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High lipoprotein(a) [Lp(a)] concentrations are one of the most important genetically determined risk factors for cardiovascular disease. Lp(a) concentrations are an enigmatic trait largely controlled by one single gene (LPA) that contains a complex interplay of several genetic elements with many surprising effects discussed in this review. A hypervariable coding copy number variation (the kringle IV type-2 repeat, KIV-2) generates >40 apolipoprotein(a) protein isoforms and determines the median Lp(a) concentrations. Carriers of small isoforms with up to 22 kringle IV domains have median Lp(a) concentrations up to 5 times higher than those with large isoforms (>22 kringle IV domains). The effect of the apo(a) isoforms are, however, modified by many functional single nucleotide polymorphisms (SNPs) distributed over the complete range of allele frequencies (<0.1% to >20%) with very pronounced effects on Lp(a) concentrations. A complex interaction is present between the apo(a) isoforms and LPA SNPs, with isoforms partially masking the effect of functional SNPs and, vice versa, SNPs lowering the Lp(a) concentrations of affected isoforms. This picture is further complicated by SNP-SNP interactions, a poorly understood role of other polymorphisms such as short tandem repeats and linkage structures that are poorly captured by common R2 values. A further layer of complexity derives from recent findings that several functional SNPs are located in the KIV-2 repeat and are thus not accessible to conventional sequencing and genotyping technologies. A critical impact of the ancestry on correlation structures and baseline Lp(a) values becomes increasingly evident. This review provides a comprehensive overview on the complex genetic architecture of the Lp(a) concentrations in plasma, a field that has made tremendous progress with the introduction of new technologies. Understanding the genetics of Lp(a) might be a key to many mysteries of Lp(a) and booster new ideas on the metabolism of Lp(a) and possible interventional targets. [Display omitted] • Lipoprotein(a) is the lipoprotein with the strongest genetic regulation. • Many functional SNPs dissociate apo(a) isoform size and Lp(a) concentrations. • Multiple functional SNPs have been hidden in the KIV type-2 region until recently. • It is common that functional LPA SNPs occur only in defined isoform size ranges. • Multiple levels of linkage disequilibrium between polymorphisms govern the trait. [ABSTRACT FROM AUTHOR]

Carotid intima media thickness (cIMT) is a marker for subclinical atherosclerosis. The most recent genome-wide association meta-analysis (GWAMA) from the CHARGE consortium identified four genomic regions showing either significant ( ZHX2, APOC1, PINX1 ) or suggestive evidence ( SLC17A4 ) for an association. Here we assess these four cIMT loci in a pooled analysis of four independent studies including 5446 individuals by providing updated unbiased effect estimates of the cIMT association signals. The pooled estimates of our four independent samples pointed in the same direction and were similar to those of the GWAMA. When updating the independent second stage replication results from the earlier CHARGE GWAMA by our estimates, effect size estimates were closer to those of the original CHARGE discovery. A fine-mapping approach within a ±50 kb region around each lead SNP from CHARGE revealed 27 variants with larger estimated effect sizes than the lead SNPs but only three of them showed a r 2 > 0.40 with these respective lead SNPs from CHARGE. Some variants are located within potential functional loci. [ABSTRACT FROM AUTHOR]

Abstract: Objective: GATA4iKO mice exhibit impeded triglyceride absorption from intestine and decreased plasma triglyceride levels. Data in humans are lacking. We hypothesized that triglyceride levels might also be regulated by polymorphisms in the GATA4 gene in humans. We used publicly available data from different sources to evaluate this hypothesis. Our approach is a more often applicable advance to uncover associations and their functional implications which would have been otherwise missed by standard genome-wide association studies (GWAS). Methods: We used the publicly available GWAS results from 137 SNPs in the GATA4 region for triglyceride levels. We embedded these results into the comprehensive functional genomics data provided in the UCSC Genome Browser including among others information on regulatory elements and interspecies conservation. A concise graphical presentation is proposed together with an R function for automatic data preparation. This process is presented in an educational manner using a screencast to become most useful for other researchers. Results: We observed several polymorphisms in and around the GATA4 gene which have a significant influence on plasma triglyceride levels with the lowest p-value at SNP rs1466785 (Bonferroni-corrected p-value=1.76e−5). The bioinformatic evaluation of this locus in publicly available functional genomics data provided converging evidence for the presence of a transcriptional regulator downstream of GATA4. Conclusion: The combination of different sources of data has revealed an association of GATA4 with triglyceride levels in humans. Our evaluation exemplifies how an integrative analysis including both statistical and biological perspectives can shed new light on available association data and reveals novel candidate genes, which are otherwise hidden in the noisy region below genome-wide significance. [Copyright &y& Elsevier]

Abstract: Genome-wide association studies (GWASs) led to impressive advances in the elucidation of genetic factors underlying complex phenotypes and diseases. However, the ability of GWAS to identify new susceptibility loci in a hypothesis-free approach requires tools to quickly retrieve comprehensive information about a genomic region and analyze the potential effects of coding and non-coding SNPs in a candidate gene region. Furthermore, once a candidate region is chosen for resequencing and fine-mapping studies, the identification of several rare mutations is likely and requires strong bioinformatic support to properly evaluate and prioritize the found mutations for further analysis. Due to the variety of regulatory layers that can be affected by a mutation, a comprehensive in-silico evaluation of candidate SNPs can be a demanding and very time-consuming task. Although many bioinformatic tools that significantly simplify this task were made available in the last years, their utility is often still unknown to researches not intensively involved in bioinformatics. We present a comprehensive guide of 64 tools and databases to bioinformatically analyze gene regions of interest to predict SNP effects. In addition, we discuss tools to perform data mining of large genetic regions, predict the presence of regulatory elements, make in-silico evaluations of SNPs effects and address issues ranging from interactome analysis to graphically annotated proteins sequences. Finally, we exemplify the use of these tools by applying them to hits of a recently performed GWAS. Taken together a combination of the discussed tools are summarized and constantly updated in the web-based “GenEpi Toolbox” (http://genepi_toolbox.i-med.ac.at) and can help to get a glimpse at the potential functional relevance of both large genetic regions and single nucleotide mutations which might help to prioritize the next steps. [Copyright &y& Elsevier]

HDL-mediated cholesterol efflux capacity (CEC) may protect from cardiovascular disease. Thus, we aimed to identify its genetic and non-genetic determinants. We measured CEC to 2% apolipoprotein B-depleted serum using BODIPY-cholesterol and cAMP-stimulated J774A.1 macrophages using serum samples from 4,981 participants in the German Chronic Kidney Disease (GCKD) study. Variance of CEC explained by clinical and biochemical parameters in a multivariable linear regression model was calculated by proportional marginal variance decomposition. A genome-wide association study with 7,746,917 variants was performed based on an additive genetic model. The main model was adjusted for age, sex and principal components 1-10. Further models were selected for sensitivity analysis and to reduce residual variance by known CEC pathways. Variables that explained 1% and more of the variance of CEC were concentrations of triglycerides (12.9%), HDL-cholesterol (11.8%), LDL-cholesterol (3.0%), apolipoprotein A-IV (2.8%), PCSK9 (1.0%), and eGFR (1.0%). The KLKB1 (chr4) and APOE/C1 (chr19) loci were genome-wide significantly (p < 5x10−8) associated with CEC in our main model (p = 8.8x10−10 and p = 3.3x10−10, respectively). KLKB1 remained significantly associated after additional adjustment for either kidney parameters, HDL-cholesterol, triglycerides or apolipoprotein A-IV concentrations, while the APOE/C1 locus was not significantly associated anymore after adjustment for triglycerides. Adjustment for triglycerides also revealed an association with the CLSTN2 locus (chr3; p = 6.0x10−9). We identified HDL-cholesterol and triglycerides as the main determinants of CEC. Furthermore, we newly found a significant association of CEC with the KLKB1 and the CLSTN2 locus and confirmed the association with the APOE/C1 locus, likely mediated by triglycerides. [Display omitted] • HDL-C and triglycerides are the main biochemical determinants of cholesterol efflux capacity each explaining >11% of variance. • In a GWAS, 2 novel genetic loci (KLKB1 & CLSTN2) and the known APOE/C1 locus are associated with cholesterol efflux capacity. • The KLKB1 locus is significant irrespective of adjustment for kidney function, HDL-C, triglycerides and apolipoprotein A-IV. • The association with the CLSTN2 locus is suggestive and reaches genome-wide significance with adjustment for triglycerides. [ABSTRACT FROM AUTHOR]

High lipoprotein(a) [Lp(a)] concentrations are associated with increased coronary artery disease (CAD) risk. Lp(a) is regulated mainly genetically by the LPA gene but involved genetic variants have not been fully elucidated. Improved understanding of the entanglements of genetic Lp(a) regulation may enhance genetic prediction of Lp(a) and CAD risk. We investigated an interaction between the well-known LPA missense SNP rs41272110 (known as Thr3888Pro) and the frequent LPA splicing mutation KIV-2 4925G>A. Effects on Lp(a) concentrations were investigated by multiple quantile regression in the German Chronic Kidney Disease (GCKD) study, KORA-F3 and KORA-F4 (n total = 10,405) as well as in the UK Biobank (UKB) 200k exome dataset (n = 173,878). The impact of the interaction on CAD risk was assessed by survival analysis in UKB. We observed a significant SNP-SNP interaction in all studies (p = 1.26e-05 to 3.03e-04). In quantile regression analysis, rs41272110 as a predictor shows no impact on Lp(a) (β = −0.06 [-0.79; 0.68], p = 0.879), but in a joint model including both SNPs as predictors, rs41272110 is associated with markedly higher Lp(a) (β = +9.40 mg/dL [6.45; 12.34], p = 4.07e-10). Similarly, rs41272110 shows no effect on CAD in UKB (HR = 1.01 [0.97; 1.04], p = 0.731), while rs41272110 carriers not carrying 4925G>A show an increased CAD risk (HR = 1.10 [1.04; 1.16], p = 6.9e-04). This group corresponds to 4% of the population. Adjustment for apolipoprotein(a) isoforms further modified the effect estimates markedly. This work emphasizes the complexity of the genetic regulation of Lp(a) and the importance to account for genetic subgroups in Lp(a) association studies and when interpreting genetic cardiovascular risk profiles. [Display omitted] • Effect of rs41272110 on Lp(a) and coronary artery disease (CAD) depends on the genotype of the 4925G>A. • Adjusting for 4925G>A reveals a missed Lp(a)-increasing effect of rs41272110. • Lp(a)-increasing effect increases CAD risk and affects 4% of the population. • Not accounted interactions of LPA variants can hide effects on CAD risk. [ABSTRACT FROM AUTHOR]

Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key regulator of lipid homeostasis. A few earlier genome-wide association studies (GWAS) investigated genetic variants associated with circulating PCSK9 concentrations. However, uncertainty remains about some of the genetic loci discovered beyond the PCSK9 locus. By conducting the largest PCSK9 meta-analysis of GWAS (meta -GWAS) so far, we aimed to identify novel loci and validate the previously reported loci that regulate PCSK9 concentrations. We performed GWAS for PCSK9 concentrations in two large cohorts (GCKD (n = 4,963) and KORA F3 (n = 2,895)). These were meta-analyzed with previously published data encompassing together 20,579 individuals. We further conducted a second meta-analysis in statin-naïve individuals (n = 15,390). A genetic risk score (GRS) was constructed on PCSK9-increasing SNPs and assessed its impact on the risk for coronary artery disease (CAD) in 394,943 statin-naïve participants (17,077 with events) of the UK Biobank by performing CAD-free survival analysis. Nine loci were genome-wide significantly associated with PCSK9 concentrations. These included the previously described PCSK9 , APOB, KCNA1/KCNA5, and TM6SF2/SUGP1 loci. All imputed SNPs in the PCSK9 locus account for ∼15% of variance of PCSK9 concentrations. We further identified FADS2 as a novel locus that was also found in statin-naïve participants. All imputed SNPs within the FADS2 locus explain ∼1.2% of variance of PCSK9 concentrations. Additionally, four further loci (a region on chromosome 5, SDK1, SPATA16 and HPR) were genome-wide significant in either the main model or the statin-naïve subset. The linear increase in a PCSK9 genetic risk score was associated with 1.41-fold (95%CI 1.16–1.72, p < 0.001) higher risk for incident CAD. We identified five novel loci (FADS2, SPATA16, SDK1, HPR and a region on chromosome 5) for PCSK9 concentrations that would require further research. Additionally, we confirm the genome-wide significant loci that were previously detected. [Display omitted] • Currently the largest meta-analysis of GWAS studies on PCSK9 concentrations (n=20,579) with subgroup analysis in the statin-naïve individuals (n=15,390). • Five novel loci for PCSK9 concentrations were identified, four previously detected loci were confirmed. • PCSK9 and FADS2 loci explain ∼15% and ∼1.2% of the variance of PCSK9 concentrations, respectively. • Linear increase in PCSK9 genetic risk score in statin-naïve subset was significantly associated with a 1.41-fold risk increase for incident CAD. [ABSTRACT FROM AUTHOR]

Abstract: Background: Candidate gene association studies for peripheral artery disease (PAD), including subclinical disease assessed with the ankle-brachial index (ABI), have been limited by the modest number of genes examined. We conducted a two stage meta-analysis of ∼50,000 SNPs across ∼2100 candidate genes to identify genetic variants for ABI. Methods and results: We studied subjects of European ancestry from 8 studies (n =21,547, 55% women, mean age 44–73 years) and African American ancestry from 5 studies (n =7267, 60% women, mean age 41–73 years) involved in the candidate gene association resource (CARe) consortium. In each ethnic group, additive genetic models were used (with each additional copy of the minor allele corresponding to the given beta) to test each SNP for association with continuous ABI (excluding ABI>1.40) and PAD (defined as ABI<0.90) using linear or logistic regression with adjustment for known PAD risk factors and population stratification. We then conducted a fixed-effects inverse-variance weighted meta-analyses considering a p <2×10−6 to denote statistical significance. Results: In the European ancestry discovery meta-analyses, rs2171209 in SYTL3 (β =−0.007, p =6.02×10−7) and rs290481 in TCF7L2 (β =−0.008, p =7.01×10−7) were significantly associated with ABI. None of the SNP associations for PAD were significant, though a SNP in CYP2B6 (p =4.99×10−5) was among the strongest associations. These 3 genes are linked to key PAD risk factors (lipoprotein(a), type 2 diabetes, and smoking behavior, respectively). We sought replication in 6 population-based and 3 clinical samples (n =15,440) for rs290481 and rs2171209. However, in the replication stage (rs2171209, p =0.75; rs290481, p =0.19) and in the combined discovery and replication analysis the SNP–ABI associations were no longer significant (rs2171209, p =1.14×10−3; rs290481, p =8.88×10−5). In African Americans, none of the SNP associations for ABI or PAD achieved an experiment-wide level of significance. Conclusions: Genetic determinants of ABI and PAD remain elusive. Follow-up of these preliminary findings may uncover important biology given the known gene-risk factor associations. New and more powerful approaches to PAD gene discovery are warranted. [Copyright &y& Elsevier]

Abstract: Background: High serum uric acid levels are associated with gout, atherosclerosis and cardiovascular disease. Three genes (SLC2A9, ABCG2, and SLC17A3) were reported to be involved in the regulation of uric acid levels. Research: Design and Methods: SNPs rs2231142 (ABCG2) and rs1165205 (SLC17A3) were genotyped in three cohorts (n =4492) and combined with previously genotyped SNPs within SLC2A9 (rs6855911, rs7442295, rs6449213, rs12510549). Results: Each copy of the minor allele decreased uric acid levels by 0.30–0.38mg/dL for SLC2A9 (p values: 10−20–10−36) and increased levels by 0.34mg/dL for ABCG2 (p =1.1×10−16). SLC17A3 influenced uric acid levels only modestly. Together the SNPs showed graded associations with uric acid levels of 0.111mg/dL per risk allele (p =3.8×10−42). In addition, we observed a sex-specific interaction of age with the association of SLC2A9 SNPs with uric acid levels, where increasing age strengthened the association of SNPs in women and decreased the association in men. Conclusions: Genetic variants within SLC2A9, ABCG2 and SLC17A3 show highly significant associations with uric acid levels, and for SNPs within SLC2A9 this association is strongly modified by age and sex. [Copyright &y& Elsevier]

Abstract: Objective: Plasma adiponectin is strongly associated with various components of metabolic syndrome, type 2 diabetes and cardiovascular outcomes. Concentrations are highly heritable and differ between men and women. We therefore aimed to investigate the genetics of plasma adiponectin in men and women. Methods: We combined genome-wide association scans of three population-based studies including 4659 persons. For the replication stage in 13795 subjects, we selected the 20 top signals of the combined analysis, as well as the 10 top signals with p-values less than 1.0×10−4 for each the men- and the women-specific analyses. We further selected 73 SNPs that were consistently associated with metabolic syndrome parameters in previous genome-wide association studies to check for their association with plasma adiponectin. Results: The ADIPOQ locus showed genome-wide significant p-values in the combined (p =4.3×10−24) as well as in both women- and men-specific analyses (p =8.7×10−17 and p =2.5×10−11, respectively). None of the other 39 top signal SNPs showed evidence for association in the replication analysis. None of 73 SNPs from metabolic syndrome loci exhibited association with plasma adiponectin (p >0.01). Conclusions: We demonstrated the ADIPOQ gene as the only major gene for plasma adiponectin, which explains 6.7% of the phenotypic variance. We further found that neither this gene nor any of the metabolic syndrome loci explained the sex differences observed for plasma adiponectin. Larger studies are needed to identify more moderate genetic determinants of plasma adiponectin. [Copyright &y& Elsevier]

Abstract: The 12/15-lipoxygenase plays a janus-role in inflammation with pro-inflammatory and anti-inflammatory effects in cell systems and even opposite effects on atherosclerosis in two different animal species. Screening of the human 15-lipoxygenase (ALOX15) gene detected a polymorphic C to T substitution at position c.−292, which led to three times higher ALOX15 activity in macrophages and showed a trend to be atheroprotective in a small case–control study for coronary artery disease (CAD). A second polymorphism at position c.1693C>T leading to an T560M exchange and an inactive enzyme was recently associated with increased CAD. We now investigated whether these polymorphisms or a certain haplotype of ALOX15 are associated with myocardial infarction (MI) in a case–control subset from the population-based MONIKA/KORA cohort S3. Six polymorphisms in ALOX15 were analyzed in 2629 participants to cover all major haplotypes with a frequency higher than 1% in the Caucasian population. None of the polymorphism was associated with MI but a rare ALOX15 haplotype showed a significant protective effect on the risk for MI (p =0.03). However, none of the polymorphisms or haplotypes was associated with CRP levels. These data suggest that ALOX15 may play a less prominent role during later stages of atherosclerosis involving atherothrombotic mechanisms than eventually during early plaque development. [Copyright &y& Elsevier]