (LDL-C) in blood, and thus, contributes to the risk of cardio-vascular diseases. Women tend to have higher PCSK9 plasma levels throughout their life, although the difference is smaller in patients under LDL-C lowering medication (e.g., statins). We investigated the interplay of genetics, statin-treatment and sex, using combined data from six European studies. We detected 11 genetic regions associated with PCSK9 levels, of which one was specific for women (at SLCO1B3, a statin-transporter gene), and three were specific for men (e.g., ALOX5, encoding a protein linked to chronic inflammatory diseases such as atherosclerosis). We also tested if statin use changed the genetic effect and found five genes only associated with PCSK9 levels in untreated participants. Variants in the gene encoding PCSK9 were most strongly associated and had heterogeneous effects in dependence on statin treatment and sex: On one hand, there were genetic variants with stronger effects in men than women. Those variants are also linked to sex-differential gene expression of PCSK9. On the other hand, there were also variants with treatment-depending effects, linked to protein structure and functionality of PCSK9. This indicates that the observed sexual and treatment-related effects on PCSK9 levels have a genetic basis. In addition, we compared the causal effects of PCSK9 on LDL-C levels between men and women and found a different response to statin treatment. This highlights the need for sex-sensitive dosages of lipid-lowering medication.

X-chromosome and kidney function: evidence from a multi-trait genetic analysis of 908,697 individuals reveals sex-specific and sex-differential findings in genes regulated by androgen response elements.

X-chromosomal genetic variants are understudied but can yield valuable insights into sexually dimorphic human traits and diseases. We performed a sex-stratified cross-ancestry X-chromosome-wide association meta-analysis of seven kidney-related traits (n = 908,697), identifying 23 loci genome-wide significantly associated with two of the traits: 7 for uric acid and 16 for estimated glomerular filtration rate (eGFR), including four novel eGFR loci containing the functionally plausible prioritized genes ACSL4, CLDN2, TSPAN6 and the female-specific DRP2. Further, we identified five novel sex-interactions, comprising male-specific effects at FAM9B and AR/EDA2R, and three sex-differential findings with larger genetic effect sizes in males at DCAF12L1 and MST4 and larger effect sizes in females at HPRT1. All prioritized genes in loci showing significant sex-interactions were located next to androgen response elements (ARE). Five ARE genes showed sex-differential expressions. This study contributes new insights into sex-dimorphisms of kidney traits along with new prioritized gene targets for further molecular research.

Genetically regulated gene expression and proteins revealed discordant effects.

BACKGROUND: Although gene-expression (GE) and protein levels are typically strongly genetically regulated, their correlation is known to be low. Here we investigate this phenomenon by focusing on the genetic background of this correlation in order to understand the similarities and differences in the genetic regulation of these omics layers. METHODS AND RESULTS: We performed locus-wide association studies of 92 protein levels measured in whole blood for 2,014 samples of European ancestry and found that 66 are genetically regulated. Three female- and one male-specific effects were detected. We estimated the genetically regulated GE for all significant genes in 49 GTEx v8 tissues. A total of 7 proteins showed negative correlations with their respective GE across multiple tissues. Finally, we tested for causal links of GE on protein expression via Mendelian Randomization, and confirmed a negative causal effect of GE on protein level for five of these genes in a total of 63 gene-tissue pairs: BLMH, CASP3, CXCL16, IL6R, and SFTPD. For IL6R, we replicated the negative causal effect on coronary-artery disease (CAD), while its GE was positively linked to CAD. CONCLUSION: While total GE and protein levels are only weakly correlated, we found high correlations between their genetically regulated components across multiple tissues. Of note, strong negative causal effects of tissue-specific GE on five protein levels were detected. Causal network analyses revealed that GE effects on CAD risks was in general mediated by protein levels.

Whole Blood Metabolite Profiles Reflect Changes in Energy Metabolism in Heart Failure.

A variety of atherosclerosis and cardiovascular disease (ASCVD) phenotypes are tightly linked to changes in the cardiac energy metabolism that can lead to a loss of metabolic flexibility and to unfavorable clinical outcomes. We conducted an association analysis of 31 ASCVD phenotypes and 97 whole blood amino acids, acylcarnitines and derived ratios in the LIFE-Adult (n = 9646) and LIFE-Heart (n = 5860) studies, respectively. In addition to hundreds of significant associations, a total of 62 associations of six phenotypes were found in both studies. Positive associations of various amino acids and a range of acylcarnitines with decreasing cardiovascular health indicate disruptions in mitochondrial, as well as peroxisomal fatty acid oxidation. We complemented our metabolite association analyses with whole blood and peripheral blood mononuclear cell (PBMC) gene-expression analyses of fatty acid oxidation and ketone-body metabolism related genes. This revealed several differential expressions for the heart failure biomarker N-terminal prohormone of brain natriuretic peptide (NT-proBNP) in peripheral blood mononuclear cell (PBMC) gene expression. Finally, we constructed and compared three prediction models of significant stenosis in the LIFE-Heart study using (1) traditional risk factors only, (2) the metabolite panel only and (3) a combined model. Area under the receiver operating characteristic curve (AUC) comparison of these three models shows an improved prediction accuracy for the combined metabolite and classical risk factor model (AUC = 0.78, 95%-CI: 0.76-0.80). In conclusion, we improved our understanding of metabolic implications of ASCVD phenotypes by observing associations with metabolite concentrations and gene expression of the mitochondrial and peroxisomal fatty acid oxidation. Additionally, we demonstrated the predictive potential of the metabolite profile to improve classification of patients with significant stenosis.

Impact of medication on blood transcriptome reveals off-target regulations of beta-blockers.

BACKGROUND: For many drugs, mechanisms of action with regard to desired effects and/or unwanted side effects are only incompletely understood. To investigate possible pleiotropic effects and respective molecular mechanisms, we describe here a catalogue of commonly used drugs and their impact on the blood transcriptome. METHODS AND RESULTS: From a population-based cohort in Germany (LIFE-Adult), we collected genome-wide gene-expression data in whole blood using in Illumina HT12v4 micro-arrays (n = 3,378; 19,974 gene expression probes per individual). Expression profiles were correlated with the intake of active substances as assessed by participants' medication. This resulted in a catalogue of fourteen substances that were identified as associated with differential gene expression for a total of 534 genes. As an independent replication cohort, an observational study of patients with suspected or confirmed stable coronary artery disease (CAD) or myocardial infarction (LIFE-Heart, n = 3,008, 19,966 gene expression probes per individual) was employed. Notably, we were able to replicate differential gene expression for three active substances affecting 80 genes in peripheral blood mononuclear cells (carvedilol: 25; prednisolone: 17; timolol: 38). Additionally, using gene ontology enrichment analysis, we demonstrated for timolol a significant enrichment in 23 pathways, 19 of them including either GPER1 or PDE4B. In the case of carvedilol, we showed that, beside genes with well-established association with hypertension (GPER1, PDE4B and TNFAIP3), the drug also affects genes that are only indirectly linked to hypertension due to their effects on artery walls or their role in lipid biosynthesis. CONCLUSIONS: Our developed catalogue of blood gene expressions profiles affected by medication can be used to support both, drug repurposing and the identification of possible off-target effects.

Genome-wide meta-analysis of phytosterols reveals five novel loci and a detrimental effect on coronary atherosclerosis.

Phytosterol serum concentrations are under tight genetic control. The relationship between phytosterols and coronary artery disease (CAD) is controversially discussed. We perform a genome-wide meta-analysis of 32 phytosterol traits reflecting resorption, cholesterol synthesis and esterification in six studies with up to 9758 subjects and detect ten independent genome-wide significant SNPs at seven genomic loci. We confirm previously established associations at ABCG5/8 and ABO and demonstrate an extended locus heterogeneity at ABCG5/8 with different functional mechanisms. New loci comprise HMGCR, NPC1L1, PNLIPRP2, SCARB1 and APOE. Based on these results, we perform Mendelian Randomization analyses (MR) revealing a risk-increasing causal relationship of sitosterol serum concentrations and CAD, which is partly mediated by cholesterol. Here we report that phytosterols are polygenic traits. MR add evidence of both, direct and indirect causal effects of sitosterol on CAD.

Sex-Specific Causal Relations between Steroid Hormones and Obesity-A Mendelian Randomization Study.

Steroid hormones act as important regulators of physiological processes including gene expression. They provide possible mechanistic explanations of observed sex-dimorphisms in obesity and coronary artery disease (CAD). Here, we aim to unravel causal relationships between steroid hormones, obesity, and CAD in a sex-specific manner. In genome-wide meta-analyses of four steroid hormone levels and one hormone ratio, we identified 17 genome-wide significant loci of which 11 were novel. Among loci, seven were female-specific, four male-specific, and one was sex-related (stronger effects in females). As one of the loci was the human leukocyte antigen (HLA) region, we analyzed HLA allele counts and found four HLA subtypes linked to 17-OH-progesterone (17-OHP), including HLA-B*14*02. Using Mendelian randomization approaches with four additional hormones as exposure, we detected causal effects of dehydroepiandrosterone sulfate (DHEA-S) and 17-OHP on body mass index (BMI) and waist-to-hip ratio (WHR). The DHEA-S effect was stronger in males. Additionally, we observed the causal effects of testosterone, estradiol, and their ratio on WHR. By mediation analysis, we found a direct sex-unspecific effect of 17-OHP on CAD while the other four hormone effects on CAD were mediated by BMI or WHR. In conclusion, we identified the sex-specific causal networks of steroid hormones, obesity-related traits, and CAD.

Genome-wide association analysis of pulse wave velocity traits provide new insights into the causal relationship between arterial stiffness and blood pressure.

BACKGROUND: The pathophysiology of arterial stiffness is not completely understood. Pulse wave velocity (PWV) is an established marker for arterial stiffness. We compare genetics of three PWV modes, namely carotid-femoral PWV (cfPWV), brachial-ankle (baPWV) and brachial-femoral (bfPWV), reflecting different vascular segments to analyse association with genetic variants, heritability and genetic correlation with other biological traits. Furthermore we searched for shared genetic architecture concerning PWV, blood pressure (BP) and coronary artery disease (CAD) and examined the causal relationship between PWV and BP. METHODS AND RESULTS: We performed a genome-wide association study (GWAS) for cfPWV, baPWV and bfPWV in LIFE-Adult (N = 3,643-6,734). We analysed the overlap of detected genetic loci with those of BP and CAD and performed genetic correlation analyses. By bidirectional Mendelian Randomization, we assessed the causal relationships between PWV and BP. For cfPWV we identified a new locus with genome-wide significance near SLC4A7 on cytoband 3p24.1 (lead SNP rs939834: p = 2.05x10-8). We replicated a known PWV locus on cytoband 14q32.2 near RP11-61O1.1 (lead SNPs: rs17773233, p = 1.38x10-4; rs1381289, p = 1.91x10-4) For baPWV we estimated a heritability of 28% and significant genetic correlation with hypertension (rg = 0.27, p = 6.65x10-8). We showed a positive causal effect of systolic blood pressure on PWV modes (cfPWV: p = 1.51x10-4; bfPWV: p = 1.45x10-3; baPWV: p = 6.82x10-15). CONCLUSIONS: We identified a new locus for arterial stiffness and successfully replicated an earlier proposed locus. PWV shares common genetic architecture with BP and CAD. BP causally affects PWV. Larger studies are required to further unravel the genetic determinants and effects of PWV.

Genome-wide analysis of carotid plaque burden suggests a role of IL5 in men.

BACKGROUND: Carotid artery plaque is an established marker of subclinical atherosclerosis with pronounced sex-dimorphism. Here, we aimed to identify genetic variants associated with carotid plaque burden (CPB) and to examine potential sex-specific genetic effects on plaque sizes. METHODS AND RESULTS: We defined six operationalizations of CPB considering plaques in common carotid arteries, carotid bulb, and internal carotid arteries. We performed sex-specific genome-wide association analyses for all traits in the LIFE-Adult cohort (n = 727 men and n = 550 women) and tested significantly associated loci for sex-specific effects. In order to identify causal genes, we analyzed candidate gene expression data for correlation with CPB traits and corresponding sex-specific effects. Further, we tested if previously reported SNP associations with CAD and plaque prevalence are also associated with CBP. We found seven loci with suggestive significance for CPB (p<3.33x10-7), explaining together between 6 and 13% of the CPB variance. Sex-specific analysis showed a genome-wide significant hit for men at 5q31.1 (rs201629990, ß = -0.401, p = 5.22x10-9), which was not associated in women (ß = -0.127, p = 0.093) with a significant difference in effect size (p = 0.008). Analyses of gene expression data suggested IL5 as the most plausible candidate, as it reflected the same sex-specific association with CPBs (p = 0.037). Known plaque prevalence or CAD loci showed no enrichment in the association with CPB. CONCLUSIONS: We showed that CPB is a complementary trait in analyzing genetics of subclinical atherosclerosis. We detected a novel locus for plaque size in men only suggesting a role of IL5. Several estrogen response elements in this locus point towards a functional explanation of the observed sex-specific effect.

Genetic Association Study of Eight Steroid Hormones and Implications for Sexual Dimorphism of Coronary Artery Disease.

CONTEXT: Steroid hormones are important regulators of physiological processes in humans and are under genetic control. A link to coronary artery disease (CAD) is supposed. OBJECTIVE: Our main objective was to identify genetic loci influencing steroid hormone levels. As a secondary aim, we searched for causal effects of steroid hormones on CAD. DESIGN: We conducted genome-wide meta-association studies for eight steroid hormones: cortisol, dehydroepiandrosterone sulfate (DHEAS), estradiol, and testosterone in two independent cohorts (LIFE-Adult, LIFE-Heart, maximum n = 7667), and progesterone, 17-hydroxyprogesterone, androstenedione, and aldosterone in LIFE-Heart only (maximum n = 2070). All genome-wide significant loci were tested for sex interactions. Furthermore, we tested whether previously reported CAD single-nucleotide polymorphisms were associated with our steroid hormone panel and investigated causal links between hormone levels and CAD status using Mendelian randomization (MR) approaches. RESULTS: We discovered 15 novel associated loci for 17-hydroxyprogesterone, progesterone, DHEAS, cortisol, androstenedione, and estradiol. Five of these loci relate to genes directly involved in steroid metabolism, that is, CYP21A1, CYP11B1, CYP17A1, STS, and HSD17B12, almost completing the set of steroidogenic enzymes with genetic associations. Sexual dimorphisms were found for seven of the novel loci. Other loci correspond, for example, to the WNT4/ß-catenin pathway. MR revealed that cortisol, androstenedione, 17-hydroxyprogesterone, and DHEA-S had causal effects on CAD. We also observed enrichment of cortisol and testosterone associations among known CAD hits. CONCLUSION: Our study greatly improves insight into genetic regulation of steroid hormones and their dependency on sex. These results could serve as a basis for analyzing sexual dimorphism in other complex diseases.

Genetic Regulation of PCSK9 (Proprotein Convertase Subtilisin/Kexin Type 9) Plasma Levels and Its Impact on Atherosclerotic Vascular Disease Phenotypes.

BACKGROUND: Inhibition of PCSK9 (proprotein convertase subtilisin/kexin type 9) is a novel strategy to treat hypercholesterolemia and reduce cardiovascular events. However, the potential role of circulating plasma PCSK9 concentrations as a diagnostic and predictive biomarker remains uncertain as of now. Here, we aimed to identify genetic variants associated with plasma PCSK9 and investigate possible causal effects on atherosclerotic vascular disease phenotypes. METHODS: We performed the first genome-wide association study of plasma PCSK9 levels in a cohort of suspected and confirmed coronary artery disease (LIFE-Heart; n=3290). RESULTS: Several independent variants at the PCSK9 gene locus were associated with circulating PCSK9 levels at genome-wide significance (lead SNP rs11591147, PCSK9-R46L; P=1.94×10-17). We discovered 4 independent PCSK9 SNPs explaining 4.4% of the variance of plasma PCSK9. In addition, we identified a genome-wide significant locus at chromosome 7p22.1 (rs6957201; P=7.01×10-9) and 7 suggestive hits (P<1×10-6). Using MR (Mendelian Randomization), we detected significant causal effects of circulating PCSK9 on coronary artery disease status and severity, carotid plaques, and intima-media thickness. CONCLUSIONS: Variants at the PCSK9 gene locus seem to be the major genetic determinants of plasma PCSK9 levels with 4 independent variants at the PCSK9 gene locus expressing allelic heterogeneity. The detected MR estimates support the hypothesis of a causal effect of PCSK9 on coronary artery disease and other vascular phenotypes. Other observed genetic associations for PCSK9 require validation in independent cohorts. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique Identifier: NCT00497887.

Genome-wide meta-analysis identifies novel loci of plaque burden in carotid artery.

BACKGROUND AND AIMS: Carotid artery plaque is an established marker of subclinical atherosclerosis and common patho-mechanisms with coronary artery disease (CAD) are hypothesized. We aimed to identify genetic variants associated with carotid plaque and to examine the potential shared genetic basis with CAD. METHODS: After investigating the reliability of plaque detection, we performed a genome-wide meta-association study in two independent cohorts (LIFE-Adult, n = 4037 and LIFE-Heart, n = 3152) for carotid plaque score (PS), defined as the sum of the plaque load of common carotid artery and carotid bulb. Further, we analyzed whether previously reported CAD and stroke loci were also associated with PS. RESULTS: We identified two loci with genome-wide significance for PS. One locus is the known CAD-locus at chromosome 9p21 (lead SNP rs9644862, p = 8.73 × 10-12). We also describe a novel locus on chromosome 10q24 within the SFXN2 gene as the most probable candidate (lead SNP rs2902548, p = 1.97 × 10-8). In addition, 17 out of 58 known CAD loci and six of 17 known stroke loci were associated with PS at a nominal level of significance. CONCLUSIONS: We showed that PS is a reliable trait to analyze genetics of atherosclerosis. Two new loci of genome-wide significant association with PS were found. The observed non-random overlap of CAD and PS associations strengthens the hypothesis of a shared genetic basis for these atherosclerotic manifestations.